Human Behavioral Ecology (Cambridge Studies in Biological and Evolutionary Anthropology, Series Number 92) [1 ed.] 1108421830, 9781108421836

Citation preview

Human Behavioral Ecology Human behavioral ecology (HBE) applies the principles of evolutionary theory and optimization to the study of human behavioral and cultural diversity. Characterized by an interdisciplinary approach, HBE examines the ways that individuals navigate social and ecological trade-offs to respond adaptively to challenges of acquiring and distributing resources, pursuing mating opportunities, supporting children, and both cooperating and competing with group members across the wide variety of ecologies inhabited by humans in the present and past. Summarizing decades of research, this book is a comprehensive introduction to the theoretical orientation and empirical findings of HBE. It consolidates the insights of evolution and human behavior into a single volume that surveys both the current state and future of the field. Embodying diverse expertise, the book’s authors provide a thought-provoking, broad overview of HBE and its unique contributions to the evolutionary social sciences. Throughout, the authors explain the latest developments in theory and highlight critical debates in the literature while also engaging readers with ethnographic insights and field-based studies that remain at the core of human behavioral ecology. Jeremy Koster is an external faculty member at the Max Planck Institute for Evolutionary Anthropology. He conducts research among indigenous Nicaraguans and codirects a collaborative project that examines the social determinants of wealth inequality. His interdisciplinary work on the behavior and demography of domestic dogs helps to advance understandings of the mechanisms for artificial selection. Brooke A. Scelza is Professor of Anthropology at the University of California, Los Angeles, and codirector of the Kunene Rural Health and Demography Project in Namibia, where she has been working with Himba pastoralists since 2010 to study family dynamics and reproductive decision-making. She is a former President of the Evolutionary Anthropology Society. Mary K. Shenk is Associate Professor of Anthropology, Demography and Asian Studies at The Pennsylvania State University. Her research focuses on marriage, parental investment, and fertility in South Asia, where she has conducted fieldwork since 2001. She is a fellow of the American Association for the Advancement of Science and former President of the Evolutionary Anthropology Society.

Published online by Cambridge University Press

Published online by Cambridge University Press

Cambridge Studies in Biological and Evolutionary Anthropology Consulting editors C. G. Nicholas Mascie-Taylor, University of Cambridge Robert A. Foley, University of Cambridge Series editors Agustín Fuentes, Princeton University Nina G. Jablonski, Pennsylvania State University Clark Spencer Larsen, The Ohio State University Michael P. Muehlenbein, Baylor University Dennis H. O’Rourke, The University of Kansas Karen B. Strier, University of Wisconsin David P. Watts, Yale University Also available in the series 53. Technique and Application in Dental Anthropology Joel D. Irish and Greg C. Nelson (eds.) 978 0 521 87061 0 54. Western Diseases: An Evolutionary Perspective Tessa M. Pollard 978 0 521 61737 6 55. Spider Monkeys: The Biology, Behavior and Ecology of the Genus Ateles Christina J. Campbell (ed.) 978 0 521 86750 4 56. Between Biology and Culture Holger Schutkowski (ed.) 978 0 521 85936 3 57. Primate Parasite Ecology: The Dynamics and Study of Host-Parasite Relationships Michael A. Huffman and Colin A. Chapman (eds.) 978 0 521 87246 1 58. The Evolutionary Biology of Human Body Fatness: Thrift and Control Jonathan C. K. Wells 978 0 521 88420 4 59. Reproduction and Adaptation: Topics in Human Reproductive Ecology C. G. Nicholas MascieTaylor and Lyliane Rosetta (eds.) 978 0 521 50963 3 60. Monkeys on the Edge: Ecology and Management of Long-Tailed Macaques and Their Interface with Humans Michael D. Gumert, Agustín Fuentes and Lisa Jones-Engel (eds.) 978 0 521 76433 9 61. The Monkeys of Stormy Mountain: Sixty Years of Primatological Research on the Japanese Macaques of Arashiyama Jean-Baptiste Leca, Michael A. Huffman and Paul L. Vasey (eds.) 978 0 521 76185 7 62. African Genesis: Perspectives on Hominin Evolution Sally C. Reynolds and Andrew Gallagher (eds.) 978 1 107 01995 9 63. Consanguinity in Context Alan H. Bittles 978 0 521 78186 2 64. Evolving Human Nutrition: Implications for Public Health Stanley Ulijaszek, Neil Mann and Sarah Elton (eds.) 978 0 521 86916 4 65. Evolutionary Biology and Conservation of Titis, Sakis and Uacaris Liza M. Veiga, Adrian A. Barnett, Stephen F. Ferrari and Marilyn A. Norconk (eds.) 978 0 521 88158 6 66. Anthropological Perspectives on Tooth Morphology: Genetics, Evolution, Variation G. Richard Scott and Joel D. Irish (eds.) 978 1 107 01145 8 67. Bioarchaeological and Forensic Perspectives on Violence: How Violent Death is Interpreted from Skeletal Remains Debra L. Martin and Cheryl P. Anderson (eds.) 978 1 107 04544 6 68. The Foragers of Point Hope: The Biology and Archaeology of Humans on the Edge of the Alaskan Arctic Charles E. Hilton, Benjamin M. Auerbach and Libby W. Cowgill (eds.) 978 1 107 02250 8

Published online by Cambridge University Press

69. Bioarchaeology: Interpreting Behavior from the Human Skeleton, 2nd Ed. Clark Spencer Larsen 978 0 521 83869 6 & 978 0 521 54748 2 70. Fossil Primates Susan Cachel 978 1 107 00530 3 71. Skeletal Biology of the Ancient Rapanui (Easter Islanders) Vincent H. Stefan and George W. Gill (eds.) 978 1 107 02366 6 72. Demography and Evolutionary Ecology of Hadza Hunter-Gatherers Nicholas Blurton Jones 978 1 107 06982 4 73. The Dwarf and Mouse Lemurs of Madagascar: Biology, Behavior and Conservation Biogeography of the Cheirogaleidae Shawn M. Lehman, Ute Radespiel and Elke Zimmermann (eds.) 978 1 107 07559 7 74. The Missing Lemur Link: An Ancestral Step in Human Evolution Ivan Norscia and Elisabetta Palagi 978 1 107 01608 8 75. Studies in Forensic Biohistory: Anthropological Perspectives Christopher M. Stojanowski and William N. Duncan (eds.) 978 1 107 07354 8 76. Ethnoprimatology: A Practical Guide to Research at the Human-Nonhuman Primate Interface Kerry M. Dore, Erin P. Riley and Agustín Fuentes (eds.) 978 1 107 10996 4 77. Building Bones: Bone Formation and Development in Anthropology Christopher J. Percival and Joan T. Richtsmeier (eds.) 978 1 107 12278 9 78. Models of Obesity: From Ecology to Complexity in Science and Policy Stanley J. Ulijaszek 978 1 107 11751 8 79. The Anthropology of Modern Human Teeth: Dental Morphology and Its Variation in Recent and Fossil Homo Sapiens, 2nd Ed. G. Richard Scott, Christy G. TurnerII, Grant C. Townsend and María Martinón-Torres 978 1 107 17441 2 80. The Backbone of Europe: Health, Diet, Work, and Violence over Two Millennia Richard H. Steckel, Clark Spencer Larsen, Charlotte A. Roberts and Joerg Baten (eds.) 978 1 108 42195 9 81. Hunter-Gatherer Adaptation and Resilience: A Bioarchaeological Perspective Daniel H. Temple and Christopher M. Stojanowski (eds.) 978 1 107 18735 1 82. Primate Research and Conservation in the Anthropocene Alison M. Behie, Julie A. Teichroeb and N. Malone (eds.) 978 1 107 15748 4 83. Evaluating Evidence in Biological Anthropology: The Strange and the Familiar Cathy Willermet and Sang-Hee Lee (eds.) 978 1 108 47684 3 84. The Genetics of African Populations in Health and Disease Muntaser E. Ibrahim and Charles N. Rotimi (eds.) 978 1 107 07202 2 85. The Evolutionary Biology of the Human Pelvis: An Integrative Approach Cara M. Wall-Scheffler, Helen K. Kurki and Benjamin M. Auerbach 978 1 107 19957 6 86. Evolution, Ecology and Conservation of Lorises and Pottos K. A. I. Nekaris and Anne M. Burrows (eds.) 978 1 108 42902 3 87. The Biodemography of Subsistence Farming: Population, Food and Family James W. Wood 978 1 107 03341 2 88. Patterns of Human Growth, 3rd Ed. Barry Bogin 978 1 108 43448 5 89. The Colobines: Natural History, Behaviour and Ecological Diversity Ikki Matsuda, Cyril C. Grueter and Julie A. Teichroeb (eds.) 978 1 108 42138 6 90. World Archaeoprimatology: Interconnections of Humans and Nonhuman Primates in the Past Bernardo Urbani, Dionisios Youlatos and Andrzej T. Antczak (eds.) 978 1 108 48733 7 91. The Bioarchaeology of Cardiovascular Disease Michaela Binder, Charlotte A. Roberts and Daniel Antoine (eds.) 978 1 108 480345 Published online by Cambridge University Press

Human Behavioral Ecology Edited by

JEREMY KOSTER Max Planck Institute for Evolutionary Anthropology

BROOKE A. SCELZA University of California, Los Angeles

MARY K. SHENK The Pennsylvania State University

Published online by Cambridge University Press

Shaftesbury Road, Cambridge CB2 8EA, United Kingdom One Liberty Plaza, 20th Floor, New York, NY 10006, USA 477 Williamstown Road, Port Melbourne, VIC 3207, Australia 314–321, 3rd Floor, Plot 3, Splendor Forum, Jasola District Centre, New Delhi – 110025, India 103 Penang Road, #05-06/07, Visioncrest Commercial, Singapore 238467 Cambridge University Press is part of Cambridge University Press & Assessment, a department of the University of Cambridge. We share the University’s mission to contribute to society through the pursuit of education, learning and research at the highest international levels of excellence. www.cambridge.org Information on this title: www.cambridge.org/9781108421836 DOI: 10.1017/9781108377911 © Cambridge University Press & Assessment 2024 This publication is in copyright. Subject to statutory exception and to the provisions of relevant collective licensing agreements, no reproduction of any part may take place without the written permission of Cambridge University Press & Assessment. First published 2024 A catalogue record for this publication is available from the British Library Library of Congress Cataloging-in-Publication Data Names: Koster, Jeremy, 1976- author. | Scelza, Brooke, 1976- author. | Shenk, Mary K., author. Title: Human behavioral ecology / Jeremy Koster, Max Planck Institute for Evolutionary Anthropology, Brooke Scelza, University of California, Los Angeles, Mary K. Shenk, Pennsylvania State University. Description: New York, NY : Cambridge University Press, 2023. | Series: Cambridge studies in biological and evolutionary anthropology | Includes bibliographical references and index. Identifiers: LCCN 2023032021 (print) | LCCN 2023032022 (ebook) | ISBN 9781108421836 (hardback) | ISBN 9781108434348 (paperback) | ISBN 9781108377911 (epub) Subjects: LCSH: Human ecology. | Human behavior. | Human evolution. Classification: LCC GF41 .K68 2023 (print) | LCC GF41 (ebook) | DDC 304.2–dc23/eng/20231016 LC record available at https://lccn.loc.gov/2023032021 LC ebook record available at https://lccn.loc.gov/2023032022 ISBN 978-1-108-42183-6 Hardback ISBN 978-1-108-43434-8 Paperback Cambridge University Press & Assessment has no responsibility for the persistence or accuracy of URLs for external or third-party internet websites referred to in this publication and does not guarantee that any content on such websites is, or will remain, accurate or appropriate.

Published online by Cambridge University Press

Contents

List of Contributors Foreword Eric Alden Smith and Bruce P. Winterhalder

1

Human Behavioral Ecology

page ix xi

1

Brooke A. Scelza, Jeremy Koster, and Mary K. Shenk

2

Life History

20

Michael D. Gurven

3

Foraging Strategies

48

Jeremy Koster and Douglas W. Bird

4

Modes of Production

76

Bram Tucker

5

Cooperation

104

Michael Alvard and David Nolin

6

Division of Labor

130

Brian F. Codding and Rebecca Bliege Bird

7

Status

153

Christopher von Rueden

8

Political Organization

180

Paul L. Hooper and Adrian V. Jaeggi

9

Mating

203

Brooke A. Scelza

10

Marriage

230

Mary K. Shenk

11

Parental Care

256

David W. Lawson

12

Allocare Karen L. Kramer

Published online by Cambridge University Press

283

viii

Contents

13

Demography

307

Rebecca Sear, Siobhán M. Mattison, and Mary K. Shenk

14

Human Biology

333

Aaron D. Blackwell and Benjamin C. Trumble

15

Cultural Evolution

356

Karthik Panchanathan

16

Evolutionary Psychology

380

H. Clark Barrett

17

The End of Human Behavioral Ecology

402

Richard McElreath and Jeremy Koster Bibliography Index

Published online by Cambridge University Press

420 516

Contributors

Michael Alvard Professor of Anthropology, Texas A&M University H. Clark Barrett Professor of Anthropology, University of California, Los Angeles Douglas W. Bird Professor of Anthropology, The Pennsylvania State University Aaron D. Blackwell Associate Professor of Anthropology, Washington State University Rebecca Bliege Bird Professor of Anthropology, The Pennsylvania State University Brian F. Codding Professor of Anthropology, University of Utah Michael D. Gurven Professor of Anthropology, University of California, Santa Barbara Paul L. Hooper Systems Science Ltd. Adrian V. Jaeggi Assistant Professor, Institute of Evolutionary Medicine, University of Zurich Jeremy Koster Affiliate, Department of Human Behavior, Ecology, and Culture, Max Planck Institute for Evolutionary Anthropology Karen L. Kramer Professor of Anthropology, University of Utah David W. Lawson Associate Professor of Anthropology, University of California, Santa Barbara Siobhán M. Mattison Associate Professor of Evolutionary Anthropology, University of New Mexico Richard McElreath Director, Department of Human Behavior, Ecology, and Culture, Max Planck Institute for Evolutionary Anthropology

Published online by Cambridge University Press

x

Contributors

David Nolin Senior Research Fellow, University of Massachusetts, Amherst Karthik Panchanathan Associate Professor of Anthropology, University of Missouri Brooke A. Scelza Professor of Anthropology, University of California, Los Angeles Rebecca Sear Professor of Population Health, London School of Hygiene and Tropical Medicine Mary K. Shenk Associate Professor of Anthropology and Demography, The Pennsylvania State University Benjamin C. Trumble Associate Professor, School of Human Evolution and Social Change, Arizona State University Bram Tucker Associate Professor of Anthropology, University of Georgia Christopher von Rueden Associate Professor, Jepson School of Leadership Studies, University of Richmond

Published online by Cambridge University Press

Foreword: Reflections on Five Decades of Human Behavioral Ecology The volume before you authoritatively summarizes the state of the art in contemporary human behavioral ecology (HBE). The earliest HBE publications go back nearly five decades. Compared to other frameworks in anthropology, HBE has a record of exceptional durability. Having been present at the creation, so to speak, we offer some personal insights into the foundations of HBE, and we discuss briefly features we believe account for the longevity and cumulative productivity of this research tradition. By the late 1970s, the subfield of ecological anthropology was in flux – seemingly in decline. Cultural ecology had faded in popularity. Strenuous debates concerning “cultural materialism,” functionalism, population pressure, and the role of energy flow occupied the subfield and its critics. The cognate field of economic anthropology appeared stymied by the formalist–substantivist dispute. Key players in the ecological approach to sociocultural variation began, one by one, renouncing one framework to advance another, which in turn tended to last only a decade or so before being subject to sustained questioning and desertion. Human adaptability approaches in biological anthropology were less riven by dispute but remained a minor specialty in that subfield. As graduate students in anthropology with an abiding interest in evolution and ecology, we might have been discouraged by this. But, in fact, we and a group of peers found opportunities to immerse ourselves in the exciting frameworks emerging in biology, including population ecology, biogeography, sociobiology, and, most importantly, what was being called “socioecology” or “behavioral ecology.” Revolution was in the air, and a small number of young anthropologists began to see the potential for revitalizing the study of human behavioral adaptation with the combination of selectionist logic, optimization modeling, and rigorous empirical evaluation being advanced by biologists such as Jerram Brown, Eric Charnov, John Hurrell Crook, Richard Levins, John Maynard Smith, Robert MacArthur, Gordon Orians, and others. Much of the early discovery and adoption of behavioral ecology by anthropologists was midwifed by biologist mentors. In our case, this included inspiring coursework with Steve Emlen and Eric’s postdoc with Orians; similar interactions occurred with Frank Bayham (Stephen Fretwell), John Beaton (Martin Cody), Kristen Hawkes and Kim Hill (Eric Charnov), Ray Hames (Richard Alexander), and Monique Borgerhoff Mulder (Tim Clutton-Brock), among others. We know of at least five PhD dissertations framed explicitly in HBE terms that emerged from various anthropology departments between 1977 and 1982. Other landmarks in the early history of HBE include a 1981 volume on natural selection and social behavior edited by the biologists Alexander and Tinkle that included chapters by anthropologists, the 1979 Chagnon and Irons collection stemming from an American Anthropological Association (AAA) session that included E. O. Wilson

https://doi.org/10.1017/9781108377911.001 Published online by Cambridge University Press

xii

Foreword

and Robert Trivers, and the 1981 volume on hunter-gatherer foraging strategies edited by us, also germinated from an AAA session. The journal Ethology and Sociobiology (later renamed Evolution and Human Behavior) was inaugurated in 1979, and a decade later, Jane Lancaster founded Human Nature. In the ensuing years, HBE research has burgeoned (as amply reviewed in the present volume). What explains the success of HBE when so many other styles of ecological anthropology have faded? How did our field grow from early days when, as a colleague once joked, a couple of well-placed explosions or an elevator failure could have basically erased the field? On reflection, we would highlight five features of HBE. First, HBE started with and has retained a solid foundation in evolutionary biology, based not just in general principles but in ongoing engagement with the literature in theoretical and empirical behavioral ecology and cognate fields. The increasing frequency with which HBE papers appear in top-line biology or general science journals is one indication that our field remains conversant with current developments in BE and evolutionary biology in general. As the HBE literature grows, it will become more difficult to avoid involution, but the history of HBE suggests that attentiveness to developments in evolutionary ecology and behavioral economics is vital. Of equal importance, the biological foundations of HBE have not come at the expense of discounting unique (or uniquely developed) human characteristics, from social learning and cultural transmission to specific features such as large-scale cooperation, symbolic language, ritual, and technology. Second, in marked contrast to much of anthropology, HBE has consistently practiced a hypothetico-deductive (H-D) research strategy, utilizing formal models to generate explicit and testable hypotheses, which in turn are subject to rigorous empirical testing. In turn, test results are used to evaluate and, as necessary, modify or discard the assumptions and models used to generate these hypotheses. Finely detailed, quantitative field studies likewise have been a strength of HBE. We are not claiming that all HBE research adheres to the H-D format, or that the field is entirely free of untested plausibility arguments or confirmation bias. But relative to other anthropological research traditions, HBE has been highly productive because of its emphasis on a judicious combination of formal models and empirical evaluation. Third, collaboration with biological mentors was vital at the origin of HBE; interdisciplinary team-oriented studies will be even more important to its future. When the first HBE generation went to the field, our equipment consisted of pencils and notepads, a stopwatch, SLR camera and perhaps a cassette tape recorder, steel tape measure and spring scale, paper maps, black-and-white air photos usually of WWII vintage, and a portable mechanical typewriter. Surprisingly, those simple tools accomplished a lot. Our analyses consisted mainly of descriptive statistics, compiled from punch cards on an unseen “mainframe” computer, or produced with handheld calculators. Much has changed. Foremost is the technology available for recording and analyzing complex behavioral data. From GPS and remote sensing to Bayesian and multilevel statistical methods, the potential of behavioral data analyses has grown enormously. In parallel, the skill sets required to make use of this potential have

https://doi.org/10.1017/9781108377911.001 Published online by Cambridge University Press

Foreword

xiii

proliferated and have grown more demanding. Collaboration – with our anthropological colleagues, ethnographers, archaeologists, paleoanthropologists, and primatologists, and with geographers, satellite data analysts, biomathematicians, and others with relevant skill sets – has become more common and indeed necessary. Fourth, HBE has flourished by being intellectually omnivorous. Although research on subsistence decisions dominated in the earliest field studies, applications of HBE quickly expanded to work on mating systems, parental care, reciprocity and collective action, the origins of agriculture, and evolution of inequality. Studies of pastoralists, horticulturalists, and fisherfolk were added to those of hunter-gatherers. Policy-framed studies likewise have begun to appear. They range from research on the decision-making of auto thieves to the potential for spread of zoonotic infections via the foraging decisions of women and children. Application of games and experimental methods drawn from behavioral economics and cognitive psychology have opened new research possibilities, as have analyses of existing cross-cultural databases as well as those newly assembled from past or contemporary studies. The current volume is testimony to this topical expansion. We should also draw attention to the burgeoning of HBE-based work in archaeology, evident in the present volume but of breadth and abundance to merit a companion volume of its own. Finally, a fifth feature that has helped HBE prosper is an avoidance of intellectual hubris. Practitioners of HBE rarely claim to possess a master narrative that comprehensively explains human society; they generally remain cautious about having found the definitive answer even to much more specific questions. The field has been explicit in acknowledging the multi-causality of human behavior and in seeking to understand its own explanatory limits. Furthermore, HBE has a good record of avoiding such pitfalls as genetic determinism and gender essentialism – HBE remains, in other words, anthropologically informed about human diversity and flexibility. In sum, five decades of hindsight suggest to us that these are among HBE’s more important guiding features. In any case, we are confident that the next 50 years of this evolving research tradition will be equally productive of creativity and insights. Eric Alden Smith Professor Emeritus of Anthropology University of Washington, Seattle

https://doi.org/10.1017/9781108377911.001 Published online by Cambridge University Press

Bruce P. Winterhalder Professor Emeritus of Anthropology University of California, Davis

https://doi.org/10.1017/9781108377911.001 Published online by Cambridge University Press

1

Human Behavioral Ecology Brooke A. Scelza, Jeremy Koster, and Mary K. Shenk

The study of human behavior has been at the core of scientific research since its inception, and theories to describe its emergence, transformation, and diversity continue to engage scholars across the natural and social sciences. For many social scientists, evolutionary theory has been a useful framework for understanding what motivates and constrains human behavior and also why it varies both among individuals in the same society and across cultures. Within the diversity of perspectives studying the nexus of evolution and human behavior, the field of human behavioral ecology (HBE) emerged as the study of the adaptive nature of behavior as a function of socioecological context. In this volume, we explore the history and diversification of HBE, a field which has grown considerably in the decades since its emergence in the 1970s. At its core, the principles of HBE have remained a clear and cogent way to derive predictions about the adaptive function of behavior, even as the questions and methods of the discipline have evolved to be more interdisciplinary and more synergistic with other fields in the evolutionary social sciences. Any study of human behavior is helped by first highlighting the myriad ways in which we are unique as a species. As primates, we share many important traits with our closest relatives, the great apes, including a slow life history, a large brain-to-body size ratio, group living with kin-based alliances, and complex patterns of social behavior. However, among apes, humans are also distinct. For instance, humans exhibit less sexual dimorphism than other great apes, not only in overall body size but also in the size of canine teeth that can serve as weaponry among primate males. The slow life history of apes is even more extended in humans, with a long period of childhood and a delayed age at first birth. Yet, compared to other primates, humans have a relatively high fertility rate, resulting from shorter interbirth intervals. In addition, humans routinely live for an extended time beyond the birth of their last children, and this long postreproductive life span is common even in settings without modern health care technologies. The intersecting features of delayed maturity, short interbirth intervals, and long life span contribute to our designation as a species of cooperative breeders, as it is common for multiple individuals to contribute to the care and provisioning of human children, including care from grandparents and elder siblings. Other facets of human behavior also distinguish us from our primate relatives. In general, collaborative subsistence strategies and food sharing are ubiquitous features of human societies, as opposed to the more solitary foraging habits of other primates. Our social organization is relatively flexible, and kinship systems, rules of descent, and postmarital residence rules exhibit remarkable cross-cultural diversity.

https://doi.org/10.1017/9781108377911.002 Published online by Cambridge University Press

2

Brooke A. Scelza, Jeremy Koster, and Mary K. Shenk

This variation partly relates to local ecological constraints, paralleling the heterogeneous social organization of nonhuman primates. However, the diversity of social structures among humans displays variety and combinations not seen within other species. These structures are further elaborated by cultural practices, which add additional complexity. For example, marriage is a cultural universal with deep evolutionary roots, and it involves social connections and obligations that go far beyond mating. Kinship likewise extends beyond biological bonds through cultural processes such as fictive kinship, affinal relationships, and adoption. Our system of communication, including symbolic language, is also unrivaled in the animal world. In particular, humans exhibit a pronounced reliance on language for cultural transmission and social learning. Cumulative cultural transmission facilitates the use of tools and other technological adaptations to local environments. Language and other adaptations also allow humans to cooperate on unparalleled scales, not only with kin and other local group members but also with out-group members – an unusual trait for any primate. Together, the capacity for human culture has allowed us to inhabit and thrive on the most remote parts of the planet, create complex institutions, and develop cumulative technologies that transform both our own ways of life and the ecosystems we inhabit. Human behavioral ecologists maintain a long-standing interest in both the evolution of these distinctive traits and the ways in which they vary within our species. To pursue research questions along these lines, projects typically occur at the level of individuals. This methodological individualism (Udehn 2002) reflects several key assumptions of the HBE approach. First, long-term evolutionary processes are the result of variation in fitness-related outcomes among individuals throughout their lives (Williams 1966b). Accordingly, studies of behavioral variation in human populations can elucidate key trade-offs that underlie the long-term evolution of adaptive traits. Relatedly, humans are assumed to respond flexibly to socio-environmental variation in ways that promote fitness-enhancing outcomes. This assumption of behavioral flexibility is central and implicit in theoretical models, meaning that behavior is expected to vary across individuals based on their respective socioecological circumstances. The resulting view of behavioral flexibility departs from alternative views of behavior as instinctive, rote, or culturally determined. That is not to claim, however, that all human behaviors are unambiguously adaptive. Humans also exhibit maladaptive behaviors, and these behaviors potentially reflect important constraints on human evolution, therefore meriting attention from researchers, too. In general, though, the HBE approach posits that humans evolved to respond effectively to diverse evolutionary challenges, and the resulting natural history of our species is what motivates human behavioral ecologists to pursue their research.

1.1

The Intellectual History of Human Behavioral Ecology Human behavioral ecology has its roots in two fields, both of which emerged in the middle of the twentieth century. The first, cultural ecology, sought to understand the

https://doi.org/10.1017/9781108377911.002 Published online by Cambridge University Press

Human Behavioral Ecology

3

role of the natural environment in effecting culture change. Cultural ecology was a response to two opposing worldviews of the time, each of which propagated an iteration of the nature versus culture dichotomy. First, emphasizing nature as primary, environmental determinists proposed that human behavior was dictated by local environmental conditions, relegating culture to a response rather than a primary force. On the other hand, the possibilists, led by Franz Boas and Alfred Kroeber, posited that human response to environmental conditions was extremely mutable and that culture could take a variety of possible forms in the same environment, with cultural history and the diffusion of ideas and technologies playing key roles. The cultural ecology movement, led by Julian Steward, proposed that the environment influenced the ways that people adapted to their environment but did not determine it, offering a middle ground between determinism and possibilism. This middle ground was a critical contribution of cultural ecology. However, it did not offer an explanation for why such patterns of adaptation would occur. To fill this gap, early human behavioral ecologists turned to evolutionary theory. Like cultural ecology, the field of ethology focused on human-environment interactions, but it grew out of biology and comparative psychology. It can be traced back to Darwin, but the works of scholars such as Konrad Lorenz and Niko Tinbergen focused evolutionary theory on the study of behavior in natural settings, which would become a hallmark of behavioral ecology. The 1960s and 1970s saw the emergence of many of the models and theories that would form the backbone of behavioral ecology, including kin selection theory (Hamilton 1964), optimal foraging theory (MacArthur and Pianka 1966), parental investment theory (Trivers 1972), and life history theory (Stearns 1976). These models continue to be at the core of behavioral ecology and are the foundation of much of the work in this volume. In the mid-1970s, a number of anthropologists and archaeologists began to apply evolutionary theory and the aforementioned models within particular human populations through ethnographic fieldwork. These early studies tackled basic questions about the roles of kin selection, sexual selection, and fitness optimization in humans (Chagnon 1979; Hames 1979; Strassmann 1981; Turke and Betzig 1985). Around the same time, the first applications of optimal foraging theory were applied to huntergatherers (Winterhalder and Smith 1981; O’Connell and Hawkes 1981; Smith 1985). In general, the results of these studies frequently upheld the predictions of HBE models, which helped to launch additional theorizing and applications to increasingly diverse research questions.

1.2

Basic Principles of HBE The evolutionary study of behavior is traditionally organized around four complementary approaches: causation, development, function, and phylogeny (Tinbergen 1963). The first two focus on proximate (i.e., more temporally direct or immediate) explanations: understanding the mechanism of the behavior (causation) and its ontogeny (development). The second two questions address ultimate (i.e., more distal or evolutionary) explanations: studies of phylogeny and studies of adaptation or

https://doi.org/10.1017/9781108377911.002 Published online by Cambridge University Press

4

Brooke A. Scelza, Jeremy Koster, and Mary K. Shenk

function. Of these, behavioral ecologists have almost exclusively focused on function, aiming to understand how natural selection has produced organisms that respond to environmental conditions in ways that increase their chances of surviving and passing on genes to the next generation. This focus on adaptation means that HBE uses, as a starting point, the hypothesis that behavior will be close to optimal in terms of maximizing fitness. Human behavioral ecology’s conventional agnosticism about development and mechanism has been exemplified through its acceptance of the “phenotypic gambit,” an assumption that systems of inheritance do not meaningfully constrain adaptive responses to local variation. In practice, this approach allows a researcher to study the fit between ecology and behavior without needing to uncover or specify the exact proximate mechanisms (developmental, physiological, or behavioral) through which this fit is achieved. While HBE research continues to focus on function, the field has become more integrative of other approaches to the study of behavior. In so doing, the methodological agnosticism that initially characterized HBE is being replaced by the notion that “mechanisms matter” (Borgerhoff Mulder 2013). For example, researchers in genomics have made important discoveries about feedbacks between genes and behavior that highlight the need for a deeper consideration of genetic mechanisms (Adkins et al. 2018; Kuzawa and Thayer 2011). In addition, the role of transmitted culture is increasingly being recognized by human behavioral ecologists as important not only to understanding why maladaptive outcomes occur but also in illuminating how behavioral strategies arise and thrive (Mesoudi 2021; Newson et al. 2007), which again highlights a need for greater integration of proximate and ultimate approaches in research. Throughout this volume, readers will see evidence of this integration of the four basic approaches, though generally still with an overarching emphasis on adaptation and function. Another central tenet of behavioral ecology involves conceptualizing behavior in terms of conditional strategies to understand variation in phenotypes, often organized around a strategy set that represents possible variations of a behavior in a particular context. In simple form, conditional strategies involve logic such as: “When conditions are X, use strategy i, but when conditions are Y, switch to strategy j.” For example, males in a population who want to find a mate could either fight to control a territory and the females on it or try to sneak matings from within other males’ territories. Which strategy any individual male chooses is predicted to be contingent on factors such as his physical condition, his relative status, and the density of females in the area. More complex decisions require much larger strategy sets. When a forager decides what resources to pursue, for example, she has a variety of possible combinations to choose from. Strategies can also cross domains, including decisions about how to meet both childcare and food production goals (Scelza and Bliege Bird 2008; Starkweather et al. 2023), or assessing both the social and productive aspects of foraging alone versus in a group (Smith 1985; Alvard and Nolin 2002). Behavioral responses are expected to vary according to local conditions; thus, what is optimal in

https://doi.org/10.1017/9781108377911.002 Published online by Cambridge University Press

Human Behavioral Ecology

5

one context is likely to differ from what is optimal in another circumstance or for another person. Early HBE studies focused on how ecological variation in the physical environment helps to explain the diverse behavioral repertoire that characterizes modern humans despite a lack of noteworthy genetic differences across populations. As the field has grown, ecology has begun to be construed more broadly to include social and institutional contexts such as socially enforced norms and government policies. The goal of HBE continues to be understanding variation in phenotypes and predicting what characteristics of the local environment lead to the uptake of one strategy over another. At their core, these decisions are believed to be about optimizing fitness. This approach might include predictions that foragers will pursue only resources that increase their return rate, that optimal family size will reflect local mortality risks, or that the likelihood of cooperation between individuals depends on their biological relatedness and level of need. Human behavioral ecology’s reliance on the logic of optimization does not presuppose that humans are perfectly adapted to their environments (though this is a common misconception).1 Instead, optimization models follow from the principles of natural selection, which is expected to favor locally advantageous adaptations over time, leading to an increasingly better fit of behavior with local environments. Yet, behavioral ecologists are also keenly aware of the potential for mismatch between fitness and local behavioral adaptations when environments change very quickly, as they have been in many regions of the world in the era of globalization (Gurven et al. 2017). In these contexts, behavioral ecologists aim to understand how traditional behavior may have been adaptive given the past environment and also how changing patterns of behavior may be understood from an evolutionary perspective. In order to assess the costs and benefits of alternative strategies, behavioral ecologists need a standardized “currency“ for comparison. The ideal currency for evolutionary models is fitness, but fitness is a probabilistic rather than an absolute measure, representing the likelihood that an individual will survive and pass on genes to the next generation. This makes it very difficult to measure directly. Instead, behavioral ecologists use fitness proxies, traits that are widely accepted to be positively correlated with survival and reproduction. Within human behavioral ecology, commonly used proxies include calories, body composition, mating frequency, number of children born, and number of children who survive early childhood.

1

Another common misconception about behavioral ecology involves the individuals’ conscious awareness of their decision-making processes. One might imagine, for instance, that advanced mathematics might be necessary for individuals to identify the optimum strategy amid a large set of possible alternatives. On the contrary, behavioral ecologists expect that natural selection will equip individuals with the cognitive architecture needed to make adaptive decisions, often relying on informal heuristics. By analogy, consider the challenge of catching a fly ball in the game of baseball. When fielding the ball, players are not consciously using trigonometry and calculus to calculate where the ball will fall. Instead, it is sufficient for them to adjust their running speed so that the angle of the ball relative to the ground remains constant (McLeod and Dienes 1996). Simple heuristics are often adequate solutions to complex adaptive problems.

https://doi.org/10.1017/9781108377911.002 Published online by Cambridge University Press

6

Brooke A. Scelza, Jeremy Koster, and Mary K. Shenk

The final factors that behavioral ecologists must consider are the constraints to the system, namely the aspects of the environment that are not under the control of the actors whose decisions are being modeled. Most systems have both extrinsic and intrinsic constraints. Extrinsic constraints include ecological characteristics, such as the distribution of prey in the landscape, the number of competing hunters in the group, or the level of risk from infectious disease. Intrinsic constraints can include diverse perceptual and sensory factors, cognitive constraints, and physiological limitations and other morphological considerations.

1.3

What We Work On Human behavioral ecology focuses on behavioral responses to variation in the environment, which opens up a wide variety of topics for its practitioners. However, the majority of HBE studies have focused on production, cooperation, distribution of resources, and reproduction. Here we provide a brief history of work on these topics, and then we shift to describe what we perceive as the major trends that are guiding current and future research in HBE. Human behavioral ecology largely originated with applications of optimal foraging models, borrowed from behavioral ecology and applied to contemporary foraging societies. These models address trade-offs and strategies of subsistencebased production, including whether to pursue a prey type when it is encountered, how long to stay in a particular location or “patch,” and how to account for stochasticity in the resource base to avoid shortfalls. Over time, this part of the field expanded further to consider the motivations behind foraging activities (e.g., do men hunt to provision families or to attract mates?), how foraging strategies vary across the life span, and the sexual division of labor. Market integration has also resulted in changing modes of production and increased the likelihood of mixed modes of production within communities, meaning researchers need to pay careful attention to complicated aspects of the household economy, including the practice of traditional livelihood strategies (e.g., agriculture, fishing, herding) alongside new ones (running a local shop, migrating to cities for work) – several of which may be simultaneously evident among members of the same family, household, compound, or village (Tucker et al. 2010; Ready and Power 2018; Starkweather 2017). The first part of this volume addresses these topics with chapters on foraging strategies (Chapter 3), modes of subsistence (Chapter 4), and the division of labor (Chapter 6). Another recurrent theme within HBE research has been a focus on the unprecedented scale of cooperation that humans exhibit. At first, much of this work examined the question of altruism and the conundrum of how natural selection could favor behaviors that benefit others at a cost to the actor. Kin selection and reciprocal altruism, both also widely discussed in other species, were early models that HBE practitioners considered in depth. Much of the empirical work on this front focused on food sharing and cooperative production, providing interesting addenda to tests

https://doi.org/10.1017/9781108377911.002 Published online by Cambridge University Press

Human Behavioral Ecology

7

of optimal foraging models. These extensions include the ways in which biological markets have affected cooperation and food sharing (Jaeggi et al. 2016b). Beyond food production and distribution, HBE has devoted attention to myriad other aspects of cooperation, including political alliances, warfare, and childcare. This volume addresses these topics in chapters on cooperation (Chapter 5), status and hierarchy (Chapter 7), and political organization (Chapter 8). Studies of reproduction represent the broadest and fastest-growing area of research within HBE (Nettle et al. 2013). This literature encompasses studies of mating and marriage, the role of parents and alloparents, and broader demographic patterns of fertility and mortality. Much of this work relies on principles from life history theory, which outlines how natural selection can shape patterns of growth, survival, and reproduction in a given species. Classic research in this area focused on variation in mating and marriage strategies, often extrapolating from models like the polygyny threshold model (Borgerhoff Mulder 1990), as well as tackling variation in marriage payments across societies (Dickemann 1991; Gaulin and Boster 1990). Early work on fertility and parental investment investigated the optimality of birth spacing (Blurton Jones 1987) and differential investment (Mace 1996; Daly and Wilson 1983; Borgerhoff Mulder 1998a), and researchers also took on the challenge of explaining the demographic transition (Borgerhoff Mulder 1998b; Mace 1998). As with studies of production, changes brought about by urbanization, market integration, and globalization have also spurred strong interest in shifting patterns of mating, marriage, and parental and alloparental investment. Recent studies of mating and marriage have considered how an HBE perspective can be useful for understanding issues such as dowry inflation (Shenk 2007), the relationship between wealth inequality and polygyny (Ross et al. 2018), and how labor migration affects mating market dynamics (Schacht and Smith 2017). Industrialization is also often implicated in the shift toward more intensive investment in a smaller number of children who can compete for opportunities in the emerging wage labor economy (Kaplan 1996). This shift has prompted novel forms of parental investment, notably including formal education, which was traditionally nonexistent but is often the primary form of investment in children in market-integrated societies. These changes have motivated researchers to consider how investment in children changes with subsistence patterns (Hassan et al. 2021) and also how to conceptualize such new forms of investment from a theoretical perspective. Moreover, education leads to novel forms of social learning and cultural transmission (Kline et al. 2013), which may accelerate the effects of cultural change in market-integrated societies (Richerson and Boyd 2005); it is thus unsurprising that the study of social learning has become a very active field of study in the past few years. Finally, new iterations of sexual selection theory have triggered reevaluations of some classic evolutionary models, as seen in studies of the adult sex ratio and mating market dynamics (Schacht and Borgerhoff Mulder 2015) and the role of multiple mating for women (Scelza 2013). Often drawing upon life history theory (Chapter 2), the second half of this volume addresses these topics, including chapters on mating (Chapter 9),

https://doi.org/10.1017/9781108377911.002 Published online by Cambridge University Press

8

Brooke A. Scelza, Jeremy Koster, and Mary K. Shenk

marriage (Chapter 10), parental investment (Chapter 11), cooperative breeding (Chapter 12), and evolutionary demography (Chapter 13). As HBE has developed, not only have the questions changed, but so have the ways in which researchers have addressed them. With an increasing number of researchers working alongside NGOs and in areas of the world where economic development policies are being implemented, the field has also taken a turn toward applied approaches, leading to the emergence of a subfield of applied evolutionary anthropology (Gibson and Lawson 2015; Pisor and Jones 2021; Tucker and Rende Taylor 2007). The goals of this approach are to apply the logic and models of HBE to address practical challenges faced by communities and to engage with the international development community to understand the consequences of development projects, ideally steering programs in a more locally appropriate direction. Human behavioral ecologists taking this approach have studied numerous topics, including health (Lawson and Uggla 2014; Pepper and Nettle 2017), the green revolution (Tucker 2014), microfinance (Lamba 2014), family planning decisions (Leonetti et al. 2007), the nutrition transition (Neill 2007), sex ratio bias (Shenk et al. 2014), and climate change (Bliege Bird and Bird 2021). As in other subfields of anthropology, these approaches sometimes constitute a critique of policies promoted by development agencies that ignore important ethnographic context or take unrealistic or ethnocentric approaches to problems where evolutionary theory provides key insights, such as work on “child” marriage (Schaffnit and Lawson 2021), dowry (Shenk 2007), and domestic violence (Stieglitz et al. 2018). To address these issues and generally add depth to the study of HBE, causal mechanisms have become an area of greater interest. There has also been a shift from studies focused largely on individual-level decision-making to ones that encompass institutions and cultural processes. Whereas HBE has historically been set in tension with other disciplines studying evolution and human behavior, increasingly researchers are finding fruitful areas of overlap. Accordingly, this volume includes chapters on human biology (Chapter 14), cultural evolution (Chapter 15), and evolutionary psychology (Chapter 16), which showcase the ways in which HBE fits within the larger field of evolutionary social science.

1.4

How We Work Like most basic science research, HBE relies on a hypothetico-deductive research strategy, which involves the use of models to derive specific, testable predictions. HBE strategically relies on simple models that capture the basic elements of a situation, sacrificing detail and nuance for clarity and generalizability. Simple models are useful because they can be applied across many contexts. This means that general theoretical concepts can be applied across diverse settings to identify the kinds of conditional strategies that are at the core of the field. But the fact that HBE models are generalizable rather than context-specific has sparked intermittent criticism from cultural anthropologists, who assert that such reductionism is unrealistic. In one sense, this criticism is justified; simple models cannot provide a holistic replication

https://doi.org/10.1017/9781108377911.002 Published online by Cambridge University Press

Human Behavioral Ecology

9

of real-world dynamics. Yet, rather than trying to replicate reality, HBE models aim to highlight the central role of particular variables and trade-offs that underlie behavioral strategies in multiple contexts. This approach requires simplifying assumptions, including assumptions that are unlikely to capture all relevant variation. For example, when human behavioral ecologists first adapted the polygyny threshold model from biology (Orians 1969), it was assumed that co-wives did not offer benefits to one another, such as increased production efficiency or help with childcare (Figure 1.1). The models focused only on the relative benefits that women could gain from partnering with either an unmarried or an already married man. This allowed for the derivation of clear predictions (e.g., women should choose to marry a married man only when the share of resources that she would receive are greater than those she would have upon marrying an unmarried man). The goal was to identify the effect of male resources on women’s decisions about whom to marry.

Fitness

Monogamous Option Polygynous Option

A

B

Partner Resources Figure 1.1 A graphical depiction of the polygyny threshold model (Orians 1969). The two

sigmoidal curves show the respective fitness functions of a woman who either partners monogamously (solid line) or as a second mate (dashed line). The curves vary as a function of the male partner’s resources, and assuming an unconstrained choice, women are expected to choose the option that maximizes their fitness. The optimal choice depends on the potential partners’ respective resources. Consider the choice between the monogamous option in which the partner’s resources are represented by point A and the polygynous option with a partner’s resources at point B. The horizontal dotted line represents the threshold at which the choices are equivalent. If point B were to shift downward, then monogamy would be favored. Conversely, if point B were to shift upward, the polygynous option would be advantageous. Note that the fitness functions depicted here are hypothetical and could vary substantially in different contexts, particularly when integrating additional considerations such as those described in the text (e.g., potentially beneficial cooperation among co-wives).

https://doi.org/10.1017/9781108377911.002 Published online by Cambridge University Press

10

Brooke A. Scelza, Jeremy Koster, and Mary K. Shenk

Empirically, however, researchers found mixed support for the basic polygyny threshold model. Among Kipsigis of Kenya, female choice based on relative resource access appeared to be a key factor in the decision to marry polygynously, supporting the conceptual model (Borgerhoff Mulder 1990). In other settings, however, polygynous women fared worse than their monogamous counterparts, indicating that the female choice model advanced by Orians does not necessarily fit well in human populations and that men may be coercing women into polygynous marriages that benefit their own fitness interests (Chisholm and Burbank 1991). This led researchers to follow up with studies that focused on the importance of co-wife cooperation and conflict as motivators or detractors for choosing polygyny (Jankowiak et al. 2005; Scelza 2015), the interaction of polygyny with other socioecological factors (Lawson et al. 2015), and the role of parental marriage arrangements in curtailing female choice (Apostolou 2007). Other work incorporated richer demographic data to assess the links between polygyny and fertility and to assess whether a choice or coercion model is a better fit (Winking et al. 2013). That is, researchers started with a simple model, and then, as they accrued data, they were able to use previous results to develop refined models that better predicted men’s and women’s decisions. To test their models, human behavioral ecologists employ diverse methods from biology, anthropology, economics, and psychology, often integrating quantitative and qualitative data. Typically, quantitative data are used in direct tests of predictions, while qualitative data help researchers to design methodological tools and contextualize their results. Quantitative methods frequently include surveys or questionnaires for demographic data, direct observation for behavioral data, weighing and measuring of items (e.g., gathered foods or household goods) to understand return rates or wealth, and health measurements (e.g., height, weight, blood pressure). Traditional qualitative methods from cultural anthropology are also widely used, including open-ended interviews, focus groups, and participant observation. These are central to gaining local ethnographic knowledge, developing nuanced questions for more structured data collection, and interpreting the results of those data during analysis (Box 1.1). One set of methods, borrowed from behavioral ecology studies of other species and advantageous for providing both reliable observations of behavior and deeply contextualized data, is the systematic recording of time allocation (Hames 1992). Common sampling designs include focal follows, which allow for longer periods of observation focused on a single individual, or instantaneous scans, which are designed to gather information on many individuals over a short period of time. In humans, time allocation data have been used to test optimal foraging models (Hill et al. 1987; Koster 2008), to assess the role of parents and alloparents in studies of investment (Ivey 2000; Scelza 2009), and to examine behavioral specialization and trade-offs in subsistence strategies (Koster and McElreath 2017). The methods have also been used to address questions about human life histories, including how time allocation changes across the life span (Gurven and Kaplan 2006) and how children’s labor can help to offset their costs, allowing for larger family sizes (Kramer 2004).

https://doi.org/10.1017/9781108377911.002 Published online by Cambridge University Press

Human Behavioral Ecology

Box 1.1

Illustrating the Human Behavioral Ecology Approach

To illustrate how human behavioral ecologists approach research problems, it is useful to consider an example. In this case, consider the example of polyandry, marital unions with one woman and multiple men. Ethnographically, polyandrous marriages are significantly rarer than polygynous marriages, but a survey of the literature reveals a few societies, mostly in the Himalayas, where polyandry is common (Figure B1.1.1). If natural selection favors behaviors and decisions that tend to increase an individual’s long-term evolutionary fitness, then initially it may seem irrational for a man to consider a polyandrous union that limits his fertility relative to a monogamously or polygynously married man. However, this seemingly suboptimal behavior recurs intermittently in diverse contexts, which invites attention and scrutiny from human behavioral ecologists. To consider why polyandry occurs, a human behavioral ecologist might begin by considering similar behaviors among nonhuman primates and other animals. The comparative approach is valuable because behavioral strategies among animals may be homologous traits that are similar because of shared ancestry (Wrangham 1987). For example, many primates exhibit predispositions to develop fears of snakes, and consequently the presence of this homologous trait in humans does not require an explanation of its origin in the hominin lineage (Öhman and Mineka 2003). In the case of polyandry,

Figure B1.1.1 Fraternal polyandry has been documented primarily in the Himalayas, including the state of Himachal Pradesh in northern India. Credit: kiwisoul/iStock/Getty Images Plus.

https://doi.org/10.1017/9781108377911.002 Published online by Cambridge University Press

11

12

Brooke A. Scelza, Jeremy Koster, and Mary K. Shenk

however, the behavior is not found generally among extant catarrhine primates, including apes, which suggests that polyandry in humans is not an ancestral trait. Independent of homology, though, humans often face decisions that resemble those by nonhuman animals. Among some nonhuman primates, males similarly decide either to stay in a social group with a dominant breeding male – with limited reproductive opportunities – or to disperse in search of other females (e.g., Snyder-Mackler et al. 2012). The decision to stay and share reproduction with another male often results from a lack of better alternatives, and these theoretical models can be adapted to human contexts. Analogously, most explanations of polyandry in humans maintain that polyandry is more likely when socioecological constraints limit men’s ability to support their families through monogamous marriage, and thus wife-sharing may be a better alternative than remaining single (Levine and Silk 1997). Human behavioral ecologists attempt to consider the full range of costs and benefits that underlie behavioral choices. For example, following kin selection theory (see Chapter 5), the costs of polyandry can be mitigated if co-husbands are related because the offspring are genetic relatives of all husbands. Known as fraternal polyandry, marriages involving brothers are the most common type of polyandrous union across human societies (Starkweather and Hames 2012). In human contexts, meanwhile, institutions and cultural norms can also shape the trade-offs of different strategies. In Himalayan settings, for example, oldest sons often inherit their parents’ estate, which provides them with advantages in the marriage market. With these considerations in mind, Smith (1998) examined the trade-offs of fraternal polyandry by adapting the member-joiner model, which had been developed previously to study the aggregation of foraging groups in animal populations, including humans (see Chapter 3). Applying the model to a polyandrous Tibetan population, Smith found that for “members” (i.e., the already married eldest brother), polyandry seemingly results in a loss of inclusive fitness compared to monogamy, but for “joiners” (i.e., younger brothers), polyandry increases their inclusive fitness relative to their alternative options. Notably, this result was based on the tenuous assumption that all husbands have an equal probability of fathering the wife’s offspring. Greater reproductive opportunities for the older husband within the marriage would alter the trade-offs accordingly. The potentially asymmetric benefits to the co-husbands, however, illustrate a general point that family relationships are often unstable as individuals constantly reevaluate the costs and benefits of their possible choices. In principle, if all of the contributing factors can be identified and measured precisely for a given individual at a certain moment in time, then the individual’s adaptive decision is knowable scientifically. Although such comprehensive precision may be impossible, the theoretical models nonetheless facilitate

https://doi.org/10.1017/9781108377911.002 Published online by Cambridge University Press

Human Behavioral Ecology

13

hypotheses that can be tested empirically. Whether those hypotheses relate to polyandrous marriages or other decisions, the enterprise of human behavioral ecologists is to theorize about the primary determinants of adaptive decisionmaking and to marshal the evidence needed to test the predictions of those theories.

Time allocation observations are the methods most closely associated with HBE, and the approach has several benefits. First, it allows researchers to learn about actual behavior, rather than normative rules or hypotheticals that ask participants to speculate on how they would behave in a certain situation. Quantitative observational studies can reduce reporting biases from interviews and ethnographic observations that tend to overrepresent cultural rules while underestimating behavioral variability (Johnson and Behrens 1989). Second, because the methods are clearly defined, the studies are replicable and amenable to cross-cultural comparisons. For example, a cross-cultural study leveraged time allocation data from twelve different study sites to investigate how the local socioecology, including the risk of encountering dangerous animals and the sexual division of labor, affected children’s activity budgets (Lew-Levy et al. 2022). However, there are some important limitations to using time allocation data, including the time required to get participants accustomed to being observed and the inability to observe certain types of behavior that are either private or otherwise inaccessible to the researcher. Structured and semi-structured interviews are another key method of HBE research that aims to collect systematic data for hypothesis testing. These interviews can be used to elicit demographic data (e.g., reproductive and marital histories), life history trajectories, measures of household wealth, or patterns of mobility. Many researchers develop questions and measures to fit local situations, but increasingly crossculturally validated measures are also used, including food and water security scales (Young et al. 2019), the Big Five personality inventory (Gurven et al. 2013), and measures of sexual conflict (Stieglitz et al. 2018) and mental health (Hadley and Patil 2006; Lawson et al. 2021). Human behavioral ecologists also borrow methods from other disciplines in the social sciences. For example, economic games have been widely used to assess norms about cooperation (Henrich et al. 2005). However, the mixed-method approach favored by human behavioral ecologists has led to integration of these games with other behavioral measures. For example, Gerkey (2013) used locally relevant derivations of the public goods game to understand how cultural norms and institutions frame cooperative decision-making. In another novel experiment, Gervais (2017) had Fijian participants allocate money within their social networks to assess how factors like relative need, altruism, and spite affect behavior. While human behavioral ecologists have long studied cooperation, conflict, kin residence patterns, and other forms of social interactions, quantitative data on social networks allow social relationships to be described and analyzed in a more

https://doi.org/10.1017/9781108377911.002 Published online by Cambridge University Press

14

Brooke A. Scelza, Jeremy Koster, and Mary K. Shenk

sophisticated way. Social network data can be used to illuminate the latent structure of the underlying network, examine the relationships of different networks to each other, and compare how networks change across time. Such studies have allowed testing of hypotheses about food sharing (Nolin 2010) and religious practices (Power 2017b), as well as the dynamics of multiplex networks in studying cooperation and reciprocity across multiple domains (Atkisson et al. 2020). Increasing interest in physiological proxies of fitness such as cardiovascular health, malnutrition, and stress have also led human behavioral ecologists to integrate health measurements into their work. These range from conventional anthropometrics (e.g., height, weight, triceps skinfolds) to biomarkers of conditions such as anemia, diabetes, and inflammation that are evident in blood and saliva samples. Health trackers have also been used to analyze heart rate, sleep, and blood pressure. These studies also allow for further integration of proximate and ultimate explanations of behavior, as mechanisms are studied alongside functional outcomes. When used alongside demographic and behavioral data, these measures can be used to test adaptive predictions. For example, Wander and Mattison (2013) used anthropometric and breastfeeding data to test the Trivers-Willard hypothesis of sex-biased investment, Scelza and Silk (2014) used anthropometrics to test predictions about whether fosterage is adaptive among Himba pastoralists, and Trumble et al. (2014) looked at testosterone and cortisol to test between signaling and provisioning predictions for explaining men’s work. As with other fields of anthropology, there has also been a recent shift toward greater collaboration in the research process. This includes increased community engagement in the development of research projects (Broesch et al. 2020; Mangola et al. 2022; Scelza et al. 2020a), integrating positive outcomes for communities into research plans (Gurven et al. 2017), co-publication with local scholars and/or members of study communities (Urassa et al. 2021) and a commitment to better engagement with policy, development, and the general public (Jones et al. 2021a). These shifts are motivated by goals of both increased equity and improved science.

1.5

Where We Work At the field’s inception, human behavioral ecologists worked mainly in small-scale societies, particularly among foraging and pastoralist groups. This focus reflected both theoretical and practical constraints. Theoretically, foraging populations were often chosen because they had features that were believed to have been common throughout our evolutionary history, such as a strong reliance on kin, low population density, substantial familiarity with one’s social group, fertility and mortality patterns that were minimally affected by contraception and biomedical care, and a reliance on intermittently acquired food resources (Box 1.2). Practically, the initial emphasis of HBE on foraging strategies led to the frequent choice of field sites where groups were still hunting and gathering for a substantial portion of their calories. These sites represent some of the best long-term anthropological field sites in the

https://doi.org/10.1017/9781108377911.002 Published online by Cambridge University Press

Human Behavioral Ecology

Box 1.2

The Human Behavioral Ecology of Academic Research: An Ideal Free Distribution

A premise of HBE is that humans flexibly adapt to the costs and benefits of behavioral choices in a given setting. This adaptive flexibility is evident not only among the people being studied but also among the researchers themselves. When selecting research questions and study sites, human behavioral ecologists respond to incentives that reward certain kinds of studies. Among human behavioral ecologists, the perceived value of a study typically is commensurate with its purported relevance for understanding key aspects of human evolution. This emphasis is shared by cognate subdisciplines. Among primatologists, for instance, that relevance is assumed to vary as a function of phylogenetic distance to humans, lending extra cachet to research on the great apes. Among paleoanthropologists, there is similar prestige associated with studying hominin species that are assumed to be directly on the human lineage, more than offshoot clades such as paranthropines. Accordingly, particularly since the Harvard Kalahari Project among the !Kung of Botswana in the 1960s, human behavioral ecologists were motivated to seek out contemporary study populations living in environments or engaging in subsistence practices that presumedly resemble those of human populations in the Pleistocene (Yellen 1990; see Chapter 16). The societies that are studied by human behavioral ecologists often exhibit noteworthy variation in food production directed to meeting subsistence needs, social organization based around kinship, and sociopolitical arrangements in which state-level involvement may be minimal (Figure B1.2.1). In many cases, these societies are Indigenous or ethnic minorities who maintain distinct languages and cultures that differ from the majority in the nation-states where they reside. In general, these settings often provide worthwhile opportunities for human behavioral ecologists to examine specific predictions from theoretical models. For example, when research questions focus on cooperative food production by groups of kin, it is sensible to focus on study sites where these behaviors occur regularly. To explain the preponderance of HBE studies among subsistence-oriented ethnic minorities, it is helpful to refocus the field’s theoretical models onto its practitioners. Chapter 3, for instance, presents the Ideal Free Distribution model. Similar to the polygyny threshold model, the Ideal Free Distribution model assumes that individuals select habitats that offer the greatest value, adjusting for the extent to which the benefits are shared with others. By analogy, the high value that is placed on studies with perceived evolutionary relevance helps to explain why human behavioral ecologists have chosen their study sites and research questions in accordance with an Ideal Free Distribution. The approach has pros and cons. On the one hand, the effort to document and understand human diversity has merit. It remains an effort that anthropologists

https://doi.org/10.1017/9781108377911.002 Published online by Cambridge University Press

15

Brooke A. Scelza, Jeremy Koster, and Mary K. Shenk

1.0

16

0.6 0.4 0.0

0.2

Proportion of Maximum

0.8

U.S. Chile Taiwan Portugal U.K. Netherlands Israel Tsimane Hadza Agta Himba Datoga Mayangna

Years of Maturity Before First Birth

Child Mortality

Total Fertility Rate

Wealth per Adult

Figure B.1.2.1 This figure shows a comparison of selected demographic and economic

variables for a diverse set of societies. Calculated as averages, the variables include (1) years of maturity, starting at age 15, before individuals have their first child, (2) rates of child mortality under the age of 5 years old, (3) the total fertility rate, and (4) wealth per adult. Values within each category are standardized as the proportion of the maximum value. So-called WEIRD populations are represented with darkened symbols, whereas the six other societies are unfilled, with the latter sample drawn from studies by human behavioral ecologists. Among other implications, the comparisons suggest that HBE research often expands the range of behavioral variation observed in human populations. (WEIRD is an acronym to describe societies that are Western, Educated, Industrialized, Rich, and Developed.) Adapted from Winking et al. (2018), with permission from John Wiley and Sons © 2018 IARR.

have taken more seriously than any other academic community. On the other hand, the emphasis on similarities to ancestral populations can lead researchers to exaggerate or misrepresent aspects of their study sites in order to fit preconceptions about the ideal analogues for studying human evolution. In contrast to exotified narratives, ubiquitous features of nearly all study populations include monetized economies, modern contraceptive methods, medicines and vaccines, reliance on domesticated crops and animals, involvement of state-level governments, exposure to tourists and missionaries, and other factors that preclude the use of contemporary societies as straightforward analogues of Pleistocene populations. Clear acknowledgments of these factors benefit the interpretations of findings from HBE studies. It is also important to acknowledge that the economic, social, and demographic orientation of many study communities relates in part to a legacy of political and racial marginalization. In some cases, the societies studied by

https://doi.org/10.1017/9781108377911.002 Published online by Cambridge University Press

Human Behavioral Ecology

17

human behavioral ecologists have retreated to remote locations to escape genocides and other violations of human rights, to maintain cultural independence, and to seek sustainable livelihoods. Those histories are considered carefully by human behavioral ecologists, who typically have substantial respect and affinity for their study communities and who hope to preempt the misuse of their published findings as a basis for further discrimination. In principle, valuable research can be done in any human community. As human behavioral ecologists reconsider past biases, including the emphasis on contemporary societies as proxies for ancestral populations, there is likely to be a shift in the Ideal Free Distribution as greater consideration is given to the diversification of samples and the alignment between research questions and study populations.

field of HBE, including researchers of several generations (Marlowe 2010; Gurven et al. 2017). Between the small-scale societies, where early HBE research was primarily conducted, and the postindustrial societies, in which researchers primarily live, lies most of the world – and our work is increasingly shifting to fill this gap both geographically and topically (Barrett 2020a). Owing to the recent rise of globalization and market integration, few societies rely solely on their own subsistence, and some have argued that the process has created an ecological shift as great as the widespread adoption of intensive agriculture. Upon encountering changing lifeways in their own field sites, many researchers have explored the causes and consequences of change – while for some the process of market integration itself has become a central organizational concept. Integration into regional and global market economies creates a shift in subsistence patterns (Gurven et al. 2015) with the potential to create downstream changes in numerous aspects of life, including parental investment (Colleran 2020), fertility and mortality rates (Shenk et al. 2013), and health (Mattison et al. 2022b). These shifts also alter local cultural patterns of cooperation, kinship, family, residence, marriage (Shenk et al. 2016b; Scelza et al. 2019). These changes have steered attention toward novel research questions while motivating new methodological approaches. The use of national-level data and large demographic surveys has also allowed for tests of adaptive hypotheses with large sample sizes typically unavailable in smallscale ethnographic fieldwork (Mattison and Sear 2016). These studies test the assumption within HBE that phenotypic plasticity leads to relatively fast adaptation to novel conditions. At the same time, they also highlight areas of potential adaptive lag, namely the possibility that humans exhibit suboptimal behavioral responses to novel environmental conditions that differ considerably from the settings to which human behavioral tendencies are adapted (Irons 1998). Finally, because human behavioral ecologists have long been interested in the sources of behavioral variation, cross-cultural comparisons have played an important

https://doi.org/10.1017/9781108377911.002 Published online by Cambridge University Press

18

Brooke A. Scelza, Jeremy Koster, and Mary K. Shenk

role in HBE research. Often, these studies rely on comparative analyses of similar demographic measures across cultures, such as variance in reproductive success (Brown et al. 2009), the effects of alloparents on child mortality (Sear and Mace 2008), and kinship dynamics as a function of age (Koster et al. 2019). As with time allocation data, demographic data are comparatively straightforward to categorize and operationalize in cross-cultural studies. By contrast, studies that require consistent definitions of constructs such as “household” or “marriage” or “status” or other analogous variables have conventionally been challenging to standardize and analyze cross-culturally. Studies of psychology and cognition are likewise challenging, particularly those that require translations of complex concepts into diverse languages and cultural contexts. Successfully navigating those challenges requires a thoughtful research design, and human behavioral ecologists have responded with careful attention to key methodological details and translations. Instead of replicating protocols that were developed in other disciplines, for instance, researchers have found success by beginning with considerations of local contexts and by pioneering methods that are appropriate to the study population (e.g., Hruschka et al. 2018). Other collaborative studies have brought human behavioral ecologists together with those studying evolutionary psychology and cultural evolution to look at variation and universals in behavior and psychology (Barrett et al. 2016; Scelza and Prall 2018). As the methods of HBE become increasingly refined and standardized, cross-cultural comparisons should continue to flourish.

1.6

The Future of the Field When HBE arose as a field, it was one of several theoretical perspectives aiming to use evolutionary theory to better understand human behavior, the others being evolutionary psychology, which focuses on evolved psychological mechanisms, and dual inheritance theory, which focuses on culture-gene coevolution. At the time, as is common with nascent fields of research, the three perspectives were often pitted against each other, and differences between the three perspectives were highlighted (Smith 2000). In many ways, these differences have fallen increasingly into the background with a freer exchange of methods (Scelza et al. 2020c), increasing engagement with culture and social learning in the development of predictions (McElreath et al. 2005; Colleran 2016), and more nuanced understandings of the relationship between psychological mechanisms and behavior (Barrett 2015). Why then produce a volume entitled Human Behavioral Ecology now? While HBE has become more methodologically diverse and more integrative of both proximate mechanisms and broader processes of cultural evolution, its approach remains distinct within the evolutionary social sciences. Unlike its sister fields, HBE has strong grounding in both qualitative and quantitative methods. Ethnography is at the core of most projects, not only to provide context for quantitative data but also to drive the formation of locally specific predictions, which can then be used to understand variation in behavior across time and place. Moreover, at its core, HBE

https://doi.org/10.1017/9781108377911.002 Published online by Cambridge University Press

Human Behavioral Ecology

19

is a field that embraces human behavioral and cultural diversity. Understanding variation in behavior is a central tenet of the field, an emphasis that enables a theoretically informed position on processes such as market integration, globalization, and climate change. Amid the rapid social and environmental changes, that is, viewpoints from behavioral ecology can help to discern shifting trade-offs and novel strategic responses. For example, Colleran (2020) has shown that increasing market integration reduces the density of kin networks among women in rural Poland, and given that kin tend to have more pro-natal influences on women’s reproductive decisions, this could facilitate the transition to smaller family sizes. Meanwhile, Schaffnit et al. (2023) show that market integration alters the dynamics of parent-offspring conflict over marriage arrangements, with daughters increasingly able to control their own partnership decisions. Behavioral ecologists have also highlighted the ways that an adaptationist perspective can usefully inform climate change policy by emphasizing relationships between risk and innovation, examining ways that people maintain access to resources in the face of changing ecologies, and uncovering how social networks foster and transmit adaptations (Pisor and Jones 2021). Given that globalization is increasing the pace and scope of change, HBE should continue to have an important role in studies of human behavior around the world.

https://doi.org/10.1017/9781108377911.002 Published online by Cambridge University Press

2

Life History Michael D. Gurven

2.1

Introduction A life history describes the timing and duration of key demographic events – like gestation, birth, reproduction, and death – and also rates of physiological processes such as growth, development, and aging (Figure 2.1). All species’ life histories are unique, and so what does it mean to reflect upon the uniqueness of our own species? Humans are indeed curious creatures. We have big brains and develop slowly with a long juvenile period with novel stages of childhood and adolescence. We live long postreproductive life spans and cooperate extensively in a multigenerational network, whereby kin and nonkin help subsidize female reproduction (see Chapters 5, 6, 12, and 13). Biparental care, and aid from grandparents, adult siblings, other kin, and neighbors are vital. Human children soak up information from others and creatively adapt and innovate new cultures and technologies. Learning and skill development, combined with cooperative acquisition and distribution, enables complex subsistence strategies targeting high-quality, nutrient-dense foods. This bundle of demographic and socioeconomic traits comprises the Human Adaptive Complex (Kaplan et al. 2010), whose origin, maintenance, and variable expression has generated much discussion and controversy, and a growing body of empirical studies. Theories that are too human-specific may be criticized for their limited generalizability or utility in the biological sciences, in the same way that defining culture to include language and other human traits limits the ability to ever study culture in nonhumans. One way of defining uniqueness is to compare traits among species with shared phylogenetic history. Humans are mammals, primates, and hominins. So we can ask how the life history of humans differs from that of other mammals, primates, and hominins. Comparisons with our nearest relatives, wild chimpanzees and bonobos, offer important insights, as these are believed to have a life history similar to our last common ancestor from 7–10 million years ago (Wrangham 1987). Compared to humans, our chimpanzee cousins have shorter lives, smaller brains, and bodies that grow and develop more rapidly. Another approach is to assess whether human traits are outside the range expected for a comparably sized mammal or primate. Given allometric (or scaling) relationships of many physiological processes and traits with body size, we can assess uniqueness by taking our speciestypical body size into account. This chapter introduces life history theory (LHT) and applies it to understanding the evolution of the human life course. The perspective I take serves to illustrate the

https://doi.org/10.1017/9781108377911.003 Published online by Cambridge University Press

Life History

21

TSIMANE 0.75 1.5

gestation

weaning

14

19

IBI=2.2

ACHÉ gestation weaning

48

First menses

13

First menses

TFR=9 IBI=3.2

18

e0=43

e15=41

e40=24

e0=37

e15=43

e40=25

80

last menses

First birth

0.74 2.1

39

last birth

42

~50

75

last menses

First birth

TFR=8

last birth

CHIMPANZEES 0.63

gestation

4.8

14

18

IBI=6.6

weaning First menses

First birth

TFR=3.5

43 45

e0=15

e15=15

e40=6

last last menses birth

Figure 2.1 Comparative life histories of humans and chimpanzees. Aché data from Hill and

Hurtado (1996), Tsimane data from Gurven et al. (2007). Chimpanzee mortality data from Gurven and Gomes (2017). Maximum life span is defined as age X, where survivorship LX = 0.05.

broad utility of a life history framework for studying human variability, and so cannot possibly cover all areas of study. Section 2.2 reviews the history of LHT in the evolutionary social sciences. Section 2.3 synthesizes theoretical and empirical approaches toward understanding the Human Adaptive Complex, focusing primarily here on postreproductive life span. Section 2.4 discusses applications of LHT to understanding variation among humans, focusing on demographic, physiological, and psychological traits. Finally, Section 2.5 highlights several unresolved issues and future directions.

2.2

Life History Theory as a Theoretical Framework

2.2.1

What Is Life History Theory? Life history theory studies the diversity of life history “strategies” across species that have been shaped by natural selection. While core ideas of life history theory can be traced back to Darwin and R. A. Fisher, Lamont Cole’s 1954 paper “The population consequences of life history phenomena” presented the first mathematical formulation for evaluating fitness consequences of variation in life history traits. LHT soon developed largely from evolutionary biology and population ecology (see Roff (1993)

https://doi.org/10.1017/9781108377911.003 Published online by Cambridge University Press

22

Michael D. Gurven

Figure 2.2 The human life cycle. Infancy, childhood, adolescence, adulthood, grandparenthood. Central to the evolved human life history is the transfer of food, aid, information, and other resources within and among generations. Photos credit: Michael Gurven.

and Stearns (1992)), with human applications appearing by the 1980s. Life history strategies reflect the timing and duration of key life cycle components that can affect biological fitness. The life cycle includes gestation, birth, juvenility, maturation, reproduction, senescence, and death (Figure 2.2). Related traits derived from this cycle include size at birth and at sexual maturity, adult life span, number and size of offspring, and length of interbirth intervals. The idea of an optimal life history is best illustrated by considering the hypothetical “Darwinian Demon” – an organism that reproduces immediately after being born, then produces unlimited offspring over an infinitely long life span. That no such organism could exist confirms the inability to maximize all fitness components simultaneously, and the importance of trade-offs given limited time, effort, and energy. Energy allocated to one function cannot be spent on others, and hence the optimal allocations among growth, reproduction, and maintenance functions favored by natural selection result in a species’ life history (Figure 2.3). A major trade-off early in life is between growth and reproduction, where growth affects future production, reproduction, and survival. Another way to frame this trade-off is between current and future reproduction, often identified as the cost of reproduction (see Section 2.4.3). In general, this trade-off results in greater reproductive effort with

https://doi.org/10.1017/9781108377911.003 Published online by Cambridge University Press

Life History IgG Acute Phase

IgA

IgM

TH1

23

IgE

CD8+ Complement

TH2

Phagocytosis

B cells

CD4+

Non-specific

Cell Mediated

Repair

Offspring Production

Parental Care

Humoral

Immune Defense

Maintenance

Muscle

Adipose

Height Parental Investment

Mating Effort

Reproduction

Weight

Organs, Brain, Etc.

Growth and Development

Figure 2.3 Life history trade-offs. Energy is allocated to somatic growth and development,

reproduction, and somatic maintenance. Each of these three macro-categories contains multiple suballocation decisions. Adapted from Blackwell (2009).

age among adults, as the diminishing shadow of the future reduces the cost of reproduction (this idea has been called the terminal investment hypothesis). While trade-offs in the face of energetic limitation represent the bread and butter of LHT, empirical evaluation of trade-offs can be tricky if individuals vary in budget size and other constraints, a problem often identified as “phenotypic correlation” (see Box 2.1). One of the fundamental insights of LHT is that mortality is the prime sculptor of life history pace and investments. More precisely, exogenous mortality – that is, deaths due to age- and condition-independent causes – affects trade-offs between present and future decisions and consequences. Although the concept of exogenous mortality may be problematic due to its unrealistic partitioning of causes of death, its heuristic value permits a convenient starting point for modeling trait evolution. High exogenous mortality puts a premium on stopping or accelerating growth, earlier reproduction, and less maintenance (i.e., more rapid aging and shorter life span). Low exogenous mortality promotes slower growth and larger body size (when fecundity is size-dependent), slower aging due to higher investments in maintenance, and hence longer life span. This chief insight, often credited to Williams (1957), is usually stated as a universal principle rather than as a prediction specific

https://doi.org/10.1017/9781108377911.003 Published online by Cambridge University Press

24

Michael D. Gurven

Box 2.1

Challenge of Phenotypic Correlations

1.0 0.5

lnTFR

1.5

2.0

An ideal way to assess a life history trade-off is to experimentally induce a change in one phenotypic trait, and/or in energy budgets, and measure a causal response in the focal trait of interest. However, randomized sample selection and experimental manipulation are practically, and often ethically, difficult obstacles when working with humans. Many human studies instead use cross-sectional, observational designs. While convenient, these usually lack the ability to make strong causal inferences and are fraught with “phenotypic correlations” (referred to as self-selection or endogeneity in other disciplines). For example, individuals in better condition may both live longer and can afford to support more children, resulting in a spurious positive relationship between survivorship and fertility, instead of the negative trade-off suggested by the cost of reproduction. Alternatively, a predicted inverse relationship may be revealed by such analysis, but may not reflect actual trade-offs. Figure B2.1.1 shows the expected inverse relationship between total fertility rate (TFR) and life expectancy (e0) across 183 countries. However, countries with high e0 are wealthier, and a country’s wealth reflects higherquality investments in schooling and fewer children. The “true” relationship between fertility and life expectancy is thus confounded by wealth and other factors. One method for handling phenotypic correlations involves using multivariate statistics to adjust for the self-selected differences in condition. In the example previously, we can add covariates that might otherwise account for a potentially spurious relationship between e0 and TFR. Including per capita

50

55

60

65

70

75

80

85

Life Expectancy, e 0

Figure B2.1.1 Relationship between total fertility rate (TFR) and life expectancy (e0) in 183 countries. Data source: Human Development Report 2015.

https://doi.org/10.1017/9781108377911.003 Published online by Cambridge University Press

Life History

25

Table B2.1.1 Regression of fertility (lnTFR) on life expectancy (e0). Variables included in regression e0 +ln GNP +ln GNP, ln MMR +ln GNP, ln MMR, education index +ln GNP, ln MMR, education index, Gini index

b (for e0) Std. β 0.046 0.031 0.018 0.017 0.011

0.82 0.55 0.32 0.30 0.20

p

Adj R2

50

Age category

Figure 9.3 Informal relationships among Himba pastoralists. Informal (nonmarital) partnerships

are common and relatively unstigmatized among Himba living in northwest Namibia. Unlike stereotypes of “short-term” mating, these relationships are long-lasting and constitute important reproductive and social links. (A) Informal relationships are similar in longevity to formal (marital) ones. In the oldest age set, both formal and informal partnerships have lasted on average 20 years, with some informal partnerships having lasted more than 40 years. (B) Many informal partnerships produce children. These data show the proportion of current informal partnerships that have resulted in at least one child.

or at least less formalized, in informal relationships. Another feature that tends to distinguish formal and informal partnerships is their level of social recognition and the involvement of people other than the couple themselves, most often their families. These differences can have considerable impact on partnership dynamics and partner choice (Apostolou 2007), though they have received much less attention than the temporal distinction between short- and long-term relationships.

9.4.3

Serial Monogamy and “Trading-Up” In many societies, it is typical for individuals to have more than one sexual partner across their life span, either via divorce and remarriage or through premarital and intermarital partnerships. This is more often true for men than women, for whom rules regarding divorce and nonmarital sex are often stricter (Betzig 1989), but even

https://doi.org/10.1017/9781108377911.010 Published online by Cambridge University Press

Mating

219

with these differences, it is not uncommon for women to have more than one lifetime partner (Scelza 2013). Given this, decisions about partnership length and number are highly relevant to thinking about human mating psychology and behavior. Behavioral ecologists have studied the fitness consequences of sequential partnerships across species. A meta-analysis of 64 socially monogamous bird species showed that individuals were more likely to switch partners when breeding success was low and that breeding success was likely to rise in the new partnership (Culina et al.2015). This indicates a strategy of “trading-up.” For example, in an experimental mate-removal study, black-capped chickadees favored new mates who were highly ranked and who were dominant to their previous ones (Otter and Ratcliffe 1996). Extending this idea to humans, Buss and colleagues recently introduced the “mate switching hypothesis,” which proposes a suite of psychological and behavioral adaptations that can facilitate and optimize serial monogamy (Buss et al. 2017). These include the cultivation of “back-up mates” and assessing the relative values of self and mate. The proposed value of “trading-up” is that it reduces some of the costs that would be associated with divorce and remarriage by allowing for a trial period before deciding to desert the current partner and eliminating some of the costs of reentering the mating market. However, studies of “trading-up” come almost exclusively from studies of college students, whose relationships are not necessarily representative of long-term unions (Goetz et al. 2019). One exception is a study of Pimbwe marriage patterns, which has shown that women with more spouses have greater reproductive success (Borgerhoff Mulder and Ross 2019), and in a related paper, Borgerhoff Mulder (2009) explains that this may be attributed to “trading-up” as women tend to divorce their husbands when they experience hard times, as a strategy to buffer themselves against unpredictability in male support. Who benefits from partner switching is also the subject of debate. In line with Bateman’s contention that males will generally gain more from multiple mating than females, serial monogamy is often predicted to increase the reproductive success of men more than women. Proximate pathways for this in humans include the increased likelihood that a man will remarry a younger woman of higher reproductive value, as well as differential investments in the children of previous unions that could allow men to mate switch with fewer costs. Some studies have demonstrated these effects. Jokela and colleagues show that US men, but not women, with more spouses had more children (Jokela et al. 2010), and similar results were found in a historical Finnish population (Pettay et al. 2014). But among Pimbwe, described previously, while women with more spouses have greater reproductive success, men show the opposite pattern (Borgerhoff Mulder and Ross 2019). This finding mirrors studies in the animal literature, which have also shown females to benefit more from partner switching than males (Culina et al. 2015).

9.5

Paternity and Fidelity The range of partnerships that have been described previously relate to a prominent conundrum in studies of human mating: how to distinguish between the social and

https://doi.org/10.1017/9781108377911.010 Published online by Cambridge University Press

220

Brooke A. Scelza

the genetic mating systems. The social mating system is that which we can easily see, and which is recorded in social norms and practices. Monogamous marriage, for example, is the social mating system in the United States. How well the social mating system aligns with the genetic mating system is a function of how often children are born outside of wedlock, or through extra-pair liaisons. Most studies within human behavioral ecology focus on the social mating system, often labeling societies as “monogamous” or “polygynous.” Gathering genetic paternity data is ethically and logistically challenging, and often it cannot be accomplished without harming the communities we work with (Scelza et al. 2020a). However, increasingly, there is interest in understanding how more covert strategies occur within socially sanctioned mating systems; in other words, how the social and genetic mating systems might differ, and why. The frequency of nonmarital births is still widely debated and reflects a number of factors, including the frequency of premarital and extramarital sex, norms about assigning paternity, and the degree of social recognition of children born outside of marriage (Figure 9.4). Data from the Standard Cross-Cultural Sample on premarital sex shows that while there is great variation, from cultures that are entirely permissive to those that restrict any and all sexual activity before marriage, the practice is common for women in the majority of societies (Broude and Greene 1976). Births resulting from these relationships can be treated any number of ways, including by

Percent of societies

Pre-marital sex 50

Men

40

Women

30 20 10 0

Universal

Moderate

Occasional

Uncommon

Percent of societies

Extra-marital sex 50 40 30 20 10 0

Universal

Moderate

Occasional

Uncommon

Figure 9.4 Cross-cultural rates of premarital and extramarital sex. Both premarital and

extramarital sex were common for both men and women across cultures. While premarital sex is more common than extramarital sex, the latter is still found at either universal or moderate rates for both men and women in more than half of societies reporting. Data are from the Standard Cross-Cultural Sample (SCCS) as coded by Broude and Greene (1976).

https://doi.org/10.1017/9781108377911.010 Published online by Cambridge University Press

Mating

221

marrying the father before the child is born, assigning lineal recognition to the mother’s father, or categorizing the child as being “fatherless.” How paternity is assigned is a matter of local social convention, but it has direct implications for how well the social and genetic mating systems will align. Extramarital sex is less common and more likely to be prohibited than premarital sex (Broude and Greene 1976). Because of this, it is more difficult to quantify the frequency of extra-pair births. Most anthropologists and demographers ask only about marital and premarital births, not about paternity per se, and birth registries tend to report mother’s legal husband as the father. Despite a dearth of quantitative data, it is widely assumed that in most cases the rate of extra-pair paternity in humans is quite low (around 1–2%) (Larmuseau et al. 2016). There are exceptions, however. In a cross-cultural examination of paternity, Anderson (2006) finds a similarly low rate of extra-pair paternity in settings where paternity confidence is high, but also cites cases where it is purported to be much higher. Among Himba pastoralists living in northern Namibia, almost half of children born into marriages are fathered by someone other than the husband, with as many as 70% of couples having at least one child who is extra-pair (Scelza et al. 2020b). These data indicate that there may be greater variation in extra-pair paternity (EPP) than previously assumed, but to understand the true diversity in EPP, we need more genetic data, and we need studies from a range of populations that reflect the variation in extramarital sex. One of the major reasons human behavioral ecologists care about EPP is because it is believed to impact patterns of investment (see also Chapter 11). Across species, there is evidence that males adjust their care based on cues of paternity (Dixon et al. 1994; Sheldon and Ellegren 1998; Neff 2003). But this is not always the case. For example, in a study of more than 50 bird species, males tended to titrate their investment in some domains like provisioning, but not in others like nest-building and incubation periods (Møller and Birkhead 1993). In humans, we see similar variation in the ways men respond to uncertainty with their paternal investment. The notion of men being “cuckolded,” tricked into investing in another man’s child, continues to be prominent within evolutionary psychology (Wilson and Daly 1995; Geary 2006; Platek and Shackelford 2006), but, in fact, there is important variation in the ways in which social and biological fatherhood are identified and treated. For example, men are predicted to have stronger preferences for chastity and fidelity in women (Buss and Schmitt 1993) and to be more upset by sexual infidelity than emotional infidelity (Buss et al. 1992). However, when the focus is on the similarities in male behavior, much of the nuance in behavior is underappreciated (Box 9.2). There are examples of societies where women have a high degree of sexual autonomy, nonmarital births are common, and men are accepting of non-biological children. This can occur through formal polyandry, where men are expected to invest in all children born to the family (Levine 1980) or through more informal systems, including societies that practice partible paternity, the belief that more than one man can contribute to conception. Here, men appear to be participating in the system by encouraging their wives to have sex with specific male kin and friends as a way of

https://doi.org/10.1017/9781108377911.010 Published online by Cambridge University Press

222

Brooke A. Scelza

Box 9.2

When Are Three “Fathers” Better than One?

One important consequence of seeing the variation in human fidelity is that it triggered a rethinking of conventional notions of female choice and the benefits that women could accrue by having multiple concurrent partners (Starkweather and Hames 2012; Scelza 2013). This change was inspired in large part by findings in the nonhuman literature. With the advent of DNA fingerprinting, a revolution in our understanding of social versus genetic monogamy caused scientists to reevaluate the potential benefits of multiple mating for females (remember that benefits to multiple mating in males are less controversial and less theoretically interesting). Social monogamy and biparental care are more common among birds than any other class of vertebrates, leading scientists to believe that genetic monogamy in birds was generally high. But genetic testing revealed that most socially monogamous birds exhibited at least some EPP (Griffith et al. 2002; Brouwer and Griffith 2019). These findings led to a series of influential papers discussing the possible benefits to females of having multiple partners (Jennions and Petrie 2000; Zeh and Zeh 2001). Across species, females who choose to have multiple partners have been shown to have higher fertility and greater offspring viability (Newcomer et al. 1999). Explanations for these results have been lumped into two groups: genetic and nongenetic. In other species, the material (nongenetic) benefits of polyandry became known first and include everything from a greater supply of sperm to extra paternal care to nuptial gifts (Fedorka and Mousseau 2002). With the advent of DNA fingerprinting, it was later discovered that genetic benefits can accrue if females are either able to mate with a higher-quality partner than their current social mate, or mate with multiple males across time to increase heterogeneity in their offspring (Petrie and Kempenaers 1998; Zeh and Zeh 2001). In humans, the same two categories of benefits have been considered; however, as of yet, there are no clear answers as to when, how, and how much women benefit from polyandry (Table B9.2.1). Walker et al. (2010) hypothesize that there are several potential benefits to female multiple mating, some of which benefit women, others men, and some of which are mutually beneficial. In terms of material benefits, some of the strongest evidence comes from studies of partible paternity in South America. In these groups, it is permissible for women to have more than one concurrent partner, and children are assigned primary and secondary fathers. Among both the Aché and Bari, children with more than one assigned father have greater survival to age 15 than those with only a single father (Hill and Hurtado 1996; Beckerman et al. 1998). Other studies have also shown that women who have multiple partners have better access to resources. Himba women who are married with at least one concurrent partner have greater food security than women with a

https://doi.org/10.1017/9781108377911.010 Published online by Cambridge University Press

https://doi.org/10.1017/9781108377911.010 Published online by Cambridge University Press

Table B9.2.1 Potential benefits of female multiple mating in humans. Strategy

Benefits for Women

Theoretical References

Evidence for Hypothesis

Evidence against Hypothesis

Dual Mating

Women gain from having longterm partners who are “good investors” and short-term partners with “good genes”

Gangestad and Simpson (2000), Pillsworth and Haselton (2006)

Trading-Up

Woman utilize short-term relationships as a way to evaluate men’s potential as long-term partners, especially in comparison with their current partner Resources from multiple men can provide either supplementary or complementary support for women and their children

Halliday (1983); Jennions and Petrie (2000); Buss et al. 2017

Japan/Britain: Penton-Voak et al. 1999 United States: Pillsworth and Haselton (2006); Larson et al. (2013) U.S.: Greiling and Buss (2000); Bzostek et al. (2012); Pimbwe: Borgerhoff Mulder et al. (2019) Aché: Hill and Hurtado (1996)

Poland: Marcinkowska et al. 2016 United States/Germany: Jünger et al. 2018 Himba: Scelza and Prall (2018) Canela: Crocker and Crocker (2004)

Multiple Investors

Hrdy (2000); Walker et al. (2010)

Aché: Hill and Hurtado (1996); Ellsworth et al. (2014) Bari: Beckerman et al. (1998) tbl_ch9_1 Scelza and Prall (2018); Scelza and Prall (2023) Inuit: Guemple (1986) Pimbwe: Kasper and Borgerhoff Mulder (2015)

224

Brooke A. Scelza

husband and no other partner, and this is attributed to gifts of food and cash that come from romantic partners (Scelza et al. 2021). The genetic benefits of polyandry for women are less well understood. As mentioned earlier, it is possible that women might benefit from a dualmating strategy, where they look for a long-term partner who will be a reliable provider and partner while also seeking short-term partnerships with men of high “genetic quality.” However, in addition to the methodological shortcomings already mentioned, dual-mating theory rests on a number of other assumptions that are not well studied, especially outside of WEIRD contexts. First, there is the presumption that men with “good genes” and men who are “good partners” form two distinct groups. Second, it is unclear what genes specifically women might be seeking. Major histocompatibility complex (MHC) studies, which posit that women will seek partners who are dissimilar to them in areas of the genome linked to adaptive immune function, so far are equivocal (Havlíˇcek et al. 2020), and other studies rely on only proxy measures of genetic quality, like measures of masculinity and facial symmetry. To better understand the potential genetic benefits of polyandry, there is a need for more diverse study populations and multimodal datasets that combine genetic, ethnographic, and demographic data.

cementing alliances (Walker et al. 2010). In societies where children have great economic importance, men have also been shown to tolerate, and even fight to keep, non-biological children in order to maintain their labor for the household (Bledsoe 1980; Prall and Scelza 2020b).

9.6

Mechanisms for Mate Retention While the extent and range of extra-pair paternity in humans is still unclear, extrapair partnerships have been, and continue to be, a part of the human mating system. However, the fact that they are “extra-pair” implies that they occur within the context of other, often long-term partnerships. This co-occurrence means that both men and women should be motivated to minimize defection from the partnership and to strive to outcompete those a partner might defect with. Physical and psychological mechanisms for “mate guarding” are phylogenetically old, occurring in most species with stable breeding bonds, and humans are no exception. In most cases, research on mate guarding has tended to focus on male mate guarding, and coevolutionary responses by females to subvert those efforts. This is because when weighing the costs and benefits of mate guarding, males must worry about both a loss of paternity and the loss of a partner, whereas for females, only the latter is of concern. This bias exists in the human literature, too, but given the importance of men’s roles in the human family, women also have a lot to protect. Section 9.6.1 addresses research on mate guarding in both genders.

https://doi.org/10.1017/9781108377911.010 Published online by Cambridge University Press

Mating

9.6.1

225

Physical Mechanisms Restrictions on women’s sexuality are well known, to the point that some evolutionary scholars have claimed that such constraints are a human universal (Daly and Wilson 1983:295). In general, these restrictions focus on reducing women’s choice and agency, either by limiting their mobility and autonomy or by increasing aggression toward male interlopers. Often, this is done through cultural practices like purdah (seclusion of women through either physical segregation or body coverings) and female genital modification, which have been well documented by cultural anthropologists. Restrictions on mobility also occur, either by physically limiting women’s movements or by enlisting kin or other institutional entities to keep women under watch when they are outside the home. The findings of human behavioral ecologists on this issue largely conform with those of cultural anthropologists, with both groups viewing these practices as a form of sexual control. Prominent examples within HBE include Flinn’s (1988) study of conflicts among men in Trinidad, where he shows that daughter guarding behaviors are associated with a woman’s reproductive potential, and Dickemann’s (1981) study of purdah, which showed that practices restricting women’s autonomy are more common in highly stratified societies, as these are places with a dearth of high-status men, and therefore intense competition among women and their families for access to them. More recently, Ross et al. (2016) showed that the origins of female genital modification may be linked to social hierarchy where there is more competition among brides for higherstatus men. In addition to preventing extramarital sex, physical mechanisms can also be used to detect extra-pair paternity after it has occurred. For example, in a study of the use and function of menstrual huts among Dogon, Strassmann (1992) finds that the huts are used as a way to broadcast women’s reproductive status to husbands and affines, allowing them to detect nonpaternity events. Because the use of menstrual huts occurs in conjunction with a suite of other norms that sanction both infidelity and lying about menstrual timing (i.e., misuse of the menstrual hut), men are able to rely on the huts for useful information about paternity. Women in this case are coerced into following the practice because the costs of lying are higher than the benefits that can be gained through infidelity. Women also have high incentives to maintain long-term partnerships and prevent their partners from leaving or diverting resources to other women. Evolutionary psychologists have posited that women’s tactics will be more subtle and indirect, given that in many societies women do not have the same level of societal control as men, and therefore have been unable to enact institutionalized forms of mate guarding or restrict men’s mobility (Krems et al. 2016). There is some evidence that men and women differ in the kinds of strategies they enact. In one study, women were shown to pay more attention to their rivals, whereas men focused more on their partners and whether they were showing signs of straying (Ein-Dor et al. 2015). Finally, not all mechanisms of mate retention are negative deterrents. Buss (1988) created the Mate Retention Inventory, which lists 104 mate retention acts,

https://doi.org/10.1017/9781108377911.010 Published online by Cambridge University Press

226

Brooke A. Scelza

divided into 19 general tactics. These were initially designed to understand college undergraduates, but the general categories reflect much of the behavior discussed earlier, including vigilance, mate concealment, and signals of possession or control. However, Buss also lists positive inducements like the purchase of gifts, enhancement of physical appearance, and maintaining a strong sexual relationship. Sprecher (2002) found that sexual satisfaction among premarital couples was positively associated over time with overall relationship satisfaction and commitment.

9.6.2

Psychological Mechanisms Underlying many “mate guarding” behaviors are aspects of our psychology that help us to maintain vigilance, deter defection, and increase partnership stability. Chief among these is jealousy. Most evolutionary studies of jealousy have focused on a sex difference in the ways that men and women respond to threats of infidelity, reflecting the different adaptive problems that they face (Daly et al. 1982; Buss et al. 1992). Men, who face the risk of paternity uncertainty and potential misallocation of parental investment, are expected to be more upset than women by the threat of sexual infidelity, while women, who risk the diversion of critical resources for themselves and their children if their partner is unfaithful, are expected to be more upset by the idea of emotional infidelity. There have now been robust replications of this effect, leading to presumptions of universality. However, there is considerable variation in the extent to which jealousy is expressed across cultures, as well as the magnitude of the sex difference. In a large cross-cultural study, human behavioral ecologists examined this variation (Figure 9.5). Some variation could be attributed to individual differences, like age and marital status, but, more interestingly, the study showed that in places where assessments of paternal investment were higher, jealous response was more severe (Scelza et al. 2020c). Behavioral ecologists have also studied the manifestations of jealousy on partnership behaviors. Among Tsimane, researchers show that marital arguments center on women’s jealousy over husband’s infidelity, but that events of spousal abuse occur mainly over disputes about the diversion of resources. From these findings, they posit that men are using intimate partner violence as a way to limit their wives’ attempts to restrain their own extra-pair partnerships (Stieglitz et al. 2012). As with the physical mechanisms for mate retention, psychological mechanisms extend beyond jealousy, and can also include positive inducements to maintain fidelity. For example, in his Mate Retention Inventory, Buss (1988) includes emphasizing the positive affect of the relationship (e.g., telling your partner you love them) and flattering behaviors (e.g., complimenting your partner’s appearance) as possible strategies. In a study conducted in Spain, the most frequently used mate retention tactic was the “use of love and care” for both men and women, and those in more committed relationships were more likely to engage in these behaviors (de Miguel and Buss 2011).

https://doi.org/10.1017/9781108377911.010 Published online by Cambridge University Press

Mating

(A)

Female Emotional Infidelity

Female Sexual Infidelity

Male Emotional Infidelity

227

Male Sexual Infidelity

P(PI | Response)

1.00

0.75

0.50

0.25

0.00 −1

0

1

−1

0

1

−1

0

1

−1

0

1

Provisioning

(B)

Female Emotional Infidelity

Female Sexual Infidelity

Male Emotional Infidelity

−1

−1

Male Sexual Infidelity

P(PI | Response)

1.00

0.75

0.50

0.25

0.00 −1

0

1

2

0

1

2

0

1

2

−1

0

1

2

Direct Care Very bad

Bad

Ok

Good

Very good

Figure 9.5 Jealousy and Paternal Investment. The level of paternal investment in a society predicts

the severity of people’s responses to infidelity. Here, we look at two types of paternal investment: (A) provisioning and (B) direct care. Posterior predictions (posterior median and 90% credible intervals shown) show that as both forms of investment increase, the conditional probability of a more severe jealous response also increases. The effects are stronger for responses to sexual infidelity than emotional infidelity. Note that the color key corresponds to the median predictions for the respective categories. “Good” and “Very good” responses are rare, and their prediction intervals overlap. The ordered logistic models are adapted from data in Scelza et al. (2020).

9.7

Future Directions Evolutionary studies of human mating continue to be dominated by evolutionary psychologists rather than human behavioral ecologists. This is puzzling in that

https://doi.org/10.1017/9781108377911.010 Published online by Cambridge University Press

228

Brooke A. Scelza

questions of reproductive decision-making have long been viewed as an essential part of HBE, both because they have direct impacts on fitness and because reproduction is so intimately tied to other aspects of our behavior, culture, and social structure. The trend continues even amid significant shifts within HBE toward more studies focused on reproduction (Nettle et al. 2013). Life history theory is regularly used within HBE to understand questions related to parental investment and trade-offs between reproduction, growth, and maintenance (Chapter 2), and studies of marriage and marriage systems have long been a staple (Borgerhoff Mulder 1992a; Chapter 10). But studies of mate choice, or, more broadly, how and why partnerships form and persist, continue to be rare. I have tried to highlight work that has been done in these areas in this chapter, but I would argue that HBE’s relative absence in the study of human mating has had some detrimental effects, and increased attention to this topic would greatly improve our understanding of the adaptive (and sometimes maladaptive) nature of sexual partnerships. First, more than any other part of evolutionary anthropology, human mating studies are beset by a predominance of WEIRD samples (Western, Educated, Industrialized, Rich, and Democratic) (Henrich et al. 2010). In a recent review of studies of human mating in two major disciplinary journals, 81% of samples were found to come from western populations, and 70% were from online or student samples (Pollet and Saxton 2019). WEIRD studies of human mating are especially problematic because university students are particularly mismatched with the types of partnerships that are seen in broader society, both now and throughout human history. Goetz et al. (2019) identify several examples of how students tend to differ, including being more likely to be young, nulliparous, more autonomous in their mating decisions, more likely to be in temporary relationships, and with access to a much larger pool of potential partners due to their use of social media. However, it is not enough just to shift focus from WEIRD to non-WEIRD samples. Simple, binary comparisons of WEIRD and non-WEIRD populations can challenge claims of universality, but they are not nearly as useful, or as interesting, as cross-cultural work that aims to understand and predict underlying variation. Human behavioral ecologists are particularly well-equipped to take on these kinds of studies because they routinely blend ethnographic, demographic, and observational data. Second, HBE has great potential to answer questions about human mating that are missing from the current corpus. Most evolutionary psychology studies rely on hypotheticals and proxies to understand partner preferences. Where “real” relationships are studied, these are mostly among unmarried university students, whose dating lives occur within a very particular context, and even then the focus tends to be on self-reported measures of attraction and affect, and usually only from one member of the pair. These kinds of studies are insufficient for addressing the next generation of questions in evolutionary studies of human mating: How do partner preferences map onto actual partnership formation? How do characteristics like partner similarity and compatibility affect partnership stability, and do these characteristics have more or less robust effects across environments? What direction is

https://doi.org/10.1017/9781108377911.010 Published online by Cambridge University Press

Mating

229

the causal arrow between partner similarity and partnership stability? As the size and shape of mating pools change, due to increased access to technology or loosening of rules about intergroup relationships, how do partnership dynamics (e.g., number of partners, desirability of particular traits) shift? Both the theoretical and methodological aspects of HBE will be useful for addressing these questions. The fact that behavioral ecologists tend to have long-term fieldsites opens up the possibility for longitudinal partnership studies that could look at issues of causality and stability, and the mix of observational, demographic, and ethnographic methods common within HBE allows for an integration of “bottom-up” descriptive and “top-down” theoretical projects that should provide a deeper understanding of human partnerships (Gurven 2020). Finally, despite decades of pushback, reductionist sexual stereotypes continue to plague evolutionary studies of human mating. Studies of “sex differences” are much more common than studies that examine individual variation based on age, reproductive status, wealth, or other traits. Studies of intra-sexual conflict continue to focus on men and male traits like masculinity and aggression despite the fact that humans have mutual mate choice and long-term partnerships that require sacrifice and vigilance from both parties to maintain. Behavioral ecology serves as a useful model for how we can challenge academic and popular understandings of conventional sex roles. Studies of other species have come a long way in identifying variation and contesting older models of sexual selection. We must view the diversity of human experience similarly. In fact, it is particularly important that we confront sexual stereotypes in human studies because we are human. The diverse and everchanging nature of culture, along with the diversity of environments in which humans live, means that human mating decisions are less likely to be stable and more likely to be diverse than in any other species. Our individual decisions are also taking place within increasingly complex institutional structures (such as online dating) and norms (e.g., “hook-up culture”) necessitating more integration between individual and cultural group levels of analysis. This puts an added responsibility on human behavioral ecologists to integrate their work with that of cultural anthropologists, demographers, economists, and sociologists. This integrated approach will accentuate, rather than dampen, the impact that HBE can have in answering questions about human mating.

https://doi.org/10.1017/9781108377911.010 Published online by Cambridge University Press

10 Marriage Mary K. Shenk

10.1

An Evolutionary Perspective on Marriage Marriage is an evolutionary puzzle. It is unique to our species and found across human societies, such that most researchers agree it is a universal, species-typical trait. Yet, marriage in human societies is also enormously variable in form and function, making it hard to define in a way that satisfies everyone. Human behavioral ecology (HBE) has existed as an intellectual tradition only since the 1970s, but it has older roots. The anthropological study of marriage begins with the unilineal evolutionists (Tylor, Morgan, Bachofen, Engels) who argued that marriage evolved from a state of promiscuity through a series of stages that finally arrived at the monogamous family. HBE, however, arguably owes more to the early tradition of resistance to this approach. For marriage, this begins with Edvard Westermarck, a Finnish sociologist and opponent of unilineal evolutionary thinking. Westermarck’s key texts (1891, 1936) were highly critical of many claims made by nineteenth-century writers, arguing that much of what they said about marriage was not based in fact: “After examining in detail all the cases which are known to me of peoples said to live in a state of promiscuity, I have arrived at the conclusion that it would be difficult to find a more untrustworthy collection of statements” (1936:16). By privileging empirical observation, including of small-scale societies, and applying Darwinian thinking to the topic of marriage, Westermarck began a tradition that continues in modern HBE.

10.1.1 How Is Marriage Distinct from Mating? Humans resemble many other animals in that they form pair-bonds, and human marriage likely evolved, at least in part, from ancestral primate patterns of pairbonding (Chapais 2008) such that the pair-bond is now a “ubiquitous feature” of human mating relationships (Schacht and Kramer 2019). Pair-bonds are often associated with socially monogamous mating systems in which the primary form of mating involves an enduring bond between one adult male and one adult female. This is not to suggest that pair-bonding species practice lifelong sexually exclusivity (genetic monogamy), however – and the same can be said of humans whether they are married monogamously or not (Beckerman and Valentine 2002; Scelza 2013). This distinction applies to many socially monogamous species, including numerous bird species that exhibit patterns of social monogamy

https://doi.org/10.1017/9781108377911.011 Published online by Cambridge University Press

Marriage

231

combined with occasional extra-pair mating. Compared to other socially monogamous birds and mammals, however, humans show relatively low rates of extra-pair paternity (Anderson 2006; Schacht and Kramer 2019), and most human reproduction occurs within marriage (Wood 1994). Yet there are no clear equivalents of marriage among nonhuman animals (Flinn and Low 1986; Chapais 2013). Indeed, many have argued that marriage is part of a unique modern human social structure involving multiple smaller family groups organized into larger social units in patterns that combine both relatives (consanguineal kin) and nonrelatives (especially affinal kin related through marriage) (Chapais 2008; Hill et al. 2011; Walker et al. 2011). While marriage generally (though not always) involves mating, it is driven by much more than having sex, or even reproduction. Pair-bonding has generally evolved in contexts where there are fitness benefits via either (a) investment in offspring by more than one parent, or (b) high levels of investment in mate defense/retention (Lukas and Clutton-Brock 2013). Human marriage takes these nonhuman patterns as a starting point and elaborates on them in diverse ways, though always serving one or more key evolutionary functions – mate acquisition, mate defense, reproduction, parental investment, resource acquisition/defense, or the acquisition/maintenance of social status. Thus, while marriage often involves mating, this is only one of its many functions – and one that is not equally important in all societies. Instead, the functions of marriage are much broader than mating, and deeply integrated in systems of subsistence, cooperation, and exchange as much as (if not more so) than in systems of reproduction. Marriage is also a fundamental social institution deeply bound up in, and coevolved with, systems of kinship, family, and inheritance. Indeed, some researchers argue that it is social acknowledgment from others (i.e., the blessing of the union in terms of local norms) that makes marriage most distinct from mating. As such, marriage provides one of the most compelling case studies for the entanglement of human biological and cultural evolution.

10.1.2 Is Marriage Adaptive? Is It an Adaptation? Most scientifically focused researchers have argued that marriage is universal because it is found in virtually all human societies past and present (Murdock 1949; Brown 1991; Harrell 1997; Coontz 2005), but is it solving the same adaptive problems cross-culturally? There are two answers to this question. First, some functions of marriage are universal (or nearly so), suggesting it is a species-typical adaptation; these include the facilitation of biparental care and the cementing of social linkages between kin groups through the creation of affines. Indeed, some have argued that the universality of marriage suggests a deep evolutionary history (Chapais 2008). Walker et al. (2011) reconstruct ancient marriage patterns using a phylogeny of contemporary hunter-gatherers based on mitochondrial DNA, and infer that several characteristics of present-day human marriage – including arranged marriage, low levels of polygyny (low reproductive skew), and reciprocal exchanges

https://doi.org/10.1017/9781108377911.011 Published online by Cambridge University Press

232

Mary K. Shenk

at marriage (bride-price or bride service) – likely date to first human migrations out of Africa. This lends credence to arguments that some aspects of marriage are examples of a species-wide adaptation. On the other hand, the many cross-culturally variable aspects of marriage – how many spouses one has, when one marries, whom one marries, who makes marriage decisions, where one lives after marriage, and how marriage is bound up in systems of resources, kinship, parental investment, and exchange – suggest that marriage systems are shaped by adaptive responses to local subsistence systems and environments through strategic decision-making in iterative feedback with processes of cultural evolution (Flinn and Low 1986). Marriage is thus both an adaptation – and also varies cross-culturally in ways that are locally adaptive. In order to unpack its adaptive aspects, I begin by discussing the diverse functions of marriage and then consider the major ecological dimensions of its variation.

10.2

The Functions of Marriage What are the major functions of marriage, how do they vary cross-culturally and ecologically, and what does it tell us about how and why marriage evolved? While a long list of marital functions has been identified and discussed in the anthropological literature (Leach 1955), a few functions stand out as being both common and having clear relevance for evolutionary explanations. While far from its only purpose, a key function of marriage in many societies is the regulation of mating, or legitimating sexual relationships and setting boundaries to reduce mate competition within and between groups. Indeed, Betzig (1989) found that infidelity was the most common cause of divorce in the Standard Cross-Cultural Sample (SCCS) (88/186 societies). As husbands and in-laws often invest in a wife’s children, there is concern that their investment is directed toward biological children, making paternity certainty (and thus sexual fidelity) a relevant consideration in many contexts (Schlegel 1991). Even in contexts where sex outside of marriage is allowed, there are generally social norms regulating who one’s extramarital partners can be and at what point in one’s marriage one can be involved with them in order to avoid conflict with one’s spouse (Beckerman and Valentine 2002; Scelza 2013). Relatedly, reproduction is a key function of marriage in many societies. Its importance is obvious from an evolutionary perspective, as reproduction is a primary currency of fitness, but children may also be economically valuable or socially important for other reasons – for example, agricultural labor (Kramer 2005a) or the recruitment of members to one’s kin network (Harrell 1997). Accordingly, infertility (and related problems) are also common cross-cultural reasons for divorce (75/186 societies in the SCCS; Betzig 1989). More than simply having children, though, marriage establishes the membership of children in kin networks and other social groups, which become conduits of resources, information, and help that they may rely on – and contribute to – for the rest of their lives. Concomitantly, marriage also establishes responsibility for a child with members of the child’s kin group. Although the specific adults charged

https://doi.org/10.1017/9781108377911.011 Published online by Cambridge University Press

Marriage

233

with parental or alloparental responsibilities vary across societies (Sear 2016; Chapters 11 and 12), the existence of such responsibilities is universal. Another central function of marriage is establishing or perpetuating a cooperative subsistence unit. This function, while not universal, is very common – and though there are other ways to establish subsistence units, marriage is often the basis for creating and perpetuating a household, the most frequent and fundamental unit of economic cooperation cross-culturally. Indeed, Murdock (1949) emphasized economic cooperation based on the sexual division of labor as the central reason for marriage. Many researchers have taken issue with this, pointing to the fact that households are not the primary economic unit in hunter-gatherer bands, Dayak longhouses, and collective kibbutzim. Yet, in some societies, HBE researchers have found that the household, organized around marriage, is a central economic unit (Gurven et al. 2009; Leonetti and Chabot-Hanowell 2011; Starkweather 2017), and that marriage generally provides economic benefits for spouses, as their labor is complementary (though these costs and benefits may not be equal). A related function of marriage is organizing and regulating inheritance and the transmission of property. Be it property such as land or symbolic resources such as offices, the right to inherit is generally ascribed by virtue of birth into a particular family and/or through a particular line of descent (Hartung 1976). In cases where valuable resources are inherited, moreover, there is generally more emphasis on the sociolegal customs formalizing marriage and on the notion of the legitimacy of children born within marriage (Goody 1976; Schlegel 1991). Finally, one of the most important functions of marriage is to forge or strengthen alliances between families, kin groups, or members of other social units; this is done both through the marriage itself and through the children that may come from the marriage. Indeed, influential thinkers have identified alliance formation as the central and most universal function of marriage (Lévi-Strauss 1949/1969; Chapais 2008). As historian of marriage Stephanie Coontz puts it, “You can have sex without marriage, you can have children without marriage, you can have social status without marriage . . . you cannot have in-laws without marriage” (Coontz 2005). Walker et al. (2011) find that arranged marriage, limited polygyny, and marriage transactions involving resources or labor are likely part of the ancestral marriage pattern of all modern humans that may have enhanced the “complexity of human meta-group structure with coalitions and alliances spanning across multiple residential communities” (p. 1). This type of system characterizes humans in the present and Lévi-Strauss (1949/1969) famously argued that the fundamental human social structure has marriage at its heart. Similarly, Salali et al. (2016) use data on transmission of medicinal knowledge among hunter-gatherers to suggest that “long-term pair-bonds, affinal kin recognition, exogamy, and multi-locality create ties between unrelated families” (p. 2516), which facilitates flows of information while Hill et al. (2011) argue that multifamily camps with low relatedness facilitate cooperative relationships with potential implications for the development of larger social structures. By creating durable bonds between families, clans, villages, or even kingdoms, marriage creates the foundation for human social structure and, arguably, for the

https://doi.org/10.1017/9781108377911.011 Published online by Cambridge University Press

234

Mary K. Shenk

evolution of modern human patterns of cognition and social learning that have been so central to the adaptability and success of our species (Chapais 2014).

10.3

Spouse Choice Evolutionary theories of mate choice (see also Chapter 9) have traditionally emphasized male competition and female choice, especially among mammals, in which relatively low-investing males compete over mating opportunities with highinvesting females (Trivers 1972). Yet, while humans retain the mammalian pattern of higher obligate parental investment by females (through gestation, lactation, and higher levels of direct care), human mate choice does not follow a simple pattern of female choice. Rather, mate choice is very often under the control of parents or other senior kin (Apostolou 2007, 2010; Buunk et al. 2008). Relatively unrestricted choice is common in contemporary Western societies, but has not been normative either historically or cross-culturally, especially when it comes to the crucial decision of a marriage partner, which has implications for resource access, sociopolitical connections, and status – not just for the spouses themselves but for their families, kin groups, and communities (Shenk 2017). Women have full control over spouse choice only in a minority of human societies, making “female choice” an inaccurate descriptor: marriage decisions are made by the bride alone in only 8% of SCCS societies (Figure 10.1A), while men fully control their own marriage decisions in only 31% of societies (Figure 10.1B). Instead, parental choice, or joint decision-making (in which parents/other kin cooperate with prospective spouses), much more commonly characterize marriage decisions (Figures 10.1A and 10.1B; Murdock 1949; Apostolou 2007, 2010; Shenk 2017), suggesting the pattern may have deep evolutionary origins (Apostolou 2007; Walker et al. 2011). This argument is supported by four lines of evidence. First, ethnographic evidence on marriage patterns of modern foragers indicates heavy involvement of parents in marital choice (Apostolou 2007). Second, analyses comparing human and nonhuman primate social systems suggests that the evolution of modern human social organization depended on both pair-bonding and alliances between kin groups (Chapais 2008, 2013). Third, phylogenetic evidence suggests that arranged marriage potentially dates to 50,000 years ago (Walker et al. 2011). Finally, evidence suggests that among humans, choosing one’s own spouse does not increase reproductive success (Sorokowski et al. 2017). Indeed, many scholars (Lévi-Strauss 1949/1969; Coontz 2005; Chapais 2008, 2013) have argued that the central function of marriage is to create and/or strengthen alliances between kin groups, suggesting that familial influence over marriage decisions may be central to the evolution of marriage itself. Moreover, while arranged marriage and parental decision-making are not universal, the capacity for them is, and departures from parental involvement occur primarily in circumstances where the costs of parental influence increase, the benefits to individual choice increase, or both – and individual choice of marriage partners is most common when children are economically independent of their parents. These patterns suggest that marital arrangement decisions are ecologically influenced, and that even strong patterns of

https://doi.org/10.1017/9781108377911.011 Published online by Cambridge University Press

(a) Individual Choice 7.9% 12

Arranged Marriage 45.0%

68

44

27

Parental Approval 29.1%

Choice and Arranged Are Alternatives 17.9%

(b)

Arranged Marriage 29.7%

Choice and Arranged Are Alternatives 18.2%

44

46

Individual Choice 31.1%

27 31 Parental Approval 20.9%

Figure 10.1 Prevalence of arranged marriage for women (A) and men (B) in the Standard Cross-

Cultural Sample. (A) Marriage Arrangements (Female); SCCS740; n = 151. (B) Marriage Arrangements (Male); SCCS739; n = 148. Note: Codes modified from original sources. Codes: Individual Choice. Individuals choose their own partners (consistent with Code 1 in original). Parental Approval. Individuals choose or suggest their own partners, but parental approval is either highly desire or required (replaces Codes 2 and 3 in original). Alternatives: Individual choice and arranged marriage are alternatives (consistent with Code 4 in original). Arranged Marriage: Parents choose partners. Includes codes for cases in in which individuals can object and/or cannot or rarely object to the choice (replaces Codes 5 and 6 in original). Sources: Broude and Greene (1983) and Kirby et al. (2016).

https://doi.org/10.1017/9781108377911.011 Published online by Cambridge University Press

236

Mary K. Shenk

parental control over marriage may erode under conditions of ecological change – such as when Ju/’hoansi foragers settled and were no longer reliant on foraging and groupwide food sharing but instead wage labor and government transfers (Wiessner 2009).

10.4

When to Marry Evolutionary researchers have been interested in age at marriage, given its relationship to life history strategies both within and across sexes. Husband-older marriage is nearly universal across human societies (Carmichael 2011; Conroy-Beam and Buss 2019). The size of the age gap varies, however, with gaps of 7.3 years in West Africa and 1 year in North America (Hertrich 2017). Cross-culturally, women are most often married in their late teens and early twenties with a slightly younger age at marriage in polygynous than monogamous societies (Shapiro and Gebreselassie 2014). Ages at marriage are later where women receive formal schooling (Carmichael 2011) and/or women’s marriages are dependent on inheritance or accumulation of property. Crossculturally, men most often marry in their twenties or early thirties, with notably older ages at marriage in polygynous than monogamous societies (Ember 1984). Men also marry later when their marriageability is dependent on property – e.g., saving for bridewealth, waiting to inherit a family farm, earning a self-supporting income. Evolutionary researchers generally interpret these differences through life history theory and the differing fitness trade-offs faced by men and women. Such trade-offs may be especially steep in humans, since we are cooperative breeders who often have multiple dependent children and rely on resources from others (Hrdy 2009, Chapter 12), some of which come from the spouses and in-laws whom women acquire through marriage. Since women have higher reproductive value when they are younger, they may have more bargaining power on the marriage market, and they or their parents may be motivated to deploy this to find a spouse with better skills, more wealth, or higher status. Men with such characteristics are on average older, since it generally takes time to accumulate skills or resources (Kaplan et al. 2000). This age gap is consistent with well-researched mate preferences (see Chapter 9, Buss 1989; Conroy-Beam and Buss 2019), suggesting a substantial evolutionary history. In terms of fitness outcomes, preference for a younger spouse may be related to preference for higher fertility (Buss et al. 2000), and several studies suggest that husband-older couples have more children (Fieder and Huber 2007; Helle et al. 2008). Yet practices and preferences may be mediated by socioecology. Spousal age gaps and preferences for older men are reduced with increases in female status and gender equality, especially in market economies (Eagly and Wood 1999; Carmichael 2011). Similarly, in post-demographic transition contexts where the emphasis is on intensive parental investment rather than high fertility, men often place less value on youth (Mace 1998; Lawson and Mace 2011). While all of this suggests that husband-older marriage may often serve the interests of both men and women, men may be the only beneficiaries if they exert

https://doi.org/10.1017/9781108377911.011 Published online by Cambridge University Press

Marriage

237

dominance in conflicts of interest and women are forced to accept the result. Lawson et al. (2021) test these two models with data from rural Tanzania and find no evidence for strong benefits or costs to women: women married older men than they preferred, but had better mental health and autonomy in husband-older households, suggesting a need for additional research.

10.5

Whom to Marry There are no human societies in which spouse choice is unrestricted. All societies have complex rules about whom one can, cannot, should, or should not marry. These rules are variable, yet also patterned across cultures, focusing on culturally salient social categories like kinship, lineage, class, caste, and gender, reinforcing the idea that a central function of marriage is cementing alliances between groups. van den Berghe and Barash (1977) and Fox (1980) argued that inclusive fitness and kin selection provide an evolutionary perspective on rules and norms regarding whom one should or should not marry.

10.5.1 Exogamy Rules of exogamy specify that a person must marry outside a family or group, whether marriage outside of the village in North India, clan exogamy in Kwakiutl communities in pre-contact British Columbia, or taboos against marrying siblings in most societies. Several functions have been proposed for exogamy, including inbreeding avoidance (Morgan 1877; Westermarck 1891; Fox 1980), securing beneficial alliances between family lineages or other groups (Lévi-Strauss 1949/1969; Flinn and Low 1986; Chapais 2013, 2014), and reducing competition and promoting social cohesion within and between families and descent groups (Tylor 1889; Durkheim 1912/1915; Malinowski 1927). One of the most widely discussed types of exogamy in HBE is the “incest taboo.” Incest taboos prohibit sexual relations and marriage between close relatives, and some form is found in all cultures (Fox 1980; Brown 1991). While there is crosscultural variation in the degree of relatedness considered to be incestual (Westermarck 1891), parents, children, and siblings are almost always taboo. From an evolutionary perspective, such taboos make excellent sense in discouraging mating between close kin that may lead to reduced fitness via inbreeding depression (Fox 1980; van den Berghe 1983). But this is a trickier problem in humans than in many other primates or mammals, since, unusually, both sexes are sometimes philopatric. This means that humans often live much of our lives in groups with both male and female kin – thus a mechanism is needed to avoid mating with close kin. Westermarck (1891) famously observed that people reared together during early childhood tend to avoid sexual contact with each other upon maturity, proposing that living in close proximity triggers an evolved aversion toward incest with close relatives. Westermarck’s idea contrasted with other contemporaneous

https://doi.org/10.1017/9781108377911.011 Published online by Cambridge University Press

238

Mary K. Shenk

perspectives on incest, which assumed that incest taboos were learned cultural norms – but Westermarck, a devotee of Darwin, argued that they were based on instinct, and thus natural rather than learned, with the implication that incest taboos were derived from biology rather than culture. Indeed, some evolutionary anthropologists and psychologists have argued that the phenomenon, labeled the “Westermarck effect,” may be an evolved psychological mechanism for inbreeding avoidance given human social structures (van den Berghe 1983). Given that inbreeding avoidance is common among primates and mammals, however, including through similar mechanisms (Pusey and Wolf 1996), it is plausible that the Westermarck effect could even be an ancestral, homologous trait rather than a derived trait specific to hominins. Tests of the Westermarck effect have tended to lend empirical support (Shepher 1971; Wolf 1985; Bevc and Silverman 2000; Walter and Buyske 2003, see also Lieberman and Symons 1998), though a recent review (Rantala and Marcinkowska 2011) concluded that the effect is relatively weak in humans. Thus, how important this effect may be in the evolution of modern human social systems – and specifically the incest taboo – remains an open question. Other than inbreeding avoidance, most arguments for the evolution of exogamy focus on the expansion of social connections to other groups – securing beneficial alliances, reducing competition among group members, and promoting social cohesion between groups. Chapais (2008, 2013, 2014) argues that humans evolved to retain ties with other foraging bands through exogamous marriage, a practice which helps modern humans create and perpetuate larger social entities. This work draws on a deep knowledge of primate behavioral ecology and social structure in combination with the work by Tylor (1889) and Lévi-Strauss (1949/1969), whose alliance theory put marriage at the heart of human social organization.

10.5.2 Endogamy Rules specifying that marriage must or should be within a particular group (the same caste in South Asia, the nobility in historical Europe), or norms of marrying people who share a similar status or identify (members of the same social class or religion in industrial societies) are examples of endogamy. Endogamy functions to keep wealth or hereditary status intact within families or social groups (Flinn and Low 1986) and to maintain group identity and boundaries (Lévi-Strauss 1949/1969). Individuals are also more compatible with each other than with outsiders, which may reduce the risk of marital dissolution (Betzig 1989). Consanguineous marriage, or simply consanguinity, is a common form of endogamy, most frequently taking the form of cousin marriage. Recently practiced by an estimated 10.4% of the world’s population (Bittles and Black 2010a), SCCS data (see Figure 10.2) indicates that over one-third of ethnographically known societies have a preference for cousin marriage, by far the most common type of kin endogamy cross-culturally (Murdock 1962–1971; Gray 1999; Kirby et al. 2016). While

https://doi.org/10.1017/9781108377911.011 Published online by Cambridge University Press

Marriage

61

No Preference 64.9%

239

Cousin Preference 35.1%

113

Figure 10.2 Prevalence of preference for cousin marriage in the Standard Cross-Cultural Sample

(Cousin Marriages Preferred; SCCS228). n = 174. Note: Codes modified from original sources. Cousins Preferred. Cousins of some type are preferred (Codes 1–14 in original). No Preference. There is no preference for cousin marriage (Code 15 in original). Sources: Gray (1999), Kirby et al. (2016), Murdock (1962–1971).

consanguinity has declined in many parts of the world alongside market integration, some rates remain as high as 20–50% (Bittles et al. 1991). For those interested in HBE, kin marriage is a fundamental form of endogamy, as it forms a marriage bond – with all of its related economic, reproductive, and social functions – between partners who also share genes and thus inclusive fitness motivations. This changes the evolutionary stakes surrounding marriage. There are risks to cousin marriage as a form of inbreeding, because deleterious recessive alleles are more likely to be expressed (Bittles and Black 2010a), yet these risks are not especially high among marriages between first or second cousins if they do not take place iteratively or in a closed population (Bittles and Black 2010a; Mobarak et al. 2013; Romdhane et al. 2019). Moreover, in societies where cousin marriage is customarily practiced, its social and economic benefits are often thought to outweigh its risks, especially when couples have high fertility (Bittles and Black 2010b; Bailey et al. 2014; Walker and Bailey 2014). Under what ecological circumstances do the benefits of marrying kin outweigh its costs? Cousin marriages may benefit individuals by allowing kin to limit the division of property and the sharing of assets with nonkin (Goody 1976; Harrell 1997; Obeyesekere 2008). Such marriages are found more commonly among agriculturalists and pastoralists, likely because heritable wealth, in animals or land, is central to both subsistence and status in these societies (Borgerhoff Mulder et al. 2010; Shenk

https://doi.org/10.1017/9781108377911.011 Published online by Cambridge University Press

240

Mary K. Shenk

et al. 2010). For example, Johow et al. (2019) find that high consanguinity promoted the intergenerational concentration of resources among wealthy families in the Krummhorn region of Germany in the eighteenth and nineteenth centuries. Yet, the evolutionary origins of cousin marriage may be different than the patterns most commonly observed later in time. Chagnon et al. (2017) find that individuals have more lineal descendants when their children or opposite-sex siblings marry relatives but fewer when they, their parents, or same-sex siblings do. This suggests that crossculturally common prescriptions to marry cross cousins (the children of opposite sex siblings) and taboos against marrying parallel cousins (the children of same sex siblings) may be related to parent–offspring conflict and competition between samesex siblings. Status-based positive assortative mating is also a common type of endogamy. People assort on a variety of characteristics, such as height (Stulp et al. 2017) and health (Gurven et al. 2009), yet endogamy is most common on the basis of social characteristics associated with status. A classic example is caste endogamy in South Asia, which allows members of high castes to preserve their caste status by marrying and producing heirs only with others who share that status (Dumont 1980). Marital assortment by social class, including assortment by income, occupation, and education, is common and serves a similar purpose of maintaining wealth and status in class-based societies (Hopcroft 2006). As with kin endogamy, status-based endogamy is more common in societies with significant inequality in wealth or status. In extreme cases, there are even rare exceptions to the brother– sister incest taboo (Fox 1980; van den Berghe 1983) among royalty or other highstatus individuals (e.g., ancient Egypt and pre-contact Hawai’i), where individuals maintain political or ritual status through marriage, but only siblings have enough status to qualify.

10.5.3 Extensive and Intensive Kinship Strategies The contrast between exogamy and endogamy suggests that when making marriage decisions, people face a trade-off between forging new alliances as part of a pattern of “extensive kinship” (what my Bangladeshi participants call “making new relatives”; Shenk et al. 2016b) and strengthening their existing kin networks through cousin marriage to create patterns of “intensive kinship.” These two strategies have recently been contrasted in terms of their differing prevalence across subsistence systems (Bailey et al. 2014; Walker and Bailey 2014; Shenk et al. 2016b) and their association with changing sociopolitical patterns (Shenk et al. 2016b; Henrich 2020). Extensive kinship networks are formed through exogamy and broaden social networks by creating more kin as well as more varied social ties (Bailey et al. 2014; Walker and Bailey 2014). Such networks are common in foragers, who use them to mitigate risk through resource sharing, territory access, or exchange partnerships (Lee 1984; Marlowe 2004a; Kramer and Greaves 2011b) and to help find spouses for their children (Wiessner 2009). In such systems, consanguineous

https://doi.org/10.1017/9781108377911.011 Published online by Cambridge University Press

Marriage

241

marriage is often rare, and may be the subject of taboos (Tonkinson 1978; Lee 1984). In contrast, intensive kinship systems are formed through consanguineous marriages, creating overlapping kin networks efficient for organizing cooperative labor, property defense, and property inheritance (Bailey et al. 2014; Walker and Bailey 2014) in which individuals are additionally motivated to cooperate due to inclusive fitness (Hamilton 1964). Such networks have fewer kin but more interconnections and higher levels of group relatedness that are formed through reinforcing kin relationships and avoiding the introduction of new ties. They are associated with intensive agriculture and pastoralism in contexts where heritable wealth in land or animals are key to livelihoods and status (Borgerhoff Mulder et al. 2010; Shenk et al. 2010). In keeping with this, Walker and Bailey (2014) found that foragers had low levels of group-level genetic relatedness, while some agricultural and pastoral groups with high rates of cousin marriage had high group-level genetic relatedness. Shenk et al. (2016b) argue that the transition from agricultural subsistence toward a market economy is often accompanied by a switch from intensive to extensive kinship. Under intensive agriculture, land limitation, and social stratification based on land ownership, the practice of cousin marriage reduces the number of claimants to property. Yet, with market integration, a new niche emerges in which there are increasing benefits to a broader range of social connections useful for helping one get a good job, forge connections to the city, and find a marriage partner in a world of scarcer cousins and increasing economic differentiation among kin. In this context, the benefits of cousin marriage decrease; people should be less willing to tolerate its risks, and negative attitudes towards consanguinity may emerge as social norms. Most HBE researchers have argued that subsistence systems have motivated the adoption of intensive and extensive kinship systems in a bottom-up fashion (Bailey et al. 2014; Shenk et al. 2016b). In contrast, Henrich (2020) argues that the Catholic Church’s prohibition on cousin marriage in medieval Europe – a top-down enforcement of extensive kinship intended to reduce the power of the European nobility visà-vis the church – may have fostered broader social networks and thus faster rates of economic development and democratization in Europe.

10.6

Spouse Number How do marriage systems differ in terms of the numbers of spouses allowed – and how does this vary by gender? What do we know about the evolutionary motivations for these systems? This has been one of the most active areas of research in HBE studies of marriage. Nonhuman primates show a wide variety of mating systems (Smuts et al. 2008; Mitani et al. 2012), the most common of which is the uni-male group consisting of one breeding male, several adult females, and the offspring of the females (e.g., langurs); male tenure in such groups is generally time-limited, and males unable to join a group may live in bachelor troops. The other common type of primate mating system is the multimale group consisting of multiple adult males and females plus

https://doi.org/10.1017/9781108377911.011 Published online by Cambridge University Press

242

Mary K. Shenk

offspring. Multimale groups can vary from promiscuous systems with mating determined by male dominance and female choice (e.g., macaques and chimpanzees) to systems in which males defend a small group of females within a group context (e.g., hamadryas baboons). Both systems are found among Old World monkeys, New World monkeys, and African apes. Much rarer systems include solitary breeding (tarsiers, orangutans) where females raise offspring by themselves, and monogamy among gibbons and siamangs who pair-bond and jointly defend fruit trees using vocalizations. A continuum of systems is found among callitrichids (i.e., marmosets and tamarins) where groups may be monogamous or polyandrous depending on the level of competition for breeding habitats. Human marriage systems are as diverse as the mating systems found across all other primates combined – running the gamut from high to low levels of polygyny, to both lifetime and serial monogamy, to formal and informal polyandry, to societies where marriages are common only among some social groups, many people are single, and children are raised in single-parent or multigenerational households. Yet, diversity in marriage practices is especially interesting because, unlike nonhuman primates, virtually all humans live in relatively large multimale multifemale groups – meaning mating conflicts cannot be limited through the absence of one sex. Humans also share with nonhuman primates a fit between reproductive and resource-related social structures. In nonhuman primates, the classic primate socioecology model suggests that females distribute themselves in the environment to efficiently access resources in cooperation with consanguineal (usually matrilineal) kin, whereas males distribute themselves in the environment to maximize access to females (Crook and Gartlan 1966). While this model has been tested and critiqued extensively (Thierry 2008), critical features endure (Koenig et al. 2013). In humans, the relationship between reproduction and resource cooperation is more entangled, producing complex family and kinship structures in which mating and reproduction are embedded alongside acquisition and processing of food, defense of territory, and status competition (Chapais 2008).

10.6.1 Polygyny Polygyny is a custom permitting men to have more than one wife at a time. The vast majority of human societies (estimated at 85%; Murdock 1949) have allowed or preferred polygyny (Figures 10.3A and 10.3B), even though many men are not able to have more than one wife. While in some societies polygyny is commonplace and practiced by most men at some point in their lives, in most societies polygyny is primarily the domain of wealthy or high-status men. A key question in the study of polygyny is who benefits and how. Most work has focused on how men benefit from polygynous marriage in terms of reproductive success. As discussed in Chapter 9, polygyny is often associated with male reproductive skew. This skew can be quite high in some primates, particularly those with uni-male social organizations, with some males never reproducing at all and others siring numerous offspring (Smuts et al. 2008; Mitani et al. 2012). While this potential for

https://doi.org/10.1017/9781108377911.011 Published online by Cambridge University Press

Marriage

243

(a) Polyandry 1.1%

Monogamy 16.7% 31

Polygyny > 20% 30.6%

57

96 Polygyny < 20% 51.6% (b) Monogamy, Prescribed 15.2%

Polyandry 1.1% 27 Polygyny > 20% 33.7%

60

33

Monogamy, Preferred 18.5%

56 Polygyny < 20% 31.5%

Figure 10.3 Prevalence of types of marriage across the Standard Cross-Cultural Sample.

(A) Polygamy; SCCS79; n = 186. Codes: Polyandry. Primarily monogamous with some women having multiple husbands. Monogamy. Polygyny < 20%. Under 20% of married males have multiple wives. Polygyny > 20%. Over 20% of married males have multiple wives. Sources: Kirby et al. (2016) and Murdock and Wilson (1972). (B) Standard Polygamy Code; SCCS861; n = 178. Codes: Polyandry. Monogamy Prescribed. Monogamy Preferred. Exceptional cases of polygyny but monogamy is preferred. Limited Polygyny. Under 20% of married males have multiple wives. Full Polygyny. Over 20% of married males have multiple wives. Sources: Kirby et al. (2016) and White et al. (1986). https://doi.org/10.1017/9781108377911.011 Published online by Cambridge University Press

244

Mary K. Shenk

reproductive skew exists in humans – and has certainly been observed (Betzig 1986) – it is rarely as pronounced; for example, von Rueden and Jaeggi (2016) find that the effect of status on reproductive success are far weaker in humans (r = 0.19) than other primates (r = 0.80). Models of polygyny among primates have traditionally fallen into two categories – resource defense and mate defense, though the latter is not common in humans. Resource defense polygyny, however, characterizes many human societies where polygyny is strongly related to resources, women are dependent for reproduction on resources controlled by men, and men control different amounts of resources (Emlen and Oring 1977; Hartung 1982; Borgerhoff Mulder 1988a). Women (and/or their parents) thus have the challenge of strategically choosing whether to marry a man with more resources who already has a wife or instead marry a bachelor with fewer. As described in Chapter 1, Orians’s (1969) “polygyny threshold model” (originally developed for birds) suggests that polygyny should be maintained if the “difference in quality between resources held by males is sufficient to enable females to raise as many or more offspring by mating with alreadypaired males on superior territories than with bachelors on inferior territories” (Borgerhoff Mulder 1992b:47). Females are thus predicted to distribute themselves across males according to the availability of resources or territory (Fretwell 1972). Pollet and Nettle (2009), for example, find that polygyny in Uganda is associated with both male land ownership and female-biased sex ratios, but that land ownership has the strongest effect when few men own land. Yet, polygyny can also exist without significant wealth, especially in small-scale groups, including foragers and horticulturalists; in these cases, polygyny is limited to men with special characteristics such as prowess in warfare (Chagnon 1988), generosity (Chaudhary et al. 2015), or ritual knowledge (Tonkinson 1978). Polygyny has also been associated with high male mortality in warfare and high pathogen stress (Ember et al. 2007), the latter generally interpreted (following Hamilton 1982) as a motivation to increase genetic variation in children. The default evolutionary assumption is that male interest in polygyny is motivated primarily by the increased reproductive success that men can achieve through multiple wives, but in some cases, men may have economic motivations as well. In contexts where women are highly economically productive, for example, men may benefit further from polygyny, as women support themselves and their offspring, reducing the need for direct investment by men and making polygyny more practicable for both men and women. Indeed, female contribution to subsistence is significantly positively related to polygyny in cross-cultural studies, particularly in horticultural contexts (Heath 1958; Minocher et al. 2019). In contrast, there is a common assumption that women’s fitness will be negatively impacted by polygynous marriage, but this is not always true. Altmann et al. (1977) outline two perspectives on the evolution of polygyny – competitive “female choice,” which suggests that polygynously married women will compete for limited resources (implying polygyny is unlikely to benefit women), and “cooperative female choice,”

https://doi.org/10.1017/9781108377911.011 Published online by Cambridge University Press

Marriage

245

in which women may benefit by the addition of co-wives with whom they can cooperate in childcare or subsistence labor. As in birds, both competitive and cooperative versions of polygyny have been observed in human societies, and this variation likely shapes the choice of marriage partners by women and their families (Borgerhoff Mulder 1992b). Indeed, researchers have found that some women in polygynous marriages may benefit through higher fertility, greater autonomy, or higher levels of investment in children (Borgerhoff Mulder 1992b; Lawson et al. 2015). In other cases, however, polygyny appears to have negative effects on women, including reduced fitness through higher child mortality (Chisholm and Burbank 1991; Strassmann 2000). Finally, while there are many reasons that men are likely to win conflicts of interest in marital decision-making, this is not inevitable. Borgerhoff Mulder and Ross (2019) test foundational predictions by Bateman that there is greater variance in male than female reproductive and mating success and that there are stronger effects of mating success on reproductive success for males compared to females in Pimbwe communities with serial monogamy and limited polygyny. Using annually resolved data and holding constant the duration of marriages across partners, they find that an increase in the number of mating partners increases female but decreases male reproductive success. While these results may be driven in part by the older age of husbands in polygyny and thus may not hold across contexts, this result helps to illustrate the complex strategies entailed in marriage, fertility, and parental investment decisions in a long-lived species where marriage and parental investment decisions are made over multiple iterations.

10.6.2 Monogamy Among humans, monogamy is a custom permitting only one spouse at a time. While most human societies have allowed or preferred polygyny (Murdock 1949; Figures 10.3A and 10.3B), monogamy is by far the most common form of marriage at the individual level. It is likely that early human ancestors were polygynous, suggested by the fact that these are the characteristics of our closest relatives, the African apes, and by the high levels of sexual dimorphism in early hominins. The origins of monogamy in humans have been debated since the origins of anthropology, a pattern which continues among evolutionary researchers. There are two major questions at issue. One focuses on how monogamy arose as the primary human marriage strategy and the other on how monogamy became a normative and socially enforced custom in a minority of societies – historically, mainly large, wealthy state societies in Europe and Asia, but with industrialization and market integration increasingly common in many parts of the world. Schacht and Kramer (2019) review the evolution of pair-bonding in humans, weaving together several lines of evidence to understand whether monogamy is the human-typical mating system. Human anatomical characteristics, including sexual size dimorphism and testis size, diverge from those of great apes, suggesting a

https://doi.org/10.1017/9781108377911.011 Published online by Cambridge University Press

246

Mary K. Shenk

divergent history of sexual selection in the direction of monogamy among humans. Moreover, while polygyny is allowed in most societies, monogamy is the dominant type of marriage within virtually all societies – and while sex outside of marriage occurs across human societies, human rates of extra-pair paternity are low compared to socially monogamous birds and mammals. Taken together, these suggest that pairbonds are a ubiquitous feature of human mating, most commonly taking the shape of monogamous, or serially monogamous, relationships. But why should this be true? In nonhuman behavioral ecology, much ink has been spilled on the evolution of “social monogamy” or long-term reproductive pairings between a single male and female (this term avoids implications of sexual fidelity or a lifelong bond, neither of which are widespread among mammals). The ancestral condition of all mammals is solitary individualism, meaning monogamy is a derived trait (Lukas and Clutton-Brock 2013). Social monogamy has evolved in nonhuman mammals where reproductive females are intolerant of each other and female density is low, suggesting it develops where males are not able to defend access to more than one female. Schacht and Bell (2016) model several scenarios, including multiple mating, mate guarding, and paternal care, relative to partner availability and find that under human ancestral conditions, mate guarding is most likely to drive the evolution of monogamy, as it helps gain a partner and also assure paternity. In contrast, Lukas and Clutton-Brock (2013) argue that the evolution of monogamy in humans could also result from the need for extended periods of paternal investment. Given the rarity of transitions to social monogamy from group-living, polygynous species, the impetus of the shift in humans may have been changes in diet that decreased female density and limited male ability to mate guard more than one female. While the timing of such a transition is speculative, humans have experienced major dietary shifts in our evolution, including becoming extractive foragers, eating meat, and cooking food, and it has been argued that such shifts led to significant changes in life history and behavior (Kaplan et al. 2000; Wrangham 2009). Yet, such ecological explanations are only one line of reasoning on the origins of monogamy. Indeed, one of the central arguments on the evolution of marriage revolves around whether monogamy is either ecologically imposed or instead socially imposed (Alexander 1987; see also Alexander 1979). Ecologically imposed monogamy assumes that individual men are willing to adopt monogamy when they have little to gain in terms of fitness or resources by having more than one wife, while socially imposed monogamy occurs when laws and rules prohibit polygyny and prescribe monogamy. A major question is why high-status men in wealthy societies with high degrees of wealth inequality – whether these are premodern agrarian states or modern market economies – are often monogamous rather than highly polygynous as one might expect based on analogy with other species or many highly polygynous rulers in the human past (Betzig 1986). Several evolutionary authors have argued that socially imposed monogamy resulted from a compromise in which high-status men receive political support from low-status men in exchange for foregoing multiple wives (Betzig 1986; Alexander

https://doi.org/10.1017/9781108377911.011 Published online by Cambridge University Press

Marriage

247

1987; MacDonald 1995). Betzig (1986) argues this compromise is related to economic specialization, while MacDonald (1995) argues that it coincides with the rise of democracy and elected officials beholden to voters. Henrich et al. (2012) hypothesize that modern socially imposed monogamous marriage has been favored by cultural group selection acting on group-level benefits, including the suppression of intrasexual competition, reduced crime and conflict, increases in gender equality, and shifting male efforts to parental investment. Yet, such arguments are often unsatisfying to human behavioral ecologists because they are top-down (Kanazawa and Still 1999) and thus unconvincing as individual-level explanations; there are also concerns that these approaches ignore underlying ecological explanations. In contrast, arguments for ecologically imposed monogamy have been driven by explanations focusing on the details of economic and subsistence systems from the level of the individual or household, and these arguments are often linked to models from other species. Fortunato and Archetti (2010), for example, contend that monogamy should be viewed as an outcome of strategic decision-making to allocate resources to the next generation in the context of intensive agriculture and land scarcity, as estates become less valuable if they are partitioned across the offspring of more than one wife. Gould et al. (2008) apply related logic to monogamy in modern market economies, arguing that male inequality in education and wealth does not increase polygyny, because polygyny is less affordable and inequality among women increases also. Yet, ecologically imposed and socially imposed monogamy are not necessarily mutually exclusive. It is plausible that ecological conditions have encouraged the widespread adoption of monogamy under conditions of land-limitation and competitive parental investment – and that processes of cultural evolution then elaborated these systems to enforce monogamy and taboo polygyny.

10.6.3 Polyandry Polyandry is the marriage of a woman to more than one man at a time (Murdock 1949; see also Box 1.1). Weigel and Weigel (1987) argued that “as a mammal and an anthropoid primate, the human male would appear to be one of the least likely candidates for polyandry” (quoted in Trevithick 1997; see also Orians 1969; Alexander 1979; Symons 1979), and indeed polyandry is the least common form of marriage globally, customary in only 1.1% of all societies worldwide (see Figure 10.3), primarily located in the Himalayan region and a few parts of Southeast Asia and the Pacific. Yet, while formal (customary) polyandry is indeed quite rare, informal polyandry is much more common (Starkweather and Hames 2012). Human polyandry generally takes one of three forms. Fraternal polyandry, by the far the most common type of formal polyandry, involves the marriage of a group of brothers to a single wife. This is usually practiced alongside monogamy, and occasionally group marriage (e.g. brothers marry a second wife). Fraternal polyandry reduces the potential for male reproductive conflict, as children of the marriage are closely related to all husbands (Crook and Crook 1988; Smith 1998). Many

https://doi.org/10.1017/9781108377911.011 Published online by Cambridge University Press

248

Mary K. Shenk

researchers have argued that children are more likely to be fathered by the oldest husband who may have more influence in the family and be better age-matched to his wife than his younger brothers (e.g., Smith 1998). Yet, Smith (1998) argues that while senior brothers may see reduced inclusive fitness by sharing a wife, junior brothers (who otherwise might not marry or inherit the estate) and parents see increased fitness. Smith argues that Tibetan polyandry appears to be an “adaptive system for preserving family estates, and hence reliably supporting lineal descendants, across the generations” (p. 252), since a group of brothers cooperates to keep property intact by limiting their heirs to the children of one wife (e.g., Goldstein 1976; Crook and Crook 1988). This observation is consistent with arguments for the evolution of monogamy in land-limited agricultural societies, especially given that arable land is particularly limited in mountainous contexts – and with the observation that wealthier, land-owning families are often polyandrous, while families without land are often monogamous (Smith 1998; Stone 2010). Polyandry may also take the form of “visiting husbands,” most famously described among recent historical Nayar communities in South India (Gough 1959) and some Mosuo communities in China (Mattison 2010b). Women are visited by their partners in their own homes and may have multiple partners over time; some partnerships may be short-term, but others are very long-standing relationships, resulting in numerous children of acknowledged paternity. Such customs have been linked to either matrilineal landholdings or frequent male absence – Nayar men were part of a warrior caste often away on campaign, Mosuo men engaged in long-distance trading expeditions, and Mappilla men were maritime traders – making families focused on a pair-bond less stable. Instead, family life focuses on groups of brothers and sisters who live together and cooperate throughout life, and women raise their children in their own natal household while men’s children are raised in their mothers’ households. Although some have argued that such societies lack marriage (Hua 2001), researchers have commonly referred to this custom as polyandry because of the formal social and ritual conventions surrounding partnerships (Gough 1965; Stone 2010). Finally, Starkweather and Hames (2012) describe informal polyandry, as marriage between a woman and more than one, generally unrelated, man occurring in a setting in which the practice is not customary. They argue that globally and historically informal polyandry is found at low levels in smaller-scale societies with flexible marriage systems, especially in contexts of male-biased sex ratios or high levels of male mortality or absenteeism. Informal polyandry is likely to have existed during our evolutionary history, as it is common in foraging contexts, whereas customary forms of polyandry are associated with intensive agriculture, family ownership of estates in land, and established practices of long-distance trade, which have emerged only in the past few thousand years.

10.6.4 Celibacy In humans, monogamy and polyandry are sometimes accompanied by high rates of celibacy, the practice of remaining unmarried or abstinent from sex/reproduction.

https://doi.org/10.1017/9781108377911.011 Published online by Cambridge University Press

Marriage

249

Celibates may be members of organized religious communities, as in Catholicism and Buddhism, but may instead be brothers and sisters who do not marry and stay in their natal households. Celibacy is a common cultural practice associated with landlimited societies in which families are motivated to limit heirship to maintain large estates in land and/or other resources, ensuring lineage survival (Goody 1976; Hartung 1976; Boone 1986). At first glance, celibacy would seem to be maladaptive, yet several evolutionary explanations have been proposed. Barrett et al. (2002) suggest that celibacy may be a phase during which individuals accumulate the status and resources needed for marriage; this is consistent with practices in which vows of celibacy are temporary and mainly apply to younger people, such as Buddhist traditions where most boys spend time as monks. Yet, in many situations, celibacy is lifelong – through permanently joining a religious institution or remaining a bachelor or spinster. In such cases, celibacy may result from parental manipulation, allowing parents to increase fitness by focusing investment on certain children in contexts where heritable wealth is limited and has strong effects on status and fitness (Hartung 1976). Alternatively, celibacy may be directly adaptive if it increases the inclusive fitness of the celibate person, potentially by increasing investment in close kin, such as nieces and nephews (Deady et al. 2006). Irish priests, for example, came from landholding families who were wealthier and had more sons than average (Deady et al. 2006). Among Amdo Tibetan agropastoralists, men with at least one older brother are more likely to become monks and men with at least one celibate brother are wealthier than those with only non-monk brothers (Zhou et al. 2022). And younger daughters more frequently became nuns among Portuguese nobility, allowing families to concentrate dowry in a single daughter (Boone 1986). Unmarried aunts and uncles also commonly serve as helpers at the nest (see Chapter 12).

10.7

Where to Live after Marriage All species have patterns of dispersal, but humans have combined these with marriage customs to produce complex but ecologically predictable patterns of postmarital residence. The primary evolutionary ecological motivations for dispersal (see also Chapter 13) include gaining access to new mating opportunities (Clarke 1993), novel resources and territories (Hamilton and May 1977), and reducing the risk of inbreeding (Moore 1993). Here I review the main types of postmarital residence and their ecological correlates while emphasizing the major patterns of relevance to an evolutionary understanding of mate dispersal (see Figure 10.4): male philopatry (males stay in their natal group or territory), female philopatry (females stay in their natal group or territory), and dual dispersal of both males and females. Three types of residence are characterized by male philopatry and female dispersal, in which a bride leaves her natal family to live with her husband, and may be based either with her husband’s kin (patrilocal) or not (virilocal), or less commonly with his maternal uncle (avunculocal). About 55.7% of the societies in the SCCS have

https://doi.org/10.1017/9781108377911.011 Published online by Cambridge University Press

250

Mary K. Shenk

Natalocal 0.5% Uxorilocal 11.9%

22

Ambi-/Neolocal 31.9%

59

103

Virilocal 55.7%

Figure 10.4 Prevalence of types of postmarital residence across the Standard Cross-Cultural

Sample (Transfer of Residence at Marriage: Prevailing Pattern; SCCS214). n = 185. Sources: Gray (1999) and Kirby et al. (2016).

a patrilocal, virilocal, or avunculocal residence pattern (Figure 10.4; Gray 1999; Kirby et al. 2016). Virilocal and patrilocal residence are widespread in many types of subsistence systems. High levels of internal warfare (Ember and Ember 1971; Divale 1974) and economically defensible resources such as land under intensive agriculture provides an incentive for territoriality and resource defense by men (Dyson-Hudson and Smith 1978; Cashdan et al. 1983; Shenk et al. 2010) and are thus associated with male philopatry, female dispersal, and virilocal postmarital residence (Murdock 1949; Flinn and Low 1986). This is especially likely to be true when resources are associated with male reproductive skew (Goody 1976; Boone 1986; Hrdy and Judge 1993). Indeed, van den Berghe (1979) argues that virilocal rules of residence are especially common because they put the “fewest limiting conditions on polygyny” (p. 14). Two types of residence are characterized by female philopatry and male dispersal, in which a husband leaves his natal family to live with his wife, either near her family (matrilocal) or not (uxorilocal). About 22% of societies in the SCCS have a uxorilocal or matrilocal residence pattern (Figure 10.4; Gray 1999; Kirby et al. 2016). Some researchers find that foraging is associated with a bias toward female philopatry (uxorilocal residence) immediately after marriage (Lee 1984; Marlowe 2004a), while others do not find this pattern (Ember 1975). External warfare and contribution of women to subsistence have been associated with female philopatry (Ember 1974). Some have also found that horticulture (Aberle 1961) and male absence (e.g., due to long-distance trading, warfare; Ember and Ember 1971;

https://doi.org/10.1017/9781108377911.011 Published online by Cambridge University Press

Marriage

251

Divale 1974) are found in association with either uxorilocal or matrilocal residence – often in the context of economic cooperation with female kin (e.g., Leonetti et al. 2007; Mattison 2010b; Alesina et al. 2013). Neolocal residence occurs when spouses establish a new residence apart from either natal family. Ambilocal residence occurs when spouses choose to live with either set of kin or to live with each set of kin at different times (the latter is sometimes also called bilocal). About 31.9% of societies in the SCCS have an ambilocal, bilocal, or neolocal residence pattern (Gray 1999; Kirby et al. 2016). Neolocality and especially ambilocality are common among hunter-gatherers. Hill et al. (2011) argue that hunter-gatherers have a unique social structure where either sex may disperse, adult brothers and sisters may co-reside, and most individuals in residential groups are genetically unrelated. These patterns produce large networks of unrelated adults that are likely implicated in the evolved capacities of humans for social learning and cumulative culture. Kramer et al. (2017) model the dynamics of adult sex ratio and dispersal in small populations with attention to the problem of partner availability/scarcity in hunter-gatherer social organization, and find that if adult sex ratio is biased, the globally rarer sex should disperse. Given stochastic population fluctuations in such societies, either sex might disperse at different times, consistent with the hunter-gatherer pattern of variation in sex dispersal and common patterns of ambilocal or bilocal residence (see also Macfarlan et al. 2020b). Postmarital residence near kin forms extended families (van den Berghe 1979), which can facilitate cooperation in resource acquisition, childcare, herding, defense, and so forth. Yet, the dynamics of residence change dramatically with industrialization, and neolocality is commonly associated with residential mobility of the nuclear family in modern market economies (Harrell 1997; Stone 2010). Natalocal residence occurs when spouses remain in their natal household/group after marriage; about 0.5% of societies in the SCCS have this pattern (Gray 1999; Kirby et al. 2016; Figure 10.4). Kramer and Greaves (2011b) discuss Pumé foragers of Venezuela as an example of a society that primarily practices natalocality, as most people marry spouses from their natal group and thus remain coresident with their families after marriage – likely as a means of maintaining bilateral kin associations that “may be especially important in foraging economies where subsistence activities change throughout the year and large kin networks permit greater potential flexibility in residential mobility.” Societies with visiting husbands have also traditionally practiced natalocality, remaining in their natal households with their mothers, maternal aunts and uncles, siblings, and matrilateral cousins (Gough 1959, 1965), though this has changed over time in many such communities (Mattison 2010b). Brewer (2016) finds that among prehistoric foragers, most adults were local, with females slightly more likely to be local than males. Women in neighboring communities had somewhat more distinct mtDNA than men, burial communities appeared mostly endogamous, and exogamous marriages were more likely to be matrilocal, suggesting that endogamy may have been more common than exogamy in prehistory. Yet Moravec et al. (2018) test the hypothesis that postmarital residence patterns have evolved in similar ways across different geographic regions of the world, and

https://doi.org/10.1017/9781108377911.011 Published online by Cambridge University Press

252

Mary K. Shenk

they find that the evolution of postmarital residence is lineage-specific – underlining the complexity of human residence patterns in many regions of the world.

10.8

Marriage and Resource Transfers Resource transfers have likely been entangled with marriage from far back in our ancestry. Common functions of marriage include establishing/perpetuating a cooperative subsistence unit and regulating inheritance – but the relationship with resources is broader than this: Mates with resources are more attractive and better partners for parental investment, and marriage alliances are often centrally concerned with resource access. Such motivations are not limited to societies with significant amounts of heritable wealth; Lee (1984) argues that access to waterholes was a key reason for !Kung to want connections to other groups, and Weissner (2009) describes Ju/’hoansi individuals with more hxaro exchange partners as not just more attractive on the marriage market, but also in a better position to arrange advantageous matches for their own children. Marriage payments, prestations, or exchanges of one kind or another are very common (Brown 1991; Huber et al. 2011), though the forms that they take vary widely in ways that are linked to subsistence patterns and the local resource base. There are several kinds of exchanges or payments commonly made in connection with marriage (see Figure 10.5); here I will focus on those that are most common and/ or have received the most attention in the literature: bride service, bridewealth Bride Service 12.9%

Insignificant 22.6%

24 42

Dowry 4.8%

9

Gift Exchange 8.1%

15

71

Bridewealth 38.2%

9 Bride Exchange 4.8%

16

Token Bridewealth 8.6%

Figure 10.5 Prevalence of types of marriage payments and exchanges in the Standard Cross-

Cultural Sample (Transactions at Marriage: Prevailing Type; SCCS208). n = 186. Sources: Gray (1999), Kirby et al. (2016), Murdock (1962–1971).

https://doi.org/10.1017/9781108377911.011 Published online by Cambridge University Press

Marriage

253

(sometimes called bride-price), dowry, and indirect dowry (see Huber et al. 2011 for a more detailed typology). Resource transfers from the groom to the bride or her family are the most common pattern across human societies, consistent with Bateman’s first principle that men are more likely to compete for women, as women are the higher-investing sex (Trivers 1972). Such transfers take two primary forms. In bride service, a husband works for his wife’s family before and/or after they are married. Bride service occurs mainly in foraging societies, where the primary resource is foraged foods. For example, Lee (1984) reports that among Dobe !Kung, a man may work for his wife’s family for as long as 15 years or until the birth of their third child. Bridewealth (also known as bride-price) is property given by the groom’s kin to the bride’s kin to seal a marriage; this is similar to bride service in terms of the direction of transfer, but usually consists of animals, movable goods, money, or prestige items. Bridewealth is the most common form of marriage exchange (see Figure 10.5); it is strongly but not exclusively associated with polygyny – 90.8% of polygynous societies pay bridewealth (Hartung 1982), consistent with the interpretation that humans mainly practice resource defense polygyny. Bridewealth functions to help secure a bride in contexts where there is competition on the marriage market. This is especially true of contexts where polygyny is common (Schlegel and Eloul 1988). Bridewealth is more common where women are economically important in cultivation (especially in horticulture) or otherwise economically productive (Heath 1958; Schlegel and Eloul 1988), as a woman’s marriage may represent a loss of productivity and resource access to her natal household. Bridewealth may also be important where children are highly prized, as in labor-limited societies where recruitment of people to the lineage is important for status and resource access (Harrell 1997). Common in pastoralist, horticulturalist, and smaller scale agricultural societies, the importance of bridewealth exchanges is indicated by their necessity to the functions of marriage itself: bridewealth is often returned if the marriage is terminated, children may be considered part of the groom’s family/lineage only if bridewealth has been paid, and compensation for a violation of conjugal rights may be given only if the bridewealth has been paid (Harrell 1997). Bridewealth also serves to legitimate the marriage itself in the eyes of community members and the law (Shadle 2003), and thus may be an important part of formalizing social connections established through the marriage. Dowry involves a presentation of wealth from the bride’s kin to the bride or the groom/groom’s kin. This usually consists of movable goods such as jewelry, clothing, furniture, appliances, and cash, though animals, land, and houses may also be transferred. Dowries can serve multiple functions, sometimes simultaneously. In some cases, a dowry may be seen as a woman’s share of her family inheritance, while in other cases, it is seen as a payment to obtain a high-status groom (also called groomprice; Huber et al. 2011). Dickemann (1979b) and Shenk (2004) have argued that from an evolutionary perspective, both of these can be viewed as forms of parental investment in the daughter, as they represent either direct investment (inheritance) or indirect investment in the status and resources of the groom

https://doi.org/10.1017/9781108377911.011 Published online by Cambridge University Press

254

Mary K. Shenk

(groomprice) and thus the daughter’s standard of living and ability to invest in children. Finally, dowries may be used as costly signals of the family’s wealth (Shenk 2005a). Dowry is more common where women are economically dependent or in abundant supply (Goody 1976). Dowry is usually associated with monogamy (Gaulin and Boster 1990), except in the case of very high-status grooms (Dickemann 1979b). It is also associated with stratified agricultural and industrial societies where the families of brides compete for their daughters to be the only legitimate wife of high-status grooms, whose children will later inherit their father’s property (Dickemann 1979b; Gaulin and Boster 1990). Historically, large dowries have typically only been common in land-limited agricultural societies with high levels of inequality in Europe, Asia, and their diasporas (Goody 1976; Fortunato et al. 2006), though dowry has also been practiced among high-status people in other parts of the world and small dowries of household goods have been common in many agricultural societies. Finally, indirect dowry (Goody 1976) involves a transfer of resources from the groom or groom’s kin to the bride before, at the time of, or after marriage. It can consist of any type of wealth, but is most commonly in the form of jewelry, clothing, and/or cash. Indirect dowries may serve as an endowment for the new couple, as a reciprocal gift for a dowry paid by the bride’s family, or (like dowry) as a means of signaling the wealth of the groom’s family. Indirect dowry may also serve as an endowment for the woman in case of divorce (e.g., the practice of meher in Islam). From an evolutionary perspective, bridewealth and bride service are somewhat analogous to the “nuptial gifts” of food or other resources given by males to females during courtship and mating in other species, but there is an important difference, since in humans, bridewealth generally goes not to the wife but rather to her parents or family (likewise, bride service is directed at family members as much as the bride). Indirect dowry – which goes to the bride (or at least with her to her new household) – may be more closely analogous, but again is not fully parallel, as the groom’s family may fund the indirect dowry as often as the groom does so himself. Bridewealth may be paid by the groom, particularly if he is older or already married, but it may also be paid by the groom’s kin if he is young or for his first marriage – creating competition among men in a family for bridewealth resources, and establishing a motivation for family members to seek bridewealth for their daughters and sisters. Large dowries are virtually always paid by the family of the bride, though in the case of smaller dowries, brides themselves often contribute by making household or decorative items. These facts makes the embeddedness of marriage in the larger social and kin context particularly clear – while mating may be a matter of individuals, marriage rarely is: Kin are deeply enmeshed in the costs and benefits – whether economic or status-related – of an individual’s marriage.

10.9

Conclusions Marriage is central to human society in several ways: as a primary context in which human sexual behavior and fertility occur, as a key building block in establishing

https://doi.org/10.1017/9781108377911.011 Published online by Cambridge University Press

Marriage

255

units of economic cooperation central to resource acquisition and parental investment across most societies, as a key site of social learning and cultural transmission, and as a building block for larger social institutions with significant implications for political systems (Betzig 1986; Shenk et al. 2019; Henrich 2020). It is thus not surprising that marriage has been a central source of fascination to anthropologists, other social scientists, and evolutionary researchers for decades. Marriage practices have been deeply influenced by the theoretical principles underlying all major areas of HBE, including life history theory, sexual selection and sexual conflict theory, parental investment theory, theories related to subsistence and resource access, and theories of cooperation. Moreover, all human marriage systems have been greatly elaborated through the process of cultural evolution, making marriage one of our best examples of the entanglement of nature and culture. While many aspects of marriage are well-researched from an evolutionary perspective, it is high time for reevaluations, extensions, and critiques of much of the older literature discussed here. Classic theories should be formally modeled, classic findings should be reanalyzed with new statistical methods, and new data should be collected where they are lacking. For example, evolutionary research has concentrated on marriages between men and women. Yet, many societies historically and cross-culturally have allowed marriages between people of the same sex or gender, or between people of the same sex but different genders – and there is reason to believe that these practices are patterned by ecology. Human behavioral ecologists should ask how and why same-sex marriages are patterned relative to ecology, subsistence, and political organization. Moreover, HBE has only begun to focus on the question of marriage in modern industrial contexts and the effects of market integration on marriage strategies. While sociologists and demographers have described these patterns, they are undertheorized from an evolutionary perspective. Finally, there is significantly more work to be done in combining HBE and cultural evolutionary approaches – both clearly implicated in marriage patterns, but rarely harmoniously combined in research.

https://doi.org/10.1017/9781108377911.011 Published online by Cambridge University Press

11 Parental Care David W. Lawson

11.1

Introduction In this chapter, I aim to synthesize what we know about the behavioral ecology of parental care in humans, what is yet to be understood, and what advancements are needed to get us there. I take a broad comparative perspective, situating humans among other taxa and emphasizing patterns of socioecological variation within our species. From this perspective, parental care in humans can be characterized as both remarkable in its reach and as highly plastic, with the form and extent of care varying widely across contexts and between individuals. At one extreme, many of us will live only a fraction of our life outside the sphere of parental influence. At the other, neglect, abandonment, and even filicide have been documented across cultures (Box 11.1). Humans are also distinguished, although not unique, in the extent to which child-rearing involves alloparental care, a topic discussed in Chapter 12. The challenge for behavioral ecologists is to make sense of parental care strategies as a product of natural selection. In addressing this challenge, studies of parental care can be categorized into three main research foci. First, parental care is studied in terms of life history trade-offs (Stearns 1992; Chapter 2). Under the rubric of life history theory, “parental investment” can be defined as “any parental allocation of resources to the benefit of offspring at a cost to that parent’s ability to invest in other components of fitness” (Trivers 1972; Clutton-Brock 1991). The term “parental care” is often used interchangeably with parental investment, but technically has a broader definition encompassing any parental trait that enhances the fitness of offspring, and is likely to have originated and/or to be maintained for that function, without necessarily being costly to the parent (Clutton-Brock 1991; Royle et al. 2012). Following pioneering research into the evolution of avian clutch size (Lack 1947), some of the earliest studies in human behavioral ecology (HBE) considered whether variation in fertility schedules could be understood in light of a life history trade-off between fertility and parental investment per offspring, with mixed success (Blurton Jones 1986; Lawson and Borgerhoff Mulder 2016). Another major life history trade-off occurs between investment in mating and parenting (Magrath and Komdeur 2003; Stiver and Alonzo 2009). This trade-off has most often been considered in terms of male strategies (e.g., Gettler et al. 2011), but is also relevant to females when parenting is combined with the demands of retaining an existing mate or attracting a new partner (e.g., Lawson and Mace 2009).

https://doi.org/10.1017/9781108377911.012 Published online by Cambridge University Press

Parental Care

Box 11.1

257

Filicide as a Parental Care Strategy

Filicide, the murder of a child by a parent, has been observed throughout history and across cultures (Daly and Wilson 1984). The terms “filicide” and “infanticide” are frequently used interchangeably, but the latter refers specifically to children under 12 months and includes nonparents as the perpetrator. Most filicides occur early in a child’s life. One clear ultimate motivation for fathers is uncertain paternity, with risk of death from unrelated males common among primates; killing nursing offspring brings lactating females back into ovulation (Opie et al. 2013). Ethnographies from various societies suggest that uncertain paternity is linked to filicide (Daly and Wilson 1984). However, during infancy, mothers are more likely than fathers to kill a child (Bourget et al. 2007; Carolus and Ringen 2018). Why would a mother kill her own child? A solution to this puzzle comes from recognizing that human offspring are so costly to rear that, during times of scarcity, a poorly timed birth jeopardizes the fitness of parents and/or other children. Similarly, young mothers may benefit from abandoning a child if forgoing current reproduction enables successful later reproductive attempts. Indeed, filicide is most common in resource-limited environments and among young mothers (Bourget et al. 2007; Hatters Friedman and Resnick 2007). Younger single women, with the highest probably of future reproduction, are also the most likely to undergo modern abortion procedures (Lycett and Dunbar 1999), and frequently report that they are unprepared for the transition to motherhood, while older women more often cite responsibility to their dependents as a motivation to terminate a pregnancy (Finer et al. 2005). Filicide may also reflect a strategy to avoid sunken cost investment in children with low chances of survival. Filicide has been linked with circumstances where the mother lacks support from a partner or extended kin (Hatters Friedman and Resnick 2007; Carolus and Ringen 2018). Similarly, the presence of severe physical or mental disability is deemed grounds for killing a child in many small-scale populations (Daly and Wilson 1984) and “infant euthanasia” in some contemporary Western nations (Verhagen and Sauer 2005). In some cultures, parents may kill one or all children born from a multiple birth, consistent with twin births suffering from elevated mortality and the difficulties mothers face in providing adequate care to multiple infants simultaneously (Hill and Ball 1996). Mothers have also been observed to practice selective neglect of weak children in contexts of high and uncertain mortality, freeing resources to channel into family members whose survival is more likely (Scheper-Hughes 1992; Onarheim et al. 2017). Functional accounts of filicide by no means contradict the observation that mental health issues are often present in the parent, nor does it imply that killing a child is always consistent with fitness maximization; indeed, a nontrivial proportion of filicides are accompanied by suicide (Bourget et al. 2007). However, a

https://doi.org/10.1017/9781108377911.012 Published online by Cambridge University Press

258

David W. Lawson

behavioral ecological perspective provides clues into the underlying motivations behind filicide and child neglect and highlights that successful parental care strategies necessarily require balancing multiple life history trade-offs (current vs. future reproduction; offspring quantity vs. “quality”). In some circumstances, sacrificing the well-being, or life, of one child to safeguard the interests of other family members may be what it takes to be a successful parent.

Figure 11.1 The three main conflicts over parental care. Adapted from Parker et al. (2002), with

permission from the Royal Society.

Second, parental care is studied as a conflict trait, with conflicts stemming from the cost of care and relatedness asymmetries among family members (Parker et al. 2002; Figure 11.1). Natural selection acts on fitness returns across all offspring, leading to both sibling conflict and parent–offspring conflict over the allocation of parental care (Trivers 1974; Figure 11.2). Sibling conflict in turn leads to the evolution of sibling rivalry, which may be expressed as aggressive behavior, including siblicide (Mock and Parker 1997). Likewise, parent–offspring conflict leads to the evolution of offspring strategies to maximize investment, such as begging behavior, and parental counterstrategies to limit over investment in individual offspring (Godfray 1995). Furthermore, sexual conflict between mothers and fathers will occur when investment from one sex enables the other to reduce investment, freeing resources for allocation into other components of fitness (Houston et al. 2005; Borgerhoff Mulder and Rauch 2009). Conflicts over parental care are escalated when paternity is uncertain, lowering incentives for fathers to invest in putative offspring, reducing perceived relatedness between siblings, and leading to female and offspring strategies to deceive males over true paternity and male counterstrategies to ensure paternity (Smuts 1992; Borgerhoff Mulder and Rauch 2009).

https://doi.org/10.1017/9781108377911.012 Published online by Cambridge University Press

Parental Care

259

Figure 11.2 Trivers’ (1974) theory of parent–offspring conflict. Optimal allocations of parental

investment per offspring are defined by the balance between benefits accrued to an individual offspring versus the costs of reduced investment in alternative offspring (i.e., siblings). For both parents and offspring, increased parental investment has diminishing fitness returns, as it begins to saturate an offspring’s need. Both parents and offspring also experience equivalent costs to continued investment, since, assuming full rather than half-siblings, parents are equally related to offspring as siblings are to each other (each sharing half their genes). However, for offspring, the individual benefits of continued parental investment are considerably amplified, because, while a parent only shares half its genes with an offspring, offspring are fully related to themselves. Consequently, the optimal level of parental investment is lower for parents than for offspring. A classic scenario where we can anticipate this conflict is over age at weaning, with young benefiting from continued breastfeeding, while mothers would benefit from moving on to the next child. Redrawn from Lazarus and Inglis (1986), with permission from © 1986 Published by Elsevier Ltd.

In the next two sections, I first contrast human parental care to neighboring species and consider the alternative forms that parental care can take. From this base, I then overview broad patterns of socioecological variation among humans. These two sections collectively review parental care as a life history trait and a conflict trait. I then turn to the third and final research foci: the application of “parental investment theory” to variation in care by parental and offspring characteristics. Rather than offer an exhaustive review, this section is grouped around three offspring characteristics that have received particular attention in the literature: birth order, sex, and (putative) relatedness between parent and child. I then conclude with a brief appraisal. This chapter adopts the phenotypic and behavioral gambit approach characteristic of HBE (Nettle et al. 2013). I focus on evaluating the adaptive function of parental care, spilling relatively little ink on the underlying adaptive mechanisms that regulate behavior. The genetics and hormonal mediation of parental care are active areas

https://doi.org/10.1017/9781108377911.012 Published online by Cambridge University Press

260

David W. Lawson

of enquiry in human and animal studies, but will not be covered here (see Royle and Moore 2019). I also provide only very limited coverage of several related topics addressed elsewhere in this book, including alloparental care (Chapter 12.), the coevolution of parental care and fertility rates (Chapter 13.), or the impact of sex differences in parental investment on human sex roles (Chapter 9). Throughout, I integrate citations to classic and recent behavioral ecology literature with research in neighboring fields such as economics, demography, and sociology that test overlapping predictions and provide relevant empirical data.

11.2

Human Parental Care in Comparative Context

11.2.1 How Do Humans Compare to Other Taxa? In approaching human parental care in comparative context, it is instructive to consider not only our closest relatives (i.e., the great apes) but also more distant taxonomic groupings that share commonalities with human parenting. As mammals, humans inherit a number of important characteristics, including internal gestation and lactation that together establish a substantially higher minimum parental contribution from females relative to males. Like most mammals, we are also iteroparous, meaning we have the capacity for multiple reproductive bouts across the lifetime, introducing life history trade-offs between current and future reproduction (Williams 1966a) and creating the possibility of sibling competition for parental care between offspring of different ages. Humans also exaggerate general trends observed among primates as we birth highly altricial (helpless) young, and parental care is remarkably extended so that offspring are rarely independent until well into the second, if not third, decade (Kaplan et al. 2000). Like other apes, human clutch size is also generally one (i.e., most births are singletons), with multiple births very rare and associated with elevated maternal and child mortality. There is evidence that twinning is most common among women of relatively high phenotypic quality, suggesting that only these mothers are able to afford the physiological costs of multiple births (Sear et al. 2001; Robson and Smith 2011; but see Rickard et al. 2012). Unlike most mammals, including nonhuman primates, paternal care is relatively high in humans, although the importance of fathers is decidedly variable across and within cultures (Sear and Mace 2008; Bribiescas et al. 2012; Gray and Anderson 2012; Mattison et al. 2014) (Box 11.2). This combination of exceptionally altricial young and biparental care means that in some respects humans are more like monogamous songbirds than other primates (Black 1996). Parallels can also be drawn with distantly related mammal species that tend toward monogamy and biparental care, such as canids and some rodents (Lukas and Clutton-Brock 2013). Whenever biparental care is observed, male care tends to be less extensive and effective than female care, including in humans (Sear and Mace 2008; Royle et al. 2016). Comparative analyses across taxa have concluded that selection drives males to join females in caring for young in response to socioecological factors that

https://doi.org/10.1017/9781108377911.012 Published online by Cambridge University Press

Parental Care

Box 11.2

261

The Importance of Fathers

Early literature in evolutionary anthropology emphasized the importance of paternal provisioning, especially among foragers (Lovejoy 1981; Mattison 2017). This view has gradually been replaced by an understanding that in many contexts children spend substantial proportions of their childhood apart from one or both parents, even when parents remain alive, and that such circumstances are not always detrimental. An influential paper by Sear and Mace (2008) reviewed studies considering whether the absence of alternative kin predicted child survival among small-scale societies. In only one-third of studies was the presence of a father associated with greater likelihood of survival. Related studies of child health have also often found only modest evidence that father presence is advantageous (e.g., Lawson et al. 2017b). More subtle measures of paternal care than simply absence/presence are clearly required (see Boyette et al. 2018), but nevertheless these results imply that, while fathers frequently invest in their offspring, paternal care is readily substitutable by care from mothers or alloparents in many contexts. Recent research has shifted focus to ask not whether fathers are important, but in what contexts are fathers important? Most obviously this will depend on the extent to which fathers dominate resource provision or provide unique forms of investment (e.g., training in sex-specific subsistence skills), the availability of alloparents, and extent to which child well-being is determined by extrinsic (care-independent) factors. Bernardi and Boertien (2016), for example, conclude that British children from relatively wealthy families have “more to lose” from father absence, because the reduction in household income associated with parental separation is larger. In some societies, the importance of fathers may not be observed until adolescence and early adulthood, as they assist in marital arrangements and establishment of independent careers (Scelza 2010; Shenk and Scelza 2012). Behavioral ecologists have also begun to study shifts in paternal behavior in reaction to socioecological change within populations. While ascribing the causes of observed changes is not always straightforward, this approach offers new opportunities to understand what factors favor a stronger role for fathers. Schacht et al. (2018), for example, document intensified paternal involvement in childcare among the Maya of Mexico as they became increasingly market integrated. They interpret this trend as driven by reduced time demands from farming, which lowered the opportunity costs of direct care, and new incentives to invest in children’s education via payoffs an emerging labor market.

https://doi.org/10.1017/9781108377911.012 Published online by Cambridge University Press

262

David W. Lawson

constrain the availability of further mating opportunities (Lukas and Clutton-Brock 2013; Gilbert and Manica 2015; Remeš et al. 2015). Ensuring paternity and protecting young from infanticidal males can also provide important incentives for males to care for young (Kvarnemo 2005; Hopwood et al. 2015), with some phylogenetic analyses suggesting that infanticide protection was an important selective force driving the evolution of biparental care among primates (Opie et al. 2013). Paternal care can be categorized into direct or indirect forms (Kleiman and Malcolm 1981). Direct care includes behaviors such as carrying, feeding, and maintaining proximity to offspring, whereas indirect care encompasses more distal behaviors such as protection, including from infanticide, and the acquisition and defense of resources. Such distinctions can, of course, equally be applied to maternal care, but the distinction has been particularly useful in studies of paternal behavior, because direct paternal care is often absent and indirect forms can be less obvious and more difficult to quantify. Direct paternal care is likely traded off with mating effort in many contexts. Hormonal mediation of this trade-off is apparent. Across a range of taxa, males have relatively high testosterone when engaging in mating effort, and relatively low testosterone when cooperating with a female to raise young (Magrath and Komdeur 2003; Gettler et al. 2011; Lawson et al. 2017a; Figure 11.3). Complicating matters, both direct and indirect paternal care have been alternatively modeled as either parenting or mating effort, since females are attracted to good fathers (Hawkes 1991; Bribiescas et al. 2012; Wood and Marlowe 2014), making it difficult to quantify trade-offs between mating and parenting effort. One area where humans are distinct from most mammals and birds is that we “stack” offspring (Wells 2012). Other primates raise offspring to nutritional independence before beginning a new pregnancy, while in humans weaned children remain highly dependent on parental provisioning, setting up novel dynamics whereby different forms of care must be supplied to offspring at distinct life stages. Stacking offspring extends the scope for birth order to influence the allocation of parental care and patterns of sibling competition. Human families are also unusual, at least among primates, in the extent to which offspring are recruited into productive roles that subsidize the costs of their own care, taking on a variety of subsistence tasks from young ages (Kramer 2011) and providing alloparental care to their younger siblings (Chapter 12). In contrast, juvenile chimpanzees are nutritionally independent and do not typically provision younger siblings, although mothers may benefit from maintaining social ties with juvenile offspring (Stanton et al. 2017).

11.2.2 What Do Humans Invest in Offspring? Parental care in humans takes qualitatively distinct forms from infancy to adulthood (Table 11.1). Considering this multidimensionality is important not least because alternative forms of care correspond more or less well to the narrow definition of parental investment – i.e., are both beneficial to offspring and costly to parental fitness (Royle et al. 2012; Fromhage 2017). Likewise, alternative forms of care may be more or less subject to dilution between siblings, and so differ in the extent to which

https://doi.org/10.1017/9781108377911.012 Published online by Cambridge University Press

150 140 130 120 110 100 90 80 70 60 50 40 30 20 10 0

Morning

Afternoon

Unmarried Married

Unmarried Married

(c) 150 140 130 120 110 100 90 80 70 60 50 40 30 20 10 0

Morning

Without Children

With Children

Afternoon

Without Children

With Children

Average Morning Testosterone (pq/ml)

(b)

Testosterone (pq/ml)

Testosterone (pq/ml)

https://doi.org/10.1017/9781108377911.012 Published online by Cambridge University Press

(a)

unmarried monogamous polygynous

300 250 200 150 100 50 0 10

20

30 40 50 Age (years)

60

70

Figure 11.3 Testosterone, paternal care, and mating effort in rural Gambia. Variation in male testosterone has been hypothesized to reflect the

hormonal regulation of investment in mating versus parenting effort. Consistent with this hypothesis, married men have lower testosterone levels than unmarried men (A); and men who sleep in close proximity to young children (and are presumably more involved in direct care) have lower testosterone than men who sleep apart from their children (B). However, since men in this context all marry around a similar age (C), the association between testosterone and marital status is difficult to untangle from general age declines in testosterone. Data presented come from a study of 100 men in rural Gambia; see Lawson et al. (2017a) for details. Error bars are standard errors. From Lawson (2017a), Copyright © 2017, Springer International Publishing, used with permission.

https://doi.org/10.1017/9781108377911.012 Published online by Cambridge University Press

Table 11.1 Postnatal parental care in humans: form, socioecological variation, and scope for sibling competition.

Infancy

Form of parental care

Socioecological variation

Scope for sibling competition

Exemplary reference(s)

Breastfeeding

Children are typically weaned earlier in high-income countries Variation in maternal and paternal roles depending on subsistence strategy

High High, but reduced when children are active producers

(Sellen 2007; Wander and Mattison 2013) (Kramer 2005a; Kaplan et al. 2009)

Low

(Opie et al. 2013)

High if payment required, less so if time-based and/or if pathogen risk is extrinsic Modest

(Uggla and Mace 2016b; Onarheim et al. 2017)

Modest

(Kline 2015; Lancy 2016b)

High, especially if school fees or opportunity costs are present

(Goodmanet al. 2012; Hedges et al. 2016)

High, sex specific

(Borgerhoff Mulder 1990; Mace 1996; Anderson 2007)

High, sex specific

(Hrdy and Judge 1993; Keister 2003; Gibson and Gurmu 2011; Fortunato 2012)

High for practical support, low for emotional support

(Gibson and Mace 2005; Coall et al. 2009; Schaffnit and Sear 2017)

Provisioning (i.e., foraging, hunting, food preparation) Protection, Shelter Childhood

Adulthood

Health care (e.g., washing, taking to the doctor, etc.) Emotional closeness/ affection/attention Informal teaching, including socialization Schooling

Marriage payments

Wealth transfers and inheritance

Child rearing assistance

Variation in physical and social threats; some may be extrinsic risks Marked variation in access to health services and in local health risks Affection and attention exaggerated among modern high-income countries Mode and extent of teaching varies, as does the importance of skill accumulation in subsistence Primary schooling is now almost universal, secondary and tertiary education less so Often substantial among pastoralists and agriculturalists. Some practice bridewealth, others dowry Low in subsistence foragers, but otherwise often substantial. Some practice patrilineal inheritance, others matrilineal inheritance Proximity to grandparents depends on residence system, maternal grandparents usually more important

(Lancy 2014)

Parental Care

265

they foster sibling and parent–offspring conflict. Some forms of care may typically be carried out by parents alone, while others can be done by alloparents. It is also useful to consider parental care as constructed of energetic, interpersonal, and material dimensions. Energetic investment is common to any parental activity requiring caloric expenditure but is in its purest form in maternal investments in gestation and lactation. The duration of breastfeeding is relatively short in humans compared to other primates of similar body size, but is critical in both the transmission of immunity and transfers of maternal body fat and other stored nutrients (Sellen 2007). Pregnancy and lactation entail substantial energetic costs to mothers (Butte and King 2005). Despite these costs, evidence of maternal depletion (i.e., reduced health with additional pregnancies) is surprisingly mixed, perhaps reflecting methodological difficulties in accounting for phenotypic differences between high and low fertility mothers (Hruschka and Hagaman 2015; Gurven et al. 2016a). Sibling competition over early energetic investments is more evident; both breastfeeding duration and interbirth intervals are positively associated with survival and nutritional outcomes for young children (Sellen 2007; Lawson et al. 2012). With the rare exception of surrogacy, gestation must be done by mothers, but allomaternal nursing has been documented in many cultural settings, often by grandmothers (Hewlett and Winn 2014). “Wet-nursing” frees mothers to invest in the next pregnancy and is particularly important where mothers are not able to breastfeed, due to absence or death, but also entails costs to infants, including pathogen transmission risk (Hewlett and Winn 2014). Interpersonal investments are time-intensive and require parent–offspring interaction (although not necessarily physical proximity, thanks to modern communication technology). Included here are parental behaviors associated with attention, affection, and encouragement, the embodiment of skills and knowledge via teaching and socialization (Lancy 2014, 2016b; Kline 2015). Interpersonal investments are also critical in monitoring and attending to children’s health (Uggla and Mace 2016b). Interpersonal investments have the potential to be costly to be parents, both in terms of limited time and energy allocation, but also in terms of draining parental emotional capital. There is some evidence that children in larger families spend less time with both parents in direct care activities (Downey 1995; Lawson and Mace 2009; Wu 2016), suggesting that some interpersonal investments are subject to sibling competition. However, family size is strongly associated with a range of parental characteristics (e.g., age, socioeconomic status, social support), making it difficult to establish causality. Mehr and Krasnow (2017) argue that infant-directed song evolved to signal parental attention to infants, accounting for both the cross-cultural ubiquity of lullabies and their soothing impact on children. By extension, infant-direct song may be subject to parent–offspring conflict. Parents may attempt to deceive offspring, falsely implying attention via song while engaging in other tasks, while infants respond best to lullabies containing song patterns that honestly signal attention – that is, are hard to combine with activities that divert parental attention (e.g., physical exertion, care for another child). Yet, wider patterns of parent–child interaction are culturally variable, suggesting flexible pathways between care and

https://doi.org/10.1017/9781108377911.012 Published online by Cambridge University Press

266

David W. Lawson

child development. For example, infant-directed speech appears less common in nonindustrial populations (Cristia et al. 2019). Third, material resources are invested in offspring throughout life. Provisioning offspring with food and shelter is universally critical. Parental resources are also important in accessing health care and formal schooling, depending on the extent to which such services are available. As young adults, resource transfers are also frequently critical in obtaining marriage partners via payments of bridewealth and dowry, with payments often coming at substantial economic cost (Anderson 2007). Parental bequests are furthermore pivotal in establishing independence as offspring disperse and start their own families (e.g., in setting up or buying a first home), and at inheritance in later life following parental death (Hrdy and Judge 1993). Such transfers of wealth lead to heritable wealth inequalities across generations (Borgerhoff Mulder et al. 2009), and make the division of parental wealth a key site of sibling competition (Keister 2003; Gibson and Gurmu 2011; Goodman et al. 2012).

11.3

Socioecological Variation A fundamental tenet of the behavioral ecological approach is that behavioral variation springs from socioecological diversity in the costs and benefits of action (Nettle et al. 2013). Parental care, like all other behaviors, can only be understood by rooting our understanding in local context. Here, I identify four key ways that context is critical to parental care, paying particular attention to the downstream consequences of subsistence mode.

11.3.1 Labor Contributions Subsistence mode is closely linked to the labor inputs of men, women, and children. Foragers are characterized by a gendered division in labor (Chapter 6). Hunting, at least of larger game, is hard to combine with intensive mothering, infant carrying, and lactation-on-demand, so men typically source game, while women take on most direct care duties (Kaplan et al. 2009, but see Haas et al. 2020). While forager women can make substantial economic contributions via gathering, fishing, and food processing activities done while caring for children, shifts to settlement and agriculture are accompanied by increasing compatibility of productive work and childcare for both sexes. Available data nevertheless suggest direct care by fathers is minimal among farmers compared to foragers (Marlowe 2000b). This may reflect higher levels of polygyny associated with shifts away from foraging, with some men’s time now split between wives and their children, along with escalating male time commitments to resource defense and mate-guarding (Marlowe 2000b). Yet, comparative data on childcare activities across small-scale societies is patchy, and our understanding of work versus childcare trade-offs remains limited. Wage-labor economies vary widely in the compatibility of women’s work and childcare and the extent of father involvement, but women remain the primary caregivers everywhere. In the United States, for example, from the 1960s to today,

https://doi.org/10.1017/9781108377911.012 Published online by Cambridge University Press

Parental Care

267

women’s participation in the labor force increased dramatically and has been met with an increase in father’s involvement in childcare and household work (Bianchi 2011). Yet, across the same period, women have also increased time allocation to childcare, and still allocate substantially more time to care than fathers (Bianchi 2011; Negraia et al. 2018). Children’s work also influences parental care. Hunting takes a long time to become proficient and thus children can do little to offset their costs to parents among foragers, making them costly to rear (Kaplan et al. 2009). In contrast, among farmers, children are more frequently enrolled in tasks requiring less skill, underwriting their costs to parents and freeing parental resources for investment in alternative fitness functions, such as increasing fertility (Kramer 2011). Where there is formal education, children’s work also introduces time allocation trade-offs between work and school, although depending on the context schooling can trade off more with children’s leisure time (Hedges et al. 2018; Figure 11.4). In contemporary highincome countries, children’s work in and outside of the household is relatively minimal, with children spending most of the day in school. Schooling frees parental time to work rather than supervise children, but formal educational is typically a

Figure 11.4 Young men walk the street in Mwanza, Tanzania. Young people in high-income

countries almost universally attend school and rarely contribute economically to their household. In contrast, adolescents and even young children in many relatively low-income countries face important time allocation trade-offs between formal education and work activities (e.g., domestic work, farmwork, or engaging in petty trade). The balance of these trade-offs can have important impacts on both well-being and parental care strategies. Image credit: David W Lawson.

https://doi.org/10.1017/9781108377911.012 Published online by Cambridge University Press

268

David W. Lawson

costly form of parental investment, especially when extended into higher education. A lack of juvenile production and the cost of educating children make modern childrearing especially costly (Kaplan 1996).

11.3.2 Wealth Inheritance The inheritance of extrasomatic wealth (i.e., resources like land, cattle, or cash, not contained within the body) is limited in foraging and horticultural societies, but often substantial among pastoralists, agriculturalists, and modern wage-labor economies (Borgerhoff Mulder et al. 2009). This has major consequences for parental care. First, wealth inheritance elevates sibling competition and rivalry. This is particularly true among males who are frequently the inheriting sex, with many studies finding relatively low male reproductive success in the presence of brothers (Low 1991; Mace 1996; Borgerhoff Mulder 1998a; Gibson and Gurmu 2011). Yet, material resources vary in the extent to which their fitness value is reduced by division among heirs. Among intensive agriculturalists, productivity is land-limited and thus inheritance shares are often fundamental determinants of adult success. Among horticulturalists and pastoralists, wealth is more elastic, with opportunities to offset a small inheritance via increased horticultural labor or animal breeding, provided environmental resources are abundant. When the stakes are especially high, such as when inheritance brings not only material goods but also ascension to roles of political power, sibling competition can incentivize siblicide (e.g., Dunbar et al. 1995). In contrast, among foragers, who lack significant extrasomatic wealth, large sibships appear mostly beneficial via nepotistic social affiliations (Draper and Hames 2000). Wealth inheritance as a form of parental care also influences scope for parent– offspring over marriage arrangements and sexual conflict due to increased costs to cuckoldry, as discussed in Chapters 9 and 10.

11.3.3 Extrinsic Risk Child mortality is high in most foraging societies; less than 50% of offspring surviving to age 15 is common (Walker et al. 2006). Transitions to settlement and farming only tend to further increase child mortality, probably due to increased pathogen transmission (Page et al. 2016). The critical point from a parental care perspective is that when mortality is high, it is also generally relatively extrinsic; that is, survival depends mostly on external factors, such as ecological vulnerability to subsistence failure, natural disasters, unavoidable pathogens, warfare, and luck. Under these conditions, the returns to parental investment peak early and parents are anticipated to limit investment (Pennington and Harpending 1988). While theoretically sound, evidence to support this hypothesized role of extrinsic risk is limited. Quinlan (2007) found that in a cross-cultural sample, the incidence of warfare and famine is inversely correlated with maternal care, as proxied by sleeping proximity, response to infant crying, and bodily contact with infants. Gibson and Lawson (2011) report that the installation of water taps in rural Ethiopia, which reduced child

https://doi.org/10.1017/9781108377911.012 Published online by Cambridge University Press

Parental Care

269

mortality, was associated with increased parental investment in education. There is also evidence that negative impacts of sibling competition on child well-being are weakened in contexts of especially high mortality, consistent with the idea that extrinsic risk reduces the importance of parental care as a determinant of offspring success (Desai 1995; Gibson and Lawson 2011; Lawson et al. 2012). Socioecological variation in extrinsic risk can also influence parental care among contemporary high-income populations, weakening relationships between parental care and non-mortality outcomes, such as child health and socioeconomic capital. The association between poverty and environmental uncertainty may account for socioeconomic gradients in parental care, with wealthier parents spending relatively more time in direct childcare per child because they reap greater returns (Nettle 2008; Lawson and Mace 2009). There is also evidence that parents are attentive to the local returns on their investment when deciding how much to invest. Biroli et al. (2022), for example, report that less-educated British parents perceive the returns to investing in child health to be lower, and that this perception is predictive of both lower health investments and poorer child well-being.

11.3.4 Runaway Parental Investment Lancy (2008) argues that while gerontocracy is the norm for low-income countries, high-income countries are characterized by “neontocracy”; the needs of children are placed before all others. Shifts toward intensive parenting can be observed in recent history within high-income contexts; time spent in direct childcare has doubled over the last 50 years in some countries, with high socioeconomic-status parents most likely to adopt especially intensive parenting (Bianchi 2011; Dotti Sani and Treas 2016). Parents also spend more money on children’s education, postponing financial independence and effectively further increasing the length of our already elongated juvenile phase relative to other primates (Kaplan 1996). Observing delayed transitions to adulthood (including timing of education, marriage, and parenthood), public health scholars have argued that adulthood should be defined to begin at 25 rather than 19 years (Sawyer et al. 2018). Mace (2007) coins the term “runaway parental investment” to describe this state of affairs, arguing that in competitive labor and mating markets the value of parental care is dictated largely via its impact on relative social status – with seemingly no ceiling effect. This remarkable intensification of parental care has no doubt coevolved with a remarkable decline in fertility, with a trade-off between offspring number and parental investment key to understanding the demographic transition (Kaplan et al. 2002; Chapter 13).

11.4

Birth Order

11.4.1 Is It Better to Be an Earlyborn or a Laterborn? Three main factors predict an earlyborn advantage in parental care. First, by being closer to maturity at any given time across childhood than their younger siblings,

https://doi.org/10.1017/9781108377911.012 Published online by Cambridge University Press

270

David W. Lawson

and thus subject to lower risk of dying before adulthood, earlyborns generally have higher reproductive value (Clutton-Brock 1991; Jeon 2008) – that is, expected future reproduction (Fisher 1930). Second, prioritizing the success of earlyborn offspring can enable parents to shorten generation time, thus increasing their relative genetic representation in future generations (Jones and Bliege Bird 2015). Third, even if parents equalize care across dependent offspring, earlyborns benefit from a period of relatively unrivaled parental attention in early life (Hertwig et al. 2002). Independent of parental behavior, earlyborn offspring may also have the upper hand when siblings compete for parental care, such as when dividing delivered food, due to their relative physical and cognitive maturity (Mock and Parker 1997; Jeon 2008). Other factors predict a laterborn advantage. The “terminal investment hypothesis” proposes that a decreasing expectation of future reproduction at older ages incentivizes investment in current reproduction (Duffield et al. 2017). Independently of parent care allocation, experience and skill in parenting behaviors are also likely to improve with subsequent births (Stanton et al. 2014). This may be particularly important in nonhuman species less able to socially learn parenting skills and who instead must rely on trial and error learning in parenting offspring. Laterborns may also benefit if older siblings are alloparents or if parents benefit from maintaining social ties with elder offspring (Stanton et al. 2017). Finally, laterborns may also benefit materially from having older siblings if they are able to use goods (e.g., books, clothes) handed down from their elder brothers and sisters.

11.4.2 Evidence of Biased Parental Investment by Birth Order Cultural rules privileging firstborns are common, including more elaborate birth ceremonies and recognized authority over younger siblings (Rosenblatt and Skoogberg 1974). Daly and Wilson (1984) also point out that in the rare practice of filicide (see Box 11.1), the victim is most often a laterborn child, consistent with a preference for earlyborn offspring when harsh ecological conditions favor the sacrifice of one offspring for the survival of another. Studies of parental time allocation also suggest modest favoritism of earlyborns, although data of this type is mainly from high-income populations (Price 2008; Lawson and Mace 2009). In chimpanzees, primiparous mothers nurse, groom, and play with infants longer than multiparous mothers (Stanton et al. 2014), suggesting that discriminative behavior is not a derived trait. However, in chimpanzees, differences in mothering behavior have been interpreted as compensatory effort, making up for maternal inexperience, with the probability of early survival unrelated to birth order (Stanton et al. 2014). In humans, on the other hand, there is evidence that low investment in laterborns is consequential for child well-being. The most conspicuous example of preferential treatment by birth order is the widespread practice of primogeniture among pastoralist and agrarian societies, whereby the oldest offspring, typically sons, inherit most or all parental resources (i.e., land, cattle, assets). Here, older brothers substantially depress male marital and

https://doi.org/10.1017/9781108377911.012 Published online by Cambridge University Press

Parental Care

271

reproductive success (Boone 1986, 1988; Low 1990; Mace 1996; Gibson and Gurmu 2011). In some cases, laterborns may be encouraged to opt out of the competition altogether. In a historical study of Portuguese nobility, Boone (1986, 1988) demonstrates higher rates of death in warfare in laterborn males, and higher rates of becoming a nun in laterborn females. Preferential inheritance to earlyborn offspring is, however, not universal. Equally distributed inheritance, or, in rare cases, ultimogeniture (inheritance to the last-born offspring), have also been documented (Hrdy and Judge 1993). Ultimogeniture remains understudied by behavioral ecologists but may represent a strategy to ensure long-term lineage survival, by lowering the number of inheritance divisions over time, in the face of harsh economic constraints such as habitat saturation (Beise and Voland 2008).

11.4.3 Birth Order and Well-being Laterborn children are heavier at birth, a pattern not easily interpreted as consistent with the terminal investment hypothesis, since children of older mothers are not heavier at birth (Fessler et al. 2004). In proximate terms, anatomical shifts in vascular structure with each pregnancy may account for the laterborn advantage, making the womb more effective at nurturing the fetus (Khong et al. 2003). Firstborns have been observed to suffer a penalty in terms of infant survival in high-mortality settings, but more generally, infant and child mortality are highest for children with many older siblings (Howell et al. 2016). Historical studies of Europe and North America confirm lower survival of laterborns to and during adulthood (Modin 2002; Penn and Smith 2007). Late birth order also predicts higher rates of stunting in many African national demographic surveys (Howell et al. 2016). In more high-income settings, late birth order is associated with short stature and lower physical fitness (Lawson and Mace 2008; Barclay and Myrskylä 2014). Collectively, these findings indicate a laterborn health disadvantage. However, if we specifically consider wide interbirth intervals, there is some evidence that older siblings, particularly older sisters, increase chances of child survival through alloparenting activities (Sear and Mace 2008; Helfrecht and Meehan 2016). Furthermore, within high-income countries, health costs of late birth order seem to have attenuated in recent cohorts, as standards of living have increased (Myrskylä et al. 2013). The survival and health consequences of birth order are clearly context-dependent. In high-income countries, earlyborns outperform laterborns in educational attainment and achievement (Steelman et al. 2002; Lawson et al. 2013). These effects appear driven by social rank within the family rather than biological birth order, since they are only observed in situations where siblings are living (Kristensen and Bjerkedal 2007). However, the estimated impact of older siblings on educationrelated outcomes is often minor and does not appear to meaningfully impact adult income (Lawson et al. 2013) (Figure 11.5). Evidence for a laterborn disadvantage is also mixed among low-income populations, where formal schooling has only recently been established (Hedges et al. 2019a). This is likely partly attributable to the variable role of children’s work in subsistence economies, and the extent to which

https://doi.org/10.1017/9781108377911.012 Published online by Cambridge University Press

272

David W. Lawson (b)

Schoolmarks

Family income 0

1

2

3

4

0 –0.1 –0.2 –0.3

Entering university

–0.4

Change in standard deviations adjusted effect (95%Cl)

–0.5 –1

Schoolmarks

–1.5

Change in standard deviations adjusted effect (95%Cl)

0

(a)

5+

0

1

Number of siblings

Entering university

1

2

3+

Change in standard deviations adjusted effect (95%Cl) –0.3 –0.2 –0.1 0 0.1

0

3+

Family income

(d)

Change in standard deviations adjusted effect (95%Cl) –0.6 –0.4 –0.2 0 0.2

(c)

2 No. older siblings No. younger siblings

No. older siblings No. younger siblings

0

1

2

3+

No. older siblings No. younger siblings

Figure 11.5 Siblings, education, and income in Swedish families. Children in larger families

perform worse in school tests, have a lower likelihood of entering university, and earn lower incomes as adults (A). Older siblings appear more detrimental than younger siblings to school performance and likelihood of entering university (B and C), implying a laterborn disadvantage. However, the number of older versus younger siblings has equivalent relationships with adult family income (D). This suggests that large family size rather than birth order has lasting socioeconomic consequences. All data come from a sample of over 10,000 families; results adjust for birthweight, gestational age, twin/triplet status, mother’s age and marital status, parental socioeconomic position, and birth year. See Lawson et al. (2013) for details. Copyright: © 2013 Lawson et al. Open Access.

age dictates its productivity and appropriateness. In rural Tanzania, for example, domestic tasks are allocated primarily to older daughters, freeing up younger girls to attend school. In contrast, boys living with older children had the lowest likelihood of school enrollment, and in cattle-herding households, younger boys take on more labor to support older children (Hedges et al. 2019a). One area where laterborns may do better is in mental health. Lawson and Mace (2010) found that British children with more older siblings were shorter for their age

https://doi.org/10.1017/9781108377911.012 Published online by Cambridge University Press

Parental Care

273

and performed relatively poorly at school, yet parents viewed them as having fewer mental health difficulties. A recent large-scale within-family analysis also found laterborns performed better on cooperative tasks requiring social coordination (Prime et al. 2017). There may be a social maturation benefit for children interacting with older siblings, and/or laterborns may benefit from being born into a household environment already socially and emotionally prepared for family life (Lawson and Mace 2010). Whether these relationships generalize across cultural contexts remains to be investigated.

11.5.

Sex-Biased Parental Care

11.5.1 Fisherian Sex Ratios Fisher (1930) recognized that, provided that sons and daughters are equally costly to rear, natural selection will favor equal distribution of parental investment by offspring sex, and thus a 50:50 offspring sex ratio. This is because if one sex becomes less abundant in the breeding population, greater production of that sex will be favored, because it will, on average, outreproduce the more abundant sex. However, if one sex of offspring has a higher mortality rate than the other, mothers may be selected to give birth to more of the low-viability sex (Fisher 1930), or to invest relatively more pre- and/or postnatally in this sex (Clutton-Brock 1991). In humans, males are subject to higher neonatal and infant mortality than females. This is thought to underlie the slight male-bias in sex ratio at birth commonly observed in humans, since it acts to rebalance the Fisherian ratio (Wells 2000). There is also evidence of higher maternal energy allocation to male fetuses during pregnancy. Male fetuses have a faster rate of growth and are heavier at birth (Maršál et al. 1996; Loos et al. 2001), and women carrying male fetuses have relatively higher energy intake (Tamimi et al. 2003). Following Fisher, evolutionary biologists have also recognized broader circumstances in which the costs and benefits of rearing sons versus daughters may differ, predicting deviations from Fisher’s principle of equal investment (Hamilton 1967; Trivers and Willard 1973). Emerging hypotheses have stimulated a large, complex evolutionary literature on sex-biased parental care, encompassing both biases in sex ratio at birth and in postnatal care.

11.5.2 The Trivers–Willard Hypothesis The Trivers–Willard hypothesis stipulates that sex-biased parental investment will be favored when reproductive success of the sexes is differentially influenced by parental condition or investments (Trivers and Willard 1973). This is evident, for example, in polygynously mating mammal species with higher variance in male reproductive success and where male reproductive success is influenced by parental social rank or physical condition. Under such circumstances, which apply in at least some human populations, the fitness returns on producing a daughter will be higher for parents in

https://doi.org/10.1017/9781108377911.012 Published online by Cambridge University Press

274

David W. Lawson

poor condition, while the returns on producing a son will be higher for parents in good condition (Trivers and Willard 1973). Studies of mammalian sex ratios have produced contradictory results in tests of this hypothesis (Brown 2001; Cameron 2004; Douhard 2017). Supportive results include studies demonstrating healthier women produce more sons in rural Ethiopia (Gibson and Mace 2003); that billionaires have more male-biased sex ratios than the general population (Cameron and Dalerum 2009); and that wealthier families in rural China produce more sons, while poorer families produce more daughters (Luo et al. 2017). However, others report no evidence of sex ratio bias by socioeconomic status, even in large samples (Kolk and Schnettler 2016; Morita et al. 2017). Reviewing over 400 mammalian studies, Cameron (2004) concluded that support is strongest in studies assessing maternal body condition close to conception, suggesting the effect is real, albeit highly sensitive to the measure of condition considered. If variance in physical health is crucial to the mechanism by which sex ratio is altered, this may explain why no effect is often found among well-nourished populations where health differences are relatively small. Wells (2000) argues that the higher mortality of male newborns may itself be understood as a Trivers–Willard mechanism, ultimately making unhealthy mothers, who more likely to lose a child, less likely to rear sons (Wells 2000). Whether postnatal care is predicted to follow a Trivers–Willard pattern has been a point of persistent confusion (Keller et al. 2001; Veller et al. 2016). This is because the comparative fitness value of having a son versus a daughter can vary independently of the marginal fitness returns of investing in current offspring of either sex. Following Trivers and Willard (1973), a mother with poor access to resources would achieve higher fitness by rearing a daughter rather than a son. However, considering a mother of the same condition with both a son and a daughter already in her care, postnatal investments should be biased in favor of the son, because under the Trivers–Willard model, each unit of investment will have a larger impact on male reproductive success. Hence, provided males do indeed benefit more from increases in investment, a bias in postnatal care favoring males is predicted independent of parental wealth (Keller et al. 2001). Complications to this argument arise because the line between sex ratio bias at birth and postnatal care is blurred, such as when lowering parental care increases risk of offspring death.

11.5.3 Are Males the Preferred Sex? If a broad generalization is to be made of humans, then the general pattern surely attests to widespread care biases favoring sons over daughters. In dowry-practicing cultures, economic transfers to secure marriage partners for daughters can be substantial, but across the ethnographic record, preferential wealth inheritance to sons is near-ubiquitous (Hartung 1997). Studies of time allocation to childcare report evidence of son favoritism across an array of cultural contexts, although differences are often modest and often appear driven primarily by discriminatory investment from fathers (e.g., Nettle 2008; Lawson and Mace 2009; Hassan et al. 2019; Figure 11.6).

https://doi.org/10.1017/9781108377911.012 Published online by Cambridge University Press

Parental Care

275

Figure 11.6 Sex differences in parental care in rural Mwanza, Tanzania. Mothers spend more

time engaged in all forms of direct childcare compared to fathers. While mothers care equally for sons and daughters, fathers are more likely to engage in several forms of direct care with their sons. Similar patterns have been documented in other populations (see main text). Presented data show the percentage of children reported to receive material resources in past three months and direct/physical care in past two weeks from their biological fathers and mothers, by child’s sex from a sample of 800 children. “Sick” refers to caring for a child who had been sick during the last two weeks (215 of the sampled children). See Hassan et al. (2019) for details.

Some studies find evidence of sex-matching in preferences, with mothers preferring daughters and fathers preferring sons (Nikiforidis et al. 2018). Dahl and Moretti (2008) present particularly striking evidence of son-preference in the United States: Women with firstborn daughters are less likely to marry the father; parents who have firstborn girls are significantly more likely to be divorced; and after a divorce, fathers are more likely to obtain custody of sons compared to daughters. Across low- and high-income populations, parental investment in educating daughters has historically lagged behind investment in sons, though this gap has lessened and even reversed in recent cohorts (Grant and Behrman 2010). Whether relatively high parental investment in sons is profitable for parents is less well studied, but there is some evidence that males are more likely than females to translate educational investment into high adult incomes and reproductive success (Pink et al. 2017).

11.5.4 Where Daughters Are Advantaged Preferential treatment of males is not universal. Human behavioral ecologists have documented numerous instances of apparent daughter preference, sometimes going

https://doi.org/10.1017/9781108377911.012 Published online by Cambridge University Press

276

David W. Lawson

against stated preferences (Cronk 1991b; Holden and Mace 2003a; Quinlan 2006; Du and Mace 2018). Some of these cases fit a Trivers–Willard-like pattern with lowsocioeconomic-status families favoring daughters. Among the relatively poor Mukogodo of Kenya, for example, Cronk (1993) found that daughters receive more frequent breastfeeding and better medical care than sons. This was interpreted as an adaptive strategy because daughters had better marital prospects and reproductive success than their brothers, who are not sought after as husbands due to their low social position. In an experimental study, Durante et al. (2015) report that in hypothetical investment decisions, parents prefer daughters over sons when considering economic recessions. Other studies find no evidence of a Trivers–Willard pattern in postnatal parental investment (e.g., Keller et al. 2001; Hassan et al. 2019). Trivers–Willard is not the only potential explanation for daughter-biased care. Hamilton (1964) recognized that selection will favor biased investment in the sex more likely to cooperate with parents over local resources (Griffin et al. 2005). Such dynamics have been proposed to account for higher investment in daughters in populations where daughters are especially active alloparents to younger siblings (Margulis et al. 1993; Bereczkei and Dunbar 1997, 2002), and higher investment in sons where they are particularly important in contributing calories to the household (Hewlett 1991a). By extension, the compatibility of children’s work and some forms of parental care may also influence investment decisions. Among agropastoralist populations in Tanzania, for example, daughters are more likely to be in schools than sons, a pattern potentially attributable to girl’s household work being more compatible with school attendance compared to herding activities for boys (Hedges et al. 2016, 2018). Female educational attainment is now greater than males in many high-income populations, dramatically reversing historical trends (Grant and Behrman 2010; McDaniel 2012). Along with the growing involvement of women in labor force, one important explanatory factor appears to be that males from socioeconomically deprived households are more vulnerable to educational dropout due to mental health issues (McDaniel 2012). Importantly, this line of explanation does not imply that biases in parental care are involved, but rather implicates unrelated gender differences in development and behavior. Such reasoning serves as a reminder that differences in child outcomes are imprecise proxies for parental care.

11.6

Relatedness and Parental Care

11.6.1 Care by Stepparents Kin selection theory (Hamilton 1964) predicts that relatedness will be a critical determinant of parental care, leading to a literature addressing situations where non-biological parents rear children. This occurs under three main scenarios, including stepparent families, where a child lives with one biological parent (usually the mother) and one stepparent (usually a father figure) aware that the child is not their biological kin. Behavioral ecologists have reported data from a range of societies

https://doi.org/10.1017/9781108377911.012 Published online by Cambridge University Press

Parental Care

277

indicating that father figures allocate less time to stepchildren (Marlowe 1999; Lawson and Mace 2009). Mothers have also been found to allocate less time to childcare in the presence of stepfathers, possibly representing a maternal trade-off between parenting and mating effort (Lawson and Mace 2009). Stepparents also often have relatively antagonistic relationships with children (Flinn 1988b; O’Connor and Boag 2010). Daly and Wilson (1985) famously documented that North American children are more likely to suffer abuse and even homicide in the presence of a stepparent, a finding known as the “Cinderella effect” (Daly and Wilson 1998; Tooley et al. 2006). This effect remains even in well-controlled analyses, although the risk of homicide may have been overestimated in Daly and Wilson’s original study (Nobes et al. 2018). These findings are supportive of kin selection theory, but there are caveats. First, “absent” (i.e., nonresident) fathers may still be investing in the child, so that less care from the stepparent may simply reflect the fact that additional care is not necessary. Indeed, if children in stepparent households retain contact with their biological father and receive care from both their stepfather and their biological father, it is feasible that they receive more care in total. We need more studies that integrate measures of care from multiple caregivers to explore this possibility. Second, adults in different types of families differ in their general disposition for violence, with stepparents more generally prone to violent behavior rather than specifically child abuse (Temrin et al. 2011). One recent study confirms that men with stepchildren are both more likely to commit child abuse and have greater antisocial tendencies; however, even taking this account, parents are more likely to assault stepchildren than their biological children (Hilton et al. 2015).

11.6.2 Care When Paternity Is Uncertain The second scenario under which parents care for non-biological children is when putative fathers care for a child where paternity is uncertain or incorrectly assigned. In many taxa, males do not abandon young or reduce care when they are cuckolded by other males. In species with relatively low risk of cuckoldry, this can be explained, because fathers risk a serious cost if they desert their own young. It may, therefore, take a substantial cuckoldry risk to influence paternal care strategies (Griffin et al. 2013). Cross-cultural evidence suggests that paternity uncertainty is often notable in humans (Scelza et al. 2020b), and there is evidence that fathers use multiple cues to estimate kinship in cases of uncertainty (Box 11.3). Societies with relatively low paternity confidence are characterized by low levels of paternal involvement and inheritance from paternal relatives (Gaulin and Schlegel 1980; Hartung 1985). Within populations, there is also evidence that cues of nonpaternity predict lower paternal investment. In one study, English men that reported low father–child resemblance or high perceptions of mate infidelity also reported lower investment in their children (Apicella and Marlowe 2004). In Senegal, children that look and smell less like their putative fathers (as rated by third-party judges) receive less care and tend to be in poorer health (Alvergne et al. 2009a). In Chinese

https://doi.org/10.1017/9781108377911.012 Published online by Cambridge University Press

278

David W. Lawson

Box 11.3

How Do We Recognize Kin?

Relatedness fundamentally determines the incentives for altruism, including parental investment, yet is always uncertain between fathers and children, and between siblings. These observations have led to considerable interest in the heuristic cues used to estimate relatedness by putative family members. For fathers, perceived sexual fidelity of women can be important in evaluating paternity confidence and investment decisions, leading to widespread behavior aimed at regulating female sexuality (Strassmann 1992; Smuts 1992; Howard and Gibson 2018). More generally, social cues (i.e., who is said to be related) provide easily accessible information. However, such cues are very open to strategic deception, including via malicious gossip. Evidence for deceptive tactics comes from the observation that parents of newborns are more likely to be informed by others that their child looks like the father than like the mother, a behavior consistent with attempts to limit paternity uncertainty (Daly and Wilson 1982). More honest cues of relatedness are available. Most obviously, phenotypic similarity can be directly assessed. Humans are apparently quite capable at correctly matching fathers and biological children via phenotypic resemblance, particularly facial resemblance (Bressan and Grassi 2004; Alvergne et al. 2009a). There is also evidence that men in particular are more anxious about facial similarity than women (Yu et al. 2016), and are better able to recognize similar faces (Wu et al. 2013). Furthermore, phenotypic resemblance has been shown to predict paternal investment decisions (see main text). We can also expect siblings to be attentive to cues of relatedness, since both shared maternity and paternity are in question. Accordingly, facial resemblance has been shown to predict altruistic tendencies between siblings (Lewis 2011). One additional type of cue available to putative siblings is contextual information regarding shared rearing environments. Both coresidence during childhood and “maternal perinatal association” (i.e., witnessing a child being cared for by one’s mother) provide useful information about likely relatedness. Experimental studies demonstrate that these cues independently predict both altruistic tendencies and sexual aversion among siblings (to safeguard against incest) (Lieberman et al. 2007). Among younger siblings, who may lack cues to maternal perinatal association, most weight appears to be placed on coresidence duration in judging relatedness (Lieberman et al. 2007).

schoolchildren, facial resemblance is positively associated with the quality of parent–child relations among fathers, but not among mothers, indicating men are especially sensitive to relatedness (Yu et al. 2017). In the United States, children reported to look like their father receive more investment and have better health in infancy (Tracey and Polachek 2018).

https://doi.org/10.1017/9781108377911.012 Published online by Cambridge University Press

Parental Care

279

11.6.3 Fostering Finally, children may live away from both biological parents, who may be living or dead. Fostering (i.e., permanently or temporarily raising children that are not one’s biological offspring) is common in many societies worldwide (Silk 1980; Scelza and Silk 2014). Out-fostering may bring a number of benefits to the biological parents, including forming advantageous alliances with other households, alleviating resource scarcity, or adjusting the household sex ratio (Goody 1982; Franklin and Volk 2016). Among the Himba, Scelza and Silk (2014) found that out-fostering children was associated with higher maternal reproductive success, but increased risk of stunting and being underweight for foster children. The wider literature reveals that in many cases the well-being of fostered children is indistinguishable from children living with both biological parents (Lawson et al. 2017b; Hedges et al. 2019b). Indeed, some studies suggest that fostering can actually facilitate access to schooling (Eloundou-Enyegue and Shapiro 2002; Akresh 2004). Why do foster parents care, and why are foster child outcomes often equal or better that of non-fostered children? The most obvious answer is that fostering is almost always carried out by close relatives, especially grandparents (Silk 1980; Franklin and Volk 2016). Fostering a genetically related child may increase a foster parent’s inclusive fitness. It is also consistent with the observation that foster children’s wellbeing is most likely to be unaffected when they reside with close rather than distant relatives (Franklin and Volk 2016). In a Sukuma population in Tanzania, for example, only children living with distant kin, but not close kin, received lower educational investment than children living with their biological parents (Hedges et al. 2019b; Figure 11.7). However, genetic relatedness is still higher between biological parents and child, compared to grandparents and grandchild, or aunt/ uncle and niece/nephew. As such, this explanation cannot completely explain why the well-being of fostered and biological children is often indistinguishable; by the same logic, biological children should be prioritized within fostering households. A complementary explanation is that in contexts where households largely produce their own food, fostered children can work to offset their own costs, and may even be regarded as an economic asset (Abebe 2012). Several ethnographic accounts of fostering describe households recruiting children in order to meet work demands, helping older or childless individuals, or assisting with farmwork [i.e., “purposive fostering” (Hampshire et al. 2015)]. Time allocation studies also suggest fostered children work harder than children living with both biological parents (Fafchamps and Wahba 2006; Assaad et al. 2010). In Hedges et al. (2019b), fostered children in Tanzania were more likely to report doing farmwork in the previous week than other children, but time allocation to work activities did not differ during school days, minimizing trade-offs with school attendance.

11.7

Appraisal Over the last fifty years, human behavioral ecologists have studied parental care as (i) a life history trait, and thus a fundamental component of reproductive effort subject

https://doi.org/10.1017/9781108377911.012 Published online by Cambridge University Press

280

David W. Lawson

Figure 11.7 Fostering and child schooling in rural Mwanza, Tanzania. Fostering is very common

among Sukuma families in rural Tanzania. Children living with close kin (mostly grandparents) had very similar levels of school enrollment, educational achievement, and progression to secondary school as children living with their biological parent(s). However, children living with more distant kin had poorer educational outcomes across all three measures. Data come from a survey of over 1,000 children, 95% confidence intervals are shown. See Hedges et al. (2019b) for details.

to trade-offs in resource allocation; (ii) a conflict trait, with conflict dictated by divergence in optimal allocations of parental care within the family; and (iii) a behavior strategically guided by the costs and benefits of investing in alternative categories of offspring (e.g., by birth order, sex, or relatedness). This work has transformed understandings of the human family, exposing the fragile mix of cooperation and competition that underlies family relationships. This chapter concludes with a few recommendations for future research. The first is to achieve greater rigor in the quantification of parental care. One way this can be achieved is via more studies directly measuring parental behavior across its multiple dimensions, across all stages of offspring dependency, and across cultures. Variation in parental care is too often assumed from studies only measuring offspring outcomes, introducing opportunities for false inference. For example, a demonstration that high fertility is associated with low child survival is consistent with a life history trade-off between offspring quantity and quality, but diluted parental care is only one

https://doi.org/10.1017/9781108377911.012 Published online by Cambridge University Press

Parental Care

281

possible mechanism that could lead to such an association (alternatives include replacement births, insurance births, or confounding variables) (Lawson and Borgerhoff Mulder 2016). Likewise, a demonstration that girls achieve higher educational attainment or experience less growth stunting than boys is superficially consistent with daughter-biased care, but greater male vulnerability to disease or school dropout may provide more feasible explanations (Wamani et al. 2007; Mcdaniel 2012). To date, we have also achieved only a limited understanding of the extent to which alternative forms of parenting behavior (Table 11.1) meet Trivers’ definition of parental investment – that is, truly costly to parents and beneficial to offspring (see also Alonso-Alvarez and Velando 2012). Illustrating this point, recent research questions the assumption that time-intensive parenting actually benefits children (Milkie et al. 2015). This indicates that parents may be responding to perceived rather than actual benefits of childcare, or that factors beyond the returns to care drive parental behavior (e.g., signaling mate quality or commitment to a mate). Second, shifts in topical focus are overdue. In recent years, the study of family conflict (Figure 11.1) has been extremely active in nonhuman behavioral ecology (Royle et al. 2012, 2016; Smiseth and Royle 2018). The study of human parental care as a conflict trait could also be developed, especially with respect to sexual conflict. In humans, sexual conflict is more often discussed in relation to mating strategies than parenting behavior per se (e.g., Buss 2017). A shift in the right direction is recent work considering the hypothesis that women and men disagree over optimal fertility rate, with males preferring strategies of relatively high fertility at the expense of parental investment per offspring (Borgerhoff Mulder and Rauch 2009; Moya et al. 2016). Drawing primarily on Lessells (2012), Table 11.2 provides examples of additional hypotheses regarding sexual conflict over parental care that have received only limited attention in HBE; I hope that highlighting these ideas will stimulate further research. One potential explanation for the slow uptake of recent developments in sexual conflict theory is the “disco problem,” a term West et al. (2011) use in observation that behavioral ecologists working on humans and nonhumans have operated somewhat separately since the 1970s, and as a result, human research is relatively isolated from theoretical advances in evolutionary biology. Consistent with this explanation, sexual conflict research only really took off in the late 1980s onward. Whatever the case, future work in this area could offer fresh insights into the evolution of human parental care strategies (see also Borgerhoff Mulder and Rauch 2009). Finally, arguably the biggest gains remain to be made by continuing to draw on HBE’s close ties to anthropology via the comparative study of family life across cultures. We still know little, for example, about childcare differences between monogamous and polygynous families (Lawson and Gibson 2018), whether birth order influences child cognitive and social development in small-scale societies (Draper and Hames 2000), and how relatedness influences sibling relationships and kin recognition in societies with high rates of polygyny or fostering (Janowiak and Diderich 2000). Addressing such diversity is critical not just in deriving an accurate natural history of the human family, but also in countering widespread assumptions that the nuclear family is universally normative and somehow the optimal state for

https://doi.org/10.1017/9781108377911.012 Published online by Cambridge University Press

282

David W. Lawson

Table 11.2 How does sexual conflict influence parental care? Hypothesis

Supporting evidence/example

Reference(s)

Parents manipulate each other into increasing care via exploiting signaling systems

In birds, females may reduce egg size in the presence of a male and/or deposit yolk androgens that modulate offspring begging behavior, altering the male’s perception of offspring need, thereby increasing male contributions to care In some polygynous bird species, females have been observed preventing their mates from remating and killing offspring from his other broods In penduline tits, desertion by one or both sexes is common. Females increase the chance of being able to desert first by hiding eggs in nesting material during laying Females may strategically over exert themselves by producing large clutches that leave her unable to successfully care for a clutch alone, incentivizing male care In Zebra finches, females rearing offspring alone provide greater overall parental investment compared to when both parents work together to provision offspring Support primarily comes from theoretical modeling

(Müller et al. 2007; Paquet and Smiseth 2017)

Parental care from a mate can be increased by sabotaging their opportunities to invest resources in alternative existing or future offspring Desertion can be used as a strategy to increase parental care from a mate, leaving them “holding the baby”

“Self-handicapping,” making care less possible, can be used to incentivize the other mate to care

Negotiation over repeated bouts of parental investment reduces overall care provided to offspring

Task specialization over parental care (i.e., mothers and fathers provide unique investments) reduces sexual conflict and need for negotiation behavior

(Sandell and Smith 1996; Hansson et al. 1997) (Valera et al. 1997)

(Houston et al. 2005)

(Royle et al. 2002; Lessells and McNamara 2012) (Lessells 2012)

child-rearing (Lawson and Uggla 2014; Sear 2018). Moreover, much remains to be learnt about the coevolution of parental care patterns and culturally variable beliefs about the family, including diverse kinship terminology (Jordan 2011; Fortunato 2012; Cronk et al. 2019), theories of reproduction (e.g., Hrdy 2000; Walker et al. 2010), and ideas of personhood (i.e., the point at which an infant or child becomes fully recognized as a person) (Lancy 2014). Human behavioral ecology, in collaboration with related approaches to cultural evolution and adaptation, is uniquely positioned among the social and natural sciences to address these questions.

https://doi.org/10.1017/9781108377911.012 Published online by Cambridge University Press

12 Allocare Karen L. Kramer

Human mothers rarely raise children on their own. Rather, others commonly help support their children. Biologists refer to this reproductive system as “cooperative breeding,” which is found across relatively few but diverse taxa. Because cooperative breeding is not a trait shared with other great apes, its emergence in the human lineage marks a significant departure in reproductive and parenting strategies that has far-reaching consequences for human life history, sociality, and the demographic success of our species. Mothers and children benefit from the assistance of others in numerous ways. However, recruiting help is not simple (Hamilton 1964; West et al. 2007), setting up the central evolutionary problem of cooperative breeding: How and why do individuals spend valuable time and energy helping to support another’s offspring? Much of what has been theoretically developed to solve this puzzle has been established in the nonhuman literature. This provides a useful framework to consider what becomes the characteristically human pattern of shared parenting. But it also raises a challenge, because, although humans share many traits in common with other cooperative breeders, they are atypical in several key ways. This chapter addresses these and other points about the unifying characteristics of cooperative breeding species and how humans fit in. What are the benefits of help to mothers and their offspring, and how do helpers overcome the costs and obstacles of helping? Who are the key helpers, and what do they do? Why cooperative breeding developed in humans but not in other great apes is also considered, as are some of the downstream life history and cognitive effects of cooperatively raising children. Examples focus on research in natural fertility and small-scale societies because they more closely represent the high-fertility, high-mortality demographic conditions in which cooperative childrearing became a predominant human strategy. The last section then turns to the implications for cooperative breeding following the modern demographic transition. Because cooperative breeding is unusual among hominoids, its evolution brings together ideas about life history, our cooperative nature, group and family structure, and other traits that characterize human modernity.

12.1

Foundational Knowledge

12.1.1 What Is Cooperative Breeding? Cooperative breeding is variously defined in both the nonhuman literature, where the concept originated, and the human literature (see Clutton-Brock 2006 for a

https://doi.org/10.1017/9781108377911.013 Published online by Cambridge University Press

284

Karen L. Kramer

discussion of cooperative breeding classifications). It is used in this chapter in its general sense as a reproductive and social system in which individuals other than parents (referred to as alloparents) help to raise offspring who are not their own. Cooperative breeding has evolved numerous times across various taxa, including in insects, spiders, crustaceans, fish, birds, and mammals (Emlen 1991 [1978]; Solomon and French 1997; Koenig and Dickinson 2016). Although expressed in diverse taxa, cooperative breeding is relatively rare, occurring in only an estimated 9% of birds (Cockburn 2006) and 3% of mammalian species (Russell 2004).1 In mammals, cooperative breeding is predominantly found in wild canids, carnivores, meerkats, rodents, and primates. Among primates, reproductive cooperation is best documented for humans, tamarins, and marmosets (McKenna 1987; Tardif 1997). Although care by nonparents occurs across a range of other primate species (Mitani and Watts 1997; Ross and MacLarnon 2000), cooperative breeding is not a nonhuman great ape-reproductive strategy (Lancaster and Lancaster 1983; Hrdy 2005a), and therefore, its emergence is relevant to hominin evolution. Who helps mothers and their young varies considerably across cooperative breeders. In birds, helpers are usually sexually mature siblings, as they are in some mammals (Russell and Lummaa 2009). Among the eusocial insects, Hymenoptera (bees, wasps, ants) helpers tend to be either fertile or sterile adults (Hughes et al. 2008), while Isoptera (termites) juveniles are likely to help (Boomsma 2013). In many cooperative breeding mammals, juvenile helpers are typical (Clutton-Brock et al. 2002; Russell 2004; Gilchrist and Russell 2007; Russell and Lummaa 2009), as they are in humans (Kramer 2011, 2014). While food transfers to grandoffspring are exceedingly rare in wild populations, exceptions are found among pilot and killer whales (Croft et al. 2015) and African elephants (Péron et al. 2019), and grandmaternal investments are common in human societies (Hawkes et al. 1997). The investment of fathers (social or biological) in their offspring is also well documented across human societies and is associated with improved survivorship, well-being, and maternal fertility (Gurven and Hill 2009; Meehan et al. 2013; cf. Sear and Mace 2008 for discussion of the facultative nature of paternal investment). Among evolutionary biologists, however, biparental care is usually subsumed under parental investment theory rather than cooperative breeding (Clutton-Brock 1991; Lukas and Clutton-Brock 2012). Following this convention, this chapter focuses on nonparental helpers, and their effects on mothers and her offspring, while Chapter 11 addresses parental care and the role of fathers.

12.1.2 How Humans Fit in as Cooperative Breeders Although cooperative breeding systems vary across species, two commonalities are widely shared. First, nonparental individuals who provide care are currently not 1

Estimates vary depending on how narrowly or broadly cooperative breeding is defined. About 1% of mammals are estimated to be cooperative breeders if cooperative breeding is specified as “systems where a small number of breeding individuals are reared by nonbreeding helpers or workers” (Clutton-Brock and Manser 2016:294). When cooperative breeding is more broadly defined, an estimated 3% of mammals are cooperative breeders (Russell 2004).

https://doi.org/10.1017/9781108377911.013 Published online by Cambridge University Press

Allocare

285

breeding (Brown 1987; Emlen 1991 [1978]; Russell 2004) either because they are not yet mature (juveniles), are permanently sterile (sterile workers, post-fertile females), or because they are temporarily constrained from breeding (sexually mature, but nonreproducing helpers). The second commonality, one that distinguishes reproductive help from other forms of cooperation, is that helping behaviors are directed toward another’s offspring or toward mothers to facilitate reproduction now or in the future. Human child-rearing, however, also differs from other cooperative breeding systems in several key ways (Hrdy 2009; Kramer 2010; Crespi 2014). First, although humans might best be described as cooperative breeders (Clutton-Brock 2006), they also incorporate elements of communal breeding (Box 12.1). Beside nonbreeders, other mothers may help women raise their children, a trait of communal breeding. While human reproductive support is diverse and flexible, cooperative breeding is used throughout this chapter as the best term to encapsulate common usage of a reproductive system where mothers rely on others, without diluting too much of its theoretical intention as developed in evolutionary biology. Second, female reproductive skew, which is an essential feature of cooperative breeding in some definitions (Lukas and Clutton-Brock 2012), is comparatively low in humans (Betzig 2012). In some species of cooperatively breeding birds and mammals, one or a small group of dominant females monopolize reproduction, and subordinate females help to raise their offspring (Clutton-Brock 1998; Johnstone 2000; Magrath et al. 2004). These dominant females often have unique physiological or behavioral traits, and aggressively suppress the breeding efforts of subordinate females. Among African meerkats, for instance, dominant females produce about 80% of the group’s litters (Clutton-Brock et al. 2001b; Grueter et al. 2012). Female skew is not characteristic of human sociality. Instead, we live in multilevel groups with multiple breeding females, referred to as plural breeding in the cooperative breeding literature (Grueter et al. 2012). Some have argued that reproductive senescence in human females is a case of reproductive suppression and coercion (Cant and Johnstone 2008; Mace and Alvergne 2012). While compelling as an explanation for grandmothering, we first have to rule out that menopause is simply explained by the deep ancestral mammalian pattern of age-related atresia. Across mammals, the cessation of reproductive function is pleiotropically linked to restricted oocyte production, in which humans do not appear to be biologically exceptional (Ellison 2001; Walker and Herndon 2008). Thus, the question for humans becomes not why reproductive function declines but why life span is extended. An important consideration in placing humans in the context of other cooperative breeders is that most theory building has been developed in biology, based initially on bird models (Brown 1987; Skutch 1987; Emlen 1991 [1978]; Koenig and Dickinson 2004), subsequently applied to mammals and only relatively recently to humans (see Russell 2004). Originally, attention was focused on nonbreeding, sexually mature helpers, who present a particularly thorny evolutionary problem. Not only does cooperation have to be explained (i.e., why an individual expends

https://doi.org/10.1017/9781108377911.013 Published online by Cambridge University Press

286

Karen L. Kramer

Box 12.1

Are Humans Cooperative or Communal Breeders?

Cooperative and communal breeding are variously defined in both the nonhuman and human literature, which has led to unfortunate confusion. In this chapter, I refer to Lukas and Clutton-Brock’s (2012:1) distinction: “in a small proportion of species, breeding females either pool their young and share care and provisioning (communal breeders), or are assisted in protecting and feeding their offspring by non-breeding helpers (cooperative breeders).” Communal breeders appear to derive from different phylogenetic lineages, mating systems, and evolutionary pathways than cooperative breeders, and are associated with species such as mice, bats, elephants, whales, and social carnivores. In communal species, mothers may band together during the breeding season or live in groups of plural breeders, and they may pool young into nursery groups or crèches for warmth or protection. Communal babysitting occurs in some species (primates, whales, cats, coatis are examples) when one or more mothers stay with the nursery group, while others are absent. In these cases, breeding females often provide little direct care to nonoffspring (Lewis and Pusey 1997). However, mothers mutually benefit from group-size effects on offspring survival through enhanced social thermoregulation or protection from predators or infanticidal conspecifics. A notable exception is allonursing, which is more common in species that roost together (bats), are communal reproducers (social carnivores, rodents), bear young in confined spaces (seals), or give birth to large litters (Packer et al. 1992). The frequency of allonursing, however, is usually rare in these species. Various forms of these behaviors occur in humans. Mothers may care for the young of another, or form nursery groups. Communal care of non-offspring by other mothers is known, for example, among Shingu River native South Americans and Australian Aborigines; however, these helpers are less common than nonreproductive helpers, such as juveniles and grandmothers. Allonursing is noted in many societies, but it is a normative behavior in relatively few (Hewlett and Winn 2014). Among hunter-gatherers, allonursing is commonly observed among the Aka and Efé (Congo River hunter-gatherers), occurs, albeit rarely, among the Savanna Pumé (South American huntergatherers), and is absent in the !Kung and Hadza (for an overview, see Hewlett and Winn 2014). Communal breeding in the animal literature is usually associated with minimal and indirect care. Although mothers help each other in human societies (as mentioned previously), many others do as well, nonbreeders in particular. Because human reproductive help is often direct and provided by nonbreeders and other reproductive-aged individuals, cooperative breeding seems to be the most inclusive moniker to situate humans.

https://doi.org/10.1017/9781108377911.013 Published online by Cambridge University Press

Allocare

287

time and energy helping), but also why individuals delay or forgo their own reproduction to do so. Although the reasons are widely debated, most biologists concur that some group dynamic, ecological, or life history factor gives rise to sexually mature individuals benefiting from staying in their natal group. Benefits may include fitness gains, improvements to their own survival, coercion, or ecological constraints (Emlen 1995; Hatchwell and Komdeur 2000; Clutton-Brock 2002; Hatchwell 2009; Sparkman et al. 2011).2 In human studies, the postponement of marriage and low marriage rates in historic Europe have been associated with constraints in the land or wealth required to attract mates (Boone 1988; Clarke 1993; Strassman and Clarke 1998). Although great strides have been made in understanding why sexually mature helpers help, evolutionary biology’s focus on them as helpers has detracted from thinking more broadly about the costs and benefits for other nonbreeders to help (e.g., juveniles, grandparents). For example, subadult helpers are well documented in eusocial species, birds, fish, and mammals, including primates (Emlen 1990; Fairbanks 1990; Alexander et al. 1991; Solomon 1991; Gursky 2000; CluttonBrock et al. 2002; Taborsky 2016). However, juveniles are seldom the target of investigation or theory building, perhaps because they present less of an evolutionary puzzle than do sexually mature helpers. A fourth substantive difference between human and nonhuman cooperative breeders is that humans assist not only infants but also juveniles. One reason cooperative breeding is suggested to be uncommon among mammals is because the dependence of young generally terminates at weaning, which limits the needs and opportunities for help (Russell 2004). Because humans provide food, shelter, and protection through the juvenile stage, it introduces a wide range of potential helping behaviors not seen in other cooperative breeders. Importantly, assisting a nursing infant versus a weaned juvenile has very different implications for the cost of helping (Kramer 2011). Primary among these divergent costs is that infant care requires helpers to spend time in activities that they would not otherwise do for themselves, such as carrying, holding, feeding, and babysitting. In contrast to infant care, because juveniles consume adult foods and resources, helpers can integrate provisioning into their own daily routines. For instance, a portion of the wild roots that a foraging 10-year-old collects is consumed by herself, and a portion is consumed by her parents and younger siblings. However, the time she spends holding or carrying her young brother is an added time and energy expenditure. While infants are too young to reciprocate, juveniles produce, process, and share food with others, and they are important contributors to domestic tasks (fetching water and firewood, washing, etc.) in most preindustrial societies (Blurton Jones et al. 1994b; Hawkes et al. 1995; Kramer 2005b, 2014; Tucker and Young 2005; Crittenden et al. 2013). 2

Subsequent studies pointed out that staying in one’s natal group does not necessarily imply that these individuals help and that explanations for staying and helping might be different (Bergmüller et al. 2007; Cockburn 1998; Russell 2004).

https://doi.org/10.1017/9781108377911.013 Published online by Cambridge University Press

288

Karen L. Kramer

This means that at least part of the cost to help a juvenile is recouped or offset, because juveniles give back (Kramer 2011). This point, though obvious, is not well incorporated into ideas about the cost of reproduction, the cost of children, and evolutionary explanations for human pair-bonding, male parental care, or the sexual division of labor. In sum, cooperative breeding has much to offer as a framework to think about reproductive cooperation and to explain the human life history of early weaning, short birth intervals, high fertility, and a long juvenile period. When applying cooperative breeding approaches to humans, it is important to keep in mind that much of the theorizing originated in biology to explain care directed toward hatchlings and infants and to explain the cooperation of nonbreeding sexually mature helpers. Consequently, several key elements of human cooperative breeding – the role and implications of help from juveniles, grandmothers, and other reproductive-aged kin and nonkin – are largely unaddressed in the nonhuman behavior ecology literature. In studying human behavior, our charge then is to expand existing theory and empirical research to generate new hypotheses and predictions that address this gap and explain the diversity of child-rearing networks.

12.1.3 Notes on Terminology Throughout, allocare and allocaretaker are used when referencing infant care, and help and helper more generally refer to either childcare or economic aid directed toward mothers and children. Alloparent refers to nonparental helpers and allomother to nonmaternal helpers. Infant refers to a nursing child, and juvenile is used in the general mammalian sense for an individual from weaning to sexual maturity. An adult refers to a reproductive-aged individual. Child and children are used as general terms for all subadult states. Consistent with other analyses of human childcare, infant care is subset into direct care and indirect care. Direct care refers to intimate childcare behaviors that imply close physical proximity, which includes nursing, feeding, carrying, holding, and grooming (dressing, bathing, delousing, minor medical tasks). Indirect care refers to behaviors such as walking alongside a child, laying in a hammock with a child, playing with a child, talking to a child, comforting a child, watching, or keeping a child out of trouble.3

12.2

The Evolutionary Puzzle of Cooperative Breeding

12.2.1 Benefits of Help to Mothers and Offspring Generally across taxa, the help that mothers receive benefits them by redistributing the cost of raising young, which may have a positive effect on maternal fertility or offspring outcomes. For example, among meerkats, the number of helpers per pup 3

Note that direct and indirect childcare are both forms of direct investment, sensu Kleiman and Malcolm (1981). Indirect childcare should not be confused with indirect investment, which refers to territory defense, nest construction, resource provisioning, and other similar behaviors (Kleiman and Malcolm 1981).

https://doi.org/10.1017/9781108377911.013 Published online by Cambridge University Press

Allocare

289

has a positive influence on pup food intake and daily rates of weight gain (CluttonBrock and Manser 2016). In nonhuman primates, allocare is associated with accelerated infant growth, shorter weaning times, and faster reproductive rates (Fairbanks 1990; Mitani and Watts 1997; Ross and MacLarnon 2000). In several species of callitrichid monkeys, the number of helpers in a group is associated with increased infant survival and decreased energetic burden on parents (Bales et al. 2000). If helpers transport young, as they commonly do in primates, then mothers can forage more efficiently and reallocate energy from carrying to lactation and reproduction (Hrdy 1977; Goldizen 1987; Koenig 1995; Tardif 1997; Bales et al. 2000). Human mothers and children have been shown to benefit from cooperative childrearing in two important ways. First, it alleviates maternal time constraints of simultaneously raising both younger and older children, a distinctive human life history feature. For example, among the Aka (hunter-gatherers) and Ngandu (agriculturalists) of Central Africa, mothers hold their infants less when engaged in work, and allomothers effectively offset this decrease in maternal care (Hewlett et al. 2000; Meehan 2009). In managing the competing demands of supporting younger and older children, nursing mothers tend not to compromise direct infant care. In a number of ethnographic cases, mothers find the extra time to care for a newborn by downwardly adjusting their investment in economic activities (Hurtado et al. 1985, 1992; Hames 1988; Hawkes et al. 1997; Kramer 2009). For instance, among Maya subsistence farmers (Yucatan, Mexico), mothers with young nursing infants spend no time working in their fields, which is an investment in food production that benefits older children and requires mothers to leave their infants at home (Kramer 2009). To compensate for their reduction in agricultural work, husbands and older children increase their effort. In other cases, caretakers allow nursing mothers to increase the time spent in economic activities (Ivey et al. 2005). Second, cooperation is associated with positive fitness outcomes, since help from others can have important mitigating effects in permitting mothers to reproduce at a faster rate without compromising child survival (Hrdy 1999a; Kramer 2005b). Using demographic variables as proxies for the help available to mothers, case studies and meta-analyses indicate that the presence of potential helpers in a household (either a grandmother or older siblings) is associated with higher fertility (Draper and Hames 2000; Crognier et al. 2001; Lahdenpera et al. 2004) or improved probabilities of child survival when controlling for other variables that may affect mortality (Sear et al. 2002; Leonetti et al. 2005; Mace and Sear 2005; Sear and Mace 2008; but see Voland and Beise 2002; Strassman and Kurapati 2010). While demographic studies often utilize historic and large-scale census data, behavioral observations provide detailed accounts of what helpers actually do and their effects on maternal fitness. Behavioral observation studies show that labor substitution by sons and daughters saves mothers considerable time and effort, which is associated with higher maternal fertility and improved sibling outcomes (Turke 1988; Bereczkei 1998; Bove et al. 2002; Lee and Kramer 2002; Kramer 2005a, 2009). For instance, the economic contributions of older Maya children not only offset a substantial portion of their own costs, but early-born children enable their

https://doi.org/10.1017/9781108377911.013 Published online by Cambridge University Press

290

Karen L. Kramer

mothers to continue childbearing when parents exceed the time they have available each day to support their family (Lee and Kramer 2002). Among the Aka of the Central Africa Republic, allocare provided to young children reduces a mother’s energy expenditure by up to 216 kcal over a 9-hour period (Meehan et al. 2013), a caloric savings that can be directed to other reproductive goals. In addition to these benefits, reproductive cooperation appears to have important cognitive and emotional benefits for children. Exposure to multiple caretakers expands a child’s social sphere and is associated with cognitive and psychological benefits (Weisner and Gallimore 1977; Wilson 1986; McKenna 1987; Pope et al. 1993; Burkart et al. 2009; Isler and van Schaik 2012). Cooperative child-rearing also has important implications for the development of prosociality (van Schaik and Burkart 2010; Isler and van Schaik 2012), and it is a vital factor in learned sociability (Hrdy 2001; Gottlieb 2009).

12.2.2 Why Helpers Help As a cooperation problem, we have to square evidence across taxa that mothers and offspring benefit from cooperative breeding with the potential cost to helpers (Fisher 1930). Helpers could spend their time in other, and perhaps more, valuable, ways. Besides an opportunity cost (the foregone benefit from an alternative time or energy expenditure), the effort allocated to helping others could compromise their own growth, survival, or fitness. Consequently, cooperative breeding raises a classic evolutionary question: Why would an individual spend time and energy helping to support another’s reproductive interests? The theoretical expectation is that if helping incurs a cost, then it should be offset by some benefit (Chapter 5). For cooperative breeding, most explanations fall into three broad categories: indirect kin-selected benefits, direct fitness benefits, and mutual benefits.

12.2.2.1 Kin-Selected Benefits Prior to Hamilton’s inclusive fitness theory (1964), there was no satisfactory theoretical framework to explain helping behaviors, which were seen as enigmatic expressions of altruism. Kin selection as an explanation for why helpers help builds upon Hamilton’s Rule that cooperation can develop when helpers and recipients are closely related. Three general observations have been made from empirical studies relating kin-selected benefits to cooperative breeding. First, both case studies and metaanalyses show that when choosing between assisting a close relative, distant relative, or unrelated individual, strong preferences are shown for helping close relatives (Cockburn 1998; Hatchwell et al. 2001; Griffin and West 2003; Cornwallis et al. 2009). Because of this added value, kin-selected benefits have had broad appeal as the evolutionary basis for cooperative breeding (Cockburn 1998; Hughes et al. 2008; Boomsma 2009). Second, while the decision to help is strongly related to kinship, the amount of care a helper gives is more influenced by personal costs and benefits (Griffin and West 2003; Cornwallis et al. 2009). Third, helpers are more likely to help when the effect is substantial (Griffin and West 2003). These observations are well

https://doi.org/10.1017/9781108377911.013 Published online by Cambridge University Press

Allocare

291

supported in cooperative breeding species (Skutch 1987; Emlen 1991 [1978], 1997; Koenig and Rothe 1991) and are consistent with case studies in human societies that associate the probability of relatedness with who helps and the amount and quality of the help they provide (Ivey et al. 2005; Leonetti et al. 2005; Crittenden and Marlowe 2008; Kramer 2009). Because kin-based benefits are diluted under widespread promiscuity, biologists have hypothesized that an ancestral history of monogamy was a critical step to raise relatedness within groups and sibships (Boomsma 2007, 2009; Hughes et al. 2008; Lukas and Clutton-Brock 2012). The logic is that in a promiscuous or polyandrous mating system, a sexually mature individual is more likely to be closely related to one’s own offspring (Wright’s r = .5) than to siblings who may have different fathers (Wright’s r between siblings = .25–.5). Consequently, after sexual maturity one’s fitness is generally maximized by investing in one’s own offspring rather than helping to raise siblings. All else being equal, continuing to help would require either halving the costs or doubling the benefits. In a monogamous mating system, however, the value for a sexually mature sibling to stay in their natal group and help full siblings is equal to that of rearing one’s own offspring (Wright’s r = .5 for both) (Boomsma 2007, 2009; Lukas and Clutton-Brock 2012). Although monogamy undoubtedly raises relatedness between siblings and increases the probability that sexually mature helpers will care for full siblings rather than half siblings, it is not a necessary condition to explain human cooperative breeding (Box 12.2). Foremost, an ancestry of monogamy is important to explain why sexually mature adults help. Cooperation between mothers and her juvenile children or between grandmothers and her daughters can be favored irrespective of breeding system as long as helpers can identify their mothers and siblings. While kin selection is commonly given as the reason why helpers help, recent explanations have become more nuanced. In particular, they raise the question whether kin selection alone suffices to explain cooperative breeding (Cockburn 1998; Heinsohn and Legge 1999; Clutton-Brock 2002). While kin may ultimately benefit, because fitness payoffs often are time delayed, especially in long-lived animals, factors other than kin selection may be needed to motivate cooperative behaviors (Silk 2006; de Waal 2008; Coall and Hertwig 2010). In the human case, several emotional mechanisms have been forwarded as incentivizing helping behaviors, including empathy, fairness, and sympathy (de Waal 2008; Coall and Hertwig 2010; Blake et al. 2015).

12.2.2.2 Direct Benefits Helpers may directly benefit by increasing their own survival or mating prospects or by learning to become a competent mother. For example, recently fledged or matured individuals may improve their survival prospects by delaying dispersal and staying in their natal group to assist their parents to raise the next brood or litter (referred to as “pay-to-stay,” Dunn et al. 1995). Helpers also may directly benefit if engaging in cooperative behaviors increases their mating success (referred to as the “prestige hypothesis,” Grinnell et al. 1995; Zahavi 1995;

https://doi.org/10.1017/9781108377911.013 Published online by Cambridge University Press

292

Karen L. Kramer

Box 12.2

Is Monogamy a Necessary Condition for Cooperative Breeding to Evolve in Humans?

Behavioral ecologists have long recognized that breeding and parenting systems are closely associated. Phylogenetic studies offer compelling evidence that an ancestry of monogamy preceded the evolution of cooperative breeding across insect, bird, and mammalian taxa (Hughes et al. 2008; Cornwallis et al. 2010; Lukas and Clutton-Brock 2012). Although these studies suggest that monogamy provides a general rule for evolutionary transitions to cooperative breeding (Boomsma 2013), it may not apply to humans (overview in Kramer and Russell 2015). First, an ancestry of monogamy as the mechanism to raise relatedness in groups has strong support to explain why sexually mature helpers help, but it is not needed to explain why juveniles and grandmothers help. Because neither is able to produce offspring currently (or in the future in the case of grandmothers), helping does not carry the same reproductive or opportunity cost for juveniles or grandmothers, who can gain an immediate indirect fitness benefit by helping to raise the reproductive potential of their parents and descendants, respectively (see Section 12.2.2.1). Second, traits typically associated with monogamy (testes size, concealed ovulation, body size dimorphism, cross-cultural mating pattern) are inconclusive in characterizing ancestral human mating patterns as monogamous (Dixson 2009; reviewed in Martin and May 1981; Marlowe 2000b; Plavcan 2012; Kramer and Russell 2015). Third, even if past breeding patterns were monogamous, serial monogamy was likely the norm throughout most of the human past. Because of relatively high mortality and long breeding careers, both males and females in small-scale populations often have more than one spouse over their lifetime. For example, among largely monogamous Savanna Pumé huntergatherers, 40% of adults reenter the mating market after their first marriage due to spousal death or divorce (Kramer et al. 2017). If cooperative breeding is ancient, it likely emerged in a mating environment of multiple partners, not monogamy. Juvenile and post-fertile female cooperation can be favored in the absence of lifetime monogamy, while a more constrained breeding system (female monandry), which increases relatedness among siblings, is a pathway to favor helping by adult siblings.

Cockburn 1998; Zahavi and Zahavi 1999; Bergmüller et al. 2007). In humans, cooperation as a costly signal of male quality and status has largely been discussed in the context of hunting and meat provisioning (Hawkes 1991; Hawkes and Bliege Bird 2002). Of note, both pay-to-stay and prestige benefits pertain specifically to the payoff for sexually mature individuals to help.

https://doi.org/10.1017/9781108377911.013 Published online by Cambridge University Press

Allocare

293

Juvenile helpers may directly benefit by learning skills that enhance their future success in raising offspring of their own (Hrdy 1976; McKenna 1987; Fairbanks 1993; Tardif 1997). For example, longitudinal observations of vervet monkeys show that females who spent more time carrying infants as juveniles were significantly more likely to have a firstborn who survived (Fairbanks 1990). While the learning-to-mother payoff has been proposed for humans (Lancaster 1971; Ivey 2000), the challenge of testing this hypothesis is the scarcity of large samples of longitudinal data that track girls from childhood into their reproductive careers. Another direct benefit is group size augmentation (Cockburn 1998; Clutton-Brock 2002; Russell 2004; Bergmüller et al. 2007). If individuals survive and reproduce better in larger groups, they may benefit if caring for another’s offspring augments breeder survivorship or fertility, thereby increasing the group’s size (Brown 1987; Pusey and Packer 1987; Kokko et al. 2001).

12.2.2.3 Mutual Benefits Helpers may also benefit by engaging in mutualistic cooperative interactions (Clutton-Brock 2002). For example, among social birds, juveniles may contribute to building a communal nest that they will utilize as adults. The benefits of mutual cooperation may be particularly germane to cooperative breeding in humans for several reasons related to the human feeding niche. The human diet is distinguished by its broad diversity of plant, animal, and aquatic foods, which are often located in disparate locations on the landscape and transported long distances back to base camps. Daily foraging ranges are large, and most food resources require multistage processing, central-place foraging, and complex technologies to access and process (Kramer 2019). Simply said, there are insufficient hours in the day for any one person to get the plants and animals they need, to procure and process raw materials to manufacture the tools, to haul water, to chop firewood, to construct clothing and shelter, to take care of children, and to maintain the social and information networks that are needed to access geographically dispersed resources. This introduces a time allocation constraint for an individual of any age to be self-reliant, making it difficult for juveniles as well as adults to be independent. These distinctive features of the human diet present both opportunities and benefits for the division of labor, which is central to many explanations for cooperative breeding (see Section 12.4).

12.3

Human Cooperative Breeders: Who Helps and How Turke’s (1988) seminal study among Micronesian islanders first introduced humans as cooperative breeders. Using time allocation data, he showed that Ifaluk mothers who bore girls, who are valuable household helpers, early in their reproductive careers had greater completed fertility than if their firstborn children were boys. This study was followed by Ivey’s (1993) examination of the range of childcare helpers among the Efé (Ituri Forest hunter-gatherers). Since then, reproductive

https://doi.org/10.1017/9781108377911.013 Published online by Cambridge University Press

294

Karen L. Kramer

cooperation has become a central explanation for the evolution of human life history and sociality (Hrdy 1999a). Individuals who cooperate with mothers vary culturally, demographically, and situationally, and they may include mothers, grandparents, juveniles, and a variety of other kin and nonkin (Ivey 2000; Kramer and Veile 2018; Helfrecht et al. 2020). The discussion here is focused on juveniles and grandmothers in natural fertility settings. This emphasis does not obviate the overall importance of diverse and flexible caregiving networks for humans.

12.3.1 Who Helps Distinct theoretical arguments have been made for the evolutionary importance of grandmothers (Hawkes et al. 1998; Alvarez 2000) and juveniles (Kramer 2011, 2014). Grandmothers are closely related to their daughters and grandchildren, and since they are often postmenopausal, helping provides a means for them to further their inclusive fitness. Likewise, juveniles cannot reproduce, and because they are closely related to their mother and siblings, they can leverage their non-fertile status into a higher reproductive potential for their mother, increasing their inclusive fitness. If juveniles contribute, either through direct calorie transfers by producing and sharing food or by performing tasks that reduce their mother’s energy expenditure, they can make the most of growing slowly and receive an immediate fitness benefit rather than having to wait until they are sexually mature. This time-discounting advantage may be important in selecting for slow juvenile growth, especially in high-mortality environments where up to 10% of juveniles who survive weaning may not survive to reproductive age (Reiches et al. 2009; Kramer and Ellison 2010). Juveniles might incur a disadvantage if the caloric cost to helping is high. The potential trade-off with compromising the energy available for growth has been examined in small mammalian cooperative breeders. Researchers found that for meerkats, while the energy expended in helping resulted in a short-term growth cost, there was no enduring fitness cost (Russell et al. 2003b; Clutton-Brock 2006; Clutton-Brock and Manser 2016). Beside siblings and grandmothers, aunts (usually mother’s sister), grandfathers, other relatives, and nonrelatives may provide care, food, shelter, and assistance to mothers and children. For example, among the Maya, young children receive 8% of their direct care from their aunts (Kramer 2010). Among the Ye’kwana of Venezuela, young children receive 6.6% of their direct care from aunts (Hames 1988). Aunts and uncles provide 4.5% of the care that young Trinidadian children receive (Flinn 1992). Most published studies aggregate non-grandmother adult helpers as “other relative” or “nonrelative,” who, together in the case of Australian Aborigines, provide up to 30% of a young child’s care (Scelza 2009). The few studies that specify the contributions of elder men (grandfathers and uncles are often combined in reporting) concur that they provide little direct childcare. Among the Aka, who are well documented for paternal infant care, infants were held by grandfathers less than 1% of the time (Hewlett 1991b:79). Efé grandfathers and uncles spend approximately 2.5% and 1% of their time in allocare, respectively (Ivey

https://doi.org/10.1017/9781108377911.013 Published online by Cambridge University Press

Allocare

295

2000:860). While older men do not commonly take on active childcare roles, they may provide important food, resources, property, and social access (Hooper et al. 2015b). Aché, Hiwi, Hadza (Kaplan et al. 2000), and Maya men (Kramer 2005b) over the age of 50 on average remain net producers for another decade, suggesting that some of their food surplus flows to younger generations. In Tanzania, Hadza men’s foraging returns remain consistent after the age of 40, and older men may provide meat calories to grandchildren (Marlowe 2000a). In many small-scale societies, older men are vital in brokering social status, settling disputes, providing agonistic support, promoting group cohesion, and arranging marriage ties, which affect the lives and success of younger generations (Wiessner 2002). For example, the presence of an uncle or grandfather lowers the age of a Martu boy’s initiation, which is correlated with future reproductive success (Scelza 2010). Aside from these few studies, understanding the function of grandfathering in small-scale societies is generally understudied.

12.3.2 Not All Helpers Are the Same Because of paternity uncertainty and the expectation that cooperators will bias their investment toward kin, the role of maternal grandmothers is most frequently highlighted. Where resources are shared, an investment in female kin is assumed to more likely be transformed into benefits for children than an investment in male kin, who may alternatively allocate resources to mating effort. Ethnographic exceptions are noted, particularly in patrilineal societies where mothers extend help to their sons’ children. For similar reasons, a distinction between maternal and paternal grandmother effects is observed in many studies. Generally, positive effects on grandchild survivorship (and other outcomes) are associated with maternal grandmothers (Sear et al. 2002; Voland and Beise 2002; Leonetti et al. 2004; Gibson and Mace 2005; Sear and Mace 2008), while paternal grandmothers exhibit a range of positive (Sear and Mace 2008), neutral (Griffiths et al. 2001; Sear et al. 2002), and negative associations with child survival (Voland and Beise 2002). Besides the sensitivity of cooperative behaviors to kin selection and paternity certainty, negative effects are also suggested to arise from resource competition in households where paternal grandmothers have a stake in biasing the sex or number of heirs. Others suggest that the inconsistent results in grandmothering effects derive from confounding differences in X-chromosome relatedness between maternal and paternal grandmothers (Fox et al. 2009). The range of positive, negative, and neutral findings suggests that complex economic and socioecological factors condition grandmaternal effects.

12.3.3 What Helpers Do 12.3.3.1 Infant Allocare In a cross-cultural sample of time allocation studies, mothers on average provide about half of infant care, and allocaretakers provide the balance (Kramer and Veile 2018). While allocaretaking may be considerable, it is also quite variable across societies. Among the Efé, allocaretakers provide 60% of the care that an

https://doi.org/10.1017/9781108377911.013 Published online by Cambridge University Press

296

Karen L. Kramer

infant receives at 18 weeks (Ivey 2000). Young Aka children ages two to four are fed by someone other than their mother about 60% of the time (Fouts and Brookshire 2009). Hadza allomothers hold children four and younger only 31% of the time (Crittenden and Marlowe 2008). !Kung infants in particular stand out as receiving much more of their care from their mothers, who account for 75–80% of all physical contact that an infant receives in the first 20 months of life (Howell 2010; Konner 2010). Of allocaretakers, a study using the same data collection methods in two groups of agriculturalists and a group of hunter-gatherers found that unmarried siblings, and specifically children ages 7–14 years old, invested the most time caring for infants (Kramer and Veile 2018). The tendency for young children to be childcare specialists has been qualitatively noted by many ethnographers (Barry and Paxson 1971; Weisner and Gallimore 1977; Nag et al. 1978; Hames 1988; Whiting and Edwards 1988). Humans are not unusual in this regard; juvenile allocaretaking is common in many cooperative breeding species (Clutton-Brock 2002; Russell 2004; Gilchrist and Russell 2007). One possible explanation is that because subadults and adults are stronger, more skilled, and efficient at a greater range of economic tasks, the opportunity cost for them to allocate time to childcare is higher than for younger children who have fewer competing ways that they can spend their time (Bock 2002). This explanation accords with analyses that find that the time children allocate to childcare does not predict a decrease in time spent playing, in economic activities, or school (Kramer and Veile 2018). Older women may care for their young grandchildren while their daughters spend time away from home foraging or in other economic pursuits (Hrdy 2009). In other instances, mothers with young children might reduce the time they spend in economic activities, while grandmothers take on these support tasks rather than helping with childcare (Hawkes et al. 1989, 1997; Hurtado et al. 1992; Gibson and Mace 2005; Leonetti et al. 2005). In a study of the energetic effects of helping, Aka grandmothers reduce maternal workloads by about 200 kcal per day while also offsetting the time that mothers spend in direct care (Meehan et al. 2013). Many studies infer grandmother effects from demographic data (i.e., counts of living family members) rather than from direct observations of assistance. One question that arises from demographic studies is whether the association between the presence of a grandmother in a household and child survival is due to phenotypic correlation rather than helping. That is, healthier women who survive to older ages may produce grandchildren who exhibit better health and survivorship (see Box 2.1). If larger families are associated with a living grandmother, is it because the grandmother is easing maternal constraints by helping or because long-lived women pass on the survival advantage to their grandchildren? Furthermore, while an individual may be counted as a caretaker, how much help they give is unknown without observational study. For instance, among the Savanna Pumé and the Maya, older siblings, fathers, and grandmothers allocate between 0–17% and 0–33% of their time to childcare, respectively. In other words, these potential allomothers may do nothing or a lot, and consequently they may be either a cost or benefit to a mother.

https://doi.org/10.1017/9781108377911.013 Published online by Cambridge University Press

Allocare

297

Although childcare tends to be a family affair (Kramer and Veile 2018: Figure 1; Helfrecht et al. 2020: Figure 2), childcare network size can be large and diverse. For example, Efé focal infants interact with 11 allocaregivers on average during focal observations (range from 2 to 21; Ivey 2000:860). A similar network size is found among Central African hunter-gatherers, where childcare networks average 12.1 caretakers per 9 hours of observation (range 3–24; Helfrecht et al. 2020, Table 1). Furthermore, this same study demonstrates that larger caregiver networks are associated with a decrease in the frequency of maternal care, suggesting that diversity itself is an important variable attenuating time allocation conflicts for mothers (Helfrecht et al. 2020).

12.3.3.2 Juveniles Are Both Subsidized and Provision Their Siblings Across all human societies, weaned children are fed and cared for in various ways. Because of this, adult provisioning is often highlighted as a defining feature of human evolution. But children also cooperate to provision and care for others, an equally defining human trait. Children are caretakers, share resources, and exchange labor with their mothers, siblings, and others, something other primate juveniles rarely do. Indeed, cross-culturally, toddlers are observed to go through a helpful developmental stage (Lancy 2018), and in early childhood, much of the cognitive and emotional architecture develops that establishes the human capacity for coordination and cooperation (Tomasello et al. 2005; Hrdy 2009; Tomasello and Vaish 2013). Because juveniles are helped and are helpers themselves, both of these derived human traits are evidently important to the origins of cooperative breeding. Although children receive difficult-to-acquire food and resources from others, they are also able to produce other easy-to-acquire resources (fruits, nuts, berries, small game) that contribute directly to their own energy budget and are often shared with others (Kramer 2005b, 2014; Crittenden et al. 2013). Hadza children living in subSaharan Africa spend five to six hours a day foraging for food. By the age of five, during some seasons, they supply about 50% of their own calories (Blurton Jones et al. 1989a:367). Maya children produce 50% of what they consume by age six (Sullivan Robinson et al. 2008), and much of what they produce is shared with other household members. On days that they forage, Savanna Pumé boys have an average return rate (amount of food produced per foraging trip) of 4.5 kg of wild fruit (~3200 kcal), and 0.5 kg of fish (~700 kcal). This is what a boy returns to camp after whatever field snacking that he might do on the trip, and it is a sufficient caloric return to feed himself and at least some of his family. On days that she forages, his sister brings home an average of 1.1 kg of roots (~3850 kcal), some of which she will eat, but much of which are shared with others. While juveniles both produce and consume food, foraging returns, and calorie counting do not capture other important contributions. For example, although !Kung children are known for contributing little to food production (Blurton Jones et al. 1994a; Howell 2010), by the age of eight they crack most of the mongongo nuts they eat, a substantial portion of their diet (Lee 1979). Hadza girls under the age of five

https://doi.org/10.1017/9781108377911.013 Published online by Cambridge University Press

298

Karen L. Kramer

spend more time food processing than any other age class (Hawkes et al. 1998). Many food processing and domestic activities (firewood, water), which are critical to the human feeding niche, do not have readily measurable caloric equivalents. Thus, analyses that limit children’s contributions to calorie acquisition will inevitably conclude that children do little for themselves and are costly. If the human adaptation is contingent on high-quality food requiring complex access and processing solutions, considering the time allocated to these tasks is critical to understand both the effect that juvenile dependence has on maternal time budgets and on cooperative breeding. If how children allocate their time to this broader range of food processing and other labor is considered, in most societies there are noteworthy increases between middle childhood and adolescence (Figure 12.1). If what juveniles do is standardized as a proportion of the adult mean, in many societies, juveniles work at least 50% as much as their adult counterparts (Kramer 2019). This is not insignificant if you consider that a 10-year-old, for example, is on average about 60% of adult body mass. Although children are not working equally proportional to their body size, they go a long way toward it, and while they underproduce some resources, they also overproduce others. While hunter-gatherer children are often thought to do less to support themselves than children in other subsistence economies, the empiricial data suggest otherwise. Hunter-gatherer children have both some of the highest and lowest participation in economic activities (see Figure 12.1). This suggests that the helpfulness of juveniles is not a function of whether a child is a forager, an agriculturalist, or a pastoralist. Rather, children’s contributions vary with ecology, kinds of subsistence tasks, the costs to participate, dangerousness of the environment, and how children learn to become competent adults. Another reason that human children are often characterized as an energetic burden is because the effects of overlapping dependents are not considered. Although any one child may be a net cost, how mothers experience the day-to-day support of multiple dependents is analogous to a mortgage, where others need to pay only the daily balance of what children cannot fund themselves. Because juveniles are both producers and consumers, and mothers raise children of various ages at the same time, a different picture emerges from analyses that combine these features of human families. Using a framework that incorporates the combined costs of older and younger children, food and labor exchanges between children within a family cover a substantial portion of their total costs (Lee and Kramer 2002; Kramer 2014; Kramer and Otárola-Castillo 2015). For instance, when data is modeled across a Maya woman’s reproductive career, fathers contribute as much time as mothers to child support, but parents nonetheless fall short in meeting their children’s consumption needs. Juveniles fill this gap and are especially critical to family survival after the last child is born, when parents have the maximum number of dependents (Kramer 2005b). While many reasons have been forwarded for why helpers would help, they also should be self-interested. In the case of juveniles, competition between siblings and a reluctance to cooperate might be expected. Several studies that have looked at sibling

https://doi.org/10.1017/9781108377911.013 Published online by Cambridge University Press

299

6

Juveniles Adolescents Adult Men Adult Women Adults 50+

0

2

4

Hours

8

10

12

Allocare

Hadza

!Kung

Mikea

Maya

Machi.

Mayangna

Java

Nepal

Figure 12.1 The average number of daily hours that younger juveniles ages 6–14, adolescents

ages 15–19, reproductive-aged males and females, and adults over the age of 50 spend in economic activities among hunter-gatherers and subsistence agriculturalists. Economic activities are defined, unless otherwise indicated, as time allocated to food production (foraging, hunting, fishing, caring for animals, working in fields, etc.) and domestic production (chopping firewood, fetching water, food processing, etc.). Male and female values are averaged for juveniles, adolescents, and adults over the age of 50. The sample includes known published time allocation data stratified by age and sex. Age categories vary slightly from study to study. Missing bars indicate unreported data. Sources: Hunter-gatherers: Hadza (Hawkes et al. 1997:556); observation period 12 daylight hours, reported as weekly means; instantaneous scan samples (n = 1700 observations; 90 individuals); !Kung (Lee 1979; Draper and Cashdan 1988); Pumé (Kramer and Greaves, unpublished data); observations period 12 daylight hours 6:00 a.m.–6:00 p.m.; instantaneous scan samples (n = 24,924 observations, n = 87 individuals); Mikea (Tucker and Young 2005, Figure 7.2); observation period 12.5 daylight hours; instantaneous scan samples (n = 6637 observations, 46 individuals); Agriculturalists: Maya (Kramer 2005b); observation period 11 daylight hours 7:00 a.m.–6:00 p.m.; instantaneous scan samples (n = 18,500 observations, 112 individuals); Machiguenga (Johnson 1975, Tables 1 and 2); observation period daylight hours 6:00 a.m.–7:00 p.m.; instantaneous scan samples (n = 3495 observations, 105 individuals); Mayangna (Koster 2007, Tables 5.4 and 5.5); observation period 5:30 a.m.–6:00 p.m.; instantaneous scan samples (n = 14,653 observations, n = 195 individuals); Java (Nag et al. 1978, Tables 1 and 2); 24-hour recall collected every 6th day over the course of a year (n = 105 individuals); Nepal (Nag et al. 1978, Tables 3 and 4); 24-hour recall collected every 6th day over the course of a year (n = 498 individuals).

competition have not found negative impacts on growth outcomes, however. The effects of younger and older siblings (Kramer et al. 2016), closely aged siblings (Helfrecht and Meehan 2016), male and female siblings (Hagen and Barrett 2009), and caregiver presence (Meehan et al. 2014) instead reveal a positive relationship with developmental outcomes, suggesting that sibling helpfulness outweighs competition in these circumstances.

https://doi.org/10.1017/9781108377911.013 Published online by Cambridge University Press

300

Karen L. Kramer

Figure 12.2 Cooperative breeders vary in who they are and what they do. Savanna Pumé aunts, siblings and grandmothers shown grooming (a), preparing food (b), providing childcare (c, e, f ) and food (d). Photo credits: Russell Greaves.

The idea of hardworking grandmothers has received significant traction as an evolutionary explanation for longevity (Hawkes 2003; Kim et al. 2012, 2014). Several demographic studies show an association between a maternal grandmother being alive and child survivorship. However, relatively few studies report what grandmothers actually do. Those that record time expenditures for older adults indicate that they continue to make important economic contributions throughout much of their lives (Turke 1988; Hawkes et al. 1989, 1997; Hurtado et al. 1992; Kaplan 1994; Gibson and Mace 2005; Kramer et al. 2009; Kramer and Greaves 2011a) (Figure 12.1). Other cross-cultural studies suggest that food transfers from older females are nuanced. For example, older Hadza women spend significantly more time foraging during some seasons of year, but not others. Post-reproductive Savanna Pumé females overproduce some resources (small wild roots), but not others (large wild roots or fruit) (Kramer and Greaves 2011a). Among the Hiwi, who live within 100 km of the Savanna Pumé in a similar Savanna environment, post-reproductive women spend more time foraging than younger women during certain seasons of the year (Hurtado et al. 1992), but their return rates for roots and fruit decline after about age 50 (Kaplan et al. 2000).

https://doi.org/10.1017/9781108377911.013 Published online by Cambridge University Press

Allocare

301

Comparative time allocation studies, where age-specific consumption data are paired with production data, show that among several groups of hunter-gatherers and horticulturalists, older adults often acquire more food than they can consume (Hawkes et al. 1989; Hurtado et al. 1992; Lee et al. 2002; Hill and Hurtado 2009; Kramer et al. 2009). Because food sharing is particularly difficult to document, overproduction is often assumed to be transferred to juveniles. However, overproduction may have other destinations (feasting, status competition) besides being shared with children (Codding et al. 2010). In sum, researchers emphasize the contributions of different age and sex classes of potential helpers. Although grandmothers, siblings, and fathers often are treated as mutually exclusive sources of help, helpers of different age and sex may be key at different points in a mother’s reproductive career, and under different ecological and demographic conditions. In addition to variable mortality schedules, small-scale populations are subject to pronounced stochastic swings in age and sex distribution, affecting the availability of potential helpers. Because both male and female labor and resources are important to survival and subsistence, there is strategic value for mothers to have access to a range of helpers. As a child, you only ever have two grandmothers, and under preindustrial mortality schedules, if your grandmother is alive, you are likely to have only a few years when your lives overlap (Chapman et al. 2018). Data from four Savanna Pumé camps show that 64% of mothers ages 15–30 have a surviving mother, while only 31% of mothers ages 31–45 do. This compares closely to the Aché, among whom 32% of women 36–45 have a surviving mother (Hill and Hurtado 2009). In contrast, unless juvenile mortality is particularly high, a natural fertility mother will have an increasing number of productive-aged juveniles until about age 40 when children start to leave home. We might then infer that the importance of grandmothers is greatest during early parities, but during their prime reproductive years, many mothers will have to count on the help of juveniles, fathers, and others.

12.4

Why Humans Are Cooperative Breeders While mothers and their offspring may benefit from help, and a number of reasons for why helpers might help are well-established, this does not answer why cooperative breeding emerged during hominin evolution. By comparison, nonhuman great ape juveniles would surely benefit from help, as would their mothers. Because cooperators potentially have to wait a long time to realize fitness benefits, especially long-lived animals, kin selection itself may be insufficient to motivate cooperative behaviors. Rather, proximate mechanisms may be critical to stimulate cooperation. Indeed, because cooperative breeding occurs across a range of environments – from harsh to benign, stable to fluctuating – recent research suggests that it is not determined by ecological variables alone. Rather, cooperative breeding is associated with social and group benefits that crosscut environmental differences (Shen et al. 2017). Building on this, the mutual benefits of foraging efficiency, labor economy, and the division of labor, which have been documented in other cooperative breeders

https://doi.org/10.1017/9781108377911.013 Published online by Cambridge University Press

302

Karen L. Kramer

(Kokko et al. 2001; Clutton-Brock 2002, 2006; Silk 2009), may be particularly relevant to humans as proximate mechanisms and provide clues why humans became cooperative breeders. The human feeding niche is characterized by a diverse portfolio of food types, dependence on complex technology, and food processing (see Section 12.2.2.3). When tasks vary in their costs (e.g., feeding vs. protection, foraging vs. food processing, gathering vs. hunting), task specialization is argued to be instrumental in favoring biparental care and a division of labor. Task specialization and the age division of labor (age polyethism) are widespread in many cooperative breeding insects and mammals (Thorne 1997; Clutton-Brock et al. 2002; Toth and Robinson 2007; Crespi 2014). In the human case, the mutual benefits of a division of labor is hypothesized to be critical to the formation and stability of cooperating groups (Leonetti and Chabot-Hanowell 2011) and reinforce cooperative interactions between mothers and her offspring (Chapais 2001, 2006).

12.4.1 Recruiting Helpers on the Path to Cooperative Breeding The human cooperative breeding pattern involved at least three distinct evolutionary steps: the integration of juveniles, grandmothers, and fathers into cooperative relationships. Each step would have required a payoff to cooperate (see Section 12.2.2), which may have included kin-selected benefits, direct benefits, or mutual benefits. Although most researchers agree that the advantages to cooperate arose at some point in the past, which partnerships were at the root of early cooperation is debated. These debates are not reviewed here, but the broader point is that given a benefit to cooperation, whether juveniles, grandmothers, or fathers were motivated to cooperate depended on breeding systems, dispersal, and resident patterns (Table 12.1). Juveniles are closely related to their mothers and siblings and have low opportunity costs to cooperate since they do not compete for mating opportunities and benefit by leveraging their own nonreproductive status into indirect fitness gains. Juveniles usually co-reside with mothers until sexual maturity (exceptions exist where fosterage occurs), and extended ties between mothers and juveniles and the mutual benefits of a division of labor can encourage cooperative interactions through reciprocity and mutualism (Silk 2006) and complement the positive effects of kin selection (Silk 2009). Likewise, a grandmother’s relatedness to her daughter (Wright’s r = .5) or her grandchildren (Wright’s r = .25) is unchanged by the breeding system (see Box 14.2), and opportunity costs are low to cooperate, which might be favored among postreproductive individuals. (Paternal grandmothering is more constrained by the breeding system and dispersal patterns.) However, dispersal and residence patterns and age-specific mortality and fertility affect the likelihood that the lives of grandmothers and grandchildren overlapped in sufficient numbers to select for a productive post-reproductive period during which help can be directed to grandoffspring (Chapman et al. 2018).

https://doi.org/10.1017/9781108377911.013 Published online by Cambridge University Press

Allocare

303

Table 12.1 Helper status and associated theoretic foundations and breeding systems.

Helper’s status

Theoretic foundations

Juveniles

Cooperative breeding Kin selection Learn-to-mother Age division of labor and mutualism Grandmother hypothesis Kin selection Cooperative breeding Monogamy hypothesis Ecological constraints Communal breeding Parental investment Prestige hypothesis Reciprocity Direct benefits (pay-to-stay, learn-tomother, prestige, group augmentation)

Post-fertile females Sexually mature siblings Mothers Fathers, grandfathers Nonkin

Evolutionary breeding system to realize kin-benefits Any breeding system

Any breeding system Female monandry*

Any breeding system Female monandry* Any breeding system

* Either a monogamous or polygynous pair-bonded breeding system. Note that once cooperative breeding is favored, breeding system constraints can be relaxed (e.g., Lukas and Clutton-Brock 2012) (see Box 12.1 on Monogamy).

Female monandry (either through monogamy or polygyny) is usually argued as a critical step for the inclusion of fathers, sexually mature siblings, or other collateral kin to realize kin-selected benefits for cooperating. One parsimonious interpretation is that cooperative breeding has its origin in cooperating groups of mothers and juveniles since it does not require a priori selection for a specific breeding system, dispersal pattern, or advances in offspring or old-age survivorship. With subsequent changes in life history and sociality, more complex forms of cooperative breeding follow that involved grandparents, fathers, sexually mature siblings, and other ascendant kin (Kramer and Orárola-Castillo 2015).

12.4.2 The Evolution of Cooperative Breeding and Life History Traits In contemporary natural fertility societies, mothers wean infants at a young age and have short birth intervals while juveniles rely on others in part for their well-being and have a good probability of surviving. This combination of life history traits, which means that mothers have multiple dependents of different ages, is often evoked as the reason why mothers need others. However, this suite of traits did not always characterize human life history and likely did not reach its modern form until the terminal Pleistocene (Dean 2006). In asking questions about the evolution of cooperative breeding, it is important to keep in mind that the very life history traits

https://doi.org/10.1017/9781108377911.013 Published online by Cambridge University Press

304

Karen L. Kramer

that directly impact parental care (birth intervals, survivorship, juvenile dependence, dispersal) have undergone considerable, and likely recent, modification. In other words, if cooperative breeding is ancient, it likely evolved under not fully modern life history conditions. Although substantial reorganization in life history, parental care, and energy flows occurred during hominization, these changes leave ambiguous fossil, archaeological, and molecular records. Neither is there a great ape model to help inform us what the transition from autonomous mothers and juveniles to economic interdependence might have looked like. While we often turn to ethnographic populations, particularly hunter-gatherers, they may not be that informative about the emergence of cooperative breeding in our species since they express a modern life history. Alternatively, we can simulate the transition from a general apelike pattern of long birth intervals, nutritional independence at weaning, and juveniles who were selfsufficient foragers to a modern life history of early weaning, short birth intervals, and extended juvenile dependence. Predictions can then be generated for how constraints on a mother’s time change within this evolutionary space. Models predict that early in this transition, cooperating groups of mothers and juveniles could have supported early life history modifications such as shorter birth intervals and later ages at maturity, dispersal, and independence (Kramer and Otárola-Castillo 2015). Models also predict that the modern life history parameters of a three-year birth interval and high juvenile survivorship have a marked interaction in raising the costs of children and would have required the help of other adults for mothers to support large families. In sum, the cooperative breeding literature often assumes a modern life history as the selective background for its evolution. However, if traits that directly affect parental care have undergone considerable modification, this assumption may mislead interpretations of causal relationships and selective pressures. Multiple lines of evidence suggest that cooperative breeding as we know it today was a multilevel process that developed on a changing life history landscape and involved several transitions to incorporate juveniles, grandmothers, other relatives, and fathers.

12.5

Implications for Cooperative Breeding Following the Demographic Transition Mothers in post-demographic transition societies face new challenges to the same time allocation dilemma of providing competent childcare while finding time to maintain their economic and domestic activities. While this trade-off is as relevant today as it was in the past, living in a market-based economy, having smaller families and living longer alter both the demands and opportunities for help, though not always in expected directions. Although post-demographic transition mothers have on average fewer children, balancing childcare and resource provisioning may become even more demanding. For much of human history, maternal work and childcare were combined. In smallscale societies, nursing children often accompany mothers on their daily activities,

https://doi.org/10.1017/9781108377911.013 Published online by Cambridge University Press

Allocare

305

while toddlers are left in home bases to the care of older children. Although mothers can interrupt foraging, agricultural, and domestic work to care for young children, wage work is often incompatible with childcare. Additionally, schooling separates younger children from their older-sibling caretakers. As wage earners, mothers also often have less flexibility. In managing the competing demands of finding time to support younger and older children, mothers in small-scale societies spend less time in economic activities (foraging for food, in agricultural or domestic work, depending on their subsistence base) when they have a nursing infant (Hurtado et al. 1985, 1992; Hames 1988; Kramer 2009). Instead, mothers give priority interest to childcare, while others substitute for their food production and domestic tasks. To maintain their economic position and pursuits, wage earner mothers often opt to pay for childcare. Effective contraception also allows mothers to solve competing demands in new ways by delaying first births, extending birth intervals, or limiting family size. The kinds of assistance that benefit mothers and offspring, and why helpers help, also change in a monetary economy after the demographic transition, where helper effects become disassociated with child survival. The rise in infant survivorship, a defining feature of the demographic transition, is largely accounted for by the institution of immunization, improved nutritional and sanitation conditions, and child and maternal public health programs, which reduce an infant’s exposure to mortality and morbidity risks. While helpers may be less critical to child survival, helpers continue to convey fitness benefits in other ways. Grandparenting, for example, has an important effect on the fertility decisions for working mothers (Coall and Hertwig 2010; Sear and Coall 2011). In a three-generation study of grandparents in the Netherlands, grandparental childcare increased the probability that parents have an additional child over the next decade (Kaptijn et al. 2010). While some traditional roles may be supplanted, new measures such as financial well-being, educational achievement, or status attainment may be more appropriate in evaluating helper effects in post-transitional societies. For example, close, supportive grandfather relationships are associated with improved grandchild emotional well-being, especially in single-parent households (Ruiz and Silverstein 2007). Although extended family members are more likely to geographically live at a distance and be unable to provide childcare, a monetary economy allows them to contribute from a distance with cash transfers, financial assistance, and purchased goods and services, such as paying for daycare or school fees. As siblings and juveniles fall out as helpers, opportunities for others increase. The demographic transition is accompanied by changes in both child and old-age survivorship, both of which affect the probability that ascendant and younger generations will be alive at the same time. A large genealogical Finnish sample over a 170-year period found that before the demographic transition, while 65% of children had a living maternal grandmother at birth, shared time varied between 0 and 2 years (estimate across years) (Chapman et al. 2018). After the demographic transition in the mid-nineteenth century, shared time steadily increased with a high of 80% of children having a living maternal grandmother in the 1950s and an overlap of 14

https://doi.org/10.1017/9781108377911.013 Published online by Cambridge University Press

306

Karen L. Kramer

years. Trends in shared time with paternal grandmothers were similar, but much lower both before and after the demographic transition. Surveys across European countries found that many grandparents, including grandfathers, report caring for a grandchild (Hank and Buber 2009). While grandparenting generally may become more central, grandfathering in particular appears to rise in importance (overview in Coall et al. 2016). Not only are grandparents more likely to be alive, but the role of grandfathers has changed (Sear and Coall 2011), and may make particularly important differences in grandchild outcomes in singleparent and low-income families (Coall et al. 2016). In sum, as generational time lengthens, family size reduces to one or two children, and families are more prone to geographic dispersion, child-rearing support networks often shrink. Support to raise children in post-demographic transition populations often shifts from kin to nonkin-based assistance such as paying for childcare or utilizing institutional assistance. The indirect value of helping, which may be diluted in larger families, becomes more concentrated in smaller families, and may explain the increasing role of grandparental assistance.

12.6

Conclusion Similarities and differences between human and nonhuman cooperative breeders are rooted in the human feeding niche and the diverse social and economic interactions that characterize human behavior. Resolving how humans fit into the framework of cooperative breeding will benefit from further theoretical debate and empirical research. Because humans target high-quality resources with complex access problems, it means that not only children but also adults are constrained from being selfreliant. Because human cooperative breeding is embedded in a generalized pattern of food sharing, labor cooperation, and long-term reciprocal relationships that occur across all ages and sex, the integration of cooperative breeding and cooperation theory is likely to be a productive path for future research (Bergmüller et al. 2007). The life history of high fertility and relatively high juvenile survival rates that we document in small-scale and natural fertility populations today is feasible because mothers utilize many forms of offspring support. As an ancestral strategy, however, cooperative breeding likely emerged in stages that coevolved with other features of our life history and sociality.

https://doi.org/10.1017/9781108377911.013 Published online by Cambridge University Press

13 Demography Rebecca Sear, Siobhán M. Mattison, and Mary K. Shenk

Human behavioral ecology is at heart a demographic science. Its central currency – fitness – is defined by demographic parameters, as are many outcomes of interest to behavioral ecologists. In this chapter, we introduce the basic parameters that define the field of demography, emphasizing their utility both for testing hypotheses of interest to behavioral ecologists and for describing the ecological contexts that situate behaviors. The chapter is structured along the lines of many demography textbooks, describing fertility, mortality, and migration – the three key parameters used to understand population structure and change. We describe how these parameters relate to fitness and how each may be used as predictors or outcomes in hypothesis testing in behavioral ecology. We conclude that human behavioral ecologists benefit strongly from familiarity with demographic methods, data sources and literature, given the importance of using demographic outcomes to test human behavioral ecological theory. Familiarity with demography can also produce insights that contribute to novel, or more nuanced, theory.

13.1

Why Is Demography So Important for Human Behavioral Ecology? This chapter follows Metcalf and Pavard’s (2007) call for “all evolutionary biologists [to become] demographers,” extending it explicitly to human behavioral ecology. Demography – “sex, death, and passion wrapped in indicators” (van den Brekel, cited in Coleman 2000) – is the study of population size, structure and change, and the components of population change: fertility, mortality, and migration. Demography is foundational to understanding human social systems, and demographic monitoring has long been critical for effective policy implementation; governments and aid agencies accordingly dedicate significant resources to population censuses and related activities. Given its broad applicability, the field of demography is inherently interdisciplinary and particularly influenced by sociology and economics (Sigle 2021), though anthropologists are increasingly contributing (Coast et al. 2007). Human behavioral ecology (HBE) is one of the most important subfields of anthropology to contribute to demographic inquiry. The mixed methods study of the fitness implications of human behavior, HBE naturally engages with key parameters (fertility1 and mortality) of interest to demographers, and the marriage of HBE 1

We use the social science definition of fertility, where fertility refers to the production of children and fecundity is the capacity to conceive. Biology reverses these definitions.

https://doi.org/10.1017/9781108377911.014 Published online by Cambridge University Press

308

Rebecca Sear, Siobhán M. Mattison, and Mary K. Shenk

and demography yields insights that advance both fields. In this chapter, we discuss the importance of understanding demography for human behavioral ecologists, giving many examples of how the field has fruitfully integrated demographic research. This area of research is sometimes referred to as “ecological evolutionary demography” (Mattison and Shenk, in press; Low 1993), a research area that contributes to resolving social science’s most vexing questions in ways that recognize both the context-specific and general processes underlying demographic behavior. Reproductive success – the driving concept of HBE, as of evolutionary biology in general – is a product of mortality and fertility: In order to launch genes successfully into future generations, individuals have to survive long enough to reproduce and then ensure children survive long enough to reach reproductive age themselves. In humans, parents may also help their children secure reproductive partners, raise grandchildren, and/or endow them with resources. One way to test whether behaviors are adaptive is to assess their association with mortality and fertility. Behaviors that decrease mortality of children are usually considered fitness enhancing (Lawson et al. 2012). Fertility is also sometimes used as a proxy of fitness, but this is less straightforward; observed fertility rates in contemporary societies are rarely fitnessmaximizing (Goodman et al. 2012), as “undershooting” (producing fewer children than would maximize fitness) is especially common (Mattison et al. 2018). A composite of fertility and child mortality – number of children surviving to reproductive age – is often considered the “gold standard” for measuring reproductive success (Jones and Bliege Bird 2015), but there are long-standing, unresolved debates in the behavioral ecology literature, both human and nonhuman, about the most appropriate way to measure fitness or reproductive success (McGraw and Caswell 1996; Strassmann and Gillespie 2003). In any case, measuring reproductive success is but one way to test HBE hypotheses (Maynard Smith 1978). Investigating how and why reproductive success is not being maximized in particular contexts can also give valuable insights into the mechanisms that drive fitness-relevant behavior, and this is now the focus of some research in HBE, especially in high-income, lowfertility contemporary populations (Stulp et al. 2016b). Demography is also integrated into HBE beyond the measurement of reproductive success. Demographic patterns are one feature of the environment, and so can be used by HBE researchers to understand how and why features of the environment shape human behavior and physiology. How do we behave when the environment seems risky (risk of mortality is high) versus stable (risk of mortality is low), for example? Or when others around us have a lot of children versus a few? Population structure, such as proportions of individuals in different age and gender groups, may also affect how individuals allocate resources between fitness-relevant behaviors, including mating and parenting effort, particularly given that in our cooperatively breeding species, “parenting” effort (investing in children) is not restricted only to investing directly in biological children (Chapter 12). In HBE, demographic indicators may thus be used as predictor variables in analyses focused on understanding behavioral variation as the outcome variable. Further, HBE also needs an understanding of demography because an individual’s fitness is measured relative to other

https://doi.org/10.1017/9781108377911.014 Published online by Cambridge University Press

Demography

309

people. It is therefore impossible to understand adaptive links between environment and behavior without accounting for demographic rates and population structure.

13.2

Leveraging HBE Theory and Demographic Methods for Improved Understanding of Population Phenomena The concept of fitness allows HBE to provide a unifying framework for otherwise disconnected ideas. Indeed, HBE’s strengths lie in an ability to synthesize disparate insights from across the social sciences (Kaplan and Gurven 2008), resulting in overarching theory to explain diverse phenomena, from age-specific fertility (Mace 1998) to parenting behaviors (Lawson and Mace 2009) to what people eat and why. By contrast, demography is historically more descriptive, attempting to understand the determinants (direct predictors) of demographic outcomes and the demographic consequences of policies, norms, and interventions. For example, Bongaarts (1978) – a demographer – famously delineated the “proximate determinants” of fertility by identifying the physiological and behavioral factors that directly influence fertility, including duration of breastfeeding, contraceptive use, sexual activity, and spontaneous abortion. Human behavioral ecology tends to be more interested in “distal” determinants of biodemographic outcomes, focusing on the things that drive parents to breastfeed for as long as they do (Mattison et al. 2015a), and otherwise alter inter-birth intervals in fitness-enhancing ways (Blurton Jones 1986; Low 1991). Traditionally demography has been a discipline interested in population-level, aggregate data, though in the last few decades the availability of individual-level data has meant a shift toward individual-level analysis of the determinants of fertility, mortality, and migration (“microdemography”: Caldwell et al. 1988). Demography therefore also shares an interest in the “distal” determinants of fertility, though often motivated by interests in policy-relevant factors (such as education: Martin 1995) rather than by hypotheses derived from a theoretical framework that assumes behaviors have been shaped by natural selection (an “ultimate” explanation). The next three sections consider fertility, mortality, and migration – the three components of population change – in HBE. The aim is to provide examples that demonstrate the power of demography to inform HBE analysis. Underpinning much of this work is life history theory (LHT), a framework from biology concerned with the allocation of energy across the life course, to the (partially) competing functions of growth, reproduction, and survival (Stearns 1992). As implied by this statement, LHT has much to say about demography (Chapter 2, Stulp and Barrett 2015; Box 13.1).

13.3

Analyses of Mortality in HBE Mortality, if somewhat understudied in human behavioral ecology, is important in understanding fitness. This is because an organism’s reproductive success depends on its ability to live sufficiently long to reproduce, take whatever steps are necessary to ensure that offspring themselves survive to reproduce (see Chapter 11), and adjust its

https://doi.org/10.1017/9781108377911.014 Published online by Cambridge University Press

310

Rebecca Sear, Siobhán M. Mattison, and Mary K. Shenk

Box 13.1

On the Uses and Misuses of Life History Theory

A model example of the way human behavioral ecologists can combine powerful theoretical frameworks from evolutionary biology with careful use of demographic and health data is Gibson’s and Mace’s (2002) research exploring the life history trade-off between health and reproduction, using the natural experiment of the installation of water taps in some villages in rural Ethiopia. Whereas some might anticipate energy savings being channeled toward improvements in maternal and child health, the women who experienced the most savings in energy (because they did not have to walk as far to collect water) experienced subsequent increases in fertility, with little evidence of improvements in child survival (see Figure B13.1.1). A cautionary tale of what happens when demography is ignored is provided by the “psychometric approach to life history strategy” (Figueredo 2007). This approach assumes there is a universal continuum of “life history strategy,” which can be measured in all humans using a series of psychometric questions. “Life history strategy” in evolutionary biology refers to the clustering of life history traits that characterize different species. “Slow” life history species, such as elephants, have slow growth, late first births, few offspring with long birth intervals, and senesce and die at relatively old ages; by contrast, “fast” life history species, such as insects, grow rapidly, produce offspring early and often, and die at younger ages (see Chapter 2). Life history traits are therefore demographic and health outcomes, but the psychometric approach instead extends these outcomes to encompass a suite of behavioral traits, including cooperativeness, promiscuity, and certain cognitive abilities, that supposedly cluster with life history outcomes. However, the psychometric tool used to measure “life history speed” does not contain any questions on life history or

Figure B13.1.1 Survival plot showing the divergence of average birth interval length in two Ethiopian villages after energy-saving water taps were installed in some villages (light line) but not others (dark line). Women with access to taps experienced a higher probability of birth per unit time than those without. From Gibson and Mace 2002.

https://doi.org/10.1017/9781108377911.014 Published online by Cambridge University Press

Demography

311

demographic traits, nor does it appear to have been validated against demographic traits. Recent research has found that psychometrically measured “life history speed” does not predict the demographic outcomes that are considered to differentiate “fast” and “slow” life histories in biology: Several studies have shown that a psychometrically measured “fast life history strategy” is associated with lower fertility than that of “slow life history strategists,” the opposite of what is seen in cross-species comparisons. While it is reasonable to anticipate that certain behaviors, such as time preference, may co-vary with life history strategy (Pepper and Nettle 2017), the “psychometric approach” in its current form cannot therefore be used to measure life history strategy (Sear 2020).

reproductive behavior in relation to others in a population (Roff 2002; Jones 2010). Mortality also plays important roles in shaping human decision-making, while such decision-making, in turn, shapes human mortality patterns. In other words, behavior and mortality are inextricably intertwined, and most of what interests human behavioral ecologists, including most centrally the evolution of human life histories, mating strategies, parental investment, and cooperative breeding, are better understood with consideration of prevailing patterns of mortality. In this section, we discuss research in HBE that has either used mortality as an outcome and/or as an ecological variable and consider how cooperative breeding and other behaviors may have shaped the species-typical human mortality pattern.

13.3.1 Mortality Outcomes as Tests of Hypotheses Mortality data can provide useful tests of hypotheses related to parental investment and life history theory. Which children survive, and why? Why do parents invest more in some children than others? Child mortality may be particularly sensitive to environmental circumstances and subsequent parental strategies in our species because children require substantial investment, not just from parents but also from alloparents (Hrdy 2009). For example, Hrdy (2000) noted that “mother love” is not universally expressed, but instead contingent on the environment: Maternal investment may be reduced or even withdrawn in circumstances that are not conducive to successfully raising children. While outright infanticide is rare, child mortality may still reflect variation in (allo)parental investment, either because of environmental constraints or strategic decision-making (which need not imply conscious decisionmaking). Variation in child mortality has therefore been used to examine the environmental circumstances and consequences of far-ranging behaviors, including sex-biased parental investment (demonstrating both son- and daughter-biased investment: Sieff 1990; Mattison et al. 2016a), alloparenting (where variation in child mortality has been linked to the presence of potential alloparents: Sear and Mace 2008; Du et al. 2022), and adoption and fosterage (Silk 1987). For example, Mattison et al. (2015b) analyzed child mortality in Taiwan, showing that adopted

https://doi.org/10.1017/9781108377911.014 Published online by Cambridge University Press

312

Rebecca Sear, Siobhán M. Mattison, and Mary K. Shenk

daughters, and especially daughters-in-law, experienced higher survivorship than children raised in their natal households. They interpreted this as an outcome of intentional strategies to support adopted children who would advance household interests, including perpetuating family lineages in ways that minimized conflict between mothers and daughters-in-law. Child mortality also serves as a measure of how successful parents have been in their decision-making (i.e., as a measure of reproductive success). Indeed, Strassmann and Gillespie (2002) have argued that child mortality is the key determinant of women’s reproductive success in high-mortality contexts which likely have characterized much of our evolutionary history. In such contexts, up to one in two children would perish before adulthood – and parents who found ways to mitigate mortality would have left more descendants. Adult mortality – while also a determinant of fitness – has been less often analyzed by human behavioral ecologists. This is due, in part, to the relatively low levels of adult mortality in human societies (Gurven and Kaplan 2007) and the difficulty in capturing infrequent events in large enough numbers via standard data collection methods. The few tests of adult mortality in HBE often find null results, which may (or may not) be due to its relative rarity. For example, the presence of kin was not associated with adult mortality in Aché hunter-gatherers, despite assumptions that cooperation among kin is often beneficial (Hill and Hurtado 1996). Nor were costs of reproduction evident in the adult mortality rates of women who had given birth to more children in rural Gambia (Sear 2007) in an analysis that tested whether the predicted life history trade-off between reproduction and survival might manifest in higher mortality in women who had invested more in reproduction.

13.3.2 Extrinsic Mortality and Consequences for Human Life History Decisions When and how an individual dies depends on factors that are both within and outside of an individual’s control. Extrinsic mortality is mortality that is due to the environment and unaltered by decision-making (Charlesworth 1994): Natural disasters, predation, pandemics, and resource shortfalls are typically considered sources of such mortality. Intrinsic mortality conversely is related to factors internal to the individual; cancers and cardiovascular disease typically result from such factors, which reflect both the aging process and behavioral influences on health (Stearns and Rodrigues 2020). Throughout much of human evolutionary history, mortality rates, both extrinsic and intrinsic, were much higher than they are today, with many deaths arising from infectious and parasitic disease, malnutrition, and human conflict (Gurven and Kaplan 2007). Still, compared to other nonhuman primates, human mortality has likely always been lower, with important implications for understanding the unusual behaviors and biological patterns that characterize humans. Extrinsic mortality has featured prominently in evolutionary biology and HBE because of an influential argument linking high extrinsic mortality to “fast” life

https://doi.org/10.1017/9781108377911.014 Published online by Cambridge University Press

Demography

313

history “strategies” (Williams 1957). The logic of the argument is captured neatly by the phrase “live fast, die young.” This argument hypothesizes that organisms in highmortality environments experience shorter life spans and consequently should increase their reproductive effort, producing more offspring earlier, when success is relatively assured (Charlesworth 1994). Low-mortality environments should conversely select for slower life history strategies, with later first births and fewer offspring, since the likelihood of dying before reproduction is lower, and more are likely to survive. Fast–slow continua that correspond to this model have been documented across numerous species (Promislow and Harvey 1990). Parental investments in offspring quality may also diminish in environments with high mortality, where significant investments in child quality are unlikely to be rewarded (Kaplan 1996). Thus, the fast-slow continuum may partially explain why humans – with exceptional longevity – reproduce comparatively late and infrequently, and with relatively high investments in their children (see Chapters 11 and 12). The “live fast, die young” argument is commonly used to explain variation in reproductive timing within our own species by human behavioral ecologists and other evolutionary behavioral scientists (Nettle 2010a). The extent to which this is appropriate has become the subject of significant debate, however (Stearns and Rodrigues 2020). If different processes explain variation at different levels of organization, then explanations used to understand between-species variation cannot necessarily be applied to understanding variation in life history strategies within species (Baldini 2015a; Zeitsch and Sidari 2020). Even more problematic is that recent critiques have noted its theoretical underpinnings are dubious (Moorad et al. 2019). Theoretically, high extrinsic mortality may predict a “fast” life, a “slow” life, or neither, depending on what other conditions hold, such as population growth rates (de Vries et al. 2023). There is, however, empirical evidence from our own species that age at first birth is linked to mortality risk in the environment. In both cross-cultural studies (Walker et al. 2006; Low et al. 2008), and studies within high-income populations (Wilson and Daly 1997; Uggla and Mace 2016a; Virgo and Sear 2016), women in environments with higher mortality risk tend to have earlier first births or otherwise demonstrate prioritization of reproduction at younger ages (e.g., lower abortion rates). Whether these empirical observations can be explained by some version of the “live fast, die young” hypothesis is not yet clear; the theoretical framework underpinning these associations needs fleshing out (Mathot and Frankenhuis 2018). At least one theoretical model does predict that higher extrinsic mortality should be associated with earlier reproduction, though it operates by reducing the intensity of density-dependent competition rather than decreasing the time available for reproduction (André and Rousset 2020). Another fruitful avenue of enquiry would be empirical research on within-population associations between mortality risk and variation in reproductive timing from a diverse range of populations, including those from outside the high-income world. We know that inadequate nutrition slows down growth and reproduction and also clusters together with high mortality rates, which might obscure associations between mortality and the timing of reproduction in

https://doi.org/10.1017/9781108377911.014 Published online by Cambridge University Press

314

Rebecca Sear, Siobhán M. Mattison, and Mary K. Shenk

nutritionally stressed populations (Coall and Chisholm 2003). Clearly, there are many open questions in this research area that human behavioral ecologists can contribute to.

13.3.3 Extended Longevity in Humans: Cause or Consequence?

Annual probability of death 1e-05 1e-04 0.001 0.01 0.1

1

A final area of particular interest in human behavioral ecology is how humans came to experience extended longevity. In their influential article Longevity Among Hunter-Gatherers, Gurven and Kaplan (2007) compare mortality patterns across chimpanzees, foragers, forager-horticulturalists, nonindustrial agricultural societies, and industrial societies. They found: “infant mortality is over 30 times greater among hunter-gatherers, and early child mortality is over 100 times greater than encountered in the United States” yet “this difference is only fivefold by age 50, fourfold by age 60, and threefold by age 70” (p. 340), and the modal age at death among huntergatherers who survive to adulthood is 72 years (range 68–78). Thus, despite characteristically high rates of infant and child mortality in nonindustrial conditions, survival at older ages is generally similar across populations such that extensive longevity appears to be a consistent feature of Homo sapiens, rather than a novel feature of contemporary environments with good nutrition and medical care (Figure 13.1). The fact that modern foraging populations residing in marginal environments achieve extended longevity strongly suggests that something particular to humans has allowed for a reduction in mortality – that is, that such reductions arise as a consequence rather than solely as a cause of shifting allocations into activities

Japan 2010 Japan 1947 Sweden 2010 Sweden 1900 Sweden 1800 Hunter-gatherer Acculturated h-gs Wild chimps Captive chimps

0

20

40

60

80

100

Age Figure 13.1 Age-specific mortality rates in human populations over time: the level of mortality has changed over time while the shape of the age-specific mortality curve has not. Adapted from Burger et al. (2012).

https://doi.org/10.1017/9781108377911.014 Published online by Cambridge University Press

Demography

315

affecting life histories. In particular, large-scale cooperation among individuals reduces environmental shortfalls, while alloparenting contributes to lower mortality for infants and children (see Chapter 12). Numerous additional human adaptations – technology, including control of fire and cooking, traditional ecological knowledge and cultural transmission of relevant information, sanitation – facilitate control of sources of mortality that would be deemed “extrinsic” for other species. These adaptations have strongly affected human demography in the last few centuries and open the scope for shifts in life history in the near future if mortality continues to decrease, as well as for additional feedbacks between these processes. In summary, applying an HBE lens to mortality helps to inform understandings of feedbacks between mortality environments and the behaviors they affect and to which behaviors respond. This explains species-characteristic patterns and also illuminates individual-level variation in the timing of life events and related behaviors. Mortality analysis in HBE can also help us to understand (allo)parental investment circumstances and strategies. There also remain important gaps in understanding variation in human mortality that require new answers and convergent approaches: For example, HBE has contributed relatively little to understanding the dramatic decline in mortality that has occurred worldwide over the past two centuries (Lee 2003a). This consequential topic has received substantial interest in demography, but HBE’s attention has been more focused on understanding the evolution of human longevity and the worldwide decline in fertility in recent decades. Paying more attention to mortality, alongside greater integration with demographic work on mortality, might prove fruitful in HBE.

13.4

The Analysis of Fertility in HBE Fertility has received more attention than mortality in HBE, perhaps because fertility is considered to be more influenced by behavioral decision-making than mortality, and HBE is fundamentally interested in behavior (Mattison and Shenk, in press; Low 1993). At the level of the species, human fertility is considered high, with inter-birth intervals significantly shorter than those seen in our great ape cousins (Emery Thompson and Sabbi, in press). Yet, both within and between populations, fertility varies significantly, and is patterned according to energetic status, wealth and education, among many other factors (Sear et al. 2016). Fertility is also a critical determinant of fitness (Jones 2010), though the total number of children produced is relatively rarely used as a fitness for proxy. This is partly for theoretical reasons – children need not just to be born but also to survive to adulthood to contribute to fitness – but also because of methodological challenges in measuring total fertility (see Box 13.2). HBE researchers have instead frequently tested hypotheses using the number of surviving children (reproductive success) as a fitness proxy, or they have analyzed separate components of fertility, such as the timing of onset and completion of reproduction or the spacing between births. Here, we discuss two types of analysis that human behavioral ecologists have conducted on fertility – first, to test hypotheses of interest to evolutionary scholars, such as those derived from parental

https://doi.org/10.1017/9781108377911.014 Published online by Cambridge University Press

316

Rebecca Sear, Siobhán M. Mattison, and Mary K. Shenk

Box 13.2

Methodological Challenges When Measuring Fertility

Researchers must approach the measurement of fertility with care, as it is easy to mis-estimate given difficulties of data collection, such as sensitivities around reporting children who have died. Indeed, the perceived difficulty in collecting accurate fertility data from men is one reason why fertility analyses are often performed only for women; men may suffer more recall bias or underreport children whom they do not live with (Rendall et al. 1999). On this point, HBE differs from demography in that male fertility is frequently analyzed, given evolutionary interest in fitness differentials for both sexes. There are also challenges associated with analyzing fertility data. Calculating the total number of children born (or number surviving to adulthood) can be done only for individuals who have completed their reproductive careers, restricting sample size and limiting generalizability, as postreproductive individuals may not be representative of those still reproductive. In cross-sectional data, there is also the problem of temporally matching fertility with independent variables, such as wealth, that may change over an individual’s lifetime: If one has data only on wealth during a postreproductive period, to what extent can this be used as a proxy for wealth before and during the reproductive life span (Mattison et al. 2022b)? In some contexts and for some measures, this might be reasonable, but not in others: For women in higher income, lower fertility contexts, having children often results in a wealth penalty because of trade-offs between caring for children and employment (Kleven et al., 2019), meaning any association between wealth and fertility may result from reverse causation. Longitudinal data can partially circumvent such problems, but still pose challenges for analysis (Stulp et al. 2016a). Analyzing age-specific fertility (number of births at a given age) or the components of fertility (age of first and last births, length of inter-birth intervals) is also commonly done in HBE. This is partly because the components of fertility together determine the total number of children born and so can be used as proxies for total fertility, or reproductive success. In higher fertility populations, those with higher age-specific fertility, earlier first births, later last births, or shorter birth births will have higher fertility at the end of their reproductive life spans, all else equal. But the components of fertility can also be useful for testing hypotheses in their own right; for example, age at first birth is a key life history variable, and age at last birth has been used to test theories about menopause (Towner et al. 2016; Mattison et al. 2018). Analyzing the components of fertility may be also be useful because fitness is a relative measure affected by other population parameters: For example, all else equal, in growing populations, an earlier start to reproduction will result in higher relative reproductive success (Jones 2010).

https://doi.org/10.1017/9781108377911.014 Published online by Cambridge University Press

Demography

317

Using the scheduling of reproductive events as a proxy for total fertility, however, may not work well in lower fertility populations: early first births and short birth intervals may not translate into higher numbers of children overall in contexts where women have relatively few births. Indeed, birth intervals are often shorter in comparatively lower fertility contexts where women have more resources and face fewer health risks of closely spaced births, but may experience greater costs of being out of the labor force during their childbearing years. In such contexts, what determines total fertility is whether women go on to have a second, third, or subsequent birth. These patterns can be studied using parity progression ratios (Mattison et al. 2016a). For male fertility, the total number of children (or surviving children) is most commonly used when analyzing fertility. The timing of reproduction may be less informative for men; for example, birth intervals can be short if men father children with more than one woman. It is worth noting, however, that men’s reproductive life courses are often similar to women’s given that monogamous marriage of similarly-aged spouses is the most common family form into which children are born.

investment or life history theories, and second, analyses in which HBE has contributed to understanding variation in fertility as a goal in itself, particularly in relation to the sharp decline in fertility that has happened in most populations over the past two centuries as part of global demographic transition.

13.4.1 Fertility Is, Counterintuitively, Often a Poor Proxy for Reproductive Success, Which Underscores Vexing, Yet Exciting Questions in HBE about Fertility Transition It is intuitive to begin with the premise that fitness maximization is best achieved by maximal fertility. However, ever since Lack (1954), behavioral researchers have realized that maximal fertility may often be detrimental rather than beneficial. Too many children may frequently be difficult to support. Biological and energetic constraints help to adjust the pace of reproduction such that when women have few reserves, are under lactational stress, or otherwise energetically stressed, they undergo periods of amenorrhea, relatively low fecundability (probability of conception), and high probability of pregnancy loss. This helps to explain why, when energy becomes available (e.g., due to labor-saving technology), these checks on fertility are lost and the pace of childbearing increases (Gibson and Mace 2002: see Box 13.1). At the same time, having too few children is rarely fitness-maximizing; the very low fertility seen in many contexts around the world (often under two children per woman, roughly the level of fertility needed to ensure population size remains constant) is challenging to explain from an evolutionary perspective (Burger and

https://doi.org/10.1017/9781108377911.014 Published online by Cambridge University Press

318

Rebecca Sear, Siobhán M. Mattison, and Mary K. Shenk

4 3 2 0

1

Children per Woman

5

6

DeLong 2016). Thus, an “intermediate” number of children is often expected to be fitness-maximizing. An acute challenge to Lack’s hypothesis, and indeed to evolutionary understandings of fertility and reproductive success, arises in the context of the demographic transition – the worldwide transition from high mortality and high fertility to low mortality and low fertility (Kaplan 1996; Borgerhoff Mulder 1998b; Shenk et al. 2013). Life history theory captures Lack’s theory of intermediate offspring number in the quantity-quality trade-off. According to the principle of allocation, a unit of energy that is devoted toward one function cannot be allocated to a competing function. Hence, increases in the number of children are expected to be associated with declines in child quality as parental investment in each child decreases. Under this principle, we would expect greater abundance of energy or resources to decrease the strength of the trade-off; in other words, as individuals become wealthier, we anticipate more children rather than fewer. Yet, in aggregate, the opposite trend prevails. Worldwide, over the past two centuries, fertility rates have dropped from around five to seven children per women to close to two (the global average fertility in 2021 is 2.3 children per woman; Figure 13.2). This transition has occurred at different times and paces in different populations, but almost all national populations have now demonstrated at least some drop in fertility, and many average below two children per woman. Why should this be? Is fertility the wrong measure of reproductive success? Has mismatch resulted from recent environmental changes that mean that the evolved physiological and behavioral mechanisms that determine our fertility are now misfiring, for example, by leading humans to strive for status in ways that are detrimental to reproductive success? How can HBE help us to understand why fertility falls as access to resources improves?

1950

1960

1970

1980

1990

2000

2010

2020

Year

Figure 13.2 Illustration of the global fertility transition from 1950 to 2021 during which time the Total Fertility Rate halved, falling from 5 to 2.5 children per woman. Redrawn from Our World in Data: https://ourworldindata.org/.

https://doi.org/10.1017/9781108377911.014 Published online by Cambridge University Press

Demography

319

Human behavioral ecologists have added important insights that have helped to tackle the paradox of fertility decline, once considered the “central challenge of evolutionary biology” (Vining 1986, but see Stulp and Barrett 2016 for a critique). Among these, HBE researchers have described the logic of decreasing fertility when extrinsic mortality drops, as parents no longer need to “overcompensate” for the risk of loss by having more children than they ultimately desire. Further, they have offered the hypothesis that declining fertility may be a strategy of wealth concentration to ensure the preservation and long-term continuity of lineages whose success is based on material wealth and assets (Mace 1998) though this strategy may backfire in very low fertility populations (Goodman et al. 2021). The leading explanation in HBE, modeled after Becker’s (1981) influential work in economics, suggests that contemporary environments induce parents to invest intensively in children, resulting in feedback loops where the costs of raising children, especially in association with formal education, ramp up (Kaplan 1996; Mace 1998). The reproductive payoffs, in terms of grandchildren, to this intensive investment are delayed, which makes this strategy more likely when mortality is low. But intensive and extended parental investment also becomes increasingly necessary in such environments in order to achieve greater social success and status (Shenk et al. 2016a), potentially leading to a feedback loop in which one must invest more in fewer children simply to maintain one’s social position. Finally, HBE considers the very real possibility that at least some degree of fertility transition arises due to the spread of low-fertility norms that may be maladaptive, even if the propensity to adopt norms is, on average, beneficial (Colleran 2016). All of these explanations share features of similar ones proposed in mainstream demography; yet, they unite motivations under a single currency – fitness – in explaining why fertility changes in response to environmental change. This section illustrates that HBE can have much to say about behaviors that appear not to be adaptive in contemporary environments. While HBE starts with the premise that natural selection has shaped behavior to be adaptive in certain environmental circumstances, an important component of HBE analysis is to identify when and why behavior does not appear to be adaptive. Understanding what it is about contemporary environments that results in individuals “undershooting” fertility, in terms of what an adaptive perspective might expect, can be valuable not just for improving our understanding of fertility behavior, but also in terms of policy implications. Indeed, in many high-income countries, people are also “undershooting” in terms of their own desired fertility, which is higher than actual fertility in Europe and North America (Beaujouan and Berghammer 2019). Identifying the characteristics of high-income populations (e.g., the lack of support for child-rearing arising from expectations that parents alone should be able to successfully raise children) that lead to individuals failing to meet their fertility goals may have considerable policy significance.

https://doi.org/10.1017/9781108377911.014 Published online by Cambridge University Press

320

Rebecca Sear, Siobhán M. Mattison, and Mary K. Shenk

13.4.2 Fertility Is Used to Test Hypotheses Related to Mode of Subsistence, Life History Trade-offs, and Parental Investment Challenges in measuring and theorizing fertility notwithstanding, indicators of fertility (including number of surviving children) have been widely used to test hypotheses designed to understand variation in human biology and behavior (Voland 1998; Sear 2015). Male reproductive success has been used to test hypotheses about the fitness consequences of factors such as wealth, status, and skill, given the emphasis in evolutionary research on the importance of these factors for male fitness (Nettle and Pollet 2008). This research generally confirms the positive link between wealth, status, and skill for men, in both higher- and lower-fertility contexts (Stulp and Barrett 2016). In both men and women, associations between height and reproductive success have been explored, in order to better understand how physical characteristics are linked to fitness through both reproductive partner preferences and energetic factors (Stulp et al. 2012b). Reproductive success has also been used to examine the importance of social relationships for fitness (Page et al. 2017). In women, links between reproductive success and multiple variables, including access to resources, have also been explored (Borgerhoff Mulder 1987). Other indicators of fertility have been used to test a wide range of hypotheses, including, for example, that fertility will be higher for women who have more support from kin for child-rearing (Snopkowski and Sear 2016). The timing of first births has attracted attention in HBE, particularly exploring whether mortality risk and other indicators of adversity in early life are associated with earlier first births. In high-fertility populations, the length of birth intervals is often assumed to indicate sex-biased parental investment: This approach was taken in a study of Gabbra pastoralists in northern Kenya, where birth intervals were shown to be longer after earlyborn sons, suggesting that parents preferentially invested in these children in this patrilineal population (Mace and Sear 1997). Yet, there are occasions when the study of total fertility (the number of children ever born) can be used to answer questions of interest in HBE. For example, fertility provides a useful means to assess ongoing debates about the nature of subsistence change and its effects on human lifeways: A long-standing assumption in anthropology is that fertility is highest (and fastest) among agriculturalists and lower (and slower) in mobile foragers and pastoralists. Subsistence strategy affects both dietary and physical activity patterns, each of which are known to influence fecundity (Jasienska et al. 2017), and it also affects relationships among group members, which, in turn, influence fertility through levels of both parental and alloparental investment. A shift toward sedentary farming may be associated with a shift toward greater reliance on close kin and the nuclear family, rather than the diverse relationships hunter-gatherers tend to maintain (Kraft et al. 2023); kinship systems may also differ between foragers and farmers. Some early studies provided support for the hypothesis that fertility is higher among farmers than foragers (Bentley et al. 1993), but stronger tests require comparative data from multiple study populations.

https://doi.org/10.1017/9781108377911.014 Published online by Cambridge University Press

Demography

13.5

321

Migration/Mobility and HBE Migration is a key parameter of interest from both evolutionary and demographic perspectives. In evolutionary theory, migration drives gene flow and the formation of new populations, while in demography, migration is part of the balancing equation that describes how populations change over time. While migration is a hot topic across the social sciences, it is understudied in human behavioral ecology. Existing studies of migration in demography generally focus on why people migrate and/or describe patterns of migration in terms of age, gender, origin, and destination, whereas publications on migration in HBE focus on evolutionary questions, drawing particularly on life history theory and evolutionary approaches to territoriality. These include the study of dispersal, often focused on gendered patterns of migration and associated constraints on such movement, traditionally in the context of postmarital residence patterns (Chapter 10), but increasingly in the context of market integration and other forms of social change. Such approaches are united by an interest in costs versus benefits and opportunities versus constraints in terms of the relative access to resources, availability of potential reproductive partners, and conditions for reproduction offered by particular ecologies – and thus focus on why, how, and when individuals strategically seek out new ecologies that offer improved opportunities. Dispersal in HBE is aligned with the study of mobility in demography, given it may involve only relatively short-distance moves, whereas migration is typically defined with reference to distance, for example, crossing some kind of administrative boundary (such as between counties or countries). Nevertheless, there is potential for considerable synergy between the social science and HBE literatures on migration (Clech et al. 2020).

13.5.1 Patterns of Human Dispersal Human behavioral ecology has modeled dispersal decisions considering a variety of benefits and costs. Potential benefits to dispersal include access to new reproductive partners (Clarke 1993), novel territories and resources (Hamilton and May 1977), and reduced risk of inbreeding if there is a high level of consanguinity in the natal territory (territory of birth) (Moore 1993). Key costs include time spent in dispersal, opportunity costs of leaving the natal territory (such as loss of local ecological and cultural knowledge), and energetic costs of dispersal, including hunger, increased risk of injury or disease in novel territories (where the disperser may lack local knowledge and experience), and importantly loss of access to help from kin who remain in the natal territory (Hill et al. 2011; Wood and Marlowe 2011). As in other species, dispersal in humans is patterned by sex, and human behavioral ecologists have been instrumental in linking both individual patterns of behavior and group norms to relevant evolutionary principles. When do married couples reside with the wife’s parents, or the husband’s parents? HBE informs these demographic decisions by investigating the ways that resources and social support help women and men to reproduce. Foraging is associated with a bias toward female philopatry

https://doi.org/10.1017/9781108377911.014 Published online by Cambridge University Press

322

Rebecca Sear, Siobhán M. Mattison, and Mary K. Shenk

immediately after marriage (known to anthropologists as matrilocal residence, the custom of married women living with or near their kin; see Chapter 10), often related to a period of bride service. Over longer time periods, though, forager residence patterns are often flexible and mobile, allowing individuals to follow seasonal availability of resources and prioritize opportunities for cooperation with kin or other group members (Kramer and Greaves 2011b; Wood and Marlowe 2011). Horticulture (farming with relatively simple, human-powered technology), expansive resource bases, and/or male absence (due to fishing, long-distance trading, warfare, etc.) are often associated with female philopatry and either uxorilocal or natalocal residence (the custom of people staying in their natal household or community after marriage) alongside cooperation in subsistence and childcare with female kin (Leonetti et al. 2007; BenYishay et al. 2017; Mattison et al. 2018). By contrast, the presence of economically defensible resources such as land under intensive agriculture (agriculture requiring technology such as the plow) provides incentives for territoriality and resource defense (Dyson-Hudson and Smith 1978; Cashdan et al. 1983; Shenk et al. 2010; Mattison et al. 2016b), which in turn are commonly associated with male philopatry and female dispersal, consistent with virilocal postmarital residence patterns. This is especially true if higher levels of resource access lead to greater variance in male than female reproductive success (e.g., through polygyny or inheritance) (Boone 1986; Hrdy and Judge 1993; but see Brown et al. 2009). Multigenerational sharing of resources, especially through allocare and inheritance, has also played a significant role in shaping patterns of dispersal in humans. Dispersal is often delayed by ecological constraints such as few available territories that make migration difficult (Koenig et al. 1992; Emlen 1995; Strassmann and Clarke 1998). In situations where individuals have access to good reproductive opportunities through either allocare or a strong resource base, it may be strategic to delay or forego dispersal and/or delay reproduction (Turke 1988; Low and Clarke 1991; Voland and Dunbar 1995). Benefits to delayed dispersal may include increased inclusive fitness from “helping at the nest” (raising one’s siblings) and/or increased opportunities to inherit a territory/estate/resource base from parents. Yet, delayed dispersal may be driven instead by the costs of dispersing due to ecological constraints on the resources needed for reproduction. The combination of these costs and benefits may lead to both reproductive delays (and potentially lower fertility) and to the formation of extended family units (Emlen 1995), a phenomenon that can be highly elaborated in human societies. While inheritance of territories (e.g., nesting sites) exists in many species, institutions regulating the importance of inheritance are particularly elaborated in humans given our evolution of language, cultural norms, and widespread control of heritable wealth (Hartung 1976). Norms and laws surrounding inheritance can both promote and constrain dispersal decisions depending on the type of resources inherited and the gender and birth order of the child or children who inherit territories or forms of property (Hartung 1985; Koenig 1989; Clarke and Low 1992; Clarke 1993; Strassmann and Clarke 1998; Towner 2002). This leads to a fundamental distinction between heirs and non-heirs in human societies with heritable wealth

https://doi.org/10.1017/9781108377911.014 Published online by Cambridge University Press

Demography

323

(Goody 1976). While designated heirs, or those from rich territories, smaller families, or with lower birth orders, often benefit from delaying or foregoing dispersal, if there is no estate to inherit or if one is not an heir, then the opportunity costs of dispersal are lower (Boone 1986). Non-heirs, by contrast, are more likely to benefit from dispersal, especially those in regions with harsher environments or children from larger families or born at higher birth orders. Finally, reproductive value (see Chapter 2) – along with age and gender patterns of reproduction and reproductive opportunity more generally – strongly influences patterns of dispersal and migration. As in most species, age is a key factor affecting the likelihood of dispersal. Across human societies, most people move away from their parents or family home in their late teens and twenties (Clarke and Low 1992). These are the people with the lowest opportunity costs of caring for children (which makes them good helpers at the nest if they have siblings at home) but who also likely benefit more from the opportunities that dispersal may provide (Strassmann and Clarke 1998; Towner 1999, 2002). Finally, in many societies, as in many species, males are more likely to migrate long distances than females as men often may have more to gain from additional resources or reproductive opportunities (Boone 1986). Yet, among humans virilocal and neolocal residence (the custom of a married couple starting a new residence) are common in the majority of human societies, at least in the ethnographically known recent past (Shenk et al. 2019); thus women commonly change residence at marriage and in some societies may be more likely to disperse/ migrate than are men, suggesting that either women or their families frequently have something to gain from female dispersal.

13.5.2 Push and Pull Factors in the Context of Market Integration and Urbanization While behavioral ecologists have traditionally focused on the costs and benefits of philopatry vs. dispersal, demographers studying human migration have had a parallel discussion on “push” vs. “pull” factors. Push factors are reasons why an individual would wish to leave one region in favor of another, generally markers of poor local opportunities, while pull factors are better opportunities in another region drawing people to a new community (Massey et al. 1994; Schoorl et al. 2000). Common push factors include ecological degradation or disasters, land saturation, high mortality, limited job prospects, or social factors such as discrimination, while pull factors may include less restricted access to land or other resources, good job prospects, or better institutional support (e.g., healthcare access). Overall, there has been limited emphasis on migration among human behavioral ecologists, despite some of the early work in ecological evolutionary demography focusing on migration in historical datasets (Low and Clarke 1991; Voland and Dunbar 1995; Towner 1999). This may be changing, however, as in the last decade work in HBE has increasingly focused on the process and consequences of market integration. Market integration spurs major changes in subsistence systems and profoundly alters systems of opportunities and constraints, impacting many aspects of reproductive decision-making, health, and well-being, with significant

https://doi.org/10.1017/9781108377911.014 Published online by Cambridge University Press

324

Rebecca Sear, Siobhán M. Mattison, and Mary K. Shenk

consequences for fertility and mortality (Lu 2007; Mattison et al. 2022b). Yet, market integration also impacts demography through its effects on the costs and benefits of migration versus philopatry and its capacity to initiate or hasten the process of urbanization. There are clear theoretical links between parental investment, fertility, and urbanization (Hrdy 1992; Mattison and Neill 2013) which may drive fertility to especially low levels due to either constraints on resources and reproductive opportunities (Mace 2008) or to high levels of inequality and social competition (Shenk et al. 2016a), which present interesting opportunities for work in HBE. HBE has the potential to contribute significantly to our understanding of migration, given that the process can be a key driver of access to resources, reproductive opportunities, and social support. While previous work has mainly focused on dispersal in small-scale social contexts, evolutionary approaches can provide a stronger theoretical framework combining push and pull factors in the context of ongoing processes of market integration and urbanization which have led to increasing migration to cities and across borders, along with increasing contrasts between rural and urban environments as contexts for demographic processes. Clech et al. (2020), for example, have used parental investment theory to understand rural–urban migration in Ethiopia, finding migration reflects both sibling competition and cooperation, depending on family situation and life cycle stage: last-born sons with older brothers are likely to migrate to urban areas to avoid competition with siblings, though in times of hardship first-born sons may migrate in order to provide economic support to families. We thus expect the evolutionary study of migration to be an important growth area of research in the coming years. In our discussion so far, we have followed the demographic tradition of discussing mortality, fertility, and migration separately. Many topics of interest to human behavioral ecologists involve consideration of multiple demographic outcomes, however. For example, Boxes 13.3 and 13.4 consider the issues of kinship and father absence, which incorporate multiple demographic outcomes simultaneously. Such cross-cutting topics are perhaps particularly interesting considering the small but growing body of applied HBE work that aims to inform research on policy issues, such as the health and demographic impacts of development interventions (Gibson and Lawson 2014), marriage patterns (Shenk 2007; Schaffnit and Lawson 2021), or kinship systems (Reynolds et al. 2020).

13.6

Key Demographic Data and Methods in HBE

13.6.1 Primary and Secondary Data Offer Complementary Means of Investigating Important Questions in HBE and Demography HBE researchers have often relied on primary, individual-level data collection from small-scale societies. Sometimes living for years in their study communities, researchers with this methodological emphasis meticulously collect data on individuals well known to them, reconstructing demographic statuses and events over the lifetime, including births, deaths, marriages, divorces, and incidences of movement in

https://doi.org/10.1017/9781108377911.014 Published online by Cambridge University Press

Demography

Box 13.3

325

Kinship, Health, and Demography

Kinship is foundational to social structure and health, as kinship organizes access to social and material resources including through sex-biased dispersal (Ly et al. 2019, marriage, inheritance, and fertility (Mattison et al. 2019). Evolutionary perspectives differ from non-evolutionary perspectives that consider the role of kinship in producing demographic and health outcomes. Whereas kinship systems are viewed as causal in much of demography, evolutionary perspectives posit that it is variation in ecology (resource distribution and gradients) that drives variation in domains of kinship and subsequent health and demographic outcomes. In other words, kinship institutions are not always causal, but reinforce behaviors that are, on average, adaptive for members of a given kinship system, under the particulars of social and ecological environments (Shenk and Mattison 2011). This “top-down” approach to understanding the relationship between ecology, kinship, and demography complements more typical “bottom-up” perspectives drawn from mainstream demography (Kaplan and Gurven 2008; Sear 2015). It may also provide insights that appear counter-intuitive from other perspectives. We illustrate through examples from female-biased kinship. Limited resource gradients lead to relative equality between the sexes in matrilineal kinship systems. Social scientists have long posited a relationship between matriliny, lower fertility, and improved health outcomes (Mattison 2010a). One pathway thought to mediate this relationship is higher female autonomy, which leaves women in stronger positions to advocate for themselves and their children. A second pathway sees cultural valuation of daughters as responsible. Female-biased kinship systems lack the strong son preference apparent in more patriarchal systems (Das Gupta et al. 2003; Mattison et al. 2016a), and infrastructures that erode the importance of patriarchal kinship systems have been associated with improved welfare for women and children (Fong 2002). These models posit that female-biased (or at least, non-patriarchal) kinship systems produce differences in demographic and health outcomes. By contrast, HBE posits that kinship systems themselves are products of differences in social and ecological environments, such that it is differences in ecology that produce variation in kinship systems and their associated health and demographic outcomes. In the case of female-biased inheritance systems, two issues are paramount. First, the ecology must produce resources that reward defense. If resources are distributed homogeneously, they are not conducive to group defense, and inheritance systems are not anticipated to evolve (Mattison et al. 2016b). Second, the subsistence base should not disproportionately support male reproductive success (Sieff 1990; Holden and Mace 2003b; Mattison et al. 2019, 2021); otherwise, males are predicted to take control of resources and move kinship toward son-biased inheritance systems (Alesina et al. 2013).

https://doi.org/10.1017/9781108377911.014 Published online by Cambridge University Press

326

Rebecca Sear, Siobhán M. Mattison, and Mary K. Shenk

Evolutionary researchers have also explored why female-focused kinship systems are sometimes associated with improved health and lower fertility. Research from this perspective has shown that women who are in positions to pursue their own reproductive agendas are less likely to pursue levels of fertility that compromise health (Leonetti et al. 2007). Furthermore, matriliny is associated with increased gender egalitarianism (Mattison and Shenk, in press) and minimized institutionalized differentiation between the sexes (Reynolds et al. 2020), thus, the relative welfare of daughters is likely to be improved. Ecological systems that promote matrilineal kinship may also favor wide-scale cooperation evident in re-distributive economies and improved health and well-being (Mattison et al. 2021; Mattison and Shenk, in press).

Box 13.4

Father Absence in Bangladesh

Many topics of interest in demography and HBE involve consideration of multiple demographic outcomes. For example, a longstanding debate in evolutionary anthropology and psychology focuses on the effect of father absence on the reproductive outcomes of daughters, including earlier ages at menarche and first birth (Draper and Harpending 1982; Belsky et al. 1991). Some of this literature takes inspiration from ideas in life history research in biology, such as the “live fast, die young” hypothesis (Chisholm et al. 1993), and some assumes that father absence in early life is an indicator of an adverse early life environment, but the multiple theoretical frameworks proposed are not well integrated (Ellis 2004; Sear et al. 2019). Empirical studies have also largely been conducted in Western contexts where most father absence occurs due to divorce, leaving in doubt whether it is father absence, per se, or the effects of family conflict, reduced paternal investment, or other confounding factors that produce such patterns. Shenk et al. (2013; for a Bayesian re-analysis showing similar results, see Soussan 2018) analyzed results of a natural experiment in rural Bangladesh where three types of father absence co-exist: some fathers died while their daughters were young, other parents had been divorced or fathers had abandoned their families, while yet other fathers worked as labor migrants in cities or abroad and, though absent for months or years, also sent large sums of money home in remittances. The three types of father absence have distinct associations with daughter’s age at first birth (Figure B13.4.1) compared to daughters of present fathers. While divorce/abandonment (associated with social stigma and the loss of investment from fathers and paternal relatives) was associated with earlier ages of first birth, father death was associated with

https://doi.org/10.1017/9781108377911.014 Published online by Cambridge University Press

Demography

0.25

0.50

0.75

1.00

Survival Functions for Age at First Birth (Adjusted)

0.00

Proportion of Women

327

0

10

20

30

40

Age in Years Father Present Father Divorced or Deserted

Father Migrant Father Dead

Figure B13.4.1 Survival functions for age at first birth for women experiencing different

types of father absence in Matlab, Bangladesh. Survival curves adjust for socioeconomic and demographic variables of the woman and her husband. From Shenk et al. (2013), reproduced with permission from Springer Science Business Media New York.

modest delays (likely related to poverty and reduced social networks for negotiating a marriage), while paternal labor migration was associated with significantly delayed ages of first birth (related to heavy investment in daughter’s education and spouse quality). Recent cross-cultural and comparative work (Sheppard et al. 2014; Sear et al. 2019) suggests the Bangladesh case is not unique. Instead, the effects of father absence are far from uniform cross-culturally and are linked to local socioecological circumstances. The strongest and most accelerating associations between father absence and daughter’s life history are found in modern industrialized contexts. In such environments, high levels of investment are important for social and reproductive success, but nuclear family structures often limit access to alloparental support, making the absence of a high-investing father very consequential. Such findings also have important policy implications, reinforcing that the context of father absence is important for understanding its consequences, that wealthy industrial societies are not normative benchmarks against which to measure other societies, and refocusing the search for solutions at the structural level rather than on individual family strategies.

https://doi.org/10.1017/9781108377911.014 Published online by Cambridge University Press

328

Rebecca Sear, Siobhán M. Mattison, and Mary K. Shenk

and out of groups, as well as genealogies that allow individuals to be linked together in families and lineages. Early exemplars include Nancy Howell’s Demography of the Dobe !Kung (1979). Hill and Hurtado’s Ache Life History (1996) then fomented a ‘new wave’ of HBE that united these data collection methods with new and sophisticated forms of statistical analysis emerging in demography and related disciplines. More recent examples include Nicholas Blurton Jones’ Demography and Evolutionary Ecology of Hadza Hunter-Gatherers (2016). Such primary data collection can produce rich information, but there are drawbacks to first-hand data collection, not least relatively small sample sizes, which impose significant limitations on analysis of low-probability events. There are also considerations of the research burden placed on populations traditionally of interest to human behavioral ecologists, including their lack of involvement in co-creating the research produced (Urassa et al. 2021), as well as the inaccessibility of long-term fieldwork to many scholars experiencing constraints from economics to family building to disability (Mattison et al. 2022a). At the same time, human behavioral ecologists, given their often strong relationships with community partners and longterm fieldwork, are in good positions to engage in more equitable practices of knowledge production (see McKerracher and Nuñez-de la Mora 2022) and have been leading the call for such (Urassa et al. 2021). Secondary (sometimes referred to as existing) datasets – those collected by someone other than the researcher who analyzes them – can serve as a useful alternative to first-hand data (Smith et al. 2011). HBE researchers are fortunate in the sheer amount of existing data available for our species, for example, in the many accessible large-scale survey datasets, as well as longitudinal and/or multi-wave datasets, relevant for addressing questions of interest to HBE (Mattison and Sear 2016). Multi-wave and longitudinal datasets are especially useful for studies that concern multigenerational variables, including wealth transfers, and long-term fitness outcomes of different behavioral strategies. Yet, secondary datasets are also subject to a number of important methodological challenges, including systematic biases in recall (e.g., a propensity to not report deaths of certain classes of individuals such as the unbaptized); biases in sampling (marginalized populations are often excluded from datasets that aim to collect representative data from national populations); and only including variables deemed of interest by data collectors. Large-scale secondary datasets also leave scholars with many “researcher degrees of freedom” that affect how they operationalize variables and conduct analyses and hence draw their conclusions. Pre-registering protocols may decrease unintentional researcher biases (Munafò et al. 2017), but it must be recognized that pre-registrations for secondary data analysis will necessarily look quite different from the focused experimental hypothesis tests that pre-registrations were originally developed for. The increasing use of secondary data sources in HBE (Nettle et al. 2013) brings the discipline even closer to demography, where such data sources are most commonly used, and provides more reason for HBE to engage with demography given the discipline’s long experience of working to overcome data limitations. There are also data sources used in demography that HBE could exploit more often, such as

https://doi.org/10.1017/9781108377911.014 Published online by Cambridge University Press

Demography

329

population registers – the governments of some particularly well-resourced countries, including those in Scandinavia, collect records on their populations more or less in real time (Uggla, in press). The increasing linkage of such administrative data to other datasets or surveys also expands the range of data types available for analysis. Demography is also now making use of new “big data” sources (arguably, it has always been a “big data” science), such as mobile phone records and social media usage (Kashyap 2021). These new sources of data have their own set of limitations, not least that they tend to be most widely available for high-income populations, but they have the advantage of providing detailed “real-time” data that can be used to explore behavior. Therefore, these records may provide exciting new sources of data for HBE researchers who are interested in topics such as how behavioral adaptation and social learning arise over short time-scales and the consequences of this for health and well-being.

13.6.2 Methods of Analysis Human behavioral ecology draws heavily on methods developed in demography to describe population processes, which can be useful for developing a descriptive understanding of a population. Demography excels at description, and descriptive and inductive methods should also be recognized as highly important in scientific, hypothesis-testing, disciplines such as HBE. Numerous resources are available that introduce methods of demographic analysis, including types of data used, and how to calculate demographic variables, including mortality, fertility, and migration rates. Such methods, generally termed formal demography, constitute a distinct area of study (see Box 13.5). Methodologically, demography and HBE are more similar than they are different. Although demography has traditionally focused on description, these insights are effectively inductive, serving as observations from which general theories can be tested (Kaplan and Gurven 2008). Formal quantitative methods in demography are also sometimes complemented by qualitative ones that may offer important insights (Bledsoe et al. 1998), just as HBE researchers are increasingly producing qualitative research alongside the discipline’s traditional quantitative strengths (Schaffnit et al. 2019b). Developing a better understanding of the range of methods used in demography can reinforce and challenge HBE theory in ways that help to refine understandings of human demographic behavior.

13.7

Conclusion Human behavioral ecology is full of demography, and HBE researchers would do well to engage with the considerable body of both methodological and substantive research produced in demography in order to improve their own scholarly endeavors. Given demography’s centrality to formal measures of fitness, many human behavioral ecologists may in fact already be doing demography without even realizing it. Through greater engagement with demography, HBE may be able to expand the data

https://doi.org/10.1017/9781108377911.014 Published online by Cambridge University Press

330

Rebecca Sear, Siobhán M. Mattison, and Mary K. Shenk

Box 13.5

Demographic Methods

Formal demography is a branch of demography focused on calculating demographic rates and establishing mathematical relationships between them. Here we summarize the most widely used demographic indicators. Researchers in HBE typically analyze behavior at the individual level, whereas in formal demography the aim is generally to take individual-level data and calculate population-level rates and indicators. Demographic analysis can be based either on cohorts or periods. A cohort is a group of people who experienced the same event during a particular time period (e.g., all women born in the United States in 1972); cohort analysis follows cohort members across time and records demographic events like birth, marriage, or death. In contrast, period analysis uses cross-sectional data on events within a particular time period (e.g., all births in the United States in 1972). Measures of Fertility A commonly used population-level indicator of fertility is the Total Fertility Rate (TFR), the average number of children a woman would have if she were to survive to age 50 and experience current age-specific fertility rates throughout her reproductive life. As a period measure, TFR does not describe the experience of any actual woman, but instead creates a synthetic cohort of women of different ages. TFR is highly interpretable, since the unit of measurement is number of children. Recent (2022) national-level TFRs range widely from 0.8 in South Korea to 6.7 in Niger,2 though subnational and/or historic populations have varied even more widely. Maximum fertility at the population level is ascribed to North American Hutterites in the 1930s, who averaged around 11 children per woman (Eaton and Mayer 1953). While TFRs are widely used in demography to understand current fertility levels and document how fertility changes over time (important for policy), cohort measures of fertility, typically calculated for postreproductive women, are more often used in HBE. Completed Family Size, for example, is the average number of children per woman in a particular cohort. Fertility is often analyzed in reference to the age of the mother, as the probability of birth varies by age. Age-specific fertility rates are calculated by dividing the number of children born to women of a given age by the number of women that age in the population, and they can be calculated for both periods and cohorts. Fertility can also be analyzed by parity (the number of children a woman has birthed), as her past fertility may affect her decision to have another child. The Parity Progression Ratio (PPR) is the probability that a woman will progress to the next birth given that she already has a certain

2

www.prb.org/; https://ourworldindata.org/.

https://doi.org/10.1017/9781108377911.014 Published online by Cambridge University Press

Demography

331

number of children. Factors influencing fertility often differ by birth order/ parity, and different parities may show different trends over time. Parity Progression Ratios allow us to decompose the family building process. Measures of Mortality Multiple measures of mortality are used in demographic analysis. Age-specific mortality rates (ASMRs) can be used to understand how strongly mortality depends on age – and are calculated like age-specific fertility rates. ASMRs are used to calculate a key mortality measure: life expectancy at birth (e0) – a period measure representing the average number of years a newborn could expect to live, assuming current age-specific death rates are maintained throughout their lives. This measure is used as a means of comparing longevity across societies; e0 is heavily influenced by child mortality For example, life expectancy in 2015 was 83.9 years in Japan, suggesting not just long lives for most adults but very few child deaths, yet was 50.9 years in the Central African Republic, reflecting lower life expectancies for adults but also much higher rates of child deaths (Zijdeman et al. 2015). Another commonly used comparative measure is the Infant Mortality Rate (IMR), calculated by dividing the number of deaths to infants under one year by the number of live births in that year (often multiplied by 1,000). The IMR is also used as a proxy for health conditions, extrinsic mortality, and living standards – given its sensitivity to such environmental factors – and is included in the UN’s Human Development Indicator.3 Also widely used is the similarly calculated Child Mortality Rate (CMR) for children under five years. Event History Analysis While these measures are calculated for populations, demographers are often interested in understanding why demographic behavior varies among individuals. One method of statistical analysis commonly used for this purpose is event history analysis that models the likelihood of an event (birth, death, migration) happening over time, and can be used to test associations between this event and a range of predictors. It is particularly useful where data are “censored” – that is, where the event of interest has not yet happened to all individuals, or where individuals are lost to follow-up before the event of interest happens; and can incorporate time-dependent predictor variables (predictor variables that themselves change over time, such as the survival status of a grandparent). Event history analysis has been used to test hypotheses about child and adult mortality, the timing of first birth, and the timing of inter-birth intervals.

3

https://hdr.undp.org/data-center/human-development-index#/indicies/HDI.

https://doi.org/10.1017/9781108377911.014 Published online by Cambridge University Press

332

Rebecca Sear, Siobhán M. Mattison, and Mary K. Shenk

and methods that can be used to answer research questions of interest, encompassing new secondary or historical sources, “big data,” and best practices for collection of new primary sociodemographic data. Demographers’ respect for data and methods should become standard in all evolutionary disciplines, just as anthropologists’ respect for ecological context and local validity should become standard in demography. The existing demographic literature, along with existing HBE literature, can also be used to generate ideas for new research areas. For example, the time is ripe for research on migration, especially given new “big data” sources that are highly useful for studying mobility patterns. The time is also right for new research combining perspectives and theory from HBE and cultural evolution to better understand why modern demographic behaviors – particularly fertility – may depart from fitnessmaximization, and further integrate group-level/structural variables into models of individuals’ behavior. Doing so recognizes the critical importance of group-level institutions in shaping and ultimately often constraining human demographic behavior (Glowacki 2020). Similarly, HBE may benefit from further work to elucidate the psychological underpinnings of fertility and parental investment decisions (McAllister et al. 2016). This chapter has focused on the benefits of greater engagement with demography for HBE, but a similar chapter could equally well be written for all of the evolutionary human sciences. To paraphrase Metcalf and Pavard (2007), all evolutionary behavioral scientists should be demographers.

https://doi.org/10.1017/9781108377911.014 Published online by Cambridge University Press

14 Human Biology Aaron D. Blackwell and Benjamin C. Trumble

14.1

Introduction Traditionally, human behavioral ecology has examined behavior by asking ultimate questions about the functions of behaviors as molded by natural selection. Through the application of the phenotypic gambit (Chapter 1), the evolution and function of behaviors can be examined without knowing the details of the genes or physiological mechanisms involved. This approach, referred to as “black boxing,” focuses on inputs and outcomes, but not the mechanisms by which inputs lead to outcomes. This allows researchers to narrow the frame of investigation, allowing for ultimate questions to be answered without distraction by details that may be unimportant to cause or consequence. However, in this chapter, we aim to illustrate how looking inside the black boxes, far from being just about mechanisms, can also be helpful for answering ultimate questions. In opening these boxes, we discuss how the fields of human biology and human behavioral ecology complement one another, and indeed have become intertwined for many researchers. We begin by discussing key frameworks in the field of human biology. Next, we open up the “neuro-psychological” black box to discuss how physiological systems are intertwined with behavioral ones. In the first part of this chapter, we discuss the biological substrates that enact and perform behaviors, including chemical messengers, such as hormones, which broadcast information throughout the organism, coordinating actions inside the body with those outside the body. This coordination is important for ultimate questions because natural selection is expected to “design” organisms that coordinate their behavioral strategies with internal, biological systems, and in which decision making does not lie solely in the brain, but rather, involves the entire body through processes of physiological feedback and regulation. In the third part of this chapter, we look inside the “black box of inheritance” to consider how mechanisms of inheritance beyond genes and culture are relevant for behavioral ecology. Finally, we discuss how studies of biology and behavioral ecology can complement and inform one another, leading to general insights that would be missed if both biology and behavior had not been considered in concert.

14.2

Key Frameworks

14.2.1 The Field of Human Biology Human biology, simply put, is the study of humans as biological organisms. As such, human biology is perhaps most closely associated with biological

https://doi.org/10.1017/9781108377911.015 Published online by Cambridge University Press

334

Aaron D. Blackwell and Benjamin C. Trumble

anthropology, but also bridges public health, medicine, and other specialized fields, such as human auxology, which studies human growth. Many human biologists are concerned with practical matters of public health, development, and social justice, but just as many are concerned with theoretical questions and ultimate explanations. Evolutionary medicine, an approach that uses evolutionary theory to understand health problems and solutions, is closely related to human biology. Because human biology is so amorphous, it is difficult to assign one particular history or theoretical inclination to it as a whole. However, in the United States, human biology often traces its origins to Franz Boas (as does most of American anthropology), who, through his studies of skull shape in immigrants, showed that biological traits in the skull were not strictly genetically (or racially) determined, but a consequence of developmental environment. In some ways this focus on how social and physical environments affect biology has dominated human biology as a loosely defined field. Yet, like Boas, human biologists have also consistently been interested in evolutionary explanations and committed to evolution as an explanatory principle for understanding biology.

14.2.2 Reaction Norms and Plasticity A key focus of human biology is plasticity, that is, the capacity for organisms to alter their phenotypes in response to their environments. Plasticity can take a number of forms, but generally can be divided into reversible and irreversible plasticity. Irreversible plasticity is usually developmental plasticity, that is, changes that occur during growth and development and which become fixed characteristics of the organism. Some examples include changes in height or stress reactivity which are triggered by early life events and lead to permanent changes throughout the lifespan. Reversible plasticity includes changes that are not permanent, such as increases or decreases in muscle mass or body fat, or responses to cold or altitude. Some kinds of reversible plasticity are referred to by terms such as acclimatization or physiological adaptation. Plasticity occurs because organisms have evolved mechanisms which determine reactions to environmental conditions. These are sometimes referred to as norms of reaction, reaction norms, or facultative adaptations. Reaction norms can appear to be simple constraints, for example when energy intake is restricted an organism may grow less. However, even something that appears simple such as this actually requires complex adaptive functions that, for example, redirect energy away from growth rather than other functions, such as immunity, and regulate exactly how much growth is restricted based on how much energy is restricted. In human biology, a key approach to plasticity is the Developmental Origins of Health and Disease (DOHAD) framework which subsumes hypotheses such as the thrifty-phenotype hypothesis (Hales and Barker 1992; Wells 2007), which posits that early life energy restriction leads to changes in metabolism and phenotype to conserve energy later in life (and additionally results in increased likelihood of diseases such as diabetes and obesity). Plasticity may make accommodations for the immediate environment, or

https://doi.org/10.1017/9781108377911.015 Published online by Cambridge University Press

Human Biology

335

can involve predictive adaptive responses (Gluckman et al. 2005), which use cues in the present to alter the phenotype in anticipation of future environments.

14.2.3 Subsistence Populations Much work in both behavioral ecology and human biology has been conducted in small-scale, subsistence populations. Subsistence populations are often exposed to conditions that partially resemble those experienced through most of human history, including high pathogen exposure, lack of effective birth control, and high physical activity burdens. Of course, no subsistence population today exactly replicates the mosaic of environments in which humans evolved, or the exact conditions of thousands of years ago, as all small-scale societies have in some way been affected by global processes (pollution, climate change, overfishing, etc.). Yet, working with diverse populations under varied conditions is both scientifically and ethically preferable to conducting research only among select samples of Americans or Europeans, where most biomedical research is conducted. Such limited samples can often bias our ideas about what constitutes “normal” physiological functioning (Blackwell et al. 2016; Gurven and Lieberman 2020). Studying subsistence populations is therefore important for broadening representation of these groups in medical understanding and for documenting diversity in human biology. Such work can be carried out in ethical and mutually beneficial ways (Broesch et al. 2020).

14.2.4 Projects Incorporating Human Biology and Behavioral Ecology Over the past few decades, those who initially focused primarily on behavioral ecology have taken much more of an interest in integrating behavioral ecology with studies of health and human biology. Two projects involving the authors of this chapter which have integrated these approaches are the Tsimane Health and Life History Project (Gurven et al. 2017), and the Shuar Health and Life History Project (Blackwell et al. 2009; Madimenos et al. 2011; Liebert et al. 2013; Urlacher et al. 2016). Both projects are long term, collaborative, longitudinal projects examining health, behavior, and life history among subsistence Indigenous groups. Other long term studies have also worked with the Tsimane, including the Tsimane Amazonian Panel Study, which ran from 2002 to 2010 and collected extensive data on economics and health (Leonard et al. 2015). Also, in South America, The Chaco Area Reproductive Ecology Program has worked with the Qom of Argentina to study reproduction, growth, and life history for 20 years (Valeggia and Ellison 2004). In Namibia, the Kunene Rural Health and Demography Project has examined human health and reproductive ecology among the Himba since 2009 (Scelza and Prall 2018). In the Philippines, the Cebu Longitudinal Health and Nutrition Survey began collecting data on a cohort of women and infants in 1983, and it is currently collecting data on a third generation of participants (Adair et al. 2011; Kuzawa et al. 2020). The study has investigated many questions related to multigenerational effects, hormonal effects, and stress and health. Many other projects have also been

https://doi.org/10.1017/9781108377911.015 Published online by Cambridge University Press

336

Aaron D. Blackwell and Benjamin C. Trumble

conducted with both subsistence and market integrated populations around the world, adding to our knowledge of human physiology and variation beyond industrialized urban cities in Europe or North America, giving us a deeper and richer understanding of human biology.

14.3

Human Biology and Black Boxes The term “black box” is used to describe processes in which the inputs and outputs are known, but the inner workings that turn inputs into outputs are obscured. In psychology, B. F. Skinner and other behaviorists used this term to describe the mind. They could look at stimuli, and look at resulting behaviors, but could not understand what occurred inside the brain to cause those behaviors. While behaviorism fell out of favor in the twentieth century, some aspects of black box thinking remained. A major early criticism of behavioral ecology is that it takes a black box mentality, behavior and reproductive success are assumed to be linked, and therefore one can study behavior to answer ultimate questions without needing to understand the hidden mechanisms linking behavior and reproductive success (Sear et al. 2007). For much of early human behavioral ecology, this may have been the case (e.g., through application of the phenotypic gambit) but advances in less invasive measures of physiology have made it possible to begin to open the black box. Human biology can contribute greatly to understanding these mechanisms. Here, we look at two black boxes and some of the insights gained from human biology. First, we consider the hormonal and metabolic processes involved in topics of interest to behavioral ecology (such as reproduction). Next, we consider the insights from human biology and related fields for understanding inheritance on different timescales, and implications for adaptation to local conditions. We call these two boxes the “physiological black box” and the “inheritance black box.”

14.3.1 The Physiological Black Box 14.3.1.1 Energetics and Life Histories The links between behavior and physiology are perhaps most clear when examined in terms of energy usage and allocation problems, as addressed by the subset of evolutionary theory known as life history theory (see Chapter 2). Life history theory examines how organisms allocate resources in limited supply to competing demands, including growth, reproduction, physical activity, and immune defense, among others. These allocation problems are relevant for any resource in limited supply, including energy, minerals, vitamins, and essential amino acids. Everything an organism does requires resources. This includes not just physical activity, but internal processes such as immune defense, pregnancy, and even digestion. For example, when people get a mild respiratory illness like the common cold, their resting metabolic rate (the calories they burn just surviving) increases by 8–14% (Muehlenbein et al. 2010).

https://doi.org/10.1017/9781108377911.015 Published online by Cambridge University Press

Human Biology

337

In order to consider the consequences of energy allocation problems, it is useful to consider two example energy budgets for humans from different populations. The Tsimane are a population of horticulturalist-foragers whose territory lies around the Maniqui river in lowland Bolivia (e.g., Gurven et al. 2016a). They live a life characterized by high levels of physical activity while hunting or practicing slash and burn horticulture and have little access to modern medicine. Women on average have nine children. Figure 14.1 shows the hypothetical lifetime energy usage for an average Tsimane man and woman and an average American man and women. The average Tsimane man is smaller than the average American man, weighing 62 kg compared to 85 kg (31% lighter), and the same is true for women, where the average Tsimane weight is 54 kg compared to 72 kg for Americans (29% lighter). Thus, we might expect Americans to use more energy during their lifetimes. Yet, Tsimane face a number of energetic demands that the average American does not. Tsimane must engage in much more physical activity to produce food, and their immune systems must work overtime to deal with the many pathogens in their environments. Tsimane have high resting metabolic rates, exceeding expected values by 18–47%, in large part due to high investment into immune defenses (Blackwell et al. 2016; Gurven et al. 2016b, 2020). Additionally, for women, the cost of carrying and

Figure 14.1 The lifetime energy budgets of average Tsimane and American men and women

from ages zero to 85. Values in parentheses are in gigacalories. Estimates are based on relative body size, leukocyte counts, activity budgets, and completed fertility. Details are given in Blackwell et al. (in prep.).

https://doi.org/10.1017/9781108377911.015 Published online by Cambridge University Press

338

Aaron D. Blackwell and Benjamin C. Trumble

breastfeeding nine children far exceeds the cost that American women pay for one or two children. These excess sources of energy expenditure have important consequences for behavioral ecology and theories of human life history evolution in general. Compared to other primates, large human brains require excess calories, and many theories of human evolution revolve around the challenge of supplying enough energy to keep our brains fed (Chapter 2). Recent studies have shown that human brains actually require greater energy during childhood, when learning is taking place, than they do during adulthood, representing up to 43% of daily energy requirements during this period (Kuzawa et al. 2014). If a key goal of human behavioral ecology is to understand the evolution of the human life history pattern, then these theories must take into account not only the calories needed by the brain, but also those required for other demands at various ages, such as growth, immune defense, reproduction, and activity. These caloric requirements will have important behavioral consequences affecting foraging decisions, food sharing patterns, time allocation, and juvenile dependency, among other traits.

14.3.1.2 Hormones as Indicators of Life Histories One way in which caloric availability and need can impact behaviors is by interacting with physiology, though chemical messengers called hormones. Hormones can be broadly grouped into fat-derived hormones (steroids and eicosanoids) and peptide- or amino acid-derived hormones. Broadly speaking, fatderived hormones are lipophilic and can diffuse through lipid membranes, including the blood–brain barrier and across cell membranes. They are therefore capable of transmitting signals to the entire organism including the brain where they can influence behavior. Non-fat derived hormones generally require specific receptors to cross cell membranes or the blood–brain barrier; these signals are therefore more regulated by checkpoints throughout the body. It is likely no coincidence, therefore, that steroid hormones (i.e., estradiol, progesterone, testosterone, and cortisol) are broadly responsible for coordinating whole organism life history strategies and allocations, while peptide hormones are frequently more limited in reach, and may even serve different purposes in different parts of the body (i.e., oxytocin, vasopressin). A common misconception is that hormones “cause” behavioral or physiological outcomes (i.e., the idea that testosterone causes aggression). As often as not, causality is reversed, with behavior coming first. For example, when men engage in competition, their testosterone tends to increase (Archer 2006). Hormones are messages that allow for coordinated action across the body and brain by sending signals about energy availability, reproductive readiness, external stressors, growth, and much more. As such, when we measure hormones, we can eavesdrop on this messaging and learn something about the communication happening within the body. Thus, hormones are best regarded as indicators of the messages the body is sending itself about how to make life history allocations, rather than causes.

https://doi.org/10.1017/9781108377911.015 Published online by Cambridge University Press

Human Biology

339

14.3.1.3 Hormones and Reproductive Effort Because the measurement of hormones allows for eavesdropping on internal messages, it also allows us to take a deeper look at processes like reproduction, even before an individual has children or becomes pregnant. If we are careful (Box 14.1), hormones can be useful for not only documenting life history trade-offs, such as the switch from investing in growth as a child to producing children in early adulthood, but also for figuring out the mechanisms through which these trade-offs occur and for inferring the functional design of adaptations. A prime example of this is the regulation of fertility in women which depends on signals relating to energy balance, particularly postpartum. Reproduction is quite energetically costly. For humans, pregnancy requires an additional 90 kcal per day in the first trimester, 287 in the second, and 466 kcal per day in the third, while lactation costs around 626 kcal/day (Butte and King 2005). For a forager-horticulturalist woman with nine children this will amount to over two million kcal over her lifetime, about four or five whole cows or 4,000 Big Macs (Jasienska 2009). Additional costs come after weaning – forager children are generally poor at food acquisition and usually cannot produce sufficient calories to survive until age 20 (Kaplan et al. 2000). While allomaternal provisioning can help offset these costs, energetic demands on women continue. Some studies have argued that there are long-term costs of reproduction for women, resulting in “maternal depletion syndrome” (Jasienska 2009; Jasienska et al. 2017), but not all studies find evidence of maternal depletion, even in high fertility settings (Gurven et al. 2016a). Given the obligate, continual energetic demands of multiple dependent children (Gurven and Walker 2006), it is not surprising that during times of energetic shortfall aspects of reproductive physiology can be downregulated. In human females facing multiple energetic stressors including immune activation, low food availability, or extensive physical activity, there is compelling evidence that rates of anovulation increase, as well as decreases in some reproductive hormones (Ellison 1990; Jasienska et al. 2017). Ovarian function responds on a continuum – mild stressors result in mild declines in hormone levels, while major stressors can cause severe declines in reproductive hormones and anovulation (Ellison 1994; Jasienska et al. 2017). While anovulation can occur, it should be noted that generally the female reproductive axis is robust to smaller energetic perturbations (Ellison 1994). Importantly, the caloric costs of pregnancy and lactation are not immediately due (during the first trimester the caloric costs of pregnancy average just 90 kcal per day above normal). Thus, a short-term caloric shortfall over several days (seasonally common in many environments) may not predict caloric availability nine months or a year later when caloric costs will be much higher. Indeed, studies in normal weight women suggest that even exposure to a 72-hour fast during the follicular period does not significantly alter follicular development or ovulation (Loucks and Heath 1994; Olson et al. 1995). Perhaps more important for evolutionary models than the regulation of ovulation during regular cycling is the process through which women return to cycling and fertility following a birth. Ovulation is suppressed immediately following birth, an

https://doi.org/10.1017/9781108377911.015 Published online by Cambridge University Press

340

Aaron D. Blackwell and Benjamin C. Trumble

Box 14.1

The Interpretation of Hormone Levels

While point of care devices will make it possible to measure many aspects of physiology with little training in the future, understanding how different endocrine, immune, and metabolic hormones interact is critical. With a sophomoric level of knowledge, attempts to see inside the black box may instead open Pandora’s box and confuse the literature for decades to come. Thus, while applying the human biology toolkit to human behavioral ecology opens up many new opportunities, it must be done carefully. Since hormones are messengers, it is common to interpret hormone levels as indicators of relative biological function or investment. However, some caution is warranted since the level of a hormone is not always directly related to its signal strength. This is particularly true when hormones are compared between populations. Several studies have shown that steroid hormones are consistently lower in subsistence populations, likely due to a combination of competing life history demands, including infection with parasites and pathogens, high activity levels, and less calorically dense diets. For example, Aymara in the Bolivian Andes have peak progesterone levels that are around 70% of the levels in American women (Vitzthum et al. 2004), and similarly Bangladeshi women have significantly lower levels of progesterone compared to white women in London (Nuñez-de la Mora et al. 2007). Male testosterone levels have been shown to be lower in various subsistence populations (Ellison 2002; Trumble et al. 2013, 2015) than age matched males in industrialized populations. Studies of migrants show that these hormone levels are not genetically determined, but are the consequence of life experiences before puberty. Bangladeshi men and women who migrate to the United Kingdom prior to puberty have higher testosterone (in males) and progesterone (in females) levels that those who migrate during adulthood or those who remain in Bangladesh (Nunez-De la Mora et al. 2007; Magid et al. 2018). While these lower hormone levels are linked to environmental conditions, and in a general sense do represent reductions in life history investment in reproductive effort, it would be a mistake to think that they necessarily represent equal reductions in all aspects of reproduction (Blackwell 2018). Both Aymara and Bangladeshi women have fertile cycles and conceive with progesterone levels that would be considered a sign of infertility in American women (O’Connor 2003; Vitzthum 2009). Low testosterone levels in subsistence population men are not associated with reduced reproductive success or function. Indeed, some aspects of function may be better preserved with age because hormone levels remain constant across ages, instead of falling as they do in many industrialized populations (Ellison 2002; Bribiescas 2010; Trumble et al. 2013, 2015). Hormone levels vary between populations, while function does not always vary as expected. This is because the same hormone level can mean different

https://doi.org/10.1017/9781108377911.015 Published online by Cambridge University Press

Human Biology

341

things to different people. Before and during puberty set-points are established for many hormones, which determine what constitutes “high” and what constitutes “low” for a given individual. These set-points are determined through various mechanism, including the tissue specific regulation of hormone receptors, which determine sensitivity to a given hormonal message. While difficult to study in humans, in rodents there is evidence that exposure to testosterone and estrogen during several critical developmental windows alters hormone receptor densities, and helps canalize these set points (Schulz et al. 2009). At the same time, these set-points are not arbitrary, and differences in hormone levels between populations can be meaningful. For example, In the study of Bangladeshi men by Magid et al. (2018), the pre-pubertal migrants from Bangladesh to England had higher testosterone levels, but also had earlier puberty and greater stature than older migrants. These effects are likely linked to the differences in testosterone levels, as testosterone is part of the signal stimulating skeletal growth in puberty (Richman and Kirsch 1988). Thus, there are two points to be made. The first is that caution must be used in interpreting hormone levels. Within individual differences (e.g., from multiple time points) are not necessarily the same as between individual differences, or between population differences. When interpreting hormone levels, care must be taken to not just treat hormones as “biomarkers,” but to consider the biological systems in which hormones play a key role and how those systems might vary by context. The second point, then, is that cross-cultural and cross-context work is critical to achieve a full understanding of these systems.

effect known as lactational amenorrhea. Studies among the Qom (formerly known in the literature as the Toba) of Argentina have shown that energy balance plays a role in the resumption of fertility (Valeggia and Ellison 2004, 2009). Lactating women have higher caloric needs than non-lactating women, and initially are in negative energy balance, as they mobilize weight gained during pregnancy to feed the infant. As lactation becomes a smaller proportion of infant intake (during weaning), women transition into positive energy balance and may regain weight. This shift is likely internally signaled by changing insulin production, which correlates with the resumption of cycling (Valeggia and Ellison 2009). In a high fertility population, these costs are not small. For example, among the Tsimane women of reproductive age are pregnant or in lactational amenorrhea roughly 50% of the time (Figure 14.2). Thus, periods of lactational amenorrhea are critical determinants of the length of inter-birth intervals. In “natural fertility populations,” such as the Tsimane, energetic conditions likely have much more influence on total fertility than do individual preferences or strategies – indeed many women exceed their desired family sizes (McAllister et al. 2012). Energy balance and the regulation of fertility are therefore central to understanding the patterns of human life histories.

https://doi.org/10.1017/9781108377911.015 Published online by Cambridge University Press

342

Aaron D. Blackwell and Benjamin C. Trumble 100% 90% Percent of Women

80% 70% 60% 50% 40% 30% 20% 10% 0% 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 Age Group Cycling

Pregnant

Lact. Amen.

Menopause

Other

Figure 14.2 The distribution of reproductive state by age for Tsimane. “Other” includes

women taking hormonal birth control (i.e., Depo-Provera), surgically sterilized, or known to be non-cycling due to infection or other reasons.

14.3.1.4 Hormones and Male Reproductive Effort In addition to fertility, hormones have been helpful for determining the extent to which humans have neurophysiological adaptations for parenting. Evidence for adaptations for fathering or alloparenting can help to illuminate the human reproductive niche and provide evidence for theories that link human cooperative breeding to other human life history traits. While the caloric costs of reproduction in females are paid in pregnancy and lactation, the costs of male reproduction are paid every day in terms of maintaining muscle mass, which is thought to be important for sexual selection as well as male provisioning (Bribiescas 2001; Trumble et al. 2013, 2014). Nearly one fifth of male basal metabolic rate is spent maintaining muscle mass (Bribiescas 2001). Thus, during any energetic shortfall, males immediately downregulate noncritical reproductive hormones such as testosterone to invest scarce calories in maintaining survival (e.g., investing in immune function); it is hard to reproduce if you are dead, so better to downregulate testosterone temporarily and stay alive or reproduce another day. Unsurprisingly, testosterone is downregulated during extreme physical activity (Nindl et al. 2007), both major and minor illness (Spratt et al. 1993; Simmons and Roney 2009), injury (Spratt et al. 2008), and with caloric restriction (Cameron et al. 1991; Trumble et al. 2010). In subsistence populations with high levels of physical activity to produce calories (e.g., hunting), and high pathogen loads, men have relatively low levels of testosterone compared to men in industrialized urban environments. It is important to note that men in subsistence populations do not have “low” testosterone – they have well calibrated testosterone levels for their environment – in fact it is men in industrialized populations who have excessively high levels of testosterone (Box 14.1).

https://doi.org/10.1017/9781108377911.015 Published online by Cambridge University Press

Human Biology

343

In 1990, Wingfield and colleagues published a key study on avian behavioral endocrinology and advanced the “Challenge Hypothesis” (Wingfield et al. 1990). This original study focused on how seasonally breeding male birds typically maintain relatively low levels of testosterone during the non-mating season, have a higher baseline during the mating season, and then also can achieve a shorter term spike in testosterone during male–male compettion over mates or territories (Wingfield et al. 1990). A high testosterone phenotype is energetically expensive to maintain, so males keep testosterone relatively low when focused on parenting in order to direct resources toward offspring. During the mating season, higher levels of testosterone allow for greater muscle mass and behavioral focus on mating or gaining territory, and additionally direct competition with other males leads to even higher spikes in testosterone which can have acute benefits for muscle tissue or behavior (Tsai and Sapolsky 1996). Indeed, other studies in diverse animal models from fish to rodents find that the acute increases in testosterone seen during male–male competition, and in particular among winners, result in increased future aggression, potentially reinforcing male–male competition (Oyegbile and Marler 2005; Oliveira et al. 2009a). The Challenge Hypothesis spawned a new area of research not just in avian models, but also in mammals and humans; to date, more than 400 studies in humans have explored the challenge hypothesis (Archer 2006; Gray et al. 2020). In human studies, there have been three main areas of study that have explored the Challenge Hypothesis; (1) associations between testosterone and competition or aggression, (2) testosterone and pair-bond relationship dynamics, and (3) testosterone and parenting behavior. In humans, males and females both show acute increases in testosterone during competition with conspecifics (Archer 2006; Oliveira et al. 2009b; Gray et al. 2020). These acute increases have been seen in many contexts from contact sports like judo and soccer, to video games, and even chess matches (Mazur et al. 1992; Salvador et al. 1999; Oxford et al. 2010; Trumble et al. 2012). The hormonal response appears to be higher in winners of competition than losers in most, but not all, studies (Archer 2006; Trumble et al. 2015; Gray et al. 2020). In the case of team sports, variation in the winner effect could be a result of individuals who played well relative to their peers and competitors, even if their team still lost, making the winner effect potentially more complicated (Trumble et al. 2012). Even watching video of a previous win can elicit an acute increase in human males (Carré and Putnam 2010), as can watching a favored candidate win a national election (Stanton et al. 2009). Humans are not seasonal breeders, and thus have a very different social structure than the original avian models in which the challenge hypothesis was proposed. While there is not a breeding season, there is evidence that testosterone declines once males are in a stable pair-bond, in a manner akin to male avians in the nonbreeding period. Both cross-sectional and longitudinal studies report that males in long term relationships have lower levels of testosterone than single males, controlling for age (Gray et al. 2002; Gettler et al. 2013). Similarly, separated or divorced males tend to have higher levels of testosterone than married men (Mazur and Michalek 1998;

https://doi.org/10.1017/9781108377911.015 Published online by Cambridge University Press

344

Aaron D. Blackwell and Benjamin C. Trumble

Holmboe et al. 2017; Rosenbaum et al. 2018). In some contexts, men who are partnered but do not live with their partner show higher levels of testosterone (Muller et al. 2009), but in other contexts, men in long-distance relationships have lower levels of testosterone than men not in relationships (van Anders and Watson 2007). Single males with higher levels of testosterone tend to engage in more mate seeking behaviors, and they are more likely to be in a partnership on follow up (Gettler et al. 2011; Roney and Gettler 2015). It should be noted that none of these studies demonstrate causality, but the pattern of lower testosterone in pair-bonded males has been repeated worldwide in both cross-sectional and longitudinal studies. In human males, fatherhood is generally associated with lower levels of testosterone (Gray et al. 2002, 2020; Gettler et al. 2011; Boyette and Gettler 2019). It is generally argued that males are shifting their life history strategy away from mating effort and toward parenting effort (Bribiescas 2001). Indeed, in many contexts, males who are seen as the most involved in their children’s lives (whether by hours spent with offspring, or subjective reports of caregiving) have lower levels of testosterone than fathers who are less present (Alvergne et al. 2009b; Mascaro et al. 2013; Edelstein et al. 2015; Gettler et al. 2015). While this pattern of declining testosterone in light of fatherhood has been reported worldwide (Gray et al. 2006; Muller et al. 2009; Gettler et al. 2011, 2013, 2015), a recent meta-analysis argued that associations between parenting and testosterone have relatively low effect sizes (Meijer et al. 2019). Similarly, there have long been debates over the goal of male hunting. Do men seek to hunt to provision their families, or do they hunt to signal (show off ) their ability to potential extra-pair mates (Hawkes 1991; Wood and Hill 2000; Gurven and Hill 2009)? While studies have been conducted with pile sort methods having men and women rank hunters and their hypothetical return rates, it is difficult to assess the inner motivations of male hunting (Wood and Hill 2000). However, measuring hormonal responses can give insight into the behavioral strategy of hunters independent of self-report. One such study examined acute changes in testosterone and cortisol among the Tsimane of Bolivia over the course of hunts. That study found that both testosterone and cortisol spiked for successful hunters, but not unsuccessful hunters (Trumble et al. 2014). Interestingly, the magnitude of change in hormones was the same for hunters that were returning with large amounts or small quantities of meat. Similarly, there was no evidence of an audience effect – males returning to an empty house had the same rise in testosterone as those returning to a house with multiple unrelated women (Trumble et al. 2014). Thus, endocrine data offers an approach to study motivations underlying complex evolved behaviors, and for topics relevant to human behavioral ecology.

14.3.1.5 Conclusions 1: The Physiological Black Box In sum, by utilizing advances in field friendly endocrine biomarker collection and analyses, researchers can begin to open the physiological black box. Studies using hormonal data allow us to take a deeper look into what is actually happening within the body, shedding light on how physiology can mediate behavior and how behavior

https://doi.org/10.1017/9781108377911.015 Published online by Cambridge University Press

Human Biology

345

can modify physiology. Most studies to date have focused on a single hormone or single behavior. However, advances in endocrine assays mean that many different biomarkers can now be collected in field conditions, using dried blood spot cards (McDade et al. 2007), field laboratories (Gurven et al. 2017), or point of care devices (Brindle et al. 2014). As laboratory analyses become cheaper and more field friendly, it will be possible to shine more light into this black box and examine how multiple different hormones interact with each other and behavior, as well as other aspects of physiology such as immune function. Human physiology is a complex interaction of different chemical messengers that can change course in a matter of seconds (epinephrin and other catecholamines released as a part of the fight-or-flight response), or over decades (anti-Mullerian hormone is associated with follicular reserve and slowly declines prior to menopause). By collecting longitudinal data both during short-term behaviors and across long-term life changes, human biologists can begin to understand the complex interactions that are occurring every second of every day inside our bodies and how these reflect and mediate the relationships between our social and energetic environments and our behaviors.

14.3.2 The Inheritance Black Box 14.3.2.1 Is Dual Inheritance Enough? In most species, the default assumption is that behaviors evolved genetically through mutation and selection of variants in DNA sequences. In applying the phenotypic gambit, behavioral ecology makes the simplifying assumption that human behaviors can be treated as if they were determined through simple genetic inheritance mechanisms. This works quite well as a first pass for making predictions about adaptive behaviors. However, what is becoming increasingly apparent is that progress past this first stage of inquiry will require a more detailed consideration of the mechanisms of inheritance and a consideration of how inheritance affects behavioral change over time. Much human behavioral ecology takes place in the ethnographic present. However, as the societies that behavioral ecologists have traditionally studied transition to market economies or experience other forms of rapid cultural change, human behavioral ecology must grapple with the processes through which behaviors and cultures adapt to new circumstances, or, in many cases, create new circumstances in which individuals must adapt. Mechanisms of inheritance are important for studying phenotypic change because they affect the speed and direction in which change occurs. In addition to genetic influences and the inheritance of reaction norms, human behaviors are also influenced by social learning (i.e., cultural evolution) (Chapter 15), with the transmission and replication of cultural information playing a role in determining human behavior alongside the transmission of genetic information. The joint consideration of genetic and cultural evolution is sometimes referred to as dual-inheritance theory (Richerson and Boyd 1978). However, genes and culture are not the only mechanisms through which information is passed from one generation to the next. There are a whole range of other

https://doi.org/10.1017/9781108377911.015 Published online by Cambridge University Press

346

Aaron D. Blackwell and Benjamin C. Trumble

mechanisms of inheritance, many of which can be broadly classified as epigenetic mechanisms (Jablonka and Lamb 2014). The word epigenetics literally means “on top of the genes”; it refers primarily to modifications or molecular attachments to DNA. The general effect of these modifications is to alter the expression of genes, changing how much of a protein is produced, when that protein is produced, or turning the gene on or off completely. Most (probably all) forms of developmental plasticity involve epigenetic modifications, which are required for cells to differentiate into different cell types. These epigenetic markers are acquired during the lifetime of an individual. Most of these epigenetic marks are erased during the production of gametes, or else they occur only in cell lines in the somatic tissues and thus are never present in the reproductive cell line at all. However, some small portion of epigenetic markers remain un-erased in gametes and are therefore inherited across generations. These inherited markers allow for the transmission across generations of instructions about how to express gene products. Information can also replicate across generations through a class of effects that are often termed “maternal effects.” These are not quite mechanisms of inheritance, but they can allow for the replication of phenotypic characteristics. One example of this is body size. Bigger mothers tend to have bigger babies, not just because of genetic correlation, but because bigger mothers have larger wombs and larger placental interfaces that can allow a greater flow of nutrients to the fetus. Because adult body size is influenced both by size at birth and conditions during development, a mother’s conditions during her own development influences her offspring’s starting point at birth. Mothers also transfer immunological materials to their offspring, including maternal cells that enter the growing fetus and affect the infant’s immune response to maternal antigens (Kinder et al. 2015; Harrington et al. 2017), and also maternal antibodies that protect the infant and direct the development of infant immunity (Borghesi et al. 2014).

14.3.2.2 Human Biology and Multi-Inheritance Because human biology has frequently focused on the plasticity of traits, studies of epigenetics, maternal effects, and similar phenomenon have received considerable attention in the field. As discussed in the first section of this chapter, these effects are important for DOHAD hypotheses. They are also important for understanding many phenotypic traits that human biologists and behavioral ecologists are interested in, such as body size, reproduction, and social influences on health. Phenotypic inertia is the idea that plastic phenotypes may take multiple generations to adjust to changing environmental conditions. Phenotypes are replicated across generations through epigenetic and other forms of transgenerational inheritance (Kuzawa 2005). Phenotypic inertia means that behavior may be adaptive for average conditions over time scales of a few generations but appear maladaptive on the scale of single generations due to fluctuations in ecological or social conditions. We might expect traits to evolve phenotypic inertia when short term conditions are unreliable cues for setting phenotypic or behavioral strategies, but multigenerational averages are reliable predictors.

https://doi.org/10.1017/9781108377911.015 Published online by Cambridge University Press

Human Biology

347

Secular changes in stature and body size are good example of these kinds of traits because they are easily documented and relatable to fitness outcomes. Across many documented populations, when sanitation and nutrition improve, average height increases. For example, height has steadily increased across Europe since the midnineteenth century by as much as 1–3 cm per decade (Cole 2000, 2003). Conversely, when conditions worsen, height may decline, such as happened during the late Upper Paleolithic, likely due to diet, disease, or climate (e.g., Diamond 1987; Formicola and Giannecchini 1999; Velasquez-Manoff 2013)). These trends are (1) clearly nongenetic (since they occur over just a few generations), (2) reversible, and (3) do not occur in a single generation, even when environments change quickly. Secular trends in growth may relate to heritable epigenetic changes, but they might also result simply from repeated maternal effects – (i.e., if grandmother has good nutrition during pregnancy), this may influence the development of her daughter’s reproductive system, which in turn affects how her granddaughter grows 20 years later (Kuzawa 2005). Similar secular changes also occur in other life history processes, such as age of menarche (e.g., Hoshi and Kouchi 1981; Wyshak and Frisch 1982) and age of menopause (e.g., Rödström et al. 2003). Traits related to stress reactivity and resilience, metabolism, and health outcomes have been given particular attention in studies of multigenerational effects. For example, the descendants of holocaust survivors or those exposed to the September 11 terrorist attacks show differences in stress reactivity as measured by cortisol response (Yehuda et al. 2005, 2007). Paternal effects can also matter. In mice, for instance, fear conditioning to a particular odor can be transmitted to unexposed grand-offspring through the paternal lineage (Dias and Ressler 2014). In humans, another example of a well-documented epigenetic effect is the effect of paternal age on telomere length. Telomeres are tails on the ends of chromosomes that shorten each time a chromosome is copied. Telomere length, therefore, has some relationship to the number of times a cell line can go through cell divisions. The children of men who reproduce at older ages have longer telomeres, an effect that compounds over multiple generations (Eisenberg et al. 2012). This effect is hypothesized to be a mechanism through which father’s age of reproduction serves as a cue of expected offspring lifespan and age of reproduction.

14.3.2.3 Inheritance Systems as Adaptations Among the inaccuracies that professors sometimes tell undergraduates, one of the most common is that “evolution is a change in allele frequencies over time,” a definition of evolution that grew out of the modern synthesis and the advent of population biology. Of course, it cannot be true that evolution is only a change in allele frequencies. Why? Because evolution was happening long before alleles existed. Four billion years ago, life began without DNA or other formalized mechanisms of inheritance. Evolution likely began with other forms of replicating molecules. Only much later did the innovation of DNA evolve. This makes obvious the key point: Inheritance systems are adaptations. They are both the product of evolution and the means through which evolution is facilitated.

https://doi.org/10.1017/9781108377911.015 Published online by Cambridge University Press

348

Aaron D. Blackwell and Benjamin C. Trumble

Genetic inheritance (DNA) evolved because it allowed for the stable transmission across generations of the large amounts of information required for building complex phenotypes. Characteristics of genetic inheritance also evolve, including mechanisms for correcting copying errors, mechanisms for introducing variability through sexual recombination or plasmid exchange, and the suite of codons linked to particular amino acids. Epigenetic mechanisms have also evolved. Many may have first evolved as types of immune defense (Zemach and Zilberman 2010). Once present in single celled organisms, epigenetic mechanisms were likely co-opted in multicellular organisms as mechanisms for tissue differentiation (Jablonka and Lamb 1998), and in both prokaryotes and eukaryotes these mechanisms were likely immediately somewhat heritable. Over time there has been ample opportunity for epigenetic mechanisms of inheritance to evolve alongside genetic inheritance, allowing for the transmission of information across generations. Continuity (or at least correlation) across generations in behavioral traits, knowledge, language, and attitudes is further facilitated through “cultural” inheritance mechanisms, including imitation, explicit transmission, reconstruction, and the repeated triggering of reaction norms – what might be called “evoked” culture (Tooby and Cosmides 1992)). Rudimentary forms of behavioral inheritance have evolved in many species, including sensitivity to stimulus enhancement, various forms of behavioral imprinting, and occasionally explicit teaching (Jablonka and Lamb 2014). Many species of primates have traditions that spread through social learning (Perry and Manson 2003; Whiten et al. 2007). In humans, social learning has evolved into a much more sophisticated format, allowing for cumulative cultural change and allowing humans to expand across the globe (Henrich and McElreath 2003; Henrich 2015). Why should natural selection have led to the evolution of multiple mechanisms of inheritance? The likely answer is that these mechanisms serve different purposes and have different costs and benefits (Figure 14.3). Genetic inheritance evolved because it allowed for the replication of fundamental building blocks for living organisms, such as proteins, RNAs, and regulatory elements for proteins and RNAs. Because genetic inheritance transmits fundamental building blocks, mutations in the genetic code are usually deleterious, particularly if they appear in coding sequences. Thus, genetic inheritance is inherently conservative, and evolved error correction mechanisms keep mutation rates low. Sexual reproduction likely evolved as a relatively “safe” way to introduce new genetic variation into offspring – safe because the genes with which one mixes one’s own genes have been prescreened via choosiness for a healthy and successful mate (or at the very least, one viable enough to survive and reproduce). Epigenetic marks are far less stable across generations than are genetic variants. Because they act primarily as switches, they are far less likely to have catastrophic effects when they mutate (e.g., they turn on or off the light, rather than smashing the bulb). In some circumstances, failed inheritance may even be repaired or reconstituted through modification during development. However, epigenetic marks are

https://doi.org/10.1017/9781108377911.015 Published online by Cambridge University Press

Human Biology

Low

“Mutation” Rate

Culture

Probability of Catastrophic “Mutation”

High

349

Developmental Plasticity

Epigenetics

Genetics Low

High Slow

Timescale for adaptation

Fast

Figure 14.3 Some major systems for stabilizing or varying phenotypes over time to allow for

adaptation on various timescales. Note that each of these is really a family of inheritance mechanisms; for example “epigenetics” includes methylation, siRNAs, and structural templating, while there are many ways of classifying different types of cultural or behavioral inheritance. Also note that each of these systems depends on systems at other levels, for example, culture inheritance depends on adaptations coded and inherited genetically and regulated through epigenetic and developmental processes.

likely limited to affecting the regulation of genes and therefore the expression of existing adaptations – they cannot produce new proteins or new structures. Similarly, cultural inheritance can be either very stable or have a high mutation rate because new behaviors are effectively screened (via mental simulations, etc.) before being put into practice. Cultural inheritance also shares certain similarities with genetic inheritance – namely that it allows for the transmission of a nearly infinite (though not unbounded) range of variations. Because it is composed of multiple mechanisms, culture can also be inherited with fidelity ranging from very low to very high, meaning that culture can produce both stable inheritance and inheritance that mutates quickly. The presence of multiple inheritance systems serves multiple adaptive purposes. New inheritance systems allow for new forms of biological organization, such as multicellularity or the organization of complex societies (Jablonka and Lamb 2006). On the level of lineages and individuals, multiple mechanisms of inheritance allow for adaptation on multiple timescales. Genetic evolution is slow but stable, such that new adaptations arise over many generations. Inherited epigenetic changes likely operate on the timescale of a few generations (Furrow and Feldman 2014), while non-inherited changes are critical for developmental plasticity within individual lifetimes. Epigenetic changes are particularly useful for “tuning” the system to deal with changing circumstances on multiple timescales. Think of epigenetic changes as volume knobs that alter life history traits, such as the relative balance of energy expenditure versus energy storage in adipose, or the reactivity to stimuli, such as

https://doi.org/10.1017/9781108377911.015 Published online by Cambridge University Press

350

Aaron D. Blackwell and Benjamin C. Trumble

stressful events. Cultural changes can occur very quickly but can also be surprisingly stable when they are reinforced and supported by a large population. Cultural evolution also allows for adaptation on short time scales and the adjustment of life history schedules, while simultaneously providing a nongenetic route for the evolution of complex adaptations. In other words, multiple inheritance systems have evolved because these inheritance systems solve different adaptive problems. To understand human adaptation over both long and short timescales, we should consider all forms of inheritance.

14.3.2.4 Conclusions 2: Multi-Inheritance and Human Behavioral Ecology A challenge for human behavioral ecology in the twenty-first century is to open the black box of the phenotypic gambit and examine how human behaviors are transmitted and reproduced. For example, in studying fertility and the demographic transition, we need to understand how cultural change interacts with developmental plasticity in the reproductive and endocrine systems, how epigenetics and culture can both influence fertility and mating preferences, and how all of this occurs in the context of evolutionarily novel environments. One challenge, then, is to move past studies of the ethnographic present and study behavior and culture as dynamic systems that change over time. Human behavioral ecologists who incorporate archaeological data have long thought in this way, as have those who incorporate mathematical models of change over time (Winterhalder and Smith 2000; Winterhalder and Kennett 2006). However, the incorporation of human biology suggests new ways to approach this problem. Instead of dual inheritance theory, we can now consider multi-inheritance approaches that consider all the inheritance mechanisms noted in the aforementioned sections. For example, because of effects like phenotypic inertia, researchers can use human biological traits as indicators of changing ecological conditions over time. A good example of this is body size, which represents an amalgamation of genetically selected traits, the conditions affecting grandparents and parents (through maternal and epigenetic effects), and the conditions affecting an individual during development. By looking at secular trends in height in a population, we can learn something about how the conditions affecting that population have changed over the last several generations. If genetic and epigenetic data are also included, we can better partition the timescales on which changes occur.

14.4

Final Thoughts Given that this is a behavioral ecology text, much of this chapter has been written to present the importance of human biology for behavioral ecology. We have focused primarily on understanding the mechanisms of physiology and inheritance, but human biology can also be useful for behavioral ecology by presenting novel measures which can serve as fitness proxies (Box 14.2). However, a chapter written for an audience of human biologists could just as easily argue that human behavioral ecology is critical for their discipline. Human biology sometimes falls into the trap of

https://doi.org/10.1017/9781108377911.015 Published online by Cambridge University Press

Human Biology

Box 14.2

351

Biological Measures as Outcomes

The toolkit of methods, theory, and techniques offered by human biology have many applications for the field of human behavioral ecology. Ranging from anthropometrics, hormone levels, fMRI studies, or bone density, the applications of human biology for behavioral ecology researchers are many. In many cases, they can offer finer grained insight than ultimate outcomes like mortality or total fertility, which measure the endpoints of fitness relevant processes, but may obscure finer grained continuous variation which is useful for identifying causality. For example, illness can result in death, but also can result in shorter stature for survivors (Blackwell et al. 2010, 2017; Urlacher et al. 2016; Urlacher and Kramer 2018). In small subsistence populations, it may not be possible to have a large enough mortality sample to study how a specific behavioral strategy impacts mortality, but with health data such as anthropometrics or more in-depth immune characterization, it is possible to achieve continuous or even longitudinal variation in health status with sufficient statistical power. In terms of fertility, males in poorer condition tend to have lower lifetime reproductive success than males in better condition (Trivers and Willard 1973). Instead of focusing on long-term outcomes like lifetime reproductive success, researchers can look at how short-term perturbations in condition, such as fasting, illness, or injury can impact proximate reproductive factors like testosterone. Indeed fasting, even for short periods, results in reductions in testosterone in humans (Cameron et al. 1991; Trumble et al. 2010), as does illness (Spratt et al. 1993; Simmons and Roney 2009), and injury (Spratt et al. 2008). Thus, by focusing on physiology, one can ethically create experiments to mechanistically test how environmental conditions or behavioral strategies impact proxies for mortality and fertility that would otherwise be impossible to study. A good example of using human biology to gain better insights in the behavioral ecology literature comes from studies of hunting. It has long been known that better hunters have greater reproductive success than nonhunters (Gurven and Hill 2009). Indeed, the children of better hunters are more likely to survive, and better hunters have earlier age at first reproduction (Gurven and von Rueden 2006; von Rueden et al. 2011). However, using the human biology toolkit, one can study the phenomenon in more detail to both better understand the mechanisms leading to greater reproductive success and come up with novel testable hypotheses; are the children of better hunters taller, do the children of better hunters have stronger immune function? Growth outcomes are frequently used as markers of individual and population health in human biology and as a measure of offspring “quality” in human behavioral ecology. More broadly speaking, since cumulative behavior over time affects biological status with regard to growth, nutritional

https://doi.org/10.1017/9781108377911.015 Published online by Cambridge University Press

352

Aaron D. Blackwell and Benjamin C. Trumble

status, hormone levels, and immune markers, biological measures can be used as proxies for behavior in the past, which cannot be observed directly. In short, there is no true division between mind and body; understanding either mind or body requires that we treat mind and body as a single integrated entity.

conducting only descriptive studies which fail to ask why certain effects occur. Incorporating game theoretic approaches from human behavioral ecology can suggest hypotheses for examining biological mechanisms. For example, given the differences in timescales for which different inheritance systems operate, we might predict which mechanisms are likely to underlie different behavioral or phenotypic adjustments. Returning to the example of fertility, one might expect a combination of cultural and epigenetic mechanisms to be responsible for demographic transitions over generations. From grandmothering to energetics and life history timing, the questions that structure the more impactful studies in human biology are fundamentally behavioral ecology questions. While human biology can bring to behavioral ecology a focus on the social determinants of health and the importance of biological function for understanding behavior, behavioral ecology has brought to human biology a focus on examining evolved “strategies” that address life history tradeoffs through both physiological and behavioral mechanisms. The answers to many questions about what we are as humans, and why we do the things we do (see Box 14.3), will require collaboration between subdisciplines of anthropology. Put more succinctly, human biologists can benefit by considering behaviors, behavioral strategies, and social relationships as fundamental influences on biological outcomes; human behavioral ecologists can benefit by looking inside the black box, and considering the mechanisms underlying behaviors, and the processes through which inheritance and adaptation to local conditions occurs. Humans and other organisms are not divided into minds and bodies that evolve separately but rather integrated organisms in which behavior and physiology are intimately related. Biologists have made similar integrations in other species. In insects, the adaptive significance of transgenerational effects is less controversial; maternal and epigenetic influences on multiple outcomes from immune responses to clutch size to mate choice have been documented and seem to reflect adaptive design (Mousseau and Fox 1998). Primatologists regularly integrate studies of hormones or genetics with studies of behavior (e.g., Emery Thompson et al. 2007; Altmann et al. 2010; Roberts et al. 2012; Snyder-Mackler et al. 2016). Birds are frequent models for studies integrating immune function and life history (e.g., Knowles et al. 2009; Gil and Culver 2011). One can imagine a future in which humans are understood in terms of nested cybernetic systems. Genes, maternal effects, and epigenetics interact with environments through developmental processes to produce bodies and nervous systems that

https://doi.org/10.1017/9781108377911.015 Published online by Cambridge University Press

Human Biology

Box 14.3

353

Research Needed

The connections discussed in this chapter suggest many ways in which human biology and behavioral ecology can be better integrated. Here are six examples of open questions in need of additional research: 1. Do humans use physiological indicators to signal need to conspecifics? The signaling theory of illness proposes that some symptoms of illness are exaggerated in order to serve as honest signals of illness to conspecifics who can provide care (Steinkopf 2015; Tiokhin 2016). One proposal is that these exaggerated symptoms are not “fake” but are mediated by activation of the acute phase inflammatory response which triggers symptoms such as fatigue, fever, swelling, and changes in skin tone. The receipt of care reduces the need for these exaggerated signals and thus their reduction, an explanation for the placebo effect in medicine (Evans 2002, 2005). A similar signaling function has been proposed for depression (Hagen 1999; Roulette et al. 2016), which is also frequently linked to elevated inflammation (Maes 2011). However, this seems likely to be just the tip of the iceberg for the ways in which humans signal internal states to conspecifics for social functions, including but not limited to eliciting care, intimidating competitors, and attracting mates. What are the external signs of immune activation and how do these influence needbased transfers, reciprocity, and sharing economies? 2. How do food preferences and food disgust reflect changes in subsistence and disease exposure? Humans are very adaptable omnivores, yet no culture is free from food taboos, disgust norms, and preferences for particular foods. Disgust likely evolved to motivate pathogen avoidance (Curtis et al. 2004; Stevenson et al. 2011), but the specifics are shaped by experience and exposure (Cepon-Robins et al. 2021). What remains is to integrate these models of food preferences and disgust into optimal foraging models, and to extend optimal foraging models to market economies for a complete picture of food choice and pursuit. Of particular relevance for current models is the question of how food preferences change with market integration, and along with preferences, how do disgust and taboo evolve? What role, if any, do epigenetic and maternal effects play? Does the association between disease and particular foods influence preferences? As energy balance increases, do less favored foods fall out of the diet? Humans may choose toxic foods and other substances as selfmedication (Hagen et al. 2013). How does infection influence the consumption of such toxins? Finally, changes in early life exposures and immune activation have led to large increases in food allergies in the last few decades (VelasquezManoff 2013; Bryce 2016). What is the role of immune responses to foods in dictating food choices?

https://doi.org/10.1017/9781108377911.015 Published online by Cambridge University Press

354

Aaron D. Blackwell and Benjamin C. Trumble

3. Do hormones signaling energy balance play a role in foraging deci-

sions? (adapted from Sugiyama and Schrock 2019) Hormones such as leptin and ghrelin send signals from the gut and adipose tissue to other parts of the body and brain. Past research has shown that they play a role in regulating energy intake and body weight (Klok et al. 2007). Other hormones, such as cortisol, also play a role in regulating energy intake (Tataranni et al. 1996). To what extent do these hormones influence foraging decisions in subsistence populations, such as the decision to pursue high riskhigh reward items versus low risk-low reward items? What might this reveal about how energy balance affects human decision making and the selective pressure shaping this regulatory pathway? 4. Does immune activation influence behavioral trade-offs? (adapted from Sugiyama and Schrock 2019) Similar to the influence of hormones on energy intake, immune activation can have a strong influence on energy expenditure, energy intake, and motivation for social, sexual, and productive behaviors (Shattuck and Muehlenbein 2015; Schrock et al. 2019). Beyond the basic observations of sickness behavior, with which most people are familiar, to what extent do background differences in immune activation and regulation affect behaviors? For instance, inflammation may promote impulsivity, but what about other forms of immune activation and regulation? What is the influence of relatively sterile and evolutionarily novel modern environments on decision-making? What behavioral effect is there of disruptions to ancient commensal relationships with microbes and parasites? 5. Do parasites and infection influence human social structures? Much ink and more pixels have been spilt on the behavioral immune system and its implications for human sociality, yet to date more questions than answers remain. Cross-national studies have suggested that parasitism influences political ideology and tolerance of outsiders (Fincher et al. 2008; Thornhill and Fincher 2011), yet these associations are just as likely to be due to other confounds, such as structural inequalities, sanitation, and an emphasis on traditionalism which may be culturally evolved (Tybur et al. 2015, 2016; Ross and Winterhalder 2016). Short term laboratory experiments have suggested that pathogen threat is associated with ethnocentrism at an individual level (e.g., Navarrete and Fessler 2006), but to date there is little to show the pathways between individual level effects and societal patterns. Do short-term invoked responses interact with cultural evolution over longer time scales? At what rate do cultural norms change with disease exposure? 6. How does phenotypic inertia influence personality, motivation, and hormonal responses? In a classic study on “cultures of honor,” Cohen et al. (1996) examined how American Northerners and Southerners responded to perceived insult and

https://doi.org/10.1017/9781108377911.015 Published online by Cambridge University Press

Human Biology

355

found that Southerners were more likely to feel threatened, had a stronger cortisol response, and were more likely to respond in an aggressive or dominant way. In this study, it was argued that persistent cultural differences, leftover from a history of cattle raising, were responsible for these differences. Yet, there is ample evidence that cortisol reactivity is influenced by maternal and epigenetic effects (i.e., Thayer and Kuzawa 2014). To what extent are these differences in biological response sustained by cultural learning versus other mechanisms affecting the regulation of stress reactivity? This is just one example of many possible questions in which assumed cultural differences might be influenced by other forms of nongenetic inheritance. For example, it has been suggested that phenotypic inertia in life histories may create a selfsustaining loop that further entrenches racial disparities in the United States (Kuzawa and Sweet 2009). Do similar processes play out in small-scale societies, as in the inheritance of social position? Similar processes have been observed in other animals, such as cichlid fish (Lenkov et al. 2015) and mice (Lenkov et al. 2015).

respond to input from the immune system, the gut, and within-body communication about physiological state. Individuals adjust their life histories by integrating information about the conditions experienced by distant ancestors, recent ancestors, and individual experience. These life history adjustments are characterized by alterations in energy allocations which can be read in the state of hormonal and other chemical messenger systems. Similar to how health biomarkers can be used to assess morbidity prior to death, many of these hormonal messengers can be used to examine reproductive physiology even prior to reproduction, or hormonal physiology prior to and after competitive behavior, giving us more data to examine human behavioral ecology on a finer scale. Finally, we can understand how species and individuals differ from one another as a function of their genomes, epigenomes, microbiomes, memomes, and environments, both in terms of their behavioral (e.g., personality, temperament) and physiological strategies (e.g., fertility regulation, immune response). This complex portrait will not be easy to craft, but human behavioral ecology and human biology together provide the tools and theory to make progress toward this future understanding.

https://doi.org/10.1017/9781108377911.015 Published online by Cambridge University Press

15 Cultural Evolution Karthik Panchanathan

One of the most significant facts about us may finally be that we all begin with the natural equipment to live a thousand kinds of life but end in the end having lived only one. Clifford Geertz (1973)

The student of anthropology knows that it is the range of human experiences that represents “one of the most significant facts about us” (Geertz 1973). While human universals exist (Brown 1991), including subsistence, marriage, and politics, there is no single, species-typical way in which humans live out their lives. Each human universal conceals a constellation of cross-cultural variation. While other animals have cultural traditions (Box 15.1), human variation is something altogether different. There are over 6,000 languages spoken across the globe, and there were many, many more before the ages of empire and colonialism. Human nature – if we choose to speak of such a thing – consists not of a characteristic way of life, but a set of cognitive and developmental mechanisms including our cultural capacity, “the natural equipment to live a thousand kinds of life” (Geertz 1973). It is the peculiarities of our cultures interacting with these mechanisms that shapes the specific kind of life each one of us ends up living. Since the dawn of our genus, culture has been our faithful handmaiden, transforming a Plio-Pleistocene primate at the mercy of Nature, first into a Holocene human that colonized every corner of the globe, diversifying into a thousand kinds of life, each exploring and elaborating their own particular lifeway comprising unique material cultures, social institutions, and artistic traditions; and eventually into an Anthropocene annihilator bending that same Nature to its will and in the process wreaking havoc across the biosphere. These transformations raise many questions. Why did our cultural capacity evolve during the Plio-Pleistocene? How did our species diversify into thousands of distinct ethnolinguistic groups during the Holocene? And how did the accumulation of cultural innovations in technology and social organization birth the agricultural, industrial, and scientific revolutions; launch us to the moon, to the edge of the solar system, and into the far reaches of the cosmos? The discipline of cultural evolution provides a framework for studying these kinds of questions (Cavalli-Sforza and Feldman 1981; Boyd and Richerson 1985; see also Durham 1991; Sperber 1996; for reviews, see Richerson and Boyd 2005; Mesoudi 2011; Henrich 2015; Laland 2017). With its roots going back to the 1970s and 1980s, cultural evolution developed in the wake of sociobiology and alongside evolutionary

https://doi.org/10.1017/9781108377911.016 Published online by Cambridge University Press

Cultural Evolution

Box 15.1

357

The Psychology and Phylogeny of Cumulative Culture

“If I have seen further, it is by standing on the shoulders of Giants.” Newton’s quip captures a key feature of human culture, the cumulative evolution of complex adaptations.1 While social learning and cultural traditions are common among nonhuman animals (Galef 1996; Huffman 1996; Rendell and Whitehead 2001; Hunt and Gray 2003; Perry 2003; van Schaik et al. 2003), only humans seem capable of harnessing social learning to evolve complex cultural adaptations (Tomasello et al. 1993; Boyd and Richerson 1996; Hill et al. 2009; Dean et al. 2014; but see Whiten 2019). As with biological evolution, the recipe involves beneficial modification, selective retention, and high-fidelity transmission. Repeat this process over and over and you get the countless technological and social innovations that contributed to our species’ remarkable success. If this process is so simple, why is it that no other species – especially chimpanzees – has anything like it, perhaps not even one cultural tradition so complex that it could not have been invented from scratch by a single individual? Let us start with mechanism (Tinbergen 1963; Bateson and Laland 2013), comparing social learning in adult chimps and human children. An early hypothesis held that chimps emulate the outcomes of conspecifics’ actions whereas humans imitate the behavioral sequences themselves (Tomasello 1996; Tennie et al. 2006).2 Emulating outcomes imposes a ceiling on the complexity of transmitted behavior as learners must re-invent entire behavioral sequences. By directly imitating behavioral sequences rather than inferring them from outcomes, learners have greater opportunity to experiment with modifications. As is often the case, subsequent studies sullied this simple story. Children and chimps each possess a portfolio of social learning mechanisms, including imitation and emulation, though they deploy these mechanisms differently (Whiten et al. 2009). While chimps can imitate, they do not do so with skill or ease. Chimps are also conservative when it comes to social learning, only adopting new tactics if they do not already have something that works (Tennie et al. 2009). Contrast this with children who often and automatically copy everything an experienced individual does, including actions

psychology and human behavioral ecology (Laland and Brown 2011). Whereas human behavioral ecology emerged from cultural anthropology as a theoretically inspired but ethnographically based enterprise, cultural evolution emerged from

1

2

Newton’s quip itself seems to be a product of cultural evolution, not entirely his own creation. While Newton gets credit, the idea goes back hundreds of years (Merton 1993). Here, and elsewhere, italicized words and phrases often have meanings specific to the scientific context, meanings which may or may not correspond with common usage.

https://doi.org/10.1017/9781108377911.016 Published online by Cambridge University Press

358

Karthik Panchanathan

which seem causally irrelevant, a process dubbed overimitation (Lyons et al. 2007; Nielsen and Tomaselli 2010; Nielsen et al. 2014; but see Berl and Hewlett 2015). So, the outline of the simple story still stands: Social learning in humans relies heavily on imitation, resulting in high fidelity social transmission and allowing the cumulative evolution of complex cultural adaptations. Without this faculty, social learning in nonhuman animals – mutating Newton’s quip – allows them only to glimpse what the tallest among them can already see. Nevertheless, this kind of social learning, common in nonhuman animals, facilitates the spread of adaptive behavior and generates cultural traditions (Whiten et al. 2009; McElreath et al. 2018). Next, let us turn to evolution (Tinbergen 1963; Bateson and Laland 2013), asking why humans ended up with cumulative culture while other apes did not. Assuming the common ancestor of humans and chimps possessed capacities for emulation and imitation suggests that humans added higher fidelity imitation since the split some 6–7 million years ago (Whiten et al. 2009). The Pleistocene (roughly 2.5 million to 12,000 years ago), an epoch characterized by markedly increased environmental variability, may have played a key role in this transition (Richerson and Boyd 2000, 2013). Genetically evolved adaptations are sufficient when environments are stable generation after generation. When environments are highly unpredictable from one generation to the next, it is better to turn to individual learning. Cultural evolution excels in between, when the rate of environmental change is too fast for biological evolution to track but too slow to ignore the wisdom of elders (e.g., Schniter 2014). While this hypothesis may explain when cumulative culture evolved, it does not explain why humans alone made this transition. We know that brain sizes increased across a range of species during the Pleistocene (Jerison 1973; see also Muthukrishna et al. 2018). However, as with other aspects of human uniqueness, it is hard to know with certainty why a trait evolved when it only did so in one lineage. Perhaps free forelimbs resulting from bipedalism provided a crucial pre-adaptation for technological evolution when combined with a big-brained and social ape (Washburn 1959; Neco and Richerson 2014). Perhaps complex culture co-evolved along with other traits, including an extended juvenile period, language, and cooperation (Richerson and Boyd 2020). Regardless, the same cultural capacity that allowed our ancestors to keep pace with the constantly shifting Pleistocene, when paired with the stability of the Holocene, resulted in explosions in population size and ethnolinguistic diversity, and a series of technological and social transformations including the agricultural revolution, the rise of cities and states, and the industrial revolution (Richerson et al. 2001).

https://doi.org/10.1017/9781108377911.016 Published online by Cambridge University Press

Cultural Evolution

359

population genetics as an ethnographically inspired but theoretically based enterprise. This chapter reviews both the theory of cultural evolution and recent empirical studies showcasing how it has been applied to the study of human behavior and evolution.

15.1

The Theory of Cultural Evolution This section organizes cultural evolutionary theory into three parts. The first aligns with evolutionary psychology (Barkow et al. 1992; Gaulin and McBurney 2001; Pinker 2003; Buss 2014; Barrett 2015; Chapter 16), studying how natural selection, acting on genes, favored a psychological capacity for cultural transmission. The second studies adaptation to the ecology. Whereas human behavioral ecology (Cronk 1991a; Smith and Winterhalder 1992a; Winterhalder and Smith 2000) focuses on adaptive outcomes, cultural evolution focuses on adaptive processes by modeling evolutionary forces and their interactions. And the third addresses the coevolution of genes and culture, an example of niche construction (Odling-Smee et al. 1996; Laland et al. 2000; Odling-Smee et al. 2003), in which biological evolution gives rise to a cultural system of inheritance only to have the resulting cultural environments impose selection pressures back on the genes.

15.1.1 The Evolution of Cultural Capacity Why did natural selection favor a capacity for culture in our ancestors? What role did culture play in the spectacular success and spread of our species? Why did culture evolve during the Pleistocene and not earlier? Why did other species, especially our closest relatives, not evolve a similar adaptation? These are but a few of the many questions we might ask about the evolved psychology underlying our cultural capacity. This section addresses the first two questions, and Box 15.1 the next two. Perhaps natural selection favored our cultural capacity so that social learners could avoid the hard work of discovering adaptive behavior on their own. Perhaps the innovation of some allows others to imitate, an intuition captured by the idiom warning against reinventing the wheel. This hypothesis might also suggest an answer to the second question. Perhaps culture creates a profitable division of labor as in the economics argument for specialization and trade. Perhaps the innovation of some allows others to pursue other activities – and everyone ends up better off. How might we test these hypotheses? Without access to a time machine, paleontologists and archaeologists turn to the next best thing, the fossil and material records. Building mathematical models provides another kind of test (Maynard Smith 1982; Kokko 2007; McElreath and Boyd 2007; Otto and Day 2007; Epstein 2008; Smaldino 2017). Rather than test hypotheses against data, models allow us to evaluate an argument’s logical coherence, a good first step as there is no use in pursuing logically inconsistent hypotheses. Rogers (1988) developed an evolutionary model of culture to test whether social learning evolves and whether everyone ends up better off for it. In the model, the

https://doi.org/10.1017/9781108377911.016 Published online by Cambridge University Press

360

Karthik Panchanathan

environment is characterized by one of two states (e.g., wet or dry), periodically switching from one to the other. Each environmental state is associated with an adaptive behavior (e.g., farming or herding).3 Individuals engage in one of two genetically heritable strategies: individual learners pay a cost (e.g., trial and error learning) and correctly select the adaptive behavior, whereas social learners avoid this cost by randomly copying someone else but acquire the adaptive behavior only if that person behaves adaptively.4 To analyze the model, we start with an ancestral state in which everyone individually learns, at which point a mutant social learner is introduced. With everyone else learning on their own – and therefore making the correct choice, the lone social learner is sure to acquire the adaptive behavior. And without having to pay for it, the social learner has higher fitness than individual learners – and so leaves behind more offspring. But the social learner’s advantage is short-lived. As the frequency of social learning increases, the average fitness of the social learning strategy decreases. Remember, the environment periodically shifts. When it does, prior knowledge becomes obsolete; only individual learning increases the frequency of adaptive behavior in the population. The more social learners there are, the more likely it is that any one of them copies another social learner. In the aftermath of an environmental switch, copying a social learner guarantees maladaptive behavior. The Rogers model seems to answer our first question. Natural selection can favor social learning as a form of information scrounging. However, the social learning strategy does not go to fixation and drive individual learning to extinction. Instead, the two strategies settle down to a stable equilibrium in which each strategy has the same average fitness (Figure 15.1a). In many behavioral domains, especially culture, cooperation, and conflict, the payoff to pursuing a particular strategy depends on the behavior of others and fitness is often frequency dependent (Gintis 2000a; Kokko 2007; McElreath and Boyd 2007; Chapter 5). Social learners do best when rare, as they are sure to acquire the adaptive behavior by copying from an individual learner without having to pay the cost. Individual learners also do best when rare, but for a different reason. Social learners slavishly copy others and never pay attention to the real world. A population comprised only of social learners becomes an echo chamber, prisoners in a cave of their own construction with no correspondence between environment and adaptive behavior. Individual learners ignore others and instead observe the real world and acquire adaptive behavior. When rare, each strategy can increase relative to the other. In this model, individual learning pumps adaptive

3

4

Framing this as a choice between discrete behavioral options highlights the analogy with discrete alleles in a biological system. In doing so, this framing also assumes away the problem of discovering these alternatives and all the incremental steps that go into each variant. This kind of modeling assumption is meant to aid in scientific reasoning, not represent a commitment about reality. Box 15.1 explores the cumulative evolution of cultural adaptations. This assumption means that individual learning in this model is not about discovery and innovation, but instead about identifying the correct behavior among two previously discovered alternatives. Section 1.2 explores innovation in the context of guided variation.

https://doi.org/10.1017/9781108377911.016 Published online by Cambridge University Press

Cultural Evolution (a)

361

(b) Social Learners

Social Learners Average Fitness Individual Learners

Evolutionary Equilibrium

Frequency of Social Learners

Individual Learning

Evolutionary Equilibrium

Frequency of Social Learning

Figure 15.1 (a) Following Rogers (1988), the average fitness of individual learners and social learners as a function of the frequency of social learners. When individual learning and social learning are separate strategies, the fitness of individual learners is a constant, independent of the frequency of social learners. At the evolutionary equilibrium, the average fitness of the population is the same as the fitness of a population of only individual learners. (b) Following Boyd and Richerson (1995), when individual and social learning are selectively combined, the fitness associated with individual learning increases with the frequency of social learning. At the evolutionary equilibrium, the average fitness of the population is higher than the fitness of a population of only individual learners.

behavior into the population, social learners scrounge it from them, and the population settles down to a stable mix of the two strategies. What about our second question? Is everyone better off when some learn individually and the rest learn socially? Does the evolution of cultural transmission as information scrounging, in part, explain the spectacular success of our species? No, it does not, at least according to the Rogers model. The average fitness of a mix of individual and social learners is the same as the average fitness of a population comprised only of individual learners (Figure 15.1a). To understand why, let us focus on individual learners. Regardless of what others do, individual learners pay a cost to acquire the adaptive behavior. Unlike social learners, the fitness of individual learning does not depend on the frequencies of each strategy. Instead, the fitness of individual learning is a constant. If the fitness of individual learners is the same as the fitness of social learners at the evolutionary equilibrium, and if the fitness of individual learning is a constant, then the average fitness at the equilibrium must be identical to the fitness of a population of only individual learning. Barring some other process, such as group selection (Box 15.2, Chapter 5), if social learning is only about information scrounging, it readily evolves but no one is better off for it. This result may seem counterintuitive, but the logic is sound. Does this mean that culture played no role in the success of our species? Not necessarily. Models do not automatically resolve scientific mysteries. Like maps, models are nothing more than representations of reality, each reflecting their creator’s assumptions. Being mere representations means that all models are necessarily wrong. But like maps, some models are nevertheless useful (Box 1976). Rogers assumed that individual and social learning were distinct and independent strategies. As a result, the fitness of

https://doi.org/10.1017/9781108377911.016 Published online by Cambridge University Press

362

Karthik Panchanathan

Box 15.2

Cultural Group Selection and the Evolution of Cooperation

Until the 1960s, biologists often invoked biological group selection to explain the mystery of altruism (Wynne-Edwards 1962). Natural selection favors groups with more altruists willing to sacrifice their own reproductive success for the good of the group, or so the logic went. Williams (1966b) identified the fatal flaw in this argument. For there to be selection, there must be variation (Lewontin 1970b). The problem with biological group selection is that migration across group boundaries erodes genetic variation between groups faster than mutation can pump it back in (Figure B15.2.1a). No between-group variation means no group selection (McElreath and Boyd 2007; Okasha 2009). It was Hamilton’s (1964) inclusive fitness theory which finally resolved the mystery of altruism. Natural selection favors genes that sacrifice the reproductive success of their host organism (direct fitness) so long as this cost is more than offset by a commensurate gain in the reproductive success of closely related organisms housing identical genes due to common descent (indirect fitness). While organisms may appear altruistic, it is only in service of their “selfish” genetic masters (Dawkins 1976). The 1960s saw the rise of sociobiology and demise of group selection, representing a revolution in evolutionary thought and, as part of a broader shift to methodological individualism across the social and behavioral sciences, resulted in an obsessive focus on individual behavior and selection (Segerstrale 2000). Since the revolution, group selection has become a failed paradigm, a dirty word, and inextricably linked to the problem of cooperation. This legacy contributes to the deep confusion over cultural group selection (Henrich 2004a; Richerson and Boyd 2005; McElreath and Boyd 2007; Panchanathan 2011; Chapter 5). Cultural group selection is not the same as old-school biological group selection – nor is it typically invoked as a direct solution to the problem of cooperation. Cultural group selection builds on the theory of multilevel selection (Price 1970; Hamilton 1975; Okasha 2009), and is comprised of two parts. Cultural group selection first argues that the nature of cultural transmission, unlike genetic transmission, gives rise to multiple stable equilibria. When people conform to norms or imitate prestigious individuals, they do so for purely self-interested reasons, to acquire adaptive behavior. As a byproduct, groups become homogeneous and variation between groups can be maintained despite migration (Figure B15.2.1b). This effect is amplified by other social processes including behavioral assortment using ethnic markers (Boyd and Richerson 1987; Barth 1998; McElreath et al. 2003) and social sanctions (Boyd and Richerson 1992; Panchanathan and Boyd 2004). Recent research offers empirical support, finding that substantial cultural variation resides between rather than within social groups (Bell et al. 2009; Handley and Mathew 2020). The second part of cultural group selection theory focuses on the problem of equilibrium selection. If different groups end up at different social equilibria, which equilibria spread and why? While studying individual behavior may explain why people conform to norms, it offers limited guidance in predicting which norms spread and which norms perish. Norms, like social institutions, are group-level traits (Smaldino

https://doi.org/10.1017/9781108377911.016 Published online by Cambridge University Press

Cultural Evolution

(a)

363

(b) Migration

Migration

Social Interaction

Time

Figure B15.2.1 (a) In biological evolution, migration quickly eliminates between-group genetic variation (alleles are represented by circles). (b) In cultural evolution, social interaction, including imitation, assortment, and sanctions, can offset the effect of migration and preserve betweengroup cultural variation (cultural variants are represented by squares).

2014), emergent social phenomena that cannot be reduced to the individual level. To explain the cultural evolution of group-level traits, we need a theory of cultural group selection. Cultural group selection mechanisms include conflict and conquest among groups (Soltis et al. 1995; Boyd et al. 2003), imitation across group boundaries (Hirschman 1970; Boyd and Richerson 2002), and selective migration between groups (Hirschman 1970; Boyd and Richerson 2009b). And all else equal, these mechanisms favor the spread of cooperative, group-beneficial norms. Sociobiology has provided us with two ways of understanding the evolution of social behavior. The selfish gene perspective (Hamilton 1964; Dawkins 1976) focuses on individuals and their social interactions, whereas the multilevel perspective (Price 1970; Hamilton 1975; Okasha 2009), which includes cultural group selection, focuses on groups and the social interactions within and between them. Too often, discussions of social evolution turn into debates about which approach is correct and which approach is incorrect. This is a mistake. These two approaches are formally equivalent perspectives on the same underlying process, neither correct nor incorrect (Hamilton 1975; McElreath and Boyd 2007). When it comes to studying the evolution of social institutions like marriage, kinship, and political organization, evolutionary social scientists need not choose between these perspectives. In fact, they might do better by adopting and internalizing both, a “gestalt-switching pluralism” (Kerr and GodfreySmith 2002) that can reveal more than either perspective does by itself.

individual learning is frequency independent, and so the evolution of social learning cannot explain an increase in average fitness. Boyd and Richerson (1995; see also Perreault et al. 2012) instead assumed that everyone pursues the same strategy, one which combines individual and social

https://doi.org/10.1017/9781108377911.016 Published online by Cambridge University Press

364

Karthik Panchanathan

learning. Individuals first engage in individual learning, trying out both behavioral alternatives and comparing results. In some instances, experiments yield decisive results. In others, experiments prove inconclusive and individuals copy from someone else. Individuals vary in their reliance on social learning. Some rely heavily on social learning, turning to personal experience only when results are decisive; others rely mostly on individual learning, accepting even the weakest evidence from their own experiments. The Boyd and Richerson model allows us to ask how natural selection strikes a balance between personal experience and social learning. At the evolutionary equilibrium of this model, the average fitness of the population is higher than the average fitness of a population comprised only of individual learners (Figure 15.1b). Why the difference with the Rogers model? In the Boyd and Richerson model, individuals are selective social learners, relying on personal experience only when it is decisive and otherwise turning to social learning. Selectively combining individual and social learning in this way is a game changer, increasing the effectiveness of individual learning and spreading that increased effectiveness through social learning. And, as a by-product, everyone is better off. Just to be clear, this is no appeal to group selection. Individuals pursue the strategy that maximizes individual fitness and as a by-product everyone is better off.

15.1.2 The Forces of Cultural Evolution As anyone knows, if you throw a ball into the air, it falls back down. Few, however, can predict the precise location where it lands. In fact, no one could until Newton discovered the laws of motion. Armed with Newton’s second law, an undergraduate can now build a mathematical model that accounts for the various physical forces acting on the ball and predict the precise path of a projectile from launch to landing. Since Newton, physicists have used mathematics to make sense of all manner of matter and motion. Inspired by the “unreasonable effectiveness of mathematics in the natural sciences” (Wigner 1960), biologists too built models to understand how the various forces acting on a population – mutation, migration, drift, and natural selection – result in evolution, the change in genetic composition from one generation to the next. These efforts, in turn, led cultural evolutionists to build models to understand how the cultural composition of a population changes as a result of the various forces acting upon it, including forces analogous to those in biological evolution – mutation, migration, drift, and natural selection – as well as decisionmaking forces novel to cultural evolution – guided variation and various social learning biases (Figure 15.2; the taxonomy presented here follows Richerson and Boyd 2005; see also Henrich and McElreath 2003; Mesoudi 2011).

15.1.2.1 Natural Selection and Cultural Variation As any student of biology knows, natural selection acting on genetic variation favors traits that help their bearers to survive and reproduce. In cultural evolution, natural selection acting on cultural variation (Figure 15.2) favors traits that are better able to

https://doi.org/10.1017/9781108377911.016 Published online by Cambridge University Press

Cultural Evolution (a)

365

(b)

Cultural Mutation

Cultural Natural Selection Guided Variation

Cultural Migration

Cultural Drift

Social Learning Biases Content Bias Frequency Bias Model Bias

Figure 15.2 Forces of cultural evolution that alter the frequency of cultural variants in the

population. (a) Cultural evolutionary forces analogous to biological evolution. Note: These forces refer to cultural processes acting on cultural variants, not biological processes acting on genetic variation. (b) Decision-making forces unique to cultural evolution.

thrive and replicate, regardless the effect these traits have on their bearer’s biological survival and reproduction (Boyd and Richerson 1985). In this chapter, biological natural selection or simply natural selection refers to natural selection acting on genetic variation, whereas cultural natural selection refers to natural selection acting on cultural variation. Biological natural selection and cultural natural selection are analogous but not identical evolutionary forces. Because they operate on different transmission mechanisms – genes and culture – they can have different evolutionary properties. For example, when parents socialize their children (vertical transmission), cultural natural selection favors cultural traits that also maximize reproductive success. In this case, cultural and biological natural selection act in concert. All else equal, if some people prefer to have children while others do not, cultural natural selection on cultural variation will eliminate childlessness as there will be no biological parents to pass along this preference. By contrast, when children are influenced by peers (horizontal transmission) or nonparental influences – including aunts and uncles, teachers, and the prestigious (oblique transmission) – cultural natural selection on cultural variation can, in some cases, favor the spread of genetically neutral or even maladaptive behaviors. When it comes to culture, many evolutionary social scientists still subscribe to Wilson’s (1978) metaphor of biology as the master holding its dog, culture, on a tight leash. In this view, culture is nothing more than a proximate means by which the interests of our genes are ultimately met (Figure 15.3a). To explain and predict behavior, one need only consider the logic of fitness maximization. While metaphors are indispensable tools for making sense of the unknown, we must never forget that metaphors are just that, tools. If we are not careful, we can become prisoners of our metaphors, trapped into particular ways of perceiving the world. As Rosenblueth and Weiner warned, “The price of metaphor is eternal vigilance” (Lewontin 2001). Traits that are favored by cultural evolution need not promote the biological reproductive success of their bearers. For example, if young people imitate the rich and famous while forgoing children increases the likelihood of becoming rich and famous, a

https://doi.org/10.1017/9781108377911.016 Published online by Cambridge University Press

366

Karthik Panchanathan (a)

(b)

Genes

Genes

Culture

Culture

Behavior

Behavior

Figure 15.3 The causal relationship among genes, culture, and behavior. (a) Genes shape both

culture and behavior, using culture as a proximate mechanism to produce adaptive plasticity. (b) Gene-culture coevolution in which genes and culture shape each other and jointly shape behavior.

preference for childlessness can spread – even if those holding this preference have no biological children of their own. The demographic transition (Chapter 13) may be an example of just such a process, in which a cultural preference for lower fertility was favored, in part, as a result of novel socialization patterns and economic opportunities, a point to which we will return in Section 15.2.1.

15.1.2.2 Guided Variation As with group selection (Box 15.2), most students of biology were taught that Lamarckism was not just wrong and antithetical to Darwinism, but also silly and perhaps even dangerous (Riskin 2016).5 Lamarck, like many of his contemporaries, believed that organisms could develop useful characteristics during their lifetimes and transmit these acquired characteristics to their offspring. The textbook example is the giraffe’s long neck. Ever stretching to reach the highest leaves, ancient giraffe ancestors were thought to have elongated their necks, and then transmitted these longer necks to their offspring. The repetition of this process generation after generation resulted in modern giraffes. But since the Modern Synthesis, students of biology have been taught that development and evolution are separate and distinct processes. Any changes to organisms during their lifetimes cannot be transmitted to offspring – and thus development processes cannot contribute to evolutionary outcomes. Instead, evolution results from various forces that change gene frequencies from one generation to the next. Adaptation results from natural selection whittling away at novel variation generated by random genetic mutations. While this model may be a decent approximation of biological reality, the line between evolution and development is blurry. So much so that some biologists and philosophers advocate for an Extended Evolutionary Synthesis, one that incorporates 5

Of course, the dirty secrets many of us were not taught include that Darwin himself subscribed to both group selection and Lamarckism!

https://doi.org/10.1017/9781108377911.016 Published online by Cambridge University Press

Cultural Evolution

367

Lamarckian processes including epigenetic transmission as well as ‘plasticity first’ adaptation in which development becomes a source of variation on which natural selection can act (Oyama et al. 2001; Pigliucci and Miller 2010; Jablonka and Lamb 2014; Laland et al. 2015; see also Peterson 2017). In contrast to biological evolution, cultural evolution is fundamentally Lamarckian. Culture represents a pool of adaptive information from which people can learn. They can then transform what they have learned socially through various individual learning mechanisms. In many cases, these transformations will not be random, but will instead be biased toward adaptive outcomes. In biology, this would be like having a genetic system in which mutations were not random, but instead fitness-enhancing. The opportunity for social learning then means that the next generation can pick up where the previous one left off. Instead of re-inventing the wheel, they can improve on its design. This process of linking innovations from individual learning to transmission through social learning results in the force of guided variation (Figure 15.2; Boyd and Richerson 1985) and contributes to the cumulative evolution of complex adaptations (Box 15.1).

15.1.2.3 Social Learning Biases When it comes to genetics, inheritance is destiny. We are our parents’ children.6 Not so with culture. Through the force of guided variation, individuals can intentionally modify what they have learned and transmit these modifications to others. In addition, there are various social learning biases (Figure 15.2) that influence whom or what learners choose to imitate. Unlike guided variation, which is a creative process that introduces novel variation, these social learning biases, like biological and cultural natural selection, are culling processes that selectively favor certain cultural variants over others. A content bias refers to the preferential adoption of certain cultural variants over others based on the characteristics of the variants rather than the individuals bearing them (Figure 15.2; also called a direct bias; Cavalli-Sforza and Feldman 1981; Boyd and Richerson 1985; Durham 1991). A content bias might result from individuals comparing alternatives and choosing based on perceived benefits and costs. The rate of cultural evolution will be fast when comparison is easy, such as choosing metal tools over stone tools. When difficult, beneficial innovations may spread slowly or not at all. For example, convincing people to boil water is difficult because waterborne diseases are not the only reason people get sick, because fuel is expensive, and because the idea of microscopic bacteria may not resonate with folk medical beliefs (Rogers 1995). Content biases can also result from features of cognition that make some variants more appealing than others. Boyer (1994) and Atran (2002) argue that a content bias favoring “minimally counterintuitive” stories, in which some of our

6

Not entirely, of course. Environmental factors influence genetic expression. And, whether a blessing or a curse, genetic engineering is no longer science fiction (Cyranoski 2018).

https://doi.org/10.1017/9781108377911.016 Published online by Cambridge University Press

368

Karthik Panchanathan

folk intuitions are violated while others are not, helps explains the prevalence of supernatural beliefs. Ghosts, for example, violate our understanding of physics by crossing through solid objects, but otherwise behave in ways consistent with our expectations of human behavior. When the comparison of material consequence or psychological appeal proves difficult, individuals can ignore the variants and focus instead on the individuals bearing them. In conformist biased learning, individuals disproportionately adopt the most common cultural variant (Figure 15.2; Boyd and Richerson 1985; Henrich and Boyd 1998). Suppose, for example, that you pursue a career in academic research despite the protestations of your loved ones. After landing that coveted tenure track professorship, you notice that 6 of your 10 department colleagues don a blazer while teaching. With a strict frequency bias, you too would wear a blazer with 60% probability. With a conformist bias, the probability would be higher still. How much higher depends on the degree of conformity. With a weak bias, the adoption probability will be close to the frequency of blazers among your colleagues. As the conformist bias strength increases, the probability of adopting the more common variant approaches 100%. Disproportionately adopting common cultural variants can be adaptive when other forces of cultural evolution, including cultural natural selection, guided variation, and content bias, result in adaptive variants becoming common but not going to fixation. In this way, a conformist bias amplifies other adaptive processes by allowing individuals to leverage the “wisdom of crowds” (Surowiecki 2005). This process results in the loss of uncommon variants, homogenizing social groups and maintaining differences among them, potentially fueling cultural group selection (Box 15.2). A prestige bias refers to the preferential imitation of high status people (Figure 15.2; Boyd and Richerson 1985; Henrich and Gil-White 2001). Returning to our academic example, if your colleagues vary in status, you might want to adopt the wardrobe of the Nobel Prize winner rather than the most common outfit. Such a bias would have been adaptive to our ancestors in situations in which it was easier to infer successful individuals than to infer the secret of their success. A prestige bias can result in naive individuals imitating a wide range of traits, including traits that may be correlated with but not causally contributing to success, similar to overimitation (Box 15.1).

15.1.2.4 Why Culture and Modeling Culture Matter Critics of the cultural evolutionary approach often complain that culture is not an adequate causal explanation and that modeling cultural evolutionary processes is unnecessary in predicting behavioral outcomes. Let us address these criticisms in turn. The criticism that culture is not an explanation amounts to a claim that human behavior can be sufficiently explained in terms of evolved psychology and local ecology. Once these factors are accounted for, there is nothing left for ‘culture’ to explain. This criticism would be accurate if the strength of social learning biases dwarfed the power of cultural natural selection (Figure 15.2). If this were the case, the study of cultural evolution would reduce to an environmental and behavioral

https://doi.org/10.1017/9781108377911.016 Published online by Cambridge University Press

Cultural Evolution

369

science, one in which proximate explanations of why people adopt the beliefs and behaviors they do focus on behavioral ecology and ultimate explanations focus on evolutionary psychology. If, instead, cultural natural selection is an important force, then cultural history matters, too, and the study of culture requires the social sciences in addition to ecology and psychology. Salamon’s (1995; reviewed in Richerson and Boyd 2005) ethnographic study of Illinois farming communities provides an example. Salamon identified two distinct farming strategies that have persisted across multiple generations even though everyone farms the same land. These approaches to farming reflect cultural historical differences, not ecological differences. Farmers with English ancestry treat farming as a business and land as a commodity, whereas those with German ancestry see farming as a way of life and land as a sacred family possession. The second criticism, that modeling cultural evolution is unnecessary, invokes the phenotypic gambit (Grafen 1984), that culture is just a proximate means by which the interests of our genes are ultimately met (Wilson 1978). Smith and Winterhalder (1992b), for example, argue that “selection will favor traits with high fitness. . .irrespective of the particulars of inheritance”. This approach works for simple adaptive topographies. In the limiting case, the details of genetics, culture, or learning are irrelevant in predicting outcomes; every adaptive process will discover the same fitness optimum. But adaptive topographies are not always simple. There may be multiple adaptive peaks that shift over time. In these more complex cases, the details of the inheritance system matter. To understand why particular cultural variants spread while others perish in these cases, we need to predict the net effect of all these forces of cultural evolution (Figure 15.2). This is often difficult if not impossible using intuition and verbal reasoning alone. Sometimes it is better to set aside the metaphor and build a model.

15.1.3 Gene-Culture Coevolution Consider yourself privileged if you can take milk with your coffee.7 Most adults around the world are lactose intolerant due to a steep decline in lactase production during adolescence. This pattern is the norm across mammals. Lactase persistence is restricted to a small subset of human populations. For most human societies and all other mammalian species, milk is baby food. Since the only function of lactase is to digest the milk sugar lactose, natural selection favored the cessation of lactase production around the time of weaning. This adaptive logic held for our Pleistocene ancestors. With the advent of herding, however, humans had ready access to milk as adults. Natural selection then favored lactase persistence resulting in the pattern we see today: high rates of lactase persistence among those with ancestry from northern Europe and some regions of Africa; intermediate rates among those with ancestry from the Mediterranean, the Middle East, and central and south 7

But mistaken. Black is better.

https://doi.org/10.1017/9781108377911.016 Published online by Cambridge University Press

370

Karthik Panchanathan

Asia, populations that often ferment milk into cheese or yogurt; and low rates for Native Americans, many sub-Saharan Africans, and everyone else. Lactase persistence is a population-specific rather than a species-typical adaptation, evolving independently in populations with long histories of pastoralism and milk consumption (Simoons 1970; Durham 1991; Holden and Mace 2009; Itan et al. 2009; Ségurel and Bon 2017).8 Lactase persistence is an example of gene-culture coevolution (Cavalli-Sforza and Feldman 1981; Boyd and Richerson 1985; Richerson and Boyd 2005; for a recent review, see Laland 2017). The cultural evolution of pastoralism created an environment which favored the biological evolution of lactase persistence. Gene-culture coevolution represents an example of niche construction (Odling-Smee et al. 1996; Laland et al. 2000; Odling-Smee et al. 2003). When we speak of “selection pressures” we often treat natural selection as an external force acting on populations. In the niche construction perspective, organisms modify their environments and these modified environments in turn impose new selection pressures on organisms. Naked mole rats provide an example. As the ancestors of naked mole rats burrowed deeper underground, natural selection favored a gradual loss of hair and vision. In this way, the environment is transformed from an exogenous variable to an endogenous one, requiring the researcher to keep track of the coevolutionary dynamics between organism and environment. Gene-culture coevolutionary dynamics in humans may be a particularly powerful form of niche construction (Richerson and Boyd 2005; Laland 2017). Once you adopt the gene-culture coevolution perspective, it becomes difficult not to see its effects everywhere. Take language. Compared to us, our ancestors had rudimentary communicative skills. Any selection on improved communication would have resulted in a more complex linguistic environment. This human-induced environment would then have selected for improved communicative ability. In this way, the capacity for language and the complexity of the linguistic environment coevolved (Pinker and Bloom 1990; Pinker 1994; Richerson and Boyd 2010). The human capacity for large scale cooperation may represent another example of gene-culture coevolution (Richerson and Boyd 2005; Bowles and Gintis 2011). Our pre-cultural ancestors inherited a set of behavioral predispositions shared with other primates, arising from kin selection and reciprocity, and enabling cooperation among family, friends, and local group members. The advent of our cultural capacity unleashed a process of cultural group selection and favored the cultural evolution of large-scale cooperation (Box 15.2). This novel cultural environment of cooperation then favored the biological evolution of a new set of behavioral predispositions unique to humans, including prosocial preferences, a moral psychology willing to

8

This commonly told story of why some are lactose tolerant while others are not may be an oversimplification. It seems that most people can become at least somewhat lactose tolerant regardless of their genetic makeup (Byers and Savaiano 2005).

https://doi.org/10.1017/9781108377911.016 Published online by Cambridge University Press

Cultural Evolution

371

adopt social norms and punish violators, and in-group favoritism spanning large, symbolically marked tribes. As a result, human societies resemble eusocial insect colonies in many ways, except for a reproductive division of labor. Neither ape nor ant are we, but something in between, a “crude superorganism” characterized by conflict and cooperation (Richerson and Boyd 1999). The evolution of language and cooperation through gene-culture coevolution represent examples of species-typical adaptations that arose during the Pleistocene. The evolution of lactase persistence, by contrast, is an example of a populationspecific adaptation that arose during the Holocene. The prevalence of sickle-cell anemia among those of African descent may represent another example (Durham 1991; Laland et al. 2010). West African agriculturalists cleared forests to grow yams, resulting in pools of stagnant water after the rains, a perfect breeding ground for mosquitos. As mosquitos spread malaria, natural selection favored the sickle-cell allele, which conferred malarial resistance. And as we learn more from genomics, we will likely discover many more cases of population-specific adaptations arising from gene-culture coevolution (Laland et al. 2010; Richerson et al. 2010; Laland 2017). In Wilson’s (1978) metaphor of dog and master, culture was but one form of adaptive plasticity controlled by the genes, helping to tailor phenotypic development to the local ecology (Figure 15.3a). Heeding Rosenblueth and Weiner’s warning, “eternal vigilance” (Lewontin 2001) helps us know when to discard old metaphors for new ones. As part of a larger call for an extended evolutionary synthesis (Oyama et al. 2001; Pigliucci and Muller 2010; Jablonka and Lamb 2014; Laland et al. 2015), perhaps we might re-imagine gene-culture coevolution as an intricate ballet in which genes and culture take turns leading and following (Figure 15.3b). And, despite giving birth to culture, as social and technological complexity increase, it may be our genes that spend less time leading and more time following.

15.2

The Empirics of Cultural Evolution In reviewing the “three styles” of evolutionary social science, Smith (2000) characterized cultural evolution as “theoretically rich and sophisticated, but empirically impoverished” when compared to human behavioral ecology and evolutionary psychology. While cultural evolution was never a purely theoretical research paradigm (e.g., Hewlett and Cavalli-Sforza 1986; Soltis et al. 1995), the discipline was historically dominated by theoretical investigation. But this characterization is no longer accurate. The past two decades has seen rapid growth in the empirical study of cultural evolution (Mesoudi 2011, 2017). This section reviews recent examples, categorizing them into three methods: (1) fieldwork, (2) laboratory experiment, and (3) phylogenetics and history.

15.2.1 Cultural Evolution in the Field Just as each culture follows customary rituals, each scientific discipline practices customary methods. Economists construct models. Psychologists crank out

https://doi.org/10.1017/9781108377911.016 Published online by Cambridge University Press

372

Karthik Panchanathan

experiments. And anthropologists conduct fieldwork.9 While models sharpen reason and experiments allow control, only observational fieldwork studies humans on their terms and in their natural habitats.

15.2.1.1 Fertility in Rural Poland Fertility rates have plummeted since the industrial revolution, beginning in Europe and later spreading to the rest of the world. Though the demographic transition has been well documented, explaining why it began and later spread has been a “central theoretical problem of human sociobiology” (Vining 1986; see also Borgerhoff Mulder 1998b; Colleran 2016; Chapter 13). One point of contention centers on whether the fundamental cause is ‘economic’ or ‘cultural’. One version of the economic hypothesis argues that the transition to market economies favored investment in embodied capital resulting in fewer offspring with higher levels of parental investment (Kaplan 1996; Kaplan et al. 2002; Shenk et al. 2013; Colleran 2016). One version of the cultural hypothesis argues that higher rates of nonparental social transmission (horizontal or oblique rather than vertical) coupled together with new avenues of social status competition favored the spread of low fertility norms. Some anthropologists argue that separating “cultural” and “economic” in this way makes no sense as economic systems and preferences are inseparable from other aspects of culture (e.g., Sahlins 1972; Chibnik 2011). Even if they do not go this far, most researchers agree that complex phenomena like the demographic transition are unlikely to result from a single cause. Nevertheless, most research focuses either on the economic hypothesis using individual-level data or the cultural hypothesis using population-level data (but see Shenk et al. 2013). Colleran et al. (2014) compared these two explanations of fertility decline by studying the relationship between education and fertility both within and between communities in rural Poland. Women’s education is a key predictor of fertility decline, but it is not clear whether this supports the economic or the cultural hypothesis. According to the economic hypothesis, fertility declines as individual women’s education increases. According to the cultural hypothesis, the aggregate level of education should also matter. In more educated communities, all women, even those without an education, will be more heavily exposed to and influenced by low fertility norms. Colleran et al.’s results indicate that aggregate education is a better predictor of fertility decline than individual education. For example, regardless of their own characteristics, women in the most educated community had half as many children as women in the least educated community. The lesson here is not that individual attributes are irrelevant or that the economic hypothesis is incorrect. 9

These characterizations are clearly caricatures. We should never essentialize “cultures” or “scientific disciplines” as discrete, bounded, and homogenous groups (Gupta and Ferguson 1992). Economists also conduct behavioral experiments and analyze historical data; psychologists also build computational models and conduct cross-cultural research; and anthropologists also build evolutionary models and conduct experiments in the field. As with everything else in nature, “cultures” and “scientific disciplines” are characterized by variation. Nevertheless, caricatured constructs can capture meaningful variation between groups. All models are wrong after all, but some are nevertheless useful (Box 1976).

https://doi.org/10.1017/9781108377911.016 Published online by Cambridge University Press

Cultural Evolution

373

In fact, some of Colleran et al.’s findings were consistent with the economic hypothesis. Instead, the results highlight the ways in which cultural norms may shape fitness-relevant domains of behavior, including reproduction, alongside ecological factors – and that, in some cases, the two may reinforce each other.

15.2.1.2 Cattle Raiding in Turkana Like the capacity for complex and cumulative culture (Box 15.1), large-scale cooperation among unrelated individuals represents a uniquely human adaptation (Box 15.2; Chapter 5). And like the demographic transition, cooperation represents another “central problem of sociobiology” (Wilson 1975b). The challenge of cooperation lies in solving the free rider problem. If everyone enjoys the benefits of cooperation regardless of their own contribution, self-interested individuals will, of course, choose not to contribute. Models (Boyd and Richerson 1992; Boyd et al. 2003) and experiments (Yamagishi 1986; Ostrom et al. 1992; Fehr and Gächter 2002) show how the voluntary sanctioning of free riders can sustain cooperation. But punishment just begs another question: If administering punishment is costly, what motivates selfinterested individuals to punish free riders? There are various solutions to this second-order free rider problem. In complex, state-level societies, governments police crime and administer punishment. But formal institutions like police forces and court systems were not the norm across human history. Another class of solutions, including costly signaling (Gintis et al. 2001) and social exclusion (Panchanathan and Boyd 2004), makes sanctioning individually beneficial, transforming a public good into a private one, thereby eliminating the second-order free rider problem. But these mechanisms become increasingly unworkable as group size increases. A third class of solutions focuses on unique properties of cultural transmission compared to genetic transmission, such as conformist transmission (Henrich and Boyd 2001; Guzmán et al. 2007), and how they fuel cultural group selection (Box 15.2; Boyd et al. 2003; Richerson et al. 2016). Mathew and colleagues (Mathew and Boyd 2011, 2014; Handley and Mathew 2020) studied cattle raiding among Turkana pastoralists to test aspects of the cultural group selection hypothesis. The Turkana, an East African ethnolinguistic group numbering roughly a million people, practice a form of nomadic pastoralism that includes a perpetual struggle for existence with other ethnolinguistic groups, raiding their neighbors’ cattle and protecting their own. This kind of ‘informal warfare,’ perhaps counterintuitively, represents a stark example of large-scale cooperation. Warriors incur substantial private costs in the form of injury and death, costs which are not obviously offset by the gains of private goods in the form of captured cattle. In addition, warfare provides a public good to everyone in the form of territorial defense and expansion. Raiding parties comprise hundreds of unrelated men drawn from subsections across Turkana society, providing individuals with strong temptations to desert in the lead up to a raid and take off with more cattle than socially prescribed in the aftermath – and as many as half do. Turkana cattle raiding would collapse if not for collectively administered punishment in the form of insults, fines, and beatings. While foragers and horticulturalists routinely engage in cooperation

https://doi.org/10.1017/9781108377911.016 Published online by Cambridge University Press

374

Karthik Panchanathan

comprising dozens of related and face-to-face interactants (Gurven 2004; Hill et al. 2009), cooperatives are sufficiently small to be explained by a combination of kin selection, reciprocity, and reputation. For centralized states, cooperation among millions or more can be sustained through formal punishment institutions. The Turkana represent something in between, cooperating and sanctioning free riders at the scale of an ethnolinguistic group to support inter-group warfare without recourse to a centralized political structure, a pattern of social organization and behavior that may have been common during much of human prehistory (Bowles and Gintis 2011). The maintenance of these cooperation and sanctioning norms at the scale of ethnolinguistic units is consistent with cultural group selection and hard to explain with mechanisms like kin selection, reciprocity, and reputation.

15.2.2 Cultural Evolution in the Lab While observational fieldwork has the benefit of ecological validity, it comes with a cost. How confident can we be about causal inferences when we cannot manipulate target variables? The real world is messy. Everything interacts with everything else. By isolating and manipulating theoretically relevant variables and controlling others, the experimenter, whether in the field or in the lab, can draw stronger causal inferences than can the observer.

15.2.2.1 The Evolution of Sanctioning Institutions The Turkana case study (Section 15.2.1.2) demonstrates how punishment sustains collective action in an ecologically valid setting. But demonstrating how a social institution functions is one thing. Demonstrating how it spreads is quite another. Gürerk et al. (2006) designed a cultural evolution experiment to do exactly this. Each period of the experiment comprised four stages. First, participants independently and simultaneously chose between living in a society that permitted punishment and a society that did not. Second, participants in each society chose how much of their endowment to contribute to the public good. Each dollar not contributed to the public good is a dollar the participant kept. Each dollar contributed to the public good was multiplied by a certain amount and then distributed equally to everyone in that society. Third, and only in the society that permitted punishment, participants had the option to sanction others at a personal cost. Fourth, individuals were provided anonymized data about the earnings of participants in both societies. Only one in three participants initially chose the society permitting punishment – two in three preferred a world without punishment. By the end of the experiment, however, most of the participants chose the society with punishment, having learned that punishment deters free riding. In the punishment-free society, free riders earned more than contributors. Not so in the society with punishment. These results suggest that people only reluctantly adopt punishment institutions. Many initially imagine all the people living life in peace. But as reality strikes back, more and more participants “vote with their feet” (Hirschman 1970; Boyd and Richerson 2009b) and migrate to the society

https://doi.org/10.1017/9781108377911.016 Published online by Cambridge University Press

Cultural Evolution

375

with punishment, a form of cultural group selection that favors the spread of groupbeneficial norms (Box 15.2).

15.2.2.2 Demography and Technological Complexity The first people to set foot on Tasmania did so around 35,000 years ago, when it was still a peninsula of Australia. Some 6,000 years ago, rising sea levels separated these first people from their Australian counterparts. And until the late eighteenth century, Tasmanians remained in a state of not-so-splendid isolation (Diamond 1978; Henrich 2004b). At the time of European contact, the differences in technological complexity between Tasmanians and Australians were striking, resulting in stark differences in well-being. Whereas the Australians across the Bass Strait had hundreds of tools, Tasmanians had only a few dozen. And Australian tools were comparatively more complex than Tasmanian tools. Why these dramatic differences despite similar ecologies? Theoretical models point to the importance of demography in the evolution of cumulative culture (Henrich 2004b; Powell et al. 2009). In these models, individuals vary in their skill level (e.g., some make more complex and/or more efficient spears than others). Naïve individuals imitate the most skilled members of their group. Imitation is assumed to be noisy and biased toward relative simplicity, with most imitators ending up with a lower skill level than those they imitate and only a few making improvements. In small populations, the downward force of imperfect imitation dominates, and the population ends up with a low overall level of technological complexity. In large populations, the occasional innovative leap is sufficient to overcome this entropic force, sustaining and even further developing technological complexity, a process analogous to the “ratchet” of innovation and imitation discussed in Box 15.1. Field tests of this hypothesis remain mixed (Collard et al. 2005; Kline and Boyd 2010), and so we turn to an experimental approach. Derex et al. (2013) used a laboratory experiment to test the hypothesis that population size is a key variable in the evolution of cumulative culture. The experiment lasted 15 time periods. In each period, participants chose to build either an arrowhead or a fishing net. Each task required multiple steps. Participants were rewarded based on how closely their efforts matched the optimal design. An optimally designed fishing net yielded a higher reward than an optimally designed arrowhead. However, the optimal fishing net required discovering both the appropriate shape and the order in which to build it, whereas the optimal arrowhead required only discovering the appropriate shape. Designing an efficient arrowhead was far easier than designing an efficient fishing net. Participants interacted in groups of 2 to 16 people. After each period, participants could see everyone’s score. They could then observe the procedure used by one of their group members. The results were consistent with several predictions arising from the hypothesis that population size affects the evolution of cumulative culture. First, across all group sizes, the complex technology was more likely to be lost than the simple technology – no one chose to build a fishing net in later periods. Second, the complex technology persisted longer in larger groups. Third, performance on the complex technology deteriorated in smaller groups, but remained stable in larger groups. These results

https://doi.org/10.1017/9781108377911.016 Published online by Cambridge University Press

376

Karthik Panchanathan

underscore the importance of social dynamics in the cultural evolutionary process. When it comes to cultural adaptation, it is not enough to study how individuals adapt. We must also study how they interact.

15.2.3 Cultural Phylogenetics and History In biological evolution, the effects of various evolutionary forces result in descent with modification. Micro-evolutionary processes give rise to macro-evolutionary patterns. Biologists use various methods to reconstruct these phylogenetic trees. Over the last few decades, anthropologists have borrowed these methods, using patterns of culture to infer the processes shaping cultural evolution (Mace and Pagel 1994; Gray et al. 2007; Currie 2013). Phylogenetic comparative methods allow the analyst to make inferences about the sequence and timing of cultural trait evolution and coevolution. The researcher first constructs a phylogenetic tree that is supposed to reflect the historical relationships between the groups being studied. Most studies have used linguistic features like basic vocabularies. Armed with this linguistically based phylogenetic tree, the analyst can reconstruct a possible history for the cultural trait of interest, such as residence or marriage system, and even test distinct hypotheses for the processes that may have led to the current distribution of traits (e.g., Ross et al. 2016). As with any other statistical technique, care must be taken when interpreting these results in causal terms (Uyeda et al. 2018). In addition, some researchers remain skeptical about the applicability of phylogenetic methods in the domain of cultural evolution given the differences between cultural and genetic transmission (Borgerhoff Mulder et al. 2006; Nunn et al. 2006; Foster and Evans 2019; Evans et al. 2021; Lukas et al. 2021).

15.2.3.1 The Evolution of Political Complexity Anthropology has a long and controversial history of categorizing and sometimes ranking societies based on political complexity (Currie and Mace 2011; Chapter 8). Theorists in the nineteenth century argued for unilineal theories of social evolution, such as Morgan’s (1877) sequence of savagery, barbarism, and civilization, which often ascribed notions of “progress” to the evolutionary process. Subsequent theories, including Service’s (1962) classic model of bands, tribes, chiefdoms, and states, remained evolutionary while abandoning both a unilineal sequence and any notion of progress. But questions remained. Does political evolution proceed in a gradual sequence of incremental increases in complexity or can political evolution happen in jumps – for example, can a tribe-level society transition directly to a state without first passing through a chiefdom stage? Is social evolution a one-way ratchet resulting in ever-greater levels of political complexity or can cultures collapse to lower levels of complexity – for example, can a chiefdom revert to a tribe? Currie et al. (2010) used phylogenetic comparative methods to study the evolution of political complexity among a sample of 84 Austronesian societies, first constructing a phylogeny based on language and then testing different models about how changes in political organization occurred. Their results support a model of social evolution in

https://doi.org/10.1017/9781108377911.016 Published online by Cambridge University Press

Cultural Evolution

377

which changes in political complexity can go in either direction (e.g., tribes can transform into chiefdoms, and chiefdoms can revert to tribes). While transitions in political complexity are bidirectional, the magnitude of these transitions are not equivalent. Increases seem to be incremental, while decreases can be extreme. When it comes to the evolution of political organization, sometimes it is one step forward, two steps back.

15.2.3.2 The Coevolution of Kinship and Subsistence Anthropologists long ago noticed that cultural traits in different domains are not independent but instead co-vary in predictable ways. For example, societies with matrilineal kinship (tracing descent through females) tend to practice horticulture (small-scale, low-intensity farming without the use of the plow or draft animals), whereas societies that make their living through pastoralism (herding large animals) tend to be patrilineal (tracing descent through males). Correlations like these suggest that certain bundles of cultural traits may be adaptive. But simple correlations fall victim to Galton’s problem: Cultures cannot be treated as independent data points as they may share cultural traits because of either convergent evolution (analogy) or common ancestry and proximity (homology). When testing functional hypotheses, we need to isolate analogous traits. For kinship and subsistence, we cannot distinguish between adaptive coevolution and shared ancestry when observing cultural complexes like matrilineal horticulturalists or patrilineal pastoralists. To deal with this problem, Holden and Mace (2003b; but see Surowiec et al. 2019) conducted a phylogenetic analysis of 68 Bantu-speaking societies. They used linguistic data to construct a phylogeny among the sample. Their analysis suggests that the earliest Bantu-speaking populations practiced horticulture. It is not clear whether these populations were predominantly matrilineal or patrilineal. Later, a small fraction of these horticultural societies adopted pastoralism. It seems the cultural complex of matriliny and pastoralism is highly unstable. Matrilineal societies that adopted pastoralism either revert to horticulture (matrilineal horticulturalists) or also adopt patriliny (patrilineal pastoralists). By contrast, the cultural complex of patriliny and pastoralism seems to be highly stable.

15.3

Conclusion This chapter reviewed the theory of cultural evolution and recent empirical studies inspired by this body of theory. The cultural evolution approach argues that humans evolved a dual inheritance system, in which genes and culture both contribute to human adaptation, often working in concert but sometimes in conflict with each other. The field of cultural evolution arose in the wake of sociobiology and developed alongside evolutionary psychology and human behavioral ecology. Like evolutionary psychology, cultural evolution investigates the biological evolution of the psychological capacities underlying culture (Section 15.1). And like human behavioral ecology, cultural evolution studies the factors underlying cultural diversity (Section 15.2). Cultural evolution also studies the ways in which genes and culture influence

https://doi.org/10.1017/9781108377911.016 Published online by Cambridge University Press

378

Karthik Panchanathan

the evolutionary dynamics of each other, an example of niche construction (Section 15.3). While the empirical studies reviewed in this chapter focus on traditional problems in the study of human behavior and evolution, including marriage, reproduction, and cooperation, the reach of the cultural evolutionary framework extends much further, offering an integrative framework to help organize cognitive, behavioral, and social science research. Geneticists have begun to catalog the many ways in which cultural environments shaped genetic evolution (reviewed in Laland et al. 2010; Richerson et al. 2010; Laland 2017). Psychologists have drawn from cultural evolutionary theory in the study of child development and social learning (Wertz and Wynn 2014; Legare and Nielsen 2015). Economists have been inspired by and contributed to cultural group selection and gene-culture coevolution (Bowles and Gintis 2011). Historians have used cultural evolutionary approaches to study the rise and fall of empires (Turchin 2003, 2008). Some have argued that social systems and structures constitute a third system of inheritance in addition to genes and culture (Runciman 2009; Koditschek 2019). Philosophers have begun to incorporate cultural evolution into their political theorizing (Gaus 2021; Sterelny 2021). Cultural evolution has also been applied to epistemology and metascience, offering insights into how we can understand and improve the scientific method (McElreath and Smaldino 2015; Smaldino and McElreath 2016), and sustainability, exploring how multilevel selection might inform socio-ecological interventions (Waring et al. 2015). The subject of this edited volume is human behavioral ecology. How can cultural evolution further contribute to and be informed by human behavioral ecology? Despite shared interests, human behavioral ecology and cultural evolution emerged from different disciplinary backgrounds and employed different methodologies – and so approached research problems in different ways. Emerging from cultural anthropology, human behavioral ecologists tried to make sense of the myriad ways in which populations adapt to their local socioecological conditions. The focus was on testing locally contextualized predictions using ethnographic fieldwork. Emerging from population genetics, cultural evolutionists tried to understand how culture evolves and in what ways is it adaptive. The focus was on building general theory using mathematical models. While these early cultural evolution models were built up from empirical studies of psychology and cultural ecology, they were rarely designed with the purpose of being empirically tested – and so were often of little use to field researchers. But this is all in the past. The lines between cultural evolution and human behavioral ecology – and also evolutionary psychology – are blurring as the disciplines borrow from one another. We are witnessing the birth of an integrated and integrative evolutionary social science. Field researchers have contributed to this integration by studying the ways in which local conditions structure social learning (e.g., Nielsen and Tomaselli 2010; Berl and Hewlett 2015; Kline 2015; Boyette 2016; Garfield et al. 2016; Lew-Levy et al. 2017; Cristia et al. 2019). Advances in statistical methods will become increasingly important in bridging the gap between observational field research and theoretical model building (McElreath 2018). Kandler and

https://doi.org/10.1017/9781108377911.016 Published online by Cambridge University Press

Cultural Evolution

379

Powell (2018), for example, draw from recent advances in population genetics and develop tools to infer the relative magnitudes of different social learning mechanisms using population-level observational data. Theoreticians can also contribute to this integration by developing new models. Early models were intentionally simple and abstract – so that they could address general questions about the cultural evolutionary process. New models should be more complex and tailored to local conditions – so that they might be of more use to field researchers. In addition, cultural evolutionists might reconsider some of their foundational assumptions, especially if they want to bring nonevolutionary social scientists into the fold. Critics of the cultural evolution approach (e.g., Durham 1991; Fracchia and Lewontin 1999; but see Boyd and Richerson 1985) have complained that culture is not just socially transmitted information affecting behavior, but also a system of values and meanings; that individuals cannot easily be categorized into discrete and nonoverlapping groups, but instead are embedded in many different and partially overlapping social networks; that individuals do not have unfettered agency and cannot freely choose whom to imitate or how to behave, but are often influenced, pressured, and coerced through power and ideology. None of these criticisms are damning, but neither are they wrong. Early models of cultural evolution were not built to address these kinds of concerns. As the field has matured, these earlier models have done their jobs, and some may have outlived their usefulness. As scientific knowledge accumulates, we should set aside old models and build new ones.

https://doi.org/10.1017/9781108377911.016 Published online by Cambridge University Press

16 Evolutionary Psychology H. Clark Barrett

16.1

Introduction Can human behavior be explained? It is hard to think of a weightier question, or one with a longer historical pedigree. It is a question that, from a glance at the current state of the life sciences, social sciences, and humanities, seems to remain largely up for grabs. What is certain is that it is a question that must be approached with humility and, barring the appearance of an as-yet-undiscovered Theory of Everything, in a non-totalizing, piecemeal fashion. Many scholars would accept that some aspects of human behavior can be explained, but that explanations must be matched to the phenomena they are after at the proper scale and resolution. Approaches may differ in what aspects of human behavior they are best equipped to explain. On this view, the social sciences can be seen as a patchwork of approaches that roughly but incompletely covers the territory of human behavior often in a somewhat arbitrary way (as seen, for example, in the blurry distinction between sociology and anthropology). This is not necessarily a bad thing, because fields often originate when a community of scholars realizes that there is a theoretical approach that can be used to explain aspects of human behavior and then seeks to apply it. There is no reason to expect different theoretical tools or frameworks to neatly carve up what they are trying to explain in perfectly nonoverlapping ways. The situation in the evolutionary social sciences is no different. Every evolutionist, even the early ones, has realized that a theory that can explain the origin and traits of living thing can also, in principle, explain their behaviors. That is not the question; the question is how. This is where the genealogy of different approaches in the evolutionary social sciences (ESSs) comes in. All are rooted in the idea that long-term historical processes of reproduction over time are “ultimate” or longer-term causes that shape more “proximately” caused phenomena, such as moment-to-moment behavior (a continuum without hard boundaries). Unpacking all the concepts and entailments in that simple construction, however, requires descending into the partially orderly and partially chaotic network of different approaches in ESS. Human behavioral ecology (HBE) is deeply embedded in this network of approaches, and in many ways is the historical progenitor of much of ESS. Here my aim is to describe one other adjacent approach in this network, evolutionary psychology (EP), and to explore its relationship to HBE. I will also briefly mention

https://doi.org/10.1017/9781108377911.017 Published online by Cambridge University Press

Evolutionary Psychology

381

connections to other related approaches including cultural evolution (CE), niche construction, evo-devo, and developmental systems theory. While this review must necessarily be brief, my main goal will be to explore the richness of the theoretical connections between these approaches to human behavior, especially HBE and EP, with an eye toward showing how the strengths of these approaches can be combined synergistically to produce richer, and hopefully more accurate, explanations of human behavior.

16.2

Complementary Approaches Let us begin with brief definitions. Human behavioral ecology is the study of behavior from an evolutionary point of view (Chapter 1). Evolutionary psychology is the study of psychological mechanisms from an evolutionary point of view (Tooby and Cosmides 1992).1 Practitioners of each of these approaches are interested, ultimately, in human behavior. An evolutionary perspective unites them because it is through interactions with the world that “internal” processes, such as thinking and believing, have consequences for survival and reproduction of the organisms that manifest them. And this last insight means that all of these approaches lend themselves to an embodied approach to human behavior, thought, and culture, because the action of bodies in the world is the engine of evolution. Here too we can see how ecology is essential to each of these approaches, since on the broadest possible view “ecology” just means “the world.” Historically, HBE, EP, and CE have often been seen as distinct approaches, and sometimes even at odds with each other (Smith 2000). As we will see, the approaches differ not only in their theoretical commitments and preferences, but also to a considerable degree in the phenomena they choose to study. But we will also see that there is considerable overlap in these fields in their theoretical commitments – most obviously, in the commitment to evolutionary theory as an overarching theoretical framework. When it comes to the interplay between these fields, now, I argue, is a time to be forward-looking and not overly concerned with rehearsing the historical differences between them. While each of these fields is relatively young and started quite small, each has also grown robustly and matured over the past few decades, increasing their theoretical and empirical scopes along the way. A student entering the ESSs now could easily be forgiven for struggling to understand exactly how HBE and EP carve 1

EP and HBE are approaches to the study of human behavior. As argued here, they are mutually compatible and indeed, individual researchers often adopt aspects of more than one of these approaches. For convenience, I will refer to EP and HBE as “fields.” While there are some individual researchers who refer to themselves using these category labels, it is important to keep in mind that these are approaches that can and should be combined. As I suggest at the end of the chapter, I expect and hope that these labels will eventually disappear as the evolutionary social sciences become more integrated and inclusive.

https://doi.org/10.1017/9781108377911.017 Published online by Cambridge University Press

382

H. Clark Barrett

up the theoretical and empirical terrain – because, over time, they have begun to overlap more and more in what they study. This is a good thing. Given that HBE and EP each bring different tools and perspectives to the study of behavior, we can see them as acting synergistically, through specialized division of labor – a collaborative approach to human behavior. Here I will focus my discussion EP and its connections to HBE, highlighting the synergies, both existing and still to be realized, between them.

16.3

Psychological Mechanisms as the Core of Evolutionary Psychology Broadly speaking, evolutionary psychology can be construed as the intersecting set of psychology and evolutionary biology. The EP approach uses evolutionary theory and our knowledge of the evolutionary past to understand the psychologies and psychological traits of humans and other animals. Evolutionary psychologists typically focus on psychological mechanisms, or processes, as evolved traits. Evolutionary thinking helps us to understand and explain traits that are shared across species because of descent from common ancestors (i.e., homologies) as well as traits that are uniquely derived or elaborated within a species or lineage (sometimes called synapomorphies) Thus, EP can ask about aspects of human psychology that are not unique to humans: for example, emotion regulation systems that might be shared (in modified forms) across primates. It can also ask about traits that might be unique or uniquely modified in our species, such as human forms of spoken and gestural language, moral judgment, and cultural learning, to take just a few examples. While many of these phenomena can be described using single words – “language,” “morality” – we do not know, at the outset, if these are biologically real “things,” comprised of their own distinct mechanisms and evolutionary histories, or whether they are products of natural selection. They might be produced by the emergent interactions of many mechanisms, or perhaps reflect cultural categories that do not correspond to biological reality. For this reason, evolutionary psychologists are particularly interested in questions of mental “architecture” (i.e., how the apparently seamless whole of thought and behavior is produced by underlying mechanisms that might have distinct functions and evolutionary histories) (Barrett 2015). The idea of a psychological mechanism thus plays a central role in evolutionary psychological theorizing. Mechanisms that have been shaped by natural selection to carry out functional roles in cognition, otherwise known as psychological adaptations, have been of particular interest. Theorizing about psychological adaptations in EP has made use of a suite of related concepts, including modularity, domain specificity, and computational approaches to cognition. For evolutionary psychologists, psychological mechanisms are a subcategory of biological traits: namely, ones that have evolved because of the roles they play in shaping thinking and behavior. To say that something is a trait, in biology, means that it can be individuated from other traits and, typically, acted upon in at least a semi-independent way by evolutionary processes. This is what the term “modularity” means in the evolutionary developmental biology literature. Modules

https://doi.org/10.1017/9781108377911.017 Published online by Cambridge University Press

Evolutionary Psychology

383

are aspects of the phenotype that can have at least partially separable evolutionary trajectories (Wagner and Altenberg 1996). For evolutionary psychologists, psychological mechanisms have such a modular character: They are distinct traits with distinct evolutionary histories (Barrett 2015). What it means to say that an aspect of the phenotype is a psychological mechanism is to say that it is a trait that plays a particular causal role in shaping behavior. Here is where a computational approach to cognition comes in: Evolutionary psychologists often theorize psychological mechanisms in computational terms, akin to algorithms. Typically, this means that a psychological mechanism takes in information (e.g., from perceptual systems, or other psychological mechanisms), does something with that information (computation), and produces outputs, either in the form of new information, such as a representation (memories, thoughts) or a judgment or decision that directly shapes behavior. It is via these input–output relationships that psychological mechanisms play a causal role in thought and behavior. For example, categorization mechanisms take perceptual input, such as the appearance of someone’s face, and render a category judgment (e.g., who the person is) (Kanwisher 2000). Decision-making mechanisms take in information about a situation and output a decision about how to act based on that information (Dall et al. 2005). In theorizing about psychological adaptations in EP, the notion of domain specificity plays a central role (Box 16.1). In order to carry out their functionally specialized roles, psychological mechanisms typically act on some kinds of information, but not all. A mechanism’s “domain” refers to the range of information that the mechanism has evolved to process (Barrett 2009). Here, analogies can be made to human-made artifacts. For example, the domain of a smoke detector is not the same as the domain of a cash register or a camera. They take in and operate on different kinds of information because they carry out different functions. An analogy can also be made to the body’s organ systems: The kidney and the heart carry out different functions, so they operate on (partly) different physical substrates of the body, and their activities are modulated by different kinds of information. Similarly, the domain of vision is distinct from that of hearing and smell. Evolutionary psychologists, often in dialog with work in neuroscience, posit that there are many specialized mechanisms in our brain–body cognitive system that do different things and use different informational inputs to do so. The mechanisms that cause us to be disgusted by the smell of rotting meat, for example, might use different information than the mechanisms that help us understand the words of our own language. Psychological mechanisms create a possible bridge between EP and HBE because they are the proximate mediators of much (but not all) behavior. For example, there is a rich body of work in HBE on foraging decisions, which began with work in optimal foraging theory that asks how foraging decisions are related to resource distributions (Charnov 1976; Winterhalder 1981). There is a subfield of psychology, judgment and decision-making (JDM), devoted precisely to computational and algorithmic models of decision-making. Bridging the two has led to a fruitful area of research in human cognition, including the discovery of mechanisms for search and decision making

https://doi.org/10.1017/9781108377911.017 Published online by Cambridge University Press

384

H. Clark Barrett

Box 16.1

Domain Specificity

Debates have surrounded the concept of domain specificity as used in evolutionary psychology. Early work in evolutionary psychology suggested that many if not most psychological mechanisms were likely to be specialized to solve specific problems in ancestral environments (Tooby and Cosmides 1992). Here, “domains” are linked to “adaptive problems.” Critics of evolutionary psychology questioned the validity of this assumption, suggesting that many psychological mechanisms were likely to be adapted to solving a wide range of problems, and would thus be better viewed as domain general (Buller 2006). Leaning mechanisms and other mechanisms of plasticity are often invoked as examples of such domain-general mechanisms. I have argued that this reflects a misunderstanding of what the term “domain” means from an evolutionary point of view (Barrett 2015). The domain of an adaptation, such as a psychological mechanism, simply refers to the set of circumstances that shaped it. Thus, every adaptation has a domain: namely, the set of circumstances to which it is adapted (Barrett 2009). Dan Sperber has called this the proper domain of a psychological adaptation – the domain of information it was adapted to use – and distinguishes it from the actual domain of an adaptation, which can include, for example, evolutionarily novel information that an adaptation happens to be able to process by virtue of its design features (Sperber and Hirschfeld 2004) (reminiscent, in some ways, of Gould’s notion of an exaptation; Gould 1991). What constitutes the domain (proper or actual) of a given mechanism is, therefore, an empirical matter. Domains of adaptations might be construed as either broad or narrow, but there are no adaptations that are domain-free, nor are there any that are adapted to all domains. Even very broad learning mechanisms or other mechanisms of plasticity take certain cues or information structures as inputs to their learning algorithms. Thus, claims that an evolutionary psychological approach turns on the overall degree of granularity or domain specificity of the mind misconstrue the concept.

tuned to resource distributions, which can be studied in the lab using experimental psychology methods (Hills et al. 2008; Todd and Hills 2020). Theorizing psychological mechanisms can create synergies between HBE and EP when there is overlap in phenomena of interest, and when the theoretical and empirical tools of each field can be combined to create potentially richer and more fine-grained accounts of the psychological processes generating observed behavior. As mentioned, however, the phenomena of interest to each of these fields only partially overlap, and indeed have sometimes been highly divergent. To understand this, we can look briefly at the histories of these fields, before turning to the question of how greater synergy might be achieved.

https://doi.org/10.1017/9781108377911.017 Published online by Cambridge University Press

Evolutionary Psychology

16.4

385

Histories, Divergences, Reunions Human behavioral ecology and EP were born out of a similar tradition: the “modern synthesis” of Darwinism and genetics of the early-to-mid twentieth century. This perspective began to be applied to the study of behavior by animal ethologists such as Tinbergen and Lorenz, with a distinctly adaptationist approach shaped by scholars such as Williams (1966b). Out of this framework came the early sociobiology of Wilson, Hamilton, Trivers, and others. Features of this tradition include a focus on adaptation by natural selection, cost–benefit analyses, and mathematical approaches derived from economics and demography as the formal tools for theorizing the evolution of behavior. Human behavioral ecology and EP emerged from this tradition and inherited its frameworks, though HBE was historically the first to begin implementing mathematical models of behavior and comparing them to data from humans and other animals – as exemplified by the optimal foraging literature (Chapter 3). In its early days, the founders of EP attempted to explicitly distinguish it from HBE via the putative distinction between “fitness maximization” and “adaptation execution” (Symons 1992). The question here concerned whether organisms’ behavioral decisions might be expected to maximize fitness. Human behavioral ecologists argued that they often should when organisms are in evolutionary equilibrium with their environment (an argument related to the “phenotypic gambit”; Grafen 1984). Evolutionary psychologists argued that behavioral decisions are driven by psychological mechanisms, which must always use proximal cues, because fitness itself is a long-term currency that is opaque to the organism at the time behavioral decisions are made. On this view, adaptations evolve to use cues that have been correlated with fitness over evolutionary time, but these correlations need not hold in any given case. For example, foraging mechanisms might use perceptually available cues such as sweetness or fat content in driving food choice decisions, but the function relating those cues to decisions is shaped over evolutionary (and developmental) time and does not guarantee fitness maximization in any given case (indeed, rapid environmental change can result in adaptive lag or evolutionary “mismatch,” such that reliance on ancestrally valid cues can lead to maladaptive outcomes; Giphart and Van Vugt 2018; Goetz et al. 2019). In the case of perceptual cues for sugar and fats, this can lead to adverse health outcomes when these foods become abundant (Nettle and Bateson 2017). Evolutionary psychologists claimed that the HBE practice of correlating behavioral decisions and outcomes conflated ultimate and proximate causation. Human behavioral ecologists countered that this was a misunderstanding of what they were trying to do. Because fitness is the currency through which adaptations are shaped, it can be informative to examine how decisions are associated with higher or lower fitness outcomes. Moreover, starting with optimization models that assume organisms are maximizing fitness can be a useful empirical approach, because deviations from model predictions can help to falsify or refine hypotheses about the underlying mechanisms shaping behavior (Gluckman and Hanson 2008). The shared theoretical roots of HBE and EP give them much common ground. Three prominent and shared bodies of theory include evolutionary game theory,

https://doi.org/10.1017/9781108377911.017 Published online by Cambridge University Press

386

H. Clark Barrett

parental investment theory, and life history theory (Trivers 1972; Stearns 1976; Maynard Smith 1982). As reviewed in other chapters in this volume, each of these theories has been influential in HBE, shaping entire areas of research. But the footprint of each is also clearly visible in EP.

16.5

Points of Contact

16.5.1 Cooperation One central theme in HBE and EP has been developing and testing evolutionary models of cooperation. All of this work is rooted, historically, in early work on the evolution of cooperation by game theorists such as Maynard Smith, Axelrod, Hamilton, and Trivers (Trivers 1971; Axelrod and Hamilton 1981; Maynard Smith 1982). As described in Chapter 5, this early work used the prisoner’s dilemma as a theoretical cost–benefit framework for understanding cooperation as entailing a conflict between individual and group interests. Direct reciprocity, modeled using the iterated Prisoner’s Dilemma game, became a prominent way of conceptualizing cooperation and was later expanded into new frameworks for explaining cooperation such as tolerated theft, costly signaling, indirect reciprocity, and cultural group selection (Trivers 1971; Blurton Jones 1984; Gintis et al. 2001; Nowak 2006; Boyd and Richerson 2009a). One of the most iconic early studies in EP was Leda Cosmides’ research on cheater detection (Cosmides 1989). This work was an explicit attempt to create a computational model of the psychological mechanisms that underlie direct reciprocity as theorized by Axelrod and Hamilton (1981) and Trivers (1971). As Cosmides and Tooby pointed out, nearly all evolutionary models of behavior, including gametheoretic models of cooperation, either imply or make explicit computational models of the psychological mechanisms underlying them (Cosmides and Tooby 1994). In the iterated Prisoner’s Dilemma game, for example, the “tit-for-tat” (TFT) strategy described by Axelrod and Hamilton implies a psychological mechanism that takes several kinds of information as inputs and uses a decision rule to generate an output in the form of a behavioral decision: cooperate, or defect. Specifically, the TFT mechanism looks at a partner’s last “move” (behavioral decision) in an iterated prisoner’s dilemma and computes whether or not it was cooperative. Cosmides (1989) hypothesized that this computation would involve computing the cost–benefit outcome to the other player of their prior choice, including whether they had paid a cost or met an obligation in order to receive a benefit. In the iterated prisoner’s dilemma framework, cheating means benefiting at the other player’s expense, so Cosmides called her proposed psychological mechanism a “cheater detection” mechanism and hypothesized that such a mechanism is part of human evolved psychology, having evolved because of its benefits in stabilizing cooperation via reciprocal altruism. Cosmides developed an experimental paradigm for testing the cheater detection hypothesis, using a reasoning task from experimental psychology known as the Wason Selection Task (see Box 16.2). Her initial lab studies using this task launched

https://doi.org/10.1017/9781108377911.017 Published online by Cambridge University Press

Evolutionary Psychology

Box 16.2

387

The Wason Selection Task as an Experimental Measure of Cheater Detection

To examine the hypothesis that there are psychological mechanisms for detecting cheaters, Cosmides (1989) adapted the Wason Selection Task. Groups of undergraduate students were presented with different sets of four doublesided cards and instructed to confirm that the cards adhere to different rules. In one task, for example, participants were asked to imagine that they are responsible for enforcing the unfamiliar social rule: “If a man eats cassava root, then he must have a tattoo on his face.” One side of the card showed what food the person is consuming, and the other side of the card showed information about the presence of a face tattoo: eating cassava

eating meat

has a face tattoo

does not have a face tattoo

Approximately 70% of the participants correctly selected “eating cassava” and “does not have a face tattoo” as the scenarios that need to be checked to confirm that the rule is being followed. Another task, by contrast, required participants to check adherence to a clerical rule, such as: “If the person has a ‘D’ rating, then his documents must be marked with a ‘3’ code.” One side of the card showed the rating, either “D” or “F,” and the other side of the card showed one of two numerical codes, either “3” or “7.” Participants were asked to indicate which cards require examination of both sides to confirm that the rule is being followed: D

F

3

7

In this case, only 25–30% of the participants correctly selected “D” and “7” as the cards that need to be examined. The difference is noteworthy because both tasks require similar logic. That is, both tasks entail an antecedent, denoted as P or not-P, and a consequent, denoted as Q or not-Q: P

not P

Q

not Q

To examine whether the rule is being followed, the participants must examine P and not-Q. Participants implemented this logic more successfully when the task was framed as a potential violation of a social contract. Cosmides interpreted this as evidence for a psychological mechanism that has evolved to facilitate the detection of cheaters.

https://doi.org/10.1017/9781108377911.017 Published online by Cambridge University Press

388

H. Clark Barrett

an enormous experimental literature, which included competing computational models such as Cheng and Holyoak’s (1985) pragmatic reasoning schema theory model and Sperber et al.’s (1995) relevance theory model, as well as cross-cultural and conceptual replications (Sugiyama et al. 2002). It also spawned extensions into other psychological domains, such as “precaution detection” regarding hazards (Fiddick et al. 2000). The original model has fared reasonably well, though there remains debate about whether an evolved cheater detection mechanism is the best explanation for experimental findings using the Wason task (Cheng and Holyoak 1985; Sperber et al. 1995). Regardless of how this debate turns out, Cosmides’ work is a useful example of how an EP approach can be used to generate computational models and lab and fieldbased experiments that can complement HBE observational approaches to cooperation. Human behavioral ecology researchers have used observational data to ask whether theoretical frameworks such as reciprocal altruism can explain human cooperation, and they have asked which of the available theoretical mechanisms of cooperation best explain the observational data, such as data on sharing of food and other resources (Gurven 2004; Chapter 5).

16.5.2 Parental Investment Theory Because all mammals reproduce sexually and reproduction is the currency of fitness, there has been great interest in sexual and reproductive behavior and psychology in HBE and EP. Darwin’s theory of sexual selection is the most widely applied framework for understanding sex differences in behavior related to reproduction. Human behavioral ecology and EP have historically all drawn from one particular framework for theorizing sexual selection, Trivers’ parental investment theory (Trivers 1972). According to this framework, sexes within a species can vary in amounts of “resources” (time, energy, physiological processes) devoted to different aspects of reproduction. Parental investment theory proposes that organisms face a trade-off between mating effort and parenting effort, where parenting effort refers to resources invested in raising existing offspring and mating effort refers to resources devoted to additional mating in order to produce new offspring. In Trivers’ framework, mating effort and parenting effort are in direct conflict and cannot be simultaneously maximized. Notably, while HBE and EP share this framework as common ground, the fields have tended to focus on different facets of the reproductive process addressed by parental investment theory. While EP has focused on mating and mate choice, HBE has focused on marriage, parenting, and the family (Buss 1989; Lawson and Mace 2011; Gray and Anderson 2012). While some of this difference may be historical accident or a “founder effect” due to research choices of early practitioners in each field, some of the difference may relate to where the theories and tools of each focus offer the richest theoretical and empirical traction. Because human behavioral ecologists tend to work in field settings, they have access to people of all ages and the

https://doi.org/10.1017/9781108377911.017 Published online by Cambridge University Press

Evolutionary Psychology

389

capacity to observe entire families and behavior in the home and daily life. Human behavioral ecologists have also tended to work in communities with large, coresiding families, and multigenerational childcare, allowing rich datasets on parental and alloparental care to be obtained observationally (Chapter 12). Evolutionary psychologists, in contrast, have tended to work in lab settings with college student populations who often do not yet have families, making mate choice a more tractable phenomenon. While some early high-profile EP work on mate choice was crosscultural, it still tended to focus on college student populations, with all of the caveats about treating these populations as representative of typical human mate choice (Buss 1989; Goetz et al. 2019). The use of experimental approaches for studying the psychology of mating, as well as parenting, can have both advantages and disadvantages. The use of hypotheticals (e.g., vignettes, trait rankings) comes with costs – for example, participants’ responses are unconstrained by the same incentive structures as in real life. Such methods do, on the other hand, allow for the exploration of psychological phenomena that can be difficult to observe in real life, such as judgments about rare events. They also increase observational power by allowing researchers to ask individuals about multiple possible situations, not just the one they happen to find themselves in. For that reason, HBE researchers have increasingly borrowed experimental techniques from EP, such as hypothetical vignettes about mating and parenting decisions (Scelza and Prall 2018). Where synergy has occurred is in the use of shared theoretical frameworks, such as parental investment theory, to derive and test hypotheses about the psychological mechanisms underlying mating and parenting behavior. Where this has been perhaps most obvious is in the study of sex differences. Parental investment theory has been taken to predict both “main effects” in sex differences – that is, cross-cultural similarities in sex differences between men and women – as well as aspects of sex differences that might vary across cultures or individuals as a function of ecological and social variables (i.e., interaction effects). In this synergistic mode, HBE researchers have taken materials from experimental EP and transported them across cultures, adding ecological covariates to test for variation predicted by parental investment theory. As seen in Chapter 9, for example, Scelza and colleagues have replicated the main effect of male/female differences in jealousy, originally found by Buss (1989), across cultures (Scelza et al. 2020c). They have also shown, however, that the size of this sex difference correlates with the average degree of paternal investment in children in the local community. Similarly, HBE and CE theory has been used to explain variation in parenting behavior as a function of cultural and ecological factors (Sear 2016). In the domain of reproduction, then, parental investment theory provides a shared framework that can be used to bridge EP and HBE approaches. We should be mindful, however, that to the extent that parental investment theory creates a shared framework for understanding aspects of human reproductive psychology and behavior, it may also bias our research in shared ways as well (Barrett 2020a). As is the case in

https://doi.org/10.1017/9781108377911.017 Published online by Cambridge University Press

390

H. Clark Barrett

other domains of evolutionary thinking, we must remain alert to the possibility that the ways that our fields have historically chosen to frame questions might not be the only ways of doing so.

16.5.3 Life History Theory Like parental investment theory, life history theory focuses on the limited biological resources of organisms and the trade-offs that those limits entail. It is another example of the trade-offs approach that has been so influential in evolutionary approaches to human behavior. “Life history” refers to how biological events and processes are spaced across the life span, including the timing of maturity, birth spacing, and death (Chapter 2). The key idea is that organisms face trade-offs in the patterning of these events, and natural selection shapes life history “strategies” over time to optimize these trade-offs. An ideal organism from a fitness perspective would be one that reaches reproductive maturity immediately, reproduces at the maximum possible rate, and lives forever; the impossibility of this illustrates what are called life history trade-offs. For example, because reproduction requires allocation of resources (mating effort and parenting effort, according to parental investment theory), reproducing more comes with the expense of a shorter life span. And reaching reproductive maturity sooner rather than later also has its costs because processes of development must be sped up, which has costs, such as the loss of opportunities to learn and practice skills. Biologists in the mid-twentieth century began to model these trade-offs mathematically, and these models were imported into HBE and later EP in an effort to understand both unique aspects of human life histories and those that are shared with other species (Stearns 1976; Hill 1993; Del Giudice et al. 2016). This has led to a large and fruitful area of research in HBE, using life history data from contemporary humans to test hypotheses about uniquely human life history traits and how they might explain aspects of our success as a species and why we differ from closely related species of primates (Chapter 2). For example, the influential “grandmother hypothesis” posits that overlapping generations of parental care, particularly from grandmothers, have been a key factor enabling human longevity as well as our reliance on, and the benefits derived from, cultural transmission of knowledge and skills across generations (Hawkes et al. 1998). Relatedly, human behavioral ecologists have tested a variety of hypotheses to account for the extended childhood period of humans, compared to closely related primates. Are our prolonged childhoods merely a byproduct of our extended life spans, or do we wait to reach maturity because of the benefits that come from an extended period of learning and plasticity, at the expense of dependence on others and delayed reproduction (Bogin 1997)? There are many questions here too of relevance to EP, and life history theory has become increasingly influential in EP research. Perhaps the most prominent thread of life history theory research in EP examines the “fast/slow” life history continuum (Belsky et al. 2012). Here the hypothesis is that developmental mechanisms can regulate the “speed” of development in response to environmental and social cues,

https://doi.org/10.1017/9781108377911.017 Published online by Cambridge University Press

Evolutionary Psychology

391

thereby coordinating the development of a variety of traits. The central idea is that in “harsh” environments that increase mortality, it is adaptive to “speed up” the life course in order to maximize fitness – and, especially, reproduction – within the constraints of a shorter expected life span. This acceleration entails trade-offs. For example, to the extent that prolonged juvenile (pre-reproductive) periods in humans confer benefits in the form of extended periods of plasticity, learning, and preparation for adulthood, these must be cut short if development is sped up to allow reproduction to occur earlier (Del Giudice et al. 2016; Frankenhuis and Nettle 2020). Psychologically, the fast-slow developmental mechanism has been proposed to be calibrated by cues to environmental harshness, including social cues such as the absence of a father figure (Belsky et al. 1991). The outputs of this developmental mechanism include the tuning of various psychological traits, such as risk-taking, future discounting, and sociosexual orientation. Evolutionary psychologists have sought to study these traits using a variety of data and techniques including demographic data, surveys, and experimental tasks that examine correlations between aspects of childhood environment and adult psychology, such as risk taking and future discounting (Lee et al. 2018). In HBE, researchers have looked for correlations between environmental variables, such as “father absence,” and measures of the speed of development such as age at puberty – with results increasingly challenging earlier models (Sear et al. 2019). While this has been a productive area of research and one that has involved substantial synergy between HBE and EP, there are again reasons to be mindful of other theoretical possibilities beyond life history theory for explaining the phenomena at hand. Biologists have pointed out that some aspects of the fast-slow framework as a within-species developmental mechanism may be insufficiently theorized, given that the fast-slow continuum in biology was originally conceptualized as a cross-taxon continuum, developed to explain why some species have extended life history trajectories relative to others (Jeschke and Kokko 2009; Zietsch and Sidari 2019; Galipaud and Kokko 2020; Stearns and Rodrigues 2020). There is also the important possibility that some of the correlations observed in fast-slow life history research in EP and HBE, such as correlations between early life adversity and adult psychological traits such as risk taking, future discounting, and sociosexuality, may be produced by mechanisms other than a biologically evolved facultative developmental mechanism. Poverty, for example, may influence these traits through learning and cultural transmission independent of a biological developmental mechanism. Troublingly, some of the predictions of a strictly learning or experience-based model would be exactly the same as a life history model – for example, that people raised in poverty and faced with high mortality risk and great uncertainty about the future might be less inclined to save resources for later in life (Lee et al. 2018). Sear has challenged the construct of human life history strategies, asking whether we might have rushed too quickly to see human life history traits as “strategic” in the evolutionary sense and whether we understand the underlying trade-offs well enough to test hypotheses about optimality (Sear 2020; see also Box 13.1). She urges caution in using the explicitly adaptationist language of life history theory strategies.

https://doi.org/10.1017/9781108377911.017 Published online by Cambridge University Press

392

H. Clark Barrett

It is important to establish a firm empirical grasp of underlying trade-offs in human life history and their relationships to the evolutionary past before concluding that behavioral responses to environmental cues reflect evolved reaction norms. Here again we see that the shared theoretical backgrounds and commitments of HBE and EP lead to great potential synergies, but they may also expose the two fields to the same kinds of biases in how to theorize problems. This speaks in favor of not just intersecting these approaches, but also drawing in theory and perspectives from outside them as well.

16.6

A Case of Synergy: Foraging Cognition It is not just shared theoretical background that creates possibilities for synergies between HBE and EP. The strengths of combining these approaches have proven particularly fruitful for investigating certain kinds of phenomena where cognition and ecology interact, and where a combination of theory and methods can be used to gain insights that neither approach alone would necessarily yield. One example, introduced previously, is the study of foraging cognition and its application to diverse cases of resource search. Here it has proven useful to expand our notion of what “foraging” means, and to decouple it from specific resources for which humans might have foraged in ancestral environments, such as animals and plants. Indeed, classic models in the ecological literature on foraging, such as Charnov’s marginal value theorem, are not specific to particular resources at all, but rather to what is sometimes called environment structure (Charnov 1976; Pleskac and Hertwig 2014). Charnov’s model describes a psychological decision rule for “patch leaving” that depends only on several informational parameters: the value of particular resources (ultimately, their fitness value, but typically in HBE and EP modeled as proximally available values such as caloric value or subjective “utility”), how those resources are distributed in space (e.g., in patches), and the time investments to process those resources and to travel between them. In this case, there is a very good fit between the HBE focus on environment structure and the EP focus on computational descriptions of psychological mechanisms driving behavioral decisions. Charnov’s model is, or can be construed as, just such a computational model: It specifies informational inputs, a decision policy, and behavioral outputs (e.g., a decision about whether to stay in a resource patch or leave, as a function of the dynamically changing values of the parameters described previously). Human behavioral ecology work has used observational data from people foraging for food resources to test the predictions of Charnov’s model (Chapter 3). Importantly, Charnov’s model does not predict which cues of resource value organisms will use, nor how organisms subjectively estimate things like the spatial distributions of resources (which, in turn, imply their own psychological processes). Human behavioral ecology researchers have noted that caloric estimates of food value might not be the same as the cues that foragers themselves were using (e.g., they could be using specific combinations of nutrients as cues), which would inevitably lead to differences between observations and what the model predicts

https://doi.org/10.1017/9781108377911.017 Published online by Cambridge University Press

Evolutionary Psychology

393

(Smith 1991). Given enough data, of course, this provides an opportunity to test hypotheses about the proximal cues that foragers are using. Evolutionary psychologists realized that ecological foraging theory has potential implications far beyond foraging for food resources. Indeed, if foraging is construed as search, people search for an enormous variety of things: friends, romantic partners, jobs, homes, information, entertainment. Each of these things, in turn, has an environment structure, and associated search and processing costs. We may spend some time searching for a new “patch” – for example, a TV series – and then spend some time in that patch assessing the density of its resource “value” before deciding whether to stay in the patch or leave. Evolutionary psychologists have studied the psychology of search in a variety of domains, including mate search and information search in online environments, and have found that peoples’ search behaviors and decisions can be predicted by a Charnov-style patch leaving model (Hills et al. 2008, 2012; Barrett 2018; Todd and Hills 2020). Indeed, work in this area suggests that human psychology may be influenced by environment structure in deeper ways than we are inclined to think. Some wellknown and pervasive biases in human judgment and decision making, including ones that might influence large swaths of our personal lives, may result from assumptions about environment structure that evolution has built into our brains and bodies at an implicit (unconscious) level. One of these implicit assumptions is that things in the world are not evenly distributed, but rather come in clumps – a foundational assumption of the marginal value theorem. Wilke and Barrett suggested that the so-called “hot hand” phenomenon, in which people base predictions about upcoming events on events they have just observed, may be rooted in just such an implicit assumption about the patchy distribution of resources and events in space and time (Wilke and Barrett 2009). Using experimental tasks administered in several cultural settings, they found that peoples’ predictions of future events, such as coin tosses, are highly autocorrelated with what they just observed, consistent with an implicit expectation that resources are clumped. Moreover, this judgment pattern is extremely difficult to eradicate or reverse, even for things that do not come in clumps – such as coin tosses. The effect is found in nonhuman primates, suggesting it may be ancient and phylogenetically widespread (Blanchard et al. 2014). The magnitude of hot hand is not identical across people and contexts – for example, it appears to be exaggerated in people at risk for gambling disorders – but it appears to be a deep-seated intuition that is not the product of conscious reflection (Wilke et al. 2014). Indeed, mathematical estimates of environmental clumpiness suggest that many, perhaps most, “resources” on which humans rely are indeed clumped (Wilke et al. 2018). This may be an example of an “ecologically rational” expectation (Pleskac and Hertwig 2014) that evolution has built into the decision-making systems of humans and other primates, and that appeared irrational to psychologists who first discovered that it was applied to seemingly non-clumped events like basketball free throws and coin tosses (Gilovich et al. 1985). This example carries several lessons for synergies between EP and HBE. One lesson is that when the theoretical constructs of these fields are properly aligned, translating

https://doi.org/10.1017/9781108377911.017 Published online by Cambridge University Press

394

H. Clark Barrett

between their frameworks is relatively straightforward. Human behavioral ecology theory often deals in “currencies” that can easily be imported into a psychological context, allowing observational and experimental research to align, as in this case, and allowing the approaches to complement each other – observational work allowing greater ecological validity, and experimental work allowing greater experimental control. This translational synergy can be particularly fruitful in cases where the parameters of the ecological model are directly psychological, as in optimal foraging theory and the earlier reviewed case of psychological rules for cooperation. However, care must be taken when the parameters of an ecological model are not directly psychological. For example, evolutionary psychologists have arguably rushed to turn the predictions of life history theory into theories of psychological mechanisms, when much of the original framework concerned nonpsychological processes like the timing of puberty and other physiological events. Time will tell if these translations will prove successful, but a general point is that care should be taken to ensure that hypotheses about psychological mechanisms are properly matched to the underlying processes being theorized. Another lesson from work on foraging cognition is that evolutionary theory applies not just to past but also to present conditions, and not just via “mismatch.” While it must be true that cognitive mechanisms have been shaped over evolutionary time, this does not mean that they are stuck in the past or are inflexibly tied to the minutiae of ancestral contexts. It is true that when hot hand intuitions are applied to coin tosses or slot machines, there is a form of mismatch – sometimes, perhaps, by design, as when games of chance are designed to exploit our patch-based intuitions about being on a “lucky streak.” But if many contemporary resources are, in fact, clumpily distributed, a hot hand intuition may be ecologically rational, just as HBE would predict (Wilke et al. 2018). Moreover, this example shows that psychological mechanisms need not be shackled to some ancestral past. We deploy patch-based psychology when at the supermarket, the stock market, and searching for information online, not just when searching for berries and squirrels (Hills et al. 2008). Deep and unproductive misunderstandings of EP have come from overly narrow construals of what “domain specificity” means, and the mistaken assumption that “flexibility” can emerge only from “general purpose” mechanisms (Barrett 2015). Here, we have robust evidence for foraging mechanisms that are domain-specific – tied to specific environment structures and decision tasks – and probably evolutionarily ancient, and yet are deployed widely, wherever their domain criteria are met. An interesting question, however, concerns the degree to which psychological propensities such as hot hand might influence decision-making non-adaptively, and to what degree they might shape contemporary environments. For example, work on hot hand in gamblers hints that it could influence decision making in markets, leading to “bubbles” (Johnson and Tellis 2005; Wilke et al. 2014). Finally, this example shows the importance of comparative research for EP and HBE. Comparative research includes cross-cultural work (discussed in more detail in the next section), but also cross-species comparisons. While hot hand has been

https://doi.org/10.1017/9781108377911.017 Published online by Cambridge University Press

Evolutionary Psychology

395

studied in relatively few species, the demonstration that it is found in macaques is a key finding that suggests a long phylogenetic history of the underlying mechanism (Blanchard et al. 2014). Given that distribution-related foraging decisions have been documented in a wide variety of taxa, it is plausible that psychological phenomena such as hot hand will be found widely as well (Dall et al. 2005). More generally, taxonomic comparisons are necessary for demonstrating evolutionary homologies, which are an important source of evidence for the deep phylogenetic roots of some traits. They can also be used to show cases of convergent evolution, which add to the evidence that a particular feature of human psychology or behavior evolved due to specific ecological conditions – which has proven important in the study of the evolution of social cognition and social learning (Emery and Clayton 2009). Crossspecies comparisons are thus an important, and often overlooked source of evidence for the evolutionary roots of human traits in EP and HBE alike.

16.7

Looking Forward The potential synergies between EP and HBE will continue to increase, not decrease, as the scope of our theories is expanded, and as we expand the scope of who does the research, whom we choose to study, what questions and phenomena we investigate, and the methods we use to do so. Here I will consider possible new directions for synergistic work and offer some suggestions for best practices and areas for possible expansion and improvement going forward.

16.7.1 Theoretical Innovation Evolutionary psychology and HBE can benefit from expanding their theoretical toolkits beyond their common ground in modern synthesis style approaches to evolution, and each field has begun to do so. Notably, the so-called “extended synthesis,” extending evolutionary theory beyond the original framing of the modern synthesis, offers conceptual resources that can increase the theoretical common ground of all approaches in the evolutionary social sciences (Pigliucci and Muller 2010; Jablonka and Lamb 2014; Laland et al. 2015). The concept of niche construction provides great promise for understanding the mutual co-constitution of organisms and their environments (Laland et al. 2000; Odling-Smee et al. 2003). Advocates of this approach have argued persuasively that niche construction goes beyond the “dual inheritance” frameworks that have been popular in CE and, to some degree, EP. First, niche construction embraces what has sometimes been called “inclusive inheritance:” the idea that traits are inherited not just via the dual pathways of genetic and cultural transmission, but also via extragenomic somatic mechanisms such as epigenetics, and even extra-organismal mechanisms such as environmental transmission (Jablonka and Lamb 2014; Laland et al. 2015). Relatedly, the niche construction approach breaks down the strict delineation between organisms and their environments to focus on their mutual co-constitution.

https://doi.org/10.1017/9781108377911.017 Published online by Cambridge University Press

396

H. Clark Barrett

A productive example is human influence over the food environment, via agriculture and other pre-agricultural forms of environmental modification. These in turn feed back on human bodies, development, and in the long term, evolution. Importantly, there are processes of “transmission” or causal influence here that transcend genes and minds, since food is the very stuff of which bodies are built. Because of deep causal entanglement between bodies, plants, animals, soil, climate, technologies, the microbiome, and more, we cannot just think of genes and bodies simply “adapting to” the environment, nor of the “environment” as simply responding to human agency. All are equal partners in the causal feedback loop of evolution. Earlier approaches such as the extended phenotype (Dawkins 1982) and culture-gene coevolution (Boyd and Richerson 1985) partly capture this dynamic, but partition the loci of causation differently than niche construction theory does. Adopting a more network-like view of evolutionary causation, rather than partitioning out and focusing just on the individual organism (or even more narrowly, just its genes, mind, or physiology) arguably brings a broader range of phenomena under the theoretical lens. Work at the HBE/EP interface could benefit from such an approach. This is especially the case as both fields grapple with how to properly theorize psychology and behavior in a post-industrial, globalized world saturated with human technology and human-induced environmental change. An evolutionary science of the “anthropocene,” situating humans within rapid global physical change, may require expansion beyond a traditional Darwinian modern synthesis perspective in order to grapple with the complex causal entanglements of world-shaping historical processes (Steffen et al. 2015). Some constructs that are currently popular in EP and HBE, such as market integration, likely vastly oversimplify and undertheorize how such global changes are restructuring human environments, bodies, brains, and behavior. Other constructs, such as “WEIRD,” are similarly beginning to come under scrutiny for oversimplifying processes entangled with colonialism and the global spread and influence of capitalism (Clancy and Davis 2019). Arguably, both constructs tend to neglect the causal role of environments in restructuring human psychology and behavior and vice-versa, focusing instead on cultural, economic, and psychological influences on culture change. To take another example from the previous discussion of foraging cognition, a niche construction approach might help us to theorize how human choices in navigating environments might be reciprocally influenced by the effects those choices have on the environment itself. In some online environments, peoples’ information foraging behavior shapes the environment itself through algorithms and filters that feed people new information, similar to what they sought previously. This is a kind of hot hand effect that creates autocorrelated informational environments, sometimes known as informational “bubbles” or “echo chambers” – a perfect example of niche construction (Del Vicario et al. 2016; Flaxman et al. 2016). A similar phenomenon may occur in markets, such as housing markets or stock markets, where hot hand psychology can lead to self-feeding pile-ons that drive prices ever-higher – another case of psychology shaping the environment and

https://doi.org/10.1017/9781108377911.017 Published online by Cambridge University Press

Evolutionary Psychology

397

vice-versa, in an entangled loop (Camerer 1989; Johnson and Tellis 2005). Here, a niche construction approach that integrates EP and HBE could be a powerful tool for understanding pressing contemporary phenomena. Another powerful tool in the extended synthesis toolkit is the evo-devo approach to evolutionary change (Jablonka and Lamb 2014; Barrett 2015). This approach views evolution as primarily occurring via modifications to developmental systems (Oyama et al. 2001). While it might seem like there is nothing particularly new or in conflict with the modern synthesis in this approach, it has revolutionized some areas of biology by shifting the causal focus away from a purely gene-centered view of evolution. It also stands in contrast to the phenotypic gambit in which natural selection is modeled as acting directly on developed phenotypes rather than on the developmental processes that build them (Grafen 1984). A phenotypic gambit approach can capture only the constraints built into cost–benefit trade-offs at the phenotypic level, but the gambit treats the directions that evolution can go as more or less flat, governed only by these phenotypic costs/benefit trade-offs (e.g., between mating and parenting effort, or between individual and social learning). In reality, of course, evolution is a path-dependent process, and path dependency is the bread and butter of an evo-devo approach. For EP, taking path dependence into account is vitally important for understanding, for example, the evolution of human brain structures and the cognitive mechanisms they instantiate (Barrett 2015). These are modified versions of brain structures present in the last common ancestor of humans and other apes, and it would be absurd to try to understand them as simply optimal solutions to evolutionary cost–benefit trade-off scenarios. Instead, when we try to understand the evolution of human cognitive capacities such as theory of mind, language, cooperation, and morality, we must understand them as enabled by developmental modifications to brain structures with homologs in closely related species. Phenomena that have traditionally been of interest in HBE, such as parenting, cooperation, and the human life span, may benefit from a similar evo-devo style approach – and indeed many human behavioral ecologists explicitly situate human traits such as life history traits as modified versions of those seen in other apes (Chapter 2). However, explicitly theorizing the cognitive mechanisms underlying the psychologies of parenting and cooperation (to give two examples), and how these evolved through modifications of brain mechanisms present in ancestral apes and even more distant mammalian ancestors, is likely to add explanatory power beyond just thinking of these mechanisms as solutions to phenotypic cost–benefit trade-offs. Expanding theory in this way can open up entirely new questions for investigation at the intersection of EP and HBE: for example, how human-induced climate change, infrastructural change, and global expansion have both been enabled by and feed back upon human bodies, psychology, and behavior. But increasing our theoretical breadth may also provide new angles on older debates in these fields. For example, a niche construction approach to the grandmother hypothesis debate, or an evo-devo take on how cooperation develops in childhood, could provide new insight into these problems, beyond strictly modern synthesis style approaches.

https://doi.org/10.1017/9781108377911.017 Published online by Cambridge University Press

398

H. Clark Barrett

16.7.2 The People We Study In addition to theory, research in both EP and HBE rests on multiple empirical foundations: the people we study, who does the research, the phenomena we choose to examine, and the methods we use to do so. Human behavioral ecology – and EP – can benefit from expansion and innovation in all of these areas (Nzinga et al. 2018; Pollet and Saxton 2019; Barrett 2020a, 2022). Calls for expanding the diversity of research participants have arguably been more urgent for EP than HBE, given that HBE has always been fieldwork based, and classic EP work has tended to follow the experimental psychology custom of recruiting college students for research and testing them in the lab (and more recently, online). Thus, the now-classic WEIRD paper, with its enumeration of the unusual features of the cultures that college students tend to represent, was more relevant for EP (Henrich et al. 2010). However, given that the explanatory target of both EP and HBE is humans writ large, there is still much room for improvement in both fields (Barrett 2020b). A problem facing both fields is what I have called the problem of the “missing middle” (Barrett 2020a). Work in both EP and HBE is bimodally distributed, with one mode of research occurring in urban-dwelling majority populations, largely in the global north, and another mode of research occurring in what are sometimes called traditional, or small-scale, societies largely in the global south – often the preferred sites for HBE research. There are several possible reasons for this prioritization of small-scale communities. One is that the WEIRD concept has prompted researchers to prioritize work in communities that were seen as maximally non-WEIRD, or “antiWEIRD.” Another is the pursuit of what I have called the “ancestral gambit”: the idea that some contemporary communities are proxies for ancestral lifeways (Barrett 2022; Chapter 1). This is a problematic assumption in many ways. Not only does it do harm to people in these communities via misrepresentation, it also likely leads to a variety of scientific errors because the actual match between contemporary and ancestral conditions is often unknown. What is certain is that all contemporary humans are equal products of the evolutionary process, and therefore every one of us provides evidence of how the developmental systems that build our bodies and minds respond to the circumstances in which we grow up – the “reaction norm” of human development (Barrett 2015). Seeing all human beings as coeval exemplars of how the evolutionary process has shaped us greatly expands the scope of communities that are relevant for investigating evolutionary questions, to cover the entire world. To date, we have no idea of how much the bimodal focus on urban global north populations and small-scale global south populations has limited our view of human plasticity and human variation.

16.7.3 Who Does the Research As important in the scientific process as where the data comes from is who asks the questions, and what kinds of questions they ask (Nzinga et al. 2018; Roberts et al. 2020; Barrett 2022). Until recently, this side of the scientific question has been largely

https://doi.org/10.1017/9781108377911.017 Published online by Cambridge University Press

Evolutionary Psychology

399

invisible, because ESS researchers tend to come overwhelmingly from privileged majority cultures in the global north – a category that is invisible by being unmarked. Much work in metascience has asked how point of view and positionality influence what questions we ask, and therefore, what we see. Race, gender, class, education, and politics are all aspects of identity that are likely to influence what kinds of questions a researcher considers important, and even what kinds of questions occur to them. Just as for the problem of the missing middle, skewed representation in the research community is likely to have led to a skewed view of human nature, in currently unknown ways. In psychology, one can see many ways in which conceptual structures of the European academy are projected onto “human nature,” much in the way that statistical tools become models of thought itself (Gigerenzer 1991). To take just one example, some evolutionary psychologists have suggested that mind–body dualism – a popular stance in much European philosophy and psychology – is a human universal, though the few existing cross-cultural studies provide mixed evidence, and embodied notions of mind are common in many Indigenous societies (Bloom 2007; Chudek et al. 2018; Berent 2020; Barrett et al. 2021). Sometimes, projections of European concepts and values onto the rest of the world can do harm. For example, many academic theories import culturally laden assumptions about what forms of cognition and behavior are most “rational” or ideal, creating seeming “deficits” in people who do not seem to embody them (Adams et al. 2015). The literature on “intelligence,” with culturally and ideologically laden constructs such as “IQ,” illustrates the perils of cultural bias in the construction of theory and empirics (Lewontin 1970a; Croizet 2012; Gillborn 2016). Scientific mistakes may arise when category distinctions and ontological commitments are baked into the theories themselves, and therefore, the methods and research designs used to test them. Given that much work in HBE and EP is done in Indigenous communities, Indigenous researchers and ideas have great potential to increase discovery by relaxing, challenging, or discarding hidden or entrenched assumptions that underlie most research in the field. To take one aforementioned example, niche construction theory rejects the strict delineation between organism and environment that has been the bread and butter of evolutionary theory since Darwin – a move considered radical by some, and that came only at the very end of the twentieth century (Laland et al. 2015). Many Indigenous people, on the other hand, have long conceptualized humans as part of and not separate from the natural environment, with each shaping and domesticating the other (Anderson 2005). It is arguably because of the strict European dichotomy between “man” and “nature” that it took so long for the academy to entertain this view, which is proving to be the more biologically realistic one.

16.7.4 Phenomena Finally, new synergies between HBE and EP may be achieved by expanding the scope of phenomena we examine. Just as we can and should see all humans as products of the evolutionary process, so should we see all human activities. Because evolutionary

https://doi.org/10.1017/9781108377911.017 Published online by Cambridge University Press

400

H. Clark Barrett

processes often occur over very long timescales and there is a tendency to associate evolution with prehistory, there is a tendency to want to separate out “modern” from “premodern” phenomena, and to focus evolutionary research on the latter: for example, foraging, reproduction. This is a mistake, because the same bodies and minds that make foraging and parenting decisions also make decisions about all aspects of life in the contemporary world. Because so much research effort has been dedicated to ancestral-seeming activities, the ESSs are far behind in theorizing how evolved minds and bodies generate and are entangled in contemporary and rapidly changing local and global phenomena. As mentioned, evolutionary thinking might bring unique insight to phenomena such as climate change and change associated with massive human population growth and technological change more generally (Jones et al. 2021a; Pisor and Jones 2021). Arguably many such changes are occurring because of evolved human motivations such as motivations to reproduce, to seek social success, and to benefit one’s ingroup. Human behavioral ecology and EP are well-suited to theorize these phenomena and how they interact with ecology and environment, including the amplifying effects enabled by increased political power and resource extraction potential. While some have pointed to uniquely evolved human traits as the secret of our success, these same traits are also responsible for the dark sides of human global expansion, including the group dynamics and competitiveness underlying processes of oppression, inequality, colonialism, and resource extraction (Steffen et al. 2015; Piketty 2017). Some research in HBE and EP has begun to explore such phenomena, such as work on inequality (Borgerhoff Mulder et al. 2009; Colleran et al. 2015) and the origins of coalitional psychology and political factionalism (Flinn et al. 2005; Petersen et al. 2013). Going forward, combined approaches from HBE, EP, and niche construction can help us to understand how evolution, mind, bodies, and environment interact in the historical global crescendo that has led us to where we are today. With any luck, perhaps these approaches can point to solutions as well. In its earliest days, the applied aspect of evolutionary science was astonishingly ugly, feeding projects of colonialism, oppression, and eugenics (Lindqvist 1996). Perhaps for this reason human behavioral ecologists and evolutionary psychologists have tended to shy away from policy applications and social implications of their work. This is now changing, as a new generation of human behavioral ecologists and evolutionary psychologists have begun to explore social justice angles of their research, ways to use evolutionary insights to improve human and nonhuman flourishing, and to understand harmful social phenomena such as inequality and oppression. With caveats and mindfulness about not repeating the mistakes of the past, this is another promising avenue for HBE/EP synergy, and it can only be improved by bringing a more inclusive and diverse range of scholars and perspectives into the field.

16.8

Conclusion The evolutionary social sciences have themselves evolved and continue to do so. Arguably, the most useful growth in scientific fields occurs not through orderly,

https://doi.org/10.1017/9781108377911.017 Published online by Cambridge University Press

Evolutionary Psychology

401

rational, forward-looking processes, but when practitioners face problems for which they must innovate to find solutions (Laudan 1978). The early frameworks of ESS, while productive, were also arguably constraining and limiting in the scope of phenomena that they could explain. One form of problem-solving can occur when tools and ideas are brought in from elsewhere to work on problems where progress has stagnated or plateaued. Not only can HBE and EP each benefit from such a recombination of ideas, they can both benefit from bringing in new ideas from elsewhere as well: from a broader range of theoretical perspectives, a broader range of people, and to explore and explain a broader range of phenomena. To do this, humility is required, a welcoming of new voices, and a self-reflexive recognition of the limitations of each of our perspectives. Scientists are frequently loath to admit that their frameworks contain, or perhaps simply are, ideologies (Longino 1990; Douglas 2009). Approaches like EP and HBE – and any other, for that matter – embody attitudes and values about what kinds of questions are important, what ideas and ways of framing them count as legitimate theories, what kinds of data matter or bear on those theories, and what empirical research programs are held up as exemplary. Failure to recognize this simple and obvious fact is a major impediment to scientific progress because it leads to selfcongratulation and the dismissal of other approaches as the ideological ones. The ESSs are no different in this way. My personal experience has been one of seeing smart and well-intentioned colleagues repeatedly rejecting obviously good ideas from other perspectives simply because they come from elsewhere. While nobody can entirely escape this, my view is that there is virtually nothing in the approaches I have reviewed here that is incompatible if care is taken not to oversimplify or caricature. On the contrary, to the extent that our goals are one and the same – to understand and explain human behavior – we can only benefit from filling in our own blind spots with the knowledge accumulated by others who have taken the time to look and think where we have not.

https://doi.org/10.1017/9781108377911.017 Published online by Cambridge University Press

17 The End of Human Behavioral Ecology Richard McElreath and Jeremy Koster

17.1

Introduction Edited volumes tend toward triumphalism. This one is no different. Human behavioral ecology has enjoyed a lot of success, both in terms of professional growth and scientific results. This success is more remarkable when we recognize that the field has no clear disciplinary home. Whereas many human behavioral ecologists are anthropologists, others are scattered across psychology and economics and biology departments. Some self-congratulation is deserved. But at the time of this volume, the behavioral and biological sciences are in crisis. As a consequence of failures to replicate highly cited results (Camerer et al. 2018), the impossibility of verifying analyses due to lost data and materials (Minocher et al. 2021), and even widespread fraud (Bik et al. 2016), a variety of professional organizations, funding agencies, and governments have called for methodological reform (McNutt 2014; Munafò et al. 2017). A former editor-in-chief of The Lancet summarized the situation this way: The case against science is straightforward: much of the scientific literature, perhaps half, may simply be untrue. Afflicted by studies with small sample sizes, tiny effects, invalid exploratory analyses, and flagrant conflicts of interest, together with an obsession for pursuing fashionable trends of dubious importance, science has taken a turn towards darkness. [. . .] And individual scientists, including their most senior leaders, do little to alter a research culture that occasionally veers close to misconduct. (Horton 2015)

It is reasonable to disagree about the contributing causes of the crisis, but it is no longer reasonable to deny that we are in one. It would be hubris for human behavioral ecology to think it is immune to these systemic problems. Some introspection is merited. Accordingly, this essay outlines some short-term strategies that may help human behavioral ecology (HBE) and cognate fields to achieve their long-term scientific goals. In order to decide what to do next, we should decide where we want the field to go in the long run. The current state of our field is partly explained by decisions a small number of researchers made in the early and middle twentieth century. That is not the whole story. But scientific fields are culturally evolved institutions. Their practice embodies their origins, and their origins strongly influence their practice. How we practice our field now influences where we go next. How can we deliberately steer the field in better directions, rather than waking up each day and shortsightedly chasing another grant or publication? (See Boxes 17.1 and 17.2.)

https://doi.org/10.1017/9781108377911.018 Published online by Cambridge University Press

The End of Human Behavioral Ecology

Box 17.1

403

Two Zombie Papers

The purpose of this chapter is to examine the general conditions and development of the field of human behavioral ecology. We do not focus on particular papers. However, there are two papers which have been published often enough now that they deserve special consideration.1 These papers contribute little to cumulative science but are difficult to eradicate. The first paper is entitled something like “Social Networks, Reproductive Success, and the Evolution of Human Sociality.” After an introduction that promotes the banal claim that social relationships and fertility may influence one another, the number of self-reported friends is shown to be associated with past fertility. The analysis adjusts for a basket of perfunctorily measured demographic variables, and every coefficient is interpreted as a total causal effect. The paper claims that this finding demonstrates the value of an evolutionary approach to human behavior, mainly because economists have ignored it. But since no evolutionary model predicted the result, the size and direction of the association have no impact on any evolutionary model. Any evolutionarily relevant variable like relatedness or age at first birth can be deployed in this paper to imitate, but not actually to perform, behavioral ecology. The paper is highly cited. The second appears under the banner “The Evolution of Human Cooperation: A Bayesian Phylogenetic Analysis of Kinship and Pudding Recipes.” A cross-cultural sample of stereotyped features of human societies is fed into software designed for the analysis of biological species. The procedure identifies an association between uxorilocal residence and the prominence of dessert. No model predicts this association nor its size. But rejecting a null model of no association somehow illustrates the value of an evolutionary approach. A few fatal confounds and methodological flaws flirt with the reader in the twilight paragraphs. The result has implications for the origins of human society and the possibility of world peace. We have likewise written these papers, but we are trying to stop. If we could all avoid producing, reviewing, and reading these papers ever again, we would divert a substantial amount of talent toward productive research. The authors of these papers could make a contribution by instead advancing an optimization model that resembles the models that are described in other chapters. Then the model’s predictions could be made algorithmically and contrasted with similarly precise alternatives. Data collection and analytical procedures could be designed that have some hope of causal identification. But at least the assumptions that justify a causal interpretation would be clear. Making zombies does not train us to perform any of these tasks. Our students and their students deserve better.

1

This box is an homage to Elias (1958) and can be read as a lament of the structural considerations that incentivize overstated inferences from limited data and rote modeling.

https://doi.org/10.1017/9781108377911.018 Published online by Cambridge University Press

404

Richard McElreath and Jeremy Koster

Box 17.2

The Human Behavioral Ecology of Academic Research: Status

A key premise of human behavioral ecology is that individuals respond adaptively to their environments, including the cultural norms and institutions that shape the costs and benefits associated with different strategies. This theoretical assumption applies equally to all individuals and populations, regardless of nationality, ethnicity, gender, age, and other characteristics. With that in mind, it is helpful to consider how academics, including human behavioral ecologists, are incentivized to navigate the landscape of academic research. Often working as members of academic departments, human behavioral ecologists are expected to conduct high-quality research that contributes to the cumulative advance of scientific knowledge. Assessing the quality of research at the creative edge of knowledge is difficult, however. It is a noisy process. Peer review has a subjective element; bias can intrude. Absent objective measures and pressed for time, evaluators sometimes fall back on expedient heuristics, status being an especially common one. That the process often works reasonably well does not absolve us from acknowledging and addressing its imperfections. Status is a position in a social hierarchy that accumulates from social esteem, respect, and repeated acts of deference (Chapter 7; see also Sauder et al. 2012). In academic contexts, researchers can show deference via citations of other scholars’ published work (Merton 1988). Accordingly, research is frequently assessed via citation-based metrics despite the broadly recognized limitations and ethical issues associated with these measures (Raff 2013; Chapman et al. 2019). Moreover, the peer review system is rife with deference to status, resulting in a Matthew Effect that inordinately rewards high-status scientists and their institutions (Merton 1968; Huber et al. 2022).2 This Matthew Effect is troubling given evidence that status and quality are imperfectly correlated (Sauder et al. 2012). If rewards disproportionately accrue to individuals with high-status mentors, institutional affiliations, and demographic characteristics, then high-quality research by individuals not sharing these profiles is disadvantaged (Lynn et al. 2009; Hofstra et al. 2020). Jockeying for status can quickly cease to be healthy competition and instead contribute to incentives for attention-grabbing rather than reliable and reproducible studies (Smaldino and McElreath 2016; Fraser et al. 2018). Ethical publishing choices can be overlooked or disregarded (Logan 2017). In short, the Matthew Effect can harm scientists and hinder scientific progress.

2

The Matthew Effect derives its name from the biblical passage in the book of Matthew: “For unto every one that hath shall be given, and he shall have abundance: but from him that hath not shall be taken away even that which he hath” (Matthew 25:29; as cited in Merton 1968).

https://doi.org/10.1017/9781108377911.018 Published online by Cambridge University Press

The End of Human Behavioral Ecology

405

Behavioral ecologists can choose to guard against deference to status by reading carefully and widely, attending to sources outside the usual venues, and keeping in mind their own personal biases when making decisions that affect the fair appraisal of colleagues, students, and others in the academic community. More broadly, given the importance of institutional norms in academic research settings, we all have an obligation to support institutional reforms that incentivize high-quality, reproducible studies. We are optimistic that human behavioral ecologists will adjust to those incentives, improving the science.

Many behavioral ecologists will know an optimization technique called stochastic dynamic programming. The problem facing animals in their environments is not to optimize each decision, independent of all other decisions. Rather the problem is to optimize a sequence of decisions, usually under substantial uncertainty. Stochastic dynamic programming is a way of finding optimal conditional strategies in such circumstances (Houston et al. 1988). The key insight of the approach is that the optimal strategy is not found by thinking forwards about what to do next. Rather it is found by working backwards from the end goal. Imagine the field many years in the future, when many of its original goals have been achieved. The field is not over. Instead, it enjoys successful integration with other basic and applied sciences, integration made possible through unique scientific contributions. What did researchers in the field do in the decade before reaching this end? And in the decade before that? And so on, all the way back to the present. Accordingly, the first step is not to decide what to do tomorrow. It is to decide what to do the day before the end. One must then ask: what is the end of human behavioral ecology? In this rest of this essay, we develop a future-oriented, backward-looking view of the field of HBE. As an interdisciplinary field with an orientation toward formal theory and difficult, naturalistic investigation, HBE stands to make unique contributions to both basic and applied research. The best way to realize these contributions is to work backwards from one or more ends, developing pathways of investigation and training to guide us. We do not believe that this essay resolves these questions. Instead, it foregrounds them, presents credible reforms, and aims to defy the myopic path-dependency and substitution of scientific goals with individuals’ professional rewards that have contributed to the contemporary crisis of the sciences.

17.2

The Ends The goal of HBE is to understand the evolutionary origins, mechanisms, and dynamics of human behavioral adaptation, especially in the context of variable

https://doi.org/10.1017/9781108377911.018 Published online by Cambridge University Press

406

Richard McElreath and Jeremy Koster

and culturally evolved environments. For the field to succeed, it must present a justified explanation for how, during the course of human evolution, human behavioral flexibility co-evolved with our life history traits, cognitive development, and capacity for culture. It must, together with other fields, contribute to the development of credible causal models of variation and change not only in individual behavior but also social institutions and technology over the course of human history. Equally important is the future. Already, a majority of humans live in cities. The United Nations estimates that 70% of people will live in cities by the middle of the twenty-first century. An alien biologist observing us would logically conclude that we are evolved to build and live in cities. Therefore, another proper end of HBE is to contribute to an applied understanding of how our origins shape our present and future. This contribution might be accomplished through scientific insights. But it could be realized also through tools and approaches that applied research may adopt. Many fields study human behavior, and many fields will make contributions to these goals. How can HBE make a unique and valuable contribution? Looking back from the ends of HBE, the research that maximizes its contribution is long-term, individual-based field research. Yet, before long-term studies can realize their potential, the field requires sustained investments in a culture of professional research design, data management, and data analysis. In the next sections, we outline the contributions of long-term research and the training necessary to make it sustainable and scientifically productive.

17.3

Long-Term, Individual-Based Research In the early days of anthropological fieldwork, progress was made through discovery and systematic comparison. Fieldworkers encountered and documented substantial diversity in kinship and descent, political organization, religions, livelihood strategies, and so forth. The pace of discoveries eventually slowed, and HBE has largely transitioned out of seeking such discoveries and instead is busy trying to make sense of the diversity. Yet, much like anthropologists in the early twentieth century, the careers of human behavioral ecologists generally continue to feature a series of short-term studies on distinct topics. Long-term individual-based field research provides advantages over both shortterm and population-level research. By long-term research, we mean research that studies the same local population over many years. By individual-based research, we mean designs that collect data on discrete individuals and their social lives (Box 17.3). There are accentuated structural and ethical obstacles to conducting long-term individual-based field studies on humans. From the auspicious ends of HBE, addressing these obstacles is just as important as the scientific advantages of the research. We discuss the advantages and obstacles in turn.

https://doi.org/10.1017/9781108377911.018 Published online by Cambridge University Press

The End of Human Behavioral Ecology

Box 17.3

407

Longitudinal Research Designs and the Prospects for Long-Term, Individual-Based Studies

Figure B17.3.1 depicts common research designs, including longitudinal designs that are commonly used in the social sciences (Gravlee et al. 2009). In general, cross-sectional studies have predominated in human behavioral ecology. There are noteworthy exceptions to that generalization. Using a repeated cross-sectional design, for example, Urlacher and Kramer (2018) study separate cohorts of Yucatec Maya children to examine changes in physical activity level and anthropometric outcomes between 1992 and 2012. Among the Hadza of Tanzania, Pollom et al. (2020) use a similar research design to examine changes in juvenile foraging over time. Meanwhile, because people can report on past events in interviews, it is often possible to compile datasets for retrospective panel studies. Respondents may be able to provide reliable data on significant events, such as the timing of their marriages and divorces, residence histories, and the births and deaths of their children and other family members. These data can then be organized into a unit-period format with entries for previous intervals of time that are suitable for an event history analysis (Sheppard et al. 2014; Blurton Jones 2016). There are limitations to this approach, however, when unrecoverable timevarying variables are an important part of the data-generating process. As an

Research Designs

CrossSectional

Prospective Panel

Longitudinal

Panel

Repeated CrossSectional

Retrospective Panel

Rotating Panel

Figure B17.3.1 Common research designs in the social and ecological sciences. Adapted from Gravlee et al. (2009).

https://doi.org/10.1017/9781108377911.018 Published online by Cambridge University Press

408

Richard McElreath and Jeremy Koster

example, consider the study of divorce by Winking and Koster (2021), which suggests that the risk of divorce decreases as married couples have more children together. This finding is consistent with behavioral ecology theories of serial mating and shared reproductive interests (Chapter 9). However, the event history analysis does not include the effect of the couples’ material wealth on divorce. This omission is problematic given the evidence from other studies that (1) financial problems increase the probability of divorces (Snopkowski 2016), and (2) fertility varies as a function of the wealth that is available to the married couple (Borgerhoff Mulder 1992a). If both of those relationships are evident in a particular study population, then an observed effect of couples’ fertility on divorce might represent a spurious correlation. That is, if the statistical model were to include wealth as a predictor, then the effect of fertility might be negligible. In other words, the analysis of Winking and Koster (2021) potentially suffers from an omitted variable bias. Although it is often possible to elicit measures of wealth at the time of data collection, in many study contexts it is unrealistic to expect respondents to report reliably on their annual wealth in the preceding years and decades (Bernard et al. 1984). In the absence of longitudinal data, researchers might consider using a measure of wealth collected at time t as a static predictor of the outcomes in preceding intervals ðt  1, t  2, etc:Þ. This approach, however, rests on the dubious assumption that wealth does not fluctuate over time. Overall, this example helps to illustrate the limitations of retrospective panel studies (see also Boxes 2.1 and 13.2). There are variables that can be reliably collected only via prospective panel studies, which entail multiple waves of data collection on the same individuals or units. For human behavioral ecologists, key time-varying variables might include subsistence outcomes, short-term behavioral strategies, measures of knowledge and beliefs, reputations, emotional states, and biomarkers. For robust inferences about the dynamic processes that interest human behavioral ecologists, often there is no substitute for careful data collection, repeated over time. Accordingly, prospective panel designs are an ideal option for the long-term, individual-based studies that are needed to answer longstanding research questions.

17.3.1 Advantages We focus here on five advantages of long-term individual-based field studies: (1) the possibility to study age-related changes, (2) the ability to model causes of events in different life stages, (3) the study of dyadic and higher-order relationships and their impacts, (4) the possibility of measuring life span variables like reproductive success and economic and cultural contributions, and (5) the measurement of behavioral change both within and between generations. These advantages are shared with

https://doi.org/10.1017/9781108377911.018 Published online by Cambridge University Press

The End of Human Behavioral Ecology

409

long-term studies of nonhuman animals (Clutton-Brock and Sheldon 2010). However, the longer lives and complex, dynamic phenotypes of humans increase the marginal value of sustained, individual-level data collection. We will not address any of these advantages thoroughly. Each is worth an entire chapter on its own. Also, archival data can have the same advantages as field research, which is worth keeping in mind throughout. Individual behavior is highly dynamic, and one important dimension of these dynamics is age. From an orthodox evolutionary ecology perspective, humans are age-structured organisms. Our long lives create overlapping generations, and individuals at different ages have different physiology and behavior. There are also distinct, culturally constructed stages of life in all human societies (Brown 1991). Studying the origins and evolution of human life history means studying both agerelated changes and stage-related transformations. Short-term fieldwork is limited by its mostly cross-sectional nature. Many variables, potentially including the timing of key events, cannot be elicited through retrospective interviews. Finally, the study of stage-related changes will require longer studies simply because changes in stage happen more rarely than changes in age and because sustained cultural competence may be necessary to recognize and accurately describe local stages. To study and explain human behavioral adaptation, we want to model causes of individual change. For humans, this often means modeling causal relationships between the events in individual lives in earlier ages and stages to events in later ages and stages. Only long-term individual-based research can capture the necessary evidence. It is always necessary to makes strong causal assumptions to get causal inference out of observational research. But the strength and plausibility of the assumptions are greatly reduced in long-term designs. A rigorous mathematical framework exists in evolutionary demography for structuring and modeling causes of phenotypic change (Ozgul et al. 2009). Our field should adopt it and modify it to include cultural processes (Beheim and Baldini 2012). Much of the classic theory in evolutionary ecology uses a mean-field approximation. This means that social forces are averaged across individuals and their social relationships. For example, cooperation is studied by considering an average interaction partner or an average migration context. For short-lived organisms, this is a very powerful approach because relationships do not last long and take on their own causal histories. But it is an approximation, and for long-lived organisms like humans, it can be a poor one. When dyadic and higher-order relationships can last for decades, averaging across social contexts produces misleading estimates of costs and benefits (Hauert and Szabó 2005). Studying causal forces like these requires long-term data on specific individuals and their interaction partners. Many of the theoretically important quantities in HBE are life span variables or lineage variables that require generational and even intergenerational observations for estimation. Life span variables include reproductive success, number of spouses, income, and capital accumulation. Cultural analogs of these traditional variables include number of innovations, number of languages learned, number of artworks produced, as examples. Intergenerational processes such as lineage growth, change

https://doi.org/10.1017/9781108377911.018 Published online by Cambridge University Press

410

Richard McElreath and Jeremy Koster

in any of life span quantities, and transmission of wealth and knowledge between generations are similarly central to HBE. With strong assumptions about the absence of cohort effects, these quantities can be estimated from short-term and crosssectional data. However, because the necessary strong assumptions cannot be tested, long-term research is really the only way to observe the events that allow for proper description of life span and intergenerational processes.

17.3.2 Obstacles There is a sense in which all of these assertion are obvious. Of course, long-term, individual-based research is essential for studying the processes of human behavioral adaptation. Despite obvious benefits, long-term studies are underused because there are substantial obstacles to planning and maintaining them. Some of the most substantial difficulties are (1) the short-term focus of funding for basic research, (2) the stochasticity of research funding, (3) the ethical and practical obligations to cooperate with and transfer benefits to research communities, (4) a lack of expertise in and training for research design and data management for long-term, individual-based designs. We address the last of these in detail in the next major section. We briefly address the others here. Even at long-term field sites, project designs do not typically center long-term research. Instead, many research projects promise to be able to shed new light on important questions using a few months of data collection. And some important work can be done that way. Yet, contemporary projects tend to promise that shortterm data can address long-term questions about adaptation in part because they must advance that perspective in order to win competitive grants. And competitive grants rarely cover more than a few years of support. In principle, iterated grant proposals could support longer-term research designs. Some successful long-term projects have done just that. But proposals that promise to continue doing what was done in the previous funding period compete poorly in a research culture that values innovation and rapid results. This results in shifting priorities, dropped measurements, loss of continuity, and poor data management. For the ends of HBE, these structural obstacles must be overcome. Funding agencies and research institutions could choose to support and reward long-term designs and evaluate progress toward long-term scientific goals rather than short-term publication and citation impact. Some projects can support themselves with crowd-funding, especially since necessary maintenance funding for HBE is often modest. All of these problems are shared with other fields (Clutton-Brock and Sheldon 2010). Accordingly, solutions do not have to come only from HBE initiatives, but energy must be allocated toward reforming the support and incentive environment. Perhaps the most important component of successful long-term field research is cooperation with and ethical involvement of the communities that provide data (Broesch et al. 2020; Urassa et al. 2021). There are ethical obligations but also potential advantages of increased community involvement in research. Long-term projects cannot succeed without the long-term consent of the participating community. And in most cases, this requires some sharing of rewards, either indirectly or

https://doi.org/10.1017/9781108377911.018 Published online by Cambridge University Press

The End of Human Behavioral Ecology

411

directly through meaningful involvement of local communities in research design. Trained community participation can itself be an asset to data collection and the cumulative improvement in research designs. More substantial are problems in the integration of research design with data management and analysis.

17.3.3 Training As seen throughout this book, classic papers in human behavioral ecology and cultural evolution used mathematical models, solved through optimization or game theoretic dynamics, to make non-null predictions about behavior. HBE is a highly quantitative field, but it has not succeeded yet in developing professional norms of data analysis or data management. In this regard, it is like most quantitative sciences. Yet, that should not stop us from acknowledging the field’s limitations and charting a path toward improvements. In this section we briefly outline two major projects in reforming our field’s approach to quantitative inference. The first is the development of professional norms of data and code management. The second is the importance of returning to the field’s roots and placing formal scientific causal models in charge of data analysis. To some extent, it may seem unrealistic or onerous to add more items to the already long list of skills that human behavioral ecologists are expected to master. For instance, consider a graduate student who is conducting dissertation research on an HBE topic in an international setting. Typically, the student is expected to develop a theoretically novel research question, independently secure grant funding for the fieldwork, navigate potentially complex bureaucracies to obtain permits for research, gain proficiency in another language, adapt to residing and working in a different cultural context, collect and organize high-quality data, analyze the data with complex statistical methods, and exercise superb technical writing skills while publishing the findings in peer-reviewed journals. This diverse skillset has few parallels in other academic disciplines, and it is a genuinely masterful scholar who meets all of these expectations.3 Given the benefits of improved data management and analysis, however, there are compelling motivations to support the dissemination of these skills. Fortunately, the broader scientific community develops tools and innovations that can be adapted to the HBE workflow relatively easily. Mentors of early-career researchers can facilitate the acquisition of valuable skills by researching and supporting relevant opportunities for extracurricular training. The pace of scientific progress is swift. Few graduate programs can maintain the faculty expertise to provide the needed skills via the traditional reliance on coursework and mentorship. The following overview mentions 3

There is a case to be made, of course, that expecting individual researchers to embody all of these skills is detrimental to scientific progress. Diverse teams of specialized researchers who can leverage their comparative advantages often produce better science than individuals who attempt to implement the necessary skills independently (as in the subsistence contexts described in Chapter 6). Human behavioral ecologists are often housed in academic departments and disciplines, however, that have been slow to recognize the benefits of collaboration and to rethink its evaluations of scholars’ contributions to scientific teams.

https://doi.org/10.1017/9781108377911.018 Published online by Cambridge University Press

412

Richard McElreath and Jeremy Koster

tools and methods to consider, but better alternatives may soon appear. The broader point is that progress in HBE will accelerate when the quality of data management and analysis rivals the quality of the theorizing and data collection.

17.3.4 Data Management Especially for long-term research projects, HBE will benefit from greater emphasis on data management and design. Too many projects begin without any formal training in longitudinal data management. This results in awkward and error-prone databases. Problems in data management are also problems in data collection. Seemingly simple tasks like maintaining persistent identities of individuals can be deceptively challenging. Integrated solutions that design for these problems at both time of data collection and database integration exist, but they are not well-known or commonly utilized. Additional problems arise in long-term research because eventually key personnel retire, but the data must remain intelligible to new personnel. Too many HBE projects have grown with databases designed for and understood by only one or two people, which places all of the data at risk. HBE can quickly improve by modifying solutions from allied fields like development economics and global health, in which longitudinal databases with distributed users are more common. A growing professional culture of data “carpentry” is also helping, with many students acquiring relevant data-science skills and data-design principles through professional workshop curricula (Teal et al. 2015). The problems of data management remain substantial, but HBE does not have to solve them on its own. It merely has to participate. Transparent sharing of data and analytical code is a core principle of open science (Munafò et al. 2017). Without that transparency, skepticism of published findings may be warranted given the potential for questionable research practices, which can range from fraudulent manipulations of data to seemingly minor undisclosed decisions about outlying data points and statistical modeling. For individual researchers, however, sharing data and code might seem perilous. When analysis and data can be scrutinized by others, mistakes may be revealed, potentially leading to retractions (e.g., Whitehouse et al. 2019, 2021; Beheim et al. 2021). In terms of the collective advancement of science, though, such scrutiny is unambiguously helpful. A retracted finding is preferable to unnoticed errors in the literature. Institutionalized standards are needed that reward researchers who make their data and code available. It is important, however, to consider the ethical dimensions of data sharing. Whereas research with human subjects always requires thoughtfulness, the work done by human behavioral ecologists may need extra consideration (Kraft et al. 2020). Fieldwork is often conducted among Indigenous, marginalized, or socioeconomically disadvantaged populations. These societies may exhibit familial, marital, or reproductive norms that depart from the conventions and laws of countries in which they reside. In some cases, there is potential for published data to enable discriminatory treatment by authorities. Amid ongoing conversations about best practices for data management and sharing, it is important for human behavioral ecologists to weigh local contexts alongside general principles (e.g., Carroll et al. 2021). For particularly sensitive data, it may be necessary to consider repositories

https://doi.org/10.1017/9781108377911.018 Published online by Cambridge University Press

The End of Human Behavioral Ecology

413

that curate access to the data, limiting access only to researchers who pledge to maintain the anonymity of the data. Reasonable embargo periods that limit access until time has elapsed are another method to mitigate unethical repurposing of data. With these alternatives, there are few scenarios in which HBE datasets cannot be made available to others.

17.3.5 Causal Inference The study of behavioral adaptation is not just the description of behavioral and ecological change. It also requires some way of inferring causes of behavioral change. The preferred method of causal inference in many sciences is the controlled, randomized experiment. However randomized experiments are not, and never have been, the dominant style of causal inference in the human sciences. One reason is that many of the most important questions about human behavior cannot be studied experimentally. Ultimately, behavior must be studied in the natural environments that people construct because those environments are both causes and consequences of behavior. Without studying people in their own communities, we would not even know what we are trying to explain. But equally important are the ethical limitations on experimental intervention that would be required to study, for example, the influence of family structure on behavior. Causal inference is clearly possible in observational settings, and statisticians have developed specialized methods for designing analyses that address stated causal estimands, the targets of inference (Pearl et al. 2016). Conventionally, few HBE studies have made use of these methods, often relying instead on a mixture of predictive model selection and interpretation of every coefficient as an unmediated total effect (McElreath 2020). It has become clear, however, that statistical models are not enough. What is required is a conceptual model, distinct from any statistical models, that embeds the assumptions about relationships between variables in ways that enable predictions about the consequences of interventions (Pearl et al. 2016). When the only model a researcher uses is a statistical model, there is no principled way to justify the structure of the model and no logical way to interpret its output. Not only will the estimate of interest be uninterpretable, but so will all of the other coefficients from the model. It is never justified to simply include control variables in a multiple regression and interpret every coefficient equivalently as a direct causal effect. Ignoring the overall causal structure when interpreting coefficients is known as the “Table 2 Fallacy” (Westreich and Greenland 2013). The fallacy is unfortunately very common, even in fields important to public welfare (Westreich et al. 2021). A core challenge for HBE, therefore, is to make scientific model construction an integral part of student training, research design, and peer criticism. Of course, more detailed scientific models are needed as well. But models at different levels of abstraction bring different benefits. Abstract models that can be represented as simple diagrams excel at communication while still having clear implications for measurement. More detailed causal models, based for example on dynamical systems

https://doi.org/10.1017/9781108377911.018 Published online by Cambridge University Press

414

Richard McElreath and Jeremy Koster

models or agent-based simulations, are harder to communicate but make more detailed predictions and are therefore more powerful in measurement. To understand why, consider the example of the role of ecological knowledge in foraging production. To prosecute this example, we will use a type of causal diagram known as a directed acyclic graph (DAG). DAGs are graphical causal models that communicate abstract causal assumptions and allow us to logically deduce estimation strategies. See Box 17.4 for general information about DAGs if you are unfamiliar with them.

Box 17.4

Causal Inference with Directed Acyclic Graphs

The basis of formal causal inference is to specify one or more generative models of the phenomenon and then to deduce, or to deduce the impossibility of deducing, the consequences of intervening (altering) one or more variables in the model. One problem is that most working scientists do not have complete generative models of the systems they study. But even when they do not have a complete generative model, a lot of logical work can be accomplished. Indeed, it is dangerous to attempt statistical inference without thinking about causality, even if the goal is mere description. A popular and axiomatic approach is the use of directed acyclic graphs (DAGs) to represent and communicate assumptions about causal relationships. As an illustration, consider these three schematic generative models, drawn as DAGs: Z

X !Y

X !Y !Z

X !Z

Y

In each DAG, the letters are measured variables and the arrows represent causal influence. The scientific goal is to estimate the influence of X on Y , indicated by X ! Y . In each case, a third variable Z is also available. The question is, should you include Z in your analysis? A contemporary norm in HBE is to include Z in a regression analysis and either interpret it as a control variable or use a criterion like AIC to justify its inclusion. However, in each of the three models, including Z has very different consequences. In the first example, on the left, X influences both Z and Y . If we include Z in a regression of Y on X , we lose precision on the estimate of the influence of X on Y . But it does not systematically distort the estimate. In the second and third examples, however, including Z is a mistake. In the middle model, including Z creates a form of selection bias and can induce large systematic error in the inference of the influence of X on Y . In the third model, X does not influence Y at all. But when we include Z in the analysis, it can lead to a very strong association between X and Y via a collider bias. Furthermore, although HBE rarely obtains experimental control of a variable like X , even when X is randomly assigned, including Z in a regression could ruin inference. Even experiments are not safe. These claims can be proved algebraically (Pearl 1995; Pearl et al. 2016; Cinelli et al. 2022) or demonstrated using simulation (McElreath 2020).

https://doi.org/10.1017/9781108377911.018 Published online by Cambridge University Press

The End of Human Behavioral Ecology

415

Figure 17.1 This Directed Acyclic Graph (DAG) depicts the hypothesized causal relationships

among foraging returns Y , ecological knowledge K, age A, and labor allocations to foraging L. In this example, the dashed path between labor allocations and foraging returns is representative of unmeasured confounds. In contrast to the black arrows, the gray arrow indicates that the target of inference, also known as the estimand, is the effect of knowledge on foraging returns. Generally, for a given estimand, the structure of a DAG allows researchers to determine which variables should be added or omitted in a statistical model and how coefficients should be interpreted. Also, a DAG can constructively inform research designs by illustrating which variables should be measured during data collection.

We adopt for the sake of example the causal DAG in Figure 17.1. In this example, the estimand of interest is the causal influence of knowledge K on foraging returns Y , highlighted in gray. However, there are other variables that influence both K and Y and make the task of estimation more difficult than simply regressing returns on knowledge, even with controls. In this example, there are two competing causes of foraging returns, age A and labor L allocated to foraging. Age A influences foraging returns Y through unmeasured mediating causes like physical condition, represented by the path A ! Y . But age A also influences knowledge K, since older individuals have had more time to learn. And age A also influences the labor L allocated to foraging. Knowledge K itself influences labor L, since more knowledgeable individuals allocate labor differently.4 Finally, the dashed path on top between L and Y represents unmeasured confounds, such as illness, that influence both labor and foraging success. For example, when people are ill, they will forage less and be less successful when they do forage. It is easy to imagine other paths in this diagram, or alternative diagrams. But the point is not to argue that this represents the true relationships among the variables. Rather the point is to argue that meaningful research in the evolutionary behavioral sciences requires some causal model and must be able to deduce from such a model how to use data to estimate an estimand of interest. How would you use observational data on Y , K, A, and L to estimate K ! Y ? Should you control for any of the other variables? If so, how? The value of an explicit causal model is that it provides a logical, objective way to answer these questions. In fact, a computer can do it upon being taught the causal model. But for simple models like this one, it is simple enough that a computer is not needed. In this example, in order to estimate the direct causal effect of K on Y , the 4

For this simple illustrative example, the model assumes relationships only at a particular moment in time. It is possible to extend DAGs to a longitudinal framework. For example, knowledge K could influence labor L at time t, and then the experience gained at time t could enhance knowledge at time t þ 1. These dynamics can be incorporated into a DAG with additional time-varying nodes, such as future knowledge K tþ1 . When longterm, individual-based datasets permit longitudinal analyses, expanded DAGs with time-varying nodes can help researchers to fit sensible and robust statistical models.

https://doi.org/10.1017/9781108377911.018 Published online by Cambridge University Press

416

Richard McElreath and Jeremy Koster

Figure 17.2 Replicating the causal structure of the DAG in Figure 17.1, the variations in the gray arrows indicate two important inferential considerations, the treatment of confounders (left) and distinctions between total effects and direct effects (right). In the left-hand panel, the inclusion of age A in the statistical model remedies the confounding effect of age on the causal relationship between knowledge K and foraging returns Y . In the right-hand panel, the total effect of knowledge on foraging returns includes the direct effect K ! Y and the indirect effect that is mediated by labor allocations K ! L ! Y . A statistical model that does not include labor L as a predictor variable permits the estimation of the total effect of K. As noted in the text, however, the unmeasured confounds of L and Y preclude unbiased estimates of the direct effect of K on Y .

gray arrow, we need our statistical machinery to do two things. First, we need to remove any noncausal sources of association between K and Y . In this example, age A is a common cause of both K and Y . The observed association between K and Y is partly a result of shared variation stemming from A. That is, age A is a confound. Second, we need to separate the direct effect of K from its indirect effects, if any. Any observed association between K and Y is a combination of its direct and indirect effects. In this example, there is an indirect effect of K on Y that is mediated by L. Let us redraw the diagram in Figure 17.2, highlighting each of these problems. Then let us consider, in nontechnical terms, how to accomplish our objectives. The first problem is to remove the confounding influence of A. This is accomplished by stratifying by A, estimating the association between K and Y for each level of A. Once variation in A is statistically “controlled” this way, the average association between K and Y is free of the confounding influence of A. In ordinary linear models, the way to accomplish this control is by including A as a predictor variable. But it is important to justify its inclusion in the model, as well as how it is included. It is dangerous to simply add variables and watch how coefficients change. The second problem is separating the direct and indirect effects of K. After stratifying by A, according to the causal diagram, the association between K and Y measures the total causal influence of K on Y through both direct and indirect paths. How can we isolate the direct effect? It turns out that we cannot. Similar to removing the association due to A, we might also stratify by labor L, examining the association between K and Y for each level of L. This statistically “controls” for the influence of labor. However, in this example, L and Y are confounded by unobserved influences, as indicated by the dashed path connecting them. This means we cannot estimate the causal influence of L on Y . This is no problem for estimating the total causal effect of K on Y , because we do not need to measure L ! Y to estimate the total effect of K. But in order to isolate the direct effect of K, we do need to estimate L ! Y . So according to this causal model, there is no way to estimate that direct effect. By contrast, if we were willing to assume that there are no unobserved confounds of L and Y , then stratifying by both L and A would be sufficient to estimate the direct effect of K. In this respect, devices like DAGs

https://doi.org/10.1017/9781108377911.018 Published online by Cambridge University Press

The End of Human Behavioral Ecology

417

are valuable for communicating assumptions, which can then be considered and critiqued by others. In general, the language of causal inference has not characterized the initial decades of HBE research. Until recently, distinctions between “total effects” and “direct effects” and “indirect effects” and “mediators” have not been common in the literature, nor have biases such as collider biases been considered regularly. To the contrary, the overarching concern has been the possibility of an omitted variable bias, a preoccupation that can lead to unwieldy statistical models when researchers consider nearly any available variable to be a possible confounder. It is now clear, however, that adding control variables in this way can lead to spurious or misguided inferences. It is important that we teach and learn to recognize that there are both “good controls” and “bad controls” and that distinguishing between the two requires a full causal model (Cinelli et al. 2022). There is no substitute for theory when fitting and interpreting statistical models. None of these points are novel nor controversial in the statistical community. But only recently have relevant methods started to become part of HBE’s standard training. Formerly, standard statistical practice in HBE, as reflected in many of the field’s most highly cited papers, was based on mistaken understandings of the relationship between scientific and statistical models. As a result, much of the research published in the last few decades contains a tangle of estimates of debatable value. We must tackle this both by stopping to analyze data in similar ways and by revisiting older publications and critically evaluating their results in light of explicit, theoretically informed scientific models. Fortunately, to demystify the logic of DAGs and causal modeling, software tools are available to facilitate analyses (e.g., Textor et al. 2016). To use these tools, researchers supply the DAG that represents their view of the scientific model. The software can then generate the recommended statistical model for estimating the effect of interest. With moderate effort, therefore, researchers can leverage their theoretical expertise to advance statistical models that align convincingly with key research questions. Overall, these methods enable an approach in which a scientific model asserts a data-generating process, and then statistical models are used to examine the extent to which the asserted scientific model is evident in the empirical data.5

17.3.5 Methods Inform Theory and Research Design Our overview of methodological training has been deliberately pointed, focusing on areas for improvement. Still, there is also progress to be celebrated, as multilevel

5

It is important to reiterate that multiple statistical models with heterogeneous combinations of variables may be needed when researchers aim to make inferences about different aspects of the causal structure for a particular data-generating process (Westreich and Greenland 2013). One variable’s confounder is the other variable’s mediator. Not all regression coefficients can be interpreted equivalently.

https://doi.org/10.1017/9781108377911.018 Published online by Cambridge University Press

418

Richard McElreath and Jeremy Koster

modeling and DAGs and other methodological advances have been enthusiastically adopted by rising cohorts of human behavioral ecologists (e.g., Hubbard et al. 2022; Pretelli et al. 2022; Hillemann et al. 2023). Future advances will be embraced, too. Relative to other fields, HBE is generally welcoming of methodological advances, and there are abundant opportunities for early-career researchers to pioneer new and better methods. That is fortunate. On the other hand, substantial time has elapsed since Winterhalder and Smith (2000) observed that advances in HBE theory had outpaced the quality and rigor of empirical analyses. Their observation remains salient, particularly in cases when causal reasoning and statistical modeling are post hoc considerations after data have already been collected. The ideal scenario is for researchers to anticipate the causal structure and statistical models that will be needed for convincing inferences so that the research project can be designed from the outset to collect the necessary data. New methodological tools can spur enhanced research designs and theorizing. Human behavioral ecologists who invest in learning analytical methods for longitudinal data can deduce how these approaches will be pivotal for answering fundamental research questions. This foresight, in turn, provides indelible motivation for surmounting the structural obstacles to long-term, individual-based studies.

17.4

Conclusion Compared to many scientific fields, human behavioral ecology has a strong theoretical foundation. As seen throughout this volume, evolutionary principles and the logic of optimization provide a coherent framework for explaining phenotypic variation. This framework is intrinsically causal in its orientation. That is, the variation in individual-level outcomes is posited to arise from variation in key predictor variables. Causal reasoning is necessarily chronological. In other words, a predictor X that is observed at time t leads to an outcome Y at time t þ 1. Among relatively long-lived humans, these causal processes plausibly unfold over long intervals, potentially decades in some cases. Cross-sectional studies can provide valuable glimpses into these processes, but they are often limited by possible endogeneity biases, such as omitted variable biases and concerns about reverse causality. Long-term, individualbased studies are needed for stronger tests of HBE theories. Institutions and peers can help to minimize the barriers to long-term, individualbased studies. Employers and funding agencies can provide the time and resources for researchers to conduct fieldwork at regular intervals. Assessments of early-career scholars can encompass not only published works but also their progress toward the compilation of compelling long-term datasets. Mentors can encourage training in data carpentry and longitudinal statistical analysis that enable advances, as seen in

https://doi.org/10.1017/9781108377911.018 Published online by Cambridge University Press

The End of Human Behavioral Ecology

419

other scientific disciplines. Commitments to open science and ethical research and publishing choices can be rewarded. Human behavioral ecologists are uniquely positioned to contribute holistic and incredibly detailed longitudinal studies of individuals in diverse societies. Those studies will contribute to the end of human behavioral ecology, which is attainable with sustained investments.

https://doi.org/10.1017/9781108377911.018 Published online by Cambridge University Press

Bibliography

Abebe, T (2012) AIDS-affected children, family collectives and the social dynamics of care in Ethiopia. Geoforum, 43(3), 540–550. Aberle, DF (1961) Matrilineal descent in cross-cultural perspective. In D Schneider and K Gough, eds., Matrilineal Kinship, Berkeley: University of California Press, 655–727. Abernethy, KE, Allison, EH, Molloy, PP, and Côté, IM (2007) Why do fishers fish where they fish? Using the ideal free distribution to understand the behaviour of artisanal reef fishers. Canadian Journal of Fisheries and Aquatic Sciences, 64(11), 1595–1604. Abir, Y, Sklar, A, Dotsch, R, Todorov, A, and Hassin, R (2018) The determinants of consciousness of human faces. Nature Human Behaviour, 2(3), 194–199. Abrams, PA (1993) Does increased mortality favor the evolution of more rapid senescence? Evolution, 47(3), 877–887. Adair, LS, Popkin, BM, Akin, JS, . . . Hindin, MJ (2011) Cohort profile: The Cebu longitudinal health and nutrition survey. International Journal of Epidemiology, 40(3), 619–625. Adams, G, Dobles, I, Gómez, LH, Kurti¸s, T, and Molina, LE (2015) Decolonizing psychological science: Introduction to the special thematic section. Journal of Social and Political Psychology, 3(1), 213–238. Adams, J, and Nettle, D (2009) Time perspective, personality and smoking, body mass, and physical activity: An empirical study. British Journal of Health Psychology, 14(1), 83–105. Adams, RM (1966) The Evolution of Urban Society: Early Mesopotamia and Prehispanic Mexico, Chicago: Aldine. Adkins, DE, Rasmussen, KM, and Docherty, AR (2018) Social Epigenetics of Human Behavior, Oxford: Oxford University Press. Agarwal, B (1997) “Bargaining” and gender relations: Within and beyond the household. Feminist Economics, 3(1), 1–51. Akresh, R (2004) Adjusting household structure: School enrollment impacts of child fostering in Burkina Faso. SSRN. Retrieved from https://ssrn.com/ abstract=614482 Aksnes, DW, Langfeldt, L, and Wouters, P (2019) Citations, citation indicators, and research quality:

An overview of basic concepts and theories. SAGE Open, 9(1), 2158244019829575. Aktipis, A (2016) Principles of cooperation across systems: From human sharing to multicellularity and cancer. Evolutionary Applications, 9(1), 17–36. Aktipis, A, Cronk, L, Alcock, J, . . . Sullivan, D (2018) Understanding cooperation through fitness interdependence. Nature Human Behaviour, 2(7), 429–431. Aktipis, CA, Cronk, L, and de Aguiar, R (2011) Riskpooling and herd survival: An agent-based model of a Maasai gift-giving system. Human Ecology, 39(2), 131–140. Alami, S, Stieglitz, J, Gurven, M, and Kaplan, H (2018) Low perceived control over health is associated with lower treatment uptake in a high mortality population of Bolivian forager-farmers. Social Science and Medicine, 200, 156–165. Alami, S, von Rueden, C, and Seabright, E (2020) Mother’s social status is associated with child health in a horticulturalist population. Proceedings of the Royal Society B: Biological Sciences, 287(1922), 20192783. Alchian, AA, and Demsetz, H (1972) Production, information costs, and economic organization. The American Economic Review, 62(5), 777–795. Alesina, A, Giuliano, P, and Nunn, N (2013) On the origins of gender roles: Women and the plough. Quarterly Journal of Economics, 128(2), 469–530. Alexander, RD (1974) The evolution of social behavior. Annual Review of Ecology and Systematics, 5(1), 325–383. Alexander, RD (1979) Darwinism and Human Affairs, Seattle: University of Washington Press. Alexander, RD (1986) Biology and Law (M Gruter and R Masters, eds.), New York: Elsevier Science. Alexander, RD (1987) The Biology of Moral Systems, New York: Aldine de Gruyter. Alexander, RD, Noonan, KM, and Crespi, BJ (1991) The evolution of eusociality. In PW Sherman, JUM Jarvis, and RD Alexander, eds., The Biology of the Naked Mole Rat, Princeton: Princeton University Press, 3–44. Alfani, G, Fochesato, M, and Tullio, M (2020) The determinants of wealth inequality in the Republic of

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography Venice (1400–1800), CAGE Working Paper, Coventry: University of Warwick. Algaze, G (1993) Expansionary dynamics of some early pristine states. American Anthropologist, 95(2), 304–333. Alger, I, Hooper, PL, Cox, D, Stieglitz, J, and Kaplan, HS (2020) Paternal provisioning results from ecological change. Proceedings of the National Academy of Sciences, 117(20), 10746–10754. Allal, N, Sear, R, Prentice, AM, and Mace, R (2004) An evolutionary model of stature, age at first birth and reproductive success in Gambian women. Proceedings of the Royal Society B: Biological Sciences, 271(1538), 465–470. Allee, WC (1938) The Social Life of Animals, New York: W. W. Norton. Allen, MS (2010) Oscillating climate and socio-political process: The case of the Marquesan Chiefdom, Polynesia. Antiquity, 84(323), 86–102. Allen-Arave, W, Gurven, M, and Hill, K (2008) Reciprocal altruism, rather than kin selection, maintains nepotistic food transfers on an Ache reservation. Evolution and Human Behavior, 29(5), 305–318. Allman, J, McLaughlin, T, and Hakeem, A (1993) Brain weight and life-span in primate species. Proceedings of the National Academy of Sciences, 90(1), 118–122. Allman, J, Rosin, A, Kumar, R, and Hasenstaub, A (1998) Parenting and survival in anthropoid primates: Caretakers live longer. Proceedings of the National Academy of Sciences, 95(12), 6866–6869. Alonso-Alvarez, C, and Velando, A (2012) Benefits and costs of parental care. In NJ Royle, PT Smiseth, and M Kölliker, eds., The Evolution of Parental Care, Oxford: Oxford University Press, 40–61. Altmann, J, Alberts, SC, Haines, SA, . . . Bruford, MW (1996) Behavior predicts genes structure in a wild primate group. Proceedings of the National Academy of Sciences, 93(12), 5797–5801. Altmann, J, Gesquiere, L, Galbany, J, Onyango, PO, and Alberts, SC (2010) Life history context of reproductive aging in a wild primate model. Annals of the New York Academy of Sciences, 1204(1), 127–138. Altmann, SA (1979) Altruistic behaviour: The fallacy of kin deployment. Animal Behaviour, 27, 958–959. Altmann, SA, Wagner, SS, and Lenington, S (1977) Two models for the evolution of polygyny. Behavioral Ecology and Sociobiology, 2(4), 397–410. Alvarado, L, Muller, M, and Emery Thompson, M (2015) The paternal provisioning hypothesis: Effects of

421

workload and testosterone production on men’s musculature. American Journal of Physical Anthropology, 158(1), 19–35. Alvarado, LC (2013) Do evolutionary life-history tradeoffs influence prostate cancer risk? A review of population variation in testosterone levels and prostate cancer disparities. Evolutionary Applications, 6(1), 117–133. Alvard, M (2001) Mutalistic hunting. In C Stanford and H Bunn, eds., Meat Eating and Human Evolution, New York: Oxford University Press, 261–278. Alvard, M (2003a) Cooperation, evolution, and culture. Behavioral and Brain Sciences, 26(02), 153–154. Alvard, M (2004) Good hunters keep smaller shares of larger pies. Behavioral and Brain Sciences, 27(4), 560–561. Alvard, M (2011) Genetic and cultural kinship among the lamaleran whale hunters. Human Nature, 22(1–2), 89–107. Alvard, M, and Carlson, D (2020) Identifying patch types using movement data from artisanal fishers from the Commonwealth of Dominica. Current Anthropology, 61(3), 380–387. Alvard, M, and Daiy, K (2021) A naturalistic study of norm conformity, punishment, and the veneration of the dead at Texas A&M University, USA. Human Nature, 32(3), 652–675. Alvard, MS (1993) Testing the “ecologically noble savage” hypothesis: Interspecific prey choice by Piro hunters of Amazonian Peru. Human Ecology, 21(4), 355–387. Alvard, MS (2002) Carcass ownership and meat distribution by big-game cooperative hunters. Research in Economic Anthropology, 21, 99–131. Alvard, MS (2003b) Kinship, lineage, and an evolutionary perspective on cooperative hunting groups in Indonesia. Human Nature, 14(2), 129–163. Alvard, MS (2003c) The adaptive nature of culture. Evolutionary Anthropology, 12(3), 136–149. Alvard, MS, and Gillespie, A (2004) Good Lamalera whale hunters accrue reproductive benefits. Research in Economic Anthropology, 23, 225–247. Alvard, MS, and Kuznar, L (2001) Deferred harvests: The transition from hunting to animal husbandry. American Anthropologist, 103(2), 295–311. Alvard, MS, and Nolin, DA (2002) Rousseau’s whale hunt? Coordination among big-game hunters. Current Anthropology, 43(4), 533–559. Alvarez, HP (2000) Grandmother hypothesis and primate life histories. American Journal of Physical Anthropology, 113(3), 435–450.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

422

Bibliography

Alvergne, A, Faurie, C, and Raymond, M (2009a) Father– offspring resemblance predicts paternal investment in humans. Animal Behaviour, 78(1), 61–69. Alvergne, A, Faurie, C, and Raymond, M (2009b) Variation in testosterone levels and male reproductive effort: Insight from a polygynous human population. Hormones and Behavior, 56(5), 491–497. Alvergne, A, and Lummaa, V (2014) Ecological variation in wealth–fertility relationships in Mongolia: The ‘central theoretical problem of sociobiology’ not a problem after all? Proceedings of the Royal Society B: Biological Sciences, 281(1796), 20141733. Amdam, GV, and Page Jr, RE (2005) Intergenerational transfers may have decoupled physiological and chronological age in a eusocial insect. Ageing Research Reviews, 4(3), 398–408. Ames, K (2007) The archaeology of rank. In R Alexander Bentley, HDG Maschner, and C Chippindale, eds., Handbook of Archaeological Theories, New York: AltaMira, 487–513. Ames, KM (2001) Slaves, chiefs and labour on the northern Northwest Coast. World Archaeology, 33(1), 1–17. Ames, KM (2003) The northwest coast. Evolutionary Anthropology, 12(1), 19–33. Ames, KM (2004) Tempo and scale in the evolution of social complexity in western North America: Four case studies. In T Pauketat and DD Loren, eds., North American Archaeology, Oxford: Blackwell, 45–78. Andersen, S, Ertac, S, and Gneezy, U (2013) Gender, competitiveness, and socialization at a young age: Evidence from a matrilineal and a patriarchal society. The Review of Economics and Statistics, 95(4), 1438–1443. Anderson, B (1991) Imagined Communities: Reflections on the Origin and Spread of Nationalism, New York: Verso. Anderson, C, and Brown, C (2010) The functions and dysfunctions of hierarchy. Research in Organizational Behavior, 30, 55–89. Anderson, C, and Galinsky, AD (2006) Power, optimism, and risk-taking. European Journal of Social Psychology, 36(4), 511–536. Anderson, C, Hildreth, J, and Howland, L (2015) Is the desire for status a fundamental human motive? A review of the empirical literature. Psychological Bulletin, 141(3), 574–601. Anderson, KG (2000) The life histories of American stepfathers in evolutionary perspective. Human Nature, 11(4), 307–333. Anderson, KG (2006) How well does paternity confidence match actual paternity? Evidence from

worldwide nonpaternity rates. Current Anthropology, 47(3), 513–20. Anderson, KG, Kaplan, H, and Lancaster, JB (2007) Confidence of paternity, divorce, and investment in children by Albuquerque men. Evolution and Human Behavior, 28(1), 1–10. Anderson, MK (2005) Tending the Wild, Berkeley: University of California Press. Anderson, S (2007) The economics of dowry and brideprice. Journal of Economic Perspectives, 21(4), 151–174. André, J-B, and Rousset, F (2020) Does extrinsic mortality accelerate the pace of life? A bare-bones approach. Evolution and Human Behavior, 41(6), 486–492. Andreski, S (1968) Military Organization and Society, Berkeley: University of California Press. Aoki, K (1983) A quantitative genetic model of reciprocal altruism: A condition for kin or group selection to prevail. Proceedings of the National Academy of Sciences, 80(13), 4065–4068. Apicella, C (2014) Upper-body strength predicts hunting reputation and reproductive success in Hadza hunter–gatherers. Evolution and Human Behavior, 35(6), 508–518. Apicella, C, and Dreber, A (2015) Sex differences in competitiveness: Hunter-gatherer women and girls compete less in gender-neutral and male-centric tasks. Adaptive Human Behavior and Physiology, 1, 247–269. Apicella, CL, and Marlowe, FW (2004) Perceived mate fidelity and paternal resemblance predict men’s investment in children. Evolution and Human Behavior, 25(6), 371–378. Apicella, CL, Marlowe, FW, Fowler, JH, and Christakis, NA (2012) Social networks and cooperation in hunter-gatherers. Nature, 481(7382), 497–501. Apostolou, M (2007) Sexual selection under parental choice: The role of parents in the evolution of human mating. Evolution and Human Behavior, 28(6), 403–409. Apostolou, M (2010) Sexual selection under parental choice in agropastoral societies. Evolution and Human Behavior, 31(1), 39–47. Apostolou, M (2012) Sexual selection under parental choice: Evidence from sixteen historical societies. Evolutionary Psychology, 10(3), 504–518. Apostolou, M (2015) Parent-offspring conflict over mating: Domains of agreement and disagreement. Evolutionary Psychology, 13(3) 1474704915604561.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography Araújo, MS, Bolnick, DI, and Layman, CA (2011) The ecological causes of individual specialization. Ecology Letters, 14(9), 948–958. Archer, J (1988) The Behavioral Biology of Aggression, Cambridge: Cambridge University Press. Archer, J (2006) Testosterone and human aggression: An evaluation of the challenge hypothesis. Neuroscience and Biobehavioral Reviews, 30(3), 319–345. Archer, J (2019) The reality and evolutionary significance of human psychological sex differences. Biological Reviews, 94(4), 1381–1415. Ariew, A, and Lewontin, RC (2004) The confusions of fitness. The British Journal for the Philosophy of Science, 55(2), 347–363. Arndt, J, Vail III, KE, Cox, CR, Goldenberg, JL, Piasecki, TM, and Gibbons, FX (2013) The interactive effect of mortality reminders and tobacco craving on smoking topography. Health Psychology, 32(5), 525. Arnocky, S, Woodruff, N, and Schmitt, DP (2016) Men’s sociosexuality is sensitive to changes in mate availability. Personal Relationships, 23(1), 172–81. Arnold, JE (2010) The role of politically charged property in the appearance of institutionalized leadership: A view from the North American Pacific Coast. In KJ Vaughn, JW Eerkens, and J Kantner, eds., The Evolution of Leadership: Transitions in DecisionMaking from Small-Scale to Middle-Range Societies, Santa Fe: SAR Press, 121–146. Arnold, JE, Sunell, S, Nigra, BT, Bishop, KJ, Jones, T, and Bongers, J (2016) Entrenched disbelief: Complex hunter-gatherers and the case for inclusive cultural evolutionary thinking. Journal of Archaeological Method and Theory, 23(2), 448–499. Arnold, SJ (1994) Bateman’s Principles and the measurement of sexual selection in plants and animals. American Naturalist, 144, 126–149. Arnott, G, and Elwood, R (2009) Assessment of fighting ability in animal contests. Animal Behaviour, 77(5), 991–1004. Arnqvist, G, and Rowe, L (2013) Sexual Conflict, Princeton: Princeton University Press. Aronoff, J, and Crano, WD (1975) A re-examination of the cross-cultural principles of task segregation and sex role differentiation in the family. American Sociological Review, 40(1), 12–20. Askin, N, Bothner, M, and Lee, W (2015) Emergence of stratification in small groups. Emerging Trends in the Social and Behavioral Sciences. https://web.archive .org/web/20170809085910id_; https://www.esmt

423

.org/sites/default/files/digital-measures/ Stratification-1.pdf Assaad, R, Levison, D, and Zibani, N (2010) The effect of domestic work on girls’ schooling: Evidence from Egypt. Feminist Economics, 16(1), 79–128. Aswani, S, and Graves, MW (1998) The Tongan maritime expansion: A case in the evolutionary ecology of social complexity. Asian Perspectives, 37(2), 135–164. Atkisson, C, Górski, PJ, Jackson, MO, Hołyst, JA, and D’Souza, RM (2020) Why understanding multiplex social network structuring processes will help us better understand the evolution of human behavior. Evolutionary Anthropology, 29(3), 102–107. Atran, S (2002) In Gods We Trust: The Evolutionary Landscape of Religion, Oxford: Oxford University Press. Avilés, L, Fletcher, JA, and Cutter, AD (2004) The Kin composition of social groups: Trading group size for degree of altruism. The American Naturalist, 164(2), 132–144. Axelrod, R, and Hamilton, WD (1981) The evolution of cooperation. Science, 211(4489), 1390–1396. Bagwell, L, and Bernheim, B (1996) Veblen effects in a theory of conspicuous consumption. American Economic Review, 86, 349–373. Bailey, DH, Hill, KR, and Walker, RS (2014) Fitness consequences of spousal relatedness in 46 smallscale societies. Biology Letters, 10(5), 20140160. Bailey, RC, and Aunger, R (1989) Net hunters vs. archers: Variation in women’s subsistence strategies in the Ituri Forest. Human Ecology, 17(3), 273–297. Baker, MJ (2003) An equilibrium conflict model of land tenure in hunter-gatherer societies. Journal of Political Economy, 111(1), 124–173. Baldassarri, D, and Grossman, G (2011) Centralized sanctioning and legitimate authority promote cooperation in humans. Proceedings of the National Academy of Sciences, 108(27), 11023–11027. Baldassarri, D, and Grossman, G (2013) The effect of group attachment and social position on prosocial behavior. Evidence from lab-in-the-field experiments. PLoS ONE, 8, 58750. Baldini, R (2015a) Harsh environments and “fast” human life histories: What does the theory say? BioRxiv 014647. Baldini, R (2015b) The importance of population growth and regulation in human life history evolution. PLoS ONE, 10(4), e0119789. Balee, W, and Erickson, CL (2006) Time and Complexity in Historical Ecology, New York: Columbia University Press.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

424

Bibliography

Bales, K, Dietz, J, Baker, A, Miller, K, and Tardif, SD (2000) Effects of allocare-givers on fitness of infants and parents in Callitrichid primates. Folia Primatologica, 71(1–2), 27–38. Bamberger, J (1974) The myth of matriarchy: Why men rule in primitive society. In MZ Rosaldo and L Lamphere, eds., Woman, Culture, and Society, Stanford: Stanford University Press, 263–280. Barbaro, N, Mogilski, J, Shackelford, T, and Pham, M (2018) Men’s interest in allying with a previous combatant for future group conflict. Human Nature, 29, 328–336. Barclay, K, and Myrskylä, M (2014) Birth order and physical fitness in early adulthood: Evidence from Swedish military conscription data. Social Science and Medicine, 123, 141–148. Barclay, P (2004) Trustworthiness and competitive altruism can also solve the “tragedy of the commons.” Evolution and Human Behavior, 25(4), 209–220. Barclay, P (2013) Strategies for cooperation in biological markets, especially for humans. Evolution and Human Behavior, 34(3), 164–175. Barfield, TJ (1989) The Perilous Frontier: Nomadic Empires and China, Oxford: Basil Blackwell. Barfield, TJ (2001) The shadow empires: Imperial state formation along the Chinese-nomad frontier. In S Alcock, T D’Altroy, K Morrison, and C Sinopoli, eds., Empires: Perspectives from Archaeology and History, Cambridge: Cambridge University Press, 10–41. Barker, JL, Power, EA, Heap, S, Puurtinen, M, and Sosis, R (2019) Content, cost, and context: A framework for understanding human signaling systems. Evolutionary Anthropology, 27(2), 86–99. Barkow, JH (1989) Darwin, Sex, and Status, Toronto: University of Toronto Press. Barkow, JH, Cosmides, L, and Tooby, J, eds. (1992) The Adapted Mind: Evolutionary Psychology and the Generation of Culture, Oxford: Oxford University Press. Barlow, KR (2002) Predicting maize agriculture among the Fremont: An economic comparison of farming and foraging in the American Southwest. American Antiquity, 67(1), 65–88. Barnum, H, and Squire, L (1979) A Model of an Agricultural Household: Theory and Evidence. Baltimore: Johns Hopkins University Press. Barr, WA, Pobiner, B, Rowan, J, Du, A, and Faith, JT (2022) No sustained increase in zooarchaeological evidence for carnivory after the appearance of Homo

erectus. Proceedings of the National Academy of Sciences, 119(5), e2115540119. Barrett, HC (2009) Where there is an adaptation, there is a domain: The form-function fit in information processing. In SN Platek and TK Shackelford, eds., Foundations in Evolutionary Cognitive Neuroscience, Cambridge: Cambridge University Press, 97–116. Barrett, HC (2015) The Shape of Thought: How Mental Adaptations Evolve, Oxford: Oxford University Press. Barrett, HC (2018) The varieties of foraging experience. Evolutionary Behavioral Sciences, 12(3), 135–138. Barrett, HC (2020a) Deciding what to observe: Thoughts for a post-WEIRD generation. Evolution and Human Behavior, 41(5), 445–453. Barrett, HC (2020b) Towards a cognitive science of the human: Cross-cultural approaches and their urgency. Trends in Cognitive Sciences, 24(8), 620–638. Barrett, HC (2022) Psychology within and without the state. Annual Review of Psychology, 73, 461–487. Barrett, HC, Bolyanatz, A, Broesch, T, . . . Laurence, S (2021) Intuitive dualism and afterlife beliefs: A cross-cultural study. Cognitive Science, 45(6), e12992. Barrett, HC, Bolyanatz, A, Crittenden, AN, . . . Pisor, A (2016) Small-scale societies exhibit fundamental variation in the role of intentions in moral judgment. Proceedings of the National Academy of Sciences, 113(17), 4688–4693. Barrett, L, Dunbar, R, and Lycett, J (2002) Human Evolutionary Psychology, Princeton: Princeton University Press. Barry, H (2007) Customs associated with premarital sexual freedom in 143 societies. Cross-Cultural Research, 41(3), 261–272. Barry, H, and Paxson, LM (1971) Infancy and early childhood: Cross-cultural codes 2. Ethnology, 10(4), 466–508. Barth, F (1959) Political Leadership among Swat Pathans, London: Athlone Press. Barth, F (1961) Nomads of South Persia, Boston: Little, Brown. Barth, F, ed. (1978) Scale and Social Organization, Oslo: Universitetsforl. Barth, F (1998) Ethnic Groups and Boundaries: The Social Organization of Culture Difference, Long Grove, IL: Waveland Press. Bastardoz, N, and van Vugt, M (2019) The nature of followership: Evolutionary analysis and review. Leadership Quarterly, 30(1), 81–95.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography Bateman, AJ (1948) Intra-sexual selection in Drosophila. Heredity, 2(Pt. 3), 349–368. Bates, DG (2005) Human Adaptive Strategies: Ecology, Culture and Politics, 3rd edn, Boston: Allyn & Bacon. Bateson, P, and Laland, KN (2013) Tinbergen’s four questions: An appreciation and an update. Trends in Ecology and Evolution, 28, 712–718. Batini, C, and Jobling, M (2017) Detecting past malemediated expansions using the Y chromosome. Human Genetics, 136, 547–557. Baudisch, A (2005) Hamilton’s indicators of the force of selection. Proceedings of the National Academy of Sciences, 102, 8263–8268. Baumard, N, Andre, JB, and Sperber, D (2013) A mutualistic approach to morality: The evolution of fairness by partner choice. Behavioral and Brain Sciences, 36, 59–78. Beaujouan, E, and Berghammer, C (2019) The gap between lifetime fertility intentions and completed fertility in Europe and the United States: A cohort approach. Population Research and Policy Review, 38(4), 507–535. Becker, A (2021) On the economic origins of restricting women’s promiscuity. Review of Economic Studies. Becker, GS (1976) The Economic Approach to Human Behavior, Chicago: University of Chicago Press. Becker, GS (1981) A Treatise on the Family, Cambridge: Harvard University Press. Becker, GS (1985) Human capital, effort, and the sexual division of labor. Journal of Labor Economics, 3, S33–S58. Becker, GS, and Tomes, N (1986) Human capital and the rise and fall of families. Journal of Labor Economics, 4(3), 1–39. Beckerman, S (1983) Carpe diem: An optimal foraging approach to Bari fishing and hunting. In RB Hames and WT Vickers, eds., Adaptive Strategies of Native Amazonians, New York: Academic Press, 269–299. Beckerman, S, Lizarralde, R, Ballew, C, . . . Smith, H (1998) The Barí partible paternity project: Preliminary results. Current Anthropology, 39(1), 164–168. Beckerman, S, and Valentine, P, eds. (2002) Cultures of Multiple Fathers: The Theory and Practice of Partible Paternity in Lowland South America, Gainesville: University Press of Florida. Beheim, B, Atkinson, QD, Bulbulia, J, . . . Willard, AK (2021) Treatment of missing data determined conclusions regarding moralizing gods. Nature, 595 (7866), E29–E34.

425

Beheim, BA, and Baldini, R (2012) Evolutionary decomposition and the mechanisms of cultural change. Cliodynamics, 3(2), 217–233. Behrens, C (1992) Labor specialization and the formation of markets for food in a Shipibo subsistence economy. Human Ecology, 20(4), 435–462. Beise, J, and Voland, E (2008) Intrafamilial resource competition and mate competition shaped socialgroup-specific natal dispersal in the 18th and 19th century Krummhörn population. American Journal of Human Biology, 20(3), 325–336. Beitl, CM (2015) Mobility in the mangroves: Catch rates, daily decisions, and dynamics of artisanal fishing in a coastal commons. Applied Geography, 59, 98–106. Bell, AV, Currie, TE, Irwin, G, and Bradbury, C (2015) Driving factors in the colonization of Oceania: Developing island-level statistical models to test competing hypotheses. American Antiquity, 80(2), 397–407. Bell, AV, Richerson, PJ, and McElreath, R (2009) Culture rather than genes provides greater scope for the evolution of large-scale human prosociality. Proceedings of the National Academy of Sciences, 106, 17671–17674. Bell, AV, and Winterhalder, B (2014) The population ecology of despotism: Concessions and migration between central and peripheral habitats. Human Nature, 25(1), 121–135. Bell, NW, and Vogel, EF, eds. (1960) A Modern Introduction to the Family, Glencoe: Free Press. Belsky, J, Schlomer, GL, and Ellis, BJ (2012) Beyond cumulative risk: Distinguishing harshness and unpredictability as determinants of parenting and early life history strategy. Developmental Psychology, 48(3), 662–673. Belsky, J, Steinberg, L, and Draper, P (1991) Childhood experience, interpersonal development, and reproductive strategy: An evolutionary theory of socialization. Child Development, 62(4), 647–670. Bender, A, and Beller, S (2011) The cultural constitution of cognition: Taking the anthropological perspective. Frontiers in Psychology, 2(67), 1–6. Benenson, J, and Abadzi, H (2019) Contest versus scramble competition: Sex differences in the quest for status. Current Opinion in Psychology, 33, 62–68. Benenson, J, Kuhn, M, and Ryan, P (2014) Human males appear more prepared than females to resolve conflicts with same-sex peers. Human Nature, 25, 251–268.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

426

Bibliography

Benenson, J, and Markovits, H (2014) Warriors and Worriers: The Survival of the Sexes, Oxford: Oxford University Press. Benenson, J, White, M, and Pandiani, D (2018) Competition elicits more physical affiliation between male than female friends. Scientific Reports, 8, 8380. Benshoof, L, and Thornhill, R (1979) The evolution of monogamy and concealed ovulation in humans. Journal of Social and Biological Systems, 2(2), 95–106. Bentley, GR, Jasienska, G, and Goldberg, T (1993) Is the fertility of agriculturalists higher than that of nonagriculturalists? Current Anthropology, 34(5), 778–785. BenYishay, A, Grosjean, P, and Vecci, J (2017) The fish is the friend of matriliny: Reef density and matrilineal inheritance. Journal of Development Economics, 127(C), 234–249. Berdahl, J, and Anderson, C (2005) Men, women, and leadership centralization in groups over time. Group Dynamics: Theory, Research, and Practice, 9(1), 45–57. Bereczkei, T (1998) Kinship network, direct childcare, and fertility among Hungarians and Gypsies. Evolution and Human Behavior, 19(5), 283–298. Bereczkei, T, and Dunbar, RIM (1997) Female-biased reproductive strategies in a Hungarian gypsy population. Proceedings of the Royal Society B: Biological Sciences, 264(1378), 17–22. Bereczkei, T, and Dunbar, RIM (2002) Helping-at-thenest and sex-biased parental investment in a Hungarian gypsy population. Current Anthropology, 43(5), 804–809. Berent, I (2020) The Blind Storyteller: How We Reason About Human Nature, Oxford: Oxford University Press. Bergmüller, R, Johnstone, RA, Russell, AF, and Bshary, R (2007) Integrating cooperative breeding into theoretical concepts of cooperation. Behavioural Processes, 76(2), 61–72. Bergstrom, CT, and Real, LA (2000) Toward a theory of mutual mate choice: Lessons from two-sided matching. Evolutionary Ecology Research, 2, 493–508. Berl, REW, and Hewlett, BS (2015) Cultural variation in the use of overimitation by the Aka and Ngandu of the Congo Basin. PLoS ONE, 10(3), 0120180. Bernard, HR, Killworth, P, Kronenfeld, D, and Sailer, L (1984) The problem of informant accuracy: The validity of retrospective data. Annual Review of Anthropology, 13, 495–517.

Bernardi, F, and Boertien, D (2016) Understanding heterogeneity in the effects of parental separation on educational attainment in Britain: Do children from lower educational backgrounds have less to lose? 32(6), 807–819. Bernhard, H, Fischbacher, U, and Fehr, E (2006) Parochial altruism in humans. Nature, 442(7105), 912–915. Bettencourt, LMA (2013) The origins of scaling in cities. Science, 340(6139), 1438–1441. Bettencourt, LMA, Lobo, J, Helbing, D, Kühnert, C, and West, GB (2007) Growth, innovation, scaling, and the pace of life in cities. Proceedings of the National Academy of Sciences, 104(17), 7301–7306. Bettinger, RL, Winterhalder, B, and McElreath, R (2006) A simple model of technological intensification. Journal of Archaeological Science, 33(4), 538–545. Betzig, L (1986) Despotism and Differential Reproduction: A Darwinian View of History, New York: Aldine. Betzig, L (1988) Redistribution: Equity or exploitation? In L Betzig, M Borgerhoff Mulder, and P Turke, eds., Human Reproductive Behaviour: A Darwinian Perspective, Cambridge: Cambridge University Press, 49–64. Betzig, L (1989) Causes of conjugal dissolution: A crosscultural study. Current Anthropology, 30(5), 654–676. Betzig, L (2012) Means, variances, and ranges in reproductive success: Comparative evidence. Evolution and Human Behavior, 33(4), 309–317. Betzig, LL, and Turke, PW (1986) Food sharing on Ifaluk. Current Anthropology, 27(4), 397–400. Bevc, I, and Silverman, I (2000) Early separation and sibling incest: A test of the revised Westermarck theory. Evolution and Human Behavior, 21(3), 151–161. Bhalotra, S, and Heady, C (2003) Child farm labour: The wealth paradox. The World Bank Economic Review, 17(2), 197–227. Bhaskar, V (2000) Egalitarianism and efficiency in repeated symmetric games. Games and Economic Behavior, 32(2), 247–262. Bianchi, SM (2011) Family change and time allocation in American families. The Annals of the American Academy of Political and Social Science, 638(1), 21–44. Bickel, WK, Odum, AL, and Madden, GJ (1999) Impulsivity and cigarette smoking: Delay discounting in current, never, and ex-smokers. Psychopharmacology, 146(4), 447–454.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography Bik, EM, Casadevall, A, and Fang, FC (2016) The prevalence of inappropriate image duplication in biomedical research publications. MBio, 7(3), e00809-16. Billman, BR (2002) Irrigation and the origins of the southern Moche state on the north coast of Peru. Latin American Antiquity, 13(4), 371–400. Binford, LF (2001) Constructing Frames of Reference: An Analytical Method for Archaeological Theory Building Using Ethnographic and Environmental Data Sets, Berkeley: University of California Press. Binmore, KG (1998) The evolution of fairness norms. Rationality and Society, 10(3), 275–301. Bird, DW, and Bliege Bird, R (2000) The ethnoarchaeology of juvenile foragers: Shellfishing strategies among Meriam children. Journal of Anthropological Archaeology, 19(4), 461–476. Bird, DW, and Bliege Bird, R (2002) Children on the reef. Human Nature, 13(2), 269–297. Bird, DW, Bliege Bird, R, and Codding, BF (2009) In pursuit of mobile prey: Martu hunting strategies and archaeofaunal interpretation. American Antiquity, 74(1), 3–29. Bird, DW, Bliege Bird, R, Codding, BF, and Zeanah, DW (2019) Variability in the organization and size of hunter-gatherer groups: Foragers do not live in small-scale societies. Journal of Human Evolution, 131, 96–108. Bird, DW, Bliege Bird, R, and Richardson, JL (2004) Meriam ethnoarchaeology: Shellfishing and shellmiddens. Memoirs of the Queensland Museum of Culture, 3(1), 183. Bird, DW, and Bliege Bird, RL (1997) Contemporary shellfish gathering strategies among the Meriam of the Torres Strait Islands, Australia: Testing predictions of a central place foraging model. Journal of Archaeological Science, 24(1), 39–63. Bird, DW, Codding, BF, Bliege Bird, R, Zeanah, DW, and Taylor, CJ (2013) Megafauna in a continent of small game: Archaeological implications of Martu camel hunting in Australia’s Western Desert. Quaternary International, 297, 155–166. Bird, DW, and O’Connell, JF (2006) Behavioral ecology and archaeology. Journal of Archaeological Research, 14(2), 143–188. Bird, DW, Richardson, JL, Veth, PM, and Barham, AJ (2002) Explaining shellfish variability in middens on the Meriam Islands, Torres Strait, Australia. Journal of Archaeological Science, 29(5), 457–469. Biro, PA, and Stamps, JA (2008) Are animal personality traits linked to life-history productivity? Trends in Ecology & Evolution, 23(7), 361–368.

427

Biroli, P, Boneva, T, Raja, A, and Rauh, C (2022) Parental beliefs about returns to child health investments. Journal of Econometrics, 231(1), 33–57. Bissonnette, A, Perry, S, and Barrett, L (2015) Coalitions in theory and reality: A review of pertinent variables and processes. Behaviour, 152, 1–56. Bittles, AH, and Black, ML (2010a) Consanguineous marriage and human evolution. Annual Review of Anthropology, 39, 193–207. Bittles, AH, and Black, ML (2010b) Consanguinity, human evolution, and complex diseases. Proceedings of the National Academy of Sciences, 107(suppl. 1), 1779–1786. Bittles, AH, Mason, WM, Greene, J, and Rao, NA (1991) Reproductive behavior and health in consanguineous marriages. Science, 252(5007), 789–794. Black, J (1996) Partnerships in Birds: The Study of Monogamy, Oxford: Oxford University Press. Blackwell, AD (2009) Life history trade-offs in growth and immune function: The behavioral and immunological ecology of the Shuar of Amazonian Ecuador, an indigenous population in the midst of rapid economic and ecological change (PhD Dissertation), University of Oregon. Blackwell, AD (2018) Childhood conditions set the balance. Nature Ecology and Evolution, 2, 1061–1062. Blackwell, AD, Pryor, G, Pozo, J, Tiwia, W, and Sugiyama, LS (2009) Growth and market integration in Amazonia: A comparison of growth indicators between Shuar, Shiwiar, and nonindigenous school children. American Journal of Human Biology, 21(2), 161–171. Blackwell, AD, Snodgrass, JJ, Madimenos, FC, and Sugiyama, LS (2010) Life history, immune function, and intestinal helminths: Trade-offs among immunoglobulin E, C-reactive protein, and growth in an Amazonian population. American Journal of Human Biology, 22, 836–48. Blackwell, AD, Trumble, BC, Maldonado Suarez, I, . . . Gurven, M (2016) Immune function in Amazonian horticulturalists. Annals of Human Biology, 43(6), 382–396. Blackwell, AD, Urlacher, SS, Beheim, B, . . . Kaplan, H (2017) Growth references for Tsimane foragerhorticulturalists of the Bolivian Amazon. American Journal of Physical Anthropology, 162(3), 441–461. Blake, K, Bastian, B, Denson, T, Grosjean, P, and Brooks, R (2018) Income inequality not gender inequality positively covaries with female sexualization on social media. Proceedings of the National Academy of Sciences USA, 115, 8722–8727.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

428

Bibliography

Blake, PR, McAuliffe, K, Callaghan, T, . . . H, V (2015) The ontogeny of fairness in seven societies. Nature, 528, 258–261. Blanchard, TC, Wilke, A, and Hayden, BY (2014) Hothand bias in rhesus monkeys. Journal of Experimental Psychology: Animal Learning and Cognition, 40(3), 280–286. Blanton, RE (1998) Beyond centralization: Steps toward a theory of egalitarian behavior. In GM Feinman and J Marcus, eds., Archaic States, Santa Fe: SAR Press, 135–172. Blau, P (1964) Exchange and Power in Social Life, New York: John Wiley & Sons. Bledsoe, C (1980) The manipulation of Kpelle social fatherhood. Ethnology, 19(1), 29–45. Bledsoe, C, Banja, F, and Hill, AG (1998) Reproductive mishaps and western contraception: An African challenge to fertility theory. Population and Development Review, 24(1), 15–57. Bliege Bird, R (1999) Cooperation and conflict: The behavioral ecology of the sexual division of labor. Evolutionary Anthropology, 8(2), 65–75. Bliege Bird, R (2007) Fishing and the sexual division of labor among the Meriam. American Anthropologist, 109(3), 442–451. Bliege Bird, R (2015) Disturbance, complexity, scale: New approaches to the study of human–environment interactions. Annual Review of Anthropology, 44, 241–257. Bliege Bird, R, and Bird, D (1997) Delayed reciprocity and tolerated theft. Current Anthropology, 38(1), 49. Bliege Bird, R, and Bird, DW (2002) Constraints of knowing or constraints of growing? Fishing and collecting by the children of Mer. Human Nature, 13(2), 239–267. Bliege Bird, R, and Bird, DW (2008) Why women hunt: Risk and contemporary foraging in a Western Desert aboriginal community. Current Anthropology, 49(4), 655–693. Bliege Bird, R, and Bird, DW (2021) Climate, landscape diversity, and food sovereignty in arid Australia: The firestick farming hypothesis. American Journal of Human Biology, 33(4), e23527. Bliege Bird, R, Bird, DW, Codding, BF, Parker, CH, and Jones, JH (2008) The “fire stick farming” hypothesis: Australian Aboriginal foraging strategies, biodiversity, and anthropogenic fire mosaics. Proceedings of the National Academy of Sciences, 105(39), 14796–14801. Bliege Bird, R, Bird, DW, Smith, EA, and Kushnick, GC (2002) Risk and reciprocity in Meriam food sharing. Evolution and Human Behavior, 23(4), 297–321.

Bliege Bird, R, and Codding, BF (2015) The sexual division of labor. In RA Scott and MC Buchmann, eds., Emerging Trends in the Social and Behavioral Sciences, John Wiley & Sons, 1–16. Bliege Bird, R, Codding, BF, and Bird, DW (2009) What explains differences in men’s and women’s production? Human Nature, 20(2), 105–129. Bliege Bird, R, McGuire, C, Bird, DW, Price, MH, Zeanah, D, and Nimmo, DG (2020) Fire mosaics and habitat choice in nomadic foragers. Proceedings of the National Academy of Sciences, 117(23), 12904–12914. Bliege Bird, R, and Power, E (2015) Prosocial signaling and cooperation among Martu hunters. Evolution and Human Behavior, 36(5), 389–397. Bliege Bird, R, Ready, E, and Power, EA (2018) The social significance of subtle signals. Nature Human Behaviour, 2, 452–457. Bliege Bird, R, Scelza, B, Bird, DW, and Smith, EA (2012) The hierarchy of virtue: Mutualism, altruism and signaling in Martu women’s cooperative hunting. Evolution and Human Behavior, 33(1), 64–78. Bliege Bird, R, and Smith, E (2005) Signaling theory, strategic interaction, and symbolic capital. Current Anthropology, 46(2), 221–248. Bliege Bird, R, Smith, E, and Bird, DW (2001) The hunting handicap: Costly signaling in human foraging strategies. Behavioral Ecology and Sociobiology, 50(1), 9–19. Bliege Bird, R, Tayor, N, Codding, BF, and Bird, DW (2013) Niche construction and dreaming logic: Aboriginal patch mosaic burning and varanid lizards (Varanus gouldii) in Australia. Proceedings of the Royal Society B: Biological Sciences, 280(1772), 20132297. Bloom, P (2007) Religion is natural. Developmental Science, 10(1), 147–151. Blurton Jones, N (1984) A selfish origin for human food sharing: Tolerated theft. Ethology and Sociobiology, 5(1), 1–3. Blurton Jones, N (1986) Bushman birth spacing: A test for optimal interbirth intervals. Ethology and Sociobiology, 7(2), 91–105. Blurton Jones, N (1987) Bushman birth spacing: Direct tests of some simple predictions. Ethology and Sociobiology, 8(3), 183–203. Blurton Jones, N (2016) Demography and Evolutionary Ecology of Hadza Hunter-Gatherers, Cambridge: Cambridge University Press. Blurton Jones, N, Hawkes, K, and Draper, P (1994a) Differences between Hadza and !Kung children’s

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography work: Affluence or practical reason. In ES Burch and LJ Ellana, eds., Key Issues in Hunter-Gatherer Research, Berg: Oxford Press, 189–215. Blurton Jones, N, Hawkes, K, and Draperq, P (1994b) Foraging returns of !Kung adults and children: Why didn’t !Kung children forage? Journal of Anthropological Research, 50(3), 217–248. Blurton Jones, N, Hawkes, K, and O’Connell, JF (1989a) Measuring and modeling costs of children in two foraging societies: Implications for schedule of reproduction. In V Standen and R Foley, eds., Comparative Socioecology: The Behavorial Ecology of Humans and Other Mammals, Oxford: Blackwell Scientific Publications, 367–390. Blurton Jones, N, Marlowe, F, Hawkes, K, and O’Connell, J (2000) Hunter-gatherer divorce rates and the paternal investment theory of human pair-bonding. In L Cronk, N Chagnon, and W Irons, eds., Adaptation and Human Behavior: An Anthropological Perspective, New York: Aldine, 69–90. Blurton Jones, NG, Hawkes, K, and O’Connell, JF (1989b) Modelling and measuring costs of children in two foraging societies. In V. Standen, ed., Comparative Socioecology of Humans and Other Mammals, London: Basil Blackwell. Bobak, M, Pikhart, H, Rose, R, Hertzman, C, and Marmot, M (2000) Socioeconomic factors, material inequalities, and perceived control in self-rated health: Cross-sectional data from seven post-communist countries. Social Science and Medicine, 51(9), 1343–1350. Bock, J (2002) Learning, life history and productivity: Children’s lives in the Okavango Delta, Botswana. Human Nature, 13(2), 161–197. Boddy, AM, Kokko, H, Breden, F, Wilkinson, GS, and Aktipis, CA (2015) Cancer susceptibility and reproductive trade-offs: A model of the evolution of cancer defences. Philosophical Transactions of the Royal Society B: Biological Sciences, 370(1673), 20140220. Boehm, C (1993) Egalitarian behavior and reverse dominance hierarchy. Current Anthropology, 34(3), 227–254. Boehm, C (1999) Hierarchy in the Forest: The Evolution of Egalitarian Behavior, Cambridge: Harvard University Press. Boehm, C (2016) Bullies: Redefining the human freerider problem. In J Carroll, D McAdams, and EO Wilson, eds., Darwin’s Bridge: Uniting the Humanities and Sciences, Oxford: Oxford University Press, 11–28.

429

Bogaard, A, Fochesato, M, and Bowles, S (2019) The farming-inequality nexus: New insights from ancient Western Eurasia. Antiquity, 93(371). www .sciencedirect.com/science/article/pii/ S1048984318302364. Boggild, T (2020) Cheater detection in politics: Evolution and citizens’ capacity to hold political leaders accountable. The Leadership Quarterly, 31(2), 101268. Bogin, B (1997) Evolutionary hypotheses for human childhood. American Journal of Physical Anthropology, 104(S25), 63–89. Bogin, B (2009) Childhood, adolescence, and longevity: A multilevel model of the evolution of reserve capacity in human life history. American Journal of Human Biology, 21(4), 567–577. Bogin, B, and Smith, BH (1996) Evolution of the human life cycle. American Journal of Human Biology, 8(6), 703–716. Bohannan, P, and Bohannan, L (1968) Tiv Economy, Evanston: Northwestern University Press. Boixadera, J, Esteban, I, Albert, RM, and Poch, RM (2019) Anthropogenic soils from Llanos de Moxos (Bolivia): Soils from pre-Columbian raised fields. Catena, 172, 21–39. Bolnick, DI, Svanbäck, R, Fordyce, JA, . . . Forister, ML (2003) The ecology of individuals: Incidence and implications of individual specialization. The American Naturalist, 161(1), 1–28. Bolton, P, and Dewatripont, M (2005) Contract Theory, Cambridge: MIT Press. Bongaarts, J (1978) A framework for analysing the proximate determinants of fertility. Population and Development Review, 4(1), 105–132. Bonte, W (2015) Gender differences in competitive preferences: New cross-country empirical evidence. Applied Economics Letters, 22, 71–75. Boomgarden, S, A., M, D., and Simons, ET (2019) An optimal irrigation model: Theory, experimental results, and implications for future research. American Antiquity, 84(2), 252–273. Boomsma, JJ (2007) Kin selection versus sexual selection: Why the ends do not meet. Current Biology, 17, R673–R683. Boomsma, JJ (2009) Lifetime monogamy and the evolution of eusociality. Philosophical Transactions of the Royal Society B: Biological Sciences, 364(1533), 3191–3207. Boomsma, JJ (2013) Beyond promiscuity: Mate-choice commitments in social breeding. Philosophical Transactions of the Royal Society of London B: Biological Sciences, 368(1613), 20120050.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

430

Bibliography

Boone, JL (1986) Parental investment and elite family structure in preindustrial states: A case study of late medieval-early modern Portuguese genealogies. American Anthropologist, 88(4), 859–878. Boone, JL (1988) Parental investment, social subordination and population processes among the fifteen and sixteen century Portuguese nobility. In L Betzig, M Borgerhoff Mulder, and P Turke, eds., Human Reproductive Behavior: A Darwinian Perspective, Cambridge: Cambridge University Press, 201–219. Boone, JL (1992) Competition, conflict, and the development of social hierarchies. In EA. Smith and B Winterhalder, eds., Evolutionary Ecology and Human Behavior, New York: Aldine de Gruyter, 301–337. Boone, JL (1998) The evolution of magnanimity: When is it better to give than to receive? Human Nature, 9, 1–21. Borgerhoff Mulder, M (1987) Resources and reproductive success in women with an example from the Kipsigis of Kenya. Journal of Zoology, 213, 489–505. Borgerhoff Mulder, M (1988a) Is the polygyny threshold model relevant to humans? Kipsigis evidence. In CGN Mascie-Taylor and AJ Boyce, eds., Mating Patterns, Cambridge: Cambridge University Press, 209–230. Borgerhoff Mulder, M (1988b) Reproductive success in three Kipsigis cohorts. Reproductive Success. In TH Clutton Brock, ed., Reproductive Success: Studies of Individual Variation, Chicago: University of Chicago Press, 419–438. Borgerhoff Mulder, M (1990) Kipsigis women’s preferences for wealthy men: Evidence for female choice in mammals? Behavioral Ecology and Sociobiology, 27(4), 255–264. Borgerhoff Mulder, M (1991) Human behavioural ecology. In JR Krebs and N B. Davies, eds., Behavioural Ecology: An Evolutionary Approach, Oxford: Blackwell, 69–98. Borgerhoff Mulder, M (1992a) Reproductive decisions. In EA Smith and B Winterhalder, eds., Evolutionary Ecology and Human Behavior, New York: Aldine de Gruyter, 339–374. Borgerhoff Mulder, M (1992b) Women’s strategies in polygynous marriage. Kipsigis, Datoga, and other East African cases. Human Nature, 3(1), 45–70. Borgerhoff Mulder, M (1998a) Brothers and sisters: How sibling interactions affect optimal parental allocations. Human Nature, 9(2), 119–61. Borgerhoff Mulder, M (1998b) The demographic transition: Are we any closer to an evolutionary

explanation? Trends in Ecology and Evolution, 13, 266–270. Borgerhoff Mulder, M (2004) Are men and women really so different? Trends in Ecology and Evolution, 19(1), 3–6. Borgerhoff Mulder, M (2009) Serial monogamy as polygyny or polyandry? Human Nature, 20(2), 130–50. Borgerhoff Mulder, M (2013) Human behavioral ecology – necessary but not sufficient for the evolutionary analysis of human behavior. Behavioral Ecology, 24(5), 1042–1043. Borgerhoff Mulder, M, and Beheim, B (2011) Understanding the nature of wealth and its effects on human fitness. Proceedings of the Royal Society B: Biological Sciences, 366(1563), 344–356. Borgerhoff Mulder, M, Bowles, S, Hertz, T, . . . Hooper, PL (2009) Intergenerational wealth transmission and the dynamics of inequality in small-scale societies. Science, 326(5953), 682–688. Borgerhoff Mulder, M, Fazzio, I, Irons, W, and Hazzah, L (2010) Pastoralism and wealth inequality: Revisiting an old question. Current Anthropology, 51(1), 35–48. Borgerhoff Mulder, M, George-Cramer, M, Eshleman, J, and Ortolani, A (2001) A study of East African kinship and marriage using a phylogenetically based comparative method. American Anthropologist, 103(4), 1059–1082. Borgerhoff Mulder, M, and Ross, CT (2019) Unpacking mating success and testing Bateman’s Principles in a human population. Proceedings of the Royal Society B: Biological Sciences, 286(1908), 20191516. Borgerhoff Mulder, M, McElreath, R, and Schroeder, KB (2006) Analogies are powerful and dangerous things. Behavioral and Brain Sciences, 29(4), 350–351. Borgerhoff Mulder, M, and Rauch, KL (2009) Sexual conflict in humans: Variations and solutions. Evolutionary Anthropology, 18(5), 201–14. Borgerhoff Mulder, M, and Sellen, DW (1994) Pastoralist decision making: A behavioral ecological perspective. In E Fratkin, KA Galvin, and EA Roth, eds., African Pastoralist Systems: An Integrated Approach, Boulder: Lynne Rienner, 205–229. Borghesi, J, Mario, LC, Rodrigues, MN, Favaron, PO, and Miglino, MA (2014) Immunoglobulin transport during gestation in domestic animals and humans: A review. Open Journal of Animal Sciences, 04(5), 323–336. Boserup, E (2017 [1965]) The Conditions of Agricultural Growth: The Economics of Agrarian Change under Population Pressure, New York: Routledge.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography Boster, J (1984) Inferring decision making from preferences and behavior. Human Ecology, 12(4), 343–358. Bothner, M, Hayes, R, Lee, W, and Smith, E (2010) When do Matthew effects occur? The Journal of Mathematical Sociology, 34(2), 80–114. Bourget, D, Grace, J, and Whitehurst, L (2007) A review of maternal and paternal filicide. Journal of the American Academy of Psychiatry Law, 35(1), 74–82. Bove, RB, Valeggia, CR, and Ellison, PT (2002) Girl helpers and time allocation of nursing women among the Toba of Argentina. Human Nature, 13(4), 457–472. Bovet, J, Raiber, E, Ren, W, Wang, C, and Seabright, P (2018) Parent-offspring conflict over mate choice: An experimental study in China. British Journal of Psychology, 109(4), 674–693. Bowles, S (2004) Microeconomics: Behavior, Institutions, and Evolution, Princeton: Princeton University Press. Bowles, S (2006) Group competition, reproductive leveling, and the evolution of human altruism. Science, 314(5805), 1569–1572. Bowles, S (2011) Cultivation of cereals by the first farmers was not more productive than foraging. Proceedings of the National Academy of Sciences, 108(12), 4760–4765. Bowles, S, and Choi, J-K (2013) Coevolution of farming and private property during the early Holocene. Proceedings of the National Academy of Sciences, 110(22), 8830–8835. Bowles, S, and Gintis, H (1998) The moral economy of communities: Structured populations and the evolution of pro-social norms. Evolution and Human Behavior, 19(1), 3–25. Bowles, S, and Gintis, H (2002a) Social capital and community governance. Economic Journal, 112(483), 419–436. Bowles, S, and Gintis, H (2002b) The inheritance of inequality. Journal of Economic Perspectives, 16(3), 3–30. Bowles, S, and Gintis, H (2011) A Cooperative Species, Princeton: Princeton University Press. Bowser, B, and Patton, J (2010) Women’s leadership: Political alliance, economic resources, and reproductive success in the Ecuadorian Amazon. In KJ Vaughn, JW Eerkens, and J Kantner, eds., The Evolution of Leadership: Transitions in Decision Making from Small-Scale to Middle-Range Societies, Santa Fe: SAR Press, 51–71. Box, GEP (1976) Science and statistics. Journal of the American Statistical Association, 71, 791–799.

431

Boyd, R (2003) The evolution of altruistic punishment. Proceedings of the National Academy of Sciences, 100, 3531–3535. Boyd, R, Gintis, H, Bowles, S and Richerson, PJ (2003) The evolution of altruistic punishment. Proceedings of the National Academy of Sciences, 100, 3531–3535. Boyd, R (2006) Reciprocity: You have to think different. Journal of Evolutionary Biology, 19(5), 1380–1382. Boyd, R, Gintis, H, and Bowles, S (2010) Coordinated punishment of defectors sustains cooperation and can proliferate when rare. Science, 328(5978), 617–620. Boyd, R, and Richerson, P (1976) Simple dual inheritance model of conflict between social and biological evolution. Zygon, 11(3), 254–262. Boyd, R, and Richerson, PJ (1985) Culture and the Evolutionary Process, Chicago: University of Chicago Press. Boyd, R, and Richerson, PJ (1987) The evolution of ethnic markers. Cultural Anthropology, 2, 65–79. Boyd, R, and Richerson, PJ (1988) The evolution of reciprocity in sizable groups. Journal of Theoretical Biology, 132(3), 337–356. Boyd, R, and Richerson, PJ (1990) Group selection among alternative evolutionarily stable strategies. Journal of Theoretical Biology, 145(3), 331–342. Boyd, R, and Richerson, PJ (1992) Punishment allows the evolution of cooperation (or anything else) in sizable groups. Ethology and Sociobiology, 13(3), 171–195. Boyd, R, and Richerson, PJ (1995) Why does culture increase human adaptability? Ethology and Sociobiology, 16, 125–143. Boyd, R, and Richerson, PJ (1996) Why culture is common, but cultural evolution is rare. ProceedingsBritish Academy, 88, 77–94. Boyd, R, and Richerson, PJ (2002) Group beneficial norms can spread rapidly in a structured population. Journal of Theoretical Biology, 215, 287–296. Boyd, R, and Richerson, PJ (2005) The Origin and Evolution of Cultures, Oxford University Press. Boyd, R, and Richerson, PJ (2009a) Culture and the evolution of human cooperation. Philosophical Transactions of the Royal Society B: Biological Sciences, 364(1533), 3281–3288. Boyd, R, and Richerson, PJ (2009b) Voting with your feet: Payoff biased migration and the evolution of group beneficial behavior. Journal of Theoretical Biology, 257(2), 331–339. Boyd, R, and Richerson, PJ (2010) Transmission coupling mechanisms: Cultural group selection. Philosophical Transactions of the Royal Society B: Biological Sciences, 365, 3787–3795.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

432

Bibliography

Boyd, R, Schonmann, R, and Vicente, R (2014) Huntergatherer population structure and the evolution of contingent cooperation. Evolution and Human Behavior, 35(3), 219–227. Boyer, P (1994) The Naturalness of Religious Ideas: A Cognitive Theory of Religion, Berkeley: University of California Press. Boyette, A, Lew-Levy, S, and Gettler, L (2018) Dimensions of fatherhood in a Congo basin village: A multimethod analysis of intracultural variation in men’s parenting and its relevance for child health. Current Anthropology, 59(6), 839–847. Boyette, AH (2016) Children’s play and culture learning in an egalitarian foraging society. Child Development, 87(3), 759–769. Boyette, AH, and Gettler, LT (2019) Evolution and human fatherhood. In LLM Welling and TK Shackelford, eds., The Oxford Handbook of Evolutionary Psychology and Behavioral Endocrinology, Oxford: Oxford University Press, 179–199. Bradbury, JW, and Vehrencamp, SL (2014) Complexity and behavioral ecology. Behavioral Ecology, 25(3), 435–442. Braudel, F (1992) Civilization and Capitalism, fifteeneighteen Century, Vol. 1, The Structures of Everyday Life. Berkeley: University of California Press. Brent, LJ, Franks, DW, Foster, EA, Balcomb, KC, Cant, MA, and Croft, DP (2015) Ecological knowledge, leadership, and the evolution of menopause in killer whales. Current Biology, 25(6), 746–750. Bressan, P, and Grassi, M (2004) Parental resemblance in 1-year-olds and the Gaussian curve. Evolution and Human Behavior, 25(3), 133–141. Brewer, DD (2016) A systematic review of post-marital residence patterns in prehistoric hunter-gatherers. BioRxiv, 057059. Bribiescas, RG (2001) Reproductive ecology and life history of the human male. Yearbook of Physical Anthropology, 44, 148–176. Bribiescas, RG (2010) An evolutionary and life history perspective on human male reproductive senescence. Annals of the New York Academy of Sciences, 1204, 54–64. Bribiescas, RG, Ellison, PT, and Gray, PB (2012) Male life history, reproductive effort, and the evolution of the Genus Homo. Current Anthropology, 53(S6), 424–435. Briga, M, Pen, I, and Wright, J (2012) Care for kin: Within-group relatedness and allomaternal care are positively correlated and conserved throughout the mammalian phylogeny. Biology Letters, 8, 533–536.

Brindle, E, O’Connor, KA, and Garrett, DA (2014) Applications of dried blood spots in general human health studies. In W Li and MS Lee, eds., Dried Blood Spots: Applications and Techniques, Hoboken: John Wiley & Sons, 114–129. Broesch, T, Crittenden, AN, Beheim, BA, . . . Borgerhoff Mulder, M (2020) Navigating cross-cultural research: Methodological and ethical considerations. Proceedings of the Royal Society B: Biological Sciences, 287(1935), 20201245. Broom, M, Koenig, A, and Borries, C (2009) Variation in dominance hierarchies among group-living animals: Modelling stability and the likelihood of coalitions. Behavioral Ecology, 20(4), 844–855. Broome, J (1991) Utility. Economics and Philosophy, 7, 1–12. Brosnan, SF, and Bshary, R (2010) Cooperation and deception: From evolution to mechanisms. Philosophical Transactions of the Royal Society B: Biological Sciences, 365(1553), 2593–2598. Broude, GJ, and Greene, SJ (1976) Cross-cultural codes on twenty sexual attitudes and practices. Ethnology, 15(4), 409–29. Broude, GJ, and Greene, SJ (1983) Cross-cultural codes on husband-wife relationships. Ethnology, 22(3), 263–280. Broughton, JM, Cannon, MD, and Bartelink, EJ (2010) Evolutionary ecology, resource depression, and niche construction theory: Applications to central California hunter-gatherers and Mimbres-Mogollon agriculturalists. Journal of Archaeological Method and Theory, 17(4), 371–421. Brouwer, L, and Griffith, SC (2019) Extra-pair paternity in birds. Molecular Ecology, 28(22), 4864–4882. Brown, D (1991) Human Universals, New York: McGraw-Hill. Brown, GR (2001) Sex-biased investment in nonhuman primates: Can Trivers & Willard’s theory be tested? Animal Behaviour, 61(4), 683–694. Brown, GR, Laland, KN, and Borgerhoff Mulder, M (2009) Bateman’s principles and human sex roles. Trends in Ecology and Evolution, 24(6), 297–304. Brown, J (1970a) Economic organization and the position of women among the Iroquois. Ethnohistory, 17, 151–167. Brown, JK (1970b) A note on the division of labor by sex. American Anthropologist, 72(5), 1073–1078. Brown, JK (1985) Introduction. In JK Brown and V Kerns, eds., In Her Prime: A New View of Middle-Aged Women, South Hadley: Bergin & Garvey, 1–11.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography Brown, JL (1964) The evolution of diversity in avian territorial systems. The Wilson Bulletin, 76(2), 160–169. Brown, JL (1974) Alternate routes to sociality in jays: With a theory for the evolution of altruism and communal breeding. American Zoology, 14, 63–80. Brown, JL (1987) Helping and Communal Breeding in Birds, Princeton: Princeton University Press. Browning, LE, Patrick, SC, Rollins, LA, Griffith, SC, and Russell, AF (2012) Kin selection, not group augmentation, predicts helping in an obligate cooperative breeding bird. Proceedings of the Royal Society B: Biological Sciences, 279, 3861–3869. Bryce, PJ (2016) Balancing tolerance or allergy to food proteins. Trends in Immunology, 37, 659–667. Buckner, W (2018) On secret cults and male dominance. Traditions of Conflict. Bugos, PE (1985) An evolutionary ecological analysis of the social organization of the Ayoreo of the Northern Gran Chaco (PhD Dissertation), Northwestern University, Evanston. Buller, DJ (2006) Adapting Minds: Evolutionary psychology and the Persistent Quest for Human Nature, Cambridge: MIT Press. Bulley, A, and Pepper, GV (2017) Cross-country relationships between life expectancy, intertemporal choice and age at first birth. Evolution and Human Behavior, 38(5), 652–658. Burger, O, Baudisch, A, and Vaupel, JW (2012) Human mortality improvement in evolutionary context. Proceedings of the National Academy of Sciences, 109(44), 18210–18214. Burger, O, and DeLong, J (2016) What if fertility decline is not permanent? The need for an evolutionarilyinformed approach to understanding low fertility. Philosophical Transactions of the Royal Society B: Biological Sciences – Biological Sciences, 371(1692), 20150157. Burger, O, Lee, R, and Sear, R, eds. (n.d.) Human Evolutionary Demography. OSF preprints. https://osf .io/p59eu/. Burkart, JM, Hrdy, SB, and Schaik, C (2009) Cooperative breeding and human cognitive evolution. Evolutionary Anthropology, 18, 175–186. Burton, ML, and White, DR (1984) Sexual division of labor in agriculture. American Anthropologist, 86(3), 568–583. Buss, DM (1988) From vigilance to violence: Tactics of mate retention in American undergraduates. Ethology and Sociobiology, 9(5), 291–317.

433

Buss, DM (1989) Sex differences in human mate preferences: Evolutionary hypotheses tested in 37 cultures. Behavioral and Brain Sciences, 12(1), 1–14. Buss, DM (2014) Evolutionary Psychology: The New Science of the Mind, New York: Psychology Press. Buss, DM (2016) The Evolution of Desire: Strategies of Human Mating, New York: Basic Books. Buss, DM (2017) Sexual conflict in human mating. Current Directions in Psychological Science, 26(4), 307–313. Buss, DM, and Barnes, M (1986) Preferences in human mate selection. Journal of Personality and Social Psychology, 50(3), 559–70. Buss, DM, Goetz, C, Duntley, JD, Asao, K, and ConroyBeam, D (2017) The mate switching hypothesis. Personality and Individual Differences, 104, 143–149. Buss, DM, Larsen, RJ, Westen, D, and Semmelroth, J (1992) Sex differences in jealousy: Evolution, physiology, and psychology. Psychological Science, 3(4), 251–255. Buss, DM, and Schmitt, DP (1993) Sexual strategies theory: An evolutionary perspective on human mating. Psychological Review, 100(2), 204. Buss, DM, Shackelford, TK, and LeBlanc, GJ (2000) Number of children desired and preferred spousal age difference: Context-specific mate preference patterns across 37 cultures. Evolution and Human Behavior, 21(5), 323–331. Buston, PM, and Emlen, ST (2003) Cognitive processes Underlying human mate choice: The relationship between self-perception and mate preference in western society. Proceedings of the National Academy of Sciences, 100(15), 8805–10. Butler, MA, and King, AA (2004) Phylogenetic comparative analysis: A modeling approach for adaptive evolution. American Naturalist, 164(6), 683–695. Butte, NF, and King, JC (2005) Energy requirements during pregnancy and lactation. Public Health Nutrition, 8(7a), 1010–1027. Buunk, AP, Park, JH, and Dubbs, SL (2008) Parent– offspring conflict in mate preferences. Review of General Psychology, 12(1), 47–62. Byers, KG, and Savaiano, DA (2005) The myth of increased lactose intolerance in African-Americans. Journal of the American College of Nutrition, 24, 569–573. Bzostek, SH, McLanahan, SS, and Carlson, MJ (2012) Mothers’ repartnering after a nonmarital birth. Social Forces, 90(3), 817–841.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

434

Bibliography

Caldwell, JC, Hill, AG, and Hull, VJ (1988) MicroApproaches to Demographic Research, New York: Routledge. Calvo, GA, and Wellisz, S (1978) Supervision, loss of control, and the optimum size of the firm. Journal of Political Economy, 86(5), 943–952. Camerer, C (1989) Bubbles and fads in asset prices. Journal of Economic Surveys, 3(1), 3–41. Camerer, CF, Dreber, A, Holzmeister, F, . . . Wu, H (2018) Evaluating the replicability of social science experiments in Nature and Science between 2010 and 2015. Nature Human Behaviour, 2(9), 637–644. Cameron, EZ (2004) Facultative adjustment of mammalian sex ratios in support of the Trivers-Willard hypothesis: Evidence for a mechanism. Proceedings of the Royal Society B: Biological Sciences, 271(1549), 1723–1728. Cameron, EZ, and Dalerum, F (2009) A Trivers-Willard effect in contemporary humans: Male-biased sex ratios among billionaires. PLoS ONE, 4(1), 4195. Cameron, JL, Weltzin, TE, McConaha, C, Helmreich, DL, and Kaye, WH (1991) Slowing of pulsatile luteinizing hormone secretion in men after forty-eight hours of fasting. Journal of Clinical Endocrinology and Metabolism, 73, 35–41. Campbell, A (2013) A Mind of Her Own, Oxford: Oxford University Press. Cannon, MD (2000) Large mammal relative abundance in pithouse and pueblo period archaeofaunas from southwestern New Mexico: Resource depression among the Mimbres-Mogollon? Journal of Anthropological Archaeology, 19(3), 317–347. Cant, MA, and Johnstone, RA (2008) Reproductive conflict and the separation of reproductive generations in humans. Proceedings of the National Academy of Sciences, 105(14), 5332–5336. Cantor, M, Shoemaker, LG, Cabral, RB, Flores, CO, Varga, M, and Whitehead, H (2015) Multilevel animal societies can emerge from cultural transmission. Nature Communications, 6(1), 8091. Cao, Y, Enke, B, Falk, A, Giuliano, P, and Nunn, N (2021) Herding, warfare, and a culture of honor: Global evidence. NBER Working Paper Series, 29250. Carballo, DM, Roscoe, P, and Feinman, GM (2014) Cooperation and collective action in the cultural evolution of complex societies. Journal of Archaeological Method and Theory, 21(1), 98–133. Carey, JR, and Gruenfelder, C (1997) Population biology of the elderly. In KW Wachter and CE Finch, eds., Between Zeus and the Salmon, Washington: National Academy Press, 17–37.

Carmichael, S (2011) Marriage and power: Age at first marriage and spousal age gap in lesser developed countries. The History of the Family, 16(4), 416–436. Carneiro, R (2000) The transition from quantity to quality: A neglected causal mechanism in accounting for social evolution. Proceedings of the National Academy of Sciences, 97, 12926–12931. Carneiro, RL (1970) A theory of the origin of the state. Science, 169(3947), 733–738. Carolus, C, and Ringen, E (2018) Marital status and infanticide. In TK Shackelford and VA WeekesShackelford (eds.), Encyclopedia of Evolutionary Psychological Science, Cham: Springer, 4791–4795. Carpenter, JP (2007) Punishing free-riders: How group size affects mutual monitoring and the provision of public goods. Games and Economic Behavior, 60(1), 31–51. Carré, JM, and Putnam, SK (2010) Watching a previous victory produces an increase in testosterone among elite hockey players. Psychoneuroendocrinology, 35(3), 475–479. Carroll, SR, Herczog, E, Hudson, M, Russell, K, and Stall, S (2021) Operationalizing the CARE and FAIR Principles for Indigenous data futures. Scientific Data, 8(1), 108. Carter, VA, Brunelle, A, Power, MJ, . . . Codding, BF (2021) Legacies of Indigenous land use shaped past wildfire regimes in the Basin-Plateau Region, USA. Communications Earth & Environment, 2(1), 1–9. Cashdan, E (1983) Territoriality among human foragers: Ecological models and an application to four bushman groups. Current Anthropology, 24(1), 47–66. Cashdan, E (1992) Spatial organization and habitat use. In EA Smith and B Winterhalder, eds., Evolutionary Ecology and Human Behavior, New York: Aldine de Gruyter, 237–266. Cashdan, E (1998) Are men more competitive than women? British Journal of Social Psychology, 37(2), 213–229. Cashdan, EA (1980) Egalitarianism among hunters and gatherers. American Anthropologist, 82(1), 116–120. Caspari, R, and Lee, S-H (2004) Older age becomes common late in human evolution. Proceedings of the National Academy of Sciences, 101(30), 10895–10900. Cassar, A, and Rigdon, M (2021) Option to cooperate increases women’s competitiveness and closes the gender gap. Evolution and Human Behavior, 42(6), 556–572. Cassar, A, Wordofa, F, and Zhang, Y (2016) Competing for the benefit of offspring eliminates the gender gap

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography in competitiveness. Proceedings of the National Academy of Sciences, 113(19), 5201–5205. Castro, LJ, and Rogers, A (1983) What the age composition of migrants can tell us. Population Bulletin of the United Nations, 15, 63–79. Caswell, H (2007) Extrinsic mortality and the evolution of senescence. Trends in Ecology and Evolution, 4(22), 173–174. Cavalli-Sforza, LL, and Feldman, MW (1981) Cultural Transmission and Evolution: A Quantitative Approach, Princeton: Princeton University Press. Cavalli-Sforza, LL, Menozzi, P, and Piazza, A (1994) The History and Geography of Human Genes, Princeton: Princeton University Press. Cepon-Robins, TJ, Blackwell, AD, Gildner, TE, . . . Sugiyama, LS (2021) Pathogen disgust sensitivity protects against infection in a high pathogen environment. Proceedings of the National Academy of Sciences, 118(8), e2018552118. Chabot-Hanowell, B, and Smith, EA (2012) Territorial and nonterritorial routes to power: Reconciling evolutionary ecological, social agency, and historicist approaches. Archeological Papers of the American Anthropological Association, 22(1), 72–86. Chagnon, NA (1979) Is reproductive success equal in egalitarian societies? In NA Chagnon and W Irons, Eds., Evolutionary Biology and Human Social Behavior: An Anthropological Perspective, North Scituate, MA: Duxbury Press, 374–401. Chagnon, NA (1988) Life histories, blood revenge, and warfare in a tribal population. Science, 239(4843), 985–992. Chagnon, NA, Lynch, RF, Shenk, MK, Hames, R, and Flinn, MV (2017) Cross-cousin marriage among the Yanomamö shows evidence of parent–offspring conflict and mate competition between brothers. Proceedings of the National Academy of Sciences, 114(13), 2590–2607. Chapais, B (2001) Primate nepotism: What is the explanatory value of kin selection? International Journal of Primatology, 22, 203–229. Chapais, B (2006) Kinship, competence and cooperation in primates. In PM Kappeler and CP Schaik, eds., Cooperation in Primates and Humans, Berlin: Springer-Verlag, 47–64. Chapais, B (2008) Primeval Kinship: How Pair-Bonding Gave Birth to Human Society, Cambridge: Harvard University Press. Chapais, B (2011) The deep social structure of humankind. Science, 331(6022), 1276–1277.

435

Chapais, B (2013) Monogamy, strongly bonded groups, and the evolution of human social structure. Evolutionary Anthropology, 22(2), 52–65. Chapais, B (2014) Complex kinship patterns as evolutionary constructions, and the origins of sociocultural universals. Current Anthropology, 55(6), 751–783. Chapais, B (2015) Competence and the evolutionary origins of status and power in humans. Human Nature, 26, 161–183. Chapais, B (2017) Psychological adaptations and the production of culturally polymorphic social universals. Evolutionary Behavioral Sciences, 11, 63–82. Chapman, CA, Bicca-Marques, JC, Calvignac-Spencer, S, . . . Chr. Stenseth, N (2019) Games academics play and their consequences: How authorship, h-index and journal impact factors are shaping the future of academia. Proceedings of the Royal Society B: Biological Sciences, 286(1916), 20192047. Chapman, SN, Pettay, JE, Lahdenperä, M, and Lummaa, V (2018) Grandmotherhood across the demographic transition. PLoS ONE, 13(7), e0200963. Charlesworth, B (1994) Evolution in Age-Structured Populations, Vol. 2, Cambridge: Cambridge University Press. Charnov, E, and Berrigan, D (1993) Why do female primates have such long lifespans and so few babies? Evolutionary Anthropology, 1, 191–194. Charnov, EL (1976) Optimal foraging, the marginal value theorem. Theoretical Population Biology, 9(2), 129–136. Charnov, EL (1993) Life History Invariants: Some Explanations of Symmetry in Evolutionary Ecology, Oxford, Oxford University Press. Chase, I, Tovey, C, Spangler-Martin, D, and Manfredonia, M (2002) Individual differences versus social dynamics in the formation of animal dominance hierarchies. Proceedings of the National Academy of Sciences, 99, 5744–5749. Chaudhary, N, Salali, GD, Thompson, J, . . . Migliano, AB (2015) Polygyny without wealth: Popularity in gift games predicts polygyny in BaYaka Pygmies. Royal Society Open Science, 2(5), 150054. Chaudhary, N, Salali, GD, Thompson, J, and Migliano, AB (2016) Competition for cooperation: Variability, benefits and heritability of relational wealth in hunter-gatherers. Scientific Reports, 6, 29120. Chayanov, AV (1992) Peasant Farm Organization, Madison: University of Wisconsin Press. Chen, F, Zhang, X, Laustsen, L, and Cheng, J (2021) Harsh but expedient: Dominant leaders increase

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

436

Bibliography

group cooperation via threat of punishment. Psychological Science, 32, 2005–2022. Cheng, J, Kornienko, O, and Granger, D (2018) Prestige in a large-scale social group predicts longitudinal changes in testosterone. Journal of Personality and Social Psychology, 114, 924–944. Cheng, J, Tracy, J, Foulsham, T, Kingstone, A, and Henrich, J (2013) Two ways to the top: Evidence that dominance and prestige are distinct yet viable avenues to social rank and influence. Journal of Personality and Social Psychology, 104, 103–125. Cheng, J, Tracy, J, and Henrich, J (2021) Dominance is necessary to explain human status hierarchies. Proceedings of the National Academy of Sciences, 118, 2103870118. Cheng, PW, and Holyoak, KJ (1985) Pragmatic reasoning schemas. Cognitive Psychology, 17(4), 391–416. Chibnik, M (2011) Anthropology, Economics, and Choice, Austin: University of Texas Press. Chisholm, JS (1999) Attachment and time preference: Relations between early stress and sexual behaviour in a sample of American university women. Human Nature, 10(1), 51–83. Chisholm, JS, and Burbank, VK (1991) Monogamy and polygyny in Southeast Arnhem Land: Male coercion and female choice. Ethology and Sociobiology, 12(4), 291–313. Chisholm, JS, Ellison, PT, Evans, J, . . . Worthman, CM (1993) Death, hope, and sex: Life-history theory and the development of reproductive strategies. Current Anthropology, 34(1), 1–24. Choi, JP, Chowdhury, SM, and Kim, J (2016) Group contests with internal conflict and power asymmetry. Scandinavian Journal of Economics, 118(4), 816–840. Chorpita, BF, and Barlow, DH (1998) The development of anxiety: The role of control in the early environment. Psychological Bulletin, 124(1), 3–21. Christensen, AJ, Turner, CW, Smith, TW, Holman, JM, and Gregory, MC (1991) Health locus of control and depression in end-stage renal disease. Journal of Consulting and Clinical Psychology, 59(3), 419–424. Christensen, K, Gaist, D, Jeune, B, and Vaupel, JW (1998) A tooth per child? The Lancet, 352(9137), 1387. Chuang, JS, Rivoire, O, and Leibler, S (2009) Simpson’s Paradox in a synthetic microbial system. Science, 323(5911), 272–275. Chudek, M, and Henrich, J (2011) Culture-gene coevolution, norm-psychology and the emergence of human prosociality. Trends in Cognitive Sciences, 15(5), 218–226.

Chudek, M, McNamara, RA, Birch, S, Bloom, P, and Henrich, J (2018) Do minds switch bodies? Dualist interpretations across ages and societies. Religion Brain and Behavior, 8(4), 354–368. Cinelli, C, Forney, A, and Pearl, J (2022) A crash course in good and bad controls. Sociological Methods & Research. Clancy, KB, and Davis, JL (2019) Soylent is people, and WEIRD is white: Biological anthropology, whiteness, and the limits of the WEIRD. Annual Review of Anthropology, 48, 169–186. Clark, J, and Blake, M (1994) The power of prestige: Competitive generosity and the emergence of rank societies in lowland Mesoamerica. In EM Brumfiel and JW Fox, eds., Factional Competition and Political Development in the New World, Cambridge: Cambridge University Press, 17–30. Clarke, AL (1993) Women, resources, and dispersal in nineteenth-century Sweden. Human Nature, 4(2), 109–135. Clarke, AL, and Low, B (1992) Ecological correlates of human dispersal in 19th century Sweden. Animal Behaviour, 44(4), 677–693. Clarke, P, Pradhan, G, and van Schaik, C (2009) Intersexual conflict in primates: Infanticide, paternity allocation, and the role of coercion. In MH Muller and RW Wrangham, eds., Sexual Coercion in Primates and Humans, Cambridge: Harvard University Press, 42–77. Cleaver, M (1972) The contradictions of the green revolution. The American Economic Review, 62, 177–186. Clech, L, Jones, JH, Gibson, M, E., E, Hampshire, KR, and Randall, SC (2020) Inequality in the household and rural–urban migration in Ethiopian farmers. Evolutionary Human Sciences, 2, e9. Clements, KC, and Stephens, DW (1995) Testing models of non-kin cooperation: Mutualism and the prisoner’s dilemma. Animal Behaviour, 50(2), 527–535. Cloutier CT, Coxworth JE, Hawkes K (2015) Age-related decline in ovarian follicle stocks differ between chimpanzees (Pan troglodytes) and humans. Age, 37, 1–9. Clutton-Brock, J, ed. (1989) The Walking Larder: Patterns of Domestication, Pastoralism, and Predation, London: Unwin Hyman. Clutton-Brock, T (2002) Breeding together: Kin selection and mutualism in cooperative vertebrates. Science, 296(5565), 69–72. Clutton-Brock, T (2007) Sexual selection in males and females. Science, 318(5858), 1882–1885.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography Clutton-Brock, T, and Huchard, E (2013) Social competition and selection in males and females. Philosophical Transactions of the Royal Society B: Biological Sciences, 368, 20130074. Clutton-Brock, T, and Manser, M (2016) Meerkats: Cooperative breeding in the Kalahari. In WD Koenig and JL Dickinson, eds., Cooperative Breeding in Vertebrates, Cambridge: Cambridge University Press, 294–317. Clutton-Brock, T, and Sheldon, BC (2010) Individuals and populations: The role of long-term, individualbased studies of animals in ecology and evolutionary biology. Trends in Ecology and Evolution, 25(10), 562–573. Clutton-Brock, T, and Vincent, A (1991) Sexual selection and the potential reproductive rate of males and females. Nature, 351(6321), 58–60. Clutton-Brock, TH (1991) The Evolution of Parental Care, Princeton: Princeton University Press. Clutton-Brock, TH (1998) Reproductive skew, concessions and limited control. Trends in Ecology and Evolution, 13(7), 288–292. Clutton-Brock, TH (2006) Cooperative breeding in mammals. In PM Kappeler and CP Schaik, eds., Cooperation in Primates and Humans, Berlin: Springer-Verlag, 173–190. Clutton-Brock, TH (2009) Structure and function in mammalian societies. Philosophical Transactions of the Royal Society B: Biological Sciences, 364, 3229–3242. Clutton-Brock, TH (2016) Mammal Societies, WileyBlackwell. Clutton-Brock, TH, Brotherton, PNM, O’Riain, MJ, . . . McIlrath, GM (2000) Individual contributions to babysitting in a cooperative mongoose, Suricata suricatta. Proceedings of the Royal Society B: Biological Sciences, 267, 301–305. Clutton-Brock, TH, Brotherton, PNM, O’Riain, MJ, . . . McIlrath, GM (2001a) Contributions to cooperative rearing in meerkats. Animal Behaviour, 61, 705–710. Clutton-Brock, TH, Brotherton, PNM, Russell, AF, . . . GM, M (2001b) Cooperation, control, and concession in meerkat groups. Science, 291(5503), 478–481. Clutton-Brock, TH, and Parker, GA (1992) Potential reproductive rates and the operation of sexual selection. The Quarterly Review of Biology, 67(4), 437–456. Clutton-Brock, TH, Russell, AF, Sharpe, LL, Young, AJ, B, Z, and McIlrath, GM (2002) Evolution and development of sex differences in cooperative behavior in meerkats. Science, 297, 253–256.

437

Coad, L (2007) Bushmeat hunting in Gabon: Socioeconomics and hunter behaviour (PhD Dissertation), University of Cambridge, Cambridge. Coall, DA, and Chisholm, JS (2003) Evolutionary perspectives on pregnancy: Maternal age at menarche and infant birth weight. Social Science and Medicine, 57(10), 1771–1781. Coall, DA, and Hertwig, R (2010) Grandparental investment: Past, present, and future. Behavioral and Brian Sciences, 33, 1–59. Coall, DA, Hilbrand, S, Sear, R, and Hertwig, R (2016) A new niche? The theory of grandfather involvement. In A Buchanan and A Rotkirch, eds., Grandfathers: Global Perspectives, Grandfathers: Springer, 21–44. Coall, DA, Meier, M, Hertwig, R, and Wa, M (2009) Grandparental investment: The influence of reproductive timing and family size. American Journal of Human Biology, 21(4), 455–463. Coast, EE, Hampshire, KR, and Randall, SC (2007) Disciplining anthropological demography. Demographic Research, 16, 493–518. Cockburn, A (1998) Evolution of helping behavior in cooperatively breeding birds. Annual Review of Ecology and Systematics, 29, 141–177. Cockburn, A (2006) Prevalence of different modes of parental care in birds. Proceedings of the Royal Society B: Biological Sciences, 273(1592), 1375–1383. Codding, B, Bliege Bird, R, and Bird, D (2011) Provisioning offspring and others: Risk-energy trade-offs and gender differences in huntergatherer foraging strategies. Proceedings of the Royal Society B: Biological Sciences, 278(1717), 2502–2509. Codding, BF (2012) “Any kangaroo?” On the ecology, ethnography and archaeology of foraging in Australia’s arid west (PhD Dissertation), Stanford University, Stanford. Codding, BF, and Bird, DW (2015) Behavioral ecology and the future of archaeological science. Journal of Archaeological Science, 56, 9–20. Codding, BF, Bliege Bird, R, Kauhanen, PG, and Bird, DW (2014) Conservation or co-evolution? Intermediate levels of aboriginal burning and hunting have positive effects on kangaroo populations in Western Australia. Human Ecology, 42(5), 659–669. Codding, BF, and Jones, TL (2013) Environmental productivity predicts migration, demographic, and linguistic patterns in prehistoric California. Proceedings

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

438

Bibliography

of the National Academy of Sciences, 110(36), 14569–14573. Codding, BF, and Kramer, K, eds. (2016) Why Forage? Hunters and Gatherers in the Twenty-first Century, Albuquerque: University of New Mexico Press. Codding, BF, Parker, AK, and Jones, TL (2019) Territorial behavior among Western North American foragers: Allee effects, within group cooperation, and between group conflict. Quaternary International, 518, 31–40. Codding, BF, Zeanah, DW, Bliege Bird, R, Parker, CH, and Bird, DW (2016) Martu ethnoarchaeology: Foraging ecology and the marginal value of site structure. Journal of Anthropological Archaeology, 44, 166–176. Cohen, AA (2004) Female post-reproductive lifespan: A general mammalian trait. Biological Reviews, 79(4), 733–750. Cohen, D, Nisbett, RE, Bowdle, BF, and Schwarz, N (1996) Insult, aggression, and the southern culture of honor. Journal of Personality and Social Psychology, 70, 945–960. Cole, TJ (2000) Secular trends in growth. Proceedings of the Nutrition Society, 59, 317–324. Cole, TJ (2003) The secular trend in human physical growth: A biological view. Economics of Human Biology, 1, 161–168. Coleman, D (2000) Demography in Intellectual Context: A Subject in Search of a Home. In Z Pavlik, ed., Position of Demography among Other Disciplines, Prague: Charles University Department of Demography and Geodemography, 27–35. Collard, M, Kemery, M, and Banks, S (2005) Causes of toolkit variation among hunter-gatherers: A test of four competing hypotheses. Canadian Journal of Archaeolology, 29, 1–19. Colleran, H (2016) The cultural evolution of fertility decline. Philosophical Transactions of the Royal Society B: Biological Sciences, 371, 1–12. Colleran, H (2020) Market integration reduces kin density in women’s ego-networks in rural Poland. Nature Communications, 11(1), 266. Colleran, H, Jasienska, G, Nenko, I, Galbarczyk, A, and Mace, R (2014) Community-level education accelerates the cultural evolution of fertility decline. Proceedings of the Royal Society B: Biological Sciences, 281, 1–7. Colleran, H, Jasienska, G, Nenko, I, Galbarczyk, A, and Mace, R (2015) Fertility decline and the changing dynamics of wealth, status and inequality.

Proceedings of the Royal Society B: Biological Sciences, 282(1806), 20150287. Conelly, WT (1992) Agricultural intensification in a Philippine frontier community: Impact on labor efficiency and farm diversity. Human Ecology, 20(2), 203–223. Conroy-Beam, D, and Buss, DM (2019) Why is age so important in human mating? Evolved age preferences and their influences on multiple mating behaviors. Evolutionary Behavioral Sciences, 13(2), 127–157. Cook, M (2003) A Brief History of the Human Race, New York: Norton. Coontz, S (2005) Marriage, a History: From Obedience to Intimacy or How Love Conquered Marriage, New York: Viking Press. Cooper, RW (1999) Coordination Games: Complementarities and Macroeconomics, Cambridge, New York: Cambridge University Press. Copping, LT, Campbell, A, and Muncer, S (2014) Psychometrics and life history strategy: The structure and validity of the high K strategy scale. Evolutionary Psychology, 12(1), 147470491401200130. Cornwallis, CK, West, SA, Davis, KE, and Griffin, AS (2010) Promiscuity and the evolutionary transition to complex societies. Nature, 466, 969–972. Cornwallis, CK, West, SA, and Griffin, AS (2009) Routes to indirect fitness in cooperatively breeding vertebrates: Kin discrimination and limited dispersal. Journal of Evolutionary Biology, 22, 2445–2457. Cosmides, L (1989) The logic of social exchange: Has natural selection shaped how humans reason? Studies with the Wason selection task. Cognition, 31, 187–276. Cosmides, L, and Tooby, J (1994) Beyond intuition and instinct blindness: Toward an evolutionarily rigorous cognitive science. Cognition, 50(1–3), 41–77. Cowlishaw, G, and Dunbar, R (1991) Dominance rank and mating success in male primates. Animal Behaviour, 41, 1045–1056. Coxworth, J, Kim, P, McQueen, J, and Hawkes, K (2015) Grandmothering life histories and human pair bonding. Proceedings of the National Academy of Sciences, 112, 11806–11811. Crabtree, SA, Bocinsky, RK, Hooper, PL, Ryan, SC, and Kohler, TA (2017) How to make a polity in the central Mesa Verde region. American Antiquity, 82(01), 71–95. Crespi, B (2014) The insectan apes. Human Nature, 25(1), 6–27.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography Crespi, BJ, Summers, K, and Dorus, S (2009) Genomic sister-disorders of neurodevelopment: An evolutionary approach. Evolutionary Applications, 2, 81–100. Cristia, A., Dupoux, E., Gurven, M. and Stieglitz, J. (2019) Child-directed speech is infrequent in a forager-farmer population: A time allocation study. Child Development, 90(3), 759–773. Crittenden, AN (2016) Children’s foraging and play among the Hadza. In CAL Meehan and AN Crittenden, eds., Origins and Implications of the Evolution of Childhood, Albuquerque: University of New Mexico Press, 55–172. Crittenden, AN, Conklin-Brittain, NL, Zes, DA, Schoeninger, MJ, and Marlowe, FW (2013) Juvenile foraging among the Hadza: Implications for human life history. Evolution and Human Behavior, 34, 299–304. Crittenden, AN, and Marlowe, FW (2008) Allomaternal care among the Hadza of Tanzania. Human Nature, 19, 249–262. Crittenden, AN, and Schnorr, SL (2017) Current views on hunter-gatherer nutrition and the evolution of the human diet. American Journal of Physical Anthropology, 162(S63), e23148. Crocker, WH, and Crocker, J (2004) The Canela: Kinship, Ritual, and Sex in an Amazonian Tribe, Belmont, CA: Wadsworth Publishing Company. Croft, DP, Brent, LJ, Franks, DW, and Cant, MA (2015) The evolution of prolonged life after reproduction. Trends in Ecology and Evolution, 30(7), 407–416. Crognier, E, Baali, A, and Hilali, M-K (2001) Do “helpers at the nest” increase their parents’ reproductive success? American Journal of Human Biology, 13, 365–373. Croizet, J-C (2012) The racism of intelligence: How mental testing practices have constituted an institutionalized form of group domination. In LD Bobo, L Crooms-Robinson, L Darling-Hammond, MC Dawson, HL Gates, G Jaynes, C Steele, eds., The Oxford Handbook of African American Citizenship, 1865–Present, Oxford: Oxford University Press, 769–816. Cronk, L (1991a) Human behavioral ecology. Annual Review of Anthropology, 20, 25–53. Cronk, L (1991b) Preferential parental investment in daughters over sons. Human Nature, 2(4), 387–417. Cronk, L (1991c) Wealth, status, and reproductive success among the Mukogodo of Kenya. American Anthropologist, 93(2), 345–360.

439

Cronk, L (1993) Parental favoritism toward daughters. American Scientist, 81(3), 272–279. Cronk, L, Steklis, D, Steklis, N, Akker, OR, and Aktipis, A (2019) Kin terms and fitness interdependence. Evolution and Human Behavior, 40(3), 281–291. Cronk, L, Turner, J, Madralek, R, and Maryanski, A (2015) Human cooperation: Evolutionary approaches to a complex phenomenon. In JH Turner, R Machalek, and A Maryanski, eds., Handbook on Evolution and Society: Toward an Evolutionary Social Science, Abingdon, Oxon: Routledge, 441–459. Crook, JH, and Crook, SJ (1988) Tibetan polyandry: Problems of adaptation and fitness. In LL Betzig, M Borgerhoff Mulder, and P Turke, eds., Human Reproductive Behavior: A Darwinian Perspective, Cambridge: Cambridge University Press, 97–114. Crook, JH, and Gartlan, JS (1966) Evolution of primate societies. Nature, 210(5042), 1200–1203. Culina, A, Radersma, R, and Sheldon, BC (2015) Trading up: The fitness consequences of divorce in monogamous birds. Biological Reviews, 90(4), 1015–1034. Cunningham, AJ, Worthington, S, Venkataraman, VV, and Wrangham, RW (2019) Do modern huntergatherers live in marginal habitats? Journal of Archaeological Science: Reports, 25, 584–599. Currie, TE (2013) Cultural evolution branches out: The phylogenetic approach in cross-cultural research. Cross-Cultural Research, 47, 102–130. Currie, TE, Bogaard, A, Cesaretti, R, and Williams, A (2015) Agricultural productivity in past societies: Toward an empirically informed model for testing cultural evolutionary hypotheses. Cliodynamics, 6(1), 24–56. Currie, TE, Campenni, M, Flitton, A, and Walker, L (2021) The cultural evolution and ecology of institutions. Philosophical Transactions of the Royal Society B: Biological Sciences, 376(1828), 20200047. Currie, TE, Greenhill, SJ, Gray, RD, Hasegawa, T, and Mace, R (2010) Rise and fall of political complexity in island South-East Asia and the Pacific. Nature, 467(7317), 801–804. Currie, TE, and Mace, R (2011) Mode and tempo in the evolution of socio-political organization: Reconciling ‘Darwinian’ and ‘Spencerian’ evolutionary approaches in anthropology. Philosophical Transactions of the Royal Society B: Biological Sciences, 366, 1108–1117.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

440

Bibliography

Curtis, V, Aunger, R, and Rabie, T (2004) Evidence that disgust evolved to protect from risk of disease. Biology Letters, 277, 131–133. Cutler, R (1975) Evolution of human longevity and the genetic complexity governing aging rate. Proceedings of the National Academy of Science, 72, 664–668. Cyranoski, D (2018) CRISPR-baby scientist fails to satisfy critics. Nature, 564(7734), 13–15. Dahl, GB, and Moretti, E (2008) The demand for sons. Review of Economic Studies, 75(4), 1085–1120. Dall, SRX, Giraldeau, L-A, Olsson, O, McNamara, JM, and Stephens, DW (2005) Information and its use by animals in evolutionary ecology. Trends in Ecology and Evolution, 20(4), 187–193. D’Altroy, TN (2015) The Incas, 2nd edn, West Sussex: Wiley. Daly, M, and Wilson, M (1983) Sex, Evolution and Behavior, 2nd edn, Boston: Willard Grant Press. Daly, M, and Wilson, M (1984) A sociobiological analysis of human infanticide. In H G and S Hrdy, eds., Infanticide: Comparative and Evolutionary Perspectives, New York: Aldine de Gruyter, 201–214. Daly, M, and Wilson, M (1985) Child abuse and other risks of not living with both parents. Ethology and Sociobiology, 6(4), 197–210. Daly, M, and Wilson, M (1988) Homicide, New York: Aldine de Gruyter. Daly, M, and Wilson, M (1998) The Truth about Cinderella: A Darwinian View of Parental Love, New Haven: Yale University Press. Daly, M, Wilson, M, and Weghorst, SJ (1982) Male sexual jealousy. Ethology and Sociobiology, 3(1), 11–27. Daly, M, and Wilson, MI (1982) Whom are newborn babies said to resemble? Ethology and Sociobiology, 3(2), 69–78. Damerow, P (1996) Food production and social status as documented in proto-cuneiform texts. In P Wiessner and W Schiefenhövel, eds., Food and the Status Quest, Providence: Berghahn Books, 149–170. Darwin, C (1871) The Descent of Man, and Selection in Relation to Sex. London: John Murray. Das Gupta, M, Zhenghua, J, Bohua, L, Zhenming, X, Chung, W, and Hwa-Ok, B (2003) Why is son preference so persistent in East and South Asia? A crosscountry study of China, India, and the Republic of Korea. The Journal of Development Studies, 40(2), 153–187. David-Barrett, T, and Dunbar, R (2014) Social elites can emerge naturally when interaction in networks is restricted. Behavioral Ecology, 25, 58–68.

David-Barrett, T, Rotkirch, A, and Carney, J (2015) Women favour dyadic relationships, but men prefer clubs: Cross-cultural evidence from social-networking. PLoS ONE, 10, 0118329. Davidian, E, Surbeck, M, Lukas, D, Kappeler, P, and Huchard, E (2022) The eco-evolutionary landscape of power relationships between males and females. Trends in Ecology and Evolution, 37, 706–718. Davis, D (1966) Fairs, Shops, and Supermarkets: A History of English Shopping, Toronto: University of Toronto Press. Davison, R, and Gurven, M (2022) The importance of elders: Extending Hamilton’s force of selection to include intergenerational transfers. Proceedings of the National Academy of Sciences, 119(28), e2200073119. Dawes, R (1980) Social dilemmas. Annual Review of Psychology, 31, 169–193. Dawkins, R (1976) The Selfish Gene, Oxford: Oxford University Press. Dawkins, R (1982) The Extended Phenotype: The Long Reach of the Gene, Oxford: Oxford University Press. Dawkins, R, and Carlisle, TR (1976) Parental investment, mate desertion and a fallacy. Nature, 262(5564), 131–133. de Bacco, C, Power, E, Larremore, D, and Moore, C (2017) Community detection, link prediction, and layer interdependence in multilayer networks. Physical Review E, 95(4), 042317. de Miguel, A, and Buss, DM (2011) Mate retention tactics in Spain: Personality, sex differences, and relationship status. Journal of Personality, 79(3), 563–586. de Vries, C, Galipaud, M, and Kokko, H (2023) Extrinsic mortality and senescence: A guide for the perplexed. Peer Community Journal, 3, e29. de Vries, H, Stevens, J, and Vervaecke, H (2006) Measuring and testing the steepness of dominance hierarchies. Animal Behaviour, 71, 585–592. De Vynck, JC, Difford, M, Anderson, R, Marean, CW, Cowling, RM, and Hill, K (2020) The resilience to human foraging of intertidal resources on the south Cape coast of South Africa and the implications for pre-historic foragers. Quaternary Science Reviews, 235, 106041. de Waal, F (2008) Putting the altruism back into altruism: The evolution of empathy. Annual Review of Psychology, 59, 279–300. Deady, DK, Law Smith, MJ, Kent, JP, and Dunbar, RIM (2006) Is priesthood an adaptive strategy? Evidence

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography from a historical Irish population. Human Nature, 17, 393–404. Dean, LG (2014) Human cumulative culture: A comparative perspective. Biological Reviews, 89, 284–301. Dean, MC (2006) Tooth microstructure tracks the pace of human life-history evolution. Proceedings of the Royal Society B: Biological Sciences, 273, 2799–2808. Debove, S, Andrè, JB, and Baumard, N (2015) Partner choice creates fairness in humans. Proceedings of the Royal Society B: Biological Sciences, 282(1808), 20150392. DeCasien, AR, Williams, SA, and Higham, JP (2017) Primate brain size is predicted by diet but not sociality. Nature Ecology and Evolution, 1(5), 1–7. Dehnen, T, Arbon, J, Farine, D, and Boogert, N (2022) How feedback and feed-forward mechanisms link determinants of social dominance. Biological Reviews, 97, 1210–1230. Del Giudice, M (2020) Rethinking the fast-slow continuum of individual differences. Evolution and Human Behavior, 41(6), 536–549. Del Giudice, M, Gangestad, SW, and Kaplan, HS (2016) Life history theory and evolutionary psychology. In DM Buss, ed., Handbook of Evolutionary Psychology, 2nd edn, Hoboken: Wiley Online Library, 68–95. Del Vicario, M, Bessi, A, Zollo, F, . . . Quattrociocchi, W (2016) The spreading of misinformation online. Proceedings of the National Academy of Sciences, 113(3), 554–559. Demps, K, and Winterhalder, B (2018) “Every tradesman must also be a merchant”: Behavioral ecology and household-level production for barter and trade in premodern economies. Journal of Archaeological Research, 27(1), 49–90. Deneven, WM (1966) The Aboriginal Cultural Geography of the Llanos de Mojos of Bolivia, Berkeley: University of California Press. Denham, WW (1974) Infant transport among the Alyawara tribe, Central Australia. Oceania, 64(4), 253–277. Derex, M (2013) Experimental evidence for the influence of group size on cultural complexity. Nature, 503, 389–391. Derex, M, and Boyd, R (2016) Partial connectivity increases cultural accumulation within groups. Proceedings of the National Academy of Sciences, 113(11), 2982–2987.

441

Desai, S (1995) When are children from large families disadvantaged? Evidence from cross-national analyses. Population Studies, 49(2), 195–210. DeScioli, P, and Wilson, BJ (2011) The territorial foundations of human property. Evolution and Human Behavior, 32(5), 297–304. Dewey, KG (2004) Impact of breastfeeding on maternal nutritional status. In LK Pickering, AL Morrow, GM Ruiz-Palacios, RJ Schanler, eds., Protecting Infants through Human Milk, New York: Springer, 91–100. Dey, C, Dale, J, and Quinn, J (2014) Manipulating the appearance of a badge of status causes changes in true badge expression. Proceedings of the Royal Society B: Biological Sciences, 281, 20132680. Di Cosmo, N (2002) Ancient China and Its Enemies: The Rise of Nomadic Power in East Asian History, Cambridge: Cambridge University Press. Diamond, J (1978) The Tasmanians – The longest isolation, the simplest technology. Nature, 273, 185–186. Diamond, J (1987) The worst mistake in the history of the human race. Discover, May 1, 1987, 64–66. Diamond, JM (1997) Guns, Germs, and Steel: The Fates of Human Societies, New York: W. W. Norton. Dias, BG, and Ressler, KJ (2014) Parental olfactory experience influences behavior and neural structure in subsequent generations. Nature Neuroscience, 17, 89–96. Dickemann, M (1979a) Female infanticide, reproductive strategies, and social stratification: A preliminary model. In NA Chagnon and W Irons, eds., Evolutionary Biology and Human Social Behavior: An Anthropological Perspective, North Scituate: Duxbury, 321–367. Dickemann, M (1979b) The ecology of mating systems in hypergynous dowry societies. Social Science Information, 18(2), 163–195. Dickemann, M (1981) Paternal confidence and dowry competition: A biocultural analysis of purdah. In RD Alexander and DW Tinkle, eds., Natural Selection and Social Behavior, New York: Chiron Press, 417–438. Dickemann, M (1991) Women, class, and dowry. American Anthropologist, 93(4), 944–946. Diehl, MW (2000) Hierarchies in Action: Cui Bono? Carbondale: Center for Archaeological Investigations. Divale, WT (1974) Migration, external warfare, and matrilocal residence. Behavior Science Research, 9(2), 75–133.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

442

Bibliography

Dixit, A (2011) Lawlessness and Economics: Alternative Modes of Governance, Princeton: Princeton University Press. Dixon, A, Ross, D, and O’Malley, SLC (1994) Paternal investment inversely related to degree of extra-pair paternity in the reed bunting. Nature, 371(2), 20. Dixson, AF (2009) Sexual Selection and the Origins of Human Mating Systems, Oxford: Oxford University Press. Doblhammer, G, and Oeppen, J (2003) Reproduction and longevity among the British peerage: The effect of frailty and health selection. Proceedings of the Royal Society of London. Series B: Biological Sciences, 270, 1541–1547. Dominguez, S (2002) Optimal gardening strategies: Maximizing the input and retention of water in prehistoric gridded fields in north central New Mexico. World Archaeology, 34(1), 131–163. Dotti Sani, GM, and Treas, J (2016) Educational gradients in parents’ child-care time across countries, 1965–2012. Journal of Marriage and Family, 78(4), 1083–1096. Douglas, H (2009) Science, Policy, and the Value-Free Ideal, Pittsburgh: University of Pittsburgh Press. Douhard, M (2017) Offspring sex ratio in mammals and the Trivers-Willard hypothesis: In pursuit of unambiguous evidence. BioEssays, 39(9), 1700043. Dow, GK (2003) Governing the Firm: Worker’s Control in Theory and Practice, Cambridge: Cambridge University Press. Dow, GK, and Reed, CG (2013) The origins of inequality: Insiders, outsiders, elites, and commoners. Journal of Political Economy, 121(3), 609–641. Dow, MM, and Eff, EA (2009) Multiple imputation of missing data in cross-cultural samples. CrossCultural Research, 43(3), 206–229. Downey, DB (1995) When bigger is not better: Family size, parental resources, and children’s educational performance. American Sociological Review, 60(5), 746–761. Downey, DB (2000) Number of siblings and intellectual development: The resource dilution explanation. American Psychologist, 56, 497–504. Draper, P, and Cashdan, E (1988) Change and child behavior among the !Kung. Ethnology, 27(4), 339–365. Draper, P, and Hames, R (2000) Birth order, sibling investment, and fertility among Ju/Hoansi (!Kung). Human Nature, 11(2), 117–156. Draper, P, and Harpending, H (1982) Father absence and reproductive strategy: An evolutionary perspective.

Journal of Anthropological Research, 38(3), 255–273. Dratva, J, Real, FG, Schindler, C, . . . Wjst, M (2009) Is age at menopause increasing across Europe? Results on age at menopause and determinants from two population-based studies. Menopause, 16(2), 385–394. Dreher, JC, Dunne, S, and Pazderska, A (2016) Testosterone causes both prosocial and antisocial status-enhancing behaviors in human males. Proceedings of the National Academy of Sciences, 113, 11633–11638. Drews, C (1993) The concept and definition of dominance in animal behavior. Behaviour, 125, 283–313. Du, J, and Mace, R (2018) Parental investment in Tibetan populations does not reflect stated cultural norms. Behavioral Ecology, 29(1), 106–116. Du, J, Page, AE, and Mace, R (2022) Grandpaternal care and child survival in a pastoralist society in western China. Evolution and Human Behavior, 43(5), 358–366. Duckitt, J (2006) Differential effects of right wing authoritarianism and social dominance orientation on outgroup attitudes and their mediation by threat from and competitiveness to outgroups. Personality and Social Psychology Bulletin, 32(5), 684–696. Duffield, KR, Keith Bowers, E, Sakaluk, SK, and Sadd, BM (2017) A dynamic threshold model for terminal investment. Behavioral Ecology and Sociobiology, 71(12), 185. Duffy, K, Wrangham, R, and Silk, J (2007) Male chimpanzees exchange political support for mating opportunities. Current Biology, 17, 586–587. Dugatkin, L (2001) Bystander effects and the structure of dominance hierarchies. Behavioral Ecology, 12, 348–352. Dugatkin, L, and Earley, R (2004) Individual recognition, dominance hierarchies and winner and loser effects. Proceedings of the Royal Society B: Biological Sciences, 271, 1537–1540. Dugatkin, LA (1997) Cooperation among Animals: An Evolutionary Perspective, New York: Oxford University Press. Dumont, L (1980) Homo Hierarchicus: The Caste System and Its Implications, Chicago: University of Chicago Press. Dunbar, R (1996) Grooming, Gossip, and the Evolution of Language, Cambridge: Harvard University Press. Dunbar, R (2018) The anatomy of friendship. Trends in Cognitive Sciences, 22, 32–51.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography Dunbar, RIM, Clark, A, and Hurst, NL (1995) Conflict and cooperation among the Vikings: Contingent behavioral decisions. Ethology and Sociobiology, 16(3), 233–246. Duncan, NA, Loughlin, NJD, Walker, JH, Hocking, EP, and Whitney, BS (2021) Pre-Columbian fire management and control of climate-driven floodwaters over 3,500 years in southwestern Amazonia. Proceedings of the National Academy of Sciences, 118(40), e2022206118. Dunn, MJ, Brinton, S, and Clark, L (2010) Universal sex differences in online advertisers age preferences: Comparing data from 14 Cultures and 2 religious groups. Evolution and Human Behavior, 31(6), 383–93. Dunn, PO, Cockburn, A, and Mulder, RA (1995) Fairywren helpers often care for young to which they are unrelated. Proceedings of the Royal Society B: Biological Sciences, 259(1356), 339–343. Durante, K, Griskevicius, V, Simpson, J, Cantu, S, and Tybur, J (2012) Sex ratio and women’s career choice: Does a scarcity of men lead women to choose briefcase over baby? Journal of Personality and Social Psychology, 103, 121–134. Durante, KM, Griskevicius, V, Redden, JP, and Edward White, A (2015) Spending on daughters versus sons in economic recessions. Journal of Consumer Research, 42(3), 435–457. Durham, WH (1991) Coevolution: Genes, Culture, and Human Diversity, Stanford: Stanford. Durkee, P, Goetz, A, and Lukaszewski, A (2017) Formidability assessment mechanisms: Examining their speed and automaticity. Evolution and Human Behavior, 39, 170–178. Durkee, P, Lukaszewski, A, and Buss, D (2019) Pride and shame: Key components of a culturally universal status management system. Evolution and Human Behavior, 40, 470–478. Durkee, P, Lukaszewski, A, and Buss, D (2020) Psychological foundations of human social status allocation. Proceedings of the National Academy of Sciences, 117, 21235–21241. Durkheim, É (1893) De la division du travail social (The Division of Labour in Society, Paris; Alcan. Durkheim, É (1912/1915) The Elementary Forms of the Religious Life: A Study in Religious Sociology, London and New York: G. Allen & Unwin & Macmillan. Dyble, M, Salali, G, and Chaudhary, N (2015) Sex equality can explain the unique social structure of hunter-gatherer bands. Science, 348, 796–798.

443

Dyble, M, Thompson, J, Smith, D, and Migliano, AB (2016) Networks of food sharing reveal the functional significance of multilevel sociality in two hunter-gatherer groups. Current Biology, 26(15), 2017–2021. Dyson-Hudson, N, and Dyson-Hudson, R (1999) The social organization of resource exploitation. In MA Little and PW Leslie, eds., Turkana Herders of the Dry Savanna: Ecology and Biobehavioral Response of Nomads to an Uncertain Environment, Oxford: Oxford University Press, 69–88. Dyson-Hudson, R, and Smith, EA (1978) Human territoriality: An ecological reassessment. American Anthropologist, 80, 21–41. Eagly, A (2020) Once more: The rise of female leaders. APA Research Brief. Retrieved from https://www.apa .org/research/action/female-leaders. Eagly, AH, and Wood, W (1999) The origins of sex differences in human behavior: Evolved dispositions versus social roles. American Psychologist, 54(6), 408. Earle, T (2002) Bronze Age Economics: The Beginnings of Political Economies, New York: Routledge. Earle, TK (1978) Economic and Social Organization of a Complex Chiefdom: The Halelea District, Kaua’i, Hawaii, Ann Arbor: Museum of Anthropology, University of Michigan. Earle, TK (1997) How Chiefs Come to Power: The Political Economy in Prehistory, Stanford: Stanford University Press. Eaton, JW, and Mayer, AI (1953) The social biology of very high fertility among the Hutterites; The demography of a unique population. Human Biology, 25(3), 206–264. Eckel, CC, El-Gamal, MA, and Wilson, RK (2009) Risk loving after the storm: A Bayesian-Network study of Hurricane Katrina evacuees. Journal of Economic Behavior and Organization, 69(2), 110–124. Edelstein, RS, Wardecker, BM, Chopik, WJ, Moors, AC, Shipman, EL, and Lin, NJ (2015) Prenatal hormones in first-time expectant parents: Longitudinal changes and within-couple correlations. American Journal of Human Biology, 27, 317–325. Edlund, L (2006) The price of marriage: Net vs. gross flows and the South Asian dowry debate. Journal of the European Economic Association, 4(2–3), 542–551. Edlund, L (2018) Cousin marriage is not choice: Muslim marriage and underdevelopment. AEA Papers and Proceedings, 108, 353–357.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

444

Bibliography

Ein-Dor, T, Perry-Paldi, A, Hirschberger, G, Birnbaum, GE, and Deutsch, D (2015) Coping with mate poaching: Gender differences in detection of infidelity-related threats. Evolution and Human Behavior, 36(1), 17–24. Eisenberg, DTA, Hayes, MG, and Kuzawa, CW (2012) Delayed paternal age of reproduction in humans is associated with longer telomeres across two generations of descendants. Proceedings of the National Academy of Sciences, 109, 10251–10256. Elias, P (1958) Two famous papers. IRE Transactions on Information Theory, 4(3), 99. Elkin, A (1938) Kinship in South Australia. Oceania, 8(4), 419–452. Elliott, KH, Gaston, AJ, and Crump, D (2010) Sex-specific behavior by a monomorphic seabird represents risk partitioning. Behavioral Ecology, 21(5), 1024–1032. Ellis, BJ (2004) Timing of pubertal maturation in girls: An integrated life history approach. Psychological Bulletin, 130, 920. Ellis, BJ, Bianchi, J, Griskevicius, V, and Frankenhuis, WE (2017) Beyond risk and protective factors: An adaptation-based approach to resilience. Perspectives on Psychological Science, 12(4), 561–587. Ellis, BJ, Figueredo, AJ, Brumbach, BH, and Schlomer, GL (2009) Fundamental dimensions of environmental risk. Human Nature, 20(2), 204–268. Ellis, F (1993) Peasant Economics: Farm Households and Agrarian Development, 2nd edn, Cambridge: Cambridge University Press. Ellis, S, Franks, DW, Nattrass, S, . . . Croft, DP (2018) Analyses of ovarian activity reveal repeated evolution of post-reproductive lifespans in toothed whales. Scientific Reports, 8(1), 1–10. Ellison, PT (1990) Human ovarian function and reproductive ecology: New hypotheses. American Anthropologist, 92, 933–952. Ellison, PT (1994) Advances in human reproductive ecology. Annual Review of Anthropology, 23, 255–275. Ellison, PT (2001) On Fertile Ground. A Natural History of Human Reproduction, Cambridge: Harvard University Press. Ellison, PT, Bribiescas, RG, Bentley, GR, . . . Hill, K (2002) Population variation in age-related decline in male salivary testosterone. Human Reproduction, 17(12), 3251–3253. Ellsworth, RM, Bailey, DH, Hill, KR, Hurtado, AM, and Walker, RS (2014) Relatedness, co-residence, and

shared fatherhood among Ache foragers of Paraguay. Current Anthropology, 55(5), 647–653. Ellsworth, RM, Shenk, MK, Bailey, DH, and Walker, RS (2016) Comparative study of reproductive skew and pair-bond stability using genealogies from 80 smallscale human societies. American Journal of Human Biology, 28(3), 335–342. Eloundou-Enyegue, PM, and Shapiro, D (2002) Will economic crises in Africa weaken rural-urban ties? Insights from child fosterage trends in Cameroon. Rural Sociology, 67, 278–298. Elster, J, ed. (1986) Rational Choice, New York: New York University Press. Ember, CR (1974) An evaluation of alternative theories of matrilocal versus patrilocal residence. Behavior Science Research, 9(2), 135–149. Ember, CR (1975) Residential variation among huntergatherers. Behavior Science Research, 10(3), 199–227. Ember, CR, and Ember, M (2009) Cross-Cultural Research Methods, Lanham and New York: AltaMira Press. Ember, M (1984) Alternative predictors of polygyny. Behavior Science Research, 19(1–4), 1–23. Ember, M, and Ember, CR (1971) The conditions favoring matrilocal versus patrilocal residence. American Anthropologist, 73(3), 571–594. Ember, M, Ember, CR, and Low, BS (2007) Comparing explanations of polygyny. Cross-Cultural Research, 41(4), 428–440. Emery, NJ, and Clayton, NS (2009) Comparative social cognition. Annual Review of Psychology, 60, 87–113. Emery Thompson, M, and Sabbi, K (in press) Evolutionary demography of the great apes. In O Burger, R Lee, and R Sear, eds., Human Evolutionary Demography. Emery Thompson, ME, Jones, JH, Pusey, AE, . . . Sugiyama, Y (2007) Aging and fertility patterns in wild chimpanzees provide insights into the evolution of menopause. Current Biology, 17(24), 2150–2156. Emlen, S (1990) White-fronted bee-eaters: Helping in a colonially nesting species. In PB Stacey and WD Koenig, eds., Cooperative Breeding in Birds: LongTerm Studies of Ecology and Behavior, Cambridge: Cambridge Univeristy Press, 489–526. Emlen, ST (1991 [1978]) Evolution of cooperative breeding in birds and mammals. In JR Krebs and NB Davies, eds., Behavioral Ecology: An Evolutionary Approach, Third Edition, London: Blackwell Scientific Publications, 301–337.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography Emlen, ST (1995) An evolutionary theory of the family. Proceedings of the National Academy of Sciences, 92(18), 8092–8099. Emlen, ST (1997) In JB Krebs and NB Davies, eds., Predicting Family Dynamics in Social Vertebrates, London: Blackwell Publishing, 228–253. Emlen, ST, and Oring, LW (1977) Ecology, sexual selection, and the evolution of mating systems. Science, 197(4300), 215–223. Endicott, K, and Endicott, K (2008) The Headman was a Woman, Long Grove: Waveland Press. Engelmann, J, Herrmann, E, and Tomasello, M (2012) Five-year olds, but not chimpanzees, attempt to manage their reputations. PLoS ONE, 7, 48433. Engels, F (1884) The Origin of the Family, Private Property and the State (E Untermann, Trans.), Chicago: Charles H. Kerr & Co. Ensminger, J (1992) Making a Market: The Institutional Transformation of an African Society, Cambridge: Cambridge University Press. Ensminger, J, and Knight, J (1997) Changing social norms: Common property, bridewealth, and clan exogamy. Current Anthropology, 38(1), 1–24. Epstein, JM (2008) Why model? Journal of Artificial Societies and Social Simulation, 11(4), 12. Eshel, I, and Cavalli-sforza, L (1982) Assortment of encounters and evolution of cooperativeness. Proceedings of the National Academy of Sciences, 79(4), 1331–1335. Evans, CL (2021) The uses and abuses of tree thinking in cultural evolution. Philosophical Transactions of the Royal Society B: Biological Sciences, 376(1828), 20200056. Evans, D (2002) Pain, evolution, and the placebo response. Behavioral And Brain Sciences, 25, 459–460. Evans, D (2005) Suppression of the acute-phase response as a biological mechanism for the placebo effect. Medical Hypotheses, 64, 1–7. Evans-Pritchard, EE (1940) The Nuer: A Description of the Modes of Livelihood and Political Institutions of a Nilotic People, Oxford: Oxford University Press. Evans-Pritchard, EE (1951) Kinship and Marriage among the Nuer, Oxford: Oxford Clarendon Press. Fafchamps, M, and Wahba, J (2006) Child labor, urban proximity, and household composition. Journal of Development Economics, 79, 374–397. Fairbanks, L (1990) Reciprocal benefits of allomothering for female vervet monkeys. Animal Behavior, 40, 553–562.

445

Fairbanks, LA (1993) Juvenile vervet monkeys: Establishing relationships and practicing skills for the future. In ME Pereira and LA Fairbanks, eds., Juvenile Primates: Life History, Development, and Behavior, Oxford: Oxford University Press, 211–227. Faith, JT, Rowan, J, and Du, A (2019) Early hominins evolved within non-analog ecosystems. Proceedings of the National Academy of Sciences, 116(43), 21478–21483. Fancourt, D, and Perkins, R (2018) The effects of mother–infant singing on emotional closeness, affect, anxiety and stress hormones. Music and Science, 1, 1–10. Farber, HS, Herbst, D, Kuziemko, I, and Naidu, S (2021) Unions and inequality over the twentieth century: New evidence from survey data. Quarterly Journal of Economics, 136(3), 1325–1385. Farmer, EL (1976) Early Ming Government: The Evolution of Dual Capitals, Cambridge: Harvard University Press. Fedorka, KM, and Mousseau, TA (2002) Material and genetic benefits of female multiple mating and polyandry. Animal Behaviour, 64(3), 361–367. Fehr, E, and Gächter, S (2002) Altruistic punishment in humans. Nature, 415, 137–140. Fehr, E, and Schurtenberger, I (2018) Normative foundations of human cooperation. Nature Human Behaviour, 2(7), 458–468. Fenton, WN (2010) The Great Law and the Longhouse: A Political History of the Iroquois Confederacy, Norman: University of Oklahoma Press. Fernández-López de Pablo, J, Gutiérrez-Roig, M, Gómez-Puche, M, McLaughlin, R, Silva, F, and Lozano, S (2019) Palaeodemographic modelling supports a population bottleneck during the Pleistocene-Holocene transition in Iberia. Nature Communications, 10(1), 1–13. Ferrari, MCO, Sih, A, and Chivers, DP (2009) The paradox of risk allocation: A review and prospectus. Animal Behaviour, 78(3), 579–585. Fessler, D, and Holbrook, C (2013) Friends shrink foes: The presence of comrades decreases the envisioned physical formidability of an opponent. Psychological Science, 24, 797–802. Fessler, D, and Holbrook, C (2016) Synchronized behavior increases assessments of the formidability and cohesion of coalitions. Evolution and Human Behavior, 37, 502–509. Fessler, D, Holbrook, C, and Gervais, M (2014) Men’s physical strength moderates conceptualizations of

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

446

Bibliography

prospective foes in two disparate societies. Human Nature, 25, 393–409. Fessler, DMT, Navarrete, CD, Hopkins, W, and Kay Izard, M (2004) Examining the terminal investment hypothesis in humans and chimpanzees: Associations among maternal age, parity, and birth weight. American Journal of Physical Anthropology, 127(1), 95–104. Fiddick, L, Cosmides, L, and Tooby, J (2000) No interpretation without representation: The role of domain-specific representations and inferences in the Wason selection task. Cognition, 77(1), 1–79. Fieder, M, and Huber, S (2007) The effects of sex and childlessness on the association between status and reproductive output in modern society. Evolution and Human Behavior, 28(6), 392–398. Figueredo, AJ (2007) The Arizona life history battery. https://sites.google.com/email.arizona.edu/ajf/thearizona-life-history-battery-alhb. Filippo, C, Cavalieri, D, Paola, M, . . . Lionetti, P (2010) Impact of diet in shaping gut microbiota revealed by a comparative study in children from Europe and rural Africa. Proceedings of the National Academy of Sciences, 107(33), 14691–14696. Filser, A, Barclay, K, Beckley, A, Uggla, C, and Schnettler, S (2021) Are skewed sex ratios associated with violent crime? A longitudinal analysis using Swedish registered data. Evolution and Human Behavior, 42, 212–222. Finch, CE (2012) Evolution of the human lifespan, past, present, and future: Phases in the evolution of human life expectancy in relation to the inflammatory load. Proceedings of the American Philosophical Society, 156(1), 9–44. Finch, CE, and Sapolsky, RM (1999) The evolution of Alzheimer disease, the reproductive schedule and the apoE isoforms. Neurobiology of Aging, 20, 407–428. Finch, CE, and Stanford, CB (2004) Meat-adaptive genes and the evolution of slower aging in humans. The Quarterly Review of Biology, 79, 3–50. Fincher, CL, Thornhill, R, Murray, DR, and Schaller, M (2008) Pathogen prevalence predicts human crosscultural variability in individualism/collectivism. Proceedings of the Royal Society B: Biological Sciences, 275, 1279–1285. Finer, LB, Frohwirth, LF, Dauphinee, LA, Singh, S, and Moore, AM (2005) Reasons U.S. women have abortions: Quantitative and qualitative perspectives. Perspectives on Sexual and Reproductive Health, 37(3), 110–118.

Fisher, RA (1930) The Genetical Theory of Natural Selection, Oxford: ClarendonPress. Fitzhugh, B (2003) The Evolution of Complex HunterGatherers: Archaeological Evidence from the North Pacific, New York: Kluwer Academic. Flack, J, Girvan, M, de Waal, F, and Krakauer, D (2006) Policing stabilizes construction of social niches in primates. Nature, 439, 426–429. Flannery, K (1972) The cultural evolution of civilizations. Annual Review of Ecology and Systematics, 3, 399–426. Flaxman, S, Goel, S, and Rao, JM (2016) Filter bubbles, echo chambers, and online news consumption. Public Opinion Quarterly, 80(S1), 298–320. Flinn, MV (1988a) Parent-offspring interactions in a Caribbean village: Daughter guarding. In L Betzig, M Borgerhoff Mulder, and P Turke, eds., Human Reproductive Behavior: A Darwinian Perspective, Cambridge: Cambridge University Press, 189–200. Flinn, MV (1988b) Step- and genetic parent/offspring relationships in a Caribbean village. Ethology and Sociobiology, 9, 335–369. Flinn, MV (1992) Paternal care in a Caribbean village. In B Hewlett, ed., Father–Child Relations: Cultural and Biosocial Contexts, New York: Aldine de Gruyter, 57–84. Flinn, MV, Geary, DC, and Ward, CV (2005) Ecological dominance, social competition, and coalitionary arms races: Why humans evolved extraordinary intelligence. Evolution and Human Behavior, 26(1), 10–46. Flinn, MV, and Low, BS (1986) Resource distribution, social competition and mating patterns in human societies. In DI Rubenstein and RW Wrangham, eds., Ecological Aspects of Social Evolution, Princeton: Princeton University Press, 217–243. Flory, J, Gneezy, U, Leonard, K, and List, J (2018) Gender, age, and competition: A disappearing gap? Journal of Economic Behavior & Organization, 150, 256–276. Foerster, S, Franz, M, and Murray, C (2017) Chimpanzee females queue but males compete for social status. Scientific Reports, 6, 35404. Fong, VL (2002) China’s one-child policy and the empowerment of urban daughters. American Anthropologist, 104, 1098–1109. Food and Agriculture Organization of the United Nations (2004) The ethics of sustainable agricultural intensification. Rome: FAO. www.fao.org/3/j0902e/ j0902e00.htm#Contents.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography Formicola, V, and Giannecchini, M (1999) Evolutionary trends of stature in Upper Paleolithic and Mesolithic Europe. Journal of Human Evolution, 36, 319–333. Fortunato, L (2012) The evolution of matrilineal kinship organization. Proceedings of the Royal Society B: Biological Sciences, 279(1749), 4939–4945. Fortunato, L (2015) Evolution of marriage systems. In JD Wright, ed., International Encyclopedia of the Social & Behavioral Sciences, 2nd edn, Vol. XIV, Oxford: Elsevier, 611–619. Fortunato, L, and Archetti, M (2010) Evolution of monogamous marriage by maximization of inclusive fitness. Journal of Evolutionary Biology, 23(1), 149–156. Fortunato, L, Holden, C, and Mace, R (2006) From bridewealth to dowry? A Bayesian estimation of ancestral states of marriage transfers in IndoEuropean groups. Human Nature, 17(4), 355–376. Foster, JG, and Evans, JA (2019) Promiscuous inventions: Modeling cultural evolution with multiple inheritance. In A Love and W Wimsatt, eds., Beyond the Meme: Development and Structure in Cultural Evolution, Minneapolis: University of Minnesota Press, 200–236. Fouts, HN, and Brookshire, RA (2009) Who feeds children? A child’s-eye-view of caregiver feeding patterns among the Aka foragers in Congo. Social Science and Medicine, 69(2), 285–292. Fox, M, Sear, R, Beise, J, Ragsdale, G, Voland, E, and Knapp, LA (2009) Grandma plays favourites: Xchromosome relatedness and sex-specific childhood mortality. Proceedings of the Royal Society B: Biological Sciences, 277(1681), 567–573. Fox, R (1967) Kinship and Marriage: An Anthropological Perspective, Cambridge: Cambridge University Press. Fox, R (1980) The Red Lamp of Incest: What the Taboo Can Tell Us about Who We Are & How We Got That Way, London: Hutchinson. Fracchia, J, and Lewontin, RC (1999) Does culture evolve? History and Theory, 38(4), 52–78. Frank, R (2011) The Darwin Economy: Liberty, Competition, and the Common Good, Princeton: Princeton University Press. Frank, S (1997) The Price Equation, Fisher’s fundamental theorem, kin selection, and causal analysis. Evolution, 51(6), 1712–1729. Frankenhuis, WE, and Nettle, D (2020) Current debates in human life history research. Evolution and Human Behavior, 41, 469–473. Frankenhuis, WE, Nettle, D, and Dall, SRX (2019) A case for environmental statistics of early-life effects.

447

Philosophical Transactions of the Royal Society B: Biological Sciences, 374(1770), 20180110. Frankenhuis, WE, and Panchanathan, K (2011) Balancing sampling and specialization: An adaptationist model of incremental development. Proceedings of the Royal Society B: Biological Sciences, 278(1724), 3558–3565. Franklin, P, and Volk, AA (2016) Evolutionary paradox: Adoption. In TK Shackelford and VA WeekesShackelford, eds., Encyclopedia of Evolutionary Psychological Science, Springer International Publishing, 2734–2741. Franz, M, McLean, E, Tung, T, Altmann, J, and S, A (2015) Self-organizing dominance hierarchies in a wild primate population. Proceedings of the Royal Society B: Biological Sciences, 282, 20151512. Fraser, H, Parker, T, Nakagawa, S, Barnett, A, and Fidler, F (2018) Questionable research practices in ecology and evolution. PLoS ONE, 13(7), e0200303. Frederick, S, Loewenstein, G, and O’Donoghue, T (2002) Time discounting and time preference: A critical review. Journal of Economic Literature, 40(2), 351–401. Fretwell, SD (1972) Populations in a Seasonal Environment, Princeton: Princeton University Press. Fretwell, SD, and Lucas, HL (1969) On territorial behavior and other factors influencing habitat distribution in birds. Acta Biotheoretica, 19(1), 16–36. Friebel, G, Lalanne, M, and Richter, B (2021) Gender differences in social interactions. Journal of Economic Behavior and Organization, 186, 33–45. Fried, MH (1967) The Evolution of Political Society, New York: Random House. Fromhage, L (2017) Parental care and investment. In Encyclopedia of Life Sciences, Wiley Online Library, 1–7. Fromhage, L, Elgar, MA, and Schneider, JM (2005) Faithful without care: The evolution of monogyny. Evolution, 59(7), 1400–1405. Fromhage, L, and Jennions, MD (2016) Coevolution of parental investment and sexually selected traits drives sex-role divergence. Nature Communications, 7, 12517. Fuentes, A (2004) It’s not all sex and violence: Integrated anthropology and the role of cooperation and social complexity in human evolution. American Anthropologist, 106(4), 710–718. Fulkerson, TJ, and Tushingham, S (2021) Geophyte field processing, storage, and women’s decision-making in hunter-gatherer societies: An archaeological case

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

448

Bibliography

study from western North America. Journal of Anthropological Archaeology, 62, 101299. Furrow, RE, and Feldman, MW (2014) Genetic variation and the evolution of epigenetic regulation. Evolution, 68, 673–683. Furuichi, T (2011) Female contributions to the peaceful nature of bonobo society. Evolutionary Anthropology, 20, 131–142. Gachter, S (2012) In the lab and the field: Punishment is rare in equilibrium. Behavioral and Brain Sciences, 35(1), 26. Gage, TB (1989) Bio-mathematical approaches to the study of human variation in mortality. American Journal of Physical Anthropology, 32(S10), 185–214. Gage, TB (2003) The evolution of human phenotypic plasticity: Age and nutritional status at maturity. Human Biology, 75(4), 521–537. Gagnon, A (2015) Natural fertility and longevity. Fertility and Sterility, 103(5), 1109–1116. Gagnon, A, Smith, KR, Tremblay, M, Vezina, H, Pare, PP, and DesJardins, B (2009) Is there a trade-off between fertility and longevity? A comparative study of women from three large historical databases accounting for mortality selection. American Journal of Human Biology, 21, 533–540. Gale, CR, Batty, GD, and Deary, IJ (2008) Locus of control at age 10 years and health outcomes and behaviors at age 30 years: The 1970 British Cohort Study. Psychosomatic Medicine, 70(4), 397–403. Galef, BG (1996) Social enhancement of food preferences in Norway rats: A brief review. In CM Heyes and BG Galef, eds., Social Learning in Animals: The Roots of Culture, San Diego: Academic Press, 49–64. Galef, BG (2001) Social influences on foraging in vertebrates: Causal mechanisms and adaptive functions. Animal Behaviour, 61, 3–15. Galinsky, AD, Gruenfeld, DH, and Magee, JC (2003) From power to action. Journal of Personality and Social Psychology, 85(3), 453. Galipaud, M, and Kokko, H (2020) Adaptation and plasticity in life-history theory: How to derive predictions. Evolution and Human Behavior, 41(6), 493–501. Galvin, KA, and Little, M (1999) Dietary intake and nutritional status. In MA Little and PW Leslie, eds., Turkana Herders of the Dry Savanna: Ecology and Biobehavioral Response of Nomads to an Uncertain Environment, Oxford: Oxford University Press, 125–145.

Gangestad, SW, and Haselton, MG (2015) Human estrus: Implications for relationship science. Current Opinion in Psychology, 1, 45–51. Gangestad, SW, and Simpson, JA (1990) Toward an evolutionary history of female sociosexual variation. Journal of Personality, 58(1), 69–96. Gangestad, SW, and Simpson, JA (2000) The evolution of human mating: Trade-offs and strategic pluralism. Behavioral and Brain Sciences, 23(4), 573–587. Garfield, ZH, Garfield, MJ, and Hewlett, BS (2016) A cross-cultural analysis of hunter-gatherer social learning. In Terashima and BS Hewlett, eds., Social Learning and Innovation in Contemporary HunterGatherers, Tokyo: Springer, 19–34. Garfield, ZH, and Hagen, EH (2020) Investigating evolutionary models of leadership among recently settled Ethiopian hunter-gatherers. Leadership Quarterly, 31(2), 101290. Garfield, ZH, Hubbard, RL, and Hagen, EH (2019a) Evolutionary models of leadership: Tests and synthesis. Human Nature, 30(1), 23–58. Garfield, ZH, Syme, KL, and Hagen, EH (2020) Universal and variable leadership dimensions across human societies. Evolution and Human Behavior, 41, 397–414. Garfield, ZH, von Rueden, C, and Hagen, EH (2019b) The evolutionary anthropology of political leadership. Leadership Quarterly, 30(1), 59–80. Gaulin, SJ, and Boster, JS (1990) Dowry as female competition. American Anthropologist, 92(4), 994–1005. Gaulin, SJC, and McBurney, DH (2001) Psychology: An Evolutionary Approach, United Kingdom: Prentice Hall/Pearson Education. Gaulin, SJC, and Schlegel, A (1980) Paternal confidence and paternal investment: A cross cultural test of a sociobiological hypothesis. Ethology and Sociobiology, 1(4), 301–309. Gaus, G (2021) The Open Society and Its Complexities, Oxford: Oxford University Press. Gavrilets, S (2012a) Human origins and the transition from promiscuity to pair-bonding. Proceedings of the National Academy of Sciences, 109(25), 9923–9928. Gavrilets, S (2012b) On the evolutionary origins of the egalitarian syndrome. Proceedings of the National Academy of Sciences, 109(35), 14069–14074. Gavrilets, S (2015) Collective action problem in heterogeneous groups. Philosophical Transactions of the Royal Society B: Biological Sciences, 370(1683), 20150016.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography Gavrilets, S, Anderson, DG, and Turchin, P (2010) Cycling in the complexity of early societies. Cliodynamics, 1, 58–80. Gavrilets, S, Duenez-Guzman, EA, and Vose, MD (2008) Dynamics of alliance formation and the egalitarian revolution. PLoS ONE, 3(10), e3293. Gavrilets, S, and Fortunato, L (2014) A solution to the collective action problem in between-group conflict with within-group inequality. Nature Communications, 5, 3526. Gavrilova, NS, Gavrilov, LA, Semyonova, VG, and Evdokushkina, GN (2004) Does exceptional human longevity come with a high cost of infertility?: Testing the evolutionary theories of aging. Annals of the New York Academy of Sciences, 1019(1), 513–517. Gazes, R, Hampton, R, and Lourenco, S (2017) Transitive inference of social dominance by human infants. Developmental Science, 20, 12367. Geary, D (2021) Evolution and sex differences in political engagement. Psychological Inquiry, 32, 96–104. Geary, DC (2006) Coevolution of paternal investment and cuckoldry in humans. In TK Shackelford and S Platek, eds., Female Infidelity and Paternal Uncertainty, New York: Cambridge University Press, 14–34. Geertz, C (1973) The Interpretation of Cultures, New York: Basic Books. Geniole, S, Bird, B, Ruddick, E, and Carré, J (2017) Effects of competition outcome on testosterone concentrations in humans: An updated meta-analysis. Hormones and Behavior, 92, 37–50. Geniole, S, Denson, T, Dixson, B, Carré, J, and McCormick, C (2015) Evidence from meta-analyses of the facial width-to-height ratio as an evolved cue of threat. PLoS ONE, 10, 0132726. Geniole, S, Proietti, V, and Bird, B (2019) Testosterone reduces the threat premium in competitive resource division. Proceedings of the Royal Society B: Biological Sciences, 286, 20190720. Georgiev, AV, Kuzawa, CW, and McDade, TW (2016) Early developmental exposures shape trade-offs between acquired and innate immunity in humans. Evolution, Medicine, and Public Health, 2016(1), 256–269. Gerhards, L, and Kosfeld, M (2020) I (do not) like you! But who cares? Gender differences in same-sex and mixed-sex teams. The Economic Journal, 130, 716–739. Gerkey, D (2013) Cooperation in context: Public goods games and post-Soviet collectives in Kamchatka, Russia. Current Anthropology, 54(2), 144–176.

449

Gervais, MM (2017) RICH economic games for networked relationships and communities: Development and preliminary validation in Yasawa, Fiji. Field Methods, 29(2), 113–129. Gettler, L (2016) Testosterone, fatherhood, and social networks. In WR Trevathan and KR Rosenberg, eds., Costly and Cute: Helpless Infants and Human Evolution, Albuquerque: University of New Mexico Press. Gettler, LT, Boyette, AH, and Rosenbaum, S (2020) Broadening perspectives on the evolution of human paternal care and fathers’ effects on children. Annual Review of Anthropology, 49, 141–160. Gettler, LT, McDade, TW, Agustin, SS, Feranil, AB, and Kuzawa, CW (2013) Do testosterone declines during the transition to marriage and fatherhood relate to men’s sexual behavior? Evidence from the Philippines. Hormones and Behavior, 64, 755–763. Gettler, LT, McDade, TW, Agustin, SS, Feranil, AB, and Kuzawa, CW (2015) Longitudinal perspectives on fathers’ residence status, time allocation, and testosterone in the Philippines. Adaptive Human Behavior and Physiology, 1, 124–149. Gettler, LT, McDade, TW, Feranil, AB, and Kuzawa, CW (2011) Longitudinal evidence that fatherhood decreases testosterone in human males. Proceedings of the National Academy of Sciences, 108, 16194–16199. Gibler, DM (2010) Outside-in: The effects of external threat on state centralization. Journal of Conflict Resolution, 54(4), 519–542. Gibson, M, and Lawson, D (2014) Applied Evolutionary Anthropology: Darwinian Approaches to Contemporary World Issues, New York: Springer. Gibson, M, and Mace, R (2005) Helpful grandmothers in rural Ethiopia: A study of the effect of kin on child survival and growth. Evolution and Human Behavior, 26, 469–482. Gibson, MA, and Gurmu, E (2011) Land inheritance establishes sibling competition for marriage and reproduction in rural Ethiopia. Proceedings of the National Academy of Sciences, 108(6), 2200–2204. Gibson, MA, and Lawson, DW (2011) “Modernization” increases parental investment and sibling resource competition: Evidence from a rural development initiative in Ethiopia. Evolution and Human Behavior, 32(2), 97–105. Gibson, MA, and Lawson, DW (2015) Applying evolutionary anthropology. Evolutionary Anthropology, 24(1), 3–14.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

450

Bibliography

Gibson, MA, and Mace, R (2002) Labor-saving technology and fertility increase in rural Africa. Current Anthropology, 43(4), 631–637. Gibson, MA, and Mace, R (2003) Strong mothers bear more sons in rural Ethiopia. Proceedings of the Royal Society B: Biological Sciences, 1(Suppl 1), 108–109. Gibson, MA, and Mace, R (2007) Polygyny, reproductive success and child health in rural Ethiopia: Why marry a married man? Journal of Biosocial Science, 39(2), 287–300. Gigerenzer, G (1991) From tools to theories: A heuristic of discovery in cognitive psychology. Psychological Review, 98(2), 254. Gigerenzer, G (2007) Fast and frugal heuristics: The tools of bounded rationality. In DJ Koehler and N Harvey, eds., Blackwell Handbook of Judgment and Decision Making, Malden: Blackwell Publishers, 62–88. Gil, D, and Culver, R (2011) Male ornament size in a passerine predicts the inhibitory effect of testosterone on macrophage phagocytosis. Functional Ecology, 25, 1278–1283. Gilbert, JDJ, and Manica, A (2015) The evolution of parental care in insects: A test of current hypotheses. Evolution, 69, 1255–1270. Gilby, I, Brent, L, and Wroblewski (2013) Fitness benefits of coalitionary aggression in male chimpanzees. Behavioral Ecology and Sociobiology, 67, 373–381. Gilchrist, JS, and Russell, AF (2007) Who cares? Individual contributions to pup care by breeders vs non-breeders in the cooperatively breeding banded mongoose (Mungos mungo). Behavioral Ecology and Sociobiology, 61, 1053–1060. Gildersleeve, K, Haselton, MG, and Fales, MR (2014) Do women’s mate preferences change across the ovulatory cycle? A meta-analytic review. Psychological Bulletin, 140(5), 1205. Gillborn, D (2016) Softly, softly: Genetics, intelligence and the hidden racism of the new geneism. Journal of Education Policy, 31(4), 365–388. Gillet, J, Cartwright, E, and van Vugt, M (2011) Selfish or servant leadership? Evolutionary predictions on leadership personalities in coordination games. Personality and Individual Differences, 51(3), 231–236. Gilman, A (1981) The development of social stratification in Bronze Age Europe. Current Anthropology, 22(1), 1–23. Gilovich, T, Vallone, R, and Tversky, A (1985) The hot hand in basketball: On the misperception of random sequences. Cognitive Psychology, 17(3), 295–314.

Gintis, H (2000a) Game Theory Evolving: A ProblemCentered Introduction to Modeling Strategic Behavior, Princeton: Princeton University Press. Gintis, H (2000b) Strong reciprocity and human sociality. Journal of Theoretical Biology, 206, 169–179. Gintis, H (2007) The evolution of private property. Journal of Economic Behavior and Organization, 64(1), 1–6. Gintis, H, Schaik, C, and Boehm, C (2015) Zoon Politicon: The evolutionary origins of human political systems. Current Anthropology, 56(3), 327–353. Gintis, H, Smith, EA, and Bowles, S (2001) Costly signaling and cooperation. Journal of Theoretical Biology, 213(1), 103–119. Giovas, CM, and Fitzpatrick, SM (2014) Prehistoric migration in the Caribbean: Past perspectives, new models and the ideal free distribution of West Indian colonization. World Archaeology, 46(4), 569–589. Giphart, R, and van Vugt, M (2018) Mismatch: How our Stone Age Brain Deceives Us Every Day (and What We Can Do about It), London: Robinson. Giraldeau, L-A, and Caraco, T (2000) Social Foraging Theory, Princeton: Princeton University Press. Glover, SM, and Towner, MC (2009) Long-distance dispersal to the mining frontier in late nineteen century Colorado. Behaviour, 146(4–5), 677–700. Glowacki, L (2020) The emergence of locally adaptive institutions: Insights from traditional social structures of East African pastoralists. Biosystems, 198, 104257. Glowacki, L, and von Rueden, C (2015) Leadership solves collective action problems in small-scale societies. Philosophical Transactions of the Royal Society B: Biological Sciences, 370(1683), 20150010. Glowacki, L, and Wrangham, R (2015) Warfare and reproductive success in a tribal population. Proceedings of the National Academy of Sciences, 112, 348–353. Gluckman, PD, and Hanson, MA (2008) Developmental and epigenetic pathways to obesity: An evolutionary-developmental perspective. International Journal of Obesity, 32(7), 62–71. Gluckman, PD, Hanson, MA, and Spencer, HG (2005) Predictive adaptive responses and human evolution. Trends in Ecology and Evolution, 20, 527–33. Godfray, HCJ (1995) Signaling of need between parents and young: Parent-offspring conflict and sibling rivalry. The American Naturalist, 146(1), 1–24. Godoy, R, Gurven, M, Byron, E, . . . Pérez, E (2004) Do markets worsen economic inequalities? Kuznets in the bush. Human Ecology, 32(3), 339–364.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography Godoy, R, Reyes-García, V, Byron, E, Leonard, WR, and Vadez, V (2005a) The effect of market economies on the well-being of indigenous peoples and on their use of renewable natural resources. Annual Review of Anthropology, 34, 121–138. Godoy, R, Reyes-Garcia, V, and Huanca, T (2007) Signaling by consumption in a native Amazonian society. Evolution and Human Behavior, 28, 124–134. Godoy, R, Reyes-García, V, Huanca, T, . . . Zhao, D (2005b) Why do subsistence-level people join the market economy? Testing hypotheses of push and pull determinants in Bolivian Amazonia. Journal of Anthropological Research, 61(2), 157–178. Goetz, CD, Pillsworth, EG, Buss, DM, and Conroy-Beam, D (2019) Evolutionary mismatch in mating. Frontiers in Psychology, 10, 2709. Goland, C (1993a) Agricultural risk management through diversity: Field scattering in Cuyo Cuyo, Peru. Culture and Agriculture, 45–46, 8–13. Goland, C (1993b) Field scattering as agricultural risk management: A case study from Cuyo Cuyo, Department of Puno, Peru. Mountain Research and Development, 13, 317–338. Goldizen, AW (1987) Tamarins and marmosets: Communal care of offspring. In B Smuts, D Cheney, R Seyfarth, R Wrangham, and T Struhsaker, eds., Primate Societies, Chicago: University of Chicago Press, 34–43. Goldman, N, and Pebley, A (1989) The demography of polygyny in Sub-Saharan Africa. In RJ Lesthaeghe, ed., Reproduction and Social Organization in SubSaharan Africa, Berkeley: University of California Press, 212–237. Goldstein, MC (1976) Fraternal polyandry and fertility in a high Himalayan valley in Northwest Nepal. Human Ecology, 4(3), 223–233. González-Forero, M, Faulwasser, T, and Lehmann, L (2017) A model for brain life history evolution. PLoS Computational Biology, 13(3), e1005380. Goodale, JC (1971) Tiwi Wives: A Study of the Women of Melville Island, North Australia, Seattle: University of Washington Press. Goodall, J (1986) The Chimpanzees of the Gombe: Patterns of Behavior, Cambridge: Cambridge University Press. Goodman, A, Koupil, I, and Lawson, DW (2012) Low fertility increases descendant socioeconomic position but reduces long-term fitness in a modern postindustrial society. Proceedings of the Royal Society B: Biological Sciences, 279(1746), 4342–4351.

451

Goodman, M, Griffin, P, Estioko-Griffin, A, and Grove, J (1985) The comparibility of hunting and mothering among the Agta hunter-gatherers of the Philippines. Sex Roles, 12, 1199–1209. Goody, EN (1982) Parenthood and Social Reproduction: Fostering and Occupational Roles in West Africa, Cambridge: Cambridge University Press. Goody, J (1976) Production and Reproduction: A Comparative Study of the Domestic Domain, Cambridge: Cambridge University Press. Gordon, DM (2016) From division of labor to the collective behavior of social insects. Behavioral Ecology and Sociobiology, 70(7), 1101–1108. Gottlieb, A (2009) Who minds the baby? In G Bentley and R Mace, eds., Substitute Parents Biological and Social Perspectives on Alloparenting in Human Societies, New York: Berghahn Books, 115–138. Gough, EK (1959) The Nayars and the definition of marriage. The Journal of the Royal Anthropological Institute of Great Britain and Ireland, 89(1), 23–34. Gough, EK (1960) Is the family universal? The Nayar case. In NW Bell and EF Vogel, eds., A Modern Introduction to the Family, Glencoe: Free Press, 80–96. Gough, EK (1965) A note on Nayar marriage. Man, 65(2), 8–11. Gould, ED, Moav, O, and Simhon, A (2008) The mystery of monogamy. American Economic Review, 98(1), 333–357. Gould, R (2002) The origins of status hierarchy: A formal theory and empirical test. American Journal of Sociology, 107, 1143–1178. Gould, R (2003) Collision of Wills, Chicago: University of Chicago Press. Gould, SJ (1991) Exaptation: A crucial tool for an evolutionary psychology. Journal of Social Issues, 47(3), 43–65. Gowaty, PA (1997) Sexual dialectics, sexual selection, and variation in reproductive behavior. In PA Gowaty, ed., Feminism and Evolutionary Biology, Springer, 351–384. Gowaty, PA, Kim, Y-K, and Anderson, WW (2012) No Evidence of Sexual Selection in a Repetition of Bateman’s Classic Study of Drosophila Melanogaster. Proceedings of the National Academy of Sciences, 109(29), 11740–11745. Graeber, D (2011) Debt: The First 5000 Years, Brooklyn: Melville House. Graeber, D, and Wengrow, D (2021) The Dawn of Everything: A New History of Humanity, New York: Farrar, Straus and Giroux.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

452

Bibliography

Grafen, A (1980) Opportunity cost, benefit, and degree of relatedness. Animal Behaviour, 28, 967–968. Grafen, A (1984) Natural selection, kin selection and group selection. In J Krebs and N Davies, eds., Behavioural Ecology: An Evolutionary Approach, Vol. 2, Oxford: Blackwell Scientific Publications, 62–84. Grafen, A (1990) Biological signals as handicaps. Journal of Theoretical Biology, 144, 517–546. Grafen, A (2006) Optimization of inclusive fitness. Journal of Theoretical Biology, 238(3), 541–563. Grant, MJ, and Behrman, JR (2010) Gender gaps in educational attainment in less developed countries. Population and Development Review, 36(1), 71–89. Gravlee, CC, Kennedy, DP, Godoy, R, and Leonard, WR (2009) Methods for collecting panel data: What can cultural anthropology learn from other disciplines? Journal of Anthropological Research, 65, 453–483. Gray, JP (1999) A corrected ethnographic atlas. World Cultures, 10(1), 24–85. Gray, PB, and Anderson, KG (2012) Fatherhood: Evolution and Human Paternal Behavior, Cambridge: Harvard University Press. Gray, PB, and Garcia, JR (2013) Evolution and Human Sexual Behavior. Cambridge: Harvard University Press. Gray, PB, Kahlenberg, SM, Barrett, ES, Lipson, SF, and Ellison, PT (2002) Marriage and fatherhood are associated with lower testosterone in males. Evolution and Human Behavior, 23, 193–201. Gray, PB, Straftis, AA, Bird, BM, McHale, TS, and Zilioli, S (2020) Human reproductive behavior, life history, and the challenge hypothesis: A 30-year review, retrospective and future directions. Hormones and Behavior 123, 104530. Gray, PB, Yang, CFJ, and Pope, HG (2006) Fathers have lower salivary testosterone levels than unmarried men and married non-fathers in Beijing, China. Proceedings of the Royal Society B: Biological Sciences, 273, 333–339. Gray, RD, Greenhill, SJ, and Ross, RM (2007) The pleasures and perils of Darwinizing culture (with phylogenies). Biological Theory, 2(4), 360–375. Greenaway, KH, and Cruwys, T (2019) The source model of group threat: Responding to internal and external threats. American Psychologist, 74(2), 218. Greene, PJ (1978) Promiscuity, paternity, and culture. American Ethnologist, 5(1), 151–159. Greiling, H, and Buss, DM (2000) Women’s sexual strategies: The hidden dimension of extra-pair

mating. Personality and Individual Differences, 28(5), 929–963. Gremillion, KJ (2004) Seed processing and the origins of food production in eastern North America. American Antiquity, 69(2), 215–233. Gremillion, KJ, and Piperno, DR (2009) Human behavioral ecology, phenotypic (developmental) plasticity, and agricultural origins. Current Anthropology, 50(5), 615–619. Grenier, C (2013) The Vezo way of life: “Traditional” fishing and globalization on the southwest coast of Madagascar. Annales de Géographie, 693(5), 549–571. Griffin, AS, Alonzo, SH, and Cornwallis, CK (2013) Why do cuckolded males provide paternal care? PLoS Biology, 11(3), 1001520. Griffin, AS, Sheldon, BC, and West, SA (2005) Cooperative breeders adjust offspring sex ratios to produce helpful helpers. The American Naturalist, 166(5), 628–632. Griffin, AS, and West, SA (2002) Kin selection: Fact and fiction. Trends in Ecology and Evolution, 17(1), 15–21. Griffin, AS, and West, SA (2003) Kin discrimination and the benefit of helping in cooperatively breeding vertebrates. Science, 302, 634–636. Griffith, SC, Owens, IP, and Thuman, KA (2002) Extra pair paternity in birds: A review of interspecific variation and adaptive function. Molecular Ecology, 11(11), 2195–2212. Griffiths, P, Hinde, A, and Matthews, Z (2001) Infant and child mortality in three culturally contrasting states of India. Journal of Biosocial Science, 33(4), 603–622. Grinnell, J, Packer, C, and Pusey, AE (1995) Cooperation in male lions: Kinship, reciprocity or mutualism? Animal Behaviour, 49(1), 95–105. Grosjean, P, and Khattar, R (2019) It’s raining men! Hallelujah? The long-run consequences of malebiased sex ratios. The Review of Economic Studies, 86, 723–754. Grueter, C, Isler, K, and Dixson, B (2015) Are badges of status adaptive in large complex primate groups? Evolution and Human Behavior, 36, 398–406. Grueter, CC, Chapais, B, and Zinner, D (2012) Evolution of multilevel social systems in nonhuman primates and humans. International Journal of Primatology, 33, 1002–1037. Gruijters, SL, and Fleuren, BP (2018) Measuring the unmeasurable. Human Nature, 29(1), 33–44.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography Guala, F (2012) Reciprocity: Weak or strong? What punishment experiments do (and do not) demonstrate. Behavioral and Brain Sciences, 35(1), 1–59. Guddemi, P (1992) When horticulturalists are like hunter-gatherers: The Sawiyano of Papua New Guinea. Ethnology, 31(4), 303–314. Guemple, L (1986) Men and women, husbands and wives: The role of gender in traditional Inuit society. Études Inuit Studies, 10, 9–24. Guillon, M, and Mace, R (2016) A phylogenetic comparative study of Bantu kinship terminology finds limited support for its co-evolution with social organisation. PLoS ONE, 11(3), 0147920. Gulliver, PH (1955) The Family Herds: A Study of Two Pastoral Tribes in East Africa, The Jie and Turkana, London: Routledge. Gupta, A, and Ferguson, J (1992) ‘Beyond culture’: Space, identity, and the politics of difference. Cultural Anthropology, 7, 6–23. Gur, A, Nas, K, Cevik, R, Sarac, AJ, Ataoglu, S, and Karakoc, M (2003) Influence of number of pregnancies on bone mineral density in postmenopausal women of different age groups. Journal of Bone and Mineral Metabolism, 21(4), 234–241. Gur, RE, Moore, TM, Rosen, AF, . . . Satterthwaite, TD (2019) Burden of environmental adversity associated with psychopathology, maturation, and brain behavior parameters in youths. JAMA Psychiatry, 76(9), 966–975. Gürerk, Ö, Irlenbusch, B, and Rockenbach, B (2006) The competitive advantage of sanctioning institutions. Science, 312, 108–111. Gursky, S (2000) Allocare in a nocturnal primate: Data on the spectral tarsier, Tarsius spectrum. Folia Primatologica, 71(1–2), 39–54. Gurven, M (2004) To give and to give not: The behavioral ecology of human food transfers. Behavioral and Brain Sciences, 27(4), 543–559. Gurven, M (2006) The evolution of contingent cooperation. Current Anthropology, 47(1), 185–192. Gurven, M, Allen-Arave, W, Hill, K, and Hurtado, A (2000a) It’s a wonderful life: Signaling generosity among the Ache of Paraguay. Evolution and Human Behavior, 21, 263–282. Gurven, M, Borgerhoff Mulder, M, Hooper, PL, and Bell, A (2010) Domestication alone does not lead to inequality: Intergenerational wealth transmission among horticulturalists. Current Anthropology, 51(1), 49–64. Gurven, M, Costa, M, Trumble, B, . . . Kaplan, H (2016a) Health costs of reproduction are minimal despite

453

high fertility, mortality and subsistence lifestyle. Scientific Reports, 6(1), 1–10. Gurven, M., Davison, R., Kraft, T. 2020. The optimal timing of teaching and learning across the life course. Philosophical Transactions of the Royal Society B 375: 20190500. Gurven, M, and Hill, K (2009) Why do men hunt? A reevaluation of “Man the Hunter” and the sexual division of labor. Current Anthropology, 50, 51–74. Gurven, M, Hill, K, and Kaplan, H (2002) From forest to reservation: Transitions in food-sharing behavior among the Ache of Paraguay. Journal of Anthropological Research, 58(1), 93–120. Gurven, M, Hill, K, Kaplan, H, Hurtado, A, and Lyles, R (2000b) Food transfers among Hiwi foragers of Venezuela: Tests of reciprocity. Human Ecology, 28(2), 171–218. Gurven, M, Jaeggi, A, von Rueden, C, Hooper, P, and Kaplan, H (2015) Does market integration buffer risk, erode traditional sharing practices and increase inequality? A test among Bolivian forager-farmers. Human Ecology, 43, 515–530. Gurven, M, and Kaplan, H (2006) Determinants of time allocation across the lifespan: A theoretical model and an application to the Machiguenga and Piro of Peru. Human Nature, 17, 1–49. Gurven, M, and Kaplan, H (2007) Longevity among hunter-gatherers: A cross-cultural examination. Population and Development Review, 33(2), 321–365. Gurven, M, and Kaplan, H (2008) Beyond the grandmother hypothesis: Evolutionary models of longevity. In J Sokolovsky, ed., Cultural Context of Aging, 3rd edn, Westport: Praeger Publishers, 53–66. Gurven, M, Kaplan, H, and Gutierrez, M (2006) How long does it take to become a proficient hunter? Implications for the evolution of delayed growth. Journal of Human Evolution, 51, 454–470. Gurven, M, Kraft, TS, Alami, S, . . . Trumble, B (2020) Rapidly declining body temperature in a tropical human population. Science Advances, 6, eabc6599. Gurven, M, Stieglitz, J, Hooper, PL, Gomes, C, and Kaplan, H (2012) From the womb to the tomb: The role of transfers in shaping the evolved human life history. Experimental Gerontology, 47(10), 807–813. Gurven, M, Stieglitz, J, Trumble, B, . . . Kaplan, H (2017) The Tsimane Health and Life History Project: Integrating anthropology and biomedicine. Evolutionary Anthropology, 26, 54–73. Gurven, M, and von Rueden, C (2006) Hunting, social status and biological fitness. Social Biology, 53, 81–99.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

454

Bibliography

Gurven, M, von Rueden, C, Massenkoff, M, Kaplan, H, and Lero Vie, M (2013) How universal is the Big Five? Testing the five-factor model of personality variation among forager–farmers in the Bolivian Amazon. Journal of Personality and Social Psychology, 104(2), 354. Gurven, M, and Walker, R (2006) Energetic demand of multiple dependents and the evolution of slow human growth. Proceedings of the Royal Society B: Biological Sciences, 273, 835–841. Gurven, M, Winking, J, Kaplan, H, von Rueden, C, and McAllister, L (2009) A bioeconomic approach to marriage and the sexual division of labor. Human Nature, 20(2), 151–183. Gurven, MD (2018) Broadening horizons: Sample diversity and socioecological theory are essential to the future of psychological science. Proceedings of the National Academy of Sciences, 115(45), 11420–11427. Gurven, MD (2020) Greater humility can help expand evolutionary social science. Evolution and Human Behavior, 41(5), 456–457. Gurven, MD, and Davison, RJ (2019) Periodic catastrophes over human evolutionary history are necessary to explain the forager population paradox. Proceedings of the National Academy of Sciences, 116(26), 12758–12766. Gurven, MD and Gomes, CM (2017) Mortality, senescence, and life span. In MN Muller, RW Wrangham, and DR Pilbeam, eds., Chimpanzees and Human Evolution, The Belknap Press of Harvard University Press, 181–216. Gurven, MD, and Lieberman, DE (2020) WEIRD bodies: Mismatch, medicine and missing diversity, Evolution and Human Behavior, 41(5), 330–340. Gurven, MD, Trumble, BC, Stieglitz, J, . . . Pontzer, H (2016b) High resting metabolic rate among Amazonian forager-horticulturalists experiencing high pathogen burden. American Journal of Physical Anthropology, 161(3), 414–425. Guttentag, M, and Secord, PF (1983) Too Many Women?: The Sex Ratio Question, SAGE Publications. Guzmán, RA, Rodríguez-Sickert, C, and Rowthorn, R (2007) When in Rome, do as the Romans do: The coevolution of altruistic punishment, conformist learning, and cooperation. Evolution and Human Behavior, 28, 112–117. Haas, R, Watson, J, Buonasera, T, . . . Parker, G (2020) Female hunters of the early Americas. Science Advances, 6(45), 0310. Hadley, C, and Hruschka, D (2017) Stability and change in in-group mate preferences among young people in

Ethiopia are predicted by food security and gender attitudes, but not by expected pathogen exposures. Human Nature, 28(4), 395–406. Hadley, C, and Patil, CL (2006) Food insecurity in rural Tanzania is associated with maternal anxiety and depression. American Journal of Human Biology, 18(3), 359–368. Hagen, EH (1999) The functions of postpartum depression. Evolution and Human Behavior, 20, 325–359. Hagen, EH, and Barrett, HC (2009) Cooperative breeding and adolescent siblings. Current Anthropology, 50(5), 727–737. Hagen, EH, Roulette, CJ, and Sullivan, RJ (2013) Explaining human recreational use of “pesticides”: The neurotoxin regulation model of substance use vs. the hijack model and implications for age and sex differences in drug consumption. Frontiers in Psychology, 4, 1–21. Haicheng, W (2011) Writing and the Ancient State: Early China in Comparative Perspective, Cambridge: Cambridge University Press. Haldane, J (1955) Population genetics. New Biology, 18, 34–51. Hales, CN, and Barker, DJP (1992) Type 2 (non-insulindependent) diabetes mellitus: The thrifty phenotype hypothesis. Diabetologia, 35, 595–601. Halliday, TR (1983) The study of mate choice. In P Bateson, ed., Mate Choice, Cambridge: Cambridge University Press, 1–32. Halstead, P, and O’Shea, J, eds. (1989) Bad Year Economics: Cultural Responses to Risk and Uncertainty, Cambridge: Cambridge University Press. Hames, R (1987) Garden labor exchange among the Ye’kwana. Ethology and Sociobiology, 8, 259. Hames, R (1988) The allocation of parental care among the Ye’kwana. In L Betzig, M Borgerhoff Mulder, and P Turke, eds., Human Reproductive Behavior: A Darwinian Perspective, Cambridge: Cambridge University Press, 237–251. Hames, R (1989) Time, efficiency, and fitness in the Amazonian protein quest. Research in Economic Anthropology, 11, 43–85. Hames, R (1992) Time allocation. In EA Smith and B Winterhalder, eds., Evolutionary Ecology and Human Behavior, New York: Aldine de Gruyter, 203–236. Hames, R, and McCabe, C (2007) Meal sharing among the Ye’kwana. Human Nature, 18, 1–21. Hames, RB (1979) Relatedness and interaction among the Ye’kwana: A preliminary analysis. In NA Chagnon and W Irons, eds., Evolutionary Biology and Human Social Behavior: An Anthropological

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography Perspective, North Scituate: Duxbury Press, 238–249. Hamilton, M, Milne, B, Walker, R, Burger, O, and Brown, J (2007) The complex structure of hunter-gatherer social networks. Proceedings of the Royal Society B: Biological Sciences, 274(1622), 2195–2202. Hamilton, WD (1964) The genetical evolution of social behavior I and II. Journal of Theoretical Biology, 7, 1–52. Hamilton, WD (1966) The molding of senescence by natural selection. Journal of Theoretical Biology, 12, 12–45. Hamilton, WD (1967) Extraordinary sex ratios. Science, 156, 477–488. Hamilton, WD (1975) Innate social aptitudes of man: An approach from evolutionary genetics, In R Fox, ed., Biosocial Antropology, London: Malaby Press, 133–153. Hamilton, WD (1982) Pathogens as causes of genetic diversity in their host populations. In RM Anderson and RM May, eds., Population Biology of Infectious Diseases: Report of the Dahlem Workshop on Population Biology of Infectious Disease Agents Berlin 1982, March 14–19, Berlin: Springer, 269–296. Hamilton, WD, and May, RM (1977) Dispersal in stable habitats. Nature, 269(5629), 578–581. Hammer, M, and Foley, R (1996) Longevity, life history and allometry: How long did hominids live. Human Evolution, 11, 61–66. Hammerstein, P, and Noë, R (2016) Biological trade and markets. Philosophical Transactions of the Royal Society B: Biological Sciences, 371(1687), 20150101. Hampshire, KR, Porter, G, Agblorti, S, Munthali, A, and Abane, A (2015) Context matters: Fostering, orphanhood and schooling in sub-Saharan Africa. Journal of Biosocial Science, 47, 141–164. Handley, C, and Mathew, S (2020) Human large-scale cooperation as a product of competition between cultural groups. Nature Communications, 11, 702. Hank, K, and Buber, I (2009) Grandparents caring for their grandchildren: Findings from the 2004 survey of health, aging and retirement in Europe. Journal of Family Issues, 30, 53–73. Hansson, B, Bensch, S, and Hasselquist, D (1997) Infanticide in great reed warblers: Secondary females destroy eggs of primary females. Animal Behaviour, 54(2), 297–304. Hao, Y, Armbruster, D, Cronk, L, and Aktipis, C (2015) Need-based transfers on a network: A model of risk-

455

pooling in ecologically volatile environments. Evolution and Human Behavior, 36(4), 265–273. Harcourt, A, and de Waal, F (1992) Coalitions and Alliances in Humans and Other Animals, Oxford: Oxford University Press. Hardin, G (1968) The tragedy of the commons. Science, 162, 1243–1248. Hardy, K, Brand-Miller, J, Brown, KD, Thomas, MG, and Copeland, L (2015) The importance of dietary carbohydrate in human evolution. The Quarterly Review of Biology, 90(3), 251–268. Harper, TK, Diachenko, A, Rassamakin, YY, and Kennett, DJ (2019) Ecological dimensions of population dynamics and subsistence in Neo-Eneolithic Eastern Europe. Journal of Anthropological Archaeology, 53, 92–101. Harrell, S (1997) Human Families, Boulder: Westview Press. Harrington, WE, Kanaan, SB, Muehlenbachs, A, . . . Nelson, JL (2017) Maternal microchimerism predicts increased infection but decreased disease due to plasmodium falciparum during early childhood. Journal of Infectious Disease, 215, 1445–1451. Hart, IA, Brenner-Coltrain, J, Boomgarden, S, . . . Lewis, M (2021) Evidence for a winter-snowpack derived water source for the Fremont maize farmers of Range Creek Canyon, Utah, USA. The Holocene, 31(3), 446–456. Hart, O, and Moore, J (2005) On the design of hierarchies: Coordination versus specialization. Journal of Political Economy, 113(4), 675–702. Hartley, T (2019) The continuing evolution of ownership. PLoS ONE, 14(2), 0211871. Hartung, J (1976) On natural selection and the inheritance of wealth. Current Anthropology, 17(4), 607–622. Hartung, J (1982) Polygyny and inheritance of wealth. Current Anthropology, 23(1), 1–12. Hartung, J (1985) Matrilineal inheritance: New theory and analysis. Behavioral and Brain Sciences, 8(4), 661–670. Hartung, J (1997) If I had to do it over. In L Betzig, ed., Human Nature, New York: Oxford University Press, 344–348. Hasegawa, M, and Kutsukake, N (2015) Bayesian competitiveness estimation predicts dominance turnover among wild male chimpanzees. Behavioral Ecology and Sociobiology, 69, 89–99. Hassan, A, Lawson, D, Schaffnit, S, Urassa, M, and Sear, R (2021) Childcare in transition: Evidence that patterns of childcare differ by degree of market

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

456

Bibliography

integration in North-Western Tanzania. doi:10.31219/osf.io/gtc6k. Hassan, A, Schaffnit, S, Sear, R, Urassa, M, and Lawson, D (2019) Fathers favour sons, mothers do not discriminate: Sex-biased parental care in northwestern Tanzania. Evolutionary Human Sciences, 1, e13. Hastik, R, Geitner, C, and Neuburger, M (2013) Amazonian dark earths in Bolivia? A soil study of anthropogenic ring ditches near Baures (eastern Llanos de Mojos. Erdkunde, 67(2), 137–149. Hatchwell, BJ (2009) The evolution of cooperative breeding in birds: Kinship, dispersal and life history. Philosophical Transactions of the Royal Society, B: Biological Sciences, 364, 3217–3227. Hatchwell, BJ, and Komdeur, J (2000) Ecological constraints, life history traits and the evolution of cooperative breeding. Animal Behaviour, 59(6), 1079–1086. Hatchwell, BJ, Ross, DJ, Fowlie, MK, and McGowan, A (2001) Kin discrimination in cooperatively breeding long-tailed tits. Proceedings of the Royal Society, 268, 885–890. Hatters Friedman, S, and Resnick, PJ (2007) Child murder by mothers: Patterns and prevention. World Psychiatry, 6(3), 137–41. Hauert, C, and Szabó, G (2005) Game theory and physics. American Journal of Physics, 73(5), 405–414. Haun, D, and Over, H (2015) Like me: A homophilybased account of human culture. In T Breyer, ed., Epistemological Dimensions of Evolutionary Psychology, New York: Springer, 117–130. Haushofer, J, and Fehr, E (2014) On the psychology of poverty. Science, 344(6186), 862–867. Havlíˇcek, J, Winternitz, J, and Roberts, SC (2020) Major histocompatibility complex-associated odour preferences and human mate choice: Near and far horizons. Philosophical Transactions of the Royal Society B: Biological Sciences, 375(1800), 20190260. Hawkes, K (1991) Showing off: Tests of an hypothesis about men’s foraging goals. Ethology and Sociobiology, 12, 29–54. Hawkes, K (1992) Sharing and collective action. In EA Smith and B Winterhalder, eds., Evolutionary Ecology and Human Behavior, New York: Aldine de Gruyter, 269–300. Hawkes, K (1993) Why hunter-gatherers work – An ancient version of the problem of public-goods. Current Anthropology, 34(4), 341–361. Hawkes, K (2003) Grandmothers and the evolution of human longevity. American Journal of Human Biology, 15(3), 380–400.

Hawkes, K, and Bliege Bird, R (2002) Showing off, handicap signaling, and the evolution of men’s work. Evolutionary Anthropology, 11(2), 58–67. Hawkes, K, Hill, K, and O’Connel, JF (1982) Why hunters gather: Optimal foraging and the Aché of eastern Paraguay. American Ethnologist, 9(2), 379–398. Hawkes, K, and O’Connell, J (1992) On optimal foraging models and subsistence transitions. Current Anthropology, 33(1), 63–66. Hawkes, K, O’Connell, J, and Blurton Jones, N (1989) Hardworking Hadza grandmothers. In V Standen and RA Foley, eds., Comparative Socioecology: The Behavioral Ecology of Mammals and Man, London: Basil Blackwell Press, 341–366. Hawkes, K, O’Connell, J, and Blurton Jones, N (1995) Hadza children’s foraging: Juvenile dependency, social arrangements, and mobility among huntergatherers. Current Anthropology, 36(4), 688–700. Hawkes, K, O’Connell, J, and Blurton Jones, N (1997) Hadza women’s time allocation, offspring provisioning and the evolution of long postmenopausal life spans. Current Anthropology, 38(4), 551–577. Hawkes, K, O’Connell, J, and Blurton Jones, N (2018) Hunter-gatherer studies and human evolution: A very selective review. American Journal of Physical Anthropology, 165(4), 777–800. Hawkes, K, O’Connell, J, Blurton Jones, N, Alvarez, H, and Charnov, E (1998) Grandmothering, menopause and the evolution of human life histories. Proceedings of the National Academy of Sciences, 95, 1336–1339. Hawkes, K, O’Connell, JF, and Blurton Jones, NG (1991) Hunting income patterns among the Hadza: Big game, common goods, foraging goals and the evolution of the human diet. Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, 334(1270), 243–251. Hawkes, K, O’Connell, JF, and Blurton Jones, NG (2001a) Hunting and nuclear families: Some lessons from the Hadza about men’s work. Current Anthropology, 42(5), 681–709. Hawkes, K, O’Connell, JF, Charnov, EL, and Hill, K (1985) How much is enough?: Hunters and limited needs. Ethology and Sociobiology, 6, 3–15. Hawkes, K, O’Connell, JF, and Jones, NGB (2001b) Hadza meat sharing. Evolution and Human Behavior, 22(2), 113–142. Hawley, P (2014) The duality of human nature: Coercion and prosociality in youth’s hierarchy ascension and social success. Current Directions in Psychological Science, 23, 433–438.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography Hayden, B, Deal, M, Cannon, A, and Casey, J (1986) Ecological determinants of women’s status among hunter-gatherers. Human Evolution, 1, 449–474. He, Q-Q, Zhang, Z, Zhang, J-X, . . . Tao, Y (2013) Potentials-attract or likes-attract in human mate choice in China. PLoS ONE, 8(4), e59457. Heath, DB (1958) Sexual division of labor and crosscultural research. Social Forces, 37(1), 77–79. Hedges, S, Borgerhoff Mulder, M, James, S, and Lawson, DW (2016) Sending children to school: Rural livelihoods and parental investment in education in northern Tanzania. Evolution and Human Behavior, 37(2), 142–151. Hedges, S, Lawson, DW, Todd, J, Urassa, M, and Sear, R (2019a) Sharing the load: The influence of coresident children on the intra-household allocation of work and schooling in North-Western Tanzania. Demography, 56(5), 1931–1956. Hedges, S, Sear, R, Todd, J, Urassa, M, and Lawson, D (2018) Trade-offs in children’s time allocation: Mixed support for embodied capital models of the demographic transition in Tanzania. Current Anthropology, 59(5), 644–654. Hedges, S, Sear, R, Todd, J, Urassa, M, and Lawson, DW (2019b) Earning their keep? Fostering, children’s education and work in North-Western Tanzania. Demographic Research, 41, 263–292. Heinsohn, R, and Legge, S (1999) The cost of helping. Trends in Ecology and Evolution, 14, 53–57. Heldstab, SA, Isler, K, Burkart, JM, and van Schaik, CP (2019) Allomaternal care, brains and fertility in mammals: Who cares matters. Behavioral Ecology and Sociobiology, 73(6), 1–13. Helfrecht, C, and Meehan, CL (2016) Sibling effects on nutritional status: Intersections of cooperation and competition across development. American Journal of Human Biology, 28(2), 159–170. Helfrecht, C, Roulette, JW, Lane, A, Sintayehu, B, and Meehan, CL (2020) Life history and socioecology of infancy. American Journal of Physical Anthropology, 173(4), 619–629. Helle, S, Lummaa, V, and Jokela, J (2005) Are reproductive and somatic senescence coupled in humans? Late, but not early, reproduction correlated with longevity in historical Sami women. Proceedings of the Royal Society B: Biological Sciences, 272(1558), 29–37. Helle, S, Lummaa, V, and Jokela, J (2008) Marrying women 15 years younger maximized men’s evolutionary fitness in historical Sami. Biology Letters, 4(1), 75–78.

457

Hemming, J (1978) Red Gold: The Conquest of the Brazilian Indians, Cambridge: Harvard University Press. Henrich, J (2004a) Cultural group selection, coevolutionary processes and large-scale cooperation. Journal of Economic Behavior and Organization, 53(1), 3–35. Henrich, J (2004b) Demography and cultural evolution: How adaptive cultural processes can produce maladaptive losses – The Tasmanian case. American Antiquity, 69, 197–214. Henrich, J (2015) The Secret of our Success: How Culture Is Driving Human Evolution, Domesticating our Species, and Making us Smarter, Princeton: Princeton University Press. Henrich, J (2020) The WEIRDest People in the World: How the West Became Psychologically Peculiar and Particularly Prosperous, New York: Macmillan. Henrich, J, and Boyd, R (1998) The evolution of conformist transmission and the emergence of betweengroup differences. Evolution and Human Behavior, 19, 215–241. Henrich, J, and Boyd, R (2001) Why people punish defectors: Weak conformist transmission can stabilize costly enforcement of norms in cooperative dilemmas. Journal of Theoretical Biology, 208(1), 79–89. Henrich, J, and Boyd, R (2008) Division of labor, economic specialization, and the evolution of social stratification. Current Anthropology, 49(4), 715–724. Henrich, J, Boyd, R, and Bowles, S (2001) In search of homo economicus: Behavioral experiments in 15 small-scale societies. American Economic Review, 91, 73–78. Henrich, J, Boyd, R, Bowles, S, . . . Ensminger, J (2005) “Economic man” in cross-cultural perspective: Behavioral experiments in 15 small-scale societies. Behavioral and Brain Sciences, 28(6), 795–815. Henrich, J, Boyd, R, and Richerson, P (2012) The puzzle of monogamous marriage. Philosophical Transactions of the Royal Society B: Biological Sciences, 367, 657–669. Henrich, J, Chudek, M, and Boyd, R (2015) The big man mechanism: How prestige fosters cooperation and creates prosocial leaders. Philosophical Transactions of the Royal Society B: Biological Sciences, 370(1683), 20150013. Henrich, J, and Gil-White, FJ (2001) The evolution of prestige: Freely conferred deference as a mechanism for enhancing the benefits of cultural transmission. Evolution and Human Behavior, 22(3), 165–196.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

458

Bibliography

Henrich, J, Heine, SJ, and Norenzayan, A (2010) The weirdest people in the world? Behavioral and Brain Sciences, 33(2–3), 61–83. Henrich, J, and McElreath, R (2003) The evolution of cultural evolution. Evolutionary Anthropology, 12, 123–135. Henrich, J, and McElreath, R (2007) Dual inheritance theory: The evolution of human cultural capacities and cultural evolution. In R Dunbar and L Barrett, eds., Oxford Handbook of Evolutionary Psychology, Oxford: Oxford University Press, 555–570. Hernández, CE, Rodríguez-Serrano, E, Avaria-Llautureo, J, and Meade, A (2013) Using phylogenetic information and the comparative method to evaluate hypotheses in macroecology. Methods in Ecology and Evolution, 4(5), 401–415. Hertrich, V (2017) Trends in age at marriage and the onset of fertility transition in Sub-Saharan Africa. Population and Development Review, 43(51), 112–137. Hertwig, R, Davis, JN, and Sulloway, FJ (2002) Parental investment: How an equity motive can produce inequality. Psychological Bulletin, 128(5), 728–745. Hertz, T (2007) Trends in the intergenerational elasticity of family income in the United States. Industrial Relations, 46(1), 22–50. Hess, N, and Hagen, E (2006) Sex differences in informational aggression: Psychological evidence from young adults. Evolution and Human Behavior, 27, 231–245. Hewlett, B (2006) Cultural diversity among African pygmies. In S Kent, ed., Cultural Diversity among Twentieth-Century Foragers: An African Perspective, Cambridge; London: Cambridge University Press, 215–244. Hewlett, B, Lamb, M, Leyendecker, B, and Scholmerich, ˝ A (2000) Parental investment strategies among Aka foragers, Ngandu farmers and Euro-American urban-industrialists. In L Cronk, N Chagnon, and W Irons, eds., Adaptation and Human Behavior: An Anthropological Perspective, New York: Aldine de Gruyter, 155–178. Hewlett, BS (1991a) Demography and childcare in preindustrial societies. Journal of Anthropological Research, 47(1), 1–37. Hewlett, BS (1991b) Intimate Fathers. The Nature and Context of Aka Pgymy Paternal Infant Care, Ann Arbor: The University of Michigan Press. Hewlett, BS, and Cavalli-Sforza, L (1986) Cultural transmission among Aka pygmies. American Anthropologist, 88, 922–934.

Hewlett, BS, and Winn, S (2014) Allomaternal Nursing in Humans. Current Anthropology, 55(2), 200–229. Heyer, E, Brandenburg, J, and Leonardi, M (2015) Patrilineal populations show more male transmission of reproductive success than cognatic populations in Central Asia, which reduces their genetic diversity. American Journal of Physical Anthropology, 157, 537–543. Hill, CM and Ball, HL (1996) Abnormal births and other “ill omens” The adaptive case for infanticide. Human Nature, 7, 381–401. Hill, JD, and Santos-Granero, F (2002) Comparative Arawakan Histories: Rethinking Language Family and Culture Area in Amazonia, Urbana: University of Illinois. Hill, K (1988) Macronutrient modifications of optimal foraging theory: An approach using indifference curves applied to some modern foragers. Human Ecology, 16, 157–197. Hill, K (1993) Life history theory and evolutionary anthropology. Evolutionary Anthropology, 2(3), 78–88. Hill, K, Barton, M, and Hurtado, AM (2009) The emergence of human uniqueness: Characters underlying behavioral modernity. Evolutionary Anthropology, 18, 187–200. Hill, K, and Hurtado, AM (1991) The evolution of reproductive senescence and menopause in human females. Human Nature, 2, 315–350. Hill, K, and Hurtado, AM (2009) Cooperative breeding in South American hunter-gatherers. Proceedings of the Royal Society B: Biological Sciences, 276(1674), 3863–3870. Hill, K, Kaplan, H, Hawkes, K, and Hurtado, AM (1987) Foraging decisions among Aché hunter-gatherers: New data and implications for optimal foraging models. Ethology and Sociobiology, 8(1), 1–36. Hill, K, and Kintigh, K (2009) Can anthropologists distinguish good and poor hunters? Implications for hunting hypotheses, sharing conventions, and cultural transmission. Current Anthropology, 50(3), 369–378. Hill, K, Walker, R, Božiˇcevi´c, M, . . . Wood, B (2011) Co-residence patterns in hunter-gatherer societies show unique human social structure. Science, 331(6022), 1286–1289. Hill, KR, and Hurtado, AM (1996) Ache Life History: The Ecology and Demography of a Foraging People, New York: Aldine de Gruyter. Hill, KR, and Kaplan, H (1999) Life history traits in humans: Theory and empirical studies. Annual Review of Anthropology, 28, 397–430.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography Hill, KR, Wood, BM, Baggio, J, Hurtado, AM, and Boyd, RT (2014) Hunter-gatherer inter-band interaction rates: Implications for cumulative culture. PLoS ONE, 9(7), e102806. Hill, RA, Bentley, RA, and Dunbar, RIM (2008) Network scaling reveals consistent fractal pattern in hierarchical mammalian societies. Biology Letters, 4(6), 748–751. Hillemann, F, Beheim, BA, and Ready, E (2023) Socioeconomic predictors of Inuit hunting choices and their implications for climate change adaptation. Philosophical Transactions of the Royal Society B: Biological Sciences, 378, 20220395. Hills, TT, Jones, MN, and Todd, PM (2012) Optimal foraging in semantic memory. Psychological Review, 119(2), 431. Hills, TT, Todd, PM, and Goldstone, RL (2008) Search in external and internal spaces: Evidence for generalized cognitive search processes. Psychological Science, 19(8), 802–808. Hilton, NZ, Harris, GT, and Rice, ME (2015) The stepfather effect in child abuse: Comparing discriminative parental solicitude and antisociality. Psychology of Violence, 5(1), 8–15. Hirschman, AO (1970) Voice, and Loyalty: Responses to Decline in Firms, Organizations, and States, Cambridge: Harvard University Press. Hirshleifer, D, and Rasmussen, E (1989) Cooperation in a repeated prisoner’s dilemma game with ostracism. Journal of Economic Behavior and Organization, 12, 87–106. Hirth, KG (2013) The merchant’s world: Commercial diversity and the economics of interregional exchange in highland Mesoamerica. In KG Hirth and J Pillsbury, eds., Merchants, Markets, and Exchange in the Pre-Columbian World, Washington: Dumbarton Oaks, 85–112. Hitchcock, RK, Crowell, AL, Brooks, AS, Yellen, JE, Ebert, JI, and Osborn, AJ (2019) The ethnoarchaeology of ambush hunting: A case study of ǂGi Pan, western Ngamiland, Botswana. African Archaeological Review, 36(1), 119–144. Hobson, E, Monster, D, and DeDeo, S (2021) Aggression heuristics underlie animal dominance hierarchies and provide evidence of group-level social information. Proceedings of the National Academy of Sciences, 118, 2022912118. Hodges-Simeon, C, Gurven, M, and Gaulin, S (2015) The low male voice is a costly signal of phenotypic quality among Bolivian adolescents. Evolution and Human Behavior, 36, 294–302.

459

Hoebel, EA (1954) The Law of Primitive Man, Cambridge: Harvard University Press. Hofstra, B, Kulkarni, VV, Munoz-Najar Galvez, S, He, B, Jurafsky, D, and McFarland, DA (2020) The diversity–innovation paradox in science. Proceedings of the National Academy of Sciences, 117(17), 9284–9291. Holbrook, C, and Fessler, D (2013) Sizing up the threat: The envisioned physical formidability of terrorists tracks their leaders’ failures and successes. Cognition, 127, 46–56. Holden, C, and Mace, R (2009) Phylogenetic analysis of the evolution of lactose digestion in adults. Human Biology, 81, 597–619. Holden, CJ, and Mace, R (2003a) Matriliny as daughterbiased investment. Evolution and Human Behavior, 24(2), 99–112. Holden, CJ, and Mace, R (2003b) Spread of cattle led to the loss of matrilineal descent in Africa: A coevolutionary analysis. Proceedings of the Royal Society B: Biological Sciences, 270(1532), 2425–2433. Holekamp, K, and Strauss, E (2016) Aggression and dominance: An interdisciplinary overview. Current Opinion in Behavioral Sciences, 12, 44–51. Holekamp, KE, Smale, L, Berg, R, and Cooper, SM (1997) Hunting rates and hunting success in the spotted hyena (Crocuta crocuta). Journal of Zoology, 242(1), 1–15. Holmberg, AR (1950) Nomads of the Long Bow: The Siriono of Eastern Bolivia, Prospect Heights: Waveland Press. Holmboe, SA, Priskorn, L, Jørgensen, N, . . . Andersson, AM (2017) Influence of marital status on testosterone levels – A ten year follow-up of 1113 men. Psychoneuroendocrinology, 80, 155–161. Hooper, PL (2021) Human social complexity was significantly lower during climate cooling events of the past 10 millennia. Cliodynamics, 12, 1–12. Hooper, PL, DeDeo, S, Hooper, AEC, Gurven, M, and Kaplan, HS (2013) Dynamical structure of a traditional Amazonian social network. Entropy, 15(11), 4932–4955. Hooper, PL, Demps, K, Gurven, M, Gerkey, D, and Kaplan, HS (2015a) Skills, division of labour and economies of scale among Amazonian hunters and South Indian honey collectors. Philosophical Transactions of the Royal Society B: Biological Sciences, 370(1683), 20150008. Hooper, PL, Gurven, M, Kaplan, HS, and Kaplan, HS (2014) Social and economic underpinnings of human

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

460

Bibliography

biodemography. In M Weinstein and MA Lane, eds., Sociality, Hierarchy, Health: Comparative Biodemography, Washington: National Academies Press, 169–195. Hooper, PL, Gurven, M, Winking, J, and Kaplan, HS (2015b) Inclusive fitness and differential productivity across the life course determine intergenerational transfers in a small-scale human society. Proceedings of the Royal Society B: Biological Sciences, 282 (1803), 20142808. Hooper, PL, Kaplan, HS, and Boone, JL (2010) A theory of leadership in human cooperative groups. Journal of Theoretical Biology, 265(4), 633–646. Hooper, PL, Kaplan, HS, and Jaeggi, A (2021) Gains to cooperation drive the evolution of egalitarianism. Nature Human Behaviour, v, 847–856. Hooper, PL, Smith, EA, Kohler, TA, Wright, HT, and Kaplan, HS (2018) Ecological and social dynamics of territoriality and hierarchy formation. In J Sabloff and P Sabloff, eds., The Emergence of Premodern States: New Perspectives on the Development of Complex Societies, Santa Fe: SFI Press, 105–130. Hopcroft, R (2006) Sex, status, and reproductive success in the contemporary United States. Evolution and Human Behavior, 27(2), 104–120. Hopwood, PE, Moore, AJ, Tregenza, T, and Royle, NJ (2015) Male burying beetles extend, not reduce, parental care duration when reproductive competition is high. Journal of Evolutionary Biology, 28(7), 1394–1402. Horton, R (2015) What is medicine’s 5 sigma? The Lancet, 385, 1380. Hoshi, H, and Kouchi, M (1981) Secular trend of the age at menarche of Japanese girls with special regard to the secular acceleration of the age at peak height velocity. Human Biology, 53, 593–598. Houston, A, Clark, C, McNamara, J, and Mangel, M (1988) Dynamic models in behavioural and evolutionary ecology. Nature, 332(6159), 29–34. Houston, AI, Székely, T, and McNamara, JM (2005) Conflict between parents over care. Trends in Ecology and Evolution, 20, 33–38. Howard, J, and Gibson, M (2018) Is there a link between paternity concern and female genital cutting in West Africa? Evolution and Human Behavior, 40(1), 1–11. Howell, EM, Holla, N, and Waidmann, T (2016) Being the younger child in a large African family: A study of birth order as a risk factor for poor health using the demographic and health surveys for 18 countries. BMC Nutrition, 2(1), 61.

Howell, N (1979) Demography of the Dobe !Kung, New York: Transaction. Howell, N (2010) Life histories of the Dobe !Kung: Food, Fatness, and Well-Being over the Life Span, Berkeley: University of California Press. Hrdy, S, and Judge, DS (1993) Darwin and the puzzle of primogeniture: An essay on biases in parental investment after death. Human Nature, 4(1), 1–45. Hrdy, SB (1976) Care and exploitation of nonhuman primate infants by conspecifics other than the mother. Advances in the Study of Behavior, 6, 101–158. Hrdy, SB (1977) The Langurs of Abu, Cambridge: Harvard University Press. Hrdy, SB (1979) Infanticide among animals: A review, classification, and examination of the implications for the reproductive strategies of females. Ethology and Sociobiology, 1(1), 13–40. Hrdy, SB (1992) Fitness tradeoffs in the history and evolution of delegated mothering with special reference to wet-nursing, abandonment, and infanticide. Ethology and Sociobiology, 13(5–6), 409–442. Hrdy, SB (1997) Raising Darwin’s consciousness. Human Nature, 8(1), 1–49. Hrdy, SB (1999a) Mother Nature: A History of Mothers, Infants, and Natural Selection, New York: Pantheon Books. Hrdy, SB (1999b) The Woman That Never Evolved, Cambridge: Harvard University Press. Hrdy, SB (2000) The optimal number of fathers. Evolution, demography, and history in the shaping of female mate preferences. Annals of the New York Academy of Sciences, 907, 75–96. Hrdy, SB (2001) Mothers and others. Natural History, 110(4), 50–62. Hrdy, SB (2005a) Comes the child before the man: How cooperative breeding and prolonged postweaning dependence shaped human potential. In B Hewlett and M Lamb, eds., Hunter Gatherer Childhoods Evolutionary, Developmental and Cultural Perspectives, New Brunswick: Transaction Publishers, 65–91. Hrdy, SB (2005b) Evolutionary context of human development: The cooperative breeding model. In CS Carter and L Ahnert, eds., Attachment and Bonding: A New Synthesis, Cambridge: MIT Press in cooperation with Dahlem University Press, 9–32. Hrdy, SB (2009) Mothers and Others: The Evolutionary Origins of Mutual Understanding, Cambridge: Harvard University Press.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography Hrdy, SB (2016) Of marmosets, men and the transformative power of babies. In WR Trevathan and KR Rosenberg, eds., Costly and Cute: How Helpless Newborns Made Us Human, Santa Fe: School for Advanced Research, 177–204. Hruschka, DJ, and Hagaman, A (2015) The physiological cost of reproduction for rich and poor across 65 countries. American Journal of Human Biology, 27(5), 654–659. Hruschka, DJ, Munira, S, Jesmin, K, Hackman, J, and Tiokhin, L (2018) Learning from failures of protocol in cross-cultural research. Proceedings of the National Academy of Sciences, 115(45), 11428–11434. Hua, C (2001) A Society without Fathers or Husbands: The Na of China. New York: Zone Books. Hubbard, EB, Shannon, O, and Pisor, A (2022) Non-kin involvement and child outcomes: Older siblings, but not godparents, predict educational attainment in a rural context. OSF preprints. doi:10.31219/osf.io/ 6wap9. Huber, BR, Danaher, WF, and Breedlove, WL (2011) New cross-cultural perspectives on marriage transactions. Cross-Cultural Research, 45(4), 339–375. Huber, J, Inoua, S, Kerschbamer, R, König-Kersting, C, Palan, S, and Smith, VL (2022) Nobel and novice: Author prominence affects peer review. Proceedings of the National Academy of Sciences, 119(41), e2205779119. Huberman, B, Loch, C, and Onculer, A (2004) Status as a valued resource. Social Psychology Quarterly, 67, 103–114. Huffman, MA (1996) Acquisition of innovative cultural behaviors in nonhuman primates: A case study of stone handling, a socially transmitted behavior in Japanese macaques. In CM Heyes and BG Galef Jr, eds., Social Learning in Animals: The Roots of Culture, San Diego: Academic Press, 267–289. Hughes, A (1988) Evolution and Human Kinship, New York: Oxford University Press. Hughes, AL (1982) Confidence of paternity and wifesharing in polygynous and polyandrous systems. Ethology and Sociobiology, 3(3), 125–129 Hughes, SM, and Harrison, MA (2019) Women reveal, men conceal: Current relationship disclosure when seeking an extrapair partner. Evolutionary Behavioral Sciences, 13(3), 272. Hughes, WOH, Oldroyd, BP, Beekman, M, and Ratnieks, FLW (2008) Ancestral monogamy shows kin selection in key to the evolution of eusociality. Science, 320, 1213–1216.

461

Hummert, S, Bohl, K, and Basanta, D (2014) Evolutionary game theory: Cells as players. Molecular BioSystems, 10, 3044–3065. Hunt, EK (2002) The Triumph of Utilitarianism: The Economics of Jevons, Menger, and Walras History of Economic Thought, Armonk: M. E. Sharpe. Hunt, GR, and Gray, RD (2003) Diversification and cumulative evolution in New Caledonian crow tool manufacture. Proceedings of the Royal Society B: Biological Sciences, 270, 867–874. Hurt, LS, Ronsmans, C, and Thomas, SL (2006) The effect of number of births on women’s mortality: Systematic review of the evidence for women who have completed their childbearing. Population Studies, 60(1), 55–71. Hurtado, AM, Hill, K, Hurtado, I, and Kaplan, H (1992) Trade-offs between female food acquisition and child care among Hiwi and Ache foragers. Human Nature, 3(3), 185–216. Hurtado, AM, and Hill, KR (1987) Early dry season subsistence ecology of Cuiva (Hiwi) foragers of Venezuela. Human Ecology, 15(2), 163–187. Hurtado, M, Hawkes, K, Hill, K, and Kaplan, H (1985) Female subsistence strategies among Ache hunter-gatherers of eastern Paraguay. Human Ecology, 13, 1–28. Huston, SJ, and Finke, MS (2003) Diet choice and the role of time preference. Journal of Consumer Affairs, 37(1), 143–160. İnalcık, H (1994) An Economic and Social History of the Ottoman Empire, Vol. I, Cambridge: Cambridge University Press. Irons, W (1979) Cultural and biological success. In NA Chagnon and W Irons, eds., Evolutionary Biology and Human Social Behavior: An Anthropological Perspective, North Scituate: Duxbury Press, 257–272. Irons, W (1983) Human female reproductive strategies. In S Wasser, ed., Social Behavior of Female Vertebrates, New York: Academic Press, 169–213. Irons, W (1998) Adaptively relevant environments versus the environment of evolutionary adaptedness. Evolutionary Anthropology, 6(6), 194–204. Isaac, G (1978) The food-sharing behavior of protohuman hominids. Scientific American, 238(4), 90–109. Isaacs, H (1975) Idols of the Tribe: Group Identity and Political Change, New York, Harper: Row. Isbell, LA (1991) Contest and scramble competition: Patterns of female aggression and ranging behavior among primates. Behavioral Ecology, 2(2), 143–155. Isler, K, and van Schaik, CP (2012) Allomaternal care, life history and brain size evolution in mammals. Journal of Human Evolution, 63(1), 52–63.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

462

Bibliography

Isler, K, and van Schaik, CP (2014) How humans evolved large brains: Comparative evidence. Evolutionary Anthropology, 23(2), 65–75. Ismar, SMH, Raubenheimer, D, Bury, SJ, Millar, CD, and Hauber, ME (2017) Sex-specific foraging during parental care in a size-monomorphic seabird, the Australasian Gannet (Morus serrator). The Wilson Journal of Ornithology, 129(1), 139–147. Itan, Y, Powell, A, Beaumont, MA, Burger, J, and Thomas, MG (2009) The origins of lactase persistence in Europe. PLoS Computational Biology, 5, 1000491. Ivey, PK (1993) Life-history theory perspectives on allocaretaking strategies among Efé foragers of the Ituri Forest, Zaire (PhD dissertation), University of New, Albuquerque. Ivey, PK (2000) Cooperative reproduction in Ituri Forest hunter-gatherers: Who cares for Efé infants? Current Anthropology, 41(5), 856–866. Ivey, PK, Morrelli, GA, and Tronick, EZ (2005) Child caretakers among Efé foragers of the Ituri Forest. In BS Hewlett and ME Lamb, eds., Hunter-Gatherer Childhoods, New Brunswick: Aldine Transaction, 191–213. Jablonka, E, and Lamb, MJ (1998) Epigenetic inheritance in evolution. Journal of Evolutionary Biology, 11, 159–183. Jablonka, E, and Lamb, MJ (2006) The evolution of information in the major transitions. Journal of Theoretical Biology, 239, 236–246. Jablonka, E, and Lamb, MJ (2014) Evolution in Four Dimensions: Genetic, Epigenetic, Behavioral, and Symbolic Variation in the History of Life, Cambridge: MIT Press. Jaeggi, A, Boose, K, White, F, and Gurven, M (2016a) Obstacles and catalysts of cooperation in humans, bonobos, and chimpanzees: Behavioural reaction norms can help explain variation in sex roles, inequality, war and peace. Behaviour, 153, 1015–1051. Jaeggi, A, and Gurven, M (2013) Reciprocity explains food sharing in humans and other primates independent of kin selection and tolerated scrounging: A phylogenetic meta-analysis. Proceedings of the Royal Society B: Biological Sciences, 280(1768), 20131615. Jaeggi, AV, Hooper, PL, Beheim, BA, Kaplan, HS, and Gurven, MD (2016b) Reciprocal exchange patterned by market forces helps explain cooperation in a small-scale society. Current Biology, 26(16), 2180–2187.

Janicke, T, Häderer, I, Lajeunesse, M, and Anthes, N (2016) Darwinian sex roles confirmed across the animal kingdom. Science Advances, 2, 1500983. Jankowiak, W, Sudakov, M, and Wilreker, BC (2005) Co-wife conflict and co-operation. Ethnology, 81–98. www.jstor.org/stable/3773961. Janowiak, W, and Diderich, M (2000) Sibling solidarity in a polygamous community in the USA: Unpacking inclusive fitness. Evolution and Human Behavior, 21(2), 125–139. Janvry, A, Fafchamps, M, and Sadoulet, E (1991) Peasant household behaviour with missing markets: Some paradoxes explained. Economic Journal, 101, 1400–1417. Janvry, A, and Sadoulet, E (2006) Progress in the modeling of rural households’ behavior under market failures. In A Janvry and R Kanbur, eds., Poverty, Inequality and Development, Essays in Honor of Erik Thorbecke, New York: Springer, 155–181. Jarvenpa, R, and Brumbach, HJ, eds. (2006) Circumpolar Lives and Livelihood: A Comparative Ethnoarchaeology of Gender and Subsistence, Lincoln: University of Nebraska Press. Jarvis, JUM (1981) Eusociality in a mammal: Cooperative breeding in naked mole-rate colonies. Science, 212, 571–573. Jasienska, G (2009) Reproduction and lifespan: Tradeoffs, overall energy budgets, intergenerational costs, and costs neglected by research. American Journal of Human Biology, 21, 524–532. Jasienska, G, Bribiescas, RG, Furberg, A-SS, Helle, S, and Mora, A (2017) Human reproduction and health: An evolutionary perspective. The Lancet, 390, 510–520. Jazwa, CS, and Collins-Elliott, SA (2021) An ecological model of settlement expansion in northwestern Morocco. Quaternary International, 597, 103–117. Jazwa, CS, Kennett, DJ, and Winterhalder, B (2013) The ideal free distribution and settlement history at Old Ranch Canyon, Santa Rosa Island, California. In C Jazwa, ed., Small Islands, Big Implications: The California Channel Islands and their Archaeological Contributions, Salt Lake City: University of Utah Press, 75–96. Jazwa, CS, Kennett, DJ, Winterhalder, B, and Joslin, TL (2017) Territoriality and the rise of despotic social organization on western Santa Rosa Island, California. Quaternary International, 518(30), 41–56. Jedwab, R, Christiaensen, L, and Gindelsky, M (2015) Demography, urbanization and development: Rural

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography push, urban pull and. . . urban push? Policy Research Working Paper, 98, 6–16. Jennions, MD, and Petrie, M (2000) Why do females mate multiply? A review of the genetic benefits. Biological Reviews, 75(1), 21–64. Jeon, J (2008) Evolution of parental favoritism among different-aged offspring. Behavioral Ecology, 19(2), 344–352. Jerison, HJ (1973) Evolution of the brain and intelligence. Current Anthropology, 16, 403–426. Jeschke, JM, and Kokko, H (2009) The roles of body size and phylogeny in fast and slow life histories. Evolutionary Ecology, 23(6), 867–878. Ji, T, Wu, J-J, He, Q-Q, Xu, J-J, Mace, R, and Tao, Y (2013a) Reproductive competition between females in the matrilineal Mosuo of southwestern China. Philosophical Transactions of the Royal Society of London B: Biological Sciences 368, 20130081. Ji, T, Xu, J, and Mace, R (2013b) Intergenerational and sibling conflict under patrilocality. Human Nature, 25(1), 66–79. Jochim, MA (1988) Optimal foraging and the division of labor. American Anthropologist, 90(1), 130–136. Johnson, A (1975) Time allocation in a Machiguenga community. Ethnology, 14, 301–310. Johnson, A, and Behrens, C (1989) Time allocation research and aspects of method in cross-cultural comparison. Journal of Quantitative Anthropology, 1(2), 234–245. Johnson, A, and Earle, T (1987) The Evolution of Human Societies: From Foraging Groups to Agrarian State, Stanford: Stanford University Press. Johnson, BR (2010) Division of labor in honeybees: Form, function, and proximate mechanisms. Behavioral Ecology and Sociobiology, 64, 305–316. Johnson, DDP (2005) God’s punishment and public goods: A test of the supernatural punishment hypothesis in 186 world cultures. Human Nature, 16(4), 410–444. Johnson, GA (1982) Organizational structure and scalar stress. In C Renfrew, M Rowland, and BA SegravesWhallon, eds., Theory and Explanation in Archaeology, New York: Academic Press, 389–421. Johnson, J, and Tellis, GJ (2005) Blowing bubbles: Heuristics and biases in the run-up of stock prices. Journal of the Academy of Marketing Science, 33(4), 486–503. Johnstone, RA (2000) Models of reproductive skew: A review and synthesis. Ethology, 106(1), 5–26.

463

Johnstone, RA, Reynolds, JD, and Deutsch, JC (1996) Mutual mate choice and sex differences in choosiness. Evolution, 50(4), 1382–1391. Johow, J, Willführ, KP, and Voland, E (2019) High consanguinity promotes intergenerational wealth concentration in socioeconomically privileged Krummhörn families of the eighteen and nineteen centuries. Evolution and Human Behavior, 40(2), 204–213. Jokela, M, Rotkirch, A, Rickard, IJ, Pettay, J, and Lummaa, V (2010) Serial monogamy increases reproductive success in men but not in women. Behavioral Ecology, 21(5), 906–912. Jones, B, G., N, Marlowe, FW, Hawkes, K, and O’Connell, JF (2000) Paternal investment and hunter-gatherer divorce rates. In L Cronk, N Chagnon, and W Irons, eds., Adaptation and Human Behavior: An Anthropological Perspective, New York: Aldine de Gruyter, 69–90. Jones, BC, Hahn, AC, and DeBruine, LM (2019) Ovulation, sex hormones, and women’s mating psychology. Trends in Cognitive Sciences, 23(1), 51–62. Jones, JH (2009) The force of selection on the human life cycle. Evolution and Human Behavior, 30(5), 305–314. Jones, JH (2010) Demography. In M Muehlenbein, ed., Human Evolutionary Biology, Cambridge: Cambridge University Press, 74–91. Jones, JH, and Bliege Bird, R (2015) The marginal valuation of fertility. Evolution and Human Behavior, 35(1), 65–71. Jones, JH, and Ferguson, B (2006) The marriage squeeze in Colombia, 1973–2005: The role of excess male death. Social Biology, 53(3–4), 140–151. Jones, JH, Ready, E, and Pisor, AC (2021a) Want climate-change adaptation? Evolutionary theory can help. American Journal of Human Biology, 33(4), 23539. Jones, K, and Madsen, D (1989) Calculating the cost of resource transportation: A Great Basin example. Current Anthropology, 30, 529–534. Jones, KP, Walker, LC, Anderson, D, Lacreuse, A, Robson, SL, and Hawkes, K (2007) Depletion of ovarian follicles with age in chimpanzees: Similarities to humans. Biology of Reproduction, 77 (2), 247–251. Jones, TL, Coltrain, JB, Jacobs, DK, . . . Codding, BF (2021b) Causes and consequences of the late Holocene extinction of the marine flightless duck (Chendytes lawi) in the northeastern Pacific. Quaternary Science Reviews, 260, 106914.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

464

Bibliography

Jongmann, W, and Dekker, R (1989) Public intervention in the food supply in preindustrial Europe. In C Halstead and J O’Shea, eds., Bad Year Economics: Cultural Responses to Risk and Uncertainty, Cambridge: Cambridge University Press, 114–122. Jordan, FM (2011) A phylogenetic analysis of the evolution of Austronesian sibling terminologies. Human Biology, 83(2), 297–321. Joshi, N (1987) Evolution of cooperation by reciprocation within structured demes. Journal of Genetics, 66(1), 69–84. Joshi, PD, and Fast, NJ (2013) Power and reduced temporal discounting. Psychological Science, 24(4), 432–438. Jost, J, Sapolsky, R, and Nam, H (2018) Speculations on the evolutionary origins of system justification. Evolutionary Psychology, 16, 1–21. Judge, DS, and Carey, JR (2000) Postreproductive life predicted by primate patterns. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, 55(4), B201–B209. Jünger, J, Motta-Mena, NV, Cardenas, R, . . . Puts, DA (2018) Do women’s preferences for masculine voices shift across the ovulatory cycle? Hormones and Behavior, 106, 122–134. Käär, P, Jokela, J, Merilä, J, Helle, T, and Kojola, I (1998) Sexual conflict and remarriage in preindustrial human populations: Causes and fitness consequences. Evolution and Human Behavior, 19(3), 139–151. Kakkar, H, Sivanathan, N, and Pettit, N (2019) The impact of dynamic status changes within competitive rank-ordered hierarchies. Proceedings of the National Academy of Sciences, 116, 23011–23020. Kanazawa, S, and Still, MC (1999) Why monogamy? Social Forces, 78(1), 25–50. Kandler, A, and Powell, A (2018) Generative inference for cultural evolution. Philosophical Transactions of the Royal Society B: Biological Sciences, 373(1743), 20170056. Kannisto, V (2001) Mode and dispersion of the length of life. Population: An English Selection, 13, 159–171. Kantner, J (2010) Implications of human behavioral ecology for understanding complex human behavior: Resource monopolization, package size, and turquoise. Journal of Anthropological Research, 66, 231–257. Kanwisher, N (2000) Domain specificity in face perception. Nature Neuroscience, 3(8), 759–763. Kaplan, H (1994) Evolutionary and wealth flows theories of fertility: Empirical tests and new models.

Population and Development Review, 20(4), 753–791. Kaplan, H (1996) A theory of fertility and parental investment in traditional and modern societies. Yearbook of Physical Anthropology, 39, 91–135. Kaplan, H, and Gurven, M (2005) The natural history of human food sharing and cooperation: A review and a new multi-individual approach to the negotiation of norms. In H Gintis, S Bowles, R Boyd, and E Fehr, eds., Moral Sentiments and Material Interests: The Foundations of Cooperation in Economic Life, Cambridge: MIT Press, 75–113. Kaplan, H, Gurven, M, Winking, J, Hooper, PL, and Stieglitz, J (2010) Learning, menopause, and the human adaptive complex. Annals of the New York Academy of Sciences, 1204(1), 30–42. Kaplan, H, and Hill, K (1985) Food sharing among Ache foragers: Tests of explanatory hypotheses. Current Anthropology, 26(2), 223–246. Kaplan, H, and Hill, K (1992) The evolutionary ecology of food acquisition. In EA Smith and B Winterhalder, eds., Evolutionary Ecology and Human Behavior, New York: Aldine de Gruyter, 167–201. Kaplan, H, Hill, K, Hawkes, K, and Hurtado, A (1984) Food sharing among Ache hunter-gatherers of Eastern Paraguay. Current Anthropology, 25(1), 113–115. Kaplan, H, Hill, K, Hurtado, AM, and Lancaster, J (2001) The embodied capital theory of human evolution. In PT Ellison, ed., Reproductive Ecology and Human Evolution, London: Routledge, 293–317. Kaplan, H, Hill, K, Lancaster, J, and Hurtado, AM (2000) A theory of human life history evolution: Diet, intelligence, and longevity. Evolutionary Anthropology, 9(4), 156–185. Kaplan, H, and Lancaster, JB (2000) The evolutionary economics and psychology of the demographic transition to low fertility. In L Cronk, N Chagnon, and W Irons, eds., Adaptation and Human Behavior: An Anthropological Perspective, New York: Aldine de Gruyter, 283–322. Kaplan, H, Lancaster, JB, Tucker, WT, and Anderson, KG (2002) Evolutionary approach to below replacement fertility. American Journal of Human Biology, 14, 233–256. Kaplan, HS, and Gurven, M (2008) Top-down and bottom-up research in biodemography. Demographic Research, 19, 1587–1602. Kaplan, HS, Hooper, PL, and Gurven, M (2009) The evolutionary and ecological roots of human social

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography organization. Philosophical Transactions of the Royal Society B: Biological Sciences, 364(1533), 3289–3299. Kaplan, HS, and Lancaster, JB (2003) An evolutionary and ecological analysis of human fertility, mating patterns, and parental investment. In KW Wachter and RA Bulatao, eds., Offspring: Human Fertility Behavior in Biodemographic Perspective, Washington: National Academies Press, 170–223. Kaplan, HS, Lancaster, JB, Bock, JA, and Johnson, SE (1995a) Fertility and fitness among Albuquerque men: A competitive labour market theory. In RIM Dunbar, ed., Human Reproductive Decisions, London: Palgrave, 96–136. Kaplan, HS, Lancaster, JB, Johnson, SE, and Bock, JA (1995b) Does observed fertility maximize fitness among New Mexican men? Human Nature, 6(4), 325–360. Kaplan, HS, and Robson, AJ (2002) The emergence of humans: The coevolution of intelligence and longevity with intergenerational transfers. Proceedings of the National Academy of Sciences, 99(15), 10221–10226. Kaptijn, R, Thomese, F, Tilburg, TG, and Liefbroer, AC (2010) How grandparents matter. Support for the cooperative breeding hypothesis in a contemporary Dutch population. Human Nature, 21(4), 393–405. Karmin, M, Saag, L, and Vicente, M (2015) A recent bottleneck of Y chromosome diversity coincides with a global change in culture. Genome Research, 25, 459–466. Kashyap, R (2021) Has demography witnessed a data revolution? Promises and pitfalls of a changing data ecosystem. Population Studies, 75(Suppl. 1), 47–75. Kasper, C, and Borgerhoff Mulder, M (2015) Who helps and why: Cooperative networks in Mpimbwe. Current Anthropology, 56, 701–732. Kavanagh, PH, Haynie, HJ, Kushnick, G, and Gavin, MC (2021) Drivers of global variation in land ownership. Ecography, 44(1), 67–74. Kawakatsu, M, Chodrow, P, Eikmeier, N, and Larremore, D (2021) Emergence of hierarchy in networked endorsement dynamics. Proceedings of the National Academy of Sciences, 118, e2015188118. Kayberry, PM (1939) Aboriginal Woman: Sacred and Profane, London: Routledge. Keeley, LH (1988) Hunter-gatherer economic complexity and “population pressure”: A cross-cultural analysis. Journal of Anthropological Archaeology, 7(4), 373–411.

465

Keister, LA (2003) Sharing the wealth: The effect of siblings on adults’ ownership of wealth. Demography, 40(3), 521–542. Kelbessa, W (2017) Africa and the philosophy of sexuality. In A Afolayan and T Falola, eds., The Palgrave Handbook of African Philosophy, New York: Palgrave Macmillan, 371–389. Keller, L, and Reeve, HK (1994) Partitioning of reproduction in animal societies. Trends in Ecology and Evolution, 9(3), 98–102. Keller, MC, Nesse, RM, and Hofferth, S (2001) The Trivers–Willard hypothesis of parental investment: No effect in the contemporary United States. Evolution and Human Behavior, 22(5), 343–360. Kelly, RC (1985) The Nuer Conquest: The Structure and Development of an Expansionist System, Ann Arbor: University of Michigan Press. Kelly, RL (1995) The Lifeways of Hunter-Gatherers: The Foraging Spectrum, Cambridge: Cambridge University Press. Keltner, D, Gruenfeld, DH, and Anderson, C (2003) Power, approach, and inhibition. Psychological Review, 110(2), 265. Kennedy, GE (2003) Palaeolithic grandmothers? Life history theory and early Homo. Journal of the Royal Anthropological Institute, 9(3), 549–572. Kennett, D, Voorhies, B, and Martorana, D (2006a) An ecological model for the origins of maize-based food production on the Pacific Coast of southern Mexico. In DJ Kennett and B Winterhalder, eds., Behavioral Ecology and the Origins of Agriculture, Berkeley: University of California Press, 103–136. Kennett, D, and Winterhalder, B (2008) Demographic expansion, despotism, and the colonisation of East and South Polynesia. In G Clark, F Leach, and S O’Connor, eds., Islands of Inquiry: Colonisation, Seafaring and the Archeology of Maritime Landscapes, Canberra: Australian National University Press, 87–96. Kennett, D, Winterhalder, B, Bartruff, J, and Erlandson, J (2009) An ecological model for the emergence of institutionalized social hierarchies on California’s Northern Channel Islands. In S Shennan, ed., Pattern and Process in Cultural Evolution, Berkeley: University of California Press, 297–314. Kennett, DJ (2005) The Island Chumash: Behavioral Ecology of a Maritime Society, Berkeley: University of California Press. Kennett, DJ, Anderson, A, and Winterhalder, B (2006b) The ideal free distribution, food production, and the colonization of Oceania. In DJ Kennett and B

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

466

Bibliography

Winterhalder, eds., Behavioral Ecology and the Transition to Agriculture, Berkeley: University of California Press, 265–288. Kennett, DJ, Breitenbach, S, Aquino, V, . . . Haug, G (2012) Development and disintegration of Maya political systems in response to climate change. Science, 388(6108), 788–791. Kennett, DJ, and Kennett, JP (2006) Early state formation in southern Mesopotamia: Sea levels, shorelines, and climate change. Journal of Island and Coastal Archaeology, 1(1), 67–99. Kennett, DJ, Kennett, JP, Erlandson, JM, and Cannariato, KG (2007) Human responses to Middle Holocene climate change on California’s Channel Islands. Quaternary Science Reviews, 26(3–4), 351–367. Kennett, DJ, and Marwan, N (2015) Climatic volatility, agricultural uncertainty, and the formation, consolidation and breakdown of preindustrial agrarian states. Philosophical Transactions of the Royal Society A Mathematical, Physical and Sciences, 373(2055), 20140458. Kennett, DJ, and Winterhalder, B, eds. (2006) Behavioral Ecology and the Transition to Agriculture, Berkeley: University of California Press. Kenrick, DT, and Keefe, RC (1992) Age preferences in mates reflect sex differences in human reproductive strategies. Behavioral and Brain Sciences, 15(1), 75–91. Kerr, B, and Godfrey-Smith, P (2002) Individualist and multi-level perspectives on selection in structured populations. Biology and Philosophy, 17, 477–517. Ketterson, V, and Nolan, J (1992) Hormones and life histories: An integrative approach. The American Naturalist, 140, 33–62. Khong, TY, Adema, ED, and Erwich, JJHM (2003) On an anatomical basis for the increase in birth weight in second and subsequent born children. Placenta, 24(4), 348–353. Kiernan, K (2004) Unmarried cohabitation and parenthood in Britain and Europe. Law & Policy, 26(1), 33–55. Kim, PS, Coxworth, JE, and Hawkes, K (2012) Increased longevity evolves from grandmothering. Proceedings of the Royal Society B: Biological Sciences, 279, 4880–4884. Kim, PS, McQueen, JS, Coxworth, JE, and Hawkes, K (2014) Grandmothering drives the evolution of longevity in a probabilistic model. Journal of Theoretical Biology, 353, 84–94. Kinder, JM, Jiang, TT, Ertelt, JM, . . . Way, SS (2015) Cross-generational reproductive fitness enforced by microchimeric maternal cells. Cell, 162, 505–515.

King, AJ, Johnson, DDP, and van Vugt, M (2009) The origins and evolution of leadership. Current Biology, 19(19), 911–916. Kirby, KN, Godoy, R, Reyes-García, V, . . . Wilkie, D (2002) Correlates of delay-discount rates: Evidence from Tsimane’ Amerindians of the Bolivian rain forest. Journal of Economic Psychology, 23, 291–316. Kirby, KR, Gray, RD, Greenhill, SJ, . . . Gavin, MC (2016) D-PLACE: A Global Database of Cultural, Linguistic and Environmental Diversity. PLoS ONE, 11(7), 0158s391. Kirch, P (1990) Monumental architecture and power in Polynesian chiefdoms: A comparison of Tonga and Hawaii. World Archaeology, 22, 206–222. Kirch, PV (1984) The Evolution of the Polynesian Chiefdoms, Cambridge: Cambridge University Press. Kirkwood, TB (2002) Evolution of ageing. Mechanisms of Ageing and Development, 123(7), 737–745. Kirkwood, TB, and Rose, MR (1991) Evolution of senescence: Late survival sacrificed for reproduction. Philosophical Transactions of the Royal Society of London B: Biological Sciences, 332(1262), 15–24. Kirkwood, TBL (1990) The disposable soma theory of aging. In DE Harrison, ed., Genetic Effects on Aging II, Caldwell: Telford Press, 9–19. Kleiman, DG, and Malcolm, J (1981) The evolution of male parental investment in mammals. In DJ Gubernick and PH Klopfer, eds., Parental Care in Mammals, New York and London: Plenum, 347–387. Kleven, H, Landais, C, Posch, J, Steinhauer, A, and Zweimüller, J (2019) Child penalties across countries: Evidence and explanations. AEA Papers and Proceedings, 109, 122–126. Kline, MA (2015) How to learn about teaching: An evolutionary framework for the study of teaching behavior in humans and other animals. Behavioral and Brain Sciences, 38, 1–71. Kline, MA, and Boyd, R (2010) Population size predicts technological complexity in Oceania. Proceedings of the Royal Society B: Biological Sciences, 277(1693), 2559–2564. Kline, MA, Boyd, R, and Henrich, J (2013) Teaching and the life history of cultural transmission in Fijian villages. Human Nature, 24, 351–374. Klok, MD, Jakobsdottir, S, and Drent, ML (2007) The role of leptin and ghrelin in the regulation of food intake and body weight in humans: A review. Obesity Review, 8, 21–34. Knowles, SCL, Nakagawa, S, and Sheldon, BC (2009) Elevated reproductive effort increases blood parasitaemia and decreases immune function in birds:

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography A meta-regression approach. Functional Ecology, 23, 405–415. Koditschek, T (2019) An evolutionary approach to complex hierarchical societies. Behavioural Processes, 161, 117–128. Koenig, A (1995) Group size, composition, and reproductive success in wild common marmosets (Callithrix jacchus). American Journal of Primatology, 35, 311–317. Koenig, A, and Rothe, H (1991) Infant carrying in a polygamous group of the common marmoset (Callithrix jacchus). American Journal of Primatology, 25, 185–190. Koenig, A, Scarry, CJ, Wheeler, BC, and Borries, C (2013) Variation in grouping patterns, mating systems and social structure: What socio-ecological models attempt to explain. Philosophical Transactions of the Royal Society B: Biological Sciences, 368(1618), 20120348. Koenig, WD (1989) Sex-biased dispersal in the contemporary United States. Ethology and Sociobiology, 10(4), 263–277. Koenig, WD, and Dickinson, JL, eds. (2004) Ecology and Evolution of Cooperative Breeding in Birds, Cambridge: Cambridge University Press. Koenig, WD, and Dickinson, JL, eds. (2016) Cooperative Breeding in Vertebrates: Studies of Ecology, Evolution, and Behavior, Cambridge: Cambridge University Press. Koenig, WD, and Mumme, RL (1987) Population Ecology of the Cooperatively Breeding Acorn Woodpecker, Princeton: Princeton University Press. Koenig, WD, Pitelka, FA, Carmen, WJ, Mumme, RL, and Stanback, MT (1992) The evolution of delayed dispersal in cooperative breeders. The Quarterly Review of Biology, 67(2), 111–150. Kohler, TA, Cockburn, D, Hooper, PL, Bocinsky, RK, and Kobti, Z (2012) The coevolution of group size and leadership: An agent-based public goods model for prehispanic Pueblo societies. Advances in Complex Systems, 15(1–2), 1150007. Kohler, TA, and Smith, ME (2018) Ten Thousand Years of Inequality: The Archaeology of Wealth Differences, Tucson: University of Arizona Press. Kohler, TA, Smith, ME, Bogaard, A, and Bowles, S (2017) Greater post-neolithic wealth disparities in Eurasia than in North America and Mesoamerica. Nature, 551(7682), 619–622. Kokko, H (2007) Modelling for Field Biologists and Other Interesting People, Cambridge: Cambridge University Press.

467

Kokko, H (2015) Cuckoldry: Human and nonhuman. In The International Encyclopedia of Human Sexuality, Wiley-Blackwell, 1–2. Kokko, H, and Jennions, MD (2008) Parental investment, sexual selection and sex ratios. Journal of Evolutionary Biology, 21(4), 919–948. Kokko, H, and Johnstone, RA (1999) Social queuing in animal societies: A dynamic model of reproductive skew. Proceedings of the Royal Society B: Biological Sciences, 266(1419), 571–578. Kokko, H, Johnstone, RA, and Clutton-Brock, TH (2001) The evolution of cooperative breeding through group augmentation. Proceedings of the Royal Society B: Biological Sciences, 268, 187–196. Kokko, H, Johnstone, RA, and Wright, J (2002) The evolution of parental and alloparental effort in cooperatively breeding groups: When should helpers pay to stay? Behavioral Ecology, 13(3), 291–300. Kolk, M, and Schnettler, S (2016) Socioeconomic status and sex ratios at birth in Sweden: No evidence for a Trivers-Willard effect for a wide range of status indicators. American Journal of Human Biology, 28(1), 67–73. Koneˇcná, M, and Urlacher, S (2017) Male social status and its predictors among Garisakang foragerhorticulturalists of lowland Papua New Guinea. Evolution and Human Behavior, 38, 789–797. Konigsberg, LW, and Frankenberg, SR (1992) Estimation of age structure in anthropological demography. American Journal of Physical Anthropology, 89(2), 235–256. Konner, M (2010) The Evolution of Childhood: Relationships, Emotion, Mind, Cambridge: Harvard University Press. Konner, M (2021) Nine levels of explanation: A proposed expansion of Tinbergen’s four-level framework for understanding the causes of behavior. Human Nature, 32(4), 748–793. Kordsmeyer, T, Hunt, J, Puts, D, Ostner, J, and Penke, L (2018) The relative importance of intra- and intersexual selection on human male sexually dimorphic traits. Evolution and Human Behavior, 39, 424–436. Kosec, K, and Mo, CH (2017) Aspirations and the role of social protection: Evidence from a natural disaster in rural Pakistan. World Development, 97, 49–66. Kosfeld, M, Okada, A, and Riedl, A (2009) Institution formation in public goods games. American Economic Review, 99(4), 1335–1355. Kosteas, VD (2015) Physical activity and time preference. International Journal of Health Economics and Management, 15(4), 361–386.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

468

Bibliography

Koster, JM (2007) Hunting and Subsistence among the Mayangna and Miskito of Nicaragua’s Bosawas Biosphere Reserve (PhD Dissertation), Pennsylvania State University, University Park. Koster, JM (2008) Hunting with dogs in Nicaragua: An optimal foraging approach. Current Anthropology, 49(5), 935–944. Koster, J (2010) Informant rankings via consensus analysis: A reply to Hill and Kintigh. Current Anthropology, 51(2), 257–258. Koster, JM, Hodgen, JJ, Venegas, MD, and Copeland, TJ (2010) Is meat flavor a factor in hunters’ prey choice decisions? Human Nature, 21(3), 219–242. Koster, J (2011) Interhousehold meat sharing among Mayangna and Miskito horticulturalists in Nicaragua. Human Nature, 22(4), 394–415. Koster, J (2018) Family ties: The multilevel effects of households and kinship on the networks of individuals. Royal Society Open Science, 5, 172159. Koster, J, and Aven, B (2018) The effects of individual status and group performance on network ties among teammates in the National Basketball Association. PLoS ONE, 13, 0196013. Koster, J, Bruno, O, and Burns, JL (2016) Wisdom of the Elders? Ethnobiological Knowledge across the Lifespan. Current Anthropology, 57(1), 113–121. Koster, J, and Leckie, G (2014) Food sharing networks in lowland Nicaragua: An application of the social relations model to count data. Social Networks, 38, 100–110. Koster, J, Leckie, G, Miller, A, and Hames, R (2015) Multilevel modeling analysis of dyadic network data with an application to Ye’kwana food sharing. American Journal of Physical Anthropology, 157(3), 507–512. Koster, J, Lukas, D, Nolin, D, . . . Massengill, E (2019) Kinship ties across the lifespan in human communities. Philosophical Transactions of the Royal Society B: Biological Sciences, 374(1780), 20180069. Koster, J, and McElreath, R (2017) Multinomial analysis of behavior: Statistical methods. Behavioral Ecology and Sociobiology, 71, 138. Koster, J, McElreath, R, Hill, K, . . . Ross, C (2020) The life history of human foraging: Cross-cultural and individual variation. Science Advances, 6(26), eaax9070. Kotler, BP, Brown, J, Mukherjee, S, Berger-Tal, O, and Bouskila, A (2010) Moonlight avoidance in gerbils reveals a sophisticated interplay among time allocation, vigilance and state-dependent foraging.

Proceedings of the Royal Society B: Biological Sciences, 277(1687), 1469–1474. Kourtis, AP, Read, JS, and Jamieson, DJ (2014) Pregnancy and infection. New England Journal of Medicine, 370(23), 2211–2218. Kraft, T, Venkataraman, V, Tacey, I, Dominy, N, and Endicott, K (2019) Foraging performance, prosociality, and kin presence do not predict lifetime reproductive success in Batek hunter-gatherers. Human Nature, 30, 71–97. Kraft, TS, Cummings, DK, Venkataraman, V v, . . . Gurven, M (2023) Female cooperative labour networks in hunter–gatherers and horticulturalists. Philosophical Transactions of the Royal Society B: Biological Sciences, 378(1868), 20210431. Kraft, TS, Venkataraman, VV, Endicott, KL, and Endicott, KM (2020) Preserving quantifiable ethnographic records of disappearing human lifeways. Evolutionary Anthropology, 29(3), 117–124. Kramer, K (2011) The evolution of human parental care and recruitment of juvenile help. Trends in Ecology and Evolution, 26(10), 533–540. Kramer, K (2022) Female cooperation: Evolutionary, cross-cultural and ethnographic evidence. Philosophical Transactions of the Royal Society B: Biological Sciences, 378, 20210425. Kramer, KL (2004) Reconsidering the cost of childbearing: The timing of children’s helping behavior across the life cycle of Maya families. In M Alvard, ed., Socioeconomic Aspects of Human Behavioral Ecology, Bingley: Emerald Group Publishing Limited, 335–353. Kramer, KL (2005a) Children’s help and the pace of reproduction: Cooperative breeding in humans. Evolutionary Anthropology, 14(6), 224–237. Kramer, KL (2005b) Maya Children: Helpers at the Farm, Cambridge: Harvard University Press. Kramer, KL (2009) Does it take a family to raise a child? In G Bentley and R Mace, eds., Substitute Parents: Biological and Social Perspectives on Alloparenting in Human Societies, New York: Berghahn Books, 77–99. Kramer, KL (2010) Cooperative breeding and its significance to the demographic success of humans. Annual Review of Anthropology, 39, 414–436. Kramer, KL (2014) Why what juveniles do matters in the evolution of cooperative breeding. Human Nature, 25(1), 49–65. Kramer, KL (2018) The cooperative economy of food and its effect on human life history and physiology. Physiology & Behavior, 193(B), 196–204.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography Kramer, KL (2019) How there got to be so many of us. The evolutionary story of population growth and a life history of cooperation. Journal of Anthropological Research, 75(4), 472–497. Kramer, KL (2021) The human family: Its evolutionary context and diversity. Social Sciences, 10(6), 191. Kramer, KL, and Ellison, PT (2010) Pooled energy budgets: Resituating human energy allocation tradeoffs. Evolutionary Anthropology, 19, 136–147. Kramer, KL, and Greaves, RD (2011a) Juvenile subsistence effort, activity levels and growth patterns: Middle childhood among Pumé foragers. Human Nature, 22, 303–326. Kramer, KL, and Greaves, RD (2011b) Postmarital residence and bilateral kin associations among huntergatherers. Human Nature, 22(1–2), 41–63. Kramer, KL, Greaves, RD, and Ellison, PT (2009) Early reproductive maturity among Pumé foragers. Implications of a pooled energy model to fast life histories. American Journal of Human Biology, 21(4), 430–437. Kramer, KL, and Otárola-Castillo, E (2015) When mothers need others: The impact of hominin life history evolution on cooperative breeding. Journal of Human Evolution, 84, 16–24. Kramer, KL, and Russell, AF (2014) Kin-selected cooperation without lifetime monogamy: Human insights and animal implications. Trends in Ecology and Evolution, 29(11), 600–606. Kramer, KL, and Russell, AF (2015) Was monogamy a key step on the hominin road? Reevaluation of the monogamy hypothesis. Evolutionary Anthropology, 24, 73–83. Kramer, KL, Schacht, R, and Bell, A (2017) Adult sex ratios and partner scarcity among hunter-gatherers: Implications for dispersal patterns and the evolution of human sociality. Philosophical Transactions of the Royal Society B: Biological Sciences, 372, 20160316. Kramer, KL, and Veile, A (2018) Infant allocare in traditional societies. Physiology and Behavior, 193, 117–126. Kramer, KL, Veile, A, and Otárola-Castillo, E (2016) Sibling competition and growth tradeoffs: Biological vs. statistical significance. PLoS ONE, 11(3), e0150126. Kreager, P (2009) Darwin and Lotka: Two concepts of population. Demographic Research, 21(16), 469–502. Krems, J, Claessens, S, Fales, M, and Campenni, M (2021) An agent-based model of the female rivalry hypothesis for concealed ovulation in humans. Nature Human Behaviour, 5, 726–735.

469

Krems, J, Rankin, A, and Northover, S (2019) Women’s strategic defenses against same-sex aggression: Evidence from sartorial behavior. Social Psychological and Personality Science, 11, 770–781. Krems, JA, Neel, R, Neuberg, SL, Puts, DA, and Kenrick, DT (2016) Women selectively guard their (desirable) mates from ovulating women. Journal of Personality and Social Psychology, 110(4), 551. Kristensen, P, and Bjerkedal, T (2007) Explaining the relation between birth order and intelligence. Science, 316(5832), 1717. Kruger, DI (2007) Coffee production effects on child labor and schooling in rural Brazil. Journal of Development Economics, 82(2), 448–463. Krupenye, C, and Hare, B (2018) Bonobos prefer individuals that hinder others over those that help. Current Biology, 28, 280–286. Kuchikura, Y (1988) Efficiency and focus of blowpipe hunting among Semaq Beri hunter-gatherers of Peninsular Malaysia. Human Ecology, 16(3), 271–305. Kuijt, I (2008) Demography and storage systems during the southern Levantine neolithic demographic transition. In J Bocquet-Appel and O Bar-Yosef, eds., The Neolithic Demographic Transition and Its Consequences, Germany: Springer, 287–313. Kummer, H (1968) Social organization of hamadryas baboons. A field study. Basel, New York: Karger. Kushnick, G, Gray, RD, and Jordan, FM (2014) The sequential evolution of land tenure norms. Evolution and Human Behavior, 35, 309–318. Kuzawa, CW (2005) Fetal origins of developmental plasticity: Are fetal cues reliable predictors of future nutritional environments? American Journal of Human Biology, 17, 5–21. Kuzawa, CW, Adair, L, Bechayda, SA, . . . McDade, TW (2020) Evolutionary life history theory as an organising framework for cohort studies: Insights from the Cebu Longitudinal Health and Nutrition Survey. Annals of Human Biology, 47, 94–105. Kuzawa, CW, Chugani, HT, Grossman, LI, . . . Lange, N (2014) Metabolic costs and evolutionary implications of human brain development. Proceedings of the National Academy of Sciences, 111, 13010–13015. Kuzawa, CW, and Sweet, E (2009) Epigenetics and the embodiment of race: Developmental origins of US racial disparities in cardiovascular health. American Journal of Human Biology, 21, 2–15. Kuzawa, CW, and Thayer, ZM (2011) Timescales of human adaptation: The role of epigenetic processes. Epigenomics, 3(2), 221–234.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

470

Bibliography

Kvarnemo, C (2005) Evolution and maintenance of male care: Is increased paternity a neglected benefit of care? Behavioral Ecology, 17(1), 144–148. Lack, D (1947) The significance of clutch-size. Ibis, 89(2), 302–352. Lack, D (1954) The Natural Regulation of Animal Numbers, Oxford: Oxford University Press. Lahdenperä, M, Gillespie, DO, Lummaa, V, and Russell, AF (2012) Severe intergenerational reproductive conflict and the evolution of menopause. Ecology Letters, 15(11), 1283–1290. Lahdenpera, M, Lummaa, V, Helle, S, Tremblay, M, and Russell, AF (2004) Fitness benefits of prolonged postreproductive lifespan in women. Nature, 428, 178–181. Laland, K, and Brown, G (2011) Sense and Nonsense: Evolutionary Perspectives on Human Behaviour, Oxford: Oxford University Press. Laland, KN (2017) Darwin’s Unfinished Symphony: How Culture Made the Human Mind, Princeton: Princeton University Press. Laland, KN, Odling-Smee, J, and Feldman, MW (2000) Niche construction, biological evolution, and cultural change. Behavioral and Brain Sciences, 23(1), 131–146. Laland, KN, Odling-Smee, J, and Myles, S (2010) How culture shaped the human genome: Bringing genetics and the human sciences together. Nature Reviews Genetics, 11, 137–148. Laland, KN, Sterelny, K, Odling-Smee, J, Hoppitt, W, and Uller, T (2011) Cause and effect in biology revisited: Is Mayr’s proximate-ultimate dichotomy still useful? Science, 334(6062), 1512–1516. Laland, KN, Uller, T, Feldman, M, . . . Odling-Smee, J (2014) Does evolutionary anthropology need a rethink? Yes, urgently. Nature, 514, 161–164. Laland, KN, Uller, T, Feldman, MW, . . . Odling-Smee J (2015) The extended evolutionary synthesis: Its structure, assumptions and predictions. Proceedings of the Royal Society B: Biological Sciences, 282(1813), 20151019. Lamba, S (2014) A comparison of the economic literature on microfinance and the evolutionary literature on cooperation. In Applied Evolutionary Anthropology: Darwinian Approaches to Contemporary World Issues, 39–57. Lamphere, L (1989) Historical and regional variability in Navajo women’s roles. Journal of Anthropological Research, 45(4), 431–456.

Lancaster, C (1981) The Goba of the Zambezi: Sex Roles, Economics, and Change, Norman: University of Oklahoma Press. Lancaster, J (1971) Play mothering: The relations between juvenile females and young infants among free-ranging vervet monkeys (Cercopithicus aethiops). Folia Primatologica, 15, 161–182. Lancaster, J, and Lancaster, C (1983) Parental investment: The hominid adaptation. In D Ortner, ed., How Humans Adapt: A Biocultural Odyssey. Washington: Smithsonian Institution Press, 33–56. Lancaster, JB, Kaplan, H, Hill, K, and Hurtado, AM (2000) The evolution of life history, intelligence and diet among chimpanzees and human foragers. In F Tonneau and NS Thompson, eds., Perspectives in Ethology Evolution, Culture and Behavior, New York: Kluwer Academic, 47–72. Lancy, D (2014) “Babies aren’t persons”: A survey of delayed personhood. In H Otto and H Keller, eds., Different Faces of Attachment: Cultural Variations on a Universal Human Need, Cambridge: Cambridge University Press, 66–112. Lancy, DF (2008) The Anthropology of Childhood. Cherubs, Chattel, Changelings, New York: Cambridge University Press. Lancy, DF (2016a) Playing with knives: The socialization of self-initiated learners. Child Development, 87(3), 654–665. Lancy, DF (2016b) Teaching: Natural or cultural? In D Geary and D Berch, eds., Evolutionary Perspectives on Child Development and Education, Switzerland: Springer, 33–65. Lancy, DF (2018) Anthropological Perspectives on Children as Helpers, Workers, Artisans and Laborers, New York: Palgrave Macmillan. Lansing, JS (1991) Priests and Programmers, Princeton: Princeton University Press. Lansing, JS, and de Vet, TA (2012) The functional role of Balinese water temples: A response to critics. Human Ecology, 40(3), 453–467. Lansing, S, Watkins, J, and Hallmark, B (2008) Male dominance rarely skews the frequency distribution of Y chromosome haplotypes in human populations. Proceedings of the National Academy of Sciences, 105, 11645–11650. Larke, A, and Crews, DE (2006) Parental investment, late reproduction, and increased reserve capacity are associated with longevity in humans. Journal of Physiological Anthropology, 25(1), 119–131.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography Larmuseau, MH, Matthijs, K, and Wenseleers, T (2016) Cuckolded fathers rare in human populations. Trends in Ecology and Evolution, 31(5), 327–329. Larson, CM, Haselton, MG, Gildersleeve, KA, and Pillsworth, EG (2013) Changes in women’s feelings about their romantic relationships across the ovulatory cycle. Hormones and Behavior, 63(1), 128–135. Lassek, W, and Gaulin, S (2009) Costs and benefits of fat-free muscle mass in men: Relationship to mating success, dietary requirements, and natural immunity. Evolution and Human Behavior, 30, 322–332. Lassek, W, and Gaulin, S (2019) Evidence supporting nubility and reproductive value as the key to human female physical attractiveness. Evolution and Human Behavior, 40, 408–419. Lattimore, O (1951) Inner Asian Frontiers of China, New York: American Geographic Society. Laudan, L (1978) Progress and its Problems: Towards a Theory of Scientific Growth, Vol. 282, Berkeley: University of California Press. Laustsen, L, and Petersen, M (2017) Perceived conflict and leader dominance: Individual and contextual factors behind preferences for dominant leaders. Political Psychology, 38, 1083–1101. Lawson, D, and Gibson, MA (2018) Polygynous marriage and child health in sub-Saharan Africa: What is the evidence for harm? Demographic Research, 39, 177–208. Lawson, D, James, S, Ngadaya, E, Ngowi, B, Mfinanga, SGM, and Borgerhoff Mulder, M (2015) No evidence that polygynous marriage is a harmful cultural practice in northern Tanzania. Proceedings of the National Academy of Sciences, 112(45), 1–6. Lawson, D, and Uggla, C (2014) Family structure and health in the developing world : What can evolutionary anthropology contribute to population health science? In MA Gibson and DW Lawson, eds., Applied Evolutionary Anthropology: Darwinian Approaches to Contemporary World Issues, New York: Springer, 85–118. Lawson, DW, Alvergne, A, and Gibson, MA (2012) The life-history trade-off between fertility and child survival. Proceedings of the Royal Society B: Biological Sciences, 279(1748), 4755–4764. Lawson, DW, and Borgerhoff Mulder, M (2016) The offspring quantity – quality trade-off and human fertility variation. Philosophical Transactions of the Royal Society B: Biological Sciences, 371(1692), 20150145. Lawson, DW, and Mace, R (2008) Sibling configuration and childhood growth in contemporary British

471

families. International Journal of Epidemiology, 37(6), 1408–1421. Lawson, DW, and Mace, R (2009) Trade-offs in modern parenting: A longitudinal study of sibling competition for parental care. Evolution and Human Behavior, 30(3), 170–183. Lawson, DW, and Mace, R (2010) Siblings and childhood mental health: Evidence for a later-born advantage. Social Science and Medicine, 70, 2061–2069. Lawson, DW, and Mace, R (2011) Parental investment and the optimization of human family size. Philosophical Transactions of the Royal Society B: Biological Sciences, 366(1563), 333–343. Lawson, DW, Makoli, A, and Goodman, A (2013) Sibling configuration predicts individual and descendant socioeconomic success in a modern post-industrial society. PLoS ONE, 8(9), e73698. Lawson, DW, Nuñez-de la Mora, A, Cooper, GD, Prentice, AM, Moore, SE, and Sear, R (2017a) Marital status and sleeping arrangements predict salivary testosterone levels in rural Gambian men. Adaptive Human Behavior and Physiology, 3(3), 221–240. Lawson, DW, Schaffnit, SB, Hassan, A, . . . Borgerhoff Mulder, M (2017b) Father absence but not fosterage predicts food insecurity, relative poverty, and poor child health in northern Tanzania. American Journal of Human Biology, 29(3), e22938. Lawson, DW, Schaffnit, SB, Hassan, A, and Urassa, M (2021) Shared interests or sexual conflict? Spousal age gap, women’s wellbeing and fertility in rural Tanzania. Evolution and Human Behavior, 42(2), 165–175. Layton, R (1986) Political and territorial structures among hunter-gatherers. Man, 21(1), 18. Layton, R, and O’Hara, S (2010) Human social evolution: A comparison of hunter-gatherer and chimpanzee social organization. Proceedings of the British Academy, 158, 83–113. Lazarus, J, and Inglis, IR (1986) Shared and unshared parental investment, parent-offspring conflict and brood size. Animal Behaviour, 34(6), 1791–1804. Leach, ER (1955) Polyandry, inheritance and the definition of marriage: With particular reference to Sinhalese customary law. Man, 55(199), 182–186. Leacock, E (1978) Women’s status in egalitarian society: Implications for social evolution. Current Anthropology, 19(2), 247–275. Leacock, E (1981) History, development, and the division of labor by sex: Implications for organization. Signs, 7(2), 474–491.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

472

Bibliography

Lee, AJ, DeBruine, LM, and Jones, BC (2018) Individualspecific mortality is associated with how individuals evaluate future discounting decisions. Proceedings of the Royal Society B: Biological Sciences, 285(1880), 20180304. Lee, AJ and Zietsch, BP (2011) Experimental evidence that women’s mate preferences are directly influenced by cues of pathogen prevalence and resource scarcity. Biology Letters, 7, 892–895. Lee, R (1968) What hunters do for a living, or, how to make out on scarce resources. In R Lee and I DeVore, eds., Man the Hunter, Chicago: Aldine, 30–48. Lee, R (1969) Eating Christmas in the Kalahari. Natural History, 12, 60–64. Lee, R (1979) The !Kung San: Men, Women and Work in a Foraging Society, Cambridge: Cambridge University Press. Lee, R (2003a) The demographic transition: Three centuries of fundamental change. The Journal of Economic Perspectives, 17(4), 167–190. Lee, RB (1984) The Dobe !Kung, New York: Holt, Rinehart & Winston. Lee, RB, and deVore, I, eds. (1968) Man the Hunter, Chicago: Aldine Publishing Co. Lee, RD (2003b) Rethinking the evolutionary theory of aging: Transfers, not births, shape senescence in social species. Proceedings of the National Academy of Sciences, 100(16), 9637–9642. Lee, RD, Kaplan, H, and Kramer, KL (2002) Children and the elderly in the economic life cycle of the household: A comparative study of three groups of horticulturalists and hunter-gatherers. Annual Meeting of the Population Association of America. Lee, RD, and Kramer, KL (2002) Children’s economic roles in the Maya family life cycle: Cain, Caldwell and Chayanov revisited. Population and Development Review, 28(3), 475–499. Legare, C (2017) Cumulative cultural learning: Development and diversity. Proceedings of the National Academy of Sciences of the United States of America, 114(30), 7877–7883. Legare, CH, and Nielsen, M (2015) Imitation and innovation: The dual engines of cultural learning. Trends in Cognitive Sciences, 19, 688–699. Lehmann, L, and Keller, L (2006) The evolution of cooperation and altruism – A general framework and a classification of models. Journal of Evolutionary Biology, 19(5), 1365–1376. Lehmann, L, Keller, L, West, S, and Roze, D (2007) Group selection and kin selection: Two concepts but one

process. Proceedings of the National Academy of Sciences, 104(16), 6736–6739. Lekson, SH (2008) A History of the Ancient Southwest, Santa Fe: SAR Press. Lenart, P, Kuruczova, D, Joshi, PK, and BienertováVašků, J (2019) Male mortality rates mirror mortality rates of older females. Scientific Reports, 9(1), 10589. Lenkov, K, Lee, MH, Lenkov, OD, Swafford, A, and Fernald, RD (2015) Epigenetic DNA methylation linked to social dominance. PLoS ONE, 10, 1–11. Leonard, WR, and Godoy, R (2008) Tsimane’ Amazonian Panel Study (TAPS): The first 5 years (2002–2006) of socioeconomic, demographic, and anthropometric data available to the public. Economics and Human Biology, 6, 299–301. Leonard, WR, Reyes-García, V, Tanner, S, . . . Godoy, R (2015) The Tsimane’ Amazonian Panel Study (TAPS): Nine years (2002–2010) of annual data available to the public. Economics and Human Biology, 19, 51–61. Leonetti, DL, and Chabot-Hanowell, B (2011) The foundation of kinship. Human Nature, 22(1–2), 16–40. Leonetti, DL, Nath, DC, and Hemam, NS (2007) In-law conflict: Women’s reproductive lives and the roles of their mothers and husbands among the matrilineal Khasi. Current Anthropology, 48(6), 861–890. Leonetti, DL, Nath, DC, Hemam, NS, and Neill, DB (2004) Do women really need marital partners for support of their reproductive success? The case of the matrilineal Khasi of N.E. India. In M Alvard, ed., Socioeconomic Aspects of Human Behavioral Ecology, Netherlands: Emerald Group Publishing, 151–174. Leonetti, DL, Nath, DC, Heman, NS, and Neill, DB (2005) Kinship organization and the impact of grandmothers on reproductive success among the matrilineal Khasi and patrilineal Bengali of Northeast India. In E Voland, A Chasiotis, and W Schiefenhövel, eds., Grandmotherhood: The Evolutionary Significance of the Second Half of Life, New Brunswick: Rutgers University Press, 194–214. Leslie, PW, and Little, MA, eds. (1999) Turkana Herders of the Dry Savanna: Ecology and Biobehavioral Response of Nomads to an Uncertain Environment, Oxford: Oxford University Press. Lessells, CM (2012) Sexual conflict. In M Kölliker, ed., The Evolution of Parental Care, Oxford: Oxford University Press, 150–170. Lessells, CM, and McNamara, JM (2012) Sexual conflict over parental investment in repeated bouts:

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography Negotiation reduces overall care. Proceedings of the Royal Society B: Biological Sciences, 279(1733), 1506–1514. Levine, A, Stanish, C, Williams, PR, Chávez, C, and Golitko, M (2013) Trade and early state formation in the northern Titicaca Basin, Peru. Latin American Antiquity, 24(3), 289–308. Levine, NE (1980) Nyinba polyandry and the allocation of paternity. Journal of Comparative Family Studies, 11(3), 283–298. Levine, NE, and Silk, JB (1997) Why polyandry fails: Sources of instability in polyandrous marriages. Current Anthropology, 38(3), 375–398. Lévi-Strauss, C (1949/1969) The Elementary Structures of Kinship, Boston: Beacon Press. Levitis, DA, Burger, O, and Lackey, LB (2013) The human post-fertile lifespan in comparative evolutionary context. Evolutionary Anthropology, 22, 66–79. Lewis, DMG (2011) The sibling uncertainty hypothesis: Facial resemblance as a sibling recognition cue. Personality and Individual Differences, 51(8), 969–974. Lewis, HM, Vinicius, L, Strods, J, Mace, R, and Migliano, AB (2014) High mobility explains demand sharing and enforced cooperation in egalitarian huntergatherers. Nature Communications, 5, 5789. Lewis, J (2014) Egalitarian social organization: The case of the Mbendjele BaYaka. In BS Hewlett, ed., HunterGatherers of the Congo Basin, New Brunswick: Transaction Publishers, 219–244. Lewis, R (2002) Beyond dominance: The importance of leverage. The Quarterly Review of Biology, 77, 149–164. Lewis, R (2018) Female power in primates and the phenomenon of female dominance. Annual Review of Anthropology, 47, 533–551. Lewis, SE, and Pusey, AE (1997) Factors influencing the occurrence of communal care in plural breeding mammals. In NG Solomon and JA French, eds., Cooperative Breeding in Mammals, Cambridge: Cambridge University Press, 335–363. Lew-Levy, S (2018) How do hunter-gatherer children learn social and gender norms? A meta-ethnographic review. Cross-Cultural Research, 52(2), 213–255. Lew-Levy, S, Reckin, R, Kissler, SM, . . . Koster, J (2022) Socioecology shapes child and adolescent time allocation in twelve hunter-gatherer and mixedsubsistence forager societies. Scientific Reports, 12(1), 8054. Lew-Levy, S, Reckin, R, Lavi, N, Cristóbal-Azkarate, J, and Ellis-Davies, K (2017) How do hunter-gatherer

473

children learn subsistence skills? Human Nature, 28(4), 367–394. Lewontin, RC (1970a) Race and intelligence. Bulletin of the Atomic Scientists, 26(3), 2–8. Lewontin, RC (1970b) The units of selection. Annual Review of Ecology and Systematics, 1, 1–18. Lewontin, RC (2001) The Triple Helix: Gene, Organism, and Environment, Cambridge: Harvard University Press. Lexis, W (1878) Sur la durée normale de la vie humaineet sur la théorie de la stabilité des rapports statistiques. Annales de démographie internationale, 2, 447–460. Li, S, Zeliger, O, and Strahs, L (2022) Frontal neurons driving competitive behaviour and ecology of social groups. Nature, 603, 661–666. Liebenberg, L (2006) Persistence hunting by modern hunter-gatherers. Current Anthropology, 47(6), 1017–1026. Lieberman, D, and Symons, D (1998) Sibling incest avoidance: From Westermarck to Wolf. The Quarterly Review of Biology, 73(4), 463–466. Lieberman, D, Tooby, J, and Cosmides, L (2007) The architecture of human kin detection. Nature, 445(7129), 727–731. Lieberman, E, Hauert, C, and Nowak, M (2005) Evolutionary dynamics on graphs. Nature, 433, 312–316. Liebert, MA, Snodgrass, JJ, Madimenos, FC, Cepon, TJ, Blackwell, AD, and Sugiyama, LS (2013) Implications of market integration for cardiovascular and metabolic health among an indigenous Amazonian Ecuadorian population. Annals of Human Biology, 40, 228–242. Liesen, LT (2013) The tangled web she weaves: Female– female aggression and status-seeking. In M Fisher, J Garcia, and R Sokol Chang, eds., Evolution’s Empress: Darwinian Perspectives on the Nature of Women, New York: Oxford University Press, 43–62. Lin, N (1999) Social networks and status attainment. Annual Review of Sociology, 25, 467–487. Linares-Matás, GJ, and Clark, J (2021) Seasonality and Oldowan behavioral variability in East Africa. Journal of Human Evolution, 164, 103070. Lindqvist, S (1996) Exterminate All the Brutes, New York: The New Press. Lippold, S, Xu, H, and Ko, A (2014) Human paternal and maternal demographic histories: Insights from highresolution Y chromosome and mtDNA sequences. Investigative Genetics, 5, 13.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

474

Bibliography

Liu, L, Feng, T, Suo, T, Lee, K, and Li, H (2012) Adapting to the destitute situations: Poverty cues lead to shortterm choice. PLoS ONE, 7(4), e33950. Livi Bacci, M (2008) Conquest: The Destruction of the American Indios, Cambridge: Polity Press. Livi Bacci, M (2010) El Dorado in the Marshes: Gold, Slaves and Souls between the Andes and the Amazon, Cambridge: Polity Press. Logan, CJ (2017) We can shift academic culture through publishing choices. F1000Research, 9, 6. Longino, HE (1990) Science as Social Knowledge, Princeton: Princeton University Press. Loos, RJ, Derom, C, Eeckels, R, Derom, R, and Vlietinck, R (2001) Length of gestation and birthweight in dizygotic twins. The Lancet, 358(9281), 560–561. Lorenz, K (1974) On Aggression, New York: Harvest. Lotem, A, Fishman, MA, and Stone, L (2003) From reciprocity to unconditional altruism through signalling benefits. Proceedings of the Royal Society B: Biological Sciences, 270(1511), 199–205. Loucks, AB, and Heath, EM (1994) Dietary restriction reduces luteinizing hormone (LH) pulse frequency during waking hours and increases LH pulse amplitude during sleep in young menstruating women. Journal of Clinical Endocrinology and Metabolism, 78, 910–915. Lovejoy, CO (1981) The origin of man. Science, 211, 341–350. Low, B (1992) Sex, coalitions, and politics in preindustrial societies. Politics and the Life Sciences, 11, 63–80. Low, B (2005) Women’s lives there, here, then, now: A review of women’s ecological and demographic constraints cross-culturally. Evolution and Human Behavior, 26, 64–87. Low, BS (1990) Occupational status, landownership, and reproductive behaviour in nineteen century Sweden: Tuna Parish. American Anthropologist, 92, 457–468. Low, BS (1991) Reproductive life in nineteenth century Sweden: An evolutionary perspective on demographic phenomena. Ethology and Sociobiology, 12, 411–448. Low, BS (1993) Ecological demography: A synthetic focus in evolutionary anthropology. Evolutionary Anthropology, 1(5), 177–187. Low, BS (n.d.) A biologist’s perspective on human evolutionary demography. In O Burger, R Lee, and R Sear, eds., Human Evolutionary Demography. https://osf.io/p59eu/. Low, BS, and Clarke, AL (1991) Family patterns in nineteenth-century Sweden: Impact of occupational

status and landownership. Journal of Family History, 16(2), 117–138. Low, BS, Hazel, A, Parker, N, and Welch, KB (2008) Influences on women’s reproductive lives: Unexpected ecological underpinnings. CrossCultural Research, 42(3), 201–219. Lowes, S (2021) Kinship structure, stress, and the gender gap in competition. Journal of Economic Behavior and Organization, 192, 36–57. Lu, F (2007) Integration into the market among indigenous peoples: A cross-cultural perspective from the Ecuadorian Amazon. Current Anthropology, 48(4), 593–602. Lucas, JR (1983) The role of foraging time constraints and variable prey encounter in optimal diet choice. The American Naturalist, 122(2), 191–209. Lukas, D, and Clutton-Brock, T (2012) Cooperative breeding and monogamy in mammalian societies. Proceedings of the Royal Society B — Biological Sciences, 279, 2151–2156. Lukas, D, and Clutton-Brock, TH (2013) The evolution of social monogamy in mammals. Science, 341, 526–530. Lukas, D, Towner, M, and Borgerhoff Mulder, M (2021) The potential to infer the historical pattern of cultural macroevolution. Philosophical Transactions of the Royal Society B: Biological Sciences, 376(1828), 20200057. Lukaszewski, A, Simmons, Z, Anderson, C, and Roney, J (2016) The role of physical formidability in human social status allocation. Journal of Personality and Social Psychology, 110, 385–406. Luo, L, Ding, R, Gao, X, Sun, J, and Zhao, W (2017) Socioeconomic status influences sex ratios in a Chinese rural population. PeerJ, 5, 3546. Lupo, KD (2007) Evolutionary foraging models in zooarchaeological analysis: Recent applications and future challenges. Journal of Archaeological Research, 15(2), 143–189. Lupo, KD, and Schmitt, DN (2002) Upper Paleolithic nethunting, small prey exploitation, and women’s work effort: A view from the ethnographic and ethnoarchaeological record of the Congo Basin. Journal of Archaeological Method and Theory, 9(2), 147–179. Lupo, KD, and Schmitt, DN (2016) When bigger is not better: The economics of hunting megafauna and its implications for Plio-Pleistocene hunter-gatherers. Journal of Anthropological Archaeology, 44, 185–197. Ly, G, Laurent, R, Lafosse, S, Monidarin, C, Diffloth, G, Bourdier, F, ... Chaix, R (2019) From matrimonial

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography practices to genetic diversity in Southeast Asian populations: The signature of the matrilineal puzzle. Philosophical Transactions of the Royal Society B, 374(1780), 20180434. Lycett, JE, and Dunbar, RIM (1999) Abortion rates reflect the optimization of parental investment strategies. Proceedings of the Royal Society B: Biological Sciences, 266, 2355–2358. Lyle, H, and Smith, E (2014) The reputational and social network benefits of prosociality in an Andean community. Proceedings of the National Academy of Sciences, 111, 4820–4825. Lynch, JW, Kaplan, GA, and Salonen, JT (1997) Why do poor people behave poorly? Variation in adult health behaviours and psychosocial characteristics by stages of the socioeconomic lifecourse. Social Science and Medicine, 44(6), 809–819. Lynn, FB, Podolny, JM, and Tao, L (2009) A sociological (de)construction of the relationship between status and quality. American Journal of Sociology, 115(3), 755–804. Lyons, DE, Young, AG, and Keil, FC (2007) The hidden structure of overimitation. Proceedings of the National Academy of Sciences, 104(50), 19751–19756. MacArthur, RH, and Pianka, ER (1966) On optimal use of a patchy environment. The American Naturalist, 100(916), 603–609. MacDonald, K (1995) The establishment and maintenance of socially imposed monogamy in Western Europe. Politics and the Life Sciences, 14, 3–23. Mace, R (1996) Biased parental investment and reproductive success in Gabbra pastoralists. Behavioral Ecology and Sociobiology, 38(2), 75–81. Mace, R (1998) The coevolution of human fertility and wealth inheritance strategies. Philosophical Transactions of the Royal Society of London B: Biological Sciences, 353(1367), 389–397. Mace, R (2007) The evolutionary ecology of human family size. In L Barrett and R Dunbar, eds., Oxford Handbook of Evolutionary Psychology, Oxford: Oxford University Press, 383–398. Mace, R (2008) Reproducing in cities. Science, 319(5864), 764–766. Mace, R (2015) The evolutionary ecology of the family. In DM Buss, ed., The Handbook of Evolutionary Psychology, Hoboken: John Wiley & Sons, 561–577. Mace, R, and Alvergne, A (2012) Female reproductive competition within families in rural Gambia. Proceedings of the Royal Society B: Biological Sciences, 279, 2219–2227.

475

Mace, R, and Houston, A (1989) Pastoralist strategies for survival in unpredictable environments: A model of herd composition that maximizes household viability. Agricultural Systems, 31, 185–204. Mace, R, and Pagel, M (1994) The comparative method in anthropology. Current Anthropology, 35(5), 549–564. Mace, R, and Sear, R (1997) The birth interval and the sex of children in a traditional African population: An evolutionary analysis. Journal of Biosocial Science, 29(4), 499–507. Mace, R, and Sear, R (2005) Are humans communal breeders? In E Voland, A Chasiotis, and W Schiefenhövel, eds., Grandmotherhood: The Evolutionary Significance of the Second Half of Female Life, New Brunswick: Rutgers University Press, 143–159. Macfarlan, S, and Lyle, H (2015) Multiple reputation domains and cooperative behaviour in two Latin American communities. Philosophical Transactions of the Royal Society B: Biological Sciences, 370, 20150009. Macfarlan, S, Walker, R, Flinn, M, and Chagnon, N (2014) Lethal coalitionary aggression and long-term alliance formation among Yanomamö men. Proceedings of the National Academy of Sciences, 111, 16662–16669. Macfarlan, SJ, Quinlan, R, and Remiker, M (2013) Cooperative behaviour and prosocial reputation dynamics in a Dominican village. Proceedings of the Royal Society B: Biological Sciences, 280(1761), 20130557. Macfarlan, SJ, Remiker, M, and Quinlan, R (2012) Competitive altruism explains labor exchange variation in a Dominican community. Current Anthropology, 53(1), 118–124. Macfarlan, SJ, Schacht, R, Foley, C, . . . Schniter, E (2020a) Marriage dynamics in old lower California: Ecological constraints and reproductive value in an arid peninsular frontier. Biodemography and Social Biology, 65(2), 156–171. Macfarlan, SJ, Schacht, R, Schniter, E, Garcia, JJ, Beltran, DG, and Lerback, J (2020b) The role of dispersal and school attendance on reproductive dynamics in small, dispersed populations: Choyeros of Baja California Sur, Mexico. PLoS ONE, 15(10), 0239523. Madimenos, FC, Snodgrass, JJ, Blackwell, AD, Liebert, MA, and Sugiyama, LS (2011) Physical activity in an indigenous Ecuadorian forager-horticulturalist

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

476

Bibliography

population as measured using accelerometry. American Journal of Human Biology, 23, 488–497. Maes, M (2011) Depression is an inflammatory disease, but cell-mediated immune activation is the key component of depression. Prog Neuropsychopharmacol Biol Psychiatry, 35, 664–675. Maezumi, SY, Whitney, BS, Mayle, FE, Souza, J, and Iriarte, J (2018) Reassessing climate and preColumbian drivers of paleofire activity in the Bolivian Amazon. Quaternary International, 488 (20), 81–94. Magdanz, J, Utermohle, C, and Wolfe, R (2002) The Production and Distribution of Wild Food in Wales and Deering, Alaska (Technical Paper 259, Juneau: Division of Subsistence, Alaska Department of Fish and Game. Magid, K, Chatterton, RT, Ahamed, FU, and Bentley, GR (2018) Childhood ecology influences salivary testosterone, pubertal age and stature of Bangladeshi UK migrant men. Nature Ecology and Evolution, 2, 1146–1154. Magrath, MJ, and Komdeur, J (2003) Is male care compromised by additional mating opportunity? Trends in Ecology and Evolution, 18(8), 424–430. Magrath, RD, Johnstone, RA, and Heinsohn, RG (2004) Reproductive skew. In WD Koenig and JL Dickinson, eds., Ecology and Evolution of Cooperative Breeding in Birds. Cambridge University Press, 151–176. Majolo, B, Lehmann, J, Bortoli Vizioli, A, and Schino, G (2012) Fitness-related benefits of dominance in primates. American Journal of Physical Anthropology, 147, 652–660. Makowsky, M, and Smaldino, P (2016) The evolution of power and the divergence of cooperative norms. Journal of Economic Behavior & Organization, 126, 75–88. Malinowski, B (1927) Sex and Repression in Savage Society, London: Kegan Paul, Trench, Trubner & Co. Malthus, TR (1798) An Essay on the Principle of Population, London: J. Johnson. Maner, J, and Mead, N (2010) The essential tension between leadership and power: When leaders sacrifice group goals for the sake of self-interest. Journal of Personality and Social Psychology, 99, 482–497. Mangola, SM, Lund, JR, Schnorr, SL, and Crittenden, AN (2022) Ethical microbiome research with Indigenous communities. Nature Microbiology, 7(6), 749–756. Manson, JH (1994) Female mate choice in primates. Evolutionary Anthropology, 3(6), 192–195. Manz, BF (1989) The Rise and Rule of Tamerlane, Cambridge: Cambridge University Press.

Marcinkowska, UM, Ellison, PT, Galbarczyk, A, . . . Jasienska, G (2016) Lack of support for relation between woman’s masculinity preference, estradiol level and mating context. Hormones and Behavior, 78, 1–7. Marcus, J (1998) The peaks and valleys of ancient states: An extension of the dynamic model. In GM Feinman and J Marcus, eds., Archaic States, Santa Fe: SAR Press, 59–94. Marean, CW, Anderson, RJ, Bar-Matthews, M, . . . Hill, K (2015) A new research strategy for integrating studies of paleoclimate, paleoenvironment, and paleoanthropology. Evolutionary Anthropology, 24(2), 62–72. Margulis, SW, Altmann, J, and Ober, C (1993) Sexbiased lactational duration in a human population and its reproductive costs. Behavioral Ecology and Sociobiology, 32(1), 41–45. Mari Bhat, PN, and Halli, SS (1999) Demography of brideprice and dowry: Causes and consequences of the Indian marriage squeeze. Population Studies, 53(2), 129–148. Maring, R, and Riede, F (2019) Possible wild boar management during the Ertebølle Period: A carbon and nitrogen isotope analysis of Mesolithic wild boar from Fannerup F, Denmark. Environmental Archaeology, 24(1), 15–27. Markowitz, H (1952) Portfolio selection. Journal of Finance, 7, 77–91. Marlowe, F (2000a) The patriarch hypothesis: An alternative explanation of menopause. Human Nature, 11(1), 27–42. Marlowe, F (2010) The Hadza: Hunter-Gatherers of Tanzania, Berkeley: University of California Press. Marlowe, F, and Berbesque, C (2012) The human operational sex ratio: Effects of marriage, concealed ovulation, and menopause on mate competition. Journal of Human Evolution, 63, 834–842. Marlowe, FW (1999) Male care and mating effort among Hadza Foragers. Behavioral Ecology and Sociobiology, 46, 57–64. Marlowe, FW (2000b) Paternal investment and the human mating system. Behavioural Processes, 51, 45–61. Marlowe, FW (2003a) A critical period for provisioning by Hadza men: Implications for pair bonding. Evolution and Human Behavior, 24(3), 217–229. Marlowe, FW (2003b) The mating system of foragers in the standard cross-cultural sample. Cross-Cultural Research, 37(3), 282–306.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography Marlowe, FW (2004a) Marital residence among foragers. Current Anthropology, 45(2), 277–288. Marlowe, FW (2004b) Mate preferences among Hadza hunter-gatherers. Human Nature, 15(4), 365–376. Marlowe, FW (2005) Who tends Hadza children? In B Hewlett and M Lamb, eds., Hunter-Gatherer Childhoods., New Brunswick: Aldine Transaction, 177–190. Marlowe, FW (2007) Hunting and gathering: The human sexual division of foraging labor. Cross-Cultural Research, 41(2), 170–195. Marlowe, FW (2009) Hadza cooperation: Second-party punishment, yes; third-party punishment, no. Human Nature, 20(4), 417–430. Marlowe, FW, Berbesque, JC, Barrett, C, Bolyanatz, A, Gurven, M, and Tracer, D (2010) The ‘spiteful’ origins of human cooperation. Proceedings of the Royal Society B: Biological Sciences, 278(1715), 2159–2164. Marlowe, FW, Berbesque, JC, Wood, B, Crittenden, A, Porter, C, and Mabulla, A (2014) Honey, Hadza, hunter-gatherers, and human evolution. Journal of Human Evolution, 71, 119–128. Marmot, M (2004) The Status Syndrome: How Social Standing Affects Our Health and Longevity, London: Times Books. Marquardt, WH (1988) Politics and production among the Calusa of south Florida. In T Ingold, D Riches, and J Woodburn, eds., Hunters and Gatherers: History, Evolution and Social Change, Oxford: Berg, 161–188. Maršál, K, Persson, P-H, Larsen, T, Lilja, H, Selbing, A, and Sultan, B (1996) Intrauterine growth curves based on ultrasonically estimated foetal weights. Acta Paediatrica, 85(7), 843–848. Marsh, A, Yu, H, Schechter, J, and Blair, R (2009) Larger than life: Humans’ nonverbal status cues alter perceived size. PLoS ONE, 4, 5707. Marshall, J (2011) Group selection and kin selection: Formally equivalent approaches. Trends in Ecology and Evolution, 26(7), 325–332. Martin, J (2009) Formation and stabilization of vertical hierarchies among adolescents: Towards a quantitative ethology of dominance among humans. Social Psychology Quarterly, 72, 241–264. Martin, J, Staes, N, Weiss, A, Stevens, J, and Jaeggi, A (2019a) Facial width-to-height ratio is associated with agonistic and affiliative dominance in bonobos. Biology Letters, 15, 20190232. Martin, JS, Massen, JJM, Šlipogor, V, Bugnyar, T, Jaeggi, AV, and Koski, SE (2019b) The EGA + GNM

477

framework: An integrative approach to modelling behavioural syndromes. Methods in Ecology and Evolution, 10(2), 245–257. Martin, JS, Ringen, EJ, Duda, P, and Jaeggi, AV (2020) Harsh environments promote alloparental care across human societies. Proceedings of the Royal Society B: Biological Sciences, 287(1933), 20200758. Martin, RD, and May, RM (1981) Outward signs of breeding. Nature, 293, 7–9. Martin, TC (1995) Women’s education and fertility: Results from 26 demographic and health surveys. Studies in Family Planning, 26(4), 187–202. Mascaro, JS, Hackett, PD, and Rilling, JK (2013) Testicular volume is inversely correlated with nurturing-related brain activity in human fathers. Proceedings of the National Academy of Sciences, 110, 15746–15751. Massey, DS, Arango, J, Hugo, G, Kouaouci, A, Pellegrino, A, and Taylor, JE (1994) An evaluation of international migration theory: The North American case. Population and Development Review, 20(4), 699–751. Mathew, S (2017) How the second-order free rider problem is solved in a small-scale society. American Economic Review, 107, 578–581. Mathew, S, and Boyd, R (2011) Punishment sustains large-scale cooperation in prestate warfare. Proceedings of the National Academy of Sciences, 108(28), 11375–11380. Mathew, S, and Boyd, R (2014) The cost of cowardice: Punitive sentiments towards free riders in Turkana raids. Evolution and Human Behavior, 35(1), 58–64. Mathot, KJ, and Frankenhuis, W (2018) Models of paceof-life syndromes (POLS): A systematic review. Behavioral Ecology and Sociobiology, 72, 41. Matsumura, S, and Kobayashi, T (1998) A game model for dominance relations among group-living animals. Behavioral Ecology and Sociobiology, 42, 77–84. Matthews, LJ, and Butler, PM (2011) Novelty-seeking DRD4 polymorphisms are associated with human migration distance out-of-Africa after controlling for neutral population gene structure. American Journal of Physical Anthropology, 145(3), 382–389. Mattison, S (2017) Male-provisioning hypothesis. In V Weekes-Shackelford, TK Shackleford, and VA Weekes-Shackelford, eds. Encyclopedia of Evolutionary Psychological Science. Germany: Springer, 1–6.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

478

Bibliography

Mattison, S, MacLaren, N, and Liu, R (2021) Gender differences in social networks based on prevailing kinship norms in the Mosuo of China. Social Sciences, 10, 253. Mattison, S, Moya, C, Reynolds, A, and Towner, MC (2018) Evolutionary demography of age at last birth: Integrating approaches from human behavioural ecology and cultural evolution. Philosophical Transactions of the Royal Society B: Biological Sciences, 373(1743), 20170060. Mattison, S, Quinlan, R, and Hare, D (2019) The expendable male hypothesis. Philosophical Transactions of the Royal Society B: Biological Sciences, 374, 20180080. Mattison, SM (2010a) Demystifying the Mosuo: The behavioral ecology of kinship and reproduction in China’s “last matriarchal” society (PhD Dissertation), University of Washington, Seattle. Mattison, SM (2010b) Economic impacts of tourism and erosion of the visiting system among the Mosuo of Lugu Lake. The Asia Pacific Journal of Anthropology, 11(2), 159–176. Mattison, SM, Beheim, B, Chak, B, and Buston, P (2016a) Offspring sex preferences among patrilineal and matrilineal Mosuo in Southwest China revealed by differences in parity progression. Royal Society Open Science, 3(9), 160526. Mattison, SM, Brown, MJ, Floyd, B, and Feldman, MW (2015a) Adoption does not increase the risk of mortality among Taiwanese girls in a longitudinal analysis. PLoS ONE, 10(4), 0122867. Mattison, SM, Gin, L, Abraham, AA, Moodie, M, Okanlami, F, and Wander, K (2022a) Community voices: Broadening participation in Science, Technology, Engineering, Mathematics, and Medicine among persons with disabilities. Nature Communications, 13, 7208. Mattison, SM, Hare, D, MacLaren, NG, . . . Wander, K (2022b) Context specificity of “market integration” among the matrilineal Mosuo of southwest China. Current Anthropology, 63(1), 118–124. Mattison, SM, and Neill, DB (2013) The effects of residential ecology on patterns of child work and mother’s reproductive success among Indo-Fijians. Evolution and Human Behavior, 34(3), 207–215. Mattison, SM, Scelza, B, and Blumenfield, T (2014) Paternal Investment and the positive effects of fathers among the matrilineal Mosuo of southwest China. American Anthropologist, 116(3), 591–610. Mattison, SM, and Sear, R (2016) Modernizing evolutionary anthropology. Human Nature, 27(4), 1–16.

Mattison, SM, and Shenk, MK (in press) Ecological evolutionary demography. In R Lee and R Sear, eds. Retrieved from osf.io/vwc3u. Mattison, SM, Smith, EA, Shenk, MK, and Cochrane, EE (2016b) The evolution of inequality. Evolutionary Anthropology, 25(4), 184–199. Mattison, SM, Wander, K, and Hinde, K (2015b) Breastfeeding over two years is associated with longer birth intervals, but not measures of growth or health, among children in Kilimanjaro, TZ. American Journal of Human Biology, 27(6), 807–815. Mauss, M (1967) The Gift: The Form and Reason for Exchange in Archaic Societies, London: W. W. Norton. Maynard Smith, J (1964) Group selection and kin selection. Nature, 201(4924), 1145–1147. Maynard Smith, J (1978) Optimization theory in evolution. Annual Review of Ecology and Systematics, 9, 31–56. Maynard Smith, J (1982) Evolution and the Theory of Games, Cambridge: Cambridge University Press. Maynard Smith, J, and Parker, GA (1976) The logic of asymmetric contests. Animal Behaviour, 24(1), 159–175. Maynard Smith, J, and Price, G (1973) The logic of animal conflict. Nature, 246, 15–18. Maynard-Smith, J, and Szathmary, E (1995) The Major Transitions in Evolution, Oxford and New York: W.H. Freeman Spektrum. Mazur, A, Booth, A, and Dabbs, JMJ (1992) Testosterone and chess competition. Social Psychology Quarterly, 55, 70–77. Mazur, A, and Michalek, J (1998) Marriage, divorce, and male testosterone. Social Forces, 77, 315–330. Mazur, JE (1987) An adjusting procedure for studying delayed reinforcement. In M Commons, JE Mazur, JA Nevin, and H Rachlin, eds., Quantitative Analyses of Behavior, London: Lawrence Erlbaum Associates, 55–73. McAllister, L, Gurven, M, Kaplan, H, and Stieglitz, J (2012) Why do women have more children than they want? Understanding differences in women’s ideal and actual family size in a natural fertility population. American Journal of Human Biology, 24, 786–799. McAllister, L, Pepper, G, Virgo, S, and Coall, DA (2016) The evolved psychological mechanisms of fertility motivation: Hunting for causation in a sea of correlation. Philosophical Transactions of the Royal Society B: Biological Sciences, 371, 20150151.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography McCabe, JT (2004) Cattle Bring Us to Our Enemies: Turkana Ecology, Politics, and Raiding in a Disequilibrium System, Ann Arbor: University of Michigan Press. McCarthy, FD, and McArthur, M (1960) The food quest and the time factor in aboriginal economic life. Oceania, 1(1), 97–104. McCay, BJ, and Acheson, JM (1987) Human ecology of the commons. In BJ McCay and JM Acheson, eds., The Question of the Commons: The Culture and Ecology of Communal Resources, Tucson: The University of Arizona Press, 1–34. McDade, TW, Georgiev, AV, and Kuzawa, CW (2016) Trade-offs between acquired and innate immune defenses in humans. Evolution, Medicine, and Public Health, 2016(1), 1–16. McDade, TW, Williams, S, and Snodgrass, JJ (2007) What a drop can do: Dried blood spots as a minimally invasive method for integrating biomarkers into population-based research. Demography, 44, 899–925. McDaniel, A (2012) Women’s advantage in higher education: Towards understanding a global phenomenon. Sociology Compass, 7, 581–595. McDaniel, A, and Buchmann, C (2015) Gender inequality in educational attainment. In RA Scott and MC Buchmann, eds., Emerging Trends in the Social and Behavioral Sciences, Hoboken: John Wiley & Sons, Inc, 1–14. McDonald, M, Navarrete, C, and van Vugt, M (2012) Evolution and the psychology of intergroup conflict: The male warrior hypothesis. Philosophical Transactions of the Royal Society B: Biological Sciences, 367, 670–679. McElreath, MB, Boesch, C, Kühl, H, and McElreath, R. (2018) Complex dynamics from simple cognition: The primary ratchet effect in animal culture. Evolutionary Behavioral Sciences, 12, 191. McElreath, R (2004) Social learning and the maintenance of cultural variation: An evolutionary model and data from east Africa. American Anthropologist, 106 (2), 308–321. McElreath, R (2020) Statistical Rethinking: A Bayesian Course with Examples in R and STAN, 2nd edn, Boca Raton: CRC Press. McElreath, R, and Boyd, R (2007) Mathematical Models of Social Evolution: A Guide for the Perplexed, Chicago: University of Chicago. McElreath, R, Boyd, R, and Richerson, PJ (2003) Shared norms and the evolution of ethnic markers. Current Anthropology, 44, 122–130.

479

McElreath, R, Lubell, M, Richerson, PJ, . . . Paciotti, B (2005) Applying evolutionary models to the laboratory study of social learning. Evolution and Human Behavior, 26(6), 483–508. McElreath, R, and Smaldino, PE (2015) Replication, communication, and the population dynamics of scientific discovery. PLoS ONE, 10, 0136088. McGraw, JB, and Caswell, H (1996) Estimation of individual fitness from life-history data. The American Naturalist, 147(1), 47–64. McKenna, JJ (1987) Parental supplements and surrogates among primates: Cross-species and crosscultural comparisons. In J Lancaster, J Altmann, A Rossi, and L Sherrod, eds., Parenting across the Life Span, New York: Aldine de Gruyter, 143–184. McKerracher, L, and Nunez-de la Mora, A (2022) More voices are always better: Tackling power differentials in knowledge production and access in human biology. American Journal of Human Biology, 34(S1), 23712. McLeod, P, and Dienes, Z (1996) Do fielders know where to go to catch the ball or only how to get there? Journal of Experimental Psychology, 22, 531–543. McNutt, M (2014) Journals unite for reproducibility. Science, 346(6210), 679–679. Medawar, PB (1952) An Unsolved Problem in Biology, London: Lewis. Meehan, CL (2009) Maternal time allocation in two cooperative childrearing societies. Human Nature, 20(4), 375–393. Meehan, CL, Helfrecht, C, and Quinlan, RJ (2014) Cooperative breeding and Aka children’s nutritional status: Is flexibility key? American Journal of Physical Anthropology, 153(4), 513–525. Meehan, CL, Quinlan, R, and Malcom, CD (2013) Cooperative breeding and maternal energy expenditure among Aka foragers. American Journal of Human Biology, 25, 42–57. Mehr, SA, and Krasnow, MM (2017) Parent-offspring conflict and the evolution of infant-directed song. Evolution and Human Behavior, 38(5), 674–684. Mehta, P, DesJardins, N, van Vugt, M, and Josephs, R (2017) Hormonal underpinnings of status conflict: Testosterone and cortisol are related to decisions and satisfaction in the hawk-dove game. Hormones and Behavior, 92, 141–154. Meijer WM, van IJzendoorn MH, and BakersmanKranenburg MJ (2019) Challenging the challenge hypothesis on testosterone in fathers: Limited metaanalytic support. Psychoneuroendocrinology, 110, 104435.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

480

Bibliography

Menchik, PL (1979) Inter-generational transmission of inequality: An empirical study of wealth mobility. Economica, 46(184), 349–362. Merton, RK (1968) The Matthew effect in science. Science, 159(3810), 56–63. Merton, RK (1988) The Matthew effect in science, II: Cumulative advantage and the symbolism of intellectual property. Isis, 79(4), 606–623. Merton, RK (1993) On the Shoulders of Giants: A Shandean Postscript, Chicago: University of Chicago Press. Mesoudi, A (2011) Cultural Evolution: How Darwinian Theory Can Explain Human Culture and Synthesize the Social Sciences, Chicago: University of Chicago Press. Mesoudi, A (2017) Pursuing Darwin’s curious parallel: Prospects for a science of cultural evolution. Proceedings of the National Academy of Sciences, 114, 7853–7860. Mesoudi, A (2021) Cultural selection and biased transformation: Two dynamics of cultural evolution. Philosophical Transactions of the Royal Society B: Biological Sciences, 376(1828), 20200053. Mesoudi, A, Whiten, A, and Laland, KN (2004) Perspective: Is human cultural evolution Darwinian? Evidence reviewed from the perspective of the origin of species. Evolution, 58(1), 1–11. Mesterton-Gibbons, M, and Dugatkin, LA (1997) Cooperation and the prisoner’s dilemma: Towards testable models of mutualism versus reciprocity. Animal Behaviour, 54, 551–557. Metcalf, CJE, and Pavard, S (2007) Why evolutionary biologists should be demographers. Trends in Ecology and Evolution, 22(4), 205–212. Metcalfe, D, and Barlow, KR (1992) A model for exploring the optimal trade-off between field processing and transport. American Anthropologist, 94(2), 340–356. Migliano, AB, Vinicius, L, and Lahr, MM (2007) Life history trade-offs explain the evolution of human pygmies. Proceedings of the National Academy of Sciences, 104(51), 20216–20219. Milanovic, B (2016) Global Inequality: A New Approach for the Age of Globalization, Cambridge: Harvard University Press. Milanovic, B, Lindert, PH, and Williamson, JG (2011) Pre-industrial inequality. Economic Journal, 121 (551), 255–272. Milinski, M, Semman, D, and Krambeck, H (2002) Donors to charity gain in both indirect reciprocity and political reputation. Proceedings of the

Royal Society B: Biological Sciences, 269, 881–883. Milkie, MA, Nomaguchi, KM, and Denny, KE (2015) Does the amount of time mothers spend with children or adolescents matter? Journal of Marriage and Family, 77(2), 355–372. Milton, K (1993) Diet and primate evolution. Scientific American, 269(2), 86–93. Minocher, R, Atmaca, S, Bavero, C, McElreath, R, and Beheim, B (2021) Estimating the reproducibility of social learning research published between 1955 and 2018. Royal Society Open Science, 8(9), 210450. Minocher, R, Duda, P, and Jaeggi, AV (2019) Explaining marriage patterns in a globally representative sample through socio-ecology and population history: A Bayesian phylogenetic analysis using a new supertree. Evolution and Human Behavior, 40(2), 176–187. Mirza, MU, Richter, A, Nes, EH, and Scheffer, M (2019) Technology driven inequality leads to poverty and resource depletion. Ecological Economics, 160, 215–226. Mishra, S, Barclay, P, and Sparks, J (2017) The relative state model: Integrating need-based and abilitybased pathways to risk taking. Personality and Social Psychology Review, 21, 176–198. Mitani, J, Gros-Louis, J, and Richards, A (1996) Sexual dimorphism, the operational sex ratio, and the intensity of male competition in polygynous primates. The American Naturalist, 147, 966–980. Mitani, JC (2006) Demographic influences on the behavior of chimpanzees. Primates, 47, 6–13 Mitani, JC, Call, J, Kappeler, PM, Palombit, R, and Silk, JB, eds. (2012) The Evolution of Primate Societies, Chicago: University of Chicago Press. Mitani, JC, and Rodman, PS (1979) Territoriality: The relation of ranging pattern and home range size to defendability, with an analysis of territoriality among primate species. Behavioral Ecology and Sociobiology, 5(3), 241–251. Mitani, JC, and Watts, DP (1997) The evolution of nonmaternal caretaking among anthropoid primates: Do helpers help? Behavioral Ecology and Sociobiology, 40, 213–220. Mobarak, AM, Kuhn, R, and Peters, C (2013) Consanguinity and other marriage market effects of a wealth shock in Bangladesh. Demography, 50(5), 1845–1871. Mock, D, and Parker, GA (1997) The Evolution of Sibling Rivalry, New York: Oxford University Press.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography Modin, B (2002) Birth order and mortality: A life-long follow-up of 14,200 boys and girls born in early 20th century Sweden. Social Science and Medicine, 54(7), 1051–1064. Mohlenhoff, KA, and Codding, BF (2017) When does it pay to invest in a patch? The evolution of intentional niche construction. Evolutionary Anthropology, 26(5), 218–227. Møller, AP, and Birkhead, TR (1993) Certainty of paternity covaries with paternal care in birds. Behavioral Ecology and Sociobiology, 33(4), 261–268. Moorad, J, Promislow, D, and Silvertown, J (2019) Evolutionary ecology of senescence and a reassessment of Williams’ ‘extrinsic mortality’ hypothesis. Trends in Ecology and Evolution, 34(6), 519–530. Moorad, JA, and Walling, CA (2017) Measuring selection for genes that promote long life in a historical human population. Nature Ecology and Evolution, 1(11), 1773–1781. Moore, F, Cassidy, C, Smith, M, and Perrett, D (2006) The effects of female control of resources on sexdifferentiated mate preferences. Evolution and Human Behavior, 27, 193–205. Moore, J (1993) Inbreeding and outbreeding in primates: What’s wrong with “the dispersing sex. In NW Thornhill, ed., The Natural History of Inbreeding and Outbreeding: Theoretical and Empirical Perspectives, Chicago: University of Chicago Press, 392–426. Moran Cruz, JAH, and Gerberding, R (2004) Medieval Worlds: An Introduction to European History 300–1492, Boston: Houghton Mifflin. Moravec, JC, Atkinson, Q, Bowern, C, . . . Cox, MP (2018) Post-marital residence patterns show lineagespecific evolution. Evolution and Human Behavior, 39(6), 594–601. Moreau, L (2020) Social Inequality before Farming? Multidisciplinary Approaches to the Study of Cocial Organization in Prehistoric and Ethnographic Hunter-gatherer-fisher Societies, Cambridge: McDonald Institute for Archaeological Research. Morgan, C (2012) Modeling modes of hunter-gatherer food storage. American Antiquity, 77(4), 714–736. Morgan, C (2015) Is it intensification yet? Current archaeological perspectives on the evolution of huntergatherer economies. Journal of Archaeological Research, 23(2), 163–213. Morgan, D (1988) Medieval Persia 1040–1797, London: Longman. Morgan, LH (1877) Ancient Society, Chicago: Kerr. Morin, E, Bird, D, Winterhalder, B, and Bliege Bird, R (2022) Deconstructing hunting returns: Can we

481

reconstruct and predict payoffs from pursuing prey? Journal of Archaeological Method and Theory, 29(2), 561–623. Morita, M, Go, T, Hirabayashi, K, Heike, T, and Japan Environment and Children’s Study Group (2017) Parental condition and infant sex at birth in the Japan environment and children’s study: A test of the Trivers–Willard hypothesis. Letters on Evolutionary Behavioral Science, 8(2), 40–44. Moritz, M, Behnke, R, Beitl, CM, . . . Wilson, JA (2018) Emergent sustainability in open property regimes. Proceedings of the National Academy of Sciences, 115(51), 12859–12867. Moritz, M, Gardiner, E, Hubbe, M, and Johnson, A (2019) Comparative study of pastoral property regimes in Africa offers no support for economic defensibility model. Current Anthropology, 60(5), 609–636. Moritz, M, Giblin, J, Ciccone, M, and Senn, M (2011) Social risk-management strategies in pastoral systems: A qualitative comparative analysis. CrossCultural Research, 45(3), 286–317. Moritz, M, Hamilton, IM, Chen, Y-J, and Scholte, P (2014) Mobile pastoralists in the Logone floodplain distribute themselves in an ideal free distribution. Current Anthropology, 55(1), 115–122. Moritz, M, Hamilton, IM, Yoak, AJ, . . . Pi, H (2015a) Simple movement rules result in ideal free distribution of mobile pastoralists. Ecological Modelling, 305, 54–63. Moritz, M, Handa, S, Chen, YJ, and Xiao, N (2015b) Herding contracts and pastoral mobility in the far north region of Cameroon. Human Ecology, 43(1), 141–151. Moritz, M, Scholte, P, Hamilton, IM, and Kari, S (2013) Open access, open systems: Pastoral management of common-pool resources in the Chad Basin. Human Ecology, 41(3), 351–365. Morris, J, Link, J, Martin, J, and Carrier, D (2020) Sexual dimorphism in human arm power and force: Implications for sexual selection on fighting ability. Journal of Experimental Biology, 223, 212365. Mote, FW (1999) Imperial China 900–1800, Cambridge: Harvard University Press. Mountford, CP. ed. (n.d.) Records of the AmericanAustralian Scientific Expedition to Arnhem Land 1948, Vol. 2, Melboune: Melbourne University Press. Mountford, CP, and Harvey, A (1941) Women of the Adnjamatana tribe of the Northern Flinders Ranges, South Australia. Oceania, 12(2), 155–162.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

482

Bibliography

Mousseau, T, and Fox, C (1998) The adaptive significance of maternal effects. Trends in Ecology and Evolution, 13, 403–407. Moya, C, Snopkowski, K, and Sear, R (2016) What do men want? Re-examining whether men benefit from higher fertility than is optimal for women. Philosophical Transactions of the Royal Society of London B: Biological Sciences, 371, 20150149. Muehlenbein, M, and Bribiescas, R (2005) Testosteronemediated immune functions and male life histories. American Journal of Human Biology, 17, 527–558. Muehlenbein, MP, Hirschtick, JL, Bonner, JZ, and Swartz, AM (2010) Toward quantifying the usage costs of human immunity: Altered metabolic rates and hormone levels during acute immune activation in men. American Journal of Human Biology, 22, 546–556. Mujcic, R, and Frijters, P (2012) Economic choices and status: Measuring preferences for income rank. Oxford Economic Papers, 65, 47–73. Muller, M, and Wrangham, R (2004) Dominance, aggression, and testosterone in wild chimpanzees: A test of the ‘challenge hypothesis.’ Animal Behaviour, 67, 113–123. Muller, MN, Marlowe, FW, Bugumba, R, and Ellison, PT (2009) Testosterone and paternal care in East African foragers and pastoralists. Proceedings of the Royal Society B: Biological Sciences, 276, 347–354. Müller, W, Lessells, CKM, Korsten, P, and Engelhardt, N (2007) Manipulative signals in family conflict? On the function of maternal yolk hormones in birds. The American Naturalist, 169(4), 84–96. Munafò, MR, Nosek, BA, Bishop, DVM, . . . Ioannidis, JPA (2017) A manifesto for reproducible science. Nature Human Behaviour, 1(1), 1–9. Munoz, SE, Gruley, KE, Massie, A, Fike, DA, Schroeder, S, and Williams, JW (2015) Cahokia’s emergence and decline coincided with shifts of flood frequency on the Mississippi River. Proceedings of the National Academy of Sciences, 112(20), 6319–6324. Murdock, GP (1949) Social Structure, New York: Macmillan. Murdock, GP (1962–1971) Ethnographic Atlas, Pittsburgh: University of Pittsburgh Press. Murdock, GP, and Provost, C (1973) Factors in the division of labor by sex: A cross-cultural analysis. Ethnology, 12, 203–225. Murdock, GP, and White, DR (1969) Standard CrossCultural Sample. Ethnology, 8(4), 329–369.

Murdock, GP, and Wilson, SF (1972) Settlement patterns and community organization: Cross-cultural codes 3. Ethnology, 11(3), 254–295. Murray, C, Mane, S, and Pusey, A (2007) Dominance rank influences female space use in wild chimpanzees, Pan troglodytes: Towards an ideal despotic distribution. Animal Behaviour, 74, 1795–1804. Muthukrishna, M (2020) Beyond Western, Educated, Industrial, Rich, and Democratic (WEIRD) psychology: Measuring and mapping scales of cultural and psychological distance. Psychological Science, 31, 678–701. Muthukrishna, M, Doebeli, M, Chudek, M, and Henrich, J (2018) The cultural brain hypothesis: How culture drives brain expansion, sociality, and life history. PLoS Computational Biology, 14, 1006504. Myrdal, J (2011) Farming and feudalism 1000–1700. In J Myrdal and M Morell, eds., The Agrarian History of Sweden: 4000 BC to AD 2000, Lund: Nordic Academic Press, 172–117. Myrskylä, M, Silventoinen, K, Jelenkovic, A, Tynelius, P, and Rasmussen, F (2013) The association between height and birth order: Evidence from 652,518 Swedish men. Journal of Epidemiol Community Health, 67, 571–577. Næss, MW, Bårdsen, B-J, Fauchald, P, and Tveraa, T (2010) Cooperative pastoral production – The importance of kinship. Evolution and Human Behavior, 31, 246–258. Næss, MW, Bårdsen, B-J, and Tveraa, T (2012) Wealthdependent and interdependent strategies in the Saami reindeer husbandry, Norway. Evolution and Human Behavior, 33, 696–707. Nag, M, White, B, and Peet, R (1978) An anthropological approach to the study of the economic value of children in Java and Nepal. Current Anthropology, 19(2), 293–306. Naidu, S, Hwang, SH, and Bowles, S (2010) Evolutionary bargaining with intentional idiosyncratic play. Economics Letters, 109(1), 31–33. Nakahaski, W, Wakano, JY, and Henrich, J (2012) Adaptive social learning strategies in temporally and spatially varying environments. Human Nature, 23(4), 386–414. Nash, J (1950) Equilibrium points in N-person games. Proceedings of the National Academy of Sciences, 36, 48–49. Nash, J (1978) A note on groomprice. American Anthropologist, 80(1), 106–108. Navarrete, CD, and Fessler, DMT (2006) Disease avoidance and ethnocentrism: The effects of disease

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography vulnerability and disgust sensitivity on intergroup attitudes. Evolution and Human Behavior, 27, 270–282. Neco, LC, and Richerson, PJ (2014) Was human evolution driven by Pleistocene climate change? Ciência and Ambiente, 1, 107–118. Neff, BD (2003) Decisions about parental care in response to perceived paternity. Nature, 422(6933), 716. Negraia, DV, Augustine, JM, and Prickett, KC (2018) Gender disparities in parenting time across activities, child ages, and educational groups. Journal of Family Issues, 39(11), 3006–3028. Neill, DB (2007) Exploring the Indo-Fijian children’s BMI in the context of urbanization, embodied capital, and food choice trade-offs. Human Nature, 18(3), 209–224. Neirynck, E, Vandeviver, C, and Bernasco, W (2023) The foraging perspective in criminology: A review of research literature. European Journal of Criminology, 20, 626–652. Netting, RM (1967) Cultural Ecology, 2nd edn, Prospect Heights: Waveland Press. Netting, RM (1968) Hill Farmers of Nigeria: Cultural Ecology of the Kofyar of the Jos Plateau, Seattle: University of Washington Press. Netting, RM (1993) Smallholders, Householders: Farm Families and the Ecology of Intensive, Sustainable Agriculture, Stanford: Stanford University Press. Netting, RM, Stone, GD, and Stone, MP (1993) Agricultural expansion, intensification, and market participation among the Kofyar. In R Kates, BL Turner II, and G Hyden, eds., Population Growth and Agricultural Change in Africa, Jos Plateau, Nigeria: University of Florida Press, 206–249. Netting, RM, Stone, MP, and Stone, GD (1989) Kofyar cash cropping: Choice and change in indigenous agricultural development. Human Ecology, 17, 299–319. Nettle, D (2008) Why do some dads get more involved than others? Evidence from a large British cohort. Evolution and Human Behavior, 29(6), 416–423. Nettle, D (2010a) Dying young and living fast: Variation in life history across English neighborhoods. Behavioral Ecology, 21(2), 387–395. Nettle, D (2010b) Why are there social gradients in preventative health behavior? A perspective from behavioral ecology. PLoS ONE, 5(10), e13371. Nettle, D, Andrews, C, and Bateson, M (2017) Food insecurity as a driver of obesity in humans: The

483

insurance hypothesis. Behavioral and Brain Sciences, 40, e105. Nettle, D, and Bateson, M (2017) Childhood and adult socioeconomic position interact to predict health in mid-life in a cohort of British women. PeerJ, 5, 3528. Nettle, D, and Frankenhuis, WE (2019) The evolution of life-history theory: A bibliometric analysis of an interdisciplinary research area. Proceedings of the Royal Society B: Biological Sciences, 286(1899), 20190040. Nettle, D, Gibson, MA, Lawson, DW, and Sear, R (2013) Human behavioral ecology: Current research and future prospects. Behavioral Ecology, 24(5), 1031–1040. Nettle, D, and Pollet, T (2008) Natural selection on male wealth in humans. American Naturalist, 172, 658–666. Newcomer, SD, Zeh, JA, and Zeh, DW (1999) Genetic benefits enhance the reproductive success of polyandrous females. Proceedings of the National Academy of Sciences, 96, 10236–10241. Newson, L, Richerson, PJ, and Boyd, R (2007) Cultural evolution and the shaping of cultural diversity. In S Kitayama and D Cohen,eds., Handbook of Cultural Psychology, New York: Guilford, 454–476. Newton-Fisher, N (2006) Female coalitions against male aggression in wild chimpanzees of the Budongo Forest. International Journal of Primatology, 27, 1589–1599. Nicolson, NA (1987) Infants, mothers, and other females. In BB Smuts, DL Cheney, RM Seyfarth, RW Wrangham, and TT Struhsaker, eds., Primate Societies, Chicago: University of Chicago Press, 330–342. Nielsen, M, Mushin, I, Tomaselli, K, and Whiten, A (2014) Where culture takes hold: ‘Overimitation’ and its flexible deployment in Western, Aboriginal, and Bushmen children. Child Development, 85, 2169–2184. Nielsen, M, and Tomaselli, K (2010) Overimitation in Kalahari Bushman children and the origins of human cultural cognition. Psychological Science, 21, 729–736. Nikiforidis, L, Durante, KM, Redden, JP, and Griskevicius, V (2018) Do mothers spend more on daughters while fathers spend more on sons? Journal of Consumer Psychology, 28(1), 149–156. Nindl, BC, Barnes, BR, Alemany, JA, Frykman, PN, Shippee, RL, and Friedl, KE (2007) Physiological consequences of U.S. Army Ranger training.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

484

Bibliography

Medicine and Science in Sports and Exercercise, 39, 1380–1387. Nisbett, RE, Peng, K, Choi, I, and Norenzayan, A (2001) Culture and systems of thought: Holistic versus analytic cognition. Psychological Review, 108(2), 291–310. Nobes, G, Panagiotaki, G, and Russell Jonsson, K (2018) Child homicides by stepfathers: A replication and reassessment of the British evidence. Journal of Experimental Psychology, 148, 1091. Noë, R (2017) Local mating markets in humans and nonhuman animals. Behavioral Ecology and Sociobiology, 71(10), 148. Noë, R, and Hammerstein, P (1994) Biological markets: Supply and demand determine the effect of partner choice in cooperation, mutualism and mating. Behavioral Ecology and Sociobiology, 35(1), 1–11. Noë, R, and Hammerstein, P (1995) Biological markets. Trends in Ecology and Evolution, 10(8), 336–339. Noë, R, Vanschaik, C, and Vanhooff, J (1991) The market effect – An explanation for pay-off asymmetries among collaborating animals. Ethology, 87(1–2), 97–118. Nolin, D (2008) Food-sharing networks in Lamalera: Tests of adaptive hypotheses (PhD Dissertation), University of Washington, Seattle. Nolin, DA (2010) Food-sharing Networks in Lamalera, Indonesia: Reciprocity, kinship, and distance. Human Nature, 21(3), 243–268. Nolin, D (2011) Kin preference and partner choice. Human Nature, 22(1), 156–176. Nolin, D (2012) Food-sharing networks in Lamalera, Indonesia: Status, sharing, and signaling. Evolution and Human Behavior, 33(4), 334–345. Nordenskiöld, E (1915) Forskningar och äventyr i Sydamerika, Stockholm: Albert Bonniers Förlag. Norenzayan, A, Shariff, AF, Gervais, WM, . . . Henrich, J (2016) The cultural evolution of prosocial religions. Behavioral and Brain Sciences, 39, 1–65. North, D (1990) Institutions, Institutional Change, and Economic Performance, Cambridge; New York: Cambridge University Press. Noss, AJ, and Hewlett, BS (2001) The contexts of female hunting in Central Africa. American Anthropologist, 103(4), 1024–1040. Nowak, M, and Sigmund, K (1992) Tit for tat in heterogeneous populations. Nature, 355, 250–252. Nowak, M, Tarnita, C, and Wilson, E (2010) The evolution of eusociality. Nature, 466(7310), 1057–1062. Nowak, MA (2006) Five rules for the evolution of cooperation. Science, 314(5805), 1560–1563.

Nowak, MA, and Sigmund, K (1998) The dynamics of indirect reciprocity. Journal of Theoretical Biology, 194(4), 561–574. Nunez-De La Mora, A, Chatterton, RT, Choudhury, OA, Napolitano, DA, and Bentley, GR (2007) Childhood conditions influence adult progesterone levels. PLoS Medicine, 4(5), e167. Nunn, CL (2011) The Comparative Approach in Evolutionary Anthropology and Biology, Chicago: University of Chicago Press. Nunn, CL, Mulder, MB, and Langley, S (2006) Comparative methods for studying cultural trait evolution: A simulation study. Cross-Cultural Research, 40, 177–209. Nzinga, K, Rapp, DN, Leatherwood, C, . . . Medin, DL (2018) Should social scientists be distanced from or engaged with the people they study? Proceedings of the National Academy of Sciences, 115(45), 11435–11441. Obeyesekere, G (2008) Land Tenure in Village Ceylon: A Sociological and Historical Study, Cambridge: Cambridge University Press. O’Brien, MJ, and Laland, KN (2012) Genes, culture, and agriculture: An example of human niche construction. Current Anthropology, 53(4), 434–470. O’Connell, JF, and Allen, J (2012) The restaurant at the end of the universe: Modelling the colonisation of Sahul. Australian Archaeology, 74, 5e17. O’Connell, JF, and Hawkes, K (1981) Alyawara plant use and optimal foraging theory. In B Winterhalder and EA Smith, eds., Hunter-Gatherer Foraging Strategies: Ethnographic and Archaeological Analyses, Chicago: University of Chicago Press, 99–125. O’Connell, JF, and Hawkes, K (1984) Food Choice and foraging sites among the Alyawara. Journal of Anthropological Research, 40(4), 504–535. O’Connell, JF, Hawkes, K, and Blurton Jones, NG (1999) Grandmothering and the evolution of Homo erectus. Journal of Human Evolution, 36, 461–485. O’Connell, JF, Hawkes, K, Lupo, KD, and Blurton Jones, NG (2002) Male strategies and Plio-Pleistocene archaeology. Journal of Human Evolution, 43(6), 831–872. O’Connor, A, and Boag, S (2010) Do stepparents experience more parental antagonism than biological parents? A test of evolutionary and socialization perspectives. Journal of Divorce & Remarriage, 51(8), 508–525. O’Connor, K (2003) Urinary estrone conjugate and pregnanediol 3-Glucuronide enzyme immunoassays

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography for population research. Clinical Chemistry, 49, 1139–1148. Odling-Smee, FJ, Laland, KN, and Feldman, MW (1996) Niche construction. The American Naturalist, 147, 641–648. Odling-Smee, FJ, Laland, KN, and Feldman, MW (2003) Niche Construction: The Neglected Process in Evolution, Princeton: Princeton University Press. Öhman, A, and Mineka, S (2003) The malicious serpent: Snakes as a prototypical stimulus for an evolved module of fear. Current Directions in Psychological Science, 12(1), 5–9. Ojalehto Mays, B, Seligman, R, and Medin, DL (2020) Cognition beyond the human: Cognitive psychology and the new animism. Ethos, 48(1), 50–73. Okada, D, and Bingham, PM (2008) Human uniquenessself-interest and social cooperation. Journal of Theoretical Biology, 253(2), 261–270. Okasha, S (2009) Evolution and the Levels of Selection, Oxford: Oxford University Press. Oliveira, RF, Silva, A, and Canário, AVM (2009a) Why do winners keep winning? Androgen mediation of winner but not loser effects in cichlid fish. Proceedings of the Royal Society B: Biological Sciences, 276, 2249–2256. Oliveira, T, Gouveia, MJ, and Oliveira, RF (2009b) Testosterone responsiveness to winning and losing experiences in female soccer players. Psychoneuroendocrinology, 34, 1056–1064. Oliver, MB, and Hyde, JS (1993) Gender differences in sexuality: A meta-analysis. Psychological Bulletin, 114(1), 29–51. Olson, BR, Cartledge, T, Sebring, N, Defensor, R, and Nieman, L (1995) Short-term fasting affects luteinizing hormone secretory dynamics but not reproductive function in normal-weight sedentary women. Journal of Clinical Endocrinology and Metabolism, 80, 1187–1193. Olson, M (1965) The Logic of Collective Action: Public Goods and the Theory of Groups, Cambridge: Harvard University Press. Omran, AR (1971) The epidemiologic transition: A theory of the epidemiology of population change. The Milbank Memorial Fund Quarterly, 49(4), 509–538. Onarheim, KH, Sisay, MM, Gizaw, M, Moland, KM, and Miljeteig, I (2017) What if the baby does not survive? Health-care decision making for ill newborns in Ethiopia. Social Science and Medicine, 195, 123–130. Opie, C, Atkinson, QD, Dunbar, RIM, Shultz, S, and Lovejoy, CO (2013) Male infanticide leads to social

485

monogamy in primates. Proceedings of the National Academy of Sciences, 110(33), 13328–13332. Opie, C, Shultz, S, Atkinson, QD, Currie, T, and Mace, R (2014) Phylogenetic reconstruction of Bantu kinship challenges: Main sequence theory of human social evolution. Proceedings of the National Academy of Sciences, 111(49), 17414–17419. Orians, GH (1969) On the evolution of mating systems in birds and mammals. The American Naturalist, 103 (934), 589–603. Orians, GH, and Pearson, NE (1979) On the theory of central place foraging. In DJ Horn, GR Stairs, and RD Mitchell, eds., Analysis of Ecological Systems, Columbus: Ohio State University Press, 154–177. Ortiz, A (1969) The Tewa World: Space, Time, Being, and Becoming in a Pueblo Society, Chicago: University of Chicago Press. Ortman, S, and Coffey, G (2017) Settlement scaling in middle-range societies. American Antiquity, 82(4), 662–682. Ortman, SG, Cabaniss, AHF, Sturm, JO, and Bettencourt, LMA (2014) The pre-history of urban scaling. PLoS ONE, 9(2), 87902. Ortman, SG, Cabaniss, AHF, Sturm, JO, and Bettencourt, LMA (2015) Settlement scaling and increasing returns in an ancient society. Science Advances, 1(1), 1400066. Ostrom, E (1990) Governing the Commons: The Evolution of Institutions for Collective Action, Cambridge: Cambridge University Press. Ostrom, E (2000) Collective action and the evolution of social norms. Journal of Economic Perspectives, 14(3), 137–158. Ostrom, E, Walker, J, and Gardner, R (1992) Covenants with and without a sword: Self-governance is possible. American Political Science Review, 86, 404–417. Otter, K, and Ratcliffe, L (1996) Female initiated divorce in a monogamous songbird: Abandoning mates for males of higher quality. Proceedings of the Royal Society B: Biological Sciences, 263, 351–355. Otterbein, KF (1965) Caribbean family organization: A comparative analysis. American Anthropologist, 67(1), 66–79. Otto, SP, and Day, T (2007) A Biologist’s Guide to Mathematical Modeling in Ecology and Evolution, Princeton: Princeton University Press. Oxford, J, Ponzi, D, and Geary, DC (2010) Hormonal responses differ when playing violent video games against an ingroup and outgroup. Evolution and Human Behavior, 31, 201–209.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

486

Bibliography

Oyama, S, Griffiths, PE, and Gray, RD, eds. (2001) Cycles of Contingency: Developmental Systems and Evolution, Cambridge: MIT Press. Oyegbile, TO, and Marler, CA (2005) Winning fights elevates testosterone levels in California mice and enhances future ability to win fights. Hormones and Behavior, 48, 259–267. Ozgul, A, Tuljapurkar, S, Benton, TG, Pemberton, JM, Clutton-Brock, TH, and Coulson, T (2009) The dynamics of phenotypic change and the shrinking sheep of St. Kilda. Science, 325(5939), 464–467. Pacheco-Cobos, L, Grote, MN, Kennett, DJ, and Winterhalder, B (2015) Population and environmental correlates of maize yields in Mesoamerica: A test of Boserup’s hypothesis in the milpa. Human Ecology, 43, 559–576. Pacheco-Cobos, L, Winterhalder, B, Cuatianquiz-Lima, C, Rosetti, MF, Hudson, R, and Ross, CT (2019) Nahua mushroom gatherers use area-restricted search strategies that conform to marginal value theorem predictions. Proceedings of the National Academy of Sciences, 116(21), 10339–10347. Packer, C, Lewis, S, and Pusey, A (1992) A comparative analysis of non-offspring nursing. Animal Behaviour, 43(2), 265–281. Packer, C, Pusey, AE, and Eberly, LE (2001) Egalitarianism in female African lions. Science, 293(5530), 690–693. Padilla-Coreano, N, Batra, K, and Patarino, M (2022) Cortical ensembles orchestrate social competition through hypothalamic outputs. Nature, 603, 667–671. Page, A, Chaudhary, N, and Viguier, S (2017) Huntergatherer social networks and reproductive success. Scientific Reports, 7, 1153. Page, AE, Thomas, MG, Smith, D, . . . Migliano, AB (2019) Testing adaptive hypotheses of alloparenting in Agta foragers. Nature Human Behaviour, 3, 1154–1163. Page, AE, Viguier, S, Dyble, M, . . . Migliano, AB (2016) Reproductive trade-offs in extant hunter-gatherers suggest adaptive mechanism for the Neolithic expansion. Proceedings of the National Academy of Sciences, 113(17), 4694–4699. Page, L, and Coates, J (2017) Winner and loser effects in human competitions. Evidence from equally matched tennis players. Evolution and Human Behavior, 38, 530–535. Pagel, M (1994) Detecting correlated evolution on phylogenies: A general method for the comparative analysis of discrete characters. Proceedings of the

Royal Society B: Biological Sciences, 255(1342), 37–45. Panchanathan, K (2011) George Price, the Price equation, and cultural group selection. Evolution and Human Behavior, 32, 368–371. Panchanathan, K, and Boyd, R (2004) Indirect reciprocity can stabilize cooperation without the second-order free rider problem. Nature, 432, 499–502. Pandit, S, and van Schaik, C (2003) A model of levelling coalitions among primate males: Towards a theory of egalitarianism. Behavioral Ecology and Sociobiology, 55, 161–168. Pandit, SA, Pradhan, GR, and Schaik, CP (2020) Why class formation occurs in humans but not among other primates: A primate coalitions model. Human Nature, 31(2), 155–173. Paquet, M, and Smiseth, PT (2017) Females manipulate behavior of caring males via prenatal maternal effects. Proceedings of the National Academy of Sciences, 114(26), 6800–6805. Parker, AK, Parker, CH, and Codding, BF (2019) When to defend? Optimal territoriality across the Numic homeland. Quaternary International, 518, 3–10. Parker, GA, (1979) Sexual selection and sexual conflict. In MS Blum and NA Blum, eds., Sexual Selection and Reproductive Competition in Insects, Greece: Academic Press, 123–166. Parker, GA, Royle, NJ, and Hartley, IR (2002) Intrafamilial conflict and parental investment: A synthesis. Philosophical Transactions of the Royal Society of London B: Biological Sciences, 357(1419), 295–307. Patton, J (2004) Coalitional effects on reciprocal fairness in the ultimatum game: A case from the Ecuadorian Amazon. In J Henrich, R Boyd, and S Bowles, eds., Foundations of human sociality: Economic experiments and ethnographic evidence from fifteen smallscale societies, New York: Oxford University Press, 96–124. Patton, J (2005) Meat sharing for coalitional support. Evolution & Human Behavior, 26, 137–157. Pavard, S, E. Metcalf, CJ, and Heyer, E (2008) Senescence of reproduction may explain adaptive menopause in humans: A test of the “mother” hypothesis. American Journal of Physical Anthropology, 136(2), 194–203. Pawłowski, B, and Dunbar, RIM (1999) Impact of market value on human mate choice decisions. Proceedings of the Royal Society B: Biological Sciences, 266, 281–285.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography Peacey, S, Campbell, O, and Mace, R (2022) Same-sex competition and sexual conflict expressed through witchcraft accusations. Scientific Reports, 12, 6655. Peacock, NR (1991) Rethinking the sexual division of labor. In MD Leonardo, ed., Gender at the Crossroads of Knowledge: Feminist Anthropology in the Postmodern Era, Berkeley: University of California Press, 339–360. Pearl, J (1995) Causal diagrams for empirical research. Biometrika, 82(4), 669–688. Pearl, J (2014) Comment: Understanding Simpson’s paradox. The American Statistician, 68(1), 8–13. Pearl, J, Glymour, M, and Jewell, NP (2016) Causal Inference in Statistics: A Primer, West Sussex: Wiley. Peccei, JS (2001) Menopause: Adaptation or epiphenomenon? Evolutionary Anthropology, 10(2), 43–57. Pedersen, FA (1991) Secular trends in human sex ratios. Human Nature, 2(3), 271–291. Penn, DJ, and Smith, KR (2007) Differential fitness costs of reproduction between the sexes. Proceedings of the National Academy of Sciences, 104(2), 553–558. Pennington, R (2001) Hunter-gatherer demography. In C Panter-Brick, RH Layton, and Rowley, eds., Huntergatherers: An Interdisciplinary Perspective, Cambridge: Cambridge University Press, 170–204. Pennington, R, and Harpending, H (1988) Fitness and fertility among Kalahari !Kung. American Journal of Physical Anthropology, 77(3), 303–319. Pennington, R, and Harpending, H (1993) The Structure of an African Pastoralist Community: Demography, History, and Ecology of the Ngamiland Herero, London: Clarendon Press. Penton-Voak, IS, Perrett, DI, Castles, DL, . . . Minamisawa, R (1999) Menstrual cycle alters face preference. Nature, 399(6738), 741–742. Peoples, H, and Marlowe, F (2012) Subsistence and the evolution of religion. Human Nature, 23, 253–269. Peperkoorn, L, Becker, D, and Balliet, D (2020) The prevalence of dyads in social life. PLoS ONE, 15, 0244188. Pepper, G, and Nettle, D (2017) The behavioural constellation of deprivation: Causes and consequences. Behavioral and Brain Sciences, 40, e314. Pepper, GV, and Nettle, D (2014) Out of control mortality matters: The effect of perceived uncontrollable mortality risk on a health-related decision. PeerJ, 2, e459. Péron, G, Bonenfant, C, Lemaitre, JF, Ronget, V, Tidiere, M, and Gaillard, JM (2019) Does grandparental care

487

select for a longer lifespan in non-human mammals? Biological Journal of the Linnean Society, 128(2), 360–372. Perreault, C, Moya, C, and Boyd, R (2012) A Bayesian Approach to the Evolution of Social Learning. Evolution and Human Behavior, 33, 449–459. Perret, C, Hart, E, and Powers, ST (2020) From disorganized equality to efficient hierarchy: How group size drives the evolution of hierarchy in human societies. Proceedings of the Royal Society B: Biological Sciences, 287(1928), 20200693. Perry, GH, Dominy, NJ, Claw, KG, . . . Stone, AC (2007) Diet and the evolution of human amylase gene copy number variation. Nature Genetics, 39(1), 1256–1260. Perry, S (2003) Social conventions in wild white-faced capuchin monkeys: Evidence for traditions in a neotropical primate. Current Anthropology, 44, 241–268. Perry, S, and Manson, JH (2003) Traditions in monkeys. Evolutionary Anthropology, 12, 71–81. Petersen, MB, Osmundsen, M, and Bor, A (2021) Beyond populism: The psychology of status-seeking and extreme political discontent. In JP Forgas, WD Crano, and K Fiedler, eds., The Psychology of Populism, New York: Routledge, 62–80. Petersen, MB, Skov, M, Serritzlew, S, and Ramsøy, T (2013) Motivated reasoning and political parties: Evidence for increased processing in the face of party cues. Political Behavior, 35(4), 831–854. Peterson, EL (2017) The Life Organic: The Theoretical Biology Club and the Roots of Epigenetics, Pittsburgh: University of Pittsburgh Press. Peterson, N (1993) Demand sharing – Reciprocity and the pressure for generosity among foragers. American Anthropologist, 95(4), 860–874. Petrie, M, and Kempenaers, B (1998) Extra-pair paternity in birds: Explaining variation between species and populations. Trends in Ecology and Evolution, 13(2), 52–58. Pettay, J, Helle, S, Jokela, J, and Lummaa, V (2007) Natural selection on female life history traits in relation to socio-economic class in pre-industrial human populations. PLoS ONE, 2(7), 606. Pettay, JE, Lahdenperä, M, Rotkirch, A, and Lummaa, V (2016) Costly Reproductive competition between coResident females in humans. Behavioral Ecology, 27 (6), 1601–1608. Pettay, JE, Rotkirch, A, Courtiol, A, Jokela, M, and Lummaa, V (2014) Effects of remarriage after widowhood on long-term fitness in a monogamous

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

488

Bibliography

historical human population. Behavioral Ecology and Sociobiology, 68(1), 135–143. Phillips, T, Li, J, and Kendall, G (2014) The effects of extra-somatic weapons on the evolution of human cooperation towards non-kin. PLoS ONE, 9, e95742. Pietraszewski, D (2016) How the mind sees coalitional and group conflict: The evolutionary invariances of n-person conflict dynamics. Evolution and Human Behavior, 37, 470–480. Pietraszewski, D, and Shaw, A (2015) Not by strength alone: Children’s conflict expectations follow the logic of the asymmetric war of attrition. Human Nature, 26, 44–72. Piezunka, H, Lee, W, Haynes, R, and Bothner, M (2018) Escalation of competition into conflict in competitive networks of Formula One drivers. Proceedings of the National Academy of Sciences, 115, 3361–3367. Pigliucci, M, and Muller, G, eds. (2010) Evolution, The Extended Synthesis, Cambridge: MIT Press. Piketty, T (2017) Capital in the Twenty-First Century, Cambridge: Harvard University Press. Piketty, T, and Saez, E (2014) Inequality in the long run. Science, 344(6186), 838–843. Pillsworth, EG (2008) Mate preferences among the Shuar of Ecuador: Trait rankings and peer evaluations. Evolution and Human Behavior, 29(4), 256–267. Pillsworth, EG, and Haselton, MG (2006) Women’s sexual strategies: The evolution of long-term bonds and extrapair sex. Annual Review of Sex Research, 17(1), 59–100. Pinet, P, Jaquemet, S, Phillips, RA, and Le Corre, M (2012) Sex-specific foraging strategies throughout the breeding season in a tropical, sexually monomorphic small petrel. Animal Behaviour, 83(4), 979–989. Pingali, P, Bigot, Y, and Binswanger, HP (1987) Agricultural Mechanization and the Evolution of Farming Systems in Sub-Saharan Africa, Baltimore: Johns Hopkins University Press for the World Bank. Pink, KE, Schaman, A, and Fieder, M (2017) Sex differences in intergenerational income transmission and educational attainment: Testing the Trivers-Willard hypothesis. Frontiers in Psychology, 8, 1879. Pinker, S (1994) The Language Instinct, New York: William Morrow & Co. Pinker, S (2003) The Blank Slate: The Modern Denial of Human Nature, New York: Penguin Books. Pinker, S, and Bloom, P (1990) Natural selection and natural language. Behavioral and Brain Sciences, 13, 707–784.

Piperno, D (2006) The origins of plant cultivation and domestication in the neotropics: A behavioral ecological perspective. In DJ Kennett and B Winterhalder, eds., Behavioral Ecology and the Origins of Agriculture, Berkeley: University of California Press, 137–166. Pisor, AC, and Jones, JH (2021) Human adaptation to climate change: An introduction to the special issue. American Journal of Human Biology, 33(4), e23530. Platek, SM, and Shackelford, TK (2006) Female infidelity and Paternal Uncertainty: Evolutionary Perspectives on Male Anti-Cuckoldry Tactics, Cambridge: Cambridge University Press. Plattner, S (1989) Markets and market places. In S Plattner, ed., Economic Anthropology, Stanford: Stanford University Press, 171–208. Plavcan, M (2012) Sexual size dimorphism, canine dimorphism, and male-male competition in primates: Where do humans fit in? Human Nature, 23, 45–67. Pleasant, A, and Barclay, P (2018) Why hate the good guy? Antisocial punishment of high cooperators is greater when people compete to be chosen. Psychological Science, 29, 868–876. Pleskac, TJ, and Hertwig, R (2014) Ecologically rational choice and the structure of the environment. Journal of Experimental Psychology: General, 143(5), 2000–2019. Polanyi, K (1977) The Livelihood of Man: Studies in Social Discontinuity, New York: Academic Press. Pollet, TV, and Nettle, D (2008) Driving a hard bargain: Sex ratio and male marriage success in a historical US population. Biology Letters, 4(1), 31–33. Pollet, TV, and Nettle, D (2009) Market forces affect patterns of polygyny in Uganda. Proceedings of the National Academy of Sciences, 106(7), 2114–2117. Pollet, TV, and Saxton, TK (2019) How diverse are the samples used in the journals ‘Evolution & Human Behavior’ and ‘Evolutionary Psychology’? Evolutionary Psychological Science, 5(3), 357–368. Pollet, TV, Tybur, JM, Frankenhuis, WE, and Rickard, IJ (2014) What can cross-cultural correlations teach us about human nature? Human Nature, 25(3), 410–429. Pollock, G (1989) Evolutionary stability of reciprocity in a viscous lattice. Social Networks, 11, 175–213. Pollom, TR, Herlosky, KN, Mabulla, IA, and Crittenden, AN (2020) Changes in juvenile foraging behavior among the Hadza of Tanzania during early transition to a mixed-subsistence economy. Human Nature, 31, 123–140.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography Pope, SK, Whiteside, L, Brooks-Gunn, J, . . . Casey, PH (1993) Low-birth-weight infants born to adolescent mothers: Effects of coresidency with grandmother on child development. JAMA, 269(11), 1396–1400. Popkin, BM (2001) The nutrition transition and obesity in the developing world. The Journal of Nutrition, 131(3), 871–873. Porter, CC, and Marlowe, FW (2007) How marginal are forager habitats? Journal of Archaeological Science, 34(1), 59–68. Poundstone, W (1992) Prisoner’s Dilemma, New York: Doubleday. Powell, A, Shennan, S, and Thomas, MG (2009) Late Pleistocene demography and the appearance of modern human behavior. Science, 324, 1298–1301. Power, E (2017a) Discerning devotion: Testing the signaling theory of religion. Evolution and Human Behavior, 38(1), 82–91. Power, E (2017b) Social support networks and religiosity in rural south India. Nature Human Behaviour, 1, 0057. Power, E, and Ready, E (2018) Building bigness: Reputation, prominence, and social capital in rural South India. American Anthropologist, 120, 444–459. Powers, ST, and Lehmann, L (2014) An evolutionary model explaining the Neolithic transition from egalitarianism to leadership and despotism. Proceedings of the Royal Society B: Biological Sciences, 281(1781), 20141349. Powers, ST, Schaik, CP, and Lehmann, L (2016) How institutions shaped the last major evolutionary transition to large-scale human societies. Philosophical Transactions of the Royal Society B: Biological Sciences, 371(1687), 20150098. Powers, ST, van Schaik, CP, and Lehmann, L (2021) Cooperation in large-scale human societies – What, if anything, makes it unique, and how did it evolve? Evolutionary Anthropology, 30(4), 280–293. Poznik, G, Xue, Y, and Mendez, F (2016) Punctuated bursts in human male demography inferred from 1,244 worldwide Y-chromosome sequences. Nature Genetics, 48, 593–599. Prahladachar, M (1983) Income distribution effects of the Green Revolution in India: A review of empirical evidence. World Development, 11(11), 927–944. Prall, S, and Scelza, B (2024) The causes and consequences of women’s status in Himba pastoralists. Evolution and Human Behavior (forthcoming). Prall, SP, and Scelza, BA (2020a) Resource demands reduce partner discrimination in Himba women. Evolutionary Human Sciences, 2, e45.

489

Prall, SP, and Scelza, BA (2020b) Why men invest in non-biological offspring: Paternal care and paternity confidence among Himba pastoralists. Proceedings of the Royal Society B: Biological Sciences, 287, 20192890. Prasad, C, Imrhan, V, Marotta, F, Juma, S, and Vijayagopal, P (2014) Lifestyle and advanced glycation end products (AGEs) burden: Its relevance to healthy aging. Aging and Disease, 5(3), 212. Prestes-Carneiro, G, Béarez, P, Shock, MP, Prümers, H, and Betancourt, CJ (2019) Pre-Hispanic fishing practices in interfluvial Amazonia: Zooarchaeological evidence from managed landscapes on the Llanos de Mojos savanna. PLoS ONE, 14(5), 0214638. Pretelli, I, Ringen, E, and Lew-Levy, S (2022) Foraging complexity and the evolution of childhood. Science Advances, 8(41), eabn9889. Price, GR (1970) Selection and covariance. Nature, 227, 520–521. Price, J (2008) Parent-child quality time: Does birth order matter? Journal of Human Resources, 43(1), 240–265. Price, M (2003) Pro-community altruism and social status in a Shuar village. Human Nature, 14, 191–208. Price, M, and van Vugt, M (2014) The evolution of leaderfollower reciprocity: The theory of service-for-prestige. Frontiers in Human Neuroscience, 4, 363. Prime, H, Plamondon, A, and Jenkins, JM (2017) Birth order and preschool children’s cooperative abilities: A within-family analysis. British Journal of Developmental Psychology, 35(3), 392–405. Promislow, DEL, and Harvey, PH (1990) Living fast and dying young: A comparative analysis of life history variation among mammals. Journal of Zoology, 220, 417–437. Prooijen, J (2018) The Moral Punishment Instinct, New York: Oxford University Press. Prufer, KM, Thompson, AE, Meredith, CR, and Kennett, DJ (2017) The classic period Maya transition from an ideal free to an ideal despotic settlement system at the polity of Uxbenká. Journal of Anthropological Archaeology, 45, 53–68. Purzycki, BG, Apicella, C, Atkinson, QD, and Henrich, J (2016) Moralistic gods, supernatural punishment and the expansion of human sociality. Nature, 530 (7590), 327–330. Pusey, A and Wolf, M (1996) Inbreeding avoidance in animals. Trends in Ecology & Evolution, 11(5), 201–206.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

490

Bibliography

Pusey, AE, and Packer, C (1987) The evolution of sexbiased dispersal in lions. Behaviour, 101(4), 275–310. Pusey, AE, Williams, J, and Goodall, J (1997) The influence of dominance rank on the reproductive success of female chimpanzees. Science, 277(5327), 828–831. Putnam, AE, Putnam, DE, Andreu-Hayles, L, and Broecker, WS (2016) Little Ice Age wetting of interior Asian deserts and the rise of the Mongol Empire. Quaternary Science Reviews, 131, 33–50. Qian, Y (1994) Incentives and loss of control in an optimal hierarchy. The Review of Economic Studies, 61(3), 527–544. Queller, D (2017) Fundamental theorems of evolution. American Naturalist, 189(4), 345–353. Queller, DC (1992) A general model for kin selection. Evolution, 46(2), 376–380. Quinlan, RJ (2006) Gender and risk in a matrifocal Caribbean community: A view from behavioral ecology. American Anthropologist, 108(3), 464–479. Quinlan, RJ (2007) Human parental effort and environmental risk. Proceedings of the Royal Society B: Biological Sciences, 274(1606), 121–125. Quinlan, RJ, and Hagen, EH (2008) New genealogy: It’s not just for kinship anymore. Field Methods, 20(2), 129–154. Quinlan, RJ, and Quinlan, MB (2008) Human lactation, pair-bonds, and alloparents. Human Nature, 19(1), 87–102. Radcliffe-Brown, AR (1948) The Andaman Islanders, Glencoe: The Free Press. Radcliffe-Brown, AR (1950) Introduction. In AR Radcliffe-Brown and D Forde, eds., African Systems of Kinship and Marriage, London: Oxford University Press. Raff, JW (2013) The San Francisco declaration on research assessment. Biology Open, 2(6), 533–534. Raffield, B, Price, N, and Collard, M (2017) Male-biased operational sex ratios and the Viking phenomenon: An evolutionary anthropological perspective on Late Iron Age Scandinavian raiding. Evolution and Human Behavior, 38, 315–324. Raihani, N, and Smith, S (2015) Competitive helping in online giving. Current Biology, 25, 1183–1186. Ralph, SG, Rutherford, AJ, and Wilson, J (1999) Influence of bacterial vaginosis on conception and miscarriage in the first trimester: Cohort study. BMJ, 319(7204), 220–223. Ramos, D, Victor, T, Seidl-de-Moura, ML, and Daly, M (2013) Future discounting by slum-dwelling youth

versus university students in Rio de Janeiro. Journal of Research on Adolescence, 23, 95–102. Rankin, D, and Taborsky, M (2009) Assortment and the evolution of generalized reciprocity. Evolution, 63 (7), 1913–1922. Rantala, MJ, and Marcinkowska, UM (2011) The role of sexual imprinting and the Westermarck effect in mate choice in humans. Behavioral Ecology and Sociobiology, 65(5), 859–873. Ratnieks, FLW, and Anderson, C (1999) Task partitioning in insect societies. Insectes Sociaux, 47(2), 95–108. Rayo, L (2007) Relational incentives and moral hazard in teams. Review of Economic Studies, 74, 937–963. Ready, E, and Power, E (2018) Why wage earners hunt food sharing, social structure, and influence in an Arctic mixed economy. Current Anthropology, 59(1), 74–97. Ready, E, and Price, MH (2021) Human behavioral ecology and niche construction. Evolutionary Anthropology, 30(1), 71–83. Redhead, D, Cheng, J, Driver, C, Foulsham, T, and O’Gorman, R (2019) On the dynamics of social hierarchy: A longitudinal investigation of the rise and fall of prestige, dominance, and social rank in naturalistic task groups. Evolution and Human Behavior, 40, 222–234. Redhead, D, Dhaliwal, N, and Cheng, JT (2021) Taking charge and stepping in: Individuals who punish are rewarded with prestige and dominance. Social and Personality Psychology Compass, 15(2), e12581. Redhead, D, and Power, EA (2022) Social hierarchies and social networks in humans. Philosophical Transactions of the Royal Society B: Biological Sciences, 377(1845), 20200440. Redhead, D, and von Rueden, CR (2021) Coalitions and conflict: A longitudinal analysis of men’s politics. Evolutionary Human Sciences, 3, e31. Reeve, H, and Shen, S (2006) A missing model in reproductive skew theory: The bordered tug-of-war. Proceedings of the National Academy of Sciences, 103, 8430–8434. Reiches, MW, Ellison, PT, Lipson, SF, Sharrock, KC, Gardiner, E, and Duncan, LG (2009) Pooled energy budget and human life history. American Journal of Human Biology, 21(4), 421–429. Reid, A (1988) Female roles in pre-colonial Southeast Asia. Modern Asian Studies, 22, 629–645. Remeš, V, Freckleton, RP, Tökölyi, J, Liker, A, and Székely, T (2015) The evolution of parental cooperation in birds. Proceedings of the National Academy of Sciences, 112, 13603–13608.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography Rendall, MS, Clarke, L, Peters, HE, Ranjit, N, and Verropoulou, G (1999) Incomplete reporting of men’s fertility in the United States and Britain: A research note. Demography, 36, 135–144. Rendell, L, and Whitehead, H (2001) Culture in whales and dolphins. Behavioral and Brain Sciences, 24, 309–324. Reyes-García, V, Godoy, R, Huanca, T, . . . Vadez, V (2007a) The origins of monetary income inequality: Patience, human capital, and division of labor. Evolution and Human Behavior, 28, 37–47. Reyes-Garcia, V, Godoy, R, Vadez, V, Huanca, T, and Leonard, W (2006) Personal and group incentives to invest in pro-social behavior. Journal of Anthropological Research, 62, 81–101. Reyes-García, V, Martí, N, McDade, T, Tanner, S, and Vadez, V (2007b) Concepts and methods in studies measuring individual ethnobotanical knowledge. Journal of Ethnobiology, 27(2), 182–203. Reynolds, AZ, Wander, K, Sum, CY, . . . Mattison, SM (2020) Matriliny reverses gender disparities in inflammation and hypertension among the Mosuo of China. Proceedings of the National Academy of Sciences, 117(48), 30324–30327. Reynolds, T (2022) Our grandmothers’ legacy: Challenges faced by female ancestors leave traces in modern women’s same-sex relationships. Archives of Sexual Behavior, 51(7), 3225–3256. Rice, WR (2018) The high abortion cost of human reproduction. bioRxiv, 372193. Richardson, GB, Sanning, BK, Lai, MH, Copping, LT, Hardesty, PH, and Kruger, DJ (2017) On the psychometric study of human life history strategies: State of the science and evidence of two independent dimensions. Evolutionary Psychology, 15(1), 1474704916666840. Richerson, P, and Boyd, R (1978) A dual inheritance model of the human evolutionary process I: Basic postulates and a simple model. Journal of Social and Biological Systems, 1, 127–154. Richerson, P, and Henrich, J (2012) Tribal social instincts and the cultural evolution of institutions to solve collective action problems. Cliodynamics, 3, 38–80. Richerson, PJ, Baldini, R., Bell, A. V., Demps, K., Frost, K., Hillis, V., . . . Zefferman, M. (2016) Cultural group selection plays an essential role in explaining human cooperation: A sketch of the evidence. Behavioral and Brain Sciences, 39, e30. Richerson, PJ, Bettinger, RL, and Boyd, R (2005) Evolution on a restless planet: Were environmental variability and environmental change major drivers

491

of human evolution? In F. M. Wuketits and F. J. Ayala, eds., Handbook of Evolution, Vol. 2, The Evolution of Living Systems, 223–242. Richerson, PJ, and Boyd, R (1999) Complex societies: The evolutionary origins of a crude superorganism. Human Nature, 10, 253–289. Richerson, PJ, and Boyd, R (2000) Climate, culture, and the evolution of cognition. In C Heyes and L Huber, eds., The Evolution of Cognition, Cambridge: MIT Press, 329–345. Richerson, PJ, and Boyd, R (2005) Not by Genes Alone: How Culture Transformed Human Evolution, W.W. Norton. Richerson, PJ, and Boyd, R (2010) Why possibly language evolved. Biolinguistics, 4, 289–306. Richerson, PJ, and Boyd, R (2013) Rethinking paleoanthropology: A world queerer than we supposed. In G Hatfield and H Pittman, eds., Evolution of Mind, Brain, and Culture, Philadelphia: University of Pennsylvania Museum of Archaeology and Anthropology, 263–302. Richerson, PJ, and Boyd, R (2020) The human life history is adapted to exploit the adaptive advantages of culture. Philosophical Transactions of the Royal Society B: Biological Sciences, 375(1803), 20190498. Richerson, PJ, Boyd, R, and Bettinger, RL (2001) Was agriculture impossible during the Pleistocene but mandatory during the Holocene? A climate change hypothesis. American Antiquity, 66(3), 387–411. Richerson, PJ, Boyd, R, and Henrich, J (2010) Geneculture coevolution in the age of genomics. Proceedings of the National Academy of Sciences, 107, 8985–8992. Richman, RA, and Kirsch, LR (1988) Testosterone treatment in adolescent boys with constitutional delay in growth and development. New England Journal of Medicine, 319, 1563–1567. Rickard, IJ, Courtiol, A, and Lummaa, V (2012) Why is lifetime fertility higher in twinning women? Proceedings of the Royal Society B: Biological Sciences, 279(1738), 2510–2511. Ridgeway, C (2019) Status: Why Is It Everywhere? Why Does It Matter? New York: Russell Sage. Rindos, D (1984) The Origins of Agriculture: An Evolutionary Perspective, New York: Academic Press. Ringen, EJ, Duda, P, and Jaeggi, AV (2019) The evolution of daily food sharing: A Bayesian phylogenetic analysis. Evolution and Human Behavior, 40(4), 375–384.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

492

Bibliography

Ringen, EJ, Martin, JS, and Jaeggi, A (2021) Novel phylogenetic methods reveal that resource-use intensification drove the evolution of “complex” societies. EcoEvoRxiv, doi: 10.32942/osf.io/wfp95. Riskin, J (2016) The Restless Clock: A History of the Centuries-Long Argument over What Makes Living Things Tick, Chicago: University of Chicago Press. Robbins, MM, Bermejo, M, Cipolletta, C, Magliocca, F, Parnell, RJ, and Stokes, E (2004) Social structure and life-history patterns in western gorillas (Gorilla gorilla gorilla). American Journal of Primatology, 64(2), 145–159. Roberts, EK, Lu, A, Bergman, TJ, and Beehner, JC (2012) A Bruce effect in wild geladas. Science, 335, 1222–1225. Roberts, G (1998) Competitive altruism: From reciprocity to the handicap principle. Proceedings of the Royal Society B: Biological Sciences, 265(1394), 427–431. Roberts, G (2005) Cooperation through interdependence. Animal Behaviour, 70, 901–908. Roberts, G, and Sherratt, TN (1998) Development of cooperative relationships through increasing investment. Nature, 394(6689), 175–179. Roberts, P, and Stewart, BA (2018) Defining the ‘generalist specialist’ niche for Pleistocene Homo sapiens. Nature Human Behaviour, 2(8), 542–550. Roberts, SO, Bareket-Shavit, C, Dollins, FA, Goldie, PD, and Mortenson, E (2020) Racial inequality in psychological research: Trends of the past and recommendations for the future. Perspectives on Psychological Science, 15(6), 1295–1309. Robinson, S, Kerven, C, Behnke, R, Kushenov, K, and Milner-Gulland, EJ (2017) Pastoralists as optimal foragers? Reoccupation and site selection in the deserts of post-Soviet Kazakhstan. Human Ecology, 45(1), 5–21. Robson, A, and Kaplan, H (2003) The co-evolution of longevity and intelligence in hunter-gatherer economies. American Economic Review, 93, 150–169. Robson, SL, and Smith, KR (2011) Twinning in humans: Maternal heterogeneity in reproduction and survival. Proceedings of the Royal Society B: Biological Sciences, 278, 3755–3761. Rodin, J (1986) Aging and health: Effects of the sense of control. Science, 233(4770), 1271–1276. Rodseth, L (2012) From bachelor threat to fraternal security: Male associations and modular organization in human societies. International Journal of Primatology, 33, 1194–1214. Rodseth, L, Smuts, BB, Harrigan, AM, and Wrangham, RW (1991a) On the human community as a primate

society – Reply. Current Anthropology, 32(4), 429–433. Rodseth, L, Wrangham, R, Harrigan, A, and Smuts, B (1991b) The human community as a primate society. Current Anthropology, 32(3), 221–254. Rödström, K, Bengtsson, C, Milsom, I, Lissner, L, Sundh, V, and Bjoürkelund, C (2003) Evidence for a secular trend in menopausal age: A population study of women in Gothenburg. Menopause, 10, 538–543. Roff, DA (1993) Evolution of Life Histories: Theory and Analysis, London: Chapman & Hall. Roff, DA (2002) Life History Evolution, Sunderland: Sinauer Associates. Rogers, AR (1988) Does biology constrain culture? American Anthropologist, 90, 819–831. Rogers, AR (1993) Why menopause? Evolutionary Ecology, 7(4), 406–420. Rogers, AR (1994) Evolution of time preference by natural selection. The American Economic Review, 84 (3), 460–481. Rogers, EM (1995) The Diffusion of Innovations, New York: Free Press. Rogers, JD (2012) Inner Asian states and empires: Theories and synthesis. Journal of Archaeological Research, 20(3), 205–256. Romdhane, L, Mezzi, N, Hamdi, Y, El-Kamah, G, Barakat, A, and Abdelhak, S (2019) Consanguinity and inbreeding in health and disease in North African Populations. Annual Review of Genomics and Human Genetics, 20, 155–179. Romero, G, Pham, M, and Goetz, A (2014) The implicit rules of combat. Human Nature, 25, 496–516. Roney, G, JR and Gettler, LT (2015) The role of testosterone in human romantic relationships. Current Opinion in Psychology, 1, 81–86. Roof, KA, Hopkins, WD, Izard, MK, Hook, M, and Schapiro, SJ (2005) Maternal age, parity, and reproductive outcome in captive chimpanzees (Pan troglodytes). American Journal of Primatology, 67(2), 199–207. Roscoe, P (2009) Social signaling and the organization of small-scale society: The case of contact-era New Guinea. Journal of Archaeological Method and Theory, 16, 69–116. Rose, FG (1968) Australian marriage, land-owning groups, and initiations. In RB Lee and I Devore, eds., Man the Hunter, New York: Aldine de Gruyter, 200–208. Rosenbaum, S, Gettler, LT, McDade, TW, Bechayda, SS, and Kuzawa, CW (2018) Does a man’s testosterone “rebound” as dependent children grow up, or when

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography pairbonds end? A test in Cebu. American Journal of Human Biology, 30(6), e23180. Rosenblatt, PC, and Skoogberg, EL (1974) Birth order in cross-cultural perspective. Developmental Psychology, 10(1), 48–54. Ross, C, Borgerhoff Mulder, M, and Oh, S-Y (2018) Greater wealth inequality, less polygyny: Rethinking the polygyny threshold model. Royal Society Interface, 15, 20180035. Ross, C, Campiño, PJ, and Winterhalder, B (2015) Frequency-dependent social transmission and the interethnic transfer of female genital modification in the African Diaspora and indigenous populations of Colombia. Human Nature, 26, 351–377. Ross, CT, Hooper, PL, Smith, JE, Jaeggi, AV, Smith, EA, Gavrilets, S . . . Borgherhoff Mulder, M. (2023) Reproductive inequality in humans and other mammals. Proceedings of the National Academy of Sciences, 120(22):e2220124120. Ross, C, and MacLarnon, A (2000) The evolution of non-maternal care in anthropoid primates: A test of the hypotheses. Folia Primatologica, 71(1–2), 93–113. Ross, CT, Strimling, P, Ericksen, KP, Lindenfors, P, and Borgerhoff Mulder, M (2016) The origins and maintenance of female genital modification across Africa. Human Nature, 27(2), 173–200. Ross, CT, and Winterhalder, B (2015) Sit-and-wait versus active-search hunting: A behavioral ecological model of optimal search mode. Journal of Theoretical Biology, 387, 76–87. Ross, CT, and Winterhalder, B (2016) A hierarchical Bayesian analysis of parasite prevalence and sociocultural outcomes: The role of structural racism and sanitation infrastructure. American Journal of Human Biology, 28(1), 74–89. Ross, M (1986) Female political participation: A crosscultural explanation. American Anthropologist, 88, 843–858. Rosvall, K (2011) Intrasexual competition in females. Behavioral Ecology, 22, 1131–1140. Roulette, CJ, Kazanji, M, Breurec, S, and Hagen, EH (2016) High prevalence of cannabis use among Aka foragers of the Congo Basin and its possible relationship to helminthiasis. American Journal of Human Biology, 28, 5–15. Roulin, A (2003) The neuroendocrine function of allosuckling. Ethology, 109(3), 185–195. Royle, N, Smiseth, P, and Kölliker, M, eds. (2012) The Evolution of Parental Care, Oxford: Oxford University Press.

493

Royle, NJ, Alonzo, SH, and Moore, AJ (2016) Co-evolution, conflict and complexity: What have we learned about the evolution of parental care behaviours? Current Opinion in Behavioral Sciences, 12, 30–36. Royle, NJ, Hartley, IR, and Parker, GA (2002) Sexual conflict reduces offspring fitness in zebra finches. Nature, 416(6882), 733–736. Royle, NJ, and Moore, AJ (2019) Nature and nurture of parental care. In DJ Hosken, J Hunt, and N Wedell, eds., Genes and Behaviour: Beyond Nature-Nurture, West Sussex: Wiley, 131–156. Rubin, P (2000) Hierarchy. Human Nature, 11, 259–279. Rucas, S (2017) Cooperation drives competition among Tsimane women in the Bolivian Amazon. In ML Fisher, ed., The Oxford Handbook of Women and Competition, Oxford: Oxford University Press, 107–132. Ruiz, SA, and Silverstein, M (2007) Relationships with grandparents and the emotional well-being of late adolescent and young adult grandchildren. Journal of Social Issues, 63(4), 793–808. Runciman, WG (2009) The Theory of Cultural and Social Selection, Cambridge: Cambridge University Press. Rusch, H (2014) The evolutionary interplay of intergroup conflict and altruism in humans: A review of parochial altruism theory and prospects for its extension. Proceedings of the Royal Society B: Biological Sciences, 281(1794), 20141539. Russell, A, Brotherton, P, McIlrath, G, Sharpe, L, and Clutton-Brock, T (2003a) Breeding success in cooperative meerkats: Effects of helper number and maternal state. Behavioral Ecology and Sociobiology, 14, 486–492. Russell, AF (2004) Mammals: Comparisons and contrasts. In WD Koenig and JI Dickinson, eds., Ecology and Evolution of Cooperative Breeding Birds, Cambridge: Cambridge University Press, 210–227. Russell, AF, and Hatchwell, BJ (2001) Experimental evidence for kin-biased helping in a cooperatively breeding vertebrate. Proceedings of the Royal Society B: Biological Sciences, 268(1481), 2169–2174. Russell, AF, and Lummaa, V (2009) Maternal effects in cooperative breeders: From hymenopterans to humans. Proceedings of the Royal Society B: Biological Sciences, 364(1520), 1143–1167. Russell, AF, Sharpe, LL, Brotherton, PNM, and CluttonBrock, TH (2003b) Cost minimization by helpers in cooperative vertebrates. Proceedings of the National Academy of Sciences, 100(6), 3333–3338. Rutte, C, Taborsky, M, and Brinkhof, M (2006) What sets the odds of winning and losing? Trends in Ecology and Evolution, 21, 16–21.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

494

Bibliography

Sahlins, M (1958) Social Stratification in Polynesia, Seattle: University of Washington Press. Sahlins, M (1972) Stone Age Economics, New York: Aldine de Gruyter. Sahlins, M (1976) The Use and Abuse of Biology: An Anthropological Critique of Sociobiology, Ann Arbor: The University of Michigan Press. Salali, GD, Chaudhary, N, Thompson, J, . . . Migliano, AB (2016) Knowledge-sharing networks in huntergatherers and the evolution of cumulative culture. Current Biology, 26(18), 2516–2521. Salamon, S (1995) Prairie Patrimony: Family, Farming, and Community in the Midwest, Chapel Hill: UNC Press Books. Salganik, M, Dodds, P, and Watts, D (2006) Experimental study of inequality and unpredictability in an artificial cultural market. Science, 311, 854–856. Salo, AL, and French, JA (1989) Early experience, reproductive success, and development of parental behaviour in Mongolian gerbils. Animal Behaviour, 38(4), 693–702. Salvador, A, Suay, F, Martinez-Sanchis, S, Simon, VM, and Brain, PF (1999) Correlating testosterone and fighting in male participants in judo contests. Physiology and Behavior, 68, 205–209. Sand, H, Wikenros, C, Wabakken, P, and Liberg, O (2006) Effects of hunting group size, snow depth and age on the success of wolves hunting moose. Animal Behaviour, 72(4), 781–789. Sanday, PR (1973) Toward a theory of the status of women. American Anthropologist, 75(5), 1682–1700. Sandell, MI, and Smith, HG (1996) Already mated females constrain male mating success in the European starling. Proceedings of the Royal Society B: Biological Sciences, 263(1371), 743–747. Sapolsky, R (1993) The physiology of dominance in stable versus unstable social hierarchies. In WA Mason and SP Mendoza, eds., Primate Social Conflict, Albany: State University of New York Press, 171–204. Sapolsky, R (2005) The influence of social hierarchy on primate health. Science, 308, 648–652. Sauder, M, Lynn, F, and Podolny, JM (2012) Status: Insights from organizational sociology. Annual Review of Sociology, 38(1), 267–283. Sawyer, SM, Azzopardi, PS, Wickremarathne, D, and Patton, GC (2018) The age of adolescence. The Lancet Child and Adolescent Health, 2(3), 223–228. Scalise Sugiyama, M, Mendoza, M, and Sugiyama, L (2021) War games: Intergroup coalitional play

fighting as a means of comparative coalition formidability assessment. Evolutionary Behavioral Sciences, 15, 91–110. Scelza, B, and Bliege Bird, R (2008) Group structure and female cooperative networks in Australia’s Western Desert. Human Nature, 19, 231–248. Scelza, B, Prall, S, and Starkweather, K (2021) The role of spousal separation on norms related to gender and sexuality among Himba pastoralists. Social Sciences, 10(5), 174. Scelza, BA (2009) The grandmaternal niche: Critical caretaking among Martu Aborigines. American Journal of Human Biology, 21(4), 448–454. Scelza, BA (2010) Fathers’ presence speeds the social and reproductive career of sons. Current Anthropology, 51(2), 295–303. Scelza, BA (2011) Female choice and extra-pair paternity in a traditional human population. Biology Letters, 7(6), 889–891. Scelza, BA (2013) Choosy but not chaste: Multiple mating in human females. Evolutionary Anthropology, 22(5), 259–269. Scelza, BA (2015) Perceptions of polygyny: The effects of offspring and other kin on co-wife satisfaction. Biodemography and Social Biology, 61(1), 98–110. Scelza, BA, Atkinson, EG, Prall, S, McElreath, R, Sheehama, J, and Henn, BM (2020a) The ethics and logistics of field-based genetic paternity studies. Evolutionary Human Sciences, 2, e22. Scelza, BA, and Prall, SP (2018) Partner preferences in the context of concurrency: What Himba want in formal and informal partners. Evolution and Human Behavior, 39(2), 212–219. Scelza, BA, and Prall, SP (2023) Only death will separate us: The role of extramarital partnerships among Himba pastoralists. Archives of Sexual Behavior, 52, 1355–1363. Scelza, BA, Prall, SP, Blumenfield, T, . . . McElreath, R (2020c) Patterns of paternal investment predict cross-cultural variation in jealous response. Nature Human Behaviour. 4, 20–26. Scelza, BA, Prall, SP, Swinford, N, . . . Henn, BM (2020b) High rate of extrapair paternity in a human population demonstrates diversity in human reproductive strategies. Science Advances, 6(8), eaay6195. Scelza, BA, and Silk, J (2014) Fosterage as a system of dispersed cooperative breeding: Evidence from the Himba. Human Nature, 25, 448–464. Schacht, R, and Bell, A (2016) The evolution of monogamy in response to partner scarcity. Scientific Reports, 6, 32472.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography Schacht, R, and Borgerhoff Mulder, M (2015) Sex ratio effects on reproductive strategies in humans. Royal Society Open Science, 2(1), 140402. Schacht, R, Davis, HE, and Kramer, KL (2018) Patterning of paternal investment in response to socioecological change. Frontiers in Ecology and Evolution, 6, 142. Schacht, R, and Kramer, KL (2016) Patterns of family formation in response to sex ratio variation. PLoS ONE, 11(8), e0160320. Schacht, R, and Kramer, KL (2019) Are we monogamous? A review of the evolution of pair-bonding in humans and its contemporary variation cross-culturally. Frontiers in Ecology and Evolution, 7, 230. Schacht, R, Rauch, KL, and Borgerhoff Mulder, M (2014) Too many men: The violence problem? Trends in Ecology and Evolution, 29(4), 214–222. Schacht, R, and Smith, KR (2017) Causes and consequences of adult sex ratio imbalance in a historical US population. Philosophical Transactions of the Royal Society B: Biological Sciences, 372(1729), 20160314. Schaerer, L, Rowe, L, and Arnqvist, G (2012) Anisogamy, chance and the evolution of sex roles. Trends in Ecology and Evolution, 27(5), 260–264. Schaffnit, SB, Hassan, A, Urassa, M, and Lawson, DW (2019a) Parent-offspring conflict unlikely to explain “child marriage” in northwestern Tanzania. Nature Human Behaviour, 3, 346–353. Schaffnit, SB, and Lawson, DW (2021) Married too young? The behavioral ecology of ‘child marriage.’ Social Sciences, 10(5), 161. Schaffnit, SB, Page, AE, Lynch, R, Spake, L, Sear, R, Sosis, R, Shaver, J, Alam, N, Towner, MC and Shenk, MK (2023) The impact of market integration on arranged marriages in Matlab, Bangladesh. Evolutionary Human Sciences, 5, e5. Schaffnit, SB, and Sear, R (2017) Support for new mothers and fertility in the United Kingdom: Not all support is equal in the decision to have a second child. Population Studies, 71(3), 345–361. Schaffnit, SB, Urassa, M, and Lawson, DW (2019b) Child marriage” in context: Exploring local attitudes towards early marriage in rural Tanzania. Sexual and Reproductive Health Matters, 27(1), 93–105. Scharf, I, Peter, F, and Martin, OY (2013) Reproductive trade-offs and direct costs for males in arthropods. Evolutionary Biology, 40(2), 169–184. Scheffer, M, Bavel, B, Leemput, IA, and Nes, EH (2017) Inequality in nature and society. Proceedings of the National Academy of Sciences, 114(50), 13154–13157.

495

Schelling, T (1963) The Strategy of Conflict, Cambridge: Harvard University Press. Scheper-Hughes, N (1992) Death without Weeping, Berkley and Los Angeles: University of California Press. Schlegel, A (1991) Status, property, and the value on virginity. American Ethnologist, 18(4), 719–734. Schlegel, A, and Barry, H (1986) The cultural consequences of female contribution to subsistence. American Anthropologist, 88(1), 142–150. Schlegel, A, and Eloul, R (1988) Marriage transactions: Labor, property, status. American Anthropologist, 90 (2), 291–309. Schlippe, P (1956) Shifting Cultivation in Africa: The Zande System of Agriculture, London: Routledge. Schmitt, DP, Shackelford, TK, and Buss, DM (2001) Are men really more ‘oriented’ toward short-term mating than women? A critical review of theory and research. Psychology, Evolution and Gender, 3(3), 211–239. Schneider, A, Körner, T, Mehring, M, Wensing, M, Elwyn, G, and Szecsenyi, J (2006) Impact of age, health locus of control and psychological comorbidity on patients’ preferences for shared decision making in general practice. Patient Education and Counseling, 61(2), 292–298. Schniter, E (2014) Older adults’ contributions to the Tsimane forager-farmer economy. Anthropology and Aging, 35, 56–58. Schniter, E, Gurven, M, Kaplan, H, Wilcox, N, and Hooper, P (2015) Skill ontogeny among Tsimane forager-horticulturalists. American Journal of Physical Anthropology, 158, 3–18. Schniter, E, Wilcox, NT, Beheim, BA, Kaplan, HS, and Gurven, M (2018) Information transmission and the oral tradition: Evidence of a late-life service niche for Tsimane Amerindians. Evolution and Human Behavior, 39, 94–105. Scholte, P, Kari, S, Moritz, M, and Prins, H (2006) Pastoralist responses to floodplain rehabilitation in North Cameroon. Human Ecology, 34(1), 27–51. Schoorl, JJ, Heering, L, Esveldt, I, Groenewold, GF, and van der Erf, R (2000) Push and Pull Factors of International Migration: A Comparative Report, Luxembourg: Office for Official Publications of the European Communities. Schram, A, Brandts, J, and Gerxhani, K (2019) Socialstatus ranking: A hidden channel to gender inequality under competition. Experimental Economics, 22, 396–418.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

496

Bibliography

Schrock, JM, Snodgrass, JJ, and Sugiyama, LS (2019) Lassitude: The emotion of being sick. Evolution and Human Behavior, 41, 44–57. Schroeder, T (2017) When security dominates the agenda: The influence of ongoing security threats on female representation. Journal of Conflict Resolution, 61, 564–589. Schulz, JF, Bahrami-Rad, D, Beauchamp, JP, and Henrich, J (2019) The church, intensive kinship, and global psychological variation. Science, 366(707), 1–12. Schulz, KM, Molenda-Figueira, HA, and Sisk, CL (2009) Back to the future: The organizational-activational hypothesis adapted to puberty and adolescence. Hormones and Behavior, 55, 597–604. Schuppli, C, Graber, SM, Isler, K, and van Schaik, CP (2016) Life history, cognition and the evolution of complex foraging niches. Journal of Human Evolution, 92, 91–100. Schuppli, C, Isler, K, and van Schaik, CP (2012) How to explain the unusually late age at skill competence among humans. Journal of Human Evolution, 63(6), 843–850. Schwarz, S, and Hassebrauck, M (2012) Sex and age differences in mate-selection preferences. Human Nature, 23(4), 447–466. Scott, JC (2010) The Art of Not Being Governed: An Anarchist History of Upland Southeast Asia, New Haven: Yale University Press. Scott, JC (2017) Against the Grain: A Deep History of the Earliest States, New Haven: Yale University Press. Seabright, E (2022) The burdens of public service: A game theoretical analysis (PhD Dissertation), Department of Anthropology, University of New Mexico, Albuquerque. Sear, R (2007) The impact of reproduction on Gambian women: Does controlling for phenotypic quality reveal costs of reproduction? American Journal of Physical Anthropology, 132(4), 632–641. Sear, R (2015) Evolutionary demography: A Darwinian renaissance in demography. In JD Wright, ed., International Encyclopedia of the Social & Behavioral Sciences, 2nd edn, Vol. 8, Oxford: Elsevier, 406–412. Sear, R (2016) Beyond the nuclear family: An evolutionary perspective on parenting. Current Opinion in Psychology, 7, 98–103. Sear, R (2018) Family and fertility: Does kin help influence women’s fertility, and how does this vary worldwide? Population Horizons. Population Horizons, 14(1), 18–34.

Sear, R (2020) Do human ‘life history strategies’ exist? Evolution and Human Behavior, 41(6), 513–526. Sear, R, and Coall, D (2011) How much does family matter? Cooperative breeding and the demographic transition. Population and Development Review, 37 (s1), 81–112. Sear, R, Lawson, DW, and Dickins, TE (2007) Synthesis in the human evolutionary behavioural sciences. Journal of Evolutionary Psychology, 5, 3–28. Sear, R, Lawson, DW, Kaplan, HS, and Shenk, MK (2016) Understanding variation in human fertility: What can we learn from evolutionary demography? Philosophical Transactions of the Royal Society B: Biological Sciences, 371(1692), 20150144. Sear, R, and Mace, R (2008) Who keeps children alive? A review of the effects of kin on child survival. Evolution and Human Behavior, 29(1), 1–18. Sear, R, Shanley, D, McGregor, I, and Mace, R (2001) The fitness of twin mothers: Evidence from rural Gambia. Journal of Evolutionary Biology, 14, 433–443. Sear, R, Sheppard, P, and Coall, DA (2019) Cross-cultural evidence does not support universal acceleration of puberty in father-absent households. Philosophical Transactions of the Royal Society B: Biological Sciences, 374(1770), 20180124. Sear, R, Steele, F, McGregor, IA, and Mace, R (2002) The effects of kin on child mortality in Gambia. Demography, 39(1), 43–63. Searle, JR (1995) The Construction of Social Reality, New York: Simon and Schuster. Sedziafa, AP, and Tenkorang, EY (2016) Kin group affiliation and marital violence against women in Ghana. Violence and Victims, 31(3), 486–509. Segerstrale, U (2000) Defenders of the Truth: The Battle for Science in the Sociobiology Debate and Beyond, Oxford: Oxford University Press. Ségurel, L, and Bon, C (2017) On the evolution of lactase persistence in humans. Annual Review of Genomics and Human Genetics, 18, 297–319. Seid, MA, and Traniello, JF (2006) Age-related repertoire expansion and division of labor in Pheidole dentata (Hymenoptera: Formicidae): A new perspective on temporal polytheism and behavioral plasticity in ants. Behavioral Ecology and Sociobiology, 60(5), 631–644. Sell, A, Cosmides, L, and Tooby, J (2009) Human adaptations for the visual assessment of strength and fighting ability from the body and face. Proceedings of the Royal Society B: Biological Sciences, 276, 575–584.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography Sellen, DW (2007) Evolution of infant and young child feeding: Implications for contemporary public health. Annual Review of Nutrition, 27, 123–148. Service, E (1962) Primitive Social Organization: An Evolutionary Perspective, New York: Random House. Sevilla-Callejo, M (2008) Ecoregions and Protected Areas of Bolivia, Madrid: Universidad Autonoma de Madrid. Shackelford, TK, Schmitt, DP, and Buss, DM (2005) Universal dimensions of human mate preferences. Personality and Individual Differences, 39(2), 447–458. Shadle, BL (2003) Bridewealth and female consent: Marriage disputes in African courts, Gusiiland, Kenya. The Journal of African History, 44(2), 241–262. Shapiro, D, and Gebreselassie, T (2014) Marriage in SubSaharan Africa: Trends, determinants, and consequences. Population Research and Policy Review, 33(2), 229–255. Shattuck, EC, and Muehlenbein, MP (2015) Human sickness behavior: Ultimate and proximate explanations. American Journal of Physical Anthropology, 157(1), 1–18. Sheehan, O, Watts, J, Gray, RD, and Atkinson, QD (2018) Coevolution of landesque capital intensive agriculture and sociopolitical hierarchy. Proceedings of the National Academy of Sciences, 115, 3628–3633. Sheehy-Skeffington, J, and Haushofer, J (2014) The behavioural economics of poverty”. In Barriers to and Opportunities for Poverty Reduction, Istanbul: United Nations Development Programme, 96–112. Sheldon, BC, and Ellegren, H (1998) Paternal effort related to experimentally manipulated paternity of male collared flycatchers. Proceedings of the Royal Society B: Biological Sciences, 265, 1737–1742. Shen, SF, Emlen, ST, Koenig, WD, and Rubenstein, DR (2017) The ecology of cooperative breeding behaviour. Ecology Letters, 20(6), 708–720. Shenk, MK (2004) Embodied capital and heritable wealth in complex cultures: A class-based analysis of parental investment in urban South India. Research in Economic Anthropology, 23, 307–333. Shenk, MK (2005a) How much gold will you put on your daughter? A behavioral ecology perspective on dowry marriage. CSDE Working Paper, 05-07. Shenk, MK (2005b) Kin investment in wage-labor economies. Human Nature, 16(1), 81–113. Shenk, MK (2007) Dowry and public policy in contemporary India: The behavioral ecology of a “social evil.” Human Nature, 18(3), 242–263.

497

Shenk, MK (2013) A model comparison approach shows stronger support for economic models of fertility decline. Proceedings of the National Academy of Sciences, 110(20), 8045–8050. Shenk, MK (2015) Fertility and fecundity. In P Whelehan and A Bolin, eds., The International Encyclopedia of Human Sexuality, Malden and Oxford: John Wiley & Sons. Shenk, MK (2017) Arranged marriages. In TK Shackelford and VA Weekes-Shackelford, eds., Encyclopedia of Evolutionary Psychological Science, New York: Springer, 1–11. Shenk, MK, Begley, RO, Nolin, DA, and Swiatek, A (2019) When does matriliny fail? The frequencies and causes of transitions to and from matriliny estimated from a de novo coding of a cross-cultural sample. Philosophical Transactions of the Royal Society B: Biological Sciences, 374(1780), 20190006. Shenk, MK, Borgerhoff Mulder, M, Beise, J, and Piraino, P (2010) Intergenerational wealth transmission among agriculturalists: Foundations of agrarian inequality. Current Anthropology, 51(1), 65–83. Shenk, MK, Kaplan, HS, and Hooper, PL (2016a) Status competition, inequality, and fertility: Implications for the demographic transition. Philosophical Transactions of the Royal Society B: Biological Sciences, 371(1692), 20150150. Shenk, MK, Naz, S, and Chowdhury, T (in review) The persistence of intensive kinship: Why Pakistan has the highest rates of cousin marriage in the modern world. Shenk, MK, and Scelza, BA (2012) Paternal investment and status-related child outcomes: Timing of father’s death affects offspring success. Journal of Biosocial Science, 44(5), 549–569. Shenk, MK, Starkweather, K, Kress, HC, and Alam, N (2013) Does absence matter? Human Nature, 24(1), 76–110. Shenk, MK, Towner, MC, Starkweather, K, Atkisson, CJ, and Alam, N (2014) The evolutionary demography of sex ratios in rural Bangladesh. In Applied Evolutionary Anthropology: Darwinian Approaches to Contemporary World Issues, 141–173. Shenk, MK, Towner, MC, Voss, E, and Alam, N (2016b) Consanguineous marriage, kinship ecology, and market transition. Current Anthropology, 57(S13), 167–180. Shennan, S (2008) Population processes and their consequences in early neolithic Central Europe. In J-P Bocquet-Appel and O Bar-Yosef, eds., The Neolithic

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

498

Bibliography

Demographic Transition and Its Consequences, Germany: Springer, 315–329. Shepher, J (1971) Mate selection among second generation kibbutz adolescents and adults: Incest avoidance and negative imprinting. Archives of Sexual Behavior, 1(4), 293–307. Sheppard, P, Snopkowski, K, and Sear, R (2014) Father absence and reproduction-related outcomes in Malaysia, a transitional fertility population. Human Nature, 25(2), 213–234. Sherratt, A (1981) Plough and pastoralism: Aspects of the secondary products revolution. In I Hodder, G Isaac, and N Hammond, eds., Pattern of the Past: Studies in Honor of David Clarke, Cambridge: Cambridge University Press, 261–305. Sherratt, T, and Roberts, G (1998) The evolution of generosity and choosiness in cooperative exchanges. Journal of Theoretical Biology, 193(1), 167–177. Shin, J, Price, MH, Wolpert, DH, Shimao, H, Tracey, B, and Kohler, TA (2020) Scale and informationprocessing thresholds in Holocene social evolution. Nature Communications, 11, 2394. Shipley, B (2016) Cause and Correlation in Biology, 2nd edn, Cambridge: Cambridge University Press. Shizuka, D, and McDonald, D (2015) The network motif architecture of dominance hierarchies. Journal of the Royal Society Interface, 12, 20150080. Shor, E, and Simchai, D (2009) Incest avoidance, the incest taboo, and social cohesion: Revisiting Westermarck and the case of the Israeli kibbutzim. American Journal of Sociology, 114(6), 1803–1842. Shrewder, RA (2012) Anthropology’s disenchantment with the cognitive revolution. Topics in Cognitive Science, 4, 354–361. Shultziner, D, Stevens, T, Stevens, M, Stewart, BA, Hannagan, RJ, and Saltini-Semerari, G (2010) The causes and scope of political egalitarianism during the Last Glacial: A multi-disciplinary perspective. Biology and Philosophy, 25(3), 319–346. Sieff, DF (1990) Explaining biased sex ratios in human populations: A critique of recent studies. Current Anthropology, 31, 25–48. Sigle, W (2021) Demography’s theory and approach: (How) has the view from the margins changed? Population Studies, 75(S1), 235–251. Sigmund, K, and Nowak, MA (1999) Evolutionary game theory. Current Biology, 9(14), 503–505. Silberzahn, R, and Uhlmann, EL (2015) Crowdsourced research: Many hands make tight work. Nature, 526 (7572), 189–191.

Siler, W (1979) A competing-risk model for animal mortality. Ecology, 60(4), 750–757. Silk, JB (1980) Adoption and kinship in Oceania. American Anthropologist, 82, 799–820. Silk, JB (1987) Adoption and fosterage in human societies: Adaptations or enigmas? Cultural Anthropology, 2, 39–49. Silk, JB (1999) Male bonnet macaques use information about third-party rank relationships to recruit allies. Animal Behaviour, 58, 45–51. Silk, JB (2006) Practicing Hamilton’s rule: Kin selection in primate groups. In P Kappeler and C Schaik, eds., Cooperation in Primates and Humans, Berlin: Springer Press, 25–46. Silk, JB (2009) Nepotistic cooperation in non-human primate groups. Philosophical Transactions of the Royal Society B: Biological Sciences, 364, 3243–3254. Silverman, P, and Maxwell, R (1978) How do I respect thee? Let me count the ways: Deference towards elderly men and women. Cross-Cultural Research, 2, 91–108. Simmons, ZL, and Roney, J (2009) Androgens and energy allocation: Quasi-experimental evidence for effects of influenza vaccination on men’s testosterone. American Journal of Human Biology, 21, 133–135. Simms, SR (1987) Behavioral Ecology and HunterGatherer Foraging, Oxford: British Archaeological Reports. Simoons, F (1981) Geographic patterns of adult lactose malabsorption: A further interpretation of evidence for the Old World. In DM Paige and TM Bayless, eds., Lactose Digestion: Clinical and Nutritional Implications, Baltimore: Johns Hopkins University Press, 23–48. Simoons, FJ (1970) Primary adult lactose intolerance and the milking habit: A problem in biologic and cultural interrelations. The American Journal of Digestive Diseases, 15, 695–710. Simpson, E (1951) The interpretation of interaction in contingency tables. Journal of the Royal Statistical Society Series B: Statistical Methodology, 13(2), 238–241. Singh, M, and Glowacki, L (2022) Human social organization during the Late Pleistocene: Beyond the nomadic-egalitarian model. Evolution and Human Behavior, 43, 418–431. Skoufias, E (1994) Market wages, family composition and the time allocation of children in agricultural households. Journal of Development Studies, 30(2), 335–360.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography Skutch, AF (1987) Helpers at Birds’ Nests. A Worldwide Survey of Cooperative Breeding and Related Behavior, Iowa City: University of Iowa Press. Skyrms, B (2004) The Stag Hunt and the Evolution of Social Structure, Cambridge: Cambridge University Press. Slingerland, E, Atkinson, QD, Ember, CR, and Gray, RD (2020) Coding culture: Challenges and recommendations for comparative cultural databases. Evolutionary Human Sciences, 2, e29. Smaldino, P (2014) The cultural evolution of emergent group-level traits. Behavioral and Brain Sciences, 37, 243–295. Smaldino, PE (2017) Models are stupid, and we need more of them. In RR Vallacher, SJ Read, and A Nowak, eds., Computational Social Psychology, United States: Taylor and Francis, 311–331. Smaldino, PE, and McElreath, R (2016) The natural selection of bad science. Royal Society Open Science, 3(9), 160384. Smallwood, PD (1996) An introduction to risk sensitivity: The use of Jensen’s inequality to clarify evolutionary arguments of adaptation and constraint. Integrative and Comparative Biology, 36(4), 392. Smiseth, P, and Royle, N (2018) The resolution of conflict in families. Current Opinion in Insect Science, 28, 8–12. Smith, AK, Ayanian, JZ, Covinsky, KE, . . . Steinman, MA (2011) Conducting high-value secondary dataset analysis: An introductory guide and resources. Journal of General Internal Medicine, 26(8), 920–929. Smith, BD, and Zeder, MA (2013) The onset of the Anthropocene. Anthropocene, 4, 8–13. Smith, D, Schlaepfer, P, Major, K, . . . Astete, L (2017) Cooperation and the evolution of hunter-gatherer storytelling. Nature Communications, 8(1), 1853. Smith, E (2003) Human cooperation: Perspectives from behavioral ecology. In P Hammerstein, ed., Genetic and Cultural Evolution of Cooperation, Cambridge, MA: MIT Press, 401–427. Smith, EA (1985) Inuit foraging groups: Some simple models incorporating conflicts of interest, relatedness, and central-place sharing. Ethology and Sociobiology, 6(1), 27–47. Smith, EA (1987) On fitness maximization, limited needs, and hunter-gatherer time allocation. Ethology and Sociobiology, 8(1), 73–85. Smith, EA (1991) Inujjuamiut Foraging Strategies, New York: Aldine de Gruyter.

499

Smith, EA (1998) Is Tibetan polyandry adaptive? Methodological and metatheoretical analyses. Human Nature, 9(3), 225–261. Smith, EA (2000) Three styles in the evolutionary analysis of human behavior. In L Cronk, NA Chagnon, and W Irons, eds., Adaptation and Human Behavior: An Anthropological Perspective, New York: Aldine de Gruyter, 27–46. Smith, EA (2004) Why do good hunters have higher reproductive success? Human Nature, 15(4), 343–364. Smith, EA (2010) Communication and collective action: Language and the evolution of human cooperation. Evolution and Human Behavior, 31(4), 231–245. Smith, EA, and Bliege Bird, R (2000) Turtle hunting and tombstone opening: Public generosity as costly signaling. Evolution and Human Behavior, 21, 245–261. Smith, EA, Bliege Bird, R, and Bird, DW (2003) The benefits of costly signaling: Meriam turtle hunters. Behavioral Ecology, 14(1), 116–126. Smith, EA, Borgerhoff Mulder, M, Bowles, S, Gurven, M, Hertz, T, and Shenk, MK (2010a) Production systems, inheritance, and inequality in premodern societies: Conclusions. Current Anthropology, 51(1), 85–94. Smith, EA, Borgerhoff Mulder, M, and Hill, K (2001) Controversies in the evolutionary social sciences: A guide for the perplexed. Trends in Ecology and Evolution, 16(3), 128–135. Smith, EA, and Choi, J-K (2007) The emergence of inequality in small-scale societies: Simple scenarios and agent-based simulations. In TA Kohler and S Leeuw, eds., The Model-based Archaeology of Socionatural Systems, Santa Fe: SAR Press, 105–119. Smith, EA, and Codding, BF (2021) Ecological variation and institutionalized inequality in hunter-gatherer societies. Proceedings of the National Academy of Sciences, 118(13), e2016134118. Smith, EA, Hill, K, Marlowe, FW, and Bell, A (2010b) Wealth transmission and inequality among huntergatherers. Current Anthropology, 51(1), 19–34. Smith, EA, and Winterhalder, B, eds. (1992a) Evolutionary Ecology and Human Behavior, New York: Aldine de Gruyter. Smith, EA, and Winterhalder, B (1992b) Natural selection and decision-making: Some fundamental principles. In B Winterhalder and EA Smith, eds., Evolutionary Ecology and Human Behavior, New York: Aldine de Gruyter, 26–60. Smith, J, Ortiz, C, Buhbe, M, and van Vugt, M (2020) Obstacles and opportunities for female leadership in

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

500

Bibliography

mammalian societies: A comparative perspective. The Leadership Quarterly, 31, 101267. Smith, JE, Gavrilets, S, Mulder, MB, and Smith, EA (2016) Leadership in mammalian societies: Emergence, distribution, power, and payoff. Trends in Ecology and Evolution, 31(1), 54–66. Smith, K, and Apicella, C (2020) Partner choice in human evolution: The role of cooperation, foraging ability, and culture in Hadza campmate preferences. Evolution and Human Behavior, 41, 354–366. Smuts, B (1992) Male aggression against women. Human Nature, 3(1), 1–44. Smuts, B (1995) The evolutionary origins of patriarchy. Human Nature, 6(1), 1–32. Smuts, BB, Cheney, DL, Seyfarth, RM, and Wrangham, RW, eds. (2008) Primate Societies, Chicago: University of Chicago Press. Smuts, BB, and Smuts, RW (1993) Male aggression and sexual coercion of females in nonhuman primates and other mammals: Evidence and theoretical implications. Advances in the Study of Behavior, 22(22), 1–63. Snopkowski, K (2016) Marital dissolution and child educational outcomes in San Borja, Bolivia. Human Nature, 27(4), 395–421. Snopkowski, K, Moya, C, and Sear, R (2014) A test of the intergenerational conflict model in Indonesia shows no evidence of earlier menopause in femaledispersing groups. Proceedings of the Royal Society B: Biological Sciences, 281(1788), 20140580. Snopkowski, K, and Sear, R (2016) Does grandparental help mediate the relationship between kin presence and fertility? Demographic Research, 34(17), 467–498. Snyder-Mackler, N, Alberts, SC, and Bergman, TJ (2012) Concessions of an alpha male? Cooperative defence and shared reproduction in multi-male primate groups. Proceedings of the Royal Society B: Biological Sciences, 279(1743), 3788–3795. Snyder-Mackler, N, Sanz, J, Kohn, JN, . . . Tung, J (2016) Social status alters immune regulation and response to infection in macaques. Science, 354, 1041–1045. Sober, E, and Wilson, DS (1998) Unto Others: The Evolution and Psychology of Unselfish Behavior, Cambridge, MA: Harvard University Press. Solomon, NG (1991) Current indirect fitness benefits associated with philopatry in juvenile prairie voles. Behavioral Ecology and Sociobiology, 29(4), 277–282. Solomon, NG, and French, JA, eds. (1997) Cooperative Breeding in Mammals, Cambridge, MA: Cambridge University Press.

Solon, G (2002) Cross-country differences in intergenerational earnings mobility. Journal of Economic Perspectives, 16(3), 59–66. Soltis, J, Boyd, R, and Richerson, PJ (1995) Can groupfunctional behaviors evolve by cultural group selection? An empirical test. Current Anthropology, 36, 473–494. Sonerud, GA, Steen, R, Løw, LM, . . . Slagsvold, T (2014a) Evolution of parental roles in raptors: Prey type determines role asymmetry in the Eurasian kestrel. Animal Behaviour, 96(Supplement C), 31–38. Sonerud, GA, Steen, R, Selås, V, . . . Rønning, ME (2014b) Evolution of parental roles in provisioning birds: Diet determines role asymmetry in raptors. Behavioral Ecology, 25(4), 762–772. Soons, JP, and Kalmijn, M (2009) Is marriage more than cohabitation? Well-being differences in 30 European countries. Journal of Marriage and Family, 71(5), 1141–1157. Sorokowski, P, Groyecka, A, Karwowski, M, . . . B, P (2017) Free mate choice does not influence reproductive success in humans. Scientific Reports, 7(1), 10127. Sosis, R (2002) Patch choice decisions among Ifaluk fishers. American Anthropologist, 104(2), 583–598. Sosis, R, and Bulbulia, J (2011) The behavioral ecology of religion: The benefits and costs of one evolutionary approach. Religion, 41(3), 341–362. Sosis, R, Feldstein, S, and Hill, K (1998) Bargaining theory and cooperative fishing participation on ifaluk atoll. Human Nature, 9(2), 163–203. Sosis, R, Kress, H, and Boster, J (2007) Scars for war: Evaluating alternative signaling explanations for cross-cultural variance in ritual costs. Evolution and Human Behavior, 28, 234–247. Soussan, K (2018) Bayesian approaches to survival analysis with applications in anthropology (Master’s Thesis in Applied Statistics), California State University Long Beach, Long Beach. Sparkman, AM, Adams, JR, Steury, TD, Waits, LP, and Murray, DL (2011) Direct fitness benefits of delayed dispersal in the cooperatively breeding red wolf (Canis rufus). Behavioral Ecology, 22, 199–205. Speakman, JR, and Garratt, M (2014) Oxidative stress as a cost of reproduction: Beyond the simplistic tradeoff model. Bioessays, 36, 93–106. Speiser, E (1942) The Shibboleth incident (Judges 12:6). Bulletin of the American Schools of Oriental, 85, 10–13.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography Spencer, CS (1990) On the tempo and mode of state formation: Neoevolutionism reconsidered. Journal of Anthropological Archaeology, 9(1), 1–30. Spencer, CS (1998) A mathematical model of primary state formation. Cultural Dynamics, 10(1), 5–20. Spencer, CS (2010) Territorial expansion and primary state formation. Proceedings of the National Academy of Sciences, 107(16), 7119–7126. Spencer, CS, and Redmond, EM (2004) Primary state formation in Mesoamerica. Annual Review of Anthropology, 33, 173–199. Sperber, D (1996) Explaining Culture: A Naturalistic Approach, Oxford: Blackwell. Sperber, D, Cara, F, and Girotto, V (1995) Relevance theory explains the selection task. Cognition, 57(1), 31–95. Sperber, D, and Hirschfeld, LA (2004) The cognitive foundations of cultural stability and diversity. Trends in Cognitive Sciences, 8(1), 40–46. Spiro, ME (1960) Is the family universal? The Israeli case. In NW Bell and EF Vogel, eds., A Modern Introduction to the Family, Glencoe: Free Press, 64–75. Spiro, ME (1965) Children of the Kibbutz, New York: Schocken Books. Spisak, B, Grabo, A, Arvey, R, and van Vugt, M (2014) The age of exploration and exploitation: Youngerlooking leaders endorsed for change and olderlooking leaders endorsed for stability. The Leadership Quarterly, 25, 805–816. Spratt, DI, Cox, P, Orav, J, Moloney, J, and Bigos, T (1993) Reproductive axis suppression in acute illness is related to disease severity. Journal of Clinical Endocrinology and Metabolism, 76, 1548–1554. Spratt, DI, Kramer, RS, Morton, JR, Lucas, FL, Becker, K, and Longcope, C (2008) Characterization of a prospective human model for study of the reproductive hormone responses to major illness. American Journal of Physiology, 295, 63–69. Sprecher, S (2002) Sexual satisfaction in premarital relationships: Associations with satisfaction, love, commitment, and stability. The Journal of Sex Research, 39(3), 190–96. Srinivas, MN (1984) Some Reflections on Dowry, New Delhi: Oxford University Press. Stanish, C (2003) Ancient Titicaca: The Evolution of Complex Society in Southern Peru and Northern Bolivia. Berkeley: University of California Press. Stanish, C (2010) The evolution of managerial elites in intermediate societies. In KJ Vaughn, JW Eerkens, and J Kantner, eds., The Evolution of Leadership:

501

Transitions in Decision-Making from Small-Scale to Middle-Range Societies, Santa Fe: SAR Press, 97–119. Stanton, MA, Lonsdorf, EV, Pusey, AE, Goodall, J, and Murray, CM (2014) Maternal behavior by birth order in wild chimpanzees (Pan troglodytes): Increased investment by first-time mothers. Current Anthropology, 55(4), 483–489. Stanton, MA, Lonsdorf, EV, Pusey, AE, and Murray, CM (2017) Do juveniles help or hinder? Influence of juvenile offspring on maternal behavior and reproductive outcomes in wild chimpanzees (Pan troglodytes). Journal of Human Evolution, 111, 152–162. Stanton, SJ, Beehner, JC, Saini, EK, Kuhn, CM, and LaBar, KS (2009) Dominance, politics, and physiology: Voters’ testosterone changes on the night of the 2008 United States presidential election. PLoS ONE, 4, 1–6. Starkweather, K, Shenk, M, and McElreath, R (2020) Biological constraints and socioecological influences on women’s pursuit of risk and the sexual division of labour. Evolutionary Human Sciences, 2, e59. Starkweather, KE (2017) Shodagor family strategies: Balancing work and family on the water. Human Nature, 28(2), 138–166. Starkweather, KE, and Hames, R (2012) A survey of non-classical polyandry. Human Nature, 23(2), 149–172. Starkweather, KE, Reynolds, AZ, Zohora, F, and Alam, N (2023) Shodagor women cooperate across domains of work and childcare to solve an adaptive problem. Philosophical Transactions of the Royal Society B: Biological Sciences, 378(1868), 20210433. Stearman, AM (1989) Yuqui: Forest Nomads in a Changing World, Fort Worth: Holt, Rinehart and Winston. Stearns, SC (1976) Life-history tactics: A review of the ideas. The Quarterly Review of Biology, 51(1), 3–47. Stearns, SC (1992) The Evolution of Life Histories, Vol. 249, Oxford; Oxford University Press. Stearns, SC, Byars, SG, Govindaraju, DR, and Ewbank, D (2010) Measuring selection in contemporary human populations. Nature Reviews Genetics, 11(9), 611–622. Stearns, SC, and Rodrigues, AM (2020) On the use of “life history theory” in evolutionary psychology. Evolution and Human Behavior, 41, 474–485. Steelman, LC, Powell, B, Werum, R, and Carter, S (2002) Reconsidering the effects of sibling configuration: Recent advances and challenges. Annual Review of Sociology, 28(1), 243–269.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

502

Bibliography

Steffen, W, Broadgate, W, Deutsch, L, Gaffney, O, and Ludwig, C (2015) The trajectory of the Anthropocene: The great acceleration. The Anthropocene Review, 2(1), 81–98. Steinkopf, L (2015) The signaling theory of symptoms: An evolutionary explanation of the placebo effect. Evolutionary Psychology, 13, 1–12. Stephens, DW (1981) The logic of risk-sensitive foraging preferences. Animal Behaviour, 29(2), 628–629. Stephens, DW (1990) Risk and incomplete information in behavioral ecology. In EA Cashdan, ed., Risk and Uncertainty in Tribal and Peasant Economies, Boulder: Westview Press, 19–46. Stephens, DW, and Charnov, EL (1982) Optimal foraging: Some simple stochastic models. Behavioral Ecology and Sociobiology, 10(4), 251–263. Stephens, DW, and Krebs, J (1986) Foraging Theory, Princeton: Princeton University Press. Sterck, EHM, Watts, DP, and Schaik, CP (1997) The evolution of female social relationships in nonhuman primates. Behavioral Ecology and Sociobiology, 41(5), 291–309. Sterelny, K (2021) The Pleistocene Social Contract, Oxford: Oxford University Press. Stevens, JD, and Gilby, IC (2004) A conceptual framework for nonkin food sharing: Timing and currency of benefits. Animal Behaviour, 67(4), 603–614. Stevens, JR (2017) Impulsivity: How time and risk influence decision-making. Nebraska Symposium on Motivation, 64, 1–287. Stevens, NE, and McElreath, R (2015) When are two tools better than one? Mortars, millingslabs, and the California acorn economy. Journal of Anthropological Archaeology, 37, 100–111. Stevenson, RJ, Case, TI, and Oaten, MJ (2011) Proactive strategies to avoid infectious disease. Philosophical Transactions of the Royal Society B: Biological Sciences, 366, 3361–3363. Steward, JH (1938) Basin-Plateau Aboriginal Sociopolitical Groups, Washington: U.S. Government Printing Office. Steward, JH (1955) The Theory of Culture Change, Urbana: University of Illinois Press. Stibbard-Hawkes, D (2019) Costly signaling and the handicap principle in hunter-gatherer research: A critical review. Evolutionary Anthropology, 28, 144–157. Stibbard-Hawkes, DNE (2020) Egalitarianism and democratized access to lethal weaponry: A neglected approach. In L Moreau, ed., Social Inequality Before Farming? Multidisciplinary Approaches to the Study

of Social Organization in Prehistoric and Ethnographic Hunter-Gatherer-Fisher Societies, Cambridge: McDonald Institute for Archaeological Research, 83–102. Stieglitz, J, Beheim, BA, Trumble, BC, Madimenos, FC, Kaplan, H, and Gurven, M (2015) Low mineral density of a weight-bearing bone among adult women in a high fertility population. American Journal of Physical Anthropology, 156, 637–648. Stieglitz, J, Gurven, M, Kaplan, H, and Winking, J (2012) Infidelity, jealousy, and wife abuse among Tsimane forager–farmers: Testing evolutionary hypotheses of marital conflict. Evolution and Human Behavior, 33(5), 438–448. Stieglitz, J, Schniter, E, von Rueden, C, Kaplan, H, and Gurven, M (2014) Functional disability and social conflict increase risk of depression in older adulthood among Bolivian forager-farmers. The Journal of Gerontology: Series B, 70, 948–956. Stieglitz, J, Trumble, BC, Kaplan, H, and Gurven, M (2018) Marital violence and fertility in a relatively egalitarian high-fertility population. Nature Human Behaviour, 2(8), 565–572. Stiner, MC, and Kuhn, SL (2016) Are we missing the “sweet spot” between optimality theory and niche construction theory in archaeology? Journal of Anthropological Archaeology, 44, 177–184. Stiver, KA, and Alonzo, SH (2009) Parental and mating effort: Is there necessarily a trade-off? International Journal of Behavioural Biology, 115(12), 1101–1126. Stocks, A (1983) Cocamilla fishing: Patch modification and environmental buffering in the Amazon várzea. In Adaptive Responses of Native Amazonians, Academic Press, 239–267. Stoet, G, and Geary, D (2019) A simplified approach to measuring national gender inequality. PLoS ONE, 14, 0205349. Stone, GD (1996) Settlement Ecology: The Social and Spatial Organization of Kofyar Agriculture, Tucson: University of Arizona Press. Stone, L (2010) Kinship and Gender: An Introduction, 4th edn, Boulder: Westview Press. Strassman, BI, and Clarke, AL (1998) Ecological constraints on marriage in rural Ireland. Evolution and Human Behavior, 19, 33–55. Strassman, BI, and Kurapati, NT (2010) Are humans cooperative breeders? Most studies of natural fertility populations do not support the grandmother hypothesis. Behavioral and Brain Sciences, 33, 35–38.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography Strassmann, BI (1981) Sexual selection, paternal care, and concealed ovulation in humans. Ethology and Sociobiology, 2(1), 31–40. Strassmann, BI (1992) The function of menstrual taboos among the Dogon. Human Nature, 3(2), 89–131. Strassmann, BI (2000) Polygyny, family structure, and child mortality: A prospective study among the Dogon of Mali. In L Cronk, N Chagnon, and W Irons, eds., Adaptation and Human Behavior, New York: Aldine de Gruyter, 49–68. Strassmann, BI, and Gillespie, B (2002) Life-history theory, fertility and reproductive success in humans. Proceedings of the Royal Society B: Biological Sciences, 269(1491), 553–562. Strassmann, BI, and Gillespie, B (2003) How to measure reproductive success? American Journal of Human Biology, 15(3), 361–369. Strauss, E, and Holekamp, K (2019) Social alliances improve rank and fitness in convention-based societies. Proceedings of the National Academy of Sciences, 116, 8919–8924. Stulp, G, and Barrett, L (2015) Fertility theory: Theory of life history evolution. In J Wright, ed., The International Encyclopedia of the Social and Behavioral Sciences, Amsterdam: Elsevier, 40–45. Stulp, G, and Barrett, L (2016) Wealth, fertility and adaptive behaviour in industrial populations. Philosophical Transactions of the Royal Society B: Biological Sciences, 371(1692), 20150153. Stulp, G, Kordsmeyer, T, Buunk, A, and Verhulst, S (2012a) Increased aggression during human group contests when competitive ability is more similar. Biology Letters, 8, 921–923. Stulp, G, Pollet, TV, Verhulst, S, and Buunk, AP (2012b) A curvilinear effect of height on reproductive success in human males. Behavioral Ecology and Sociobiology, 66(3), 375–384. Stulp, G, Sear, R, and Barrett, L (2016a) The reproductive ecology of industrial societies, part I: Why measuring fertility matters. Human Nature, 27(4), 422–444. Stulp, G, Sear, R, Schnaffnit, S, Mells, M, and Barrett, L (2016b) The reproductive ecology of industrial societies, part II. The association between wealth and fertility. Human Nature, 27, 445–470. Stulp, G, Simons, MJ, Grasman, S, and Pollet, TV (2017) Assortative mating for human height: A meta-analysis. American Journal of Human Biology, 29(1), e22917. Sugiyama, LS, and Schrock, JM (2019) The use of biomarkers to answer questions about the evolution of mind and behavior. American Journal of Physical Anthropology, 168, 242.

503

Sugiyama, LS, Tooby, J, and Cosmides, L (2002) Crosscultural evidence of cognitive adaptations for social exchange among the Shiwiar of Ecuadorian Amazonia. Proceedings of the National Academy of Sciences, 99(17), 11537–11542. Sugiyama, MS (2011) The forager oral tradition and the evolution of prolonged juvenility. Frontiers in Psychology, 2, 133. Sullivan Robinson, R, Lee, R, and Kramer, K (2008) Counting women’s labor: A reanalysis of children’s net productivity in Mead Cain’s Bangladeshi village. Population Studies, 62(1), 25–38. Summers, K (2005) The evolutionary ecology of despotism. Evolution and Human Behavior, 26(1), 106–135. Surowiec, A, Snyder, KT, and Creanza, N (2019) A worldwide view of matriliny: Using cross-cultural analyses to shed light on human kinship systems. Philosophical Transactions of the Royal Society B: Biological Sciences, 374(1780), 20180077. Surowiecki, J (2005) The Wisdom of Crowds, New York: Anchor. Svanbäck, R, and Bolnick, DI (2005) Intraspecific competition affects the strength of individual specialization: An optimal diet theory method. Evolutionary Ecology Research, 7(7), 993–1012. Swallow, BM, and Bromley, DW (1995) Institutions, governance and incentives in common property regimes for African rangelands. Environmental and Resource Economics, 6(2), 99–118. Symons, D (1979) The Evolution of Human Sexuality, New York: Oxford University Press. Symons, D (1992) On the use and misuse of Darwinism in the study of human behavior. In JH Barkow, J Tooby, and L Cosmides, eds., The Adapted Mind: Evolutionary Psychology and the Generation of Culture, Oxford: Oxford University Press, 137–159. Sznycer, D, Xygalatas, D, Alami, S, . . . Tooby, J (2018) Invariances in the architecture of pride across smallscale societies. Proceedings of the National Academy of Sciences, 115, 8322–8327. Taborsky, M, Koenig, WD, and Dickinson, JI (2016) Cichlid fishes: A model for the integrative study of social behavior. In WD Koenig and JL Dickinson, eds., Cooperative Breeding in Vertebrates, Cambridge: Cambridge University Press, 272–293. Tainter, J (1988) The Collapse of Complex Societies, Cambridge: Cambridge University Press. Takyi, BK, and Gyimah, SO (2007) Matrilineal family ties and marital dissolution in Ghana. Journal of Family Issues, 28(5), 682–705.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

504

Bibliography

Talhelm, T, Zhang, X, Oishi, S, . . . Kitayama, S (2014) Large-scale psychological differences within China explained by rice versus wheat agriculture. Science, 344, 603–608. Tamimi, RM, Lagiou, P, Mucci, LA, Hsieh, C-C, Adami, H-O, and Trichopoulos, D (2003) Average energy intake among pregnant women carrying a boy compared with a girl. BMJ (Clinical Research Edition), 326(7401), 1245–1246. Tardif, SD (1997) The bioenergetics of parental care in marmosets and tamarins. In NG Solomon and JA French, eds., Cooperative Breeding in Mammals, Cambridge: Cambridge University Press, 11–33. Tataranni, PA, Larson, DE, Snitker, S, Young, JB, Flatt, JP, and Ravussin, E (1996) Effects of glucocorticoids on energy metabolism and food intake in humans. American Journal of Physiology, 271, E317–E235. Taylor, C, and Nowak, MA (2007) Transforming the dilemma. Evolution, 61(10), 2281–2292. Teal, TK, Cranston, KA, Lapp, H, . . . Pawlik, A (2015) Data carpentry: Workshops to increase data literacy for researchers. International Journal of Digital Curation, 10(1), 135–143. Telban, B (1998) Dancing through Time: A Sepik Cosmology, Oxford: Clarendon. Temrin, H, Nordlund, J, Rying, M, and Tullberg, BS (2011) Is the higher rate of parental child homicide in stepfamilies an effect of non-genetic relatedness? Current Zoology, 57(3), 253–259. Tennie, C, Call, J, and Tomasello, M (2006) Push or pull: Imitation vs. emulation in great apes and human children. Ethology, 112, 1159–1169. Tennie, C, Call, J, and Tomasello, M (2009) Ratcheting up the ratchet: On the evolution of cumulative culture. Philosophical Transactions of the Royal Society of London B: Biological Sciences, 364(1528), 2405–2415. Testart, A (1982) The significance of food storage among hunter-gatherers: Residence patterns, population densities, and social inequalities. Current Anthropology, 23(5), 523–537. Testart, A (2013) Reconstructing social and cultural evolution. Current Anthropology, 54(1), 23–50. Textor, J, van der Zander, B, Gilthorpe, MS, Li´skiewicz, M, and Ellison, GT (2016) Robust causal inference using directed acyclic graphs: The R package ‘dagitty.’ International Journal of Epidemiology, 45(6), 1887–1894. Thaxter, CB, Daunt, F, Hamer, KC, . . . Wanless, S (2009) Sex-specific food provisioning in a monomorphic seabird, the common guillemot Uria aalge: Nest

defence, foraging efficiency or parental effort? Journal of Avian Biology, 40(1), 75–84. Thayer, ZM, and Kuzawa, CW (2014) Early origins of health disparities: Material deprivation predicts maternal evening cortisol in pregnancy and offspring cortisol reactivity in the first few weeks of life. American Journal of Human Biology, 730, 723–730. Thierry, B (2008) Primate socioecology, the lost dream of ecological determinism. Evolutionary Anthropology, 17(2), 93–96. Thomas, DH (1981) Complexity among Great Basin Shoshoneans: The world’s least affluent huntergatherers? Senri Ethnological Studies, 9, 19–52. Thompson, VD, Marquardt, WH, Savarese, M, and Walser, CA (2020) Ancient engineering of fish capture and storage in southwest Florida. Proceedings of the National Academy of Sciences, 117(115), 8374–8781. Thomsen, L, Frankenhuis, W, Ingold-Smith, M, and Carey, S (2011) Big and mighty: Preverbal infants mentally represent social dominance. Science, 331, 477–480. Thorne, BL (1997) Evolution of eusociality in termites. Annual Review of Ecology and Systematics, 28, 27–54. Thornhill, R, and Fincher, CL (2011) Parasite stress promotes homicide and child maltreatment. Philosophical Transactions of the Royal Society B: Biological Sciences, 366, 3466–3477. Thurber, C, Dugas, LR, Ocobock, C, Carlson, B, Speakman, JR, and Pontzer, H (2019) Extreme events reveal an alimentary limit on sustained maximal human energy expenditure. Science Advances, 5(6), eaaw0341. Tinbergen, N (1963) On aims and methods of ethology. Zeitschrift für Tierpsychologie, 20, 410–433. Tiokhin, L (2016) Do symptoms of illness serve signaling functions? (Hint: Yes). Quarterly Review of Biology, 91, 177–195. Todd, PM, and Hills, TT (2020) Foraging in mind. Current Directions in Psychological Science, 29(3), 309–315. Todd, PM, Penke, L, Fasolo, B, and Lenton, AP (2007) Different cognitive processes underlie human mate choices and mate preferences. Proceedings of the National Academy of Sciences, 104(38), 15011–15016. Tognetti, A, Berticat, C, Raymond, M, and Faurie, C (2012) Sexual selection of human cooperative behaviour: An experimental study in rural Senegal. PLoS ONE, 7, 44403.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography Tokuyama, N, and Furuichi, T (2016) Do friends help each other? Patterns of female coalition formation in wild bonobos at Wamba. Animal Behaviour, 119, 27–35. Tomasello, M (1996) Do apes ape? In CM Heyes and BG Galef, eds., Social Learning in Animals: The Roots of Culture, San Diego: Academic Press, 319–346. Tomasello, M, Carpenter, M, Call, J, Behne, T, and Moll, H (2005) Understanding and sharing intention: The origins of cultural cognition. Behavioral and Brain Sciences, 28, 675–691. Tomasello, M, Kruger, AC, and Ratner, HH (1993) Cultural learning. Behavioral and Brain Sciences, 16(3), 495–511. Tomasello, M, Melis, AP, Tennie, C, Wyman, E, and Herrmann, E (2012) Two key steps in the evolution of human cooperation: The interdependence hypothesis. Current Anthropology, 53(6), 673–692. Tomasello, M, and Vaish, A (2013) Origins of human cooperation and morality. Annual Review of Psychology, 64, 631–255. Tonkinson, R (1978) The Mardudjara Aborigines: Living the Dream in Australia’s Desert, New York: Holt, Rinehart & Winston. Tooby, J, and Cosmides, L (1992) The psychological foundations of culture. In J Barkow, L Cosmides, and J Tooby, eds., The Adapted Mind: Evolutionary Psychology and the Generation of Culture, Oxford: Oxford University Press, 19–136. Tooby, J, and Cosmides, L (1996) Friendship and the Banker’s Paradox: Other pathways to the evolution of adaptions for altruism. Proceedings of the British Academy, 88, 119–143. Tooby, J, Cosmides, L, and Price, M (2006) Cognitive adaptations for n-person exchange: The evolutionary roots of organizational behavior. Managerial and Decision Economics, 27, 103–129. Tooley, GA, Karakis, M, Stokes, M, and Ozanne-Smith, J (2006) Generalising the Cinderella Effect to unintentional childhood fatalities. Evolution and Human Behavior, 27(3), 224–230. Toth, AL, and Robinson, GE (2007) Evo-devo and the evolution of social behavior. Trends in Genetics, 23(7), 334–341. Towner, MC (1999) A dynamic model of human dispersal in a land-based economy. Behavioral Ecology and Sociobiology, 46(2), 82–94. Towner, MC (2001) Linking dispersal and resources in humans. Human Nature, 12(4), 321–349.

505

Towner, MC (2002) Linking dispersal and marriage in humans: Life history data from Oakham. Evolution and Human Behavior, 23(5), 337–357. Towner, MC, Nenko, I, and Walton, SE (2016) Why do women stop reproducing before menopause? A lifehistory approach to age at last birth. Philosophical Transactions of the Royal Society B: Biological Sciences, 371(1692), 20150147. Tracer, DP (2002) Somatic versus reproductive energy allocation in Papua New Guinea: Life history theory and public health policy. American Journal of Human Biology, 14(5), 621–626. Tracey, MR, and Polachek, SW (2018) If looks could heal: Child health and paternal investment. Journal of Health Economics, 57, 179–190. Traulsen, A, and Nowak, MA (2006) Evolution of cooperation by multilevel selection. Proceedings of the National Academy of Sciences, 103(29), 10952–10955. Tregenza, T (1995) Building on the ideal free distribution. In M Begon and A H Fitter, eds., Advances in Ecological Research, Vol. 26, San Diego: Academic Press, 253–307. Tremayne, AH, and Winterhalder, B (2017) Large mammal biomass predicts the changing distribution of hunter-gatherer settlements in mid-late Holocene Alaska. Journal of Anthropological Archaeology, 45, 81–97. Trevithick, A (1997) On a panhuman preference for monandry: Is polyandry an exception? Journal of Comparative Family Studies, 28(3), 154–181. Trigger, BG (1990) Maintaining economic equality in opposition to complexity: An Iroquoian case study. In S Upham, ed., The Evolution of Political Systems: Sociopolitics in Small-Scale Sedentary Societies, Cambridge: Cambridge University Press, 119–145. Trigger, BG (2003) Understanding Early Civilizations: A Comparative Study, Cambridge: Cambridge University Press. Trivers, RL (1971) The evolution of reciprocal altruism. The Quarterly Review of Biology, 46(1), 35–57. Trivers, RL (1972) Parental investment and sexual selection. In B Campbell, ed., Sexual Selection and the Descent of Man, Chicago: Aldine, 136–179. Trivers, RL (1974) Parent-offspring conflict. American Zoologist, 14, 249–264. Trivers, RL, and Willard, DE (1973) Natural selection of parental ability to vary the sex ratio of offspring. Science, 179, 90–92. Trumble, B, Cummings, D, von Rueden, C, . . . Kaplan, H (2012) Physical competition increases testosterone

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

506

Bibliography

among Amazonian forager-horticulturalists: A test of the ‘challenge hypothesis.’ Proceedings of the Royal Society B: Biological Sciences, 279, 2907–2912. Trumble, BC, Brindle, E, Kupsik, M, and O’Connor, KA (2010) Responsiveness of the reproductive axis to a single missed evening meal in young adult males. American Journal of Human Biology, 22, 775–781. Trumble, BC, Cummings, DK, O’Connor, KA, . . . Gurven, MD (2013) Age-independent increases in male salivary testosterone during horticultural activity among Tsimane forager-farmers. Evolution and Human Behavior, 34, 350–357. Trumble, BC, Smith, EA, O’Connor, KA, Kaplan, HS, and Gurven, MD (2014) Successful hunting increases testosterone and cortisol in a subsistence population. Proceedings of the Royal Society B: Biological Sciences, 281, 20132876. Trumble, BC, Stieglitz, J, Rodriguez, DE, Linares, EC, Kaplan, HS, and Gurven, MD (2015) Challenging the inevitability of prostate enlargement: Low levels of benign prostatic hyperplasia among Tsimane forager-horticulturalists. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 70, 1262–1268. Trumbo, ST (2012) Patterns of parental care in invertebrates. In NJ Royle, PT Smiseth, and M Kölliker, eds., The Evolution of Parental Care, Oxford: Oxford University Press, 81–100. Tsai, LW, and Sapolsky, RM (1996) Rapid stimulatory effects of testosterone upon myotubule metabolism and sugar transport, as assessed by silicon microphysiometry. Aggressive Behavior, 22, 357–364. Tucker, B (2001) The behavioral ecology and economics of risk, variation, and diversification among Mikea forager-farmers of Madagascar (PhD Dissertation), University of North Carolina at Chapel Hill, Chapel Hill. Tucker, B (2004) Giving, scrounging, hiding, and selling: Minimal food sharing among Mikea of Madagascar. In Socioeconomic Aspects of Human Behavioral Ecology, Vol. 23, Netherlands: Emerald Group Publishing Limited, 45–68. Tucker, B (2006) A future-discounting explanation for the persistence of a mixed foraging/cultivation strategy among the Mikea of Madagascar. In D Kennett and B Winterhalder, eds., Behavioral Ecology and the Transition to Agriculture, Berkeley: University of California Press, 22–40. Tucker, B (2007a) Applying behavioral ecology and behavioral economics to conservation and

development planning: Example from the Mikea Forest Madagascar. Human Nature, 18(3), 190–208. Tucker, B (2007b) Perception of interannual covariation and diversification strategies for risk reduction among Mikea of Madagascar: Individual and social learning. Human Nature, 18(2), 162–180. Tucker, B (2014) Rationality and the Green Revolution. In M Gibson and D Lawson, eds., Applied Evolutionary Anthropology: Darwinian Approaches to Contemporary World Issues, New York: Springer, 15–38. Tucker, B (2017) From risk and time preferences to cultural models of causality: On the challenges and possibilities of field experiments, with examples from rural southwestern Madagascar. Nebraska Symposium on Motivation, 64, 61–114. Tucker, B, and Nelson, D (2017) What does economic anthropology have to contribute to studies of risk and resilience? Economic Anthropology, 4(2), 161–172. Tucker, B, and Rende Taylor, L (2007) The human behavioral ecology of contemporary world issues: Applications to public policy and international development. Human Nature, 18(3), 181–189. Tucker, B, Tombo, J, Tsiazonera, H, . . . Zahatsy, C (2013) Beyond mean and variance: Economic risk versus perceived risk of farming, foraging, and fishing activities in Southwestern Madagascar. Human Ecology, 41(3), 393–407. Tucker, B, Tsimitamby, Humber, F, Benbow, S, and Iida, T (2010) Foraging for development: A comparison of food insecurity, production, and risk among farmers, forest foragers, and marine foragers in southwestern Madagascar. Human Organization, 69(4), 375–386. Tucker, B, and Young, AG (2005) Growing up Mikea. Children’s time allocation and tuber foraging in southwest Madagascar. In BS Hewlett and ME Lamb, eds., Hunter-Gatherer Childhoods, New Brunswick: Aldine Transaction, 147–171. Tuljapurkar, S, Puleston, C, and Gurven, M (2007) Why men matter: Mating pattern drives evolution of postreproductive lifespan. PLoS ONE, 2, e785. Tully, T, and Lambert, A (2011) The evolution of postreproductive life span as an insurance against indeterminancy. Evolution, 65(10), 3013–3020. Turchin, P (2003) Historical Dynamics: Why States Rise and Fall, Princeton: Princeton University Press. Turchin, P (2008) Arise ‘cliodynamics.’ Nature, 454, 34–35. Turchin, P (2013) The puzzle of human ultrasociality. How did large-scale complex societies evolve? In P

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography Richerson and M Christiansen, eds., Cultural Evolution: Society, Technology, Language, and Religion, Cambridge, MA: MIT Press, 61–74. Turchin, P (2016) Ages of Discord, Chaplin: Beresta. Turchin, P, Brennan, R, Currie, T, . . . Whitehouse, H (2015) Seshat: The global history databank. Cliodynamics, 6, 77–107. Turchin, P, and Currie, T (2016) Cultural group selection is plausible, but the predictions of its hypotheses should be tested with real-world data. Behavioral and Brain Sciences, 39, 43–44. Turchin, P, Currie, TE, Turner, E, and Gavrilets, S (2013) War, space, and the evolution of Old World complex societies. Proceedings of the National Academy of Sciences, 110(41), 16384–16389. Turchin, P, Currie, TE, Whitehouse, H, and Spencer, C (2018) Quantitative historical analysis uncovers a single dimension of complexity that structures global variation in human social organization. Proceedings of the National Academy of Sciences, 115, E144-E151. Turchin, P, and Gavrilets, S (2009) Evolution of complex hierarchical societies. Social Evolution and History, 8, 167–198. Turchin, P, Hoyer, D, Korotayev, A, and Whitehouse, H (2021) Rise of the war machines: Charting the evolution of military technologies from the Neolithic to the Industrial Revolution. PLoS ONE, 16, e0258161. Turchin, P, and Nefedov, SA (2009) Secular Cycles, Princeton: Princeton University Press. Turchin, P, Whitehouse, H, François, P, and Xie, L (2020) An introduction to Seshat: Global History Databank. Journal of Cognitive Historiography, 5(1–2), 115–123. Turke, P (1988) Helpers at the nest: Childcare networks on Ifaluk. In L Betzig, M Borgerhoff Mulder, and P Turke, eds., Human Reproductive Behavior, Cambridge: Cambridge University Press, 173–188. Turke, PW, and Betzig, LL (1985) Those who can do: Wealth, status, and reproductive success on Ifaluk. Ethology and Sociobiology, 6(2), 79–87. Tushingham, S, and Bettinger, RL (2013) Why foragers choose acorns before salmon: Storage, mobility, and risk in aboriginal California. Journal of Anthropological Archaeology, 32(4), 527–537. Tushingham, S, and Bettinger, RL (2019) Storage defense: Expansive and intensive territorialism in hunter-gatherer delayed return economies. Quaternary International, 518, 21–30. Tybur, JM, Inbar, Y, Aarøe, L, . . . Žeželj, I. (2016) Parasite stress and pathogen avoidance relate to

507

distinct dimensions of political ideology across 30 nations. Proceedings of the National Academy of Sciences, 113(44), 12408–12413. Tybur, JM, Inbar, Y, Güler, E, and Molho, C (2015) Is the relationship between pathogen avoidance and ideological conservatism explained by sexual strategies? Evolution and Human Behavior, 36, 489–497. Tylor, EB (1871) Primitive Culture: Researches into the Development of Mythology, Philosophy, Religion, Art, and Custom, Vol. 2, London: John Murray. Tylor, EB (1889) On a method of investigating the development of institutions; Applied to laws of marriage and descent. The Journal of the Anthropological Institute of Great Britain and Ireland, 18, 245–272. Udehn, L (2002) The changing face of methodological individualism. Annual Review of Sociology, 28(1), 479–507. Uematsu, K, Kutsukake, M, Fukatsu, T, Shimada, M, and Shibao, H (2010) Altruistic colony defense by menopausal female insects. Current Biology, 20(13), 1182–1186. Uggla, C (in press) Contextual effects on fertility and mortality: Complementary contributions from demography and evolutionary life history theory. In O Burger, RD Lee, and R Sear, eds., Human Evolutionary Demography. https://osf.io/ud2vw. Uggla, C, and Mace, R (2016a) Local ecology influences reproductive timing in Northern Ireland independently of individual wealth. Behavioral Ecology, 27(1), 158–165. Uggla, C, and Mace, R (2016b) Parental investment in child health in sub-Saharan Africa: A cross-national study of health-seeking behaviour. Royal Society Open Science, 3, 150460. United Nations (2019) Department of Economic and Social Affairs, Population Division. Urassa, M, Lawson, DW, Wamoyi, J, . . . Placek, C (2021) Cross-cultural research must prioritize equitable collaboration. Nature Human Behaviour, 5(6), 668–671. Urlacher, SS, Blackwell, AD, Liebert, MA, . . . Sugiyama, LS (2016) Physical growth of the Shuar: Height, weight, and BMI references for an indigenous Amazonian population. American Journal of Human Biology, 28, 16–30. Urlacher, SS, and Kramer, KL (2018) Evidence for energetic tradeoffs between physical activity and childhood growth across the nutritional transition. Scientific Reports, 8, 369.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

508

Bibliography

Uskul, AK, Kitayama, S, and Nisbett, RE (2008) Ecocultural basis of cognition: Farmers and fishermen are more holistic than herders. Proceedings of the National Academy of Sciences, 105, 8552–8556. Usner, DH (1987) The frontier exchange economy of the lower Mississippi Valley in the eighteenth century. The William and Mary Quarterly, 44, 166–192. Uyeda, JC, Zenil-Ferguson, R, and Pennell, MW (2018) Rethinking phylogenetic comparative methods. Systematic Biology, 67, 1091–1109. Vainshtein, S (1980) Nomads of South Siberia: The Pastoral Economies of Tuva, Cambridge: Cambridge University Press. Valeggia, C, and Ellison, PT (2004) Lactational amenorrhoea in well-nourished Toba women of Formosa, Argentina. Journal of Biosocial Science, 36, 573–595. Valeggia, C, and Ellison, PT (2009) Interactions between metabolic and reproductive functions in the resumption of postpartum fecundity. American Journal of Human Biology, 21, 559–566. Valeggia, CR (2009) Flexible caretakers. Responses of Toba families in transition. In G Bentley and R Mace, eds., Substitute Parents Biological and Social Perspectives on Alloparenting in Human Societies, New York: Berghahn Press, 100–114. Valera, F, Hoi, H, and Schleicher, B (1997) Egg burial in penduline tits, Remiz pendulinus: Its role in mate desertion and female polyandry. Behavioral Ecology, 8(1), 20–27. Vallois, HV (1961) The social life of early man: The evidence of skeletons. In SL Washburn, ed., Social Life of Early Man, Chicago: Aldine Publishing Company, 214–235. van Anders, S, and Watson (2007) Testosterone levels in women and men who are single, in long-distance relationships, or same-city relationships. Hormones and Behavior, 51, 286–291. van de Rijt, A, Kang, S, Restivo, M, and Patil, K (2014) Field experiments of success-breeds-success dynamics. Proceedings of the National Academy of Sciences, 111, 6934–6939. van den Berghe, P (1979) Human Family Systems: An Evolutionary View, New York: Elsevier. van den Berghe, PL (1983) Human inbreeding avoidance: Culture in nature. Behavioral and Brain Sciences, 6(1), 91–102. van den Berghe, PL, and Barash, DP (1977) Inclusive fitness and human family structure. American Anthropologist, 79(4), 809–823.

van Noordwijk, MA, and van Schaik, CP (1999) The effects of dominance rank and group size on female lifetime reproductive success in wild long-tailed macaques, Macaca fascicularis. Primates, 40(1), 105–130. van Schaik, C, and Burkart, JM (2010) Mind the gap. Cooperative breeding and the evolution of our unique features. In PM Kappler and JB Silk, eds., Mind the Gap: Tracing the Origins of Human Universals , Germany: Springer, 477–496. van Schaik, CP (1989) The ecology of social relationships amongst female primates. In V Standen and RA Foley, eds., Comparative Socioecology. The Behavioural Ecology of Humans and Other Mammals, Oxford: Blackwell Scientific Publications, 195–218. van Schaik, CP, Ancrenaz, M, Borgen, G, . . . Merrill, M (2003) Orangutan Cultures and the Evolution of Material Culture. Science, 299(5603), 102–105. van Vugt, M, and Spisak, B (2008) Sex differences in leadership emergence in competitions within and between groups. Psychological Science, 19, 854–858. van Vugt, M, and Kurzban, R (2007) Cognitive and social adaptations for leadership and followership: Evolutionary game theory and group dynamics. In JP Forgas, MG Haselton, W von Hippel, eds., The Evolution of the Social Mind: Evolutionary Psychology and Social Cognition, New York: Psychology Press, 229–244 Varki, N, Anderson, D, Herndon, JG, . . . Else, JG (2009) Heart disease is common in humans and chimpanzees, but is caused by different pathological processes. Evolutionary Applications, 2, 101–112. Vaupel, JW (1997) The remarkable improvements in survival at older ages. Philosophical Transactions of the Royal Society of London B: Biological Sciences, 352(1363), 1799–1804. Vehrencamp, SL (1983a) A model for the evolution of despotic versus egalitarian societies. Animal Behaviour, 31(3), 667–682. Vehrencamp, SL (1983b) Optimal degree of skew in cooperative societies. American Zoologist, 23(2), 327–335. Velasquez-Manoff, M (2013) An Epidemic of Absence, New York: Scribner. Veller, C, Haig, D, and Nowak, MA (2016) The Trivers– Willard hypothesis: Sex ratio or investment? Proceedings of the Royal Society B: Biological Sciences, 283(1830), 20160126. Venkataraman, VV, Kraft, TS, Dominy, NJ, and Endicott, KM (2017) Hunter-gatherer residential mobility and

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography the marginal value of rainforest patches. Proceedings of the National Academy of Sciences, 114(12), 3097–3102. Verhagen, E, and Sauer, PJJ (2005) The Groningen Protocol – Euthanasia in severely ill newborns. New England Journal of Medicine, 352(10), 959–962. Vining, DR (1986) Social versus reproductive success: The central theoretical problem of human sociobiology. Behavioral and Brain Sciences, 9(1), 167–187. Virgo, S, and Sear, R (2016) Area-level mortality and morbidity predict ‘abortion proportion’ in England and Wales. Evolution and Human Behavior, 37(5), 366–375. Vitzthum, VJ (2009) The ecology and evolutionary endocrinology of reproduction in the human female. American Journal of Physical Anthropology, 140 (Suppl), 95–136. Vitzthum, VJ, Spielvogel, H, and Thornburg, J (2004) Interpopulational differences in progesterone levels during conception and implantation in humans. Proceedings of the National Academy of Sciences, 101, 1443–1448. Voland, E (1998) Evolutionary ecology of human reproduction. Annual Review of Anthropology, 27(1), 347–374. Voland, E (2000) Contributions of family reconstitution studies to evolutionary reproductive ecology. Evolutionary Anthropology, 9(3), 134–146. Voland, E, and Beise, J (2002) Opposite effects of maternal and paternal grandmothers on infant survival in historical Krummhörn. Behavioral Ecology and Sociobiology, 52, 435–443. Voland, E, and Dunbar, RI (1995) Resource competition and reproduction: The relationship between economic and parental strategies in the Krummhörn population (1720–1874). Human Nature, 6(1), 33–49. Volk, AA, Darrell-Cheng, C, and Marini, ZA (2010) Paternal care may influence perceptions of paternal resemblance. Evolutionary Psychology, 8(3), 147470491000800320. von Rohr, C, Koski, S, and Burkart, J (2012) Impartial third-party interventions in captive chimpanzees: A reflection of community concern. PLoS ONE, 7, e32494. von Rueden, C (2020) Making and unmaking egalitarianism in small-scale human societies. Current Opinion in Psychology, 33, 167–171. von Rueden, C (2022) Unmaking egalitarianism: Comparing sources of political change in an Amazonian society. Evolution and Human Behavior.

509

von Rueden, C, Alami, S, Kaplan, H, and Gurven, M (2018) Sex differences in political leadership in an egalitarian society. Evolution and Human Behavior, 39(4), 402–411. von Rueden, C, and Gurven, M (2012) When the strong punish: Why net costs of punishment are often negligible. Behavioral and Brain Sciences, 35(1), 43. von Rueden, C, Gurven, M, and Kaplan, H (2008) The multiple dimensions of male social status in an Amazonian society. Evolution and Human Behavior, 29(6), 402–415. von Rueden, C, Gurven, M, and Kaplan, H (2011) Why do men seek status? Fitness payoffs to dominance and prestige. Proceedings of the Royal Society B: Biological Sciences, 278, 2223–2232. von Rueden, C, Gurven, M, Kaplan, H, and Stieglitz, J (2014a) Leadership in an egalitarian society. Human Nature, 25(4), 538–566. von Rueden, C, and Jaeggi, AV (2016) Men’s status and reproductive success in 33 nonindustrial societies: Effects of subsistence, marriage system, and reproductive strategy. Proceedings of the National Academy of Sciences, 113(39), 10824–10829. von Rueden, C, Redhead, D, O’Gorman, R, Kaplan, H, and Gurven, M (2019) The dynamics of men’s cooperation and social status in a small-scale society. Proceedings of the Royal Society B: Biological Sciences, 286, 20191367. von Rueden, C, Trumble, B, and Emery Thompson, M (2014b) Political influence associates with cortisol and health among egalitarian forager-farmers. Evolution, Medicine, and Public Health, 2014, 122–133. von Rueden, C, and van Vugt, M (2015) Leadership in small-scale societies: Some implications for theory, research, and practice. Leadership Quarterly, 26(6), 978–990. Wade, M (1976) Group selection among laboratory populations of tribolium. Proceedings of the National Academy of Sciences, 73(12), 4604–4607. Wade, MJ (1980) Kin selection – Its components. Science, 210(4470), 665–667. Wade, MJ, and Shuster, SM (2002) The evolution of parental care in the context of sexual selection: A critical reassessment of parental investment theory. The American Naturalist, 160(3), 285–292. Wadley, L (2010) Were snares and traps used in the Middle Stone Age and does it matter? A review and a case study from Sibudu, South Africa. Journal of Human Evolution, 58(2), 179–192.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

510

Bibliography

Wagner, GP, and Altenberg, L (1996) Perspective: Complex adaptations and the evolution of evolvability. Evolution, 50(3), 967–976. Walasek, L, and Brown, G (2015) Income inequality and status seeking: Searching for positional goods in unequal U.S. states. Psychological Science, 26, 527–533. Walker, JH (2018) Island, River, and Field: Landscape Archaeology in the Llanos de Mojos, Albuquerque: University of New Mexico Press. Walker, ML, and Herndon, JG (2008) Menopause in nonhuman primates? Biology of Reproduction, 79(3), 398–406. Walker, R, and Bailey, D (2013) Body counts in lowland South American violence. Evolution and Human Behavior, 34, 29–34. Walker, R, Gurven, M, Hill, K, . . . Kaplan, HS (2006) Growth rates and life histories in twenty-two smallscale societies. American Journal of Human Biology, 18, 295–311. Walker, R, Hill, K, Kaplan, H, and McMillan, G (2002) Age-dependency in skill, strength and hunting ability among the Ache of eastern Paraguay. Journal of Human Evolution, 42, 639–657. Walker, RS, and Bailey, DH (2014) Marrying kin in small-scale societies. American Journal of Human Biology, 26(3), 384–388. Walker, RS, Flinn, MV, and Hill, KR (2010) Evolutionary history of partible paternity in lowland South America. Proceedings of the National Academy of Sciences, 107(45), 19195–19200. Walker, RS, Hill, KR, Flinn, MV, Ellsworth, RM (2011) Evolutionary history of hunter-gatherer marriage practices. PLoS ONE, 6, e19066. Walter, A, and Buyske, S (2003) The Westermarck effect and early childhood co-socialization: Sex differences in inbreeding-avoidance. British Journal of Developmental Psychology, 21(3), 353–365. Walter, K, Conroy-Beam, D, and Buss, D (2020) Sex differences in mate preferences across 45 countries: A large-scale replication. Psychological Science, 31, 408–423. Wamani, H, Astrøm, AN, Peterson, S, Tumwine, JK, and Tylleskär, T (2007) Boys are more stunted than girls in sub-Saharan Africa: A meta-analysis of 16 demographic and health surveys. BMC Pediatrics, 7(1), 17. Wander, K, and Mattison, SM (2013) The evolutionary ecology of early weaning in Kilimanjaro, Tanzania. Proceedings of the Royal Society B: Biological Sciences, 280(1768), 20131359.

Wardle, J, and Steptoe, A (2003) Socioeconomic differences in attitudes and beliefs about healthy lifestyles. Journal of Epidemiology & Community Health, 57(6), 440–443. Waring, TM, Kline, MA, Brooks, JS, Goff, SH, Gowdy, J, Janssen, MA, Smaldino, PE, Jacquet, J (2015) A multilevel evolutionary framework for sustainability analysis. Ecology and Society, 20, 2. Warneken, F (2018) How children solve the two challenges of cooperation. Annual Review of Psychology, 69, 205–229. Washburn, S, and Lancaster, C (1968) The evolution of hunting. In RB Lee and I deVore, eds., Man the Hunter, Chicago: Aldine Publishing Co, 293–303. Washburn, SL (1959) Speculations on the interrelations of the history of tools and biological evolution. Human Biology, 31, 21–31. Watkins, C, and Jones, B (2016) Competition-related factors directly influence preferences for facial cues of dominance in allies. Behavioral Ecology and Sociobiology, 70, 2071–2079. Watts, D (1994) Agonistic relationships between female mountain gorillas (Gorilla gorilla beringei). Behavioral Ecology and Sociobiology, 34, 347–358. Waynforth, D, and Dunbar, RIM (1995) Conditional mate choice strategies in humans: Evidence from ‘Lonely Hearts’ advertisements. Behaviour, 132(9/10), 755–779. Webster, D (1975) Warfare and the evolution of the state: A reconsideration. American Antiquity, 40(4), 464–470. Weibull, JW (1997) Evolutionary Game Theory, Cambridge, MA: MIT Press. Weigel, RM, and Weigel, MM (1987) Demographic factors affecting the fitness of polyandry for human males: A mathematical model and computer simulation. Ethology and Sociobiology, 8(2), 93–133. Weir, L, Grant, J, and Hutchings, J (2011) The influence of operational sex ratio on the intensity of competition for mates. American Naturalist, 177, 167–176. Weisner, T, and Gallimore, R (1977) My brother’s keeper: Child and sibling caretaking. Current Anthropology, 18, 169–190. Weiss, KM (1981) Evolutionary perspectives on human aging. In P Amoss and S Harrell, eds., Other Ways of Growing Old, Stanford: University Press, 25–58. Welcker, J, Steen, H, Harding, AMA, and Gabrielsen, GW (2009) Sex-specific provisioning behaviour in a monomorphic seabird with a bimodal foraging strategy. Ibis, 151(3), 502–513.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography Wells, JCK (2000) Natural selection and sex differences in morbidity and mortality in early life. Journal of Theoretical Biology, 202, 65–76. Wells, JCK (2007) The thrifty phenotype as an adaptive maternal effect. Biological Reviews, 82, 143–172. Wells, JCK (2012) Ecological volatility and human evolution: A novel perspective on life history and reproductive strategy. Evolutionary Anthropology, 21(6), 277–288. Wengrow, D, and Graeber, D (2015) Farewell to the ‘childhood of man’: Seasonality, and the origins of inequality. Journal of the Royal Anthropological Institute, 21, 597–619. Werner, D (1981) Gerontocracy among the Mekranoti of central Brazil. Anthropological Quarterly, 54, 15–27. Werner, D (1984) Child care and influence among the Mekranoti of central Brazil. Sex Roles, 10, 395–404. Wertz, AE, and Wynn, K (2014) Selective social learning of plant edibility in 6-and 18-month-old infants. Psychological Science, 25, 874–882. West, S, El Mouden, C, and Gardner, A (2011) Sixteen common misconceptions about the evolution of cooperation in humans. Evolution and Human Behavior, 32, 231–262. West, SA, Griffin, AS, and Gardner, A (2007) Social semantics: Altruism, cooperation, mutualism, strong reciprocity and group selection. Journal of Evolutionary Biology, 20, 415–432. West, SA, Pen, I, and Griffin, AS (2002) Cooperation and competition between relatives. Science, 296, 72–75. Westbrook, R (ed.) (2003) A History of Ancient Near Eastern Law, Vol. 1, Leiden: Brill. Westermarck, E (1891) The History of Human Marriage, Vol. 3, London and New York: Macmillan. Westermarck, E (1936) The Future of Marriage in Western Civilisation, Vol. 59, London: Macmillan. Westreich, D, Edwards, JK, and van Smeden, M (2021) Comment on Williamson et al.: The table 2 fallacy in a study of COVID-19 mortality risk factors. Epidemiology, 32(1), e1. Westreich, D, and Greenland, S (2013) The Table 2 fallacy: Presenting and interpreting confounder and modifier coefficients. American Journal of Epidemiology, 177(4), 292–298. White, DR, Burton, ML, and Whiting, JWM (1986) Form and frequency of polygyny: Standard sample codes. World Cultures, 2(1). White, IM (1972) Hunting dogs at Yalata. Mankind, 8(3), 201–205. Whitehouse, H, François, P, Savage, PE, . . . Turchin, P (2019) Retracted article: Complex societies precede

511

moralizing gods throughout world history. Nature, 568(7751), 226–229. Whitehouse, H, François, P, Savage, PE, . . . Turchin, P (2021) Retraction Note: Complex societies precede moralizing gods throughout world history. Nature, 595(7866), 320–320. Whiten, A., McGuigan, N., Marshall-Pescini, S. and Hopper, LM. (2009) Emulation, imitation, overimitation and the scope of culture for child and chimpanzee. Philosophical Transactions of the Royal Society B: Biological Sciences, 364(1528), 2417–2428. Whiten, A (2019) Cultural evolution in animals. Annual Review of Ecology, Evolution, and Systematics, 50, 27–48. Whiten, A, Spiteri, A, Horner, V, . . . de Waal, FBM (2007) Transmission of multiple traditions within and between chimpanzee groups. Current Biology, 17, 1038–1043. Whiting, BB, and Edwards, CP (1988) Children of Different Worlds. The Formation of Social Behavior, Cambridge, MA: Harvard University Press. Whitney, BS, Dickau, R, Mayle, FE, Soto, JD, and Iriarte, J (2013) Pre-Columbian landscape impact and agriculture in the monumental mound region of the Llanos de Moxos, lowland Bolivia. Quaternary Research, 80(2), 207–217. Wiessner, P (1996) Leveling the hunter: Constraints on the status quest in foraging societies. In P Wiessner and W Schiefenhovel, eds., Food and the Status Quest: An Interdisciplinary Perspective, Providence: Berghahn Books, 171–192. Wiessner, P (2002) Hunting, healing, and hxaro exchange: A long-term perspective on! Kung (Ju/ ’hoansi) large-game hunting. Evolution and Human Behavior, 23(6), 407–436. Wiessner, P (2005) Norm enforcement among the Ju/ ’hoansi Bushmen: A case of strong reciprocity? Human Nature, 16, 115–145. Wiessner, P (2009) Parent-offspring conflict in marriage: Implications for social evolution and material culture among the Ju/’hoansi Bushmen. In S Shennan, ed., Patterns and Process in Cultural Evolution. Origins of Human Behavior and Culture, Berkeley: University of California Press, 251–263. Wiessner, P (2010) The power of one? Big men revisited. In KJ Vaughn, JW Eerkens, and J Kantner, eds., The Evolution of Leadership: Transitions in Decision-Making from Small-Scale to Middle-Range Societies, Santa Fe: SAR Press, 195–222.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

512

Bibliography

Wiessner, PW (2014) Embers of society: Firelight talk among the Ju/’hoansi Bushmen. Proceedings of the National Academy of Sciences, 111(39), 14027–14035. Wigner, E (1960) The unreasonable effectiveness of mathematics in the natural sciences. Communications in Pure and Applied Mathematics, 13, 1–14. Wikberg, EC, Jack, KM, Fedigan, LM, . . . Kawamura, S (2017) Inbreeding avoidance and female mate choice shape reproductive skew in capuchin monkeys (Cebus Capucinus imitator). Molecular Ecology, 26 (2), 653–667. Wilke, A, and Barrett, HC (2009) The hot hand phenomenon as a cognitive adaptation to clumped resources. Evolution and Human Behavior, 30(3), 161–169. Wilke, A, Lydick, J, Bedell, V, . . . Langen, TA (2018) Spatial dependency in local resource distributions. Evolutionary Behavioral Sciences, 12(3), 163. Wilke, A, Scheibehenne, B, Gaissmaier, W, McCanney, P, and Barrett, HC (2014) Illusionary pattern detection in habitual gamblers. Evolution and Human Behavior, 35(4), 291–297. Wilkie, DS, and Curran, B (1991) Why do Mbuti hunters use nets? Ungulate hunting efficiency of archers and net-hunters in the Ituri rain forest. American Anthropologist, 93(3), 680–689. Willems, EP, and Schaik, CP (2015) Collective action and the intensity of between-group competition in nonhuman primates. Behavioral Ecology, 26(2), 625–631. Willer, R (2009) Groups reward individual sacrifice: The status solution to the collective action problem. American Sociological Review, 74, 23–43. Williams, AN, Veth, P, Steffen, W, . . . Smith, M (2015) A continental narrative: Human settlement patterns and Australian climate change over the last 35,000 years. Quaternary Science Reviews, 123, 91–112. Williams, GC (1966a) Natural selection, the costs of reproduction, and a refinement of Lack’s principle. American Naturalist, 100(916), 687–690. Williams, GC (1966b) Adaptation and Natural Selection, Vol. 75, Princeton: Princeton University Press. Williams, GC (1957) Pleitropy, natural selection and the evolution of senescence. Evolution, 11, 398–411. Wilson, D (1975a) Theory of group selection. Proceedings of the National Academy of Sciences, 72(1), 143–146.

Wilson, D, and Dugatkin, L (1997) Group selection and assortative interactions. American Naturalist, 149 (2), 336–351. Wilson, DS, and Sober, E (1994) Reintroducing group selection to the human behavioral sciences. Behavioral and Brain Sciences, 17(4), 585–608. Wilson, DS, and Wilson, EO (2007) Rethinking the theoretical foundation of sociobiology. Quarterly Review of Biology, 82(4), 327–348. Wilson, EO (1975b) Some central problems of sociobiology. Social Sciences Information, Biology and Social Life, 14, 5–18. Wilson, EO (1978) On Human Nature, Cambridge, MA: Harvard University Press. Wilson, K, and Codding, B (2020) The marginal utility of inequality: A global examination across ethnographic societies. Human Nature, 31(4), 361–386. Wilson, M, and Daly, M (1995) The man who mistook his wife for a chattel. In J Tooby, L Cosmides, and J Barkow, eds., The Adapted Mind: Evolutionary Psychology and the Generation of Culture, Oxford: Oxford University Press, 289–322. Wilson, M, and Daly, M (1997) Life expectancy, economic inequality, homicide, and reproductive timing in Chicago neighbourhoods. BMJ, 314, 1271. Wilson, M, Miller, C, and Crouse, K (2017) Humans as a model species for sexual selection research. Proceedings of the Royal Society B: Biological Sciences, 284, 20171320. Wilson, ML, and Wrangham, RW (2003) Intergroup relations in chimpanzees. Annual Review of Anthropology, 32, 363–392. Wilson, MN (1986) The Black extended family: An analytical consideration. Developmental Psychology, 22(2), 246–258. Winegard, B, Winegard, B, and Geary, D (2018) The status competition model of cultural production. Evolutionary Psychological Science, 4, 351–371. Wingfield, JC, Hegner, RE, Dufty, AM, and Ball, GF (1990) The “challenge hypothesis’’: Theoretical implications for patterns of testosterone secretion, mating systems, and breeding strategies. American Naturalist, 136, 829–846. Winking, J, Eastwick, PW, Smith, LK, and Koster, J (2018) Applicability of the investment model scale in a natural-fertility population. Personal Relationships, 25(4), 497–516. Winking, J, Kaplan, H, Gurven, M, and Rucas, S (2007) Why do men marry and why do they stray? Proceedings of the Royal Society B: Biological Sciences, 274, 1643–1649.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography Winking, J, and Koster, J (2021) Timing, initiators, and causes of divorce in a Mayangna/Miskito community in Nicaragua. Social Sciences, 10(6), 212. Winking, J, Stieglitz, J, Kurten, J, Kaplan, H, and Gurven, M (2013) Polygyny among the Tsimane of Bolivia: An improved method for testing the polygyny–fertility hypothesis. Proceedings of the Royal Society B: Biological Sciences, 280(1756), 20123078. Winterhalder, B (1981) Foraging strategies in the boreal environment: An analysis of Cree hunting and gathering. In B Winterhalder and EA Smith, eds., Hunter-Gatherer Foraging Strategies, Chicago: University of Chicago Press, 66–98. Winterhalder, B (1986a) Diet choice, risk, and food sharing in a stochastic environment. Journal of Anthropological Archaeology, 5, 369–392. Winterhalder, B (1986b) Optimal foraging: Simulation studies of diet choice in a stochastic environment. Journal of Ethnobiology, 6, 205–223. Winterhalder, B (1997) Gifts given, gifts taken: The behavioral ecology of nonmarket, intragroup exchange. Journal of Archaeological Research, 5(2), 121–168. Winterhalder, B (2001) The behavioural ecology of hunter gatherers. In C Panter-Brick, PA Layton, and PA Rowley-Conway, eds., Hunter-Gatherers: An Interdisciplinary Perspective, Cambridge: Cambridge University Press, 12–38. Winterhalder, B, and Goland, C (1997) An evolutionary ecology perspective on diet choice, risk, and plant domestication. In KJ Gremillion, ed., Peoples, Plants, and Landscapes: Studies in Ethnobotany, Tuscaloosa: University of Alabama Press, 123–160. Winterhalder, B, and Kennett, D (2006) Behavioral ecology and the transition from hunting and gathering to agriculture. In D Kennett and B Winterhalder, eds., Behavioral Ecology of the Transition to Agriculture, Berkeley: University of California Press, 1–21. Winterhalder, B, and Kennett, DJ (2009) Four neglected concepts with a role to play in explaining the origins of agriculture. Current Anthropology, 50(5), 645–648. Winterhalder, B, Kennett, DJ, Grote, MN, and Bartruff, J (2010) Ideal free settlement of California’s northern Channel Islands. Journal of Anthropological Archaeology, 29(4), 469–490. Winterhalder, B, Lu, F, and Tucker, B (1999) Risk-sensitive adaptive tactics: Models and evidence from

513

subsistence studies in biology and anthropology. Journal of Archaeological Research, 7, 301–348. Winterhalder, B, and Smith, EA (1981) Hunter-Gatherer Foraging Strategies: Ethnographic and Archeological Analyses, Chicago: University of Chicago Press. Winterhalder, B, and Smith, EA (2000) Analyzing adaptive strategies: Human behavioral ecology at twenty-five. Evolutionary Anthropology, 9(2), 51–72. Winterhalder, BP, and Puleston, CO (2018) The exchequer’s guide to population ecology and resource exploitation in the agrarian state. Cliodynamics, 9(2), 1–10. Witkower, Z, Tracy, J, Cheng, J, and Henrich, J (2019) Two signals of social rank: Prestige and dominance are associated with distinct nonverbal displays. Journal of Personality and Social Psychology, 118, 89–120. Wittemyer, G, Douglas-Hamilton, I, and Getz, WM (2005) The socioecology of elephants: Analysis of the processes creating multitiered social structures. Animal Behaviour, 69(6), 1357–1371. Wohlforth, W, and Kang, D (2009) Hypotheses on status competition. APSA 2009 Toronto Meeting Paper, Available at: https://ssrn.com/abstract=1450467 Wolf, AP (1970) Childhood association and sexual attraction: A further test of the Westermarck hypothesis. American Anthropologist, 72(3), 503–515. Wolf, AP (1985) Sexual Attraction and Childhood Association: A Chinese Brief for Edward Westermarck, Stanford: Stanford University Press. Wolf, M, van Doorn, GS, Leimar, O, and Weissing, FJ (2007) Life-history trade-offs favour the evolution of animal personalities. Nature, 447, 581–584. Wood, B, and Hill, K (2000) A test of the “showing-off” hypothesis with Ache hunters. Current Anthropology, 41, 124–125. Wood, BM, and Marlowe, FW (2011) Dynamics of postmarital residence among the Hadza: A kin investment model. Human Nature, 22(1–2), 128–138. Wood, BM, and Marlowe, FW (2013) Household and kin provisioning by Hadza men. Human Nature, 24(3), 280–317. Wood, BM, and Marlowe, FW (2014) Toward a realitybased understanding of Hadza men’s work. Human Nature, 25(4), 620–630. Wood, BM, Pontzer, H, Raichlen, DA, and Marlowe, FW (2014) Mutualism and manipulation in Hadza– honeyguide interactions. Evolution and Human Behavior, 35(6), 540–546.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

514

Bibliography

Wood, JW (1994) Dynamics of Human Reproduction: Biology, Biometry, Demography, New York: Routledge. Wood, JW, Holman, DJ, Connor, O, A., K, and Ferrell, RJ (2002) Mortality models for paleodemography. In RD Hoppa and JW Vaupel, eds., Paleodemography: Age Distributions from Skeletal Samples, Cambridge: Cambridge University Press, 129–168. Woodburn, J (1968) An introduction to Hadza ecology. In L Lee and I DeVore, eds., Man the Hunter, Chicago: Aldine, 49–55. Woodburn, J (1982) Egalitarian societies. Man, 17(3), 431–451. Woodburn, J (1986) Stability and flexibility in Hadza residential groupings. In RB Lee and I deVore, eds., Man the Hunter, Chicago: Aldine Publishing Co, 103–110. Woods, C, ed. (2010) The Earliest Mesopotamian Writing, Chicago: Oriental Institute of the University of Chicago. Woolfenden, GE, and Fitzpatrick, JW (1984) The Florida Scrub Jay. Demography of a Cooperative Breeding Bird, Princeton: Princeton University Press. Wrangham, R (1980) An ecological model of femalebonded primate groups. Behaviour, 75, 262–300. Wrangham, R (2009) Catching Fire: How Cooking Made Us Human, New York: Basic Books. Wrangham, R (2019) The Goodness Paradox: The Strange Relationship between Virtue and Violence in Human Evolution, New York: Pantheon. Wrangham, R, and Peterson, D (1996) Demonic Males: Apes and the Origins of Human Violence, Boston: Houghton Mifflin. Wrangham, RW (1987) The significance of African apes for reconstructuring human social evolution. In WG Kinzey, ed., The Evolution of Human Behavior: Primate Models, New York: State University of New York Press, 51–71. Wright, HT (1977) Recent research on the origin of the state. Annual Review of Anthropology, 6(1), 379–397. Wright, HT (2018) The problem of states: The state of the problem. In J Sabloff and P Sabloff, eds., The Emergence of Premodern States: New Perspectives on the Development of Complex Societies, Santa Fe: SFI Press, 15–32. Wright, S (1922) Coefficients of inbreeding and relationship. American Naturalist, 56, 330–338. Wu, H, Yang, S, Sun, S, Liu, C, and Luo, Y-J (2013) The male advantage in child facial resemblance detection: Behavioral and ERP evidence. Social Neuroscience, 8(6), 555–567.

Wu, Q (2016) Sibship size and children’s family resources: Findings from a nationally representative survey in China. The Journal of Early Adolescence, 36, 575–594. Wynne-Edwards, V (1962) Animal Dispersion in Relation to Social Behaviour, London: Oliver and Boyd. Wyshak, G, and Frisch, RE (1982) Evidence for a secular trend in age of menarche. New England Journal of Medicine, 306, 1033–1035. Xygalatas, D, Mano, P, and Bahna, V (2021) Social inequality and signaling in a costly ritual. Evolution and Human Behavior, 42, 524–533. Yalman, N (1967) Under the Bo Tree: Studies in Caste, Kinship and Marriage in the Interior of Ceylon, Berkeley: University of California Press. Yamagishi, T (1986) The provision of a sanctioning system as a public good. Journal of Personality and Social Psychology, 51, 110–116. Yanca, C, and Low, B (2004) Female allies and female power: A cross-cultural analysis. Evolution and Human Behavior, 25, 9–23. Yapa, L (1993) What are improved seeds? An epistemology of the green revolution. Economic Geography, 69(3), 254–273. Yaworsky, PM, and Codding, BF (2018) The ideal distribution of farmers: Explaining the Euro-American settlement of Utah. American Antiquity, 83(1), 75–90. Ydenberg, RC (2007) Provisioning. In DW Stephens, JS Brown, and RC Ydenberg, eds., Foraging: Behavior and Ecology, Chicago: University of Chicago Press, 273–303. Yehuda, R, Engel, SM, Brand, SR, Seckl, J, Marcus, SM, and Berkowitz, G.S. (2005) Transgenerational effects of posttraumatic stress disorder in babies of mothers exposed to the World Trade Center attacks during pregnancy. Journal of Clinical Endocrinology and Metabolism, 90, 4115–4118. Yehuda, R, Teicher, MH, Seckl, GR a, JR, Morris, A, and Bierer, LM (2007) Parental posttraumatic stress disorder as a vulnerability factor for low cortisol trait in offspring of holocaust survivors. JAMA Psychiatry, 64, 1040–1048. Yellen, J, and Harpending, H (1972) Hunter-gatherer populations and archaeological inference. World Archaeology, 4(2), 244–253. Yellen, JE (1990) The transformation of the Kalahari ! Kung. Scientific American, 262(4), 96–105. Young, C, Schülke, O, and Ostner, J (2014) How males form coalitions against group rivals and the Pandit/

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Bibliography van Schaik coalition model. Behaviour, 151, 907–934. Young, SL, Boateng, GO, Jamaluddine, Z, . . . Stoler, J (2019) The Household Water InSecurity Experiences (HWISE) Scale: Development and validation of a household water insecurity measure for low-income and middle-income countries. BMJ Global Health, 4(5), e001750. Yu, Q, Zhang, Q, Chen, J, Jin, S, Qiao, Y, and Cai, W (2016) The effect of perceived parent-child facial resemblance on parents’ trait anxiety: The moderating effect of parents’ gender. Frontiers in Psychology, 7, 658. Yu, Q, Zhang, Q, Jin, S, Chen, J, Shi, Y, and Li, Y (2017) The effect of perceived facial resemblance on parentchild relationship. Personality and Individual Differences, 116, 359–365. Yu, Q, Zhang, Q, Xiong, Q, Jin, S, Zou, H, and Guo, Y (2019) The more similar, the more warmth: The effect of parent-child perceived facial resemblance on parenting behavior. Personality and Individual Differences, 138, 358–362. Zahavi, A (1975) Mate selection – A selection for a handicap. Journal of Theoretical Biology, 53, 205–214. Zahavi, A (1995) Altruism as a handicap: The limitations of kin selection and reciprocity. Journal of Avian Biology, 26(1), 1–3. Zahavi, A, and Zahavi, A (1999) The Handicap Principle: A Missing Piece of Darwin’s Puzzle, Oxford: Oxford University Press. Zeanah, DW, Codding, BF, Bird, DW, Bliege Bird, R, and Veth, PM (2015) Diesel and damper: Changes in seed use and mobility patterns following contact amongst the Martu of Western Australia. Journal of Anthropological Archaeology, 39, 51–62. Zeanah, DW, Codding, BF, Bird, RB, and Bird, DW (2017) Mosaics of fire and water: The co-emergence of anthropogenic landscapes and intensive seed exploitation in the Australian arid zone. Australian Archaeology, 83(1–2), 2–19. Zefferman, MR, and Mathew, S (2015) An evolutionary theory of large-scale human warfare: Groupstructured cultural selection. Evolutionary Anthropology, 24(2), 50–61.

515

Zeh, JA, and Zeh, DW (2001) Reproductive mode and the genetic benefits of polyandry. Animal Behaviour, 61(6), 1051–1063. Zemach, A, and Zilberman, D (2010) Evolution of eukaryotic DNA methylation and the pursuit of safer sex. Current Biology, 20, R780–R785. Zeng, T, Aw, A, and Feldman, M (2018) Cultural hitchhiking and competition between patrilineal kin groups explain the post-Neolithic Y-chromosome bottleneck. Nature Communications, 9, 2077. Zeng, TC, Cheng, JT, and Henrich, J (2022) Dominance in humans. Philosophical Transactions of the Royal Society B: Biological Sciences, 377(1845), 20200451. Zhou, L, Ge, E, Micheletti, AJ, Chen, Y, Du, J, and Mace, R (2022) Monks relax sibling competition over parental resources in Tibetan populations. Behavioral Ecology, 33(6), 1070–1079. Zietsch, BP, and Sidari, MJ (2020) A critique of life history approaches to human trait covariation. Evolution and Human Behavior, 6, 527–535. Zijdeman, R, Ribeira da Silva, F,(2015) Life expectancy at birth (total), IISH Dataverse, http://hdl.handle.net/ 10622/LKYT53 Ziker, J (2007) Subsistence and food sharing in Northern Siberia: Social and nutritional ecology of the Dolgan and the Nganasan. Ecology of Food and Nutrition, 46, 445–467. Ziker, J, Rasmussen, J, and Nolin, D (2016) Indigenous Siberians solve collective action problems through sharing and traditional knowledge. Sustainability Science, 11(1), 45–55. Ziker, J, and Schnegg, M (2005) Food sharing at meals: Kinship, reciprocity, and clustering in the Taimyr Autonomous Okrug, Northern Russia. Human Nature, 16, 178–211. Zilioli, S, and Watson, N (2014) Testosterone across successive competitions: Evidence for a “winner effect” in humans? Psychoneuroendocrinology, 47, 1–9. Ziomkiewicz, A, Sancilio, A, Galbarczyk, A, Klimek, M, Jasienska, G, and Bribiescas, RG (2016) Evidence for the cost of reproduction in humans: High lifetime reproductive effort is associated with greater oxidative stress in post-menopausal women. PLoS ONE, 11(1), e0145753.

https://doi.org/10.1017/9781108377911.019 Published online by Cambridge University Press

Index

!Kung, 15, 26, 27, 34, 46 Aché, 46, 111, 113, 141, 301, 312 life history, 26–27 provisioning of offspring, 144 adaptation, 5 psychological, 382–385 adult sex ratio (ASR), 212–213 agriculture, 76, 77, 175, 180, 191 intensification, 84, 94–97 origins of, xiii, 76, 90–91 Agta, 27, 111, 113, 128, 146 Aka, 27, 113, 140, 286 allocare, 289, 290, 294, 296 Allee effect, 64, 186 alliances, 159, 233 allocare, 10, 137, 148, 265, 288, 289, 290, 294, 296 anisogamy, 203, 204–206 applied evolutionary anthropology, 8, 103, 400 archaeology, 3, 55, 61, 68, 74, 129, 304, 359 Bateman, Angus J., 203–204, 206 Bateman gradient, 203 Bateman’s principles, 253 behavioral ecology, xi–xii, 3 behavioral economics, xiii behavioral flexibility, 2, 15, 48, 406 biological market theory, 119–120, 208 biparental care, 20, 139, 168, 231, 260, 284 birth order, 269–273 bonobo, 20, 160, 161, 168, 171, 215 breastfeeding, 265, 276, 338 bride service, 253, 254 brideprice, 80, 100, 214, 252–253, 254 Cebu Longitudinal Health and Nutrition Survey, 335 celibacy, 248–249 Challenge Hypothesis, 158, 343

cheating, 107, 110, 386–388 chimpanzee, 104, 125, 161, 168, 174, 215, 270, 314 disease, 37 life history, 20, 21, 30, 31, 47 reproductive value, 34 circumscription, 186, 198 coalitions, 159–160, 193 collective action, xiii, 84, 100, 105, 120, 148, 149, 178 leadership, 194–196 problems of, 130, 149 collider bias, 414, 417 commensurability, 87–88 communal breeding, 285, 286 competition, 63, 155, 196–198 female-female, 211–214 sexual selection and, 210–215 competitive altruism, 118 conditional strategies, 4–5, 208, 405 confounder, 24, 295, 326, 354, 403, 415, 417, See omitted variable bias constraints, 2, 12, 51, 55, 73, 87, 132, 135, 287, 334 intrinsic vs extrinsic, 6 cooperation, 6–7, 13, 64, 100, 104–129 psychology of, 386–388 cooperative breeding, 44, 289 and division of labor, 137–138 defined, 283–306 evolution of, 301–304 in humans, 286 in non-human species, 284, 288–289 costly signaling, 118–119, 146, 150–151, 152, 161, 386 cuckoldry, 221–224, 268, 277 cultural ecology, xi, 2–3, 86 cultural group selection, 126–127, 362–363 cultural inheritance. See cultural transmission cultural transmission, 2, 255, 315, 361, 391

https://doi.org/10.1017/9781108377911.020 Published online by Cambridge University Press

cumulative culture, 2, 45–46, 127, 163, 357–358 currency, 5, 46, 54, 72, 87, See also commensurability DAG. See directed acyclic graphs Darwin, Charles, 3, 21, 203, 238, 399 sexual selection and, 203, 207, 388 demographic transition, 269, 318–319, 372–373 and allocare, 304–306 diet breadth model, 51, 73, 133 directed acyclic graphs, 414 representing the data generating process, 414, 417 discounting, 41, 62, 89, 99, 391 dispersal, 12, 186, 249–252, 321–327 division of labor age-based, 135–136 and cooperative breeding, 137–138 and limitations of size and strength, 133 and limitations of skill and strength, 135 cooperative, 147–152 defined, 130, 132 in nonhumans, 138–139 sexual, 133–134, 138–142, 233, 266 divorce, 35, 212, 218–219, 408 dowry, 253–254, See indirect dowry dowry inflation, 7 dual inheritance theory, 18, 345, 350, 377, 395 dual mating hypothesis, 216–217 ecological anthropology, xi–xii economic defensibility, 184–189 economy of scale, 128, 132, 186 education, 164, 267–268, 372 egalitarianism, 175, 191–194 embodied capital, 144 human life history, 32–33

Index epigenetics, 345–347, 367, See extended evolutionary synthesis ethology, 3, 385 event history analysis, 331, 408 evolutionary medicine, 334 evolutionary psychology, 18, 208, 359, 381 and mating studies, 228–229 defined, 382 evolutionary theory, 1, 85, 321, 395 extended evolutionary synthesis, 101, 366, 395, 397 extra-pair copulations (EPCs), 232 extra-pair paternity (EPP), 221–224, 246 family planning, 46 fathers, 260–263, 284, 298, 326–327, 344 female choice, 207, 214, 234 fertility, 7, 10, 14, 176, 308, 315–321, 339, 350, 372, 403, 408, See reproductive success age-specific, 316 relation to lifespan, 38–39 filicide, 257–258 Fisher, Ronald A., 21 and sex ratios, 273 Fisher condition, 206 fishing, 61, 62, 67, 71, 115, 135, 142, 375, See foraging fitness, 5–6, 385 food sharing, 1, 98, 111–114, 301, 338 life history evolution and, 34–47 foragers. See hunter-gatherers foraging, xiii, 48–75, 82 and hormones, 354 marginal value theorem, 59, 392 psychology, 385, 392–395 foster parents, 279 free-rider problem, 130, 192, 373–374, See cheating game theory, 63, 108–110, 154, 182 gorilla, 174 grandmothers and allocare, 294, 295, 296–297 grandmother hypothesis, 29–32, 141, 303, 390 productivity, 300–301

group selection, 105, 121–129, 362, See cultural group selection Hadza, 27, 46, 111, 113, 133 allocare, 296 children’s foraging, 136, 407 mate choice, 209 men’s hunting, 295 Hamilton, W.D., 105, 290, 385 hawk-dove, 154, 184, 192–193, See game theory Himba, 335 adult sex ratio, 213 dual mating hypothesis, 223 extra-pair paternity, 221 female autonomy, 172 fosterage, 14, 215, 279 informal partnerships, 217, 218, 222–224 leadership, 172 mate choice, 209 horticulturalists, xiii, 26–27, 46, 78, 82, 180, 268, 377 hot hand phenomenon, 393, 396–397 Human Adaptive Complex, 20 human behavioral ecology, 359, 381 data collection, 324–329 description of, 1 future of, 18–19 methods of analysis, 201–202, 329, 417–418 human universals, 231–232, 237, 356, 409 hunter-gatherers, xiii, 3, 14, 45, 46, 81–82, 251 life history, 26–27 hunting, 73, 163, 342, See foraging cooperative, 36, 70, 105, 192 and division of labor, 139–152 with dogs, 56, 140 and life history evolution, 70, 141 by women, 139–140 goals of, 150–151, 344 hypothetico-deductive reasoning, xii, 8–10 ideal despotic distribution, 186 ideal free distribution, 15, 63–75, 186 incest taboo, 237–238

https://doi.org/10.1017/9781108377911.020 Published online by Cambridge University Press

517

inclusive fitness. See kin selection indirect dowry, 254 indirect reciprocity, 109, 119, 161, 386 inequality, xiii, 170, 178, 181, 183, 200 infanticide, 26, 214, 257 information, 73, 118, 132, 233, 360, 383, 396 inheritance, 233 of wealth, 189–191, 268, 323 institutions, 84, 100, 127, 183, 195, 362, 402, 405 interbirth intervals, 1, 22, 265, 317, 320 intergenerational transmission of wealth, 189–191, 266, See inheritance intersexual selection, 203 intrasexual selection, 203, 210–214 reproductive skew and, 211 jealousy cross-cultural variation in, 227 juveniles, 302 as helpers, 287, 288, 293, 294, 296, 297–298 productivity, 298 kin selection, 3, 12, 105–106, 122, 303, 362, 370 and cooperative breeding, 290–291 kinship, 2, 18, 115, 160, 233, 325–326, 377, 406 knowledge, 32, 48, 52, 71, 99, 135, 165, 315, 408, 415 Kunene Rural Health and Demography Project, 335 Lamalera, 69, 115–117 leader-follower game, 154, See game theory learning, xii, 20, 71, 102, See social learning life history evolution and, 36–37 life history theory, 3, 7, 70, 256–258, 303, 352–355, 390–392 defined, 20, 21–47 in harsh environments, 41–42 human uniqueness, 1, 20

518

Index

life history theory (cont.) pace of life, 390–391 physiology, 336–338 slow vs. fast, 37–38, 43, 310–314 trade-offs, 22–25, 339 immune function and, 41 reproduction and, 38–41 traits, 22 lifespan compared with other species, 30 human, 27–29 evolution of, 29 market integration, 6, 7, 17, 323–324, 345, 353, 396 markets, 84, 97–100, 396, See biological market theory failure of, 97 marriage, 2, 115, 160, 230–255 arranged, 234–236 consanguineous, 238–240 and endogamy, 238–240 and exogamy, 237–238, 240 functions of, 232–234 and mate choice, 217, 234–236 vs. mating, 230–231 vs. non-marital partnerships, 217–218 and number of spouses, 241–249 timing, 236–237 Martu, 61 children’s foraging, 133 hunting, 133–134, 151 initiation, 295 women’s hunting, 140 mate choice, 208 currencies, 208–210 mutual, 210 and partner type, 217–218 preferences, 216, 217 mate retention, 224–227 and jealousy, 226 physical mechanisms, 225–226 psychological mechanisms, 226 mating assortative, 210 guarding and, 225 multiple, 217, 219, 222–224 strategies, 216–217, 219 mating systems, xiii social vs. genetic, 219–220

matrilineality, 377 Matthew Effect, 162, 404–405, See status Mayangna/Miskito, 56–58, 71, 111, 112, 113, 299 menopause, 31, 285, 316, 345, See postreproductive lifespan methodological agnosticism, 4 methodological individualism, 2 methods, 8–14, 330, 351–352, 388–389, 407, 418 and sample selection, 335 Mikea, 81, 90, 113 Miskito. See Mayangna/Miskito mismatch, 5, 394 and maladaptation, 385 modularity, 382 and domain specificity, 383–384 monogamy, 160, 245–247, See pair bonding in birds, 219, 246 and cooperative breeding, 292 ecological, 246, 247 in mammals, 246 reproductive variance and, 206 serial, 215–216, 218–219 social, 246, 247 mortality, 16, 308, 309–315 child, 268–269, 311–312 extrinsic, 23–25, 268–269, 312–314 mothers, 32, 257, 265, 276, 285, 286, 289, 295 multilevel selection, 123–129, 362 mutualism, 102, 114–129 and cooperative breeding, 293 natural selection, 5, 7, 48, 85, 105, 319, 359, 364, 382 niche construction theory, 62, 101, 359, 370, 395–396, See extended evolutionary synthesis omitted variable bias, 408, 417, 418 open science, 412, 419 operational sex ratio, 148, 166, 204 optimal foraging theory, 3, 6, 85, 383, See foraging optimality, 142, 391

https://doi.org/10.1017/9781108377911.020 Published online by Cambridge University Press

pair bonding, 141, 230–231, 246 paleoanthropology, 15, 20, 29, 37, 68, 74, 141 parental care, xiii, 256–258 parental investment, 144, 269, 388–390 and division of labor, 139 effects of market integration, 7 overview, 204 sex-biased, 274–276 partner choice, 112, 118–120, 161, 193 partible paternity, 26, 221–224 pastoralists, xiii, 46, 66, 76, 80, 87, 175, 268, 373, 377 patch choice, 58–75 paternal investment hormones and, 344 and paternity certainty, 221–224 paternity certainty, 232, 258, 277–278, 295 patrilineality, 121, 377 phenotypic correlation, 24–25, 296 phenotypic gambit, 4, 333, 336, 345, 350, 369, 385, 397 phenotypic inertia, 346, 350, 354–355 philopatry, 160, 249–252 Pimbwe, 112, 245 plasticity, 17, 334–335, 371, 398 political organization, 125, 180–202, 363, 376–377 polyandry, 11–13, 222–224, 247–248 fraternal, 247–248 informal, 248 visiting husband, 248 polygyny, 7, 170, 175, 176, 206, 242–245, 253 and co-wife competition, 211–214 and female choice, 245 resource-defense, 244, 253 polygyny threshold model, 7, 9–19, 244 post-marital residence, 1, 249–252, 321–322, 323 ambilocal, 251 avunculocal, 250 bilocal, 251 matrilocal, 250–251 natalocal, 251 neolocal, 251

Index patrilocal, 250 uxorilocal, 250–251 virilocal, 250 postreproductive lifespan explanations for, 27–37 prey choice. See diet breadth model primatology, 1, 11, 15, 71, 124, 159, 173, 211, 238, 241, 293 pisoner’s dilemma, 108, 192–193, 386, See game theory reaction norms, 334–335, 392 reciprocity, xiii, 14, 107, 109, 370, 388 contingent, 112 reproduction, 7, 232 costs of, 339–343 reproductive skew, 174, 211 and cooperative breeding, 285 reproductive success, 18, 166, 175, 273, 308, 365, 403, 409, See fertility proxies of, 308 variance between the sexes and, 203 reproductive value, 33–47, 106, 170, 270, 323 risk, 55, 72, 84, 91–94 and division of labor, 140–152 scramble competition, 169 sex extra-marital, 168, 221 pre-marital, 220–221 sex differences, 389 study of, 229 sexual conflict, 210–215, 282 sexual dimorphism, 1, 168, 245, 292 sexual selection theory, 3, 166, 203, 210 challenges to, 7, 204–207

sexual strategies theory, 216 Shuar, 27 mate choice, 209 signaling, 132, 149–152, See costly signaling and illness, 353 social foraging, 68–70, See hunting social learning, 7, 46, 53, 348, 358–359, See cultural transmission biases, 367–368 social structure, 114, 124–125, 251 human uniqueness and, 1–2 and physiology, 354 sociobiology, xi, 356, 385 specialization, 10, 72, 114, 130, 132, 136, 247, 302, 359 Standard Cross-Cultural Sample (SCCS), 220, 234, 238, 242, 245, 247, 249, 250, 251, 252 status, 154, 192, 318, 368, 404 reproductive success and, 210–211 step-parents, 276–277 subsistence, xiii, 1, 55, 76–103, 266–267, 408 systems of, 180–181, 320, 377 Table 2 Fallacy, 413 temporal discounting. See discounting territoriality, 184–186 time allocation, 10, 18, 48, 72, 86, 89, 130, 132, 135, 140, 141, 144, 265, 267, 274, 293, 295, 298, 304, 338, 415 tolerated theft, 143, 386 transmitted culture, 4, 365, See cultural transmission Trivers, Robert, xii, 204, 385, 386 parental investment, 256, 388

https://doi.org/10.1017/9781108377911.020 Published online by Cambridge University Press

519

parent-offspring conflict, 133, 258, 259 reciprocal altruism, 106, 108, 386 sexual selection, 151, 166, 204–206, 234 Trivers-Willard hypothesis, 14, 273–274, 276 Tsimane, 27, 34, 40, 46, 335 adult sex ratio, 213 assortative mating, 148–152 coalition formation, 160 description of, 337 endocrinology, 344 energetics, 337–338 reproduction, 341 extramarital affairs, 148 fertility, 39, 337 gendered production, 149 hierarchy, 176–178 intimate partner violence, 215, 226 leadership, 164, 172, 176–178 life history, 21 locus of control, 42 men’s status, 162, 164–165 productivity, 90 social organization, 176–178, 187 women’s hunting, 140 women’s reproductive state, 342 Tsimane Health and Life History Project, 335 unilineal evolution, 230, 376 utility function, 72, 85, 142 Wason selection task, 387 WEIRD, 16, 396, 398 and mating studies, 228 Westermarck, Edvard, 230, 237–238 z-score model, 72, 91–94, See risk

https://doi.org/10.1017/9781108377911.020 Published online by Cambridge University Press