Freshwater and Marine Ecology 3031424581, 9783031424588

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Ulrich Sommer

Freshwater and Marine Ecology

Freshwater and Marine Ecology

Ulrich Sommer

Freshwater and Marine Ecology

Ulrich Sommer GEOMAR Helmholtz Centre for Ocean Research Kiel University of Kiel Kiel, Schleswig-Holstein, Germany

ISBN 978-3-031-42458-8 ISBN 978-3-031-42459-5 https://doi.org/10.1007/978-3-031-42459-5

(eBook)

# The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Cover Image: Colobometra perspinosa (Crinoidea, Echinodermata) growing on the gorgonian coral Meilthaea sp. (Octocorallia, Anthozoa); photographer: Nick Hawkins; with kind permission by Ocean School, Dalhousie University, Halifax Canada. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland Paper in this product is recyclable.

In memory of Peter Kilham (1943–1989), Susan S. Kilham (1943–2022), Elsalore Kusel-Fetzmann (1932–2020), Winfried Lampert (1941–2021), and Colin S. Reynolds (1943–2018)

Preface

The importance of surface waters for life on Earth and for human affairs is beyond doubt. Life originated in water and still the biggest diversity of building plans of organisms is found in the aquatic realm. More than 70% of the Earth’s surface is covered by water. Far more than half of the human world population live at the coasts or near the coasts of the sea or lakes or close to rivers. And even most of the humans living distant from surface waters depend on the “ecosystem goods and services” provided by surface waters. These ecosystem goods and services include the provision of drinking water, fisheries, irrigation water for agriculture, process water for industrial production, waterways for trade, and more recently in human history also opportunities for recreation and tourism. Also, the groundwater extensively used for human purposes is tightly connected to the surface waters by the global water cycle. The functioning of the biosphere and the relationships between human societies and the biosphere cannot be understood without aquatic ecology. Nevertheless, marine and inland waters are rather underrepresented in most textbooks of general ecology. In fact, most textbooks of general ecology are textbooks of terrestrial ecology, in spite of the fact that theory development in terrestrial and aquatic ecology went hand in hand. This conceptual coherence between both can be seen from the multitude of examples in this book, illustrating general ecological concepts and testing ecological theory. After introducing the physical and chemical properties of the aquatic habitat and the diversity of aquatic life forms, the book will follow the typical structure of ecology textbooks, taking a “bottom-up” approach from the building blocks (individuals having to cope with the environment) to more overarching and complex entities such as populations, communities, ecosystems, and global biogeochemical cycles. Throughout the different levels of this hierarchy, the book takes an evolutionary perspective, i.e. it views the traits of organisms including their behavior as results of natural selection. It also emphasizes the fact, that organisms do not only adapt to their environment but also modify it, thus becoming environment for each other. Over geological ages, the joint action of organisms lead to a gigantic redistribution of substances between hydrosphere, lithosphere, atmosphere, and biosphere. The present-day chemistry of the Earth’s surface cannot be explained without the activity of organisms, the aquatic ones playing a very prominent role in this gigantic biogeochemical machinery. vii

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The book is based on the author’s lifetime experience as an academic teacher in freshwater and marine ecology at the Universities of Constance, Oldenburg and Kiel. The chapters of the book begin with an introduction defining the place of ecology within the biological sciences, shortly introducing the evolutionary perspective on ecology and firmly defining ecology as a natural science. The second chapter sets the stage by introducing into the physical and chemical properties of surface waters. The third chapter introduces the actors of the big play, the life forms of aquatic organisms. Chapters 4 to 8 travel up the hierarchy from individuals to the biosphere. Chapter 4 (Ecophysiology) is dedicated to the environmental requirements of individuals and their abilities to cope with their environment. Chapter 5 (Populations) introduces growth and decline, age structure and the genetic make-up of populations of individuals belonging to the same species. Chapter 6 analyzes the interactions between populations. Chapter 7 (Communities and Ecosystems) shows how the totality of population interactions within one site can be described and analyzed as communities and ecosystems. Chapter 8 (Biogeochemistry) shows how the activities of aquatic organisms lead to local, regional, and global transfers of matter and shape the chemistry of the Earth’s surface. Chapter 9 is owed to the fact that Homo sapiens has become a dominant actor in the ecology of our planet. The chapter introduces to the most important human pressures on aquatic ecosystems. Kiel, Germany May 2023

Ulrich Sommer

Acknowledgments

I express my gratitude to my mentors from whom I have learned so much, Elsalore Kusel-Fetzmann (University of Vienna), Max M. Tilzer (University of Constance), Winfried Lampert (Max-Planck-Institute of Limnology, Plön). Multiple, intensive discussions with international colleagues have shaped my views on ecology, among them Peter Kilham, Susan S. Kilham, and Colin S. Reynolds playing an outstanding role during my early career. I have always been very happy with my working group at the GEOMAR Helmholtz Centre for Ocean Research Kiel, the Research Unit “Experimental Ecology—Food Webs.” Cooperation and discussion with my lab assistants, graduate students, postdocs, and mid-career scientists has always been a pleasure and source of inspiration. I have as much learned from them as I hope they have learned from me. I express my special thanks to Herwig Stibor (Ludwig-Maximilians University, Munich) who reviewed the manuscript for this book.

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Contents

1

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 The Place of Ecology Within Biological Sciences . . . . . . . . . . . . 1.1.1 Definition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1.2 Knowledge Import and Export . . . . . . . . . . . . . . . . . . . . 1.1.3 Why Aquatic Ecology? . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Ecology and Evolution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.1 Adaptation by Natural Selection . . . . . . . . . . . . . . . . . . . 1.2.2 Fitness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.3 Ecological and Evolutionary Time Scales . . . . . . . . . . . . 1.3 Ecology as a Natural Science . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3.1 Ecology and Environmentalism . . . . . . . . . . . . . . . . . . . 1.3.2 From Gathering Knowledge to Theory . . . . . . . . . . . . . . 1.3.3 Global Forecasts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4 Outlook on the Structure of the Book . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1 2 2 2 3 4 4 6 7 8 8 9 15 15 16

2

The Aquatic Habitat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Surface Waters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.1 World Ocean . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.2 Lakes, Ponds, and Reservoirs . . . . . . . . . . . . . . . . . . . . . 2.1.3 Running Waters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Physical Properties of Water . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.1 Density and Thermal Properties . . . . . . . . . . . . . . . . . . . 2.2.2 Viscosity and Motion in Water . . . . . . . . . . . . . . . . . . . . 2.2.3 Suspension, Sinking, and Floating . . . . . . . . . . . . . . . . . 2.3 Chemical Properties of Surface Waters . . . . . . . . . . . . . . . . . . . 2.3.1 Dissolved Salts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.2 Dissolved Gases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.3 CO2 and the Carbonate System . . . . . . . . . . . . . . . . . . . 2.3.4 Redox Reactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.5 Dissolved Organic Substances . . . . . . . . . . . . . . . . . . . . 2.4 Underwater Light Climate . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4.1 Surface Irradiance . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

17 19 19 19 20 20 20 22 24 26 26 28 29 31 33 34 34 xi

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2.4.2 Units of Measuring Irradiance . . . . . . . . . . . . . . . . . . . . 2.4.3 The Vertical Attenuation of Light . . . . . . . . . . . . . . . . . . 2.5 Vertical Stratification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5.1 Temperature Stratification in Lakes . . . . . . . . . . . . . . . . 2.5.2 Thermohaline Stratification in Marine Waters . . . . . . . . . 2.5.3 Vertical Stratification of Biologically Active Elements . . . 2.6 Bottom and Margin of Water Bodies . . . . . . . . . . . . . . . . . . . . . 2.6.1 Sediment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.6.2 Hard Substrates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.7 Horizontal Movements of Water . . . . . . . . . . . . . . . . . . . . . . . . 2.7.1 Currents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.7.2 Tides . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.7.3 Running Waters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Glossary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Exercise Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

34 35 39 39 41 41 44 44 45 45 45 46 47 48 49 50

Life Forms of Aquatic Organisms . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Representation of Higher Taxa in Water . . . . . . . . . . . . . . . . . . 3.2 Basic Trophic Types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.1 Photosynthesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.2 Chemosynthesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.3 Heterotrophy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Body Size . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3.1 Large Scale Statistical Relationships . . . . . . . . . . . . . . . . 3.3.2 Small-Scale Statistical Relationships . . . . . . . . . . . . . . . . 3.4 Stoichiometry of Biomass . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4.1 C, N, and P in Major Biochemicals . . . . . . . . . . . . . . . . 3.4.2 C:N:P Ratios of Aquatic Organisms . . . . . . . . . . . . . . . . 3.5 Plankton . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5.1 General Traits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5.2 Phytoplankton and Mixoplankton . . . . . . . . . . . . . . . . . . 3.5.3 Zooplankton . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5.4 Bacterioplankton . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5.5 Mycoplankton . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5.6 Planktonic Viruses . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.6 Nekton . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.6.1 Taxonomic Groups . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.6.2 Swimming Behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.7 Benthos on Hard Substrates . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.7.1 General Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.7.2 Phytobenthos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.7.3 Zoobenthos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.8 Benthos of Soft Substrates . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.8.1 General Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.8.2 Phytobenthos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

53 54 55 56 56 57 57 57 60 61 61 63 65 65 68 74 79 81 81 81 81 86 89 89 91 93 98 98 99

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3.8.3 Zoobenthos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.8.4 Bacteriobenthos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.9 Aquatic Larvae of Terrestrial Animals . . . . . . . . . . . . . . . . . . . . 3.9.1 Insects with Benthic Larvae . . . . . . . . . . . . . . . . . . . . . . 3.9.2 Insects with Pelagic Larvae . . . . . . . . . . . . . . . . . . . . . . Glossary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Exercise Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

100 105 106 106 107 107 109 111

4

Ecophysiology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Coping with the Abiotic Environment . . . . . . . . . . . . . . . . . . . . 4.1.1 The Optimum Curve . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1.2 Temperature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1.3 Salinity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1.4 Desiccation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Nutrition and Growth of Autotrophs . . . . . . . . . . . . . . . . . . . . . 4.2.1 Light and Photosynthesis . . . . . . . . . . . . . . . . . . . . . . . . 4.2.2 Mineral Nutrients . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.3 Chemolithoautotrophy . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Nutrition and Growth of Heterotrophs . . . . . . . . . . . . . . . . . . . . 4.3.1 Osmotrophy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.2 Phagotrophy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Dissimilatory Metabolism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4.1 Aerobic Respiration . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4.2 Anaerobiosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Glossary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Exercise Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

115 117 117 118 125 127 128 128 135 142 145 145 147 155 155 157 159 161 163

5

Populations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 Population Distribution In Space . . . . . . . . . . . . . . . . . . . . . . . . 5.1.1 Abundance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1.2 Distribution in Space . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Distribution in Time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2.1 Types of Abundance Changes . . . . . . . . . . . . . . . . . . . . 5.2.2 Mechanisms of Abundance Changes . . . . . . . . . . . . . . . . 5.3 The Mathematical Treatment of Population Growth . . . . . . . . . . 5.3.1 Growth at Constant Rates . . . . . . . . . . . . . . . . . . . . . . . 5.3.2 Limited Growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3.3 Disentangling the Components of Population Dynamics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4 Age Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4.1 Survival Curve . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4.2 Distribution of Age Classes . . . . . . . . . . . . . . . . . . . . . . 5.4.3 Life History Strategies . . . . . . . . . . . . . . . . . . . . . . . . . .

169 171 171 171 172 172 173 174 174 176 180 183 183 184 185

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5.5

Genetic Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.5.1 Founder Effect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.5.2 Genetic Drift . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.5.3 Local Adaptation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.5.4 Speciation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Glossary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Exercise Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

189 189 190 191 192 194 196 197

Interactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1 Competition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1.1 Types of Competition . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1.2 Interference Competition . . . . . . . . . . . . . . . . . . . . . . . . 6.1.3 Exploitation Competition . . . . . . . . . . . . . . . . . . . . . . . . 6.1.4 Competition Under Variable Conditions . . . . . . . . . . . . . 6.1.5 Evolutionary Consequences of Competition . . . . . . . . . . 6.2 Predator–Prey Relationships . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2.1 General Patterns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2.2 Grazing, Herbivory . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2.3 Predation Among Animals . . . . . . . . . . . . . . . . . . . . . . . 6.2.4 Parasitism and Disease . . . . . . . . . . . . . . . . . . . . . . . . . 6.3 Positive Interactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.1 Commensalism and Ecosystem Engineering . . . . . . . . . . 6.3.2 Mutualism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.4 Complex Interactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.4.1 Algal Nutrient Competition–Grazing–Nutrient Recycling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.4.2 Keystone Predation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.4.3 Trophic Cascades . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.4.4 Alternative Stable States . . . . . . . . . . . . . . . . . . . . . . . . Glossary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Exercise Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

201 202 202 203 206 219 222 224 224 229 237 244 247 248 254 258

Communities and Ecosystems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.1 General Features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.1.1 Demarcation Problems . . . . . . . . . . . . . . . . . . . . . . . . . . 7.1.2 Degree of Integration . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.1.3 Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.1.4 Collective Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2 Food Webs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2.1 Food Chains and Trophic Levels . . . . . . . . . . . . . . . . . . 7.2.2 From Food Chains to Food Webs . . . . . . . . . . . . . . . . . . 7.3 Communities and Ecosystems Based on Ecosystem Engineering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3.1 Macrophyte Stands . . . . . . . . . . . . . . . . . . . . . . . . . . . .

281 282 282 283 284 286 287 288 289

259 260 261 263 267 269 272

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7.3.2 Bivalve Reefs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3.3 Coral Reefs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.4 Diversity and Species Richness . . . . . . . . . . . . . . . . . . . . . . . . . 7.4.1 Definition and Measurement . . . . . . . . . . . . . . . . . . . . . 7.4.2 Sources and Maintenance of Diversity . . . . . . . . . . . . . . 7.4.3 Diversity Effects on Collective Properties . . . . . . . . . . . . 7.5 Succession . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.5.1 General Concept . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.5.2 Drivers of Succession . . . . . . . . . . . . . . . . . . . . . . . . . . 7.5.3 Benthic Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.5.4 Pelagic Seasonality: A Mix of Succession and Phenology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Glossary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Exercise Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

297 299 303 303 306 310 317 317 318 318

Biogeochemistry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.1 Fundamentals of Energy and Matter Transfer . . . . . . . . . . . . . . . 8.1.1 Transfer of Energy . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.1.2 Transfer of Matter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.1.3 Formation of Particulate Matter . . . . . . . . . . . . . . . . . . . 8.1.4 Regeneration of Dissolved Substances . . . . . . . . . . . . . . 8.1.5 Sedimentation and Deposition . . . . . . . . . . . . . . . . . . . . 8.1.6 Scale of Biogeochemical Cycles . . . . . . . . . . . . . . . . . . . 8.2 Specific Cycles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2.1 Carbon Cycle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2.2 Nutrient Cycles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2.3 Oxygen Cycle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3 World Production and the Oceanic Carbon Pump . . . . . . . . . . . . 8.3.1 Plankton . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3.2 Benthos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3.3 Global Sums of Primary Production . . . . . . . . . . . . . . . . 8.3.4 The Biological Carbon Pump . . . . . . . . . . . . . . . . . . . . . 8.4 The Long-Term Imprint of Biological Production in the Ocean . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.4.1 Biogenic Formation of Sediments and Rocks . . . . . . . . . 8.4.2 Biological Control of Seawater Chemistry . . . . . . . . . . . 8.4.3 Biological Control of the Atmosphere . . . . . . . . . . . . . . . Glossary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Exercise Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

335 336 336 339 340 341 342 344 345 345 347 349 350 351 353 353 354

Human Impacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.1 Eutrophication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.1.1 Causes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.1.2 Consequences in the Pelagic . . . . . . . . . . . . . . . . . . . .

373 375 375 379

. . . .

320 324 326 328

358 358 360 363 365 367 369

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Contents

9.1.3 Effects on Benthos . . . . . . . . . . . . . . . . . . . . . . . . . . . . Climate Change . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.2.1 Physical Changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.2.2 Biogeographic Shifts . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.2.3 Shifted Seasonality of Biological Processes . . . . . . . . . . . 9.2.4 Future Primary Production . . . . . . . . . . . . . . . . . . . . . . . 9.2.5 Shrinking Body Size . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.2.6 Risks for Coral Reefs . . . . . . . . . . . . . . . . . . . . . . . . . . 9.3 Acidification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.3.1 Freshwater Acidification . . . . . . . . . . . . . . . . . . . . . . . . 9.3.2 Ocean Acidification . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.4 Overfishing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.4.1 Extent and Causes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.4.2 “Fishing Down the Food Web” (Pauly et al. 1998) . . . . . 9.4.3 Restoration Efforts . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.5 Biological Invasions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.5.1 Human Transport Vectors . . . . . . . . . . . . . . . . . . . . . . . 9.5.2 From Transport to Establishment . . . . . . . . . . . . . . . . . . 9.5.3 Impacts of Invasive Species . . . . . . . . . . . . . . . . . . . . . . 9.6 The Anthropocene . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.6.1 Defining the Anthropocene . . . . . . . . . . . . . . . . . . . . . . 9.6.2 Human Domination . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.6.3 Do We Experience the Sixth Mass Extinction? . . . . . . . . Glossary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Exercise Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

384 385 385 386 387 390 391 393 394 394 395 400 400 401 404 404 404 405 406 412 412 412 413 416 418 419

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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9.2

1

Introduction

Contents 1.1 The Place of Ecology Within Biological Sciences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.1.1 Definition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.1.2 Knowledge Import and Export . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.1.3 Why Aquatic Ecology? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.2 Ecology and Evolution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.2.1 Adaptation by Natural Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.2.2 Fitness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 1.2.3 Ecological and Evolutionary Time Scales . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1.3 Ecology as a Natural Science . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 1.3.1 Ecology and Environmentalism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 1.3.2 From Gathering Knowledge to Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 1.3.3 Global Forecasts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 1.4 Outlook on the Structure of the Book . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

Summary In this chapter, the place of ecology within biological sciences will be defined together with the specifics of aquatic (freshwater and marine) ecology. It will be emphasized how tightly ecology and evolution are intertwined. Modern ecology cannot be understood without understanding the essentials of Darwinian evolutionary science, in particular the principle of natural selection. Finally, the distinction between ecology as a natural science and environmentalism will be made with a basic account of the necessary ingredients of scientific development and testing of theories

# The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 U. Sommer, Freshwater and Marine Ecology, https://doi.org/10.1007/978-3-031-42459-5_1

1

2

1 Introduction

1.1

The Place of Ecology Within Biological Sciences

1.1.1

Definition

The term ecology was first coined by the German zoologist and evolutionary biologist Ernst Haeckel. It combines the Greek words for house or household, oἶκoς (oîkos), and for science or studies, -λoγία (logía). Heckel’s (1866) original definition defined ecology as the science about the relationships between organisms and their environment, i.e., the living conditions in the widest sense. The living conditions are partially of organic nature (other organisms and their remains) and of inorganic nature (physical, chemical, and geological environment). Heckel’s definition is rather wide and permits extensive overlaps with neighboring disciplines, such as biogeography, behavioral biology, genetics, and evolutionary biology. Krebs (1985) tried to sharpen the definition of ecology as “the scientific study of the interactions that determine the distribution and abundance of organisms.” This definition might be too narrow, because explaining distributions and abundances is an important but not the only goal of ecology. It is also a central goal of ecology to understand how the activity or organisms shapes the distribution of materials at the Earth’s surface, i.e., the “household (oἶκoς) of the biosphere.” Of course, the distribution of materials is also an ingredient of explaining the distributions and abundances of organisms, but it is also a legitimate object of study in its own right. It is the focus on one of the major subdisciplines of ecology, biogeochemistry (Chap. 8). Thus, it might be wise to retain the breadth of Haeckel’s definition and to accept the overlaps with other disciplines.

1.1.2

Knowledge Import and Export

Import Ecology needs knowledge generated by most other biological disciplines, such as systematics, morphology, physiology, behavioral biology, genetics, and evolutionary biology. In addition, certain elements of physics, chemistry, and geosciences are needed, as can be seen in Chap. 2. Export Knowledge generated by ecology is required by a number of applied sciences and management issues, such as conservation biology, fisheries biology and management, agriculture, and landscape and urban planning. Ideally, there should not only be a one-way flow of information from fundamental science to application. Managerial measures should be accompanied by ecological monitoring of effects, and the data obtained by monitoring effects of environmental management should be used to test, improve, and refine ecological theory, and, if necessary, abandon concepts and theories, which have not withstood the test of application.

1.1 The Place of Ecology Within Biological Sciences

1.1.3

3

Why Aquatic Ecology?

Life originated in water. More than 70% of the Earth’s surface is covered by water. Far more than half of the human population lives at the coasts or near the coasts of the sea or lakes or close to rivers. And even most of the humans living distant from surface waters depend on the “ecosystem goods and services” provided by surface waters, be it drinking water, irrigation water for agriculture, process water for industrial production, waterways for trade, etc. Thus, there can be no doubt that the biosphere and the relationships between human societies and the biosphere cannot be understood without aquatic ecology. Nevertheless, most classic ecology textbooks are dominated by terrestrial examples, examples taken from freshwater and marine habitats playing only an exotic role. This is particularly disappointing since theory development in terrestrial and aquatic ecology went hand in hand. Just to mention one example: The concept of the ecological community (then called “biocoenosis”), i.e., the totality of locally interacting organisms of various species, was initially proposed by the zoologist Möbius (1877) based on his investigations of oyster beds in the North Sea. There are numerous such examples how aquatic ecology has inspired general ecology or how theories originating from terrestrial ecology found a premier testing ground in aquatic systems. Lakes are particularly suitable as testing ground because of their relatively clear-cut spatial demarcation from adjacent ecosystems. With good reason one of the programmatic papers of early limnology (freshwater ecology) is called “the lake as a microcosm” (Forbes 1887). The ecology of inland waters and marine ecology have developed partially in separation, but there has always been mutual intellectual inspiration and a mutual import and export of concepts and theories. During the last 5 decades, careers transgressing the freshwater–saltwater boundary have become increasingly common, including my own career. In North America, there is a joint professional society for freshwater and marine sciences, the Association for the Sciences of Limnology and Oceanography (formerly American Society for Limnology and Oceanography, ASLO), founded in 1936. In other countries, e.g., in Germany, the professional societies for both disciplines are still separated. Here we need a bit of terminology in order to clarify some terms which are almost synonyms, but not completely: Limnology and freshwater ecology are the most widespread terms used for the ecological sciences dealing with inland waters. The term “freshwater” is not completely correct here, because salt lakes are also included. While most scientists use limnology and freshwater ecology as interchangeable terms, some traditional limnologist would maintain that limnology is an interdisciplinary science giving equal weight to physics, chemistry, geology, and biology of inland waters. Marine biology, marine ecology, and biological oceanography are also often used interchangeably, but differ in the emphasis. Marine biology puts emphasis on the organisms, marine ecology on the organism–environment relationships, and biological oceanography on the ocean as an integrated system. Biological

4

1 Introduction

oceanography is seen as a subdiscipline of oceanography, together with physical oceanography and chemical oceanography.

1.2

Ecology and Evolution

1.2.1

Adaptation by Natural Selection

Conditions for Adaptation Ecology and evolutionary biology are tightly interwoven. The organisms interacting with their abiotic environment and with other organisms are the result of evolution. If they perform well in their environment we call them “being adapted.” If they are less well adapted than others, their kind becomes eventually rarer until finally dying out. This is the essence of natural selection as the driving force of evolution (Darwin 1859). The evolution of adaptation by natural selection needs several prerequisites: • Variation: Different individuals of a population are not identical. They differ at least in some traits, such as morphological appearance, size, behavior, physiological requirements and abilities, etc. • Heritability: At least some part of the variation is heritable, i.e., will be transmitted from parents to their progeny. • Different alleles: The genetic basis of heritable variation are different versions of the same gene, i.e., alleles. If a gene is uniform throughout a population, there can be no selection between alleles. • Potentially infinite growth: If not constrained by selecting forces each genotype can potentially colonize the entire Earth. The selective forces exerted by the abiotic and biotic environment prevent each genotype within the parent generation from being represented in the same proportion in future generations. The fitter genotypes and genes will increase; the less fit ones will decrease.

Adaptation vs. Acclimatization In an evolutionary context, the term adaptation is used in a more restricted sense than in everyday language. Adaptation is heritable; it is not the result of a kind of training of an individual in their attempt to better cope with environmental challenges. For these modifications the terms “acclimatization” or “accommodation” should be used. Trait modifications acquired by acclimatization are not heritable. The absence of heritability of acquired acclimatization distinguishes the Darwinian from the Lamarckian concept of evolution. However, the ability to acclimatize can be a heritable and, thus, an adaptive trait. Transgenerational Transmission of Epigenetic Modifications Acclimatization to the environment involves up- and downregulation of genes. In principle, this is the same mechanisms as the programming of somatic cells for their

1.2 Ecology and Evolution

5

function in a multicellular organism. For that purpose, up- and downregulation patterns have to be transmitted across cell divisions. According to the definition by Heard and Martinssen (2014), epigenetics “concerns the perpetuation of gene expression and function across cell divisions without changes in DNA sequence.“ During zygote formation, this information transmission is extinguished (“reprogramming”), but with different degrees of perfection in different groups of organisms. Thus, there is some epigenetic inheritance, most important among clonal organisms. It is also quite important among protists (Weiner and Katz 2021), but also in plants and some animal groups like nematodes, but rather marginal in vertebrates (Heard and Martinssen 2014).

Selection via the Phenotype The genotype of an individual is not directly visible. Environmental factors influence how the genotype is translated into the trait combination of an individual, i.e., its phenotype. It is the phenotype which has to cope with the environment. Therefore, natural selection acts on the phenotype. Selection does not change the genotype. However, by favoring one phenotype over the other, it changes the representation of the underlying genotypes in future generations and the frequency of different alleles. Thus, natural selection changes the gene pool of a population. Sources of Variation Population As stated above, natural selection can only operate if there is genetic variation within a population. In the classic genetic definition, populations consist of those members of a species which can interbreed, i.e., which are not separated by barriers, be it geographic or behavioral. In eukaryotic organisms, genetic exchange during reproduction is performed by distributing homologue genes to daughter cells (gametes) during meiosis and fusion of gametes. Prokaryotes have other mechanisms of exchanging genetic material (parasexuality). However, there are numerous taxa with only vegetative reproduction and no exchange of genetic material; i.e., the lineages of descendants are genetically identical clones. It has also become usual to use the term “populations” for assemblages of conspecific clones living together, but they do not share a joint gene pool. Mutation The accidental change of genes and, therefore, appearance of new alleles is the primary source of genetic variation. It operates without direction; i.e., mutations do not occur with the purpose of improving adaptation. Recombination Wherever there is genetic exchange within a population, new combinations of alleles from the same gene pool are possible. This means that new genotypes can be assembled. Recombination can be random, just like mutations, but there can be also a degree of non-randomness and selection, if mates are chosen because of certain traits. Strictly clonal taxa lack the possibility of increasing genotype diversity by recombination.

6

1 Introduction

“Strategy” is a frequently used term in ecology to describe patterns how organisms are adapted to their environment. One should be aware of the metaphoric character of this word because the term strategy normally implies planning for a certain purpose. However, the production of genetic variation lacks planning and foresight. Instead, adaptation is attained by selection from unplanned variation. Solutions not working at all are eliminated at once; solutions working worse than others become progressively rarer until dying out.

1.2.2

Fitness

Survival of the Fittest “Survival of the fittest” has become the proverbial characterization of Darwin’s theory. However, it has to be kept in mind that fitness is a relative term. Of course, a genotype would die out if living conditions are lethal. But after having passed the filter of lethal limits, it counts to be fitter than other genotypes within a population. Fitness is measured by the representation of a gene or a genotype in future generations compared to the starting generation. Fitter genotype and genes will enrich; less fit genotypes will become rarer. Components of Fitness It is not enough to produce as much offspring as possible. The offspring has to survive until reproduction in order to increase the representation of a genotype in future generations. This means that fitness has two components, reproductive potential and survival. Both are not only intrinsic properties of a genotype; they also depend on environmental conditions, but there is often a trade-off. Parents investing little energy, material, and effort into individual offspring can produce many offspring at the expense of survival chances. On the other hand, parents investing a lot into individual offspring can only produce few offspring, but these have better chances of survival (Sect. 5.4). Limits of Adaptation Adaptation is not always perfect because of • Time constraints: Fitness exists only in relation to the prevailing environment. However, the environmental conditions change and this change may be faster than the time needed for the fittest genotype to become dominant thorough natural selection. • Residuals from the past: New sets of traits can only evolve by changing existing ones, not by construction from scratch. • Structural limits: Even if the conditions of selection would favor the increase of on trait, e.g., swimming velocity of a fish, this cannot be increased infinitely. • Trade-offs: Most adaptations have costs; i.e., adaptation to one environmental challenge might impair the ability to maximize adaptation to other environmental challenges. Size (Sect. 3.3) is a simple example. Being bigger often means to be

1.2 Ecology and Evolution

7

safer from predation, but it is also connected to higher food demands, a slower growth, and a longer time needed until being able to reproduce. Other examples relate to the allocation problem: Matter and energy invested into one goal cannot be invested into another one. Optimization Instead of Maximization Such trade-offs and the multiple nature of environmental challenges mean that it is not possible to maximize all favorable traits at the same time. Instead, fitness is gained though the optimization of the combination of traits. Therefore, there cannot be a single genotype being fittest under all circumstances.

1.2.3

Ecological and Evolutionary Time Scales

Ecology Fast: Evolution Slow? Ecology and evolutionary biology deal both with organism–environment relationships. However, it has been a long-standing implicit or explicit assumption that time scales clearly separate both disciplines. Ecological processes were considered fast, operating from days to centuries (forest or coral reef succession). Evolutionary processes were considered slow, operating at geological time scales. Thus, it was assumed that populations and species have fixed properties during ecological processes and evolutionary changes need not to be accounted for when explaining ecological changes. Rapid Evolution The assumption of evolutionary slowness is still true for high-order phylogenetic processes, e.g., the radiation of mammals or the evolution of the vertebrate building plan. On the other hand, very rapid bacterial evolution toward resistance against antibiotics has been reported by medical microbiologists since decades. This was not taken too seriously by ecologists working primarily with more complex organisms because of the short generation time of bacteria. Meanwhile, numerous examples of rapid evolution (in the order of 101 to 102 generation times) have also been documented for more complex organisms, and several of them will be presented in this book (temperature adaptation: Sect. 4.1.2; life cycle adaptation to age-specific predation: Sect. 5.4.3; adaptation to ocean acidification: Sect. 9.3.2). A Problem for Using Indicator Species and for Paleo-Ecology? Applied ecology frequently uses “indicator species” to infer ecological conditions of local ecosystems, e.g., water quality in lakes. Paleo-ecology is the attempt to reconstruct past environmental conditions from fossil or subfossil remains of indicator species, e.g., reconstructing the pH history of acidified lakes from the species composition of diatom frustules in sediment cores. Both approaches make the implicit assumption that species or even higher taxa have environmental tolerances and preferences not changing in space (recent bioindication) and time (paleoecology).

8

1 Introduction

In practice, the use of biological indicators as proxies for past environmental conditions works in most cases satisfactorily and produces results similar to the results of independent, alternative approaches, e.g., based on chemical proxies. How can this be reconciled with the recent findings about rapid evolution? At present, there is no satisfactory answer. Potential, but untested and possibly insufficient, explanations might be: • Single factor dominance: All examples of rapid evolution are based on a single or two highly dominant selection factors applied constantly through time. Under the majority natural circumstances, there is a bigger number of selection factors and none of them has a temporally constant strength. • Single species effects: The experimental examples are based on single species cultures. Thus, a genotype of the experimental species better adapted to a new environment is not confronted with genotypes of competing species already flourishing there.

1.3

Ecology as a Natural Science

1.3.1

Ecology and Environmentalism

The increasing awareness of environmental problems has led to a widening of the meaning of “ecology” in everyday language. Especially the derived adjective “ecological” and the prefix “eco- “are now often used to characterize an environmentfriendly behavior or worldview. In this book, I will use the term ecology for a subdiscipline of biology and, therefore, a natural science strictly following the rules of natural sciences. The science of ecology has to be distinguished from environmentalism. Environmentalism is a political philosophy and societal movement putting the protection and restoration of the natural environment on top of the priority list of policy. Obviously, wise environmentalism should be informed ecologically, i.e., use the best available ecological knowledge to design its political program. However, a natural science cannot directly tell politics or economy what to do. Natural sciences are not in search for political to-do lists; they thrive to understand nature, i.e., unravel natural laws and probabilities. A good understanding enables the prediction of what would happen if human societies do this or that or fail to do it. Ideally, also costs and unwanted side effects of environmentally targeted political measures should be predicted, certainly not always by ecology but also by economic and social sciences. The advice of science to politics is therefore not: “You have to do A!” but: “If you want to achieve goal X you have to do A and accept the costs B and the side effects C.” Often, this statement will not be made in terms of certainty but in terms of probability. Then, politics has to decide whether to do A or whether costs

1.3 Ecology as a Natural Science

9

are too high and side effects are too bad. In a democratic decision, the expert has no bigger vote than the normal citizen.

1.3.2

From Gathering Knowledge to Theory

Who? Collection, Nomenclature, and Classification Usually, a natural science starts with collecting its objects of study, giving names to them, and attempting to put them into an orderly system, i.e., classification. In essence, this is the attempt to answer the question” who”? The prototype of this phase of biology is the Linnaean system of organisms, but similar classification efforts can be made with more abstract concepts, like life-form types, types of communities and ecosystems, etc. During the typological phase most of the scientific debates arise around the issue of definitions. Definitions decide whether an object belongs to one class or another class of objects. As such, typologies (classification schemes) cannot be right or wrong; they can be more or less practical. Unpractical typologies will be abandoned in the course of time and superseded by more practical ones. However, there is an element of “right or wrong” if classification schemes go beyond the demand of putting phenomena into a clear (as clear as possible) order, e.g., the claim that the taxonomic system of organisms should reflect phylogeny. How Many? How Much? Quantification Often identification and classification are followed by the question “how many?” or “how much?” This question can relate to biological species, but also to chemical entities. At first sight, it seems quite trivial to get quantitative estimates, but aquatic ecology had to spend quite a lot of effort to develop sampling gear and quantitative analytical methods. A sampling device might under-sample the objects of study; e.g., specimens smaller than the mesh size of a net might escape from sampling. An analytical method might not exactly measure the environmental concentration of a predefined chemical entity, e.g., a certain free ion when the measuring method liberates additional ions from easily breakable compounds. Representativity of samples Most of the objects of ecological research are not distributed homogenously in their environment, which means that individual samples might randomly hit local minima or maxima, thus leading to biased estimates of the mean quantity in a given environment. This problem will be further treated in the section about the distribution of populations in space (Sect. 5.1.2). State variables describe the quantitative status quo of the objects of study, e.g., the number of individuals (abundance) or biomass of organisms or the concentrations of chemical entities. The quantity is expressed as number of individuals, in molar or mass units, and related to volume or area of the environment. Sometimes, measuring the real variable of interest might be impossible or too tedious. Then we have to rely on proxies or surrogate parameters, e.g., the concentration of chlorophyll as a proxy for phytoplankton biomass.

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1 Introduction

Flux variables Many of the state variables of interest are the result of simultaneously occurring processes of addition (growth, biological or chemical production, import, etc.) and removal (death, biological or chemical consumption, export, etc.). We can gain a lot of understanding of ecological processes when we can measure which additive and which removal processes contribute how much to an observable change of a state variable of interest. Quantitative metrics of these processes are called rates or fluxes. In addition to the dimensions of the state variables, they have an additional negative time dimension, i.e., addition or removal per unit time. Absolute rates are related to volume or area of the environment; relative or specific rates are related to the state variable itself, e.g., biomass production per unit biomass and unit time. Absolute rates describe for example the performance of ecosystems, e.g., primary production per liter of water or hectare of a lake. Specific rates describe the performance of individuals or species and thus permit a comparison between them. In most cases, flux variables are far more difficult to measure than state variables. The temporal change of state variables is usually insufficient because additive and removal processes operate simultaneously. It needs experimental manipulations to stop all processes except the process of interest or the use of tracers, e.g., radioactively labeled substances whose incorporation into biomass or a chemical species can be measured.

Why? Explanation by Causality Science does not only consist of collecting, classifying, and quantifying phenomena. Instead, explaining phenomena is the core business of science. Explanation is classically provided by cause-and-effect relationships. Stating cause-and-effect relationships has the form of conditional sentences: • If A happens then B will follow. Causality cannot be observed directly. We can only observe a temporal sequence between A and B. In order to claim a causal relationship, the sequence between A and B has to be observed repeatedly and we have to make sure that B does not happen without A or an alternative cause. Ideally, we should also be able to show that we can induce B by artificially making A happen—this is the essence of an experiment. Deterministic vs. Probabilistic Causation In its strict, deterministic form, the claim of a cause-and-effect relationship does not tolerate a single exception. The statement if A happens then B will follow is falsified by a single observation of B not happening after A. However, biological and social sciences have demonstrated that deterministic cause-and-effect statements often fail and have to be relaxed in a probabilistic sense, i.e.,

1.3 Ecology as a Natural Science

11

• If A happens then B will follow with X % probability or • A increases the probability of B Causality as a Category of Human Thinking The impossibility of a direct observation of causality and the frequent occurrence of probabilistic relationships and of completely unpredictable random events have led to repeated attempts to dismiss the principle of causality in philosophy and theoretical physics, but a strictly non-causal way of thinking going beyond the probabilistic relaxation of causality could not establish itself, neither in everyday life nor in science. Therefore, I tend to stick to Kant’s (1781) position that causality is a necessary category of human thinking, not a fact of nature. Causality and Correlation The supposed cause A and the supposed effect B can be categorial (yes or no) or continuous variables (having a quantity). If both are continuous variables, causality is often inferred from correlations between A and B. However, this inference is dangerous because A and B might be independent of each other, but both depend on the third variable C. Sometimes there are good reasons to suspect such a “hidden” cause; sometimes it remains really hidden and much later some new discovery will unravel the real relationship. If there is reason to suspect a dependence on a third variable, it may be discovered if the correlations between C and A and between C and B are tighter than the correlation between A and B. Alternatively, A and C could be manipulated experimentally to see the effect on B. Why Experiments? Experiments offer the possibility to manipulate a supposed causal factor while the influence of all other potentially disturbing factors can be kept equal between treatments. Carefully designed experimental research has to fulfill the following criteria: • Control: In experimental research, it is never sufficient simply to do something and to look what happens and not to take into account what happens without the experimental manipulation. If the supposed causal factor A is a categorial variable, the responses of B between experimental units with and without A (“control”) have to be compared. If A is a continuous factor, a number of experimental units with different levels of A should be employed. It would also be possible to treat A like a categorial factor and employ only two levels, but this simplification might be misleading if B shows a unimodal response to A, i.e., being maximal at some intermediate level of A and minimal at low and high levels of A. • Replication within experiments: The difference between control and treatment might be just accidental if both are represented by a single unit. Therefore, several treatment and control units have to be used and the outcome has to be checked

12

1 Introduction

statistically for the significance of difference in appropriate two-sample comparisons (parametric tests like t-test or ANOVA if data are normally distributed or non-parametric tests in the absence of normality). In an experiment with several levels of A, the number of units has to be sufficient for the effective usage of regression analysis or comparable procedures. In all cases, the different experimental units have to be independent of each other; taking subsamples from a single unit or from units influencing each other by neighbor effects is known as pseudo-replication. For the different statistical methods to evaluate effects, see Winer et al. (1991). • Replication across experiments: A single experiment provides only information of a very low generality, being valid for one test species/test ecosystem, one location, one season, etc. If an increasing number of as similar as possible experiments with other test species, in other locations, other seasons, etc., provide similar results, the generality of the results will increase and confidence in the outcome will grow. • Reproducibility: Experiments have to be published in sufficient detail that other researchers can repeat them and test the outcome. • Scale adequacy: Ecological processes need space and time. Therefore, the size of the experimental units and the duration of the experiment have to be adequate. For example, the impact of planktivorous fish on a zooplankton community cannot be studied in a 1 m3 unit, because 1 fish m-3 is far beyond the natural density of fish. If the effect of fertilizing phytoplankton by nutrients on fish is the question of interest, 1 or 2 weeks would be totally inefficient. It takes a few days, until phytoplankton biomass grows in response to the increased nutrients and a few weeks until zooplankton biomass increases in response to the increased availability of food phytoplankton. Physiological indicators of good or poor nutrition of fish need another few days or weeks, but a response at the level of egg production may need up to a year, depending on the seasonal start of the experiment. With limited resources for research, there is often a conflict between replication and scale adequacy. Larger experimental units are more expensive, more difficult to handle, and more difficult to protect against external disturbance. Thus, the choice of scale of an experiment is often a compromise (Box 1.1), and confidence in the results increases if experiments at several scales and field observation show the same result. Box 1.1 Typology of Ecological Experiments Single individual/clone experiments are generally accepted routine in ecophysiology when the response of some biotic variables (e.g., respiration rate and production rate) to abiotic factors or to nutritional factors shall be studied. If study organisms are bigger than 1 mm to 1 cm usually single individuals are used. If organisms are smaller, clonal culture, i.e., culture consisting of genetically identical individuals, is used. (continued)

1.3 Ecology as a Natural Science

13

Box 1.1 (continued) Microcosms are experimental systems composed of several species obtained from pure cultures. They are used to study phenomena of interaction between species, such as competition and predator–prey relationships. Usually, microcosms are set up in the laboratory. Therefore, not only the access of species but also the physical and chemical conditions can be controlled tightly. Typical sizes of microcosms are in the orders of 101 to 103 mL3. Mesocosms rely on the natural mix of species, in many cases under exclusion of large predators. Field mesocosms are set up by enclosing volumes of water (pelagic mesocosms) or areas of the lake or sea bottom (benthic mesocosms) by physical barriers. These barriers can be impermeable (usually plastic sheets) or permeable (nets, permeable for chemicals and organisms smaller than the nesh size). Mesocosms can also be installed in the lab by filling containers with a natural species mix. Possible experimental manipulations include shading, addition of chemical substances, addition or removal of species, and access for mobile predators by openings in the barrier. Field mesocosms have to accept the natural variability of the weather, but the different experimental units have to be subject to the same physical conditions. Usual sizes of pelagic mesocosms range from 102 to 104 L3 and benthic mesocosms from several 10-2 to 100 m2. Open field experiments have no artificial barrier and use entire lakes or semi-enclosed bays. Addition of chemical substances and removal or addition of larger species are typical treatments. Open field experiments have the highest degree of naturality and are fully scale adequate for most ecological questions, but it is difficult to have adequate controls and almost impossible to have an adequate degree of replication. Even comparing the time before and after the start of a manipulation is not a correct form of control, because nobody can guarantee that the difference between “before” and “after” has not just been caused by the weather. This problem can be solved by the BACI (before–after, control–impact; Green 1979) design. For that, two sufficiently similar sites are repeatedly sampled before and after the onset of the experimental manipulation: one is manipulated and the other remains unmanipulated as control. The effect is evaluated by comparing the differences between them before and after the onset of manipulation.

Theory Formation What makes up a theory? In parts of the literature, the terms “hypothesis” and “theory” are used as synonyms, while other authors use the term hypothesis for single “if-then” statements and theory for a higher order system of axiomatic definitions and interconnected hypotheses. Here, the term theory will be used in the latter sense. Natural sciences thrive to transgress singular findings toward laws of nature or at least rules with general application and the formation of grand theories

14

1 Introduction

consisting of a multitude of interconnected laws and rules based on as few as possible basal principles. A successful theory should have the following attributes: • Internal consistency, i.e., the statements within a theory have to be contradiction free • Consistency with past empirical findings • Ability to absorb future empirical findings • As much as possible generality • As much as possible simplicity The first two items are absolute necessities which can be tested with present-day knowledge. The third criterion can only be tested in the future. Generality and simplicity are attributes decisive for the “fitness” of a theory in competition with other theories within the same field of science. Deduction and Induction Deduction is the derivation of statements about single cases from general laws or rules. It follows the laws of logics. Induction is the generalization toward general laws or rules from several to many singular findings. Induction is never complete because the totality of all cases can never be studied. Thus, contradictory future observations are possible. This means that we can never be sure about the truth of statements derived from induction. Popper’s Falsification Principle How can we gain confidence in scientific statements in face of the inevitable incompleteness of induction? Of course, the position “every case is a singular case with its own singular laws” is a position without risk to be proven wrong, but it leads nowhere in terms of understanding nature. A way out of the dilemma was shown by the hypothetico-deductive model of Popper (1959) which is centered around the possibility of falsifying hypotheses. Popper distinguishes the “context of discovery” and the “context of justification” of a hypothesis. The context of discovery is quite free; hypotheses can be generated by deduction from more general theories, by (incomplete) induction, by inspiration, etc. The context of justification follows strict rules. Hypotheses have to generate predictions about observable phenomena with logical necessity. If these predictions fail, the hypothesis is falsified. If the prediction is fulfilled, the rejection of the hypothesis has failed. A hypothesis cannot be falsified, if the prediction encompasses the entire range of possible outcomes (“if A happens, B will increase or decrease or stay unchanged”). A non-falsifiable hypothesis is meaningless because it is void of information. The falsification principle is asymmetric. A hypothesis can be rejected but it cannot be proven because future rejections cannot be excluded. However, an increasing number of failed rejections lead to an increasing confidence. This gain of confidence can be expressed by the word “confirmed” instead of “proven.” Axioms Falsifiable (= testable) hypotheses are not the only ingredients of a higher order theory. Such theories also contain classifications defining which hypotheses

1.4 Outlook on the Structure of the Book

15

are applicable to which classes of phenomena and of axioms. Axioms are basal definitions, like the definition of force as the product of mass and acceleration in Newtonian mechanics. Axioms cannot be falsified, but theories building on them underlie the test of time in science history and will be abandoned or restricted in the domain of applicability when more successful theories emerge.

1.3.3

Global Forecasts

The globalization of environmental deterioration and especially global climate change have confronted science with questions beyond the classic triad “who?– how much?–why?” The pressing question “what will happen globally?” cannot be answered within the framework of the hypothetic-deductive system of conducting science. A forecast of global climate and its impacts on the Earth’s ecosystems is different from the predictions used for hypothesis testing. Hypothesis testing predictions are restricted in space and time and also the conditions under which a prediction should hold are defined in an often quite restrictive way. If the entire Earth’s system is at stake, there can be no controls and replicates, at least in the physical sense of the word. Quasi-controls and quantitative dose–response relationships are possible as different scenarios predicted by complex climate model using different scenarios for driving factors, e.g., different CO2-emission scenarios. However, model outputs are strict deductions from the inputs, i.e., the equations making up a model and the parameter values. When a model contains probabilistic components, re-running the model multiple times can provide some kind of replication. Another kind of replication is achieved, if differently constructed models produce similar predictions. This is one of the avenues toward increasing confidence in model outputs. Another way of gaining confidence is the reconstruction of the past. Global models can also be tested by their ability to predict past changes (documented by paleontological proxies or by human documentation of the more recent past). Such comparisons with the past can also be used to calibrate models in order to improve the prediction of past changes. The ability to make reliable hindcast increases the confidence in the ability to make reliable forecasts.

1.4

Outlook on the Structure of the Book

The Ecological Theater and the Evolutionary Play is the programmatic title of one of the books of the famous ecologist Hutchinson (1965). If we stick to the analogy with a theater, we need a stage, we need the actors, and we need a script. The physical and chemical living conditions in surface waters are the stage of aquatic ecology. Chapter 2 introduces the physical and chemical properties of the aquatic environment. Aquatic organisms are the actors. They are introduced in Chap. 3. The chapter does not follow a taxonomic approach, but a life-form and trait-based approach. The organisms and their traits are the result of past evolution and will experience further evolution during the play outlined in the following chapters.

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1 Introduction

Chapters 4–8 are the main script of the mechanisms explaining the play. Their sequence follows a bottom-up approach along the hierarchy from individuals to the biosphere. Individuals are the elementary particles of ecology. The ability to cope with the abiotic environment, their demands for nutrition, and their abilities to fulfill those demands are the object of ecophysiology, the content of Chap. 4. Individuals of the same species living together form populations. The patterns of population growth and decline, the underlying mechanisms, the age structure, and the genetic structure of populations are presented in Chap. 5. Populations become environmental factors for each other; i.e., they interact. The effect of one population on another can be positive or negative. Pairwise interactions or interactions between few populations are the content of Chap. 6. Chapter 7 integrates what is often treated separately, communities and ecosystems. Communities are the totality of interacting populations at one site. Ecosystems are the communities plus their abiotic environment with a focus on the exchange of matter and energy between both. Community and ecosystem ecology will be treated together since most community processes like food web interactions and ecosystem engineering involve matter and energy fluxes and a separate treatment would often mean telling the same story twice. Chapter 8 is devoted to aquatic biogeochemistry. It shows how the aquatic ecosystems take part in the global exchange of matter and how the joint action of aquatic ecosystems over geological times has left its imprints on the chemistry of the Earth’s surface. In times of global change and ecosystem deterioration, a textbook cannot neglect the human impacts on aquatic ecosystems. The most important ones are presented in Chap. 9.

References Darwin C (1859) On the origin of species. Murray, London Forbes SA (1887) The lake as a microcosm. Ill Nat Hist Survey 15:536–551 Green RH (1979) Sampling design and statistical methods for environmental biologist. Wiley Interscience, Chichester Haeckel E (1866) Generelle Morphologie der Organismen. Allgemeine Grundzüge der organischen Formen-Wissenschaft, mechanisch begründet durch die von Charles Darwin reformirte Descendenz-Theorie, vol 2, p 286, Berlin Heard E, Martinssen RA (2014) Transgenerational epigenetic inheritance: myths and mechanisms. Cell 114:95–109 Hutchinson GE (1965) The ecological theater and the evolutionary play. Yale University Press, New Haven Kant I (1781) Kritik der reinen Vernunft (1974, Suhrkamp, Frankfurt) Krebs CJ (1985) Ecology. Harper & Row, New York Möbius K (1877) Die Auster und die Austernwirtschaft. Wiegandt, Hemple & Parey, Berlin (English translation: The Oyster and Oyster Farming. U.S. Commission Fish and Fisheries Report, 1880: 683–751) Popper KR (1959) The logic of scientific discovery. Harper and Row, New York Weiner AKL, Katz LA (2021) Epigenetics as driver of adaptation and diversification in microbial eukaryotes. Protists. Front Genet 12:642220 Winer BJ, Brown DR, Michels KM (1991) Statistical principles in experimental design. McGrawHill Kogakusha, Tokyo

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The Aquatic Habitat

Contents 2.1 Surface Waters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.1 World Ocean . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.2 Lakes, Ponds, and Reservoirs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.3 Running Waters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Physical Properties of Water . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.1 Density and Thermal Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.2 Viscosity and Motion in Water . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.3 Suspension, Sinking, and Floating . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Chemical Properties of Surface Waters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.1 Dissolved Salts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.2 Dissolved Gases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.3 CO2 and the Carbonate System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.4 Redox Reactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.5 Dissolved Organic Substances . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 Underwater Light Climate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4.1 Surface Irradiance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4.2 Units of Measuring Irradiance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4.3 The Vertical Attenuation of Light . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5 Vertical Stratification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5.1 Temperature Stratification in Lakes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5.2 Thermohaline Stratification in Marine Waters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5.3 Vertical Stratification of Biologically Active Elements . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.6 Bottom and Margin of Water Bodies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.6.1 Sediment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.6.2 Hard Substrates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.7 Horizontal Movements of Water . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.7.1 Currents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.7.2 Tides . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.7.3 Running Waters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Glossary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Exercise Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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# The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 U. Sommer, Freshwater and Marine Ecology, https://doi.org/10.1007/978-3-031-42459-5_2

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2 The Aquatic Habitat

Abbreviations a A CS e Eh E7 η ϕ k Ks N PT r ρ ρ′ Re v z zeu zm zs

characteristic length of a sinking/floating particle alkalinity equilibrium concentration of a gas Euler’s number (base of the natural logarithm, 2.718. . .) Redox potential Redox potential at pH = 7 dynamic viscosity form resistance vertical attenuation coefficient of light Solubility coefficient of a gas number partial pressure of a gas radius density of water density of particle suspended in water Reynolds number velocity depth euphotic depth mixing depth Secchi depth

Summary Aquatic organisms live in an environment that differs in many respects from the environment of terrestrial organisms. Therefore, this chapter provides a brief summary of the most important physical and chemical properties of aquatic environments, to the extent needed for an understanding of ecological processes. For a more detailed treatment of the physics and chemistry of the oceans, lakes, and rivers, textbooks on physical oceanography, limnology, and water chemistry should be consulted. In Sect. 2.1 of this chapter, a short summary of the main types of surface waters is provided. The following two sections are devoted to the ecologically most important physical (Sect. 2.2) and chemical (Sect. 2.3) properties of the medium water. Section 2.4 outlines the underwater light climate, one of the most important factors governing biological production in surface waters. Section 2.5 presents the vertical stratification of the water column in lakes and oceans. Section 2.6 outlines the most important properties of the bottom and margin of water bodies. Section 2.7 presents the most important types of horizontal movements of water.

2.1 Surface Waters

2.1

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Surface Waters

Surface waters are connected to each other through the global water cycle. They feed the atmospheric pool of water vapor by evaporation. Precipitation brings back water from the atmosphere to the Earth’s surface. If not evaporated again, most of this water flows either via streams, rivers, and lakes or via underground flows to the world ocean. Only a small part of the surface water flow ends on continents, either by evaporation from lakes in arid basins or by seeping into a sufficiently permeable underground.

2.1.1

World Ocean

The world ocean forms the biggest part (71%, 361,000,000 km2) of the Earth’s surface and contains ca. 97.5% of the Earth’s liquid and frozen water with a volume of 1.335 × 109 km3. It has a mean depth of 3688 m and a maximal depth of 10,971 m (Mariana Trench in the Pacific Ocean). The world ocean is a globally continuous water body with saline water in most of its parts and brackish water in some semi-enclosed marginal basins. Sometimes, the term “ocean” is only used for its biggest basins, Pacific Ocean (46.6% of ocean area, 50.1% of ocean volume), Atlantic Ocean (23.5% of area, 23.3% of volume), Indian Ocean (19.5% of area, 19.8% of volume), Southern or Antarctic Ocean (6.1% of area, 5.4% of volume), and Arctic Ocean (4.3% of area, 1.4% of volume). The open water of the ocean is called pelagic zone or just pelagic. The neritic zone is part of the pelagic zone above the continental shelves with depths rarely exceeding 200 m. Some marginal seas (e.g., North Sea, Baltic Sea, both in Europe) lie entirely within the neritic zone. The oceanic zone contains the water masses beyond the continental margins. A conventional depth classification of the pelagic distinguishes the epipelagic (0–200 m), mesopelagic (200–1000 m), bathypelagic (1000–3000 m), and abyssopelagic (>3000 m). This is just a formal classification, while from an ecological perspective a classification based on light (Sect. 2.4) and thermohaline stratification (Sect. 2.5.2) seems more appropriate. The bottom and the margin of the ocean are called benthic zone. The nearsurface, coastal part is called the littoral, with the eulittoral or intertidal between the high and low tide water levels and the sublittoral comprising the adjacent zone below extending to the depth where there is still enough light for photosynthesis.

2.1.2

Lakes, Ponds, and Reservoirs

Lakes are stagnant water bodies in natural basins and are not part of the worldwide ocean continuum. Their connection with the world ocean is the unidirectional flow of outflowing rivers reaching the ocean. Natural lakes can have a tectonic, volcanic, glacial, or fluvial origin. Human activities like damming or excavation (e.g., gravel pits) can also form basins which are subsequently filled with water. The majority of

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lakes have outflows, but some lie in arid basins without outflow and lose their water by evaporation. This leads to an increased salt content (saline lakes, Sect. 2.3.1). There is no internationally accepted definition for the boundary between lakes and ponds. The ecology of reservoirs might be closer to lake ecology at low flow-through of water and closer to river ecology at high flow-through. The Caspian Sea (Kazakhstan, Russia, Turkmenistan, Azerbaijan, Iran) is the largest lake both in terms of area (371,000 km2) and volume (78,200 km3). It is a brackish water body with a maximal depth of 1025 m, and it lies in a basin below sea level. While it is usually called “sea,” it is a lake from a geomorphological point of view because it lacks a connection to the world ocean. Lake Superior (Canada, USA) is the largest freshwater lake in terms of area (82,100 km2). It has a volume of 12,100 km3 and a maximal depth of 406 m. Lake Baikal (Russia) is the deepest (1637 m) lake and the largest freshwater lake in terms of volume (23,600 km3). Its surface area is 23,600 km2.

2.1.3

Running Waters

Rivers and streams are the conveyor belts transporting water from the land surface to the world ocean. At their start from a spring, they are called first-order streams or headwater streams. When two first-order streams join, they form a second-order stream. When two second-order streams join, they form a third-order stream, and so on. The largest rivers are 10th or 11th order streams. While the order of a stream is not defined by size or water flow, it is obvious that on average higher order streams are bigger and carry more water than lower order ones. When measuring the length of a river, it is usual to measure along the longest tributaries to the spring most distant to the mouth. The extent to which tidal channels in the delta should be included in length measurements is controversial. According to https://en.wikipedia.org/wiki/List_of_rivers_by_length, the Nile (Africa) is the longest river (6650 km), followed by the Amazon (South America, 6400 km), the Yangtze (China, 6300 km), and the Mississippi (North America, 6275 km). The Amazon has by far the biggest drainage area (7,000,000 km2), and the highest average discharge of water (209,000 m3s-1) of all rivers. The Nile has a drainage area of 3,254,555 km2 and an average discharge of 2800 m3s-1.

2.2

Physical Properties of Water

2.2.1

Density and Thermal Properties

Freezing Pure water freezes at 0 °C, while the content of solutes decreases the freezing point. Seawater with a salt content of the world ocean’s average (35 g kg-1; g salt per kg water) freezes at ca. -1.9 °C. At any salinity, ice is lighter than liquid water, in the case of freshwater 8.5% lighter than liquid water at 0 °C. This means that ice floats on water and frozen lakes and seas have an ice cover at the surface.

2.2 Physical Properties of Water

21

4

Liquid (density increases as temperature decreases)

3

Temperature (°C)

2

1

Liquid (density decreases as temperature decreases) Temperature of maximum density for liquid water Initial freezing temperature

0

Coincide at 24.70 g/kg and –1.332°C

–1

–2

–3

0 Pure water

Soild (density increases as temperature decreases)

5

10

15

20

25

30

35

40

Salt content (g/kg)

Fig. 2.1 Freezing point (black line) of water and temperature of maximal density (magenta line) depending on salinity (source: FridtjofNansen, Creative Commons Attribution-Share Alike 4.0, https://upload.wikimedia.org/wikipedia/commons/thumb/1/18/Sea_water_freezing_temperature_ and_density_maximum.png/640px-Sea_water_freezing_temperature_and_density_maximum.png

Density Pure water has a density of 998.2 kg m-3 at 20 °C. Density increases with the content of solutes. The density of freshwater deviates only negligibly from pure water, while seawater with a salinity of 35 kg kg-1 has a density of 1026 kg m-3 at 20 °C. The temperature dependence of density depends on salinity. Pure water shows a density anomaly with a maximal density not at the freezing point but at 4 °C. The temperature of maximal density decreases with salinity and at 24.7 g kg-1 (ca. 70% of average seawater) the density anomaly disappears; i.e., liquid water is heaviest just at the freezing point (Fig. 2.1). This difference between freshwater and seawater leads to different patterns of ice formation in freshwater lakes and the sea. In lakes, ice forms at the surface, while in the sea ice might crystallize within the water column and then float to the surface. If sea ice forms at underwater surfaces, bottom organism might become attached to the upward floating ice (“anchor ice”) and become transported to the underside of the ice cover. This phenomenon has been repeatedly observed by divers. Specific Heat Water is a thermally very slowly responding liquid, as expressed by a specific heat of 4.186 kJ at 15°; i.e., 4.186 kJ are needed to increase the temperature of 1 kg water by 1 °C. Only few liquids have a higher specific heat and air has a

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much lower one. The high thermal storage capacity and the slow response to heating can be seen by the difference in seasonal warming and cooling patterns between water bodies and the atmosphere. Spring and summer warming of water bodies and autumn/winter cooling are much slower in water bodies than in the atmosphere and short-term fluctuations of temperature are strongly dampened compared to air. This delay and dampening are strongest in the deepest and largest water bodies. Heat Transmission Heat can be transported within liquids via molecular diffusion and via mixing. Only the latter is really important in natural water because the former is extremely slow in spite of the fact that water has a higher heat conductivity than many other liquids. Mixing can be induced either by external mechanical impacts (wind) or by convection. Convective mixing occurs when water cools at the surface and, thereby, becomes heavier than the water masses below.

2.2.2

Viscosity and Motion in Water

Viscosity From classic mechanics we know the principle of inertia. In a frictionless world (i.e., in a vacuum) a body would remain in constant motion when no force is acting on it and motion will be accelerated if a constant force is acting on the body. However, already in air friction will continuously reduce the speed of a body pushed only once. In water, this deceleration is much stronger. The internal friction of a medium is expressed by its dynamic viscosity (η), often shortly called just “viscosity.” Dynamic viscosity of water at 20 °C: η = 1 × 10-3 kg m-1 s-1 Dynamic viscosity of water at 0 °C: η = 1.8 × 10-3 kg m-1 s-1 This is about 100 times the viscosity of air. Reynolds Number Water is one of the least viscous liquids, but nevertheless motion of water has to overcome much more friction than motion in air. The Reynolds number (Re) expresses the ratio between inertial forces and viscous forces acting on a body moving through a liquid or gaseous medium, or equivalently, of the medium moving through solid pipes or sieves. The Reynolds number can be calculated as Re = a v

-1

ð2:1Þ

a: characteristic length (m), e.g., length of a moving body in the direction of flow, diameter of a pipe through which water is flowing. v: velocity of movement (m s-1) ρ: density (kg m-3) η: dynamic viscosity (kg m-1 s-1)

2.2 Physical Properties of Water

23

Table 2.1 Reynolds numbers of different organisms moving in water (Sommer 2005) Type of movement and organisms Swimming whale Swimming herring Crustacean zooplankton (ca. 1 mm) Swimming ciliate (100 μm) Sinking, large diatom (100 μm) Water current through filtration apparatus of zooplankton (1 μm mesh size) Swimming bacterium (0.3 μm)

Re 108 105 102 10-1 10-2 10-3 10-4

This means that small and slow organisms experience the viscosity of the medium differently than large and fast ones. Fast-moving and larger organisms experience a stronger influence of inertia, while very small or slow organisms are dominated by viscous forces. Usually, it is not easy to calculate exact values of Re, because the characteristic length is ill defined for non-spherical particles. However, for most biological considerations estimating orders of magnitude is sufficient (Table 2.1). Very roughly, it can be stated that motile animals of >1 cm live in a high Reynoldsnumber world, while protists live in a viscosity-dominated world. Small metazoans around 1 mm of size, like many zooplankton, live in a transitional environment. Swimming is dominated by inertial forces, while other vital functions, such as filtering food particles from water, are dominated by viscosity. Laminar and Turbulent Flow Particles moving at high Reynolds numbers are surrounded by turbulent flow of the medium while particles moving at low Reynolds numbers are surrounded by laminar flow. Laminar flow means parallel streamlines without mixing of the water around the moving particle. For ourselves, life at low Reynolds number is difficult to imagine because we are large, move relatively fast, and move in air, a medium much less viscous than water. Life at low Re could be visualized by assuming slow swimming through honey. Most of the honey will stick to the body with the laminar flow velocity decreasing the closer the honey is to the body (boundary layer). Thus, we will carry most of the honey of the starting position with us instead of getting in touch with fresh honey while we move, as opposed to swimming at a normal velocity in a less viscous medium, like water where we will always be washed by fresh medium (Purcell 1977). Problems for Dissolved Nutrient Uptake Phytoplankton and bacteria suspended in the water are surrounded by laminar flow, even if they are moved around by larger water parcels in a turbulent environment. The resulting lack of mixing causes problems for taking up dissolved substances from water for nutrition and for the disposal of waste substances. Concentrations of nutrients become depauperated in the vicinity of cells while waste substances become enriched. Ultimately, the possibility to take up dissolved nutrient depends on molecular diffusion which is a

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slow process compared to turbulent mixing. The velocity of diffusion depends on the steepness of the concentration gradient. Therefore, for such small organisms swimming movements do not help in shedding the diffusive boundary layer. However, swimming offers the possibility to encounter higher outside concentrations and speeding up diffusion this way. Problems for Filtration Filtering small, suspended food particles from water is a widespread form of feeding among aquatic animals. However, if comb- or sieve-like filtering structures have mesh width in the μm-size range, as it is often found, low Reynolds numbers characterize the water flow through the filter. The flow becomes laminar and boundary layers of minimal flow velocity develop around the filtering structure. Only little water will pass through the filter and most will flow around sideways if the boundary layers of neighboring structures start to overlap. This can only be prevented if filters are positioned in a closed chamber and if pressure is exerted to squeeze the water through the filter (Brendelberger et al. 1986). Sieve- or comb-like structures moving free in water are nowadays not any more interpreted as filters, but as fans creating a water current from which the food can be picked up actively. Prandtl’s Boundary Layer is a boundary layer developing when water flows along flat surfaces (Lampert and Sommer 2007). Directly at the surface, flow velocities are zero and increase with distance to the surface. The thickness of the boundary layer is operationally defined as the distance from the surface to the layer where 99% of the velocity of free-flowing water is reached. Boundary layers around rocks in streams can reach several mm of thickness. Stream organism, such as insect larvae, may utilize this boundary layer as protection against being washed downstream by the flowing water. They have a streamlined upper body surface and are closely attached to the rock. Thus, their boundary layer becomes part of the boundary layer of the rock and the force of the flowing water does not displace them.

2.2.3

Suspension, Sinking, and Floating

Stoke’s Law All surface waters contain suspended particles. Most of these particles have a density different from water. Particles lighter than water float to the surface while particles heavier than water sink to the bottom. For small particles with low Reynolds numbers (ca. 10% deviation at Re = 0.5, practically no deviation at Re < 0.1), the sinking or floating velocity can be calculated according to Stoke’s law: v = 2 g r2 ð0 - Þ ð9 Þ - 1 g: acceleration by earth [9.8 m s-2] v: sinking/floating velocity ( Na+ > Mg2+ > K+,

2.3 Chemical Properties of Surface Waters

27

Fig. 2.2 Bottom salinity of the Baltic Sea (source: Paolo Momigliano, Gaël P. J. Denys, Henri Jokinen, Juha Merilä; Creative Commons Attribution 4.0 https://commons.wikimedia.org/w/index. php?search=salinit%C3%A4t+Ostsee&title=Special:MediaSearch&go=Go&type=image)

Table 2.2 Average concentration of major ions in seawater (source: Table 2.1 in Sommer 2005) Anion ClSO42HCO3BrH2BO3F-

g kg-1 18.98 2.649 0.14 0.065 0.026 0.001

mmol kg-1 535.36 27.57 2.295 0.813 0.428 0.018

Cation Na+ Mg2+ Ca2+ K+ Sr2+

g kg-1 10.556 1.272 0.4 0.38 0.013

mmol kg-1 459.16 52.32 9.98 9.72

but in some cases Na+ is dominant. Soft waters are usually acidic with pH < 7 due to dissolved CO2. Hard Waters develop in catchments with rocks that are easily weathered, often sedimentary rocks like limestone. They have a higher salinity than soft waters and the concentration rank order of anions is HCO3- > SO42- > Cl-; the one of cations is Ca2+ > Mg2+ > Na+ > K+. Because of the buffering capacity of the carbonate system (Sect. 2.2.3), hard waters are slightly alkaline. Karstic waters are extremely hard waters with a strong tendency toward the precipitation of CaCO3.

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2 The Aquatic Habitat

Salt Lakes In enclosed basins in arid regions, water loss from lakes is dominated by evaporation instead of outflow. Therefore, salts become enriched, and lakes become brackish or saline. In some cases, salinity is higher than in the ocean (e.g., Dead Sea, Great Salt Lake). Some of these terminal lakes are called “sea” (Caspian Sea, Dead Sea), although they are lakes in a geomorphological sense. According to the dominant anions, there are soda lakes (dominated by carbonate), sulfate lakes, and chloride lakes. Building Elements of Biomass The ecological importance of elements dissolved in water does not so much follow the rank order of concentration; instead, it depends on their role as essential components of the biomass of organisms. During the process of primary production (Sect. 3.4) the elements have to be taken up from solution by plants, phototrophic protists, and phototrophic and chemoautotrophic bacteria. Among these elements, C, O, H, N, S, P, K, Ca, Mg, Na, and Cl are called the “classic nutritional elements” and contribute each >0.1% to the dry mass of organisms. Several groups of organisms also use Si (diatoms, silicoflagellates, radiolarians, sponges) or Sr (Acantharia) for building their skeletal structures. As a consequence, the skeletal elements have high a contribution to their dry mass. Beyond these elements, also essential trace elements (Fe, Mn, Cu, Zn, B, Mo, V, Co, Se) are needed for vital functions, although they usually contribute 40,000 × 1018 g C, as opposed to 40.6 × 1018 g C in the hydrosphere, 5 × 1018 g C in fossil fuels, 3.8 × 1018 g C in soils and terrestrial vegetation, and 0.7 × 1018 g C in the atmosphere (Longhurst et al. 1995; Whittaker 1975; Whittaker and Likens 1973; Woodwell 1980). While this distribution of carbon pools is the result of long-term processes at geological time scales, small-scale, present-day examples can be observed in the karstic Plitvice Lakes in Croatia. These are 16 small lakes connected by cascades and waterfalls. Any piece of wood falling into these lakes is covered by a cover of freshly precipitated calcium carbonate within several weeks to months. The barriers between the lakes are 3 to 50 m high and were formed of travertine and tufa, porous calcium calcite rocks produced by chemical and biogenic decalcification from freshwaters (Biondić et al. 2010). CO2 consumption by photosynthesis, mainly by water mosses, is the main driver of biogenic decalcification in the Plitvice Lakes (Miliša et al. 2006) (Fig. 2.4).

2.3.4

Redox Reactions

Many chemical and biological reactions in aquatic ecosystems are redox reaction. The essence of a redox reaction is the transfer of electrons, where the electron acceptor is the oxidizing substance and the electron donor is the reducing substance. In photosynthesis, CO2 acts as the oxidizing agent while H2O acts as the reducing agent. Carbon becomes reduced from oxidation level + IV to 0, the produced organic

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2 The Aquatic Habitat

Fig. 2.4 The Plitvice lakes (sources: photograph: https://commons.wikimedia.org/w/index.php? search=plitvice+lakes&title=Special:MediaSearch&go=Go&ty pe=image; longitudinal section: By Raffaello - Own work, CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php? curid=4437811) Table 2.3 Oxidation level of biologically relevant elements

Oxidation level C(+IV) C(0) C(-IV) N(+V) N(+III) N(0) N(-III) S(+VI) S(0) Fe(+III) Fe(+II)

Compound or ion CO2, HCO3-, CO32C, CH2O CH4 NO3NO2N2 NH4+, NH3, -NH2 SO42S2 Fe3+ Fe2+

substance becomes a reducing agent for further reactions, and oxygen is the terminal electron acceptor. Similarly, also a number of other elements change their oxidation level (Table 2.3) during biological transformations, such as N, S, and Fe, but not P and Si. Redox Potential (Eh) is the capacity of a solution to oxidize or to reduce. It can be measured by an electrode and is often standardized to a pH of 7 (E7) because of its dependence on pH. Eh decreases by 0.058 V if pH increases by one unit. A saturated solution of oxygen has an E7 of 0.8 V, but this value is relatively insensitive to oxygen concentrations as such. A 99% decrease of oxygen concentrations alone decreases E7 only by 0.08 V, but only if there is no increase of reducing substances associated with the decrease of oxygen. However, such substances are even present in fully oxygenated natural waters. Under natural conditions, oxygen-rich surface waters have a redox potential between 0.4 and 0.6 V.

2.3 Chemical Properties of Surface Waters

33

Redox Clines Sharp vertical gradients of the redox potential are found in the transition zones between oxic and anoxic water layers and even steeper gradients are found in the pore water of sediments. These gradients are associated with redox changes of several important ions, e.g., nitrate–nitrite at a transition from 0.45 to 0.40 V, nitrite–ammonium at 0.40 to 0.35 V, Fe3+ - Fe2+ at 0.3 to 0.2 V, and sulfate to sulfide at 0.06 to 0.1 V. The transition from oxidized to reduced iron has indirect effects on the plant nutrient phosphorus, because oxidized iron tends to precipitate phosphate while precipitated phosphates at an oxidized sediment surface can be re-solubilized if iron is transformed to the reduced form at E7 < 0.3 V. If the redox potential is further reduced (50% clay and silt oligomictic lakes lakes which mix less than once per year PAR photosynthetically active radiation (light of 400–700 nm wavelength) pelagic zone open water zone of lakes and seas photosynthesis synthesis of organic matter from inorganic sources using light energy porewater water filling the interstitial space in sediments primary production synthesis of organic matter from inorganic sources pycnocline vertical zone with a steep gradient of water density Reynolds number dimensionless number characterizing the ratio between inertial and viscous forces acting on a body moving in fluids salinity salt content sand sediment with a grain size from 65 μm to 2 mm silt sediment with a grain size from 4 to 65 μm soft water water with a low concentration of dissolved bivalent cations thermocline vertical zone with a steep gradient of water temperature thermohaline circulation circulation of water driven by thermal and salinity effects on water density tides periodic water level fluctuation driven by the gravitation of the moon and the sun turbulent flow flow with irregular streamlines

Exercise Questions The right-hand column of the table below indicates the place where the answer can be found or calculated by an equation there. When calculating the result please be aware of the dimension of the different variables. The dimensions in the equations and the dimensions in the questions are not necessarily the same.

50

1 2

3

4 5 6 7 8 9 10 11 12 13 14 15 16

2 The Aquatic Habitat

Question What is the difference between the temperature dependence of the densities of freshwater and seawater? Calculate the Reynolds number of three moving organisms: (1) a flagellate with a diameter of 5 μm swimming at 0.2 mm s-1, (2) a diatom with a diameter of 30 μm sinking at 1 m d-1, (3) a fish of 0.5 m swimming at 1 m s-1.. Compare the sinking velocities of two equally shaped diatoms in seawater (density: 1026 kg m-3). Diatom A has a density of 1036 kg m-3and a diameter of 10 μ Diatom B has a density of 1046 kg m-3and a diameter of 20 μm. How much faster does A think than B? Which are the three most abundant anions and cations in seawater? Explain the buffering capacity of the carbonate system. What is the oxidation level of the most important nitrogen ions in water? Which wavelength of light can be used for photosynthesis How many % of surface irradiance are found at 20 m depth if irradiance at 10 m depths is 60% of surface irradiance How does the depth of the thermocline change when the surface water becomes cooler during autumn? Is it possible that water higher up in the depth profile of temperature can be cooler than water deeper down? If yes, why? Which grain size of sediment is characteristic of very quiet conditions? And why? Explain color changes along redox gradients in sediment. In which direction does the Coriolis force change currents? Explain the role of deep-water formation for the Great Conveyor Belt. How are the moon, sun, and earth positioned to each other during neap and spring tides? How does the temperature of a stream change with distance from the headwater?

Section 2.2.1 2.2.2

2.2.2

2.3.1 2.3.3 2.3.4 2.4.1 2.4.3 2.5.1 2.5.3 2.6.1 2.6.1 2.7.1 2.7.1 2.7.2 2.7.3

References Bearman G (1989) Seawater: its composition, properties and behavior. The Open University, Watson Hall & Pergamon, Oxford Biondić B, Biondić R, Meaški H (2010) The conceptual hydrogeological model of the Plitvice Lakes. Geologia Croatica 63:195–206 Brendelberger H, Herbeck M, Lang H, Lampert W (1986) Daphnia’s filters are not solid walls. Arch Hydrobiol 107:197–202 Gordon AL (1986) Interocean exchange of thermocline water. J Geophy Res 91:5037–5046 Kirk JTO (2011) Light and photosynthesis in aquatic ecosystems, 3rd edn. Cambridge University Press, Cambridge Lampert W, Sommer U (2007) Limnoecology, 2nd edn. Oxford University Press, Oxford Lee K, Miller FJ (1995) Thermodynamic studies of the carbonate system in seawater. Deep Sea Res I 42:2035–2062 Longhurst A, Sathyendranath S, Platt T, Caverhill C (1995) An estimate of global primary production in the ocean from satellite radiometer data. J Plankton Res 17:1245–1271

References

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Matthäus W (1996) Temperatur, Salzgehalt und Dichte. In: Reinheimer G (ed) Meereskunde der Ostsee. Springer, Berlin, pp 75–81 Miliša M, Habdija I, Primc-Habdija B, Radanović I, Matoničkin Kepčija R (2006) The role of flow velocity in the vertical distribution of particulate organic matter on moss-covered travertine barriers of the Plitvice Lakes (Croatia). Hydrobiologia 553:231–243 Morel FMM, Hering J (1993) Principles and applications of aquatic chemistry. Wiley, New York Moustaka-Gouni M, Sommer U (2019) Monitoring of cyanobacteria for water quality: doing the necessary right or wrong? Mar Freshw Res MF18381 Purcell EM (1977) Life at low Reynolds numbers. Am J Phys 45:3–11 Rahmstorf S (2003) The concept of the thermohaline circulation. Nature 421:699 Reynolds CS (1984) The ecology of freshwater phytoplankton. Cambridge University Press, Cambridge Salmaso N (2000) Factors affecting the seasonality and distribution of cyanobacteria and chlorophytes: a case study from the large lakes south of the Alps, with special reference to Lake Garda. Hydrobiologia 438:43–63 Sanders HL (1958) Benthic studies in Buzzards Bay. I. Animal-sediment relationship. Limnol Oceanogr 3:245–258 Seibold E (1974) Der Meeresboden. Ergebnisse und Probleme der Meeresgeologie. Springer, Berlin Sommer U (1994) Planktologie. Springer, Berlin Sommer U (2005) Biologische Meereskunde, 2nd edn. Springer, Berlin Whittaker RH (1975) Communities and ecosystems. Macmillan, New York Whittaker RH, Likens GE (1973) Primary production: the biosphere and man. Human Ecol 1:357– 369 Woodwell GM (1980) Aquatic systems as part of the biosphere. In: Barnes RSK, Mann KH (eds) Fundamentals of aquatic ecosystems. Blackwell, Oxford, pp 201–215

3

Life Forms of Aquatic Organisms

Contents 3.1 Representation of Higher Taxa in Water . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Basic Trophic Types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.1 Photosynthesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.2 Chemosynthesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.3 Heterotrophy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Body Size . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3.1 Large Scale Statistical Relationships . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3.2 Small-Scale Statistical Relationships . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 Stoichiometry of Biomass . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4.1 C, N, and P in Major Biochemicals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4.2 C:N:P Ratios of Aquatic Organisms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5 Plankton . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5.1 General Traits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5.2 Phytoplankton and Mixoplankton . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5.3 Zooplankton . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5.4 Bacterioplankton . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5.5 Mycoplankton . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5.6 Planktonic Viruses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.6 Nekton . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.6.1 Taxonomic Groups . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.6.2 Swimming Behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.7 Benthos on Hard Substrates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.7.1 General Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.7.2 Phytobenthos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.7.3 Zoobenthos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.8 Benthos of Soft Substrates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.8.1 General Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.8.2 Phytobenthos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.8.3 Zoobenthos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.8.4 Bacteriobenthos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.9 Aquatic Larvae of Terrestrial Animals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.9.1 Insects with Benthic Larvae . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.9.2 Insects with Pelagic Larvae . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Glossary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 U. Sommer, Freshwater and Marine Ecology, https://doi.org/10.1007/978-3-031-42459-5_3

54 55 56 56 57 57 57 60 61 61 63 65 65 68 74 79 81 81 81 81 86 89 89 91 93 98 98 99 100 105 106 106 107 107 53

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Exercise Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .109 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .111

Abbreviations b I L Ra Rs

allometry coefficient ingestion rate body length absolute metabolic rate specific metabolic rate

Summary This chapter gives a kind of minimal introduction to the organisms living in water, as far as it is needed for an ecology textbook. It will not focus on taxonomy, because this would just be a repetition of a taxonomy textbook. All phyla and most of the classes and orders have representatives living in water (Sect. 3.1). Instead of a taxonomic approach, a “life form” approach will be taken, focusing on the traits most important for growth and survival in the aquatic realm. Classification of life form types starts with basic nutritional types (Sect. 3.2). The next most important dimension of a functional characterization is body size (Sect. 3.3), an ecological “master trait” with far-reaching consequences for many other traits, like metabolic rates, growth rate, and longevity. A further functionally important trait is the stoichiometry of biomass (Sect. 3.4) which defines the elemental requirements of organisms. The remining sections are devoted to a grouping by major habitats, in pelagic waters plankton (drifting organisms, Sect. 3.5) and nekton (swimming organisms, Sect. 3.6) and benthos on solid substrates (Sect. 3.7) and benthos on soft substrates (Sect. 3.8).

3.1

Representation of Higher Taxa in Water

The diversity of aquatic organisms encompasses the entire tree of life. One of the few higher taxa without aquatic representatives are the Gymnospermae, a plant group containing among others the conifers. The number of exclusively aquatic higher taxa is much bigger and includes among others Porifera, Ctenophora, Cnidaria, Rotatoria, Polychaeta, Echinodermata, Chaetognatha, and fish. Some of these are entirely marine (Ctenophora, Echinodermata), while others are predominantly marine with a few freshwater representatives (e.g., Porifera, Cnidaria). Conversely, the majority

3.2 Basic Trophic Types

55

of Rotatoria lives in freshwaters. Some groups of algae and heterotrophic protists are predominantly aquatic, but are also represented in moist terrestrial habitats. One of the most underrepresented animal groups in water are the insects, the most species-rich animal class (> one million species). They are particularly scarce in marine habitats but also in freshwaters only a few species complete their life cycle in water, while most aquatic insect species have aquatic larvae and terrestrial adults. Flowering plants are also highly underrepresented in water, as well as reptiles and mammals. The subphylum Crustacea shows the opposite pattern of insects, with only a few terrestrial but many aquatic species. Because of the life form approach taken in this book, some of the group names used here are “names of convenience” and not in agreement with an updated phylogenetically oriented nomenclature. Some group names are highly polyphyletic, such as “algae” or “protists.” In other cases, well-established paraphyletic names, e.g., Pisces = fish, will be used instead of sticking to a phylogenetically correct monophyletic nomenclature.

3.2

Basic Trophic Types

Organisms have to assemble their body mass by synthesizing organic matter from inorganic matter or by consuming organic matter synthesized by other organisms. Building up biomass needs an energy source, a reductant (electron donor), and a carbon source. In order to label organism according to these basic needs, a threecomponent terminology is used: Photo-: light as energy source vs. chemo-: chemical (redox) reactions as energy source Litho-: inorganic electron donor vs. organo-: organic electron donor Auto-: CO2 or HCO3- as C-source vs. hetero: organic matter as C-source A photolithoautotrophic organism is an organism, which uses light as energy source, an inorganic electron donor (H2O; H2S, H2), and CO2 or HCO3- as C-source. A chemoorganoheterotrophic organism uses organic matter as energy source, electron donor, and carbon source. The terms auto- and heterotrophic can be applied to other essential elements as well; C-heterotrophic bacteria are often P-autotrophic, i.e., they obtain P from the dissolved ionic pool in the water. Mixotrophic organisms are able to combine auto- and heterotrophic nutrition. This nutritional mode is particularly common among protists with chloroplasts for photosynthesis and structures for feeding on other microorganisms. Multicellular animals can also be mixotrophic, if they are hosts of photosynthetic symbionts, the most prominent examples being many corals.

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3.2.1

Life Forms of Aquatic Organisms

Photosynthesis

Photosynthesis is the dominant form of primary production, i.e., the production of organic substances from inorganic resources. The organisms performing photosynthesis are photolithoautotrophic; all of them use light as energy source and CO2 or HCO3-as C-source, but the electron donors differ between the different types of photosynthesis. The oxygen producing type of photosynthesis of plants, autotrophic protists, and Cyanobacteria uses H2O as electron donor. The O2 released by photosynthesis is produced as terminal electron acceptor. It results from splitting the water molecule. 6CO2 þ 6H2 O → C6 H12 O6 þ 6O2 :

ð3:1Þ

Green and purple sulfur bacteria use H2S as electron donor and S2 is produced as terminal electron acceptor as a result of splitting the hydrogen sulfide molecule. 6CO2 þ 12H2 S → C6 H12 O6 þ 6H2 O þ 6S2 :

ð3:2Þ

Sulfur-free purple bacteria use H2 as electron donor. 6CO2 þ 6H2 → C6 H12 O6 :

ð3:3Þ

The oxygen producing (“plant type”) photosynthesis is quantitatively the most important pathway of primary production. It is of utmost importance for the oxygen budget of the hydrosphere and the atmosphere. It is the primordial source of O2 in the Earth’s history. The other two types of photosynthesis are restricted to relatively thin layers in the sediment or in the pelagic zone where reducing chemical conditions coincide with sufficient light for photosynthesis.

3.2.2

Chemosynthesis

Chemosynthesis is the nutritional mode of chemolithoautotrophic organisms. It is only found among bacteria and uses the energy of chemical reactions for biosynthesis. These reactions are redox reactions and need an electron donor and an electron acceptor. Electron donors (reductants) include the most reduced forms of an element but also intermediate oxidation levels, if the element in question has multiple oxidation levels. The most common electron donors are H2, CO, S2, S2-, S2O32-, SO42, NH4+, NO2-, Fe2+, Mn2+. Electron acceptors (oxidants) are mainly O2, CO2, NO3-, S2O32-, SO42. This means that intermediate oxidation levels, such as thiosulfate (S2O32-), can act both as electron donors and electron acceptors.

3.3 Body Size

57

Chemosynthesis requires the spatial co-occurrence of oxidized and reduced substances. Therefore, it is often restricted to zones of redox gradients in the sediment or in the water column.

3.2.3

Heterotrophy

The majority of Bacteria and Archaea, all fungi, and all animals are chemoorganoheterotrophic; i.e., they use organic substances as energy source, reductant, and carbon source when building up their biomass. The organic substances can either be particulate (POC, particulate organic carbon) or dissolved (DOC, dissolved organic carbon). Phagotrophy is the use of particulate food and the typical form of nutrition of animals and heterotrophic protists, formerly called Protozoa. The term phagotrophy is used for very different ways of food intake, including swallowing of entire food items, biting off pieces, or drilling and sucking. The food source can be living organisms or their dead remains. Feeding on live organisms is called herbivory, if it is plant material, and carnivory, if it is animal material. Omnivory is the ability to feed on both. Feeding on dead material is called detritivory. Osmotrophy is the uptake and use of DOC for nutrition. It is the typical feeding mode of heterotrophic Bacteria and Archaea and of many fungi and some protists. Because of the usually low concentrations of low molecular weight DOC a high surface to volume ratio is required to gain enough DOC. Therefore, osmotrophy is basically restricted to microorganisms.

3.3

Body Size

The sizes of aquatic organisms range from unicellular organisms 1. It increases with size in a decelerating way if 0 < b < 1

3.3 Body Size

59

(Fig. 3.1). In a double logarithmic plot, the relationships become straight lines with b being the slope of the relationship. Please note that the measures of size can be one-dimensional (length, radius, diameter, etc.), two-dimensional (surface area, cross section, etc.), or three-dimensional (volume, mass, etc.). Use of size measurements with different dimensionality leads to different values of b. Absolute metabolic rates The principle of allometric relationships is illustrated by the example in Fig. 3.2. relating the standard respiration rate (in W) to the live body mass (in g) of unicellular, ectothermal, and endothermal organisms. The range of data extends over 18 orders of magnitude (from pg to metric tons). Three separate regression lines (for unicellular, ectothermal, and endothermal multicellular organisms) were fitted to the data. A single line could have been fitted to all data as well, leading to a slightly different slope and a bit more scatter of the data. The slope of the three lines is b = 0.75; i.e., respiration rates increase with body mass, but they do not increase as fast as body mass. A tenfold increase in biomass would result in a ca. 5.6-fold increase in metabolic rates. Looking at the plot of data in Fig. 3.2 is instructive in several ways. The data were assembled from a multitude of sources and standardization of respiration measurements between these studies was certainly far from being perfect. However, in this plot, even a threefold change in a respiration value would shift a data point only by about a tenth of the scale units at the y-axis, i.e., roughly the thickness of the point symbols in the graph. Such a shift would not spoil the significance of the overall statistical relationship between log R and log M. However, the graph also shows that downscaling of the relationship to animals with minor size differences cannot be warranted. The inset in the lower right corner shows the distribution of respiration rates for unicells from 10 to 100 ng body mass. Obviously, the “macroscopic” relationship does not necessarily hold for smaller scale comparisons, at least if the species within a restricted size interval are taxonomically and functionally not particularly similar. A very similar allometry coefficient (b = 0.76) was found by Ernest et al. (2003) for production rates of protists, plants, and animals. Allometry coefficients around 0.75 for absolute metabolic rates have also been confirmed in studies of restricted taxonomic groups, where functional similarity reduces the scatter around the mean trend (Gillooly et al. 2001; Brown et al. 2004). Specific metabolic rates Mass specific rates, i.e., metabolic rates per unit biomass, can be calculated by dividing absolute rates by body mass. Rs = Ra =M; if Ra = aM b → Rs = aM b - 1

ð3:5Þ

It follows that -0.25 becomes the allometry coefficient for specific metabolic rates. Specific growth rates of body mass or population density follow the same rule because they are derived from specific metabolic rates (which share of their own

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body mass is produced per unit time?). While there are numerous examples in support of this -0.25 rule, data compilations for phytoplankton maximal growth rates show quite a wide array of allometry coefficients from -0.08 to -0.32 (Sommer et al. 2017). The only study including extremely small cell sizes ( 3 (5) μm

Gelatinous 0.5–10 μm Hrs to days Direct

Fast Low Slow

Weeks to a few years Several larval and subadult stages Slow High Fast

Attractive

Attractive

Unattractive

Fast Low Slow

The genus Holopedium is a gelatinous exception

Gelatinous macro- and megazooplankton are either exclusively marine, like Ctenophora (comb jellies), Tunicata, and Chaetognatha, or predominantly marine like the pelagic Cnidaria (jellyfish). Jellyfish of the group Scyphozoa and Hydrozoa undergo a bentho-pelagic alternation of generations with a sexually reproducing pelagic medusa stage and a vegetative, benthic polyp stage. Meroplankton (Fig. 3.12). Besides holoplanktonic organisms, zooplankton also contains larval stages of organisms belonging to nekton or benthos as adults. In freshwaters, there are also planktonic larvae of insects, e.g., the phantom midge Chaoborus. The trochophora is a phylogenetically widespread larval type of benthic animals (Polychaeta, Nemertina, Sipunculida, Bryozoa). The trochophora of several mollusk groups (Bivalvia, Gastropoda, Scaphopoda) develops further into a morphologically more complex veliger stage before settlement and metamorphosis. Echinodermata have bilateral larvae (bipinnaria of starfish, pluteus of sea urchins) in spite of the radial symmetry of the adults. Benthic crustaceans have larvae of the nauplius and zoea type. Fish larvae of many fish species are also planktonic. Planktonic larvae are important for the dispersal of sessile or slowly creeping benthic animals. They might be lecithotrophic or planktotrophic. In the former case, they do not feed in the plankton and live on the yolk. In the latter case, they feed on plankton. Lecitotrophic larvae can spend a shorter time in the pelagic and, therefore, have a smaller potential to disperse than planktotrophic larvae.

Motility All zooplankton are able to move actively, though their swimming ability is not sufficient to move against water currents. Besides short-term movements motivated

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Fig. 3.10 Crustacea belonging to macro- and megazooplankton, the Antarctic krill, Euphausia superba, the gammarid Parathemisto gracilipes, and the shrimp Pasiphaea tarda (source: Fig. 6.8 in Sommer 2005)

by the search of food and escape from predators, there are also regular vertical migration patterns. Diel vertical migration is a commonly observed behavior of many meso-, macro-, and megazooplankton species. The standard type consists of an ascent at the end of the light phase and a descent at the end of the dark phase. The diel amplitude can >100 m in the ocean. This means that the animals spend part of the diel cycle in deeper and colder zones, where there is usually less food. The proximate (triggers of behavior) and ultimate (evolutionary) factors responsible for this behavior are treated in Sect. 6.2.3, Box 6.2. Here, it shall be summarized shortly that diel vertical migration serves to avoid visual predation by fish in the well-illuminated surface layer. Ontogenetic vertical migration consists of the residence of different life cycle stages in different depth zones. Generally, later and therefore bigger developmental stages occupy deeper depth zones, because size makes them more vulnerable to visually oriented predators. In some copepods with an annual life cycle, the

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79

Fig. 3.11 Macro- and megaplankton: Physalia (Hydrozoa), Cyanea (Scyphozoa), Pleurobrachia (Ctenophora), Tomopteris (Polychaeta), Carolina (Gastropoda), Chirotheutis (Cephalopoda), Sagitta (Chaetognatha), Salpa (Tunicata) (source: Fig. 6.9 in Sommer 2005)

ontogenetic migration pattern includes a physiologically inactive diapause period of subadult copepodite stages at greater depth. After ending the diapause, these become adults. The eggs produced by the adults and the nauplii hatched from the eggs float toward the surface because of the buoyancy of lipids. The nauplii molt into first copepodite (C I) stages. The C I to C IV stages perform the typical diel vertical migrations within the upper 100 m; then the C V stage begin to progressively deepen their migration interval until they enter diapause at several 100 m depth (Fulton 1973).

3.5.4

Bacterioplankton

The importance of Bacteria and Archaea in plankton had for a long time been underestimated. Initially, the focus of aquatic microbiology was put on pathogenic bacteria causing health problems for swimmers or people drinking water. This included monitoring of non-pathogenic bacteria indicating fecal pollution

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Fig. 3.12 Meroplanktic larvae (source: Fig. 6.10 in Sommer 2005)

(Escherichia coli). Bacteria were “counted” as colonies developing on agar and other cultivation plates. With the development of fluorescence microscopy, it became clear that plate cultivation techniques can only capture a few percent or even permille of the actual number of bacteria. However, plate cultivation methods are still routine in procedures in hygienic water supervision. Culture independent counting methods (Box 3.2) have shown that individual numbers of bacteria are in the order of 109 cells L-1 even in many unpolluted waters. Heterotrophic bacteria can be attached to detrital particles or live freely suspended in the water. The importance of bacterioplankton for the entire pelagic ecosystem began to be appreciated fully in the late 1970s (Azam et al. 1983). While phytoplankton and zooplankton are morphologically very diverse but metabolically quite uniform, bacterioplankton is morphologically rather uniform but metabolically very diverse. In planktological studies, most attention is given to aerobic chemolithoheterotrophic bacterioplankton. Chemolithoautotrophic bacteria also exist in the plankton, but mainly along vertical redox gradients, e.g., in lakes with seasonally anaerobic deep water, and along the pycnocline in meromictic lakes

3.6 Nekton

81

and sea basins. The vast majority of studies of bacteria living in redox gradients or under anaerobic conditions are performed in sediments (Sects. 4.2.3 and 3.8.4).

3.5.5

Mycoplankton

Compared to phytoplankton, zooplankton, and bacterioplankton, planktonic fungi did not receive much attention until now. Fungi are heterotrophic organisms living either as saprophytes, i.e., from dead organic material, or as parasites (Sect. 6.2.4) on (ectoparasites) or within (endoparasites) other plankton. In many cases, parasitic fungi are not only pathogenic but also lethal for the host. The lethal parasites consume most of the host’s biomass. In terrestrial ecology, these lethal types of parasites are called parasitoids (Eggleton and Gaton 1990). Several very hostspecific parasitoids can almost extinguish populations of single phytoplankton species within a few weeks, the infection being performed by the flagellated zoospores of the fungi. Detailed studies on the epidemiology of these parasitoids were done primarily in freshwaters (Bruning 1991, Holfeld 1998).

3.5.6

Planktonic Viruses

Viruses cannot reproduce themselves because they have no metabolism of their own. They need the metabolism of their host cells to replicate their DNA or RNA. Viruses in the plankton became an active topic of research during the 1980s. Meanwhile, it became clear that they are the most abundant biological entities in the open water, even outnumbering bacteria with abundances around 1010 L-1, ranging from 3 × 108 L-1 to 1011 L-1 (Bergh et al. 1989, Fuhrman 1999). However, due to their small size they contribute only 1–5% to total pelagic biomass (Suttle 2005). Initially, research on the role of viruses as pathogens and killers of plankton concentrated on the viruses infecting heterotrophic bacteria and cyanobacteria (Proctor and Fuhrman 1990). Meanwhile, it became clear that viruses can also have strong negative effects on eukaryotic phytoplankton (Bratbak et al. 1998, Gustavsen et al. 2014). Planktonic viruses are an expanding field of research and further expansion can be expected (Mateus 2017).

3.6

Nekton

3.6.1

Taxonomic Groups

Definition Nekton are those swimming animals of open waters which can control their horizontal position by swimming against currents. There is a gradual transition between nekton and plankton, since some large plankton, e.g., krill, can move against weak currents while some fish cannot swim against strong currents. Nekton

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Fig. 3.13 Pelagic cephalopods, Loligo (Theutoidea), up to 50 cm long; Spirula (Sepioidea), up to 5.5 cm; (Octopoda), up to 20 cm; Ocythoe (Octopoda), females up to 28 cm, males only 3.5 cm (Fig. 6.16 in Sommer 1985)

contains Cephalopoda (only marine), Pisces (marine and freshwater), Reptilia (mainly turtles), and Mammalia (Cetacea, Pinnipeda, Sirenia). Cephalopoda Most of the pelagic cephalopods belong to the order Theutoidea (squids), while the other groups (Sepioidea, Octopoda) live near the bottom. The few recent Nautiloidea live in free water but near the sea bottom. Cephalopods swim by jet propulsion for fast escape from predators or for chasing prey, while slow swimming is performed using fins or arms. Swarm forming squids (Ilex, Loligo, Todarodes, etc.) have become important fisheries resources. The giant squid Architeuthis is a deep-water animal only rarely coming close to the surface. The biggest one found so far had a head length of 6 m and arms of 8 m. Cephalopods reproduce only once in their life and then die (Fig. 3.13). Fish (Pisces) are the most important group in nekton. Because of their paraphyletic nature they are not considered a phylogenetically defined taxon anymore. Nevertheless, the term will be used as a term of convenience here. The two classes of major importance for the nekton are the Chondrichthyes (cartilaginous fish; rays and sharks, Fig. 3.14) and the Osteichthyes (bony fish, teleosts). Chondrichthyes are mostly marine, with very few freshwater exceptions. Osteichthyes evolved originally in freshwaters and are found in freshwaters and marine waters today. Several fish species perform migrations between both realms. Cartilaginous fish are primarily marine, except for a few shark species. The flattened body shape of rays is an adaptation to benthic life, but the plankton feeding giant mantas (Mobula mobular, Manta birostris) belong to the nekton. Most of the

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83

Fig. 3.14 Pelagic chondrichthyes (source: Fig. 6.17 in Sommer 2005)

torpedo-shaped sharks are well adapted to pelagic life, but a few species live near the ground. Most of the sharks are predators, but the largest ones (e.g., whale shark, Rhincodon typus, up to 18 m long) feed on macrozooplankton. Pelagic sharks are viviparous, i.e., there are no free-living eggs or larvae. All teleosts of the pelagic are oviparous, i.e., lay eggs. Some lay pelagic eggs which remain suspended in the water column, e.g., sprat (Sprattus sprattus). The closely related herring (Clupea harengus) lay eggs near the bottom which then sink to the bottom or lay them directly to the bottom. Usually, pelagic bony fish have extremely high egg numbers and do not exercise parental care. Most epipelagic teleosts (Fig. 3.15) have a streamlined, torpedo shape which enables fast swimming to escape predators or to chase prey. The smaller teleosts feed on zooplankton, while the larger ones are predators on other fish. Most planktivores (herring, sardine, anchovy, sprat) form swarms, but also several predators do that, e.g., tunas and barracudas. Solitary predators, like the European swordfish Xiphias gladius, are among the largest teleosts, with a length up to 4.5 m and a body mass of 600 kg. It is one of the fastest swimmers, reaching ca. 100 km h-1. A notable exception to the torpedo shape is the slow swimming large (up to 1500 kg) sunfish (Mola mola), one of the few fish specialized in jellyfish as food. The torpedo shape is also found among mesopelagic (200–1000 m) teleosts, but it is less pronounced there (Fig. 3.16). They have large eyes as an adaptation to their low-light environment. Bathypelagic teleosts are adapted to a life without light and with only sporadic availability of food. A very large mouth and extendable guts, as found in Saccopharynx, are an adaptation to the sporadic availability of large food

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Fig. 3.15 Epipelagic teleosts (source: Fig. 6.18 in Sommer 2005)

items. Many bathypelagic fish have photophores (luminous organs), either to attract prey or to attract sexual partners. Dwarf males are another solution of finding partners in a dark environment with huge distances between individuals. Dwarf males are much smaller than females and live attached to female bodies. Reptiles and water birds. There are no reptiles and birds spending the complete life cycle in the pelagic. However, marine turtles (Cheloniidae, Dermochelidae) can justifiably be considered nekton. Mothers bury their eggs on sandy beaches and the young hatchlings immediately crawl to the sea. Turtle life in sea is a transition between benthic and nekton. Turtles are good swimmers but often feed on benthic organisms. Among the birds, the penguins (Pygoscelidae) are closest to nekton. They breed on land but feed pelagically and often swim several 100 km to the open sea.

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Fig. 3.16 Meso- and bathypelagic teleost fish (source: Fig. 6.19 in Sommer 2005)

Mammalia. Aquatic mammals include Cetacea (whales; Fig. 3.17), Pinnipeda (seals), Sirenia (dugongs), and Lutrinae (otters). Only whales and dugongs live permanently in water. Dugongs are rather benthic, while whales are truly nekton. Dugongs and whales have no fur, because as permanently aquatic animals they do not need this kind of thermal isolation. Seals and otters have fur. Toothed whales (Odontoceti) are predators. They include dolphins, orcas, and the largest extant predatory animal, the sperm whale Physeter catodon (up to 18 m long, 50 tons). It is not only the largest predator but also the deepest diving lung breathing animal reaching depths of 2000 m. Most baleen whales (Mysticeti) are planktivorous, feeding mainly on macrozooplankton, e.g., krill. The largest extant animal belongs to the baleen whales, the blue whale, 30 m, 160 t (Balaenoptera physalis).

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Fig. 3.17 Whales: Mysticeti: Blue whale (Balaenoptera musculus), humpback whale (Megaptera novaeangliae); Odontoceti: Sperm whale (Physeter catodon), orca (Orcinus orca), pilot whale (Globicephala melaena) (source: Fig. 6.21 in Sommer 2005)

3.6.2

Swimming Behavior

Swarming Many nekton animals form swarms, often consisting of equal sized individuals. There is no social rank order in such swarms, as opposed to the family-based packs of whales which include adults and their progeny. Fish swarms show a coordinated behavior, which is based on a simple set of rules. Fish try to keep a constant distance to the fish before and aside. Fish turn to the left if the fish before or left of them turn left. Fish turn to the right if the fish before them or right of them turn right. This leads to abrupt turns of entire swarms if the fish in the front start turning. Swarming has several adaptive advantages. Predators targeting individual prey organisms have it more difficult to target these in a swarm (Ioannou et al. 2012). Finding of sexual partners becomes easier. It is easier to find favorable local conditions. If a swarm swims through an adverse water body (low oxygen, poor food conditions, etc.), the entire swarm will move into more favorable conditions if the fish on the front right or front left corner discovers a reason to change direction (Kils 1986).

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Vertical Migrations Mesopelagic fish often perform diel vertical migrations, staying at depth during daytime and nearer to the surface during nighttime (Mann 1984). During daytime mesopelagic nekton often stratify in a distinctive layer which can be detected by an echosounder (“deep scattering layer”). The adaptive value of daytime descent might lie in tracking the vertical migration of their zooplankton food or in the avoidance of visual predators during daytime in the well-illuminated surface zone. Migrations Related to the Life Cycle Many nekton organisms perform migrations related to shifts between feeding grounds and spawning/nursery grounds. Often these migrations extend over large distances. Migrations might be entirely within the ocean and within freshwaters or connect both realms. Typically, migratory behavior is connected with a high ability of homing, i.e., a return to the birthplace for reproduction (Keefer and Caudill 2014). Anadromous fish have their spawning grounds in rivers and their feeding grounds in the sea. Examples are the marine salmonids (e.g., Salmo salar, several Oncorhynchus spp., Salmo trutta, etc.), the sea lamprey (Petromyzon marinus), and many others. The Atlantic salmon (S. salar) may visit the spawning grounds several times while the Pacific salmons (Oncorhynchus spp.) migrate only once upstream and die after spawning. Catadromous migrations are the opposite pattern, with spawning grounds in the ocean and feeding grounds in freshwaters. The most spectacular examples of catadromous migrations are the eels (Box 3.4). Life cyclerelated migrations within the ocean are very common among all nekton groups. Examples at the opposite ends of the nekton size spectrum are the herring (Box 3.5) and the humpback whale (Box 3.6). Migrations in freshwater are common among lake dwelling salmonids, e.g., the lake morph of brown trout (Salmo trutta f. lacustris) migrates upstream to tributaries for spawning. Box 3.4 Migration of the European (Anguilla anguilla) and the American eel (Anguilla rostrata) The leptocephalus larvae of the European eel hatch from the eggs in the Sargasso Sea and are transported with the Gulf Stream to the European coasts during a journey of up to 3 years. When approaching Europe, they metamorphose to glass eels and migrate upward to freshwaters or the Baltic Sea, where they grow as “yellow eels” until adult size. At sexual maturity, there is a change of morphology from a yellow to a silver coloration, the eyes become bigger, and the guts disintegrate. These silver eels migrate back to the Sargasso Sea where they spawn and die after spawning. The American eels share the same spawning region, but the travel distance for the larvae to the river mouths on the American east coast is much shorter than the travel distance of the European eel. The migration of the European eel is considered a phylogenetic relict of the time when the distance between America and Europe was smaller because of the continental drift (Schmidt 1924) (Fig. 3.18).

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Fig. 3.18 Catadromous migrations of the European (Anguilla anguilla) and the American eel (Anguilla rostrate), the numbers on the contour lines indicate the length of leptocephalus larvae in mm, the black areas on the continents are the regions colonized by eel (source: Fig. 6.24 in Sommer 2005).

Box 3.5 Migration of Herring (Clupea harengus) in the North Sea and the NE Atlantic Ocean The herring stocks of the NE Atlantic Ocean and the North Sea consist of distinct populations which have their own spawning grounds, feeding grounds, and spawning times. The biggest stock, the Norwegian one, spawns near the Norwegian coast at 40–70 m depth between February and April. After two weeks the larvae hatch and float to surface waters where they become ca. 4 cm long during the first year. After 1–2 years, the herrings are ca. 30 cm long and move to the open ocean between Iceland, Svålboard, and the Faroe Islands. They start to return to the spawning grounds in late autumn and repeat (continued)

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Box 3.5 (continued) this migration annually during their ca. 25 years lifetime (Tait 1981) (Fig. 3.19).

Box 3.6 Migration of Humpback Whales (Megaptera novaeangliae) Baleen whales have the problem that, being endotherms, they should give birth in warm regions while the big swarms of macrozooplankton, e.g., krill, are found during the summer period in polar and subpolar oceans. The beststudied migrations are those of the humpback whales, because their migratory routes are relatively close to the coasts. Their winter habitats are often so close to the coasts that whale watching has become a tourist attraction. There are two reproductively isolated population in the Atlantic Ocean, one with summer feeding grounds in the Arctic and the other in the Antarctic. The reproductive isolation is caused by the fact that the Arctic and the Antarctic summer are shifted by half a year (Baker 1980).

3.7

Benthos on Hard Substrates

3.7.1

General Remarks

The ecology of benthos growing on solid surfaces has been one of the cornerstones in ecological research. The concept of ecological communities (then called “biocoenosis”), i.e., of the decisive role of interactions between different species sharing one habitat, goes back to the marine zoologist Möbius (1877) and his studies of oyster and mussel beds on the North German coasts. Benthos on hard substrates is also the most diverse diverse community in terms of higher taxa and life forms.

Motility Benthos contains completely sessile organisms, (e.g., macroalgae and sessile animals), slowly creeping organisms (e.g., sea urchins, snails), and organisms which at least temporarily move quite fast (e.g., bottom fish). Sessile animals are only found in benthos and not in terrestrial ecosystems. In most higher taxa, benthic organisms are less motile than their pelagic relatives. They are often also heavier than their relatives because they do not have to avoid sinking and can, therefore, afford heavily armored exoskeletons, like bivalves, gastropods, and many crustaceans. A sessile or slowly creeping lifestyle is not compatible with long-distance dispersal. Therefore, planktonic larvae of benthos often have the function of providing long-distance dispersal (meroplankton Sect. 3.5.3).

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Fig. 3.19 Migrations of NE Atlantic and North Sea herring stocks according to (Tait 1981). Cross hatched areas. Nursery grounds; roman numbers: months of spawning; full arrows: migration to spawning grounds; broken arrow: migrations to feeding grounds (source: Fig. 6.23 in Sommer 2005)

Physical Association to the Substrate Epibenthos Most hard substrate benthos live at the surface of the substrate, either firmly attached or moving in direct contact or close vicinity to the substrate. Biogenic substrates Surfaces of organisms, in particular hard shells, but also skins can be colonized by benthos just like primary substrates. A barnacle can grow as well on a mussel shell as on a rock; it can even grow on the skin of a whale or on the hull of a ship. The phenomenon that organisms can grow on other organisms is called epibiosis, e.g., the barnacle on the skin of whales. In this case, the whale is called “basibiont” and the barnacle “epibiont.” Epibiosis is particularly important in benthos, though it is also found elsewhere, e.g., epiphytes growing on trees. Erect growth forms of benthic organisms and epibiosis add a three-dimensional structure to the benthic habitat, offering not only attachment space for epibionts but also as shelter for motile organisms. Epibionts can serve as basibionts for further organisms; e.g., a macroalga growing on a mussel shell can serve as basibiont for filamentous algae which themselves are overgrown by diatoms. The most complex examples of 3D structures created by organisms are coral reefs and kelp forests.

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They are the aquatic counterparts of forests in the sense that organisms construct the physical structure of the habitat. Endobenthos Some specialized organisms, e.g., boring mussels and sponges, can penetrate the substrate for several dm and live within rocks. This is more common in limestone because it can be dissolved by the excretion of acids, as it is done by the mussel Lithophaga lithophaga. Penetration of siliceous rocks (e.g., the mussel Pholas dactylus) is much rarer and has to be performed mechanically. Boring organisms accelerate the erosion of rocks.

Size Classes Size classification in the benthological literature is usually less well elaborated than the one for plankton and the size demarcations are less uniform. The term microbenthos is either used for sizes 1 mm. During the last few decades, also the term megabenthos became increasingly used for much larger organisms.

3.7.2

Phytobenthos

Hard substrates are not colonized by flowering plants because their roots cannot penetrate rocks. Phytobenthos of hard substrates consists of Cyanobacteria and eukaryotic algae of various taxa, with particular importance of Chlorophyta (green algae), Rhodophyta (red algae), Phaeophyceae (brown algae), and Bacillariophyceae (diatoms). However, also flagellated taxa like Cryptophyta and Dinophyta are found swimming between the sessile benthos. Microphytobenthos Submerged surfaces are almost always coated by an assemblage of microorganism and a gelatinous matrix of excreted polymers. This assemblage is often called periphyton although not all components are photolithoautotrophic. It also contains bacteria, fungi, heterotrophic protist, and microscopic animals. Usually, diatoms, green algae, and Cyanobacteria are the most important primary producers in periphyton. Periphyton can grow on primary mineral substrates (epilithon), on phototrophs (epiphyton), or on animals (epizoon). Benthic microalgae reproduce similarly fast as phytoplankton with generation times of hours to days. Benthic diatoms (Fig. 3.20) can either be sessile, sitting on gelatinous stalks, or creep with the help of the raphe along solid surfaces. A special life form is represented by Berkeleya rutilans where hundreds of single cells live in a joint gelatinous tube which macroscopically resembles a filamentous alga.

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Fig. 3.20 Benthic diatoms (source: Fig. 7.1. in Sommer 2005)

Filamentous algae Filamentous algae are widespread on solid substrates in marine and freshwaters, including rivers. They belong to a wide array of higher taxa, Cyanobacteria, Chlorophyta, Rhodophyta, Phaeophyceae, and Xanthophyceae. Diatoms (e.g., Melosira) with a filamentous morphology are not really true filaments because there is no exchange of material between cells. In some filamentous taxa, there is a division of labor between cells. This division of labor can be a metabolic one, e.g., the heterocysts of Cyanobacteria which take up and assimilate N2 while they are supported with DOC from the other cells. Specialization of cells can also be related to reproduction when specific cells act as gametangia or sporangia. Macroalgae Macroalgae have a two- or three-dimensional thallus. This can be a complex of interwoven filaments (plectenchyma, e.g., in Rhodophyta) or a truly three-dimensional tissue (parenchyma, e.g., in Phaeophyta). Many macroalgae are perennial and live several years. The largest macrophytes, e.g., the giant kelp Macrocystis pyrifera, can reach up to 100 m length and form underwater forests. Contrary to terrestrial trees, macroalgae do not need woody support structures, because bladder like structures lighter than water (pneumatocysts) can stretch them upward toward increasing light.

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Complex macroalgae developed a morphology analogous to terrestrial plants with cauloids (counterparts of stems) and phyllodis (counterparts of leaves). The biggest functional difference is the one between the rhizoids of macroalgae and roots of higher plants. Rhizoids do not extract substances from the substrate in order to support the rest of the plant. They are just mechanic holdfasts to attach the macroalga to the substrate. Alternation between haploid gametophyte and diploid sporophyte generations is a widespread phenomenon in macroalgae. In some taxa, both are similar in size and morphology while in others there are conspicuous differences. Green macroalgae (Fig. 3.21) are widely distributed both in freshwater and in marine hard substrate benthos though the morphologically more complex ones are restricted to marine habitats. Red algae and brown algae are predominantly marine, though there are a few freshwater exceptions, e.g., the red alga Hildenbrandia forming dark red crusts on calcareous rocks in clear lakes and rivers and the branched red alga Batrachospermum and the brown alga Bodanella. Brown algae are the morphologically most complex algae. Brown algae are often the dominant algae of the rocky intertidal zones and form a characteristic zonation of vegetation dependent on resistance to periodic desiccation (Sect. 4.1.4). Typical genera of the intertidal are Pelvetia and Fucus. While most of the macroalgae just contain organic tissue, coralline red algae, e.g., Corallina and Lithothamnion, have calcareous incrustations. Members of the latter genus have formed calcareous rocks in the geological past.

3.7.3

Zoobenthos

Zoobenthos on solid substrates is the most diverse animal community in terms of higher taxa, but not in terms of species number because terrestrial insects outweigh all other animal groups in species number. Thus, even a short description of all animal groups in hard bottom benthos would become almost a textbook of special zoology. For this reason, only a few selected taxa shall be highlighted which play a central role in hard bottom benthos research. Since heterotrophic protists played a much lesser role in benthos research than in plankton research, this overview will concentrate only on the most important phyla of animalia. Sessile animals are a life form restricted to the benthos and not found on land. The reason of this restriction lies in the possibility of suspension feeding, i.e., taking POC, mostly plankton, from water currents. Air does not contain enough suspended POC to make suspension feeding a viable option. Porifera (sponges) are exclusively benthic and most of them are marine, although there are also a few freshwater taxa. Sponges are suspension feeders; i.e., they take up small food particles (usually plankton) from a feeding current. This current is created by a specific flagellated cell type, choanocytes. The water current enters the sponge through small pores, passes through a system of cavities, and leaves the sponge through a central large opening (Fig. 3.22, top). The body is stiffened by

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10cm

Chlorophyta

5cm

Caulerpa prolifera

Acetabularia acetabulum

Halimeda tuna

Rhodophyta

Ulva lactuca

5cm Lithothamnion crassum

Phyllophora rubens

Chondrus crispus

5cm Dictyota dichotoma

1m

Pn cy eum st at

o

Phaeophyta

Nemalion multifidum

10cm Fucus vesiculosus

Macrocystis pyrifera

Laminaria hyperborea

Fig. 3.21 Green, red, and brown algae of macrobenthos (sources: Figs. 7.3, 7.4, and 7.5 in Sommer 2005)

3.7 Benthos on Hard Substrates

95 Haliclona oculata Demospongiae

general scheme

chamber with choanocytes Verongia aerophoba Demospongiae

Sertularia cupressina Hydrozoa

Sycon coronatum Calcarea

Actinia aurantiaca Anthozoa

tentacele mouth

general scheme

1cm

10 cm

gastral cavity

5 cm

Aurelia aurita Scyphozoa

Caryophyllia caespitosa Anthozoa

Fig. 3.22 Porifera (top) and Cnidaria (bottom) of the benthos. In the case of Aurelia, only the polyp is shown because the medusa stage is pelagic (sources: Figs. 7.9 and 7.10. in Sommer 2005)

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needles, which are calcareous (Calcarea), siliceous (Hexactinellidae), or combine SiO2 with spongin, a horn-like protein (Demospongiae). Cnidaria have no guts with two openings but just a sack-like gastral cavity with only one opening. The mouth is surrounded tentacles containing cnidocytes which inject venom into the skin of prey when getting in contact. There are two life forms, sessile polyps, and drifting medusae. The classes Hydrozoa and Scyphozoa perform an alternation of generations between the sexual medusa and the vegetative polyp stage. The class Anthozoa has no medusa stage and are sessile throughout their lives except for their planktonic larvae. In the case of colonial Anthozoa, the foundation polyp results from sexual reproduction, while all other polyps in the colony result from vegetative budding. Stony corals are the most important reef builders and have formed limestone rocks over geological time scales. Many sessile Cnidaria have endosymbiotic algae (zooxanthellae, the dinoflagellate genus Symbiodinium) and are functionally mixotrophic. Most of the cnidaria are marine, but there are a few freshwater representatives. Anthozoa are exclusively marine. Mollusks (Fig. 3.23) on solid substrate benthos are represented by the classes Polyplacophora (chitons), Gastropoda (snails and slugs), Bivalvia (bivalves), and Cephalopoda, among them mainly the Octopoda. Chitons, snails, and bivalves have a hard shell formed of aragonite (CaCO3). Slugs have either no shell or a very reduced one. Some snails are almost sessile, creeping only slowly and occasionally (e.g., limpets, Patella); others are slowly mobile (e.g., periwinkles, Littorina). Slugs and octopuses are more mobile. Bivalves are sessile, either bound to the substrate by byssus filaments (Mytilus, blue mussel) or cemented to the rocks (oyster, Ostrea).

Fig. 3.23 Mollusks of solid substrate benthos (source: Fig. 7.12 in Sommer 2005)

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Fig. 3.24 Arthropoda of solid substrate benthos (source: Fig. 7.13 in Sommer 2005)

Some of them are also penetrate rocks (Lithophaga, Pholas). Bivalve shells can become substrate for the attachment of other individuals and, thereby, form mussel beds. Arthropoda (Fig. 3.24) are mainly represented by Crustacea. Their body consists of three parts, the head carrying the antenna and the mouth appendages (mandibles, maxillae), the thorax with the legs, and the abdomen (tail). In motile species, the thorax legs are responsible for locomotion. In sessile taxa (Cirripedia, barnacles), the legs are used for suspension feeding. Isopoda, Amphipoda, and small, transparent representatives of the Decapoda (shrimps) are only slightly armored while large decapods (lobsters, crabs, crayfish, etc.) are heavily armored and can, for example, break shells of mollusks. Echinodermata are an exclusively marine phylum. The body has an exoskeleton of chitin which is calcified in many species. Most of them are slowly creeping animals; only the Crinoidea are sessile, stalked organisms, while Asteroidea (starfish), Ophiuroidea (brittle stars), Echinoidea (sea urchins), and Holothurioidea (sea cucumbers) move with their tube feet. The tube feet have an end similar to a suction pad in which under-pressure can be created for adhesion. The tube feet are connected to the water vascular system, a network of water-filled canals which serves for gas exchange, feeding, and locomotion. This system is not found in other animal groups. Chordata are represented by sessile Tunicata (class Ascidiacea) and Pisces. The morphology of benthic fish is far more diverse than the morphology of pelagic fish (Fig. 3.25). The structural complexity of the habitat (caves and crevices in rocks,

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Fig. 3.25 Fish of solid substrate benthos (source: Fig. 7.16 in Sommer 2005)

shelter between sessile animal and macrophytes, free water above the rocks) offers a multitude of morphological adaptations to the habitat, including camouflage for avoiding predation or for sitting and waiting for prey.

3.8

Benthos of Soft Substrates

3.8.1

General Remarks

Soft bottoms are far more widespread than hard bottoms. While hard substrates are restricted to rocky shores, steep underwater slopes, and fast-flowing rivers, most of the ocean and lake bottom are covered by sand or mud.

Size Classes Conventional size classifications are the same as for hard substrate benthos: macrobenthos < 0.1 (0.2) mm, meiobenthos < 0.1 (0.2) to 1 (2) mm, and macrobenthos > 1 (2) mm. Physical Association to Substrate We distinguish organisms living on sediment surfaces (epibenthic) or within the sediment (endobenthic). Depending on the preference between sand and mud, the following categories can be made:

3.8 Benthos of Soft Substrates

• • • •

99

Endopsammic: living within sand Epipsammic: living on sand Endopelic: living within mud Epipelic: living on mud

3.8.2

Phytobenthos

Microalgae Practically all taxa of unicellular algae are represented in soft substrate benthos. They live at or slightly below the surface of sediments within the euphotic zone. Usually, the Bacillariophyceae are the most important group. Sessile diatoms are primarily found on sandy sediments. They are attached to sand grains by either gelatinous pads or stalks. Motile diatoms are found both in/on muddy and sandy sediments. They can perform light- and tide-dependent vertical migrations of a few mm or cm amplitude and shift between an epi- and endobenthic living mode. Filamentous Algae Filamentous algae on soft bottoms belong mainly to Cyanobacteria, Chlorophyta, and Phaeophyta. Together with heterotrophic bacteria, Cyanophyta can form dense microbial mats which consolidate the sediment and decrease the mobilization of sediments by currents and waves (Krumbein et al. 1994). Other filamentous algae, like the brown alga Pilayella and the green algae Enteromorpha, Cladophora, Spirogyra, etc., form looser mats overlying the substrates. Initial growth often starts on solid substrates, e.g., pebbles or mussel shells, but detached mats might cover large areas of the sediments. In lakes, sometimes such mats start to float and drift in the open water. Macroalgae There are far less macroalgal taxa on sediments than on hard substrates. A marine exception is the green alga Caulerpa which can form extended meadows by vegetative budding from horizontal stolons below the sediment surface. These stolons differ from roots of higher plants because they play no role in the nutrition of the pant. Charophyceae (stoneworts) are a class of morphologically relatively complex green algae forming dense meadows in clear, nutrient-poor lakes. Mosses Water mosses (e.g., Fontinalis, Riccia) are freshwater plants found in clear lakes and low-order streams. Locally, they play an important role in the formation of tufa by calcite precipitation (Box 2.1). Flowering Plants Flowering plants are far more common in fresh than in marine waters. The only marine exception are the seagrasses (Zostera, Posidonia, Fig. 3.26). They have rhizomes (underground stem) and roots underground. The horizontally growing

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Fig. 3.26 Seagrass (source: Fig. 8.1 in Sommer 2005)

rhizomes are perennial. The leaves grow annually from the rhizomes. The rhizomes serve for anchoring, while the roots also supply the plants with nutrients from the interstitial water. Like in many other submerged water plants, vegetative reproduction is more important than sexual reproduction. In freshwaters, there are different life forms of water plants: • Emergent plants which are rooted below water but extend into air, e.g., Phragmites (reed), Typha (cattail) • Rooted, submerged plants, e.g., Potamogeton (pondweed), Myriophyllum (water milfoil) • Rooted plants with floating leaves, e.g., Nymphaea (water lily) • Unrooted submerged plants, e.g., Ceratophyllum (hornwort) • Floating plants, e.g., Lemna (duckweed), Eichhornia (water hyacinth)

3.8.3

Zoobenthos

Protists Most, if not all, higher protist taxa have representatives in or on the sediment. They range from ca. 2 μm to several cm. Contrary to plankton, the role of nano-sized heterotrophic protists has not yet received strong attention in ecological research. It is not clear whether they will ever reach the same degree of attention as HNF in plankton ecology. Larger heterotrophic protists, however, have received some

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Fig. 3.27 Depth distribution of interstitial ciliates (data from Fenchel 1969) and nematodes (data from Jensen 1987) in relation to vertical redox profile (source: Fig. 8.10 in Sommer 2005)

attention. This is particular the case with Foraminifera, a group of Rhizopoda with calcareous shells. These are important in paleontology, paleoecology, and a formation of rocks because of having formed limestone in the geological past. Most foraminifera are within the meiobenthos size range, but some reach a few cm. A similar size range is also occupied by benthic ciliates. Foraminifera are exclusively marine, while ciliates are found both in fresh and marine waters. Endobenthic ciliates show distinctive vertical distributions related to the redox gradient in the sediment (Fenchel 1969, Fig. 3.27, left).

Metazoan Meiofauna While the conventional size limits of meiofauna vary in the literature, there is an ecologically relevant functional definition. Sediment meiofauna are those animals which move within the interstitial space without being able to dig or to displace sediment grains for creating living space. Characteristic adaptations for the ability to move within the interstitial space are (Giere 1993) (Fig. 3.28): • Small size. Representatives of the interstitial fauna are smaller than their relatives in other habitats, cf. mean sizes of copepod species: interstitial: 0.5 mm, sediment surface, 0.8 mm, plankton: 1.4 mm. • Elongate, thin body shape: While many animals have length: width ratios in the range 3:1 to 10:1, interstitial animals can have length: width ratios up to 100:1. • Flexibility is needed because the interstitial space does not consist of straight channels. • Adhesion organs for temporary attachment to sand grains are widespread among interstitial animals.

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Fig. 3.28 Endobenthic meiofauna (source: Fig. 8.7 in Sommer 2005)

There are a few species-poor taxa almost exclusively represented by interstitial animals, e.g., the classes Gnathostomulida, Kinorhyncha, Loricifera, and Tardigrada. However, these are usually not the most abundant taxa. Nematoda (phylum Nemathelminthes, roundworms) make up for >60% of the number of individuals and >90% of the biomass in many meiofauna samples. The other abundant groups are Turbellaria (phylum Platyhelminthes, flat worms) and the copepod suborder Harpacticoida. Some taxa show high tolerance to anoxic

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103

conditions and even the presence of H2S and are, therefore, found at low redox potentials (Reise and Ax 1979; Giere 1992) (Fig. 3.27, right).

Endobenthic Macrofauna Endobenthic animals (“infauna”) are either completely buried or semi-buried covered by a thin layer of sediment for camouflage. Buried animals have the problem of oxygen supply, which they solve either by generating a water current through burrows (e.g., Arenicola, lugworm) or by extending siphons to the sediment surface (e.g., burrowing bivalves) (Fig. 3.29). The most important groups of the endobenthic macrofauna are: Polychaeta are a key group of marine sediment infauna. Many species form burrows and feed as sediment feeders, e.g., Arenicola and Heteromastus. They ingest sediment including the attached organisms, digest the organic matter, and egest the inorganic sediment together with the feces. Some polychaetes, however, are predators (e.g., Nereis). Bivalves. Buried bivalve have long siphons to suck in water from above the sediment for the supply of food (suspended POC) and oxygen. Marine examples are Mya, Cerastoderma, and Rudatipes; freshwater examples are Anodonta and Unio. Endobenthic fish form burrows and live there or are only semi-endobenthic, partially covered by a thin layer of sediment for camouflage while resting (e.g., flatfish like plaice, Pleuronectes) while they move at the sediment surface for escape and for search of food. Pectinaria koreni

Mya arenaria

Arenicola marina

Angulus fabula

Fig. 3.29 Endobenthic macrofauna, the polychaetes (Pectinaria, Arenicola) and bivalves Mya and Angulus (source: Fig. 4.16 in Sommer 2005)

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Epibenthic Macro- and Megafauna There are gradual transitions between endo- and epibenthos as well as between epibenthos and nekton. Example for the former transition are the predatory polychaete Nereis and semi-buried flatfish. Examples for the benthos–nekton transition are demersal fish (Fig. 3.30). Polychaeta: Besides motile polychaetes like Nereis, there are also sessile, tubedwelling ones (e.g., Lanice, Sabella, Serpula). They are suspension feeders capturing small food particles with their tentacles. Crustacea are represented mainly by crabs, e.g., the Carcinus maenas (green crab) and shrimps, Crangon crangon (brown shrimp). Typical Mollusca of the sediment epifauna are the gastropod Hydrobia, the bivalve Pinna (pen shell), and the cephalopod Sepia (cuttlefish). Echinodermata on the sediment surface are Ophiuroidea (brittle stars) and Holothuroidea (sea cucumbers). Pisces. There are all kinds of transitions between an endobenthic, epibenthic, and nektonic lifestyle among fish. Fish of the family Triglidae (gurnards) are closest to epibenthic in a strict sense. Swimming consist only of short “jumps” above the sediment. Mainly, they use the rays of the pectoral fins to walk over the sediment surface. Lanice conchilega polychaeta

Pinna nobilis Bivalvia

Sepia officinalis Cephalopoda

1cm Carcinus maenas Crustacea

10cm

5cm

10cm

10cm Trigla hirundo Pisces

Fig. 3.30 Epibenthic macrofauna (source: Fig. 8.9 in Sommer 2005)

3.8 Benthos of Soft Substrates

3.8.4

105

Bacteriobenthos

Sediments contain the biggest diversity of bacterial metabolic types within small spatial scales because of pronounced redox gradients over short distances.

Heterotrophic, Aerobic Bacteria The sediment catches the entire load of sinking organic particles which are not re-mineralized during the sinking process. The concentration of dissolved organic substances at the sediment surface and within the sediment is at least 3 orders of magnitude higher than in the pelagic water (g L-1 instead of mg L-1). Accordingly, bacterial numbers are much higher in the sediment (108 to 1011 mL-1) than in the open water (around 106 mL-1). Mud is richer in bacteria than sand because of the higher content of organic matter. Fresh sediment particles are colonized quickly by bacteria. First, a “clean” particle is covered by a conditioning film of organic macromolecules originating from porewater. Then, this film is colonized by bacteria which produce extracellular polymeric fibers which bind themselves to the grain surface by bivalent cations (Wahl 1989). The bacteria themselves cover 2 cm meiobenthos benthos 100(200) μm–1(2) mm meroplankton organisms with part of their life cycle in plankton microbenthos benthos N-based and for S-based chemosynthesis? 47. Compare the larval and the adult life spans of aquatic insects. 48. How do stream insects cope with the problem of the downstream drift of larvae? 49. Which aquatic insects can cause human health problems?

111 Section 3.8.4 3.8.4 3.8.4 3.8.4 3.9 3.9.1 3.9.2

References Alldredge AL (1977) House morphology and mechanisms of feeding in the Oikopleuridae (Tunicata, Appendicularia). J Zool Lond 181:175–188 Atkinson MJ, Smith SV (1983) C:N:P ratios of marine plants. Limnol Oceanogr 28:568–574 Azam F, Fenchel T, Field JG, Ray JS, Meyer-Reil LA, Thingstad F (1983) The ecological role of water-column microbes in the sea. Mar Ecol Progr Ser 10:257–263 Baker CS (1980) Whale migrations. Mother (Nature) calls. Nat Geogr Mag 178 Båmstedt U (1986) Chemical composition and energy content. In: Corner EDS, O’Hara SCM (eds) Biological chemistry of marine copepods. Oxford University Press, Oxford, pp 1–58 Bergh O, Børsheim KY, Bratbak G, Heldal M (1989) High abundances of viruses found in aquatic environments. Nature 340:467–469 Bi R, Arndt C, Sommer U (2012) Stoichiometric responses of phytoplankton species to the interactive effect of nutrient supply rates and growth rates. J Phycol 48:539–549 Bratbak G, Jacobsen A, Heldal M, Nagasaki K, Thingstad F (1998) Virus production in Phaeocystis pouchetii and its relation to host cell growth and nutrition. Aquat Microb Ecol 16:1–9 Brown JH, Gillooly JF, Allen AP, Savage VM, West GB (2004) Toward a metabolic theory of ecology. Ecology 85:1771–1789 Bruning K (1991) Effects of phosphorus limitation on the epidemiology of a chytrid phytoplankton parasite. Freshwat Biol 25:409–417 Droop MR (1983) 25 years of algal growth kinetics. Bot Mar 26:99–112 Eggleton P, Gaton KJ (1990) “Parasitoid” species and assemblages: convenient definitions or misleading compromises? Oikos 59:417–421 Elser JJ, Urabe J (1999) The stoichiometry of consumer-driven nutrient recycling: theory, observations, and consequences. Ecology 80:735–751 Elser JJ, Dobberfuhl D, McKay NA, Schampel JH (1996) Organism size, life history, and N:P stoichiometry: towards a unified view of cellular and ecosystem processes. Bioscience 46:674– 684 Elser JJ, Fagan WF, Denno RF, Dobberfuhl DR, Folarin A, Huberty A, Interlandi S, Kilham S, McCauley E, Schulz KL, Siemann EH, Sterner RW (2000) Nutritional constraints in terrestrial and freshwater food webs. Nature 408:578–580 Ernest SKM, Enquist BJ, Brown JH, Charnov EL, Gillooly JF, Savage V, White EP, Smith FA, Hadly EA, Haskell JP, Lyons SK, Maurer BA, Niklas KJ, Tiffney B (2003) Thermodynamic and metabolic effects on the scaling of production and population energy use. Ecol Lett 6:990– 995

112

3

Life Forms of Aquatic Organisms

Fenchel T (1969) The ecology of marine microbenthos. IV. Structure and function of the benthic ecosystem, its chemical and physical factors, and the microfauna communities with special reference to the ciliate protozoa. Ophelia 6:1–182 Flynn KJ, Mitra A et al (2019) Mixotrophic protists and a new paradigm for marine ecology: where does plankton research go now? J Plankton Res 41:375–391 Fuhrman JA (1999) Marine viruses and their biogeochemical and ecological effects. Nature 399: 541–548 Fulton J (1973) Some aspects of the life history of Calanus plumchrus in the Strait of Georgia. J Fish Res Bd Can 30:811–815 Geller W (1975) Die Nahrungsaufnahme von Daphnia in Abhängigkeit von der Futterkonzentration, der Körpergröße und dem Hungerzustand der Tiere. Arch Hydrobiol Suppl 48:47–107 Geller W, Müller H (1985) Seasonal variability in the relationships between body length and individual dry weight and individual dry weight as related to food abundance and clutch size in two coexisting Daphnia species. J Plankton Res 7:1–18 Giere O (1992) Benthic life in sulfidic zones of the seas - ecological and structural adaptations to a toxic environment. Verh Dtsch Zool Ges 85:77–93 Giere O (1993) Meiobenthology. Springer, Berlin Gillooly JF, Brown JH, West GB, Savage VM, Charnov EL (2001) Effects of size and temperature on metabolic rate. Science 293:2248–2251 Goldman JC, McCarthy JJ, Peavey DG (1979) Growth rate influence on the chemical composition of phytoplankton in oceanic waters. Nature 279:210–215 Gustavsen JA, Winget DM, Tian X, Suttle CA (2014) High temporal and spatial diversity in marine RNA viruses implies that they have an important role in mortality and structuring plankton communities. Front Microbiol 5:703 Hemmingsen A (1960) Energy metabolism as related to body size and respiratory surface, and its evolution. Report of Steno Memorial Hospital (Copenhagen) 9:1–110 Hobbie JB, Daley RJ, Jasper S (1977) Use of nuclepore filters for counting bacteria by fluorescence. Appl Environ Microb 33:1225–1228 Hochstädter S (2000) Seasonal changes of C:P ratios of seston, bacteria, phytoplankton and zooplankton in a deep, mesotrophic lake. Freshw Biol 44:453–463 Holfeld H (1998) Fungal infections of the phytoplankton: seasonality, minimal host density, and specificity in a mesotrophic lake. New Phytol 138:507–517 Ioannou CC, Guttal V, Couzin ID (2012) Predatory fish select for coordinated collective motion in virtual prey. Science 337:1212–1215 Jensen P (1987) Differences in microhabitat, abundance, biomass and body size between oxybiotic and thiobiotic free-living marine nematodes. Oecologia 71:564–567 Keefer ML, Caudill CC (2014) Homing and straying by anadromous salmonids: a review of mechanisms and rates. Rev Fish Biol Fish 24:333–368 Kils U (1986) Verhaltensphysiologische Untersuchungen pelagischen Schwärmen, Schwarmbildung als Strategie zur Orientierung in Umweltgradienten, Bedeutung der Schwarmbildung in der Aquakultur. Ber Inst Meereskunde, Kiel 163:1–168 Krumbein WE, Paterson DM, Stal LJ (1994) Biostabilization of sediments. BIS-Verlag, Oldenburg Mann KH (1984). Fish production in open ocean ecosystems. In: Fasham MJR (ed) Flows of energy and materials in marine ecosystems. NATO Conf Ser 4, Mar Sci V. Plenum, New York, pp. 435–458 Marañón E (2015) Cell size as a key determinant of phytoplankton metabolism and community structure. Annu Rev Mar Sci 7:241–264 Mateus MD (2017) Bridging the gap between knowing and modeling viruses in marine systems— an upcoming frontier. Front Mar Sci 3:284 McNeal KH, Peckarsky BI, Likens GE (2005) Stable isotopes identify dispersal patterns of stonefly populations living along stram corridors. Freshw Biol 50:117–130 Möbius K (1877). Die Auster und die Austernwirtschaft. Wiegandt, Hemple & Parey: Berlin. English translation: The Oyster and Oyster Farming. U.S. Commission Fish and Fisheries Report (1880) 683–751

References

113

Moustaka-Gouni M, Kormas KA, Scotti M, Vardaka E, Sommer U (2016) Warming and acidification effects on planktonic heterotrophic pico- and nanoflagellates in a mesocosm experiment. Protist 167:389–410 Peters RH (1983) The ecological implications of body size. Cambridge University Press, Cambridge Proctor LM, Fuhrman JA (1990) Viral mortality of marine-bacteria and cyanobacteria. Nature 343: 60–62 Redfield AC (1934) On the proportions of organic derivatives in seawater and their relation to the composition of plankton. In: Daniel RJ (ed) James Johnstone memorial volume. Liverpool University Press, Liverpool, pp 176–192 Redfield AC, Ketchum BH, Richard FA (1963) The influence of organisms on the composition of seawater. In: Hill MN (ed) The Sea. Wiley, NY, pp 26–77 Rees HC, Maddison BC, Middleditch DJ, Patmore JR, Gough KC (2014) Review: the detection of aquatic animal species using environmental DNA - a review of EDNA as a survey tool in ecology. J Appl Ecol 51:1450–1459 Reise K, Ax P (1979) A meiofaunal “thiobios” limited to the anaerobic sulfide system of marine sand does not exist. Mar Biol 54:225–237 Schmidt J (1924) The breeding of the eel. Smithonian Report, Washington Sieburth JMN, Smetacek V, Lenz J (1978) Pelagic ecosystem structure: heterotrophic compartments of the plankton and their relationship to plankton size fractions. Limnol Oceanogr 23:1256–1263 Sommer U (1988a) Does nutrient limitation of phytoplankton occur in situ? Verh internat Verein Limnol 23:707–712 Sommer U (1988b) Some size relationships in phytoflagellate motility. Hydrobiologia 161:125–131 Sommer U (1991) A comparison of the Droop and Monod models of nutrient limited growth applied to natural population of phytoplankton. Funct Ecol 5:535–544 Sommer U (1994) Planktologie. Springer, Berlin Sommer U (2005) Biologische meereskunde, 2nd edn. Springer, berlin, Heidelberg, New York Sommer U, Stibor H (2002) Cladocera – Copepoda – Tunicata: the role of three major mesozooplankton groups in pelagic food webs. Ecol Res 17:161–174 Sommer U, Charalampous E, Genitsaris S, Moustaka-Gouni M (2017) Benefits, costs and taxonomic distribution of marine phytoplankton body size. J Plankton Res 39:494–508 Stern R, Kraberg A, Bresnan E, Kooistra WHCF, Lovejoy C, Montresor M, Moran XAG, Not F, Salas R, Siano R, Vaulot D, Amaral-Zettler L, Zingone A, Metfies K (2018) J Plankton R 40: 519–539 Sterner RW, Elser JJ (2002) Ecological stoichiometry. Princeton University Press, Princeton, NJ Sutcliffe WHJ (1970) Relationships between growth rate and ribonucleic acid concentration in some invertebrates. J Fish Res Boar Can 27:606–609 Suttle CA (2005) Viruses in the sea. Nature 437:356-351 Tait RV (1981) Elements of marine ecology, 3rd edn. Butterworths, London Utermöhl H (1958) Zur Vervollkommnung der quantitativen Phytoplanktonmethodik. Mitt internat Verein Limnol 9:1–38 Veldhuis MUV, Kraay GW (2000) Application of flow cytometry in marine phytoplankton research: current applications and future perspectives. Sci Mar 64:121–134 Wahl M (1989) Marine epibiosis. I. Fouling and antifouling. Some basic aspects. Mar Ecol Progr Ser 58:175–189 Walsby AF, Reynolds CS (1980) Sinking and floating. In: Morris I (ed) The physiological ecology of phytoplankton. Blackwell, Boston, pp 371–412 Ward BB (2013) How nitrogen is lost. Science 341:352–353 West GB, Brown JH, Enquist BJ (1999) The fourth dimension of life: fractal geometry and allometric scaling of organisms. Science 284:1677–1679 Zwart G, Crump BC, Agterveld MPKV, Hagen F, Han SK (2002) Typical freshwater bacteria: an analysis of available 16S rRNA gene sequences from plankton of lakes and rivers. Aqu Microb Ecol 28:141–155

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Contents 4.1 Coping with the Abiotic Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1.1 The Optimum Curve . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1.2 Temperature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1.3 Salinity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1.4 Desiccation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Nutrition and Growth of Autotrophs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.1 Light and Photosynthesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.2 Mineral Nutrients . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.3 Chemolithoautotrophy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Nutrition and Growth of Heterotrophs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.1 Osmotrophy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.2 Phagotrophy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Dissimilatory Metabolism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4.1 Aerobic Respiration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4.2 Anaerobiosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Glossary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Exercise Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

117 117 118 125 127 128 128 135 142 145 145 147 155 155 157 159 161 163

Abbreviations A AQ C E E E0 Ei Ek Em

assimilation rate assimilation efficiency clearance rate activation energy (eV . . . 1 eV = 96.49 kJ mol-1) irradiance surface irradiance irradiance at the onset of inhibition irradiance at the onset of saturation mean irradiance of a mixed surface layer

# The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 U. Sommer, Freshwater and Marine Ecology, https://doi.org/10.1007/978-3-031-42459-5_4

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116

F I I ILL k k K km ks P P pi Pmax Q Q0 ri S T v vmax W zm α μ μmax

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food concentration ingestion rate physiological rate incipient limiting level attenuation coefficient Boltzmann constant (8.617343 10-5 eV K-1) half saturation constant of P–I curve half saturation constant of uptake half saturation constant of nutrient-limited growth production rate rate of photosynthesis relative abundance of food type i in environment maximal rate of photosynthesis cell quota of a nutrient minimal cell quota relative abundance of food type i in diet nutrient concentration in water absolute temperature in Kelvin (K = °C + 273.16) uptake rate maximal uptake rate selectivity coefficient sensu Vanderploeg and Scavia mixed layer depth Initial slope of P–I curve growth rate maximal growth rate

Summary How do individuals survive, develop, and grow in their environment? The multitude of challenges falls into two major categories: Coping with the abiotic environment, i.e., basically the physical (e.g., temperature, pressure, wave energy) and chemical conditions (e.g., salinity) which set limits to survival and may be more or less favorable within those limits. Beyond survival of abiotic stressors, organisms also have to extract resources from their environment, i.e., energy and substances needed for the production of their own body mass and for supporting their activity. At the same time, also materials are returned to the environment, consisting of “wastes,” i.e., end products of metabolism, and of architectural material, e.g., substances to build shells, reefs, etc. The matter and energy exchange (continued)

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with the environment is coupled to an internal transformation of matter and energy, called metabolism. There are two main categories of metabolic transformations: The processes building up biomass, called anabolism or assimilatory metabolism, and those processes which gain energy for maintenance and activity, called catabolism or dissimilatory metabolism.

4.1

Coping with the Abiotic Environment

4.1.1

The Optimum Curve

No species or genotype can survive and thrive everywhere. There are environmental conditions where they grow optimally, others where they just survive, and still others where they do not survive. While some of the environmental factors decisive for the well-being of a species relate to nutrition and other resources for metabolism, others are physical and chemical properties of the environment, such as temperature, salinity, and pH. The optimum curve (Fig. 4.1) is a way to relate the well-being of a species to a single physical or chemical environmental factor, assuming that the other factors do not impose any restrictions on the well-being. The curve is constructed by plotting a measure of the environmental factor on the x-axis and a measure of well-being at the y-axis. The curve is characterized by three cardinal points: The peak of the curve is called optimum and the intersection points with the x-axis tolerance limits, the terms “minimum” and “maximum” characterizing the lower and upper tolerance limit. The optimum curve may be symmetric or not. Symmetry is often just a consequence of the scaling of the x-axis (liner, logarithmic, etc.). There is also some discussion whether a one-point optimum or a flat plateau would be a better representation of reality. The regions between the plateau and the tolerance limits are called pejus regions. In practice, the scatter of real data makes decision between a point optimum and a plateau difficult. Mathematically, single equations fitted to data can have only a single point optimum. It is commonplace to distinguish between an ecological and a physiological optimum curve. The ecological curve is derived from distributions and abundances in nature. The physiological curve is derived from experimental measurements of well-being at the level of individuals (large organisms) or experimental populations (microorganisms). Physiological optimum curves are a special case of what is called reaction norm in genetics. The independent variable can be any measure of wellbeing, like production rates, growth rates, or reproduction-related parameters. Lethal limits can be explored by survivorship experiments. Obviously, the ecological tolerance limits have to be much narrower than the physiological tolerance limits, because successful establishment of a local population requires more than survival or some minimal level of reproduction. It requires reproduction rates at least in balance with mortality rates caused by senescence, predation, disease, etc.

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Fig. 4.1 Ecological and physiological optimum curves (source: Fig. 5.1 in Sommer 2005)

Ecological Niche The ecological niches of organisms are defined by mapping ecological and physiological tolerance curves related to several (N) environmental factors to an N-dimensional hyperspace. The fundamental niche of a species is derived from the physiological optimum curves in response to abiotic factors and from resource requirements, e.g., light and nutrients for phototrophs and food for animals. In the absence of negative effects of other organisms (Chap. 6), the entire fundamental niche could be occupied by the species. However, negative effects of other species, such as competition and predation, reduce the actual range of occurrence. This is called the realized niche (Hutchinson 1958). Let us consider two niche dimensions for simplicity: If tolerances to two environmental factors do not influence each other, the niche would be rectangular in a two-dimensional niche space. However, it is easy to understand that tolerance to factor 2 becomes less if factor 1 is already close to the tolerance limit. In such a case, the shape of a two-dimensional niche would be something between a rectangle with rounded corners and an ellipse, depending on the extent of interactions between both environmental factors (Fig. 4.2). With more complex and unknown interactions between environmental factors, even irregular geometries of the niche are possible (Blonder 2018).

4.1.2

Temperature

Moderate Variability of Temperature Aquatic habitats are thermally benign compared to terrestrial ones. The freezing temperature of water sets a lower limit of temperatures while more than 40 °C are rarely found in sun-heated surface waters. In contrast, air temperatures on land vary

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Fig. 4.2 Relationship of the niche to tolerance limits (MIN, MAX) of environmental factors, shown for 2 environmental factors (x, y) with elliptic (red) and irregular niche limits (green)

between -70 °C and +58 °C. Seasonal and short-term temperature changes are also less pronounced in water than in air. Higher temperatures than in sun-heated waters are found in hot springs, but their temperatures are quite constant in time, thus permitting specialization of heat-tolerant organism. Most of the extremely heattolerant organisms belong to the Archaea. Stronger temperature variability than under water can be expected during the tidal dry phase in intertidal zones with air temperatures below the freezing point in winter and strong solar heating in summer.

Thermal Optima and Environmental Temperature Ecological and physiological temperature optima do not always coincide, in particular among species living in extreme environments. El-Sayed and Taguchi (1981) assembled data on the temperature dependence of phytoplankton maximal growth rates from Antarctic and cold-temperate species. In situ, the Antarctic species experience temperatures between -1.9 and 1 °C, but their temperature optima were in the range of 2.5 and 7 °C, while the optimum curves of the cold-temperate species better coincided with the environmental temperature ranges (Fig. 4.3). Temperature Dependence of Metabolic Rates The velocity of chemical reactions increases with temperature. The same principle is true for physiological and biochemical rates, however only below the temperature optimum. Above the temperature optimum, imbalances in demand and supply of substances within the body and stability problems of enzymes decrease physiological functions (Box 4.1, aerobic scope). At temperatures well below the optimum, the increase of reaction velocities with temperature can be described by a rule of thumb,

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Fig. 4.3 Maximal growth rate of Antarctic (broken line) and cold-temperate (full lines) phytoplankton depending on temperature (source: Fig. 3.1 in Sommer 2005 based on data from Durbin 1974, El-Sayed and Taguchi 1981, Jacques 1983, Smayda 1969)

the Van’t Hoff rule: any temperature increase by a constant linear increment leads to the multiplication of the reaction velocity by a constant factor. For a temperature increment of 10 °C, this factor is called Q10. Q10 values for different physiological processes range from 0 to 4, with a tendency toward higher values for heterotrophic processes than for photoautotrophic ones (Sommer and Lengfellner 2008): • No temperature dependence for light-limited photosynthesis (Q10 = 0) (Tilzer et al. 1986) • Light saturated photosynthesis: Q10 = 1.88 (Eppley 1972) • Microalgal respiration: Q10 = 2.6–5.2 (Hancke and Glud 2004) • Zooplankton respiration: Q10 = 1.8–3.0 (Ivleva 1980; Ikeda et al. 2001) • Zooplankton filtration rates: Q10 = 2–3 (Prosser 1973) • Bacterial respiration: Q10 = 3.3 (Sand-Jensen et al. 2007) The Arrhenius equation is a description of the temperature dependence of physiological rates which is more in line with general principles of physical chemistry: I = ae - E=k T

ð4:1Þ

I: physiological rate E: activation energy (eV . . . 1 eV = 96.49 kJ mol-1) k: Boltzmann constant (8.617343 10-5 eV K-1) T: absolute temperature in Kelvin (K = °C + 273.16) For calculating E by linear regression analysis, the following transformations of the axes are recommended: x-axis: (k T)-1; y-axis: ln of I (Arrhenius plot). With this

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transformation, activation energy can be calculated as the negative slope of the regression. Brown et al. (2004) assembled temperature–rate relationships for a multitude of physiological processes and corrected the rates for body size according to the 0.75 rule, i.e., the increase of absolute metabolic rates with the 0.75th power of body mass (Sect. 3.3.1). Estimates of activation energy were rather uniform (0.68 to 0.73 eV) for a multitude of metabolic processes. Brown et al. attempt to build a theory explaining large-scale ecological pattern primarily on the size and temperature dependence of metabolic rates (“metabolic theory of ecology”) (Fig. 4.4). Box 4.1 Aerobic Scope: A Measure of Well-being The are many metrics usable for the dependent variable of optimum curves. The ones closest to fitness in the evolutionary and ecological sense relate to reproduction (fecundity) because fitness of particular genes or genotypes is defined as the representation of their own kind in future generation. However, reproduction-related measures require long-term cultivation which might be difficult under near-natural living conditions and is anyway associated with a low output: effort ratio of such experiments. Pörtner (2001, 2010) and Pörtner and Farrell (2008) suggest aerobic scope as a universal measure of performance along temperature gradients. Aerobic scope is the capacity of an organism to perform aerobic energy gain through metabolism above the minimal resting level of metabolism. This energy gain can be invested in any vital function, e.g., locomotion, growth, reproduction. Aerobic scope is maximal at optimal temperatures. In the pejus regions, oxygen supply within the animal body becomes limiting and aerobic scope decreases, even if the water is fully oxygenated. Practically, this can be measured by declining pO2 in body fluids and by increasing concentrations of anerobic products of katabolism like acetate or lactate. If the upper or lower critical temperature limits (Tc) are exceeded, mitochondrial metabolism switches to become anaerobic leading to a passive survival mode which cannot be maintained forever. At even more extreme temperature, denaturation of vital substances takes place.

Regulation of Body Temperature Most aquatic organisms are ectothermal (formerly called poikilothermal); i.e., their body temperature follows environmental temperatures and is not regulated by the organisms. Thus, the internal body temperature can be far away from the physiological optimum. Some animals, e.g., fast-swimming fish like tuna, have temperatures above the ambient temperature (up to 12° more) because the heat resulting from metabolic activities is not completely dissipated to the environment. Only birds and mammals really regulate their body temperature; they are called endothermal (formerly homoiothermal). The target temperature range for regulation is very

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Fig. 4.4 Temperature and mass dependence of metabolic rate for several groups of organisms, from unicellular eukaryotes to plants and vertebrates. (a) Relationship between mass-corrected metabolic rate, ln(IM-3/4), measured in watts/g3/4, and temperature, 1/kT, measured in K. The overall slope, calculated using ANCOVA, estimates the activation energy, and the intercepts estimate the normalization constants, C = ln(i0), for each group. The observed slope is close to the predicted range of 0.60–0.70 eV (95% ci, 0.66–0.73 eV). Note that the 1/kT values at the x-axis correspond to ca. 49.2, 32.2, 16.95, 3.14 °C, higher values at the left-hand side. (b) Relationship between temperature-corrected metabolic rate, ln(IeE/kT), measured in watts, and body mass, ln(M ), measured in grams. Variables are M, body size; I, individual metabolic rate; k, Boltzmann constant; T, absolute temperature (in K). E is the activation energy. The overall slope, calculated using ANCOVA, estimates the allometric exponent, and the intercepts estimate the normalization constants, C = ln(i0), for each group. The observed slope is close to the predicted value of ¾ (95% ci, 0.69–0.73). For clarity, data from endotherms (n = 142), fish (n = 113), amphibians (n = 64), reptiles (n = 105), invertebrates (n = 20), unicellular organisms (n = 30), and plants (n = 67) were binned and averaged for each taxonomic group to generate the points depicted in the plot (source: Fig. 1 in Brown et al. 2004, with permission by John Wiley and sons)

narrow within species and differences between species are also quite small (Irving 1969): 35.6 °C to 37 °C for whales, 36 °C to 38 °C for seals, and slightly >40 °C for most birds, but only 37.7 °C for the king penguin. Water birds can lose body temperature by a few degrees during long dives without experiencing any harm. Keeping body temperature close to the physiological optimum permits higher metabolic rates of endothermal animals compared to similar sized ectothermal ones (Fig. 3.2), but it comes with energetic costs, especially when environmental temperatures are much lower than the regulation level. Temperature regulation in water is energetically more expensive than in air, because water transmits heat 27 times faster. Therefore, most aquatic endotherms are large which reduces surface: volume ratios and, thereby, heat exchange.

Evolutionary Adaptation of Thermal Tolerance Local adaptation Many species occur through relatively wide climatic ranges. Therefore, it is interesting to compare temperature tolerances of population from warmer and colder sites. One of the examples of local adaptation are the different critical temperature (Tc) of lugworms (Arenicola marina, Polychaeta) in the

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subarctic White Sea and the cold-temperate North Sea (Sommer et al. 1997). It seems that thermal tolerance windows were shifted in parallel because both the lower and the upper critical temperature (Tc) sensu Pörtner (2001) were different by about 3 °C between both sites. Willett (2010) compared the survival rates of Tigriopus californicus (Copepoda, Crustacea) from tidepools on the North American west coast from southern California to British Columbia. The more southern populations had higher survival rates at extremely high temperatures than the northern ones (Fig. 4.5). On the other hand, Mitchell and Lampert (2000) did not find an indication for local adaptation of temperature reaction norms in Daphnia magna (a common freshwater zooplankton belonging to Cladocera, Crustacea) from sites sampled from Sicily to Finland. Clones hatching from resting eggs sampled at the different sites were subject to a “common garden experiment,” i.e., subject to the same range of temperatures and other experimental conditions. While there was strong variation between clones from the same population, no difference in the means of local populations was found. This lack of local adaptation was attributed to the restricted seasonal occurrence of Daphnia magna and the possibility to avoid adverse local climate seasons by dormant resting stages. Seasonal adaptation Mitchell et al. (2004) used a similar approach for Daphnia magna hatching from resting eggs at different seasons. There was no indication that populations hatching during warmer seasons had different reactions norm to temperature than the cold season populations. Adaptation to climate change In the face of ongoing global warming, there is an increasing interest in the extent of evolutionary temperature adaptation. It is important to know which species can adapt to increasing temperatures, i.e., increase their temperature optimum and their upper tolerance limit of temperature (Dam 2013). In this context, we are not interested in slow evolution at phylogenetic time scales but at rapid evolution which could influence the reaction norm of a population during the time at which relevant changes in environmental conditions occur (Hairston et al. 2005). Resurrection ecology is a further and very promising approach to study rapid evolution (Hairston et al. 2005; Angeler 2007). Many aquatic organisms produce resting stages which do not hatch completely the next year but become buried in the sediment. There, they might survive for decades and can serve as “seed bank” for the future. When it is possible to date them, they are also a valuable resource for experimental research because they can be hatched artificially and their reaction norms can be compared to populations from other periods. Henning-Lucass et al. (2016) hatched resting eggs of Daphnia galeata from Lake Constance originating from 1964 to 1975 and compared the historic Daphnia clones with recent ones from 2000 to 2009. There was no evidence that the recent Daphnia would perform better at higher temperature than the historic ones. It should be mentioned, however, that

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Fig. 4.5 Survival times of the copepod Tigriopus californicus originating from more southern (warm) to more northern (cold) populations (Source: Fig. 4, Willett 2010, with permission by Oxford University Press)

Lake Constance underwent several quite drastic environmental changes during that time (eutrophication until 1980, recovery from eutrophication thereafter) which probably imposed stronger selective pressures than warming. This interpretation is supported by the fact that the rapid evolution of Daphnia resistance to toxic Cyanobacteria was found in Lake Constance zooplankton (Hairston et al. 1999).

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4.1.3

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Salinity

The border between freshwater and saltwater is one of the strongest distributional barriers for many animal and plant species. Transition zones between salt- and freshwater are frequently characterized by a regional minimum of species numbers, as has been shown for zoobenthos the range of a salt content of 5–7 g kg-1 in the Baltic Sea (Remane 1940). There are few freshwater and marine species transgressing this boundary and also few species specialized in brackish waters.

Osmosis Salinity of the surrounding medium is important for the well-being of organisms because of the osmotic pressure exerted by the medium. The osmotic pressure depends on the dissolved substances in the water, primarily on the salts but also to some extent on dissolved organic substances. Biological membranes are semipermeable, i.e., water can pass through the pores of such membranes but much larger molecules cannot. If the osmotic pressures on both sides of the membrane are different, water moves in the direction of the higher osmotic pressure to dilute dissolved substances and to equalize osmotic pressures on both sides of the membrane. If the body fluids of an organism are more dilute than the medium, water is sucked out of the organism and the concentrations of solutes in the body fluids might increase to an extent harmful for an orderly physiological functioning. If the body fluids are less dilute than the medium, the organism sucks in water reducing the concentration of solutes. As a consequence, the organism starts to swell, in the extreme case until rupture. Poikilosmotic Organisms (“Conformers”) An internal osmotic value similar to the medium and the absence of regulatory mechanisms is facilitated by the absence of strong fluctuations of salinity in the sea. Therefore, organism can be isotonic, i.e., have the same osmotic value than the medium without deleterious effects of changes in the osmotic pressure of the body fluids. Most of marine plankton and many mollusks are osmotic conformers. However, in the tidal zone osmotic stress can become prevalent when evaporation increases salinity of the residual water or when dilution by rainwater decreases salinity. Intertidal mussels prevent or reduce osmotic stress by closing their valves. Intertidal algae are often protected by thick layers of slime. The slime does not mix much with rainwater and provides a storage pool of water helping against desiccation. The absence of osmoregulation does not preclude ionic regulation, i.e., the selective enrichment of certain ions under maintenance of a constant osmotic pressure. Hypertonic Regulators Vital processes are impossible in a medium as dilute and poor of ions as freshwater or brackish water of < ca. 7 g kg-1. Therefore, organisms living there have to

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Fig. 4.6 Different perfection of osmoregulation of brackish water and intertidal animals. The polychaete Nereis diversicolor is almost isotonic, the crustaceans Gammarus duebeni and Carcinus maenas are intermediate, the crustacean Heloecius cordiformis is an almost perfect hypertonic regulator, and the crustacean Palaemon varians is both a hyper- and a hypotonic regulator (source: Fig. 3.2 in Sommer 2005 after data in Beadle 1943, 1957)

maintain an internal osmotic value higher than the medium (hypertonic). Most of them are not perfect regulators (homoiosmotic), but the internal osmotic pressure increases slightly with the external osmotic value until it reaches a 1:1 relationship (Fig. 4.6). Hypertonic regulation causes a permanent inflow of water into the body. This excess water has to be removed by special mechanisms without losing at the same time ions to the surrounding medium. Both processes are energetically expensive and costs increase with the difference between the internal and external osmotic pressure. Therefore, freshwater plankton grow slower than similar sized and otherwise similar marine plankton.

Hypotonic Regulators Regulators which keep the regulation level below the ambient osmotic pressure are common in hypersaline environments such as salt lakes and salt pans. The brine shrimp Artemia salina is the most prominent example. It can live in hypersaline environments up to the limit of solubility of sodium chloride. Often it is the only

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metazoan in such environments. Osteichthyes (bony fish, teleosts) of the sea are also hypotonic regulators. This is considered as an indication that the evolution of bony fish started in the freshwaters followed by a later colonization of the oceans (Remmert 1969, 1989). The blood of Chondrichthyes (cartilaginous fish) has a higher osmotic value than the one of bony fish, but the elevation of the osmotic value is due to urea and not to dissolved salts. Hypotonic regulators have to drink permanently in order to compensate for osmotic water loss, but at the same time they have to excrete the additional salts gained by drinking seawater. Many hypertonic regulators have specific glands to excrete salts.

4.1.4

Desiccation

Desiccation is a problem in non-permanent water bodies and in the intertidal zone. In non-permanent water bodies, organisms solve this problem either by emigration, if mobility of the organisms and connectivity of the water bodies permit, or by producing desiccation-resistant resting stages such as resting eggs, spores, and cysts. Desiccation in the intertidal zone is a more regular and short time phenomenon. The organisms there have to survive periodic falling dry for hours. Sessile animals with mineral shells prevent or at least retard water loss by closing the shells. The cost of this adaptive behavior is the cessation of feeding during the closure period. Contrary to higher plants, intertidal algae do not have a water impermeable cuticle and stomata by which they can regulate transpiration. A slimy coating retards water loss, but cannot fully prevent it. Vegetation zonation in the intertidal zone and below is a characteristic feature of rocky shores. There is a sequence of dominant canopy species from the upper intertidal to the lowermost zones inhabited by algae in the subtidal. The transitions between the different zones are rather sharp. Zonation is quite consistent within large regions (Lüning 1985), with local differences mainly caused by differences in wave exposure. The upper limit of zones is defined by desiccation tolerance. As an example, the typical zonation on NW European coasts shall be presented here. The intertidal algae in Fig. 4.7 lose water almost equally fast, ca. 70 to 80% after 4 h of air exposure in sunshine (Kristensen 1968), but different species can tolerate different amounts of water loss (Dring and Brown 1982). The alga growing highest up in NW European intertidal zones, Pelvetia canaliculata, can survive several days of falling dry and can resume photosynthesis to the full extent already after 2 h of inundation following a water loss of 90% before.

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Fig. 4.7 Littoral zonation of macroalgae in the NW coast of France. The pink part of the circles shows the loss of water which can be tolerated after which photosynthesis can be resumed (source: Fig. 7.6 in Sommer 2005)

4.2

Nutrition and Growth of Autotrophs

4.2.1

Light and Photosynthesis

Types of Photosynthesis The plant type of photosynthesis is by far the dominant form of primary production of organic matter both on land and in water. The “plant type” uses DIC (CO2 or HCO3-) as carbon source and H2O as electron donor (reductant). O2 is set free by splitting the water molecule, and organic matter is produced from DIC and H2. Bacterial types of photosynthesis use either H2S or free H2 as electron donor. All types use light as energy source. The chemical summary equations are: 6CO2 þ 6H2 O → C6 H12 O6 þ 6O2 ðCyanobacteria, algae, plantsÞ

ð4:2Þ

6CO2 þ 12H2 S → C6 H12 O6 þ 6H2 O þ 6S2 ðpigmented sulfur bacteriaÞ

ð4:3Þ

6CO2 þ 6H2 → C6 H12 O6 ðsulfur free purple bacteriaÞ

ð4:4Þ

Reaction Steps Photosynthesis consists of two reaction steps. In the light reaction, light energy is converted into chemical energy and stored as ATP (photophosphorylation) and NADP is reduced to NADPH to serve as electron donor for the following reaction step. H2O or H2S are split and O2 or S2 are set free.

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In the subsequent dark reaction, the stored energy and the reductant are used to incorporate CO2 into organic matter.

Photosynthetic Pigments Capture of light energy requires pigments. Chlorophyll a is the main pigment in the reaction centers of the plant type of photosynthesis, with the notable exception of Prochlorobacteria which have divinyl-chlorophyll. Bacteriochlorophylls play the central role in the anoxygenic types of photosynthesis. Chlorophylls are good in the absorption of red and blue light but inefficient in the green part of the spectrum. Therefore, there are also accessory pigments in the antenna systems which transfer light energy to the reaction centers. Their absorption maxima are provided in Table 4.1. Several of the accessory pigments have characteristic taxonomic distributions. Accessory pigments include other types of chlorophyll, xanthophylls, carotenes, and phycobiliproteins. Interestingly, aquatic primary producers show more different colors than leaves of terrestrial vegetation. Coloration of many aquatic primary producers (except for Chlorophyta and higher plants) is dominated by accessory pigments and mixtures thereof. Therefore, reddish, brown, yellow, olive, and blue-green colors of primary producers can be found. This colorfulness facilitates maximal usage of the light spectrum, because dense layers of chlorophyll-dominated phytoplankton shift the light spectrum toward a dominance of green light which then may be used by reddish or brownish algae. Action spectra (Fig. 4.8), i.e., the dependence of photosynthetic rates on wavelength, in general have the same pattern as absorption spectra, i.e., primary producers that are photosynthetically less active in light of their own color. Photosynthesis of green and purple bacteria is bound to anoxic conditions because H2S and H2 are consumed by biological and chemical oxidation in the presence of oxygen. This means that green and purple bacteria have to grow vertically deeper and in the shade of oxygen producing primary producers. Bacteriochlorophylls absorb at the outer ends or even beyond the photosynthetically active spectrum of the plant type photosynthesis (PAR, 400–700 nm) and are thus able to use wavelengths only marginally absorbed by phytoplankton (Schlegel 1992). Box 4.2 Measurement of Photosynthesis (Wetzel and Likens 1991; Lampert and Sommer 2007) O2 production. The oldest method of measuring photosynthesis is the comparison of the temporal change of O2 concentrations in light and dark bottles. In order to obtain vertical profiles, light and dark bottles can be incubated at different depths or in light incubators shaded artificially to obtain the required irradiance levels. It is assumed that the temporal oxygen increase in the light bottles represents net photosynthesis rates and the oxygen decrease in the dark (continued)

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Table 4.1 Color and absorption maxima (in nm wavelength, exact location of maxima may slightly shift in dependence of extraction medium) of important photosynthetic pigments (after data in Lüning 1985, Schlegel 1992) Pigment Bacteriochlorophyll a Bacteriochlorophyll b Bacteriochlorophyll c,d,e Chlorophyll a Chlorophyll b Chlorophyll c1 Chlorophyll c2 Fucoxanthin R-Phycoerythrin B-Phycoerythrin R-Phycocyanin C-Phycocyanin Allophycocyanin

Color Green Green Green Green Green Green Green Brown Red Red Blue Blue Blue

Absorption maxima (nm) ca. 370 (UV) 850–890 (IR) 1020–1035 (IR) 455–470 (blue) 715–755 (red) 438 (blue) 675 (red) 470 (blue) 650 (red) 444 (blue) 634 (orange) 449 (blue) 631 (orange) 545 (green) 542 (green) 563 (yellow) 545 (green) 563 (yellow) 533 (green) 615 (orange) 620 (orange) 650 (red)

Fig. 4.8 Action spectra of Chlorophyta (green algae, pigmentation like higher plants), Chromophyta (a diverse group of algae with yellow to brown coloration, mainly due to fucoxanthin), and Rhodophyta (red algae, colored dominated by phycoerythrin) (source: Fig. 4.1 in Sommer 2005)

Box 4.2 (continued) bottles represents respiration. Gross photosynthesis can be calculated by the difference between oxygen concentrations in the light and the dark bottle. (continued)

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Box 4.2 (continued) This method rests on two assumptions which are not always met. Respiration of heterotrophs, e.g., bacteria, should be negligible in comparison to photoautotrophs and respiration should be light independent- The latter is not the case if too high light intensities lead to photorespiration. Measuring photosynthesis by oxygen changes is relatively insensitive. It works well with macrophytes or dense suspensions of microalgae, but it is too insensitive at low phytoplankton densities. 14 C incorporation. This method rests on the incorporation of the radioactive isotope 14C into POC or into organic matter. 14C is added to the bottles as 14 C-labeled bicarbonate which then dissociates according to the pH of the medium. After the incubation time samples are either filtered (incorporation of 14 C into particulate matter) or DIC is expelled after acidification and the remaining 14C is all organic. Combining both approaches allows a differentiation between photosynthetic production of POC and of excreted DOC. The calculation of carbon assimilation rates needs to know the proportion of 14C and the dominant 12C in the water. Correcting for the fact that 14C is taken up 1.05 times more slowly than 12C, the total carbon incorporation can be calculated from 14C appearing in the particulate or in the organic phase. A distinction between gross and net photosynthesis is not possible because at the start of the incubation there is no 14C in the organisms. At short incubation times, the calculated rate of photosynthesis is close to “gross,” while later more and more of the freshly incorporated 14C becomes respired and the calculated rate approaches “net photosynthesis.” The method is highly sensitive and sensitivity can be increased by increasing the amount of radioactive label. Therefore, it has become the standard method in measuring phytoplankton photosynthesis. Because of increasing safety concerns with handling radioactive material, radioactive 14C is being replaced by labeling with the stable isotope 13C. PAM (pulsed amplitude modulated) fluorescence (Beer and Björk 2000) is an incubation independent method using the change of chlorophyll fluorescence between ambient light (F) when part of the reaction centers are closed and maximal fluorescence at saturating light (Fm′) when all reaction centers are closed. The quantum yield of electron transport through photosystem II can be calculated as (Fm′-F)/Fm′. Conversion to photosynthesis rates needs irradiance data and calibration for the organisms under scrutiny. It has been successfully used for macrophytes, benthic animals with photosynthetic endosymbionts, algal mats, and also to some extent for dense phytoplankton suspensions.

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Light Dependence of Photosynthetic Rates Specific photosynthetic rates (or production rates) are expressed as organic carbon formed per unit time and biomass. Often, chlorophyll is used as proxy of biomass. The curves describing the response of specific photosynthetic rates to light are called P–I curves (photosynthesis–irradiance curves). There are several mathematical formulations of this relationship, mainly differing by the sharpness of the transition between limitation and saturation. The oldest model (Blackman 1905, used in Fig. 4.9) assumes a linear increase of light-limited P (rate of photosynthesis) with irradiance shortly before light becomes saturating and a horizontal plateau is reached at saturating light. At much higher irradiances, light becomes inhibiting because of photooxidative damage of the photosynthetic apparatus. Cardinal values of this relationship are Pmax (maximal photosynthetic rate), α (initial slope of the relationship), Ek (saturation coefficient, irradiance at the onset of saturation), and Ei (irradiance at the onset of inhibition): if E < Ek : P = αE . . . if E k < E < E i : P = Pmax

ð4:5Þ

Attempts to describe the P–I curve by a single equation lead to a gradual, asymptotic approach to saturation., e.g., a hyperbolic curve asymptotically approaching the maximal level according to Michaelis and Menten (1913): P = ðPmax EÞðE þ K Þ - 1

ð4:6Þ

where K is the irradiance value at which half of Pmax is reached. The onset of light inhibition varies between taxa and functional groups (Table 4.2) and also as a result of light or shade accommodation. There are several types of shade accommodation, the clearest contrast being between the Chlorella type and the Cyclotella type. In the Chlorella type, cellular chlorophyll contents are increased in response to low light. As a consequence, α and Pmax stay constant if P is normalized to chlorophyll, but increase if it is normalized to carbon. In the Cyclotella type, there is no additional chlorophyll synthesis but only a restructuring of chlorophyll distributions in the antenna system leading to an increase in α but no increase in Pmax. Effect of temperature The magnitude of Pmax depends on temperature. Temperature optima range from 8 °C (extremely cold-adapted Antarctic phytoplankton) to 35 °C (tropical Cyanobacteria and Chlorophyta). The Q10 at temperatures below the optimum is rather low (1.88 according to Eppley 1972). Light-limited photosynthesis is not temperature dependent, at least above 2 °C. Tilzer et al. (1986) found some indication for a decline of α at temperatures below 2 °C. Since Ek is the intersection between the ascending and the horizontal part of the P–I curve, the onset of light saturation is also temperature dependent with a higher Ek at higher temperatures. Net vs. gross production Respiration uses different biochemical pathways than photosynthesis, but its mass balance effect on O2 and CO2 is the reverse of

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Fig. 4.9 From the P–I curve (upper panel) to the vertical profile of photosynthesis based on the following assumptions: Ec (compensation point) at 10 μmol quanta m-2 s-1, saturation coefficient (Ek) at 60 μmol quanta m-2 s-1), onset of inhibition (Ei) at 300 μmol quanta m-2 s-1, surface irradiance at 1000 μmol quanta m-2 s-1. Lower left: vertical profile resulting from an attenuation coefficient of 0.1 m-1, representing low phytoplankton biomass. Lower right: vertical profile resulting from an attenuation coefficient of 0.4 m-1, representing high phytoplankton biomass (source: Fig. 4.3 in Sommer 2005)

134 Table 4.2 Onset of light limitation (in μmol quanta m-2 s-1) in different groups of aquatic primary producers (after data in Harris 1978, Kohl and Nicklisch 1988, Lüning 1985, Tilzer et al. 1986)

4

Group Phytoplankton Macroalgae, eulittoral Macroalgae, sublittoral Purple bacteria Green sulfur bacteria

Frequent 60–100 Around 500 um 150 25–70 20–25

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Extremes 10–300 60–200

photosynthesis. Since primary producers also respire, photosynthesis rates have to overcome respiratory losses of carbon to contribute to production of biomass. Net production is gross photosynthesis minus respiratory losses. It manifests itself in a rightward shift of the P–I curve with a threshold value at the irradiance permitting photosynthesis in balance with respiration. This threshold is called compensation point (Ec).

Vertical Profiles of Photosynthesis The vertical profile of phytoplankton photosynthesis depends on the parameters of the P–I curve, the surface irradiance, and the vertical light attenuation (Sect. 2.4.3). Chlorophyll concentrations are important in two ways. In order to get from specific rates of photosynthesis to absolute rates per unit water volume, the former have to be multiplied by the chlorophyll concentration. Second, chlorophyll concentrations have a decisive influence on the vertical attenuation coefficient (k), in particular in water with little or very constant background attenuation (Tilzer 1983); see also the elongate and the compressed profiles in Fig. 4.9. Surface irradiance may reach 2000 μmol quanta m-2 s-1 on a sunny summer day, while diurnal maxima on cloudy winter days in the temperate zone are around 100 μmol quanta m-2 s-1. In polar night or under snow-covered ice also complete darkness is possible at noon. Thus, it depends on surface irradiance whether the vertical profile starts with light inhibition, light saturation, or limitation at the surface. The lower limit of the profile is the compensation depth, i.e., the depth where irradiance equals Ec. Vertical mixing moves phytoplankton up and down along the vertical light gradient. The mean irradiance (Em) in a mixed surface layer of depth zm could be calculated as (Sect. 2.4.3) E m = E0 1–e - k zm ðk zm Þ - 1

ð4:7Þ

However, caution is needed if Em and the P–I curve are used for calculating rates of photosynthesis. It is at best a rough approximation, because rates Pmax in the saturated layer.

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Carbon Limitation Can photosynthesis be limited by CO2, in spite of the largeness of the total pool of DIC? All primary producers can use CO2, but its contribution to DIC drops from ca. 50% at pH = 7 to a few % at pH = 8 and almost nothing at pH = 9 (Sect. 2.3.3). Obligate CO2 users, e.g., Callitriche stagnalis (pond-water starwort), show a decline of photosynthetic rates upon a shift from neutrality to slightly alkaline conditions and stop photosynthesis at pH = 9. Facultative HCO3- users like Potamogeton pectinatus (fennel pondweed) also show a decline of photosynthesis rates at pH > 7 but a slower one and stop photosynthesis at pH = 11 (Sand-Jensen 1987). The decline of photosynthesis rate with increasing pH even among bicarbonate users indicates that using bicarbonate as C-source is metabolically more expensive than using CO2. The pH of seawater is within the pH range of bicarbonate dominance and sensitive responses of CO2 to pH changes. CO2 concentrations in the surface ocean vary between 90% of the living biomass, if mineral skeletal substances are excluded. The classic additional nutritional elements are Ca, K, Mg, N, S, P, and Cl known from early agricultural chemistry (Liebig 1855). Individually, these elements contribute >0.1% to biomass (macronutrients). Na is also present in significant amounts in biomass because of its high abundance in seawater, but it is not a nutritional element. In addition to the classic nutritional elements also trace elements (micronutrients) are needed, although at much lower quantities. These include Fe, Mn, Cu, Zn, Mo, Co, B, and V. For several microalgae (e.g., Peridinium) also Se was established as essential trace elements. In many cases, trace elements are

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essential co-factors of enzymes. Some of them become toxic at higher concentrations, e.g., Cu, Zn. Diatoms and silicoflagellates need Si for their skeletal structures. The required concentrations qualify Si as a macronutrient for them. Most mineral nutrients have to be taken up in ionic form (e.g., nitrate, ammonium, phosphate) or as undissociated solutes (silicic acid for diatoms). Nitrogen is a special case, because many important Cyanobacteria and some heterotrophic bacteria can use dissolved N2 as nitrogen source (nitrogen fixation) which makes them independent of the availability of N-containing ions. Nitrogen fixation has high energy requirements because the strong covalent bond between the two N-atoms has to be broken. In addition, nitrogen fixation needs the enzyme dinitrogenase which is sensitive against oxygen. Therefore, photosynthesis could inactivate nitrogen fixation. In order to create local microenvironments of low oxygen concentration, Cyanobacteria of the order Nostocales have specialized cells (heterocysts) for nitrogen fixation which do not perform the dark reaction of photosynthesis. Other Cyanobacteria use the night for nitrogen fixation.

Nutrient Limitation Limiting nutrients Several of the essential elements are usually available in excess of demands, e.g., Ca, K, Mg. Often their concentrations are so high that consumption for the buildup of biomass does not lead to a notable decrease of the dissolved concentrations. Some elements, however, might become depleted so strongly that their availability sets a limit to further growth of primary producers. These are called limiting nutrients. Traditionally, nitrogen and phosphorus have been considered as limiting nutrients in surface waters for all kinds of primary producers, and silicon for diatoms. More recently, iron has also been detected as a limiting factor for phytoplankton growth in some parts of the world ocean, e.g., in the Antarctic Ocean and the Northern and the Equatorial Pacific Ocean (Martin et al. 1990; Coale et al. 1996). Limitation of yield Limiting nutrients and their effects on attainable biomass was already in the focus of early agricultural chemistry. Already then, Liebig (1855) formulated the principle of the minimum. This means that the nutrient in shortest supply relative to demand determines the attainable yield of biomass. This is consistent with the non-substitutable roles of the different nutritional elements. If all available N is used up to form proteins, it does not matter for further growth whether there is still a lot of phosphorus available or just a little bit. The reverse is the case, if all available phosphorus is used up to form nucleic acids. For phytoplankton, the canonical transition between N- and P-limitation takes place at a N:P ratio of 16:1 (Redfield ratio, Sect. 3.4.2). However, this is only a mean value for phytoplankton. Individual species may have different stoichiometric transition ratios (“optimal ratios”), ranging from ca. 7:1 to 30:1 (Rhee and Gotham 1980). Therefore, both N and P addition might permit further biomass accumulation, if the availability of both nutrients is within this range of ratios and phytoplankton contains a mixture of N- and P-limited species. This is a seeming co-limitation at the community level, while single species remain limited by single nutrients.

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Nutrient limitation of uptake rates The dependence of uptake rates (v) on nutrient concentrations in the water (S) is usually described by a Michaelis and Menten (1913) type equation which assumes an asymptotic approach to a maximal uptake rate (vmax) (Dugdale 1967): v = ðvmax SÞðkm þ SÞ - 1

ð4:8Þ

where km is the half saturation constant, i.e., the nutrient concentration where half of the maximal uptake rate is reached. The efficiency of taking up nutrients at extremely low concentration is defined by the initial slope, i.e., the slope of the curve at the origin. It equals the ratio vmax km-1. Originally, vmax and kms were considered species-specific constants at a given temperature (Fig. 4.10). Meanwhile, it became clear that vmax changes with the nutritional state of the organisms (Morel 1987). If cells are maximally depleted of the limiting nutrient (“hungry cells”), the vmax parameter is maximal; if the cells have a satiated internal concentration of the limiting nutrient, the vmax parameter is minimal. For the range of intracellular concentrations (cell quotas) in between, a negative linear dependence of vmax on the cell quota can be assumed. It follows that the curves in Fig. 4.10 have to be replaced by a bundle of curves confined between the curves predicted for the upper and lower limit of vmax.

Nutrient Limitation of Growth: Monod Model In an attempt to predict also growth rates depending on dissolved nutrient concentrations, Monod’s (1950) application of the Michaelis–Menten equation for C-limited growth of heterotrophic bacteria was extended to the nutrient-limited growth of microalgae: μ = ðμmax SÞðS þ ks Þ - 1

ð4:9Þ

where μ is the specific growth rate, μmax its asymptotic value, and ks the half saturation constant of growth. Half saturation constants for P-limited growth of phytoplankton range from 0.003 to 1.8 μmol kg-1, with most values clustered in the range 0.02 to 0.2 μmol kg-1. Half saturation constants for N-limited growth of phytoplankton range from 0036 to 11.6 μmol kg-1, with most values clustered in the range 0.3 to 3.0 μmol kg-1 (Eppley and Strickland 1968; Kohl and Nicklisch 1988; Parsons et al. 1984; Sommer 1991a, b, c). Unfortunately, the Monod model is valid only under constant dissolved nutrient concentrations, i.e., if nutrients consumed by uptake are replaced by some source elsewhere at the same rate. The replacement can be excretion by animals, mixing from deeper water, or artificial addition by an experimentalist. Such a steady state is rare in nature. Experimentally, such conditions are realized in chemostat culture (Box 4.3). The Monod model is still popular in spite of its limited applicability. The attractivity of the model lies in the fact that its independent variable (S) can easily be

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Fig. 4.10 Specific ammonium uptake of two brown algae as a function of ammonium concentration, the filamentous, ephemeral Pylaiella littoralis, and the parenchymatic, perennial Fucus vesiculosus (source: Fig. 4.5 in Sommer 2005, after data in Schramm 1996)

measured. Nevertheless, for field conditions the more complex Droop model (see below) should be used (Sommer 1991a).

Nutrient Limitation: Droop Model The Droop model predicts growth rates as a function of the cell quota, i.e., the concentration of a limiting nutrient within cells (Droop 1973, 1983, Fig. 4.11). The cell quota (Q) can be related either to the number of cells or to some measure of biomass, e.g., carbon. Then, the cell quota becomes the nutrient:C ratio. μ = μ0max ð1–Q=Q0 Þ

ð4:10Þ

where Q0 is the minimal cell quota, i.e., the structural minimum of the nutrient content below which survival is not possible. μ′max is not identical with the μmax of the Monod model, because it is only a theoretical value reached at an infinite cell quota. The μmax of the Monod model is the μ calculated for a saturated cell quota (Qsat). Minimal cell quotas of microalgae (expressed as molar P:C ratios) range from 0.0003 to 0.008 P:C, with most values clustered between 0.0008 and 0.002 P:C. Minimal cell quotas of N range from 0.014 to 0.18 N:C, with most values clustered around 0.02 and 0.05 N:C. Maximal cell quotas of P range from 0.008 to 0.04 P:C,

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Fig. 4.11 Droop model of growth rate dependence on the cell quota of the limiting nutrient. Q0: minimal cell quota, Qsat: saturating cell quota, μmax: realized maximal growth rate, μmax′: asymptotic maximal growth rate

with most values clustered around 0.01 P:C. Maximal cell quotas of N range from 0.09 to 0.28 N:C, with most values clustered around 0.15 N:C (Kohl and Nicklisch 1988; Parsons et al. 1984; Sommer 1991a, b, c; Bi et al. 2012).

Box 4.3 Microalgal Cultures as Tool to Study Nutrient Requirements of Microalgae, Batch Culture vs. Chemostat (Jannasch 1974) Batch culture: A batch culture is a culture where a defined volume of medium is inoculated with a small starting population of microalgae from stock or preparatory cultures. Depending on preconditions, a short adaptation phase may be needed until algae start to grow exponentially. If the starting concentrations of nutrients are non-limiting, growth commences at the maximal growth rate (exponential phase). Nutrients are consumed with an increase of biomass. Usually, the limiting nutrient is depleted to non-detectable levels before growth stops. Under nutrient depletion growth is not any more fueled by uptake from the medium but at the expense of the internal cell quota sensu Droop (1983). Cell quotas become halved at each cell division. Consequently, growth rates decline until growth stops (stationary phase). In batch cultures, there is a permanent change of abundance, biomass, nutrient concentrations, growth rates, and cell quotas. Therefore, the growth rate–nutrient relationship does not follow the Monod model. It is not state of the art to derive Monod parameters from batch cultures. Batch cultures may, however, be used to calculate the realized maximal growth rate and the minimal cell quota, assuming that the limiting nutrient has completely been used for biomass buildup. If growth rates during the run-time of the batch culture can be assessed with (continued)

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Box 4.3 (continued) sufficient accuracy and subsamples for elemental analysis of the algae can be taken, Droop’s entire growth rate–cell quota equation can be fitted to the data. Chemostat. A chemostat is a culture system where the suspension of algae is permanently diluted by fresh medium (Monod 1950). The dilution rate (D) is the quotient of fresh medium per unit time (F) divided by the culture volume (D = F/V ). If D < μmax algae start to grow and take up nutrients from the medium, thus lowering the nutrient concentration until a dynamic equilibrium is reached between nutrient import into the culture, nutrient consumption by the algae, export of algae via the overflow, and new production of algae via cell division. There is a steady state, at which μ = D. Abundance, biomass, dissolved nutrient concentrations, and cell quotas remain constant. Under these circumstances, both the Monod model and the Droop model are correct descriptions of nutrient limitation. Comparison to nature. Neither the batch culture nor the chemostat are perfect simulations of what happens in nature. Microalgae never grow as undisturbed as in batch cultures. There is always loss of cells through grazing or sinking, and there is always some addition of nutrients. However, the ascent phase of blooms, i.e., explosive growth phase with near maximal growth rates and negligible losses, is quite similar to batch cultures. A chemostat-like steady state is also never reached in nature, but there are periods when apparent rates of change are much smaller than reproduction because algae are produced by cell division and removed by grazing and sedimentation at similar rates. At the same time, grazers excrete dissolved ammonium and phosphate, thus providing an analogue to the input of fresh nutrients into the chemostat.

Co-limitation of growth rates Do physiological rates also follow Liebig’s law of the minimum? If the attainable biomass is limited by a single nutrient, it would be no surprise that the way toward attaining this biomass level (growth) should also be limited by single nutrients. Indeed, this had been the prevalent hypothesis for a long time; i.e., if μ predicted by nutrient 1 (μ1) is smaller than μ predicted by nutrient 2 (μ2), the realized μ should be equal to μ1. However, the alternative hypothesis of a multiplicative interaction still persisted in the literature, though data were in favor of the law of the minimum (Rhee 1978). However, a more recent model about the optimal allocation of matter and energy into resource acquisition (P, N, light) indicates a certain degree of co-limitation if the non-limiting resources are also scarce (Pahlow and Oschlies 2009). Resource acquisition needs matter and energy investments into cellular structures, and these investments can be reduced if a resource is abundant. Thus, the saved matter and energy can be invested into acquisition of the limiting resource which means that the limiting resource becomes a bit less limiting. So far, the optimal allocation model seems to be at least as compatible with published data as the law of the minimum. Interestingly, the optimal

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allocation model is also in agreement with Droop’s cell quota model (Pahlow and Oschlies 2013). Nutrient limitation of phytoplankton growth rates in situ is not as easily detected as one might believe. Low concentrations of a dissolved nutrient do not necessarily indicate nutrient limitation because of the restricted applicability of the Monod model. Moreover, ks values of several phytoplankton species are well below the detection limits of some nutrients, in particular phosphate (detection limit ca. 0.03 μmol kg-1). Goldman et al. (1979) claimed that oceanic plankton grow without nutrient limitation, because they found that the C:N:P stoichiometry of filterable particulate matter (seston) is often close to the Redfield ratio (C:N: P = 106:16.1), indicative of the absence of N- and P-limitation. However, much higher C:N and C:P ratios have been reported later (Sommer 1988; Elser et al. 2000). Moreover, seston stoichiometry is a poor indicator of phytoplankton cell quotas because seston is a mixture of different phytoplankton species, detritus, heterotrophic protists, and bacteria. Sommer (1991a, b) tried to overcome this problem by a combination of size fractionation and density gradient centrifugation of seston and obtained almost pure fractions dominated by single phytoplankton species. A comparison of the cell quotas of these fractions with growth rates obtained from bioassays yielded a good fit of the Droop model and evidence for nutrient limitation. However, this procedure is far too tedious to be applied routinely. Enrichment bioassays comparing growth in enriched and unenriched samples are potentially powerful tools, but may be misleading if insufficient caution is taken to avoid artifacts. Plankton samples enclosed in a bottle are sealed from nutrient sources like excretion and mixing and protected from grazing by larger zooplankton. This may lead to more biomass accumulation in the bottles than in situ and a more stringent nutrient limitation in the unenriched control bottles. This bias can be minimized by diluting the plankton samples with filtered, unenriched in situ water and restricting the analysis to a period short enough before the original biomass is restored, usually a few days (Sommer 1991a, b). Molecular analyses of nutrient limitation are an emerging field (Palenik 2015; Lin et al. 2016; Lovio-Fragoso et al. 2021). There is a growing body of literature about the up- and downregulation of genes under certain types of nutrient stress, and about nutrient limitation signals to be detected by genomics, transcriptomics, and proteomics. It may well be that these methods will replace enrichment bioassays and elemental analysis in the near future. Macrophytes Macroalgae obtain nutrients from the same pool as plankton and microalgae on solid surfaces, i.e., from the dissolved pool in water. Generally, the nutrient requirements of macroalgae are much higher than those of microalgae because of less favorable surface: volume ratios, as can be seen from the high half saturation constants in Fig. 4.10. Several perennial macroalgae (e.g., Laminaria) have, therefore, evolved an annual cycle which consists of photosynthesis and production of storage polymers during summer and nutrient uptake and protein synthesis in winter (Lüning et al. 1973). This can be seen as an avoidance of nutrient

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competition with phytoplankton. In winter, phytoplankton are less or not at all active and consume less nutrients. Therefore, nutrient concentrations in the water are at their seasonal maximum. Higher plants differ from macroalgae by being rooted in the sediment and taking up nutrients from the interstitial water in the sediment, where concentrations of nutrients are several orders of magnitude higher than in the open water. Therefore, nutrient limitation has not played a significant role in research about the environmental factors controlling rooted macrophytes. Auxotrophy Some autotrophs require specific organic substances (“vitamins”) from external sources, because they cannot produce them by themselves (Droop 1968). Most often vitamin B12 and thiamin are mentioned as essential vitamins for some species. Uptake and usage for growth can be described by the same types of models as used for mineral nutrients limitation.

4.2.3

Chemolithoautotrophy

Electron Donors and Acceptors Chemolithoautotrophy is autotrophic production deriving its energy from redox reactions and using inorganic electron donors. This kind of primary production is also called chemosynthesis. It is restricted to Archaea and Bacteria, although some of them may live as endosymbionts in eukaryotic organisms. Electron donors of chemosynthesis Typical electron donors of chemosynthesis are lower and intermediate oxidation levels of several elements: • • • • • •

Hydrogen: H2 Carbon: CO Sulfur: S2, S2-, S2O32-, SO32Nitrogen: NH4, NO2+ Iron: Fe2+ Manganese: Mn2+

Origin of electron donors The electron donors of chemosynthesis originate either from volcanic gases (H2, CO, H2S) or from the anaerobic degradation of organic substances. However, the biological release of hydrogen and ammonium is not only restricted to anaerobic waters. Ammonium is released by animal excretion into aerobic water, and hydrogen is released as a by-product of cyanobacterial N2 fixation. Electron acceptors of chemosynthesis are oxygen, oxidized nitrogen compounds (mainly nitrate), oxidized sulfur compounds, and CO2. Compounds of intermediates oxidation levels (e.g., thiosulfate: S2O32-) can serve both as electron donors and as electron acceptors. Some chemolithoautotrophic bacteria can gain

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energy also by splitting compounds of intermediate oxidation level into a reduced and an oxidized component, e.g., thiosulfate into sulfate and sulfide.

Some Important Chemosynthetic Reactions Nitrification is the oxidation of NH4+ first to NO2- by the bacterium Nitrosomonas and further to NO3- by the bacterium Nitrobacter. NH4 þ þ 3=2 O2 = NO2 - þ 2 Hþ þ H2 O

ð4:11Þ

NO2 - þ 1=2 O2 = NO3 -

ð4:12Þ

Anammox (anaerobic ammonium oxidation). If ammonium is oxidized by nitrate, N2 is produced as the oxidized end product. 5 NH4 þ þ 3 NO3 - = 4 N2 þ 9 H2 O þ 2Hþ

ð4:13Þ

Sulfur-based chemosynthesis Thiobacillus spp. oxidize reduced sulfur compounds. Most of the species are specialized on a single compound. Some can also use organic energy sources, while most are obligate chemolithoautrotrophs. The most important reactions are: H2 S þ 1=2 O2 = S þ H2 O

ð4:14Þ

S2 þ H2 O þ 3=2 O2 = SO4 2 - þ 2 Hþ

ð4:15Þ

S2 O3 2 - þ H2 O þ 2 O2 = 2 SO4 2 - þ 2 Hþ

ð4:16Þ

The anaerobic Thiobacillus denitrificans uses nitrate as electron acceptor. A further anaerobic form of sulfur-based chemosynthesis is splitting of thiosulfate: S2 O3 2 - þ H2 O = SO4 2 - þ H2 S

ð4:17Þ

Iron-based chemosynthesis Oxidation of reduced ferrous iron (Fe2+) to oxidized ferric iron (Fe3+) is used as energy source by iron oxidizing bacteria like Ferrobacillus, Gallionella, and Leptothrix: 4 Fe2þ þ 4 Hþ þ O2 = 4 Fe3þ þ 2 H2 O

ð4:18Þ

Hydrogen oxidation Hydrogen oxidizing chemoautotrophs oxidize hydrogen either by oxygen or by sulfate and gain energy for chemosynthesis. Hydrogen results either from fermentation (an anaerobic form of dissimilatory metabolism, Sect. 4.4.2) or from volcanic sources, such as hydrothermal vents.

4

H2S

H2S photosynth.

NO2 chemosynth.

NH4+

NH4 chemosynth.

– NO2

O2

H2S chemosynth.

SO42–

O2

NO3 respiration

Depth

NO3–

Ecophysiology

SO4 respiration

144

Fig. 4.12 Vertical distribution of oxygen, nitrate, nitrite, ammonium, sulfate, and sulfide along a vertical oxygen gradient and vertical distribution of N- and S-dependent anaerobic respiration, chemosynthesis, and H2S-dependent photosynthesis (source: Fig. 4.8 in Sommer 2005)

Methane oxidation Methane (CH4) is also either supplied by volcanic sources or by fermentation and methanogenesis (Sect. 4.4.2). Methane is used as an electron donor and as carbon source by methanotrophic bacteria. 5 CH4 þ 8 O2 = 2ðCH2 OÞ þ 3 CO2 þ 8 H2 O

ð4:19Þ

Spatial Distribution Chemosynthetic reactions are bound to the simultaneous presence of electron donors and acceptors. Many of these redox reactions also happen just chemically, especially the oxidation of H2S by O2. At 20 °C the half-life of H2S in the presence of O2 is just about 1 hr. (Kuenen and Bos 1989). Therefore, a sufficient supply of H2S and the simultaneous presence of O2 for chemosynthesis are only found at vertical redox gradients (Fig. 4.12) where H2S is supplied from below and O2 from above. The restriction to boundary layers is less stringent for nitrification because of the permanent supply of ammonium by animal excretion. However, most of nitrification is also found at redox gradients because of the higher ammonium concentrations in anoxic water. In aerobic waters, nitrifying bacteria have to compete with the ammonium uptake by phytoplankton. Chemolithoautotrophs as Endosymbionts Submarine volcanic gas emission are drivers of chemosynthesis by providing reduced gases such as H2 and H2S through hydrothermal vents. High emission by the “black smokers” at the mid oceanic ridges enables the development of specific ecosystems which are not based on photosynthetic but on chemosynthetic primary production. These systems are not only rich in chemosynthetic bacteria in the water

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column, but also in animals containing endosymbiotic H2S oxidizers (Jannasch and Mottl 1985). Among them are giant tube worm Riftia pachyptila and mussels Bathymodiolus spp. (Grassle 1985; Lutz and Kennish 1993).

4.3

Nutrition and Growth of Heterotrophs

The majority of Archaea and Bacteria and all fungi, protozoa, and animals are heterotrophic. Some protozoa and animals contain autotrophic (photo- or chemotrophic) endosymbionts, making the resultant meta-organism functionally auto- or mixotrophic. Heterotrophs can use either DOC (dissolved organic carbon) or POC (particulate organic carbon) as C-source, energy source, and electron donor. The corresponding types of feeding are called osmotrophy (uptake of DOC) or phagotrophy (ingestion of POC).

4.3.1

Osmotrophy

Osmotrophy is the typical form of nutrition of heterotrophic Bacteria and Archaea and of many fungi. It also plays some role in the nutrition of some heterotrophic protists. The term substrate is widely used for the substances used by osmotrophs in the literature, especially in the microbiological one. However, this wording might lead to confusion with the physical substrate of benthos (sediment or solid surfaces).

Nutrient Limitation The uptake of DOC through biological membranes is usually described by a Michaelis–Menten equation (Sect. 4.2.2). In experimental analyses with bacterial cultures, the parameters of the Michaelis–Menten curve are often established by providing single, usually monomeric, substrates, such as sugars or amino acids. In contrast, natural DOC consists of a mixture of a diverse array of organic substances and simple monomeric ones are usually only a small part. (Sect. 2.3.5). Some of the polymeric substances are not at all usable, while others are at least more difficult to handle than simple sugars or amino acids. Thus, vmax and km are not only specific parameters for bacterial species or strains but also for specific substances. The relationship between uptake and growth is less complicated than in the case of autotroph limitation by mineral nutrients, because taking up of DOC is taking up the bulk material from which its own biomass is constructed. If the proportional allocation of assimilated carbon to growth and respiration does not change, growth and uptake remain proportional and growth limitation can be described by the Monod equation (Sect. 4.2.2) for which it was developed originally by Monod (1950). Availability of substrates The DOC concentrations in the ocean range between 0.4 and 2 g C kg-1 (Williams 1985). Even in semi-enclosed coastal seas, they are usually 1000:1 D. galeata did not produce eggs anymore (Fig. 4.16). Since animals are not perfectly homeostatic, mineral nutrient limitation can even be transmitted across trophic levels. Schoo et al. (2012) demonstrated a three-trophic-level transmission of P-limitation with the food alga Rhodomonas marina, the herbivorous copepod Acartia tonsa, and lobster (Homarus europaeus) larvae feeding on A. tonsa. Lobster larvae grew worse when R. marina was P-deficient. Biochemical quality Many animals are not able to synthesize specific organic compounds or can do that only at high metabolic costs. If these compounds have essential metabolic or structural roles, they have to be obtained from the food. Such compounds include long-chain polyunsaturated fatty acids (PUFAs, Brett and Müller-Navarra 1997) and sterols (Martin-Creuzburg and von Elert 2009). They

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can become limiting factors for animal growth like mineral nutrients. Limitation by fatty acids has been most extensively studied for EPA (eicosapentaenoic acid, C20: 5ω3, a fatty acid with 20 C atoms, 5 double bonds, and a double bond at the ω3position) and DHA (docosahexaenoic acid, C22:6ω3, a fatty acid with 22 C atoms, 6 double bonds, and a double bond at the ω3-position). The limiting role of EPA for the growth of the freshwater zooplankton Daphnia has frequently been shown, e.g., by Müller-Navarra (1995) and Von Elert (2002). DHA is an essential component of the brain, skin, and retina of vertebrates, but it has also been established as limiting factor for zooplankton (Leiknes et al. 2016). Essential fatty acids and sterols have distinctive taxonomic distributions in phytoplankton and heterotrophic protists and are sometimes used as biochemical markers for the dominance of taxonomic groups in the diet of herbivores (Ruess and Müller-Navarra 2019). Diatoms are rich in EPA, while dinoflagellates and many heterotrophic protists are rich in DHA. However, there is also a strong influence on growth conditions (nutrients, temperature, pH) on the content of essential fatty acids in phytoplankton biomass (Bi et al. 2014). The direction of these responses may even differ between species (Bi et al. 2020). Environmental effects on fatty acids and sterols can be strong enough to determine the nutritional quality of phytoplankton for zooplankton (Bi and Sommer 2020).

Numerical Response Numerical response is the dependence of birth rates on food conditions. It normally follows a kind of saturation curve (Blackman or Michaelis–Menten) with a threshold value, if food availability is corrected for food quality. Somatic vs. reproductive growth Energy and matter supporting animal production is allocated to somatic growth until reaching maturity. After reaching maturity, somatic growth continues in some animals and only part of the production is allocated to reproduction (e.g., cladoceran zooplankton). In other animals, there is no further somatic growth after maturity has been reached and the entire production is invested into reproduction, which is either distributed between repeated reproductive events (e.g., copepod zooplankton) or invested into a single reproductive event at the end of the lifetime (e.g., cephalopods, eel). These differences are important components of the life cycle strategy of organisms, which will be explored in more detail in Sect. 5.4.3. Birth rates The birth rate of an animal depends on the frequency of the reproductive events per time and of the number of offspring (eggs or neonates) released in each reproductive event. In the case of repeated reproduction, the timing is often coupled to season; in animals with life span shorter than 1 year, the interval between reproductive events often depends on temperature (McLaren 1963). The number of offspring per reproductive event depends on feeding conditions in all animals and on age of the mother animal in animals which still grow after first reproduction.

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Box 4.5 Measurement of Animal Production Direct observation of large animals. Production of animals in captivity can easily be carried out by monitoring mass growth of individuals and birth rates. To some extent this is also possible in the wild, if individuals can be marked (e.g., ringed birds) and observed through time, possibly with the help of surrogate parameters for body mass, e.g., length–mass relationships. Cohort analysis is a tool suitable for animals with synchronized reproduction, i.e., if offspring are released during short intervals, usually once per year. Individuals born in one such event are called cohort. During the interval between reproductive events, the individuals of a cohort show somatic growth and decline in number because of mortality. If individuals can be assigned to cohorts, the somatic growth of cohorts and mortality can be determined. If mortality rates are more or less constant through time, the production of a cohort during a given time interval is the mean mass growth of individuals multiplied with the geometric mean of the number of individuals. Size–age relationships. In the case of continuous reproduction, it is not possible to assign individuals to a certain cohort. Still it may be possible to determine the age of individuals, e.g., by growth rings in mollusk shells or fish otoliths. The relationship between mass and size can be used to construct a mass–age curve. The slope of this curve equals the somatic production of an individual of defined age/mass per time. With that value, the size distribution of a population can be used to calculate its production.

4.4

Dissimilatory Metabolism

4.4.1

Aerobic Respiration

Oxidation of Organic Substances Stoichiometry Aerobic respiration of carbohydrates is the reverse reaction of photosynthesis in terms of the summary budget, although biochemical pathways are completely different. C6 H12 O6 þ 6 O2 = 6 CO2 þ 6 H2 O

ð4:24Þ

The energy gain is 2802 kJ per mole of glucose. The stoichiometric ratio between oxygen consumption and CO2 release and oxygen consumption (respiratory quotient, RQ) depends on the substrate of oxidation and the extent how strongly these substances are reduced. Carbohydrates have an RQ = 1.0, proteins: RQ = 0.8 to 0.9, and lipids: RQ = 0.69 to 0.76. The effects of respiration on the oxygen availability in water are the reverse of the effects of photosynthesis. This means that oxygen consumption dominates in the

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dark and whenever heterotrophic processes dominate over oxygen producing photosynthesis. Energy gain The mass-specific energy gain of respiration decreases with the RQ and is highest for the most reduced organic substances. Since these have also the highest C-content per unit mass (lipids ca. 80%, carbohydrates ca. 40%), it is also correlated with the C-content. Carbohydrates have an average energy content of 17.2 kJ g-1, proteins on average 23.7 kJ g-1, and lipids on average 39.6 kJ g-1.

Oxygen Supply Transport within the body Even at 100% saturation, oxygen concentrations in water are much lower than in air, < 10 mL L-1 as opposed to 210 mL L-1. Since the diffusion of oxygen is very slow in the tissue of organisms, only organism with a tissue thickness < 1 mm can live without specialized systems for oxygen transport. Oxygen is transported by circulation of body fluids like blood or hemolymph. The capacity of body fluid to transport oxygen can be increased by respiratory pigments (hemoglobin, hemocyanin) which reversibly bind oxygen and release it at the site of demand. Gills The exchange of oxygen and CO2 with the surrounding water happens either at the entire body surface (mostly among very small organisms) or at gills. Gills have evolved multiple times in the phylogeny of animals and are morphologically not homologous at all. The common principle is thin epithelia and a branched or lamellate structure to increase the surface area. Gills might be external at the body surface or internal which provides a better protection against injury. Internal gills need active pumping of unused water, except for some fast-swimming high sea fish where fast swimming with an open mouth is sufficient for water supply to the gills. Coupling of respiratory and feeding flow The feeding current of many suspension feeders is also used as water current for the supply of oxygen. This might cause problems at high food densities above the incipient limiting level (Sect. 4.3.2) because the reduction of the pumping effort also reduces the supply of oxygen. Lung breathing Reptiles, birds, and mammals have to breathe air. This restricts their diving time and depth. However, there are big differences between species. The sperm whale (Physter katodon) can dive for 75 min and reach 2000 m depth, while the walrus (Odobenus rosmarus) reaches only 10 min dive-time and depth of 90 m (Andersen 1969). Adaptation to low oxygen Sediment endofauna live in an anaerobic or at least oxygen-poor environment. Burrowing animals can solve the problem by getting access to oxygenated water above the sediment surface by long siphons extending to the sediment surface, e.g., the bivalve Mya arenaria or by generating a constant flow of water through their burrows, e.g., the lugworm Arenicola marina (Fig. 4.17). Moreover, such animals are either particularly rich in hemoglobin or have

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Fig. 4.17 Supply of oxygenated water to endobenthic macrofauna, the polychaetes Pectinaria, Arenicola, and the bivalves Mya and Angelus (source: Fig. 4.16 in Sommer 2005)

hemoglobin with a higher affinity to oxygen, e.g., the oxygen affinity of Arenicola is more than about 3 times as high as the affinity of the hemoglobin of the mackerel Scomber scombrus (Penzlin 1977). Many benthic bivalves can strongly reduce their metabolism and thus persist oxygen-free periods. Problems with hydrogen sulfide Low oxygen concentrations are often accompanied by the production of toxic hydrogen sulfide (H2S). Some taxa show high tolerance to anoxic conditions even in the presence of H2S and are, therefore, found at low redox potentials (Reise and Ax 1979; Giere 1992). In the presence of oxygen, many endobenthic animals (e.g., Arenicola marina) can convert sulfide into non-toxic thiosulfate or to lesser extent into sulfite. The formation of thiosulfate occurs in the mitochondria. If the capacity to oxidize H2S is exceeded, it enriches the body fluids and blocks aerobic respiration. Sulfide-resistant animals then shift to sulfide-induced anaerobiosis even in the presence of oxygen (Oeschger and Vetter 1992).

4.4.2

Anaerobiosis

Anaerobic Respiration Nitrate respiration Organisms using nitrate as electron acceptor of respiration may be obligate or facultative anaerobic. During nitrate respiration nitrate is reduced via several intermediate steps either to nitrogen (denitrification) or to ammonium (nitrate ammonification), while the organic substances are oxidized to CO2. For

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a long time it was assumed that nitrate respiration should be restricted to Bacteria and Archaea, but Finlay (1985) found it also in ciliates. The energy gain of nitrate respiration is only ca. 10% less than the energy gain by aerobic respiration. The reduction steps of nitrate are: Nitrate ammonification : NO3 - → NO2 - → NO → NH2 OH → NH4þ Denitrification : NO3 - → NO2 - → NO → N2 O → N2

ð4:25Þ ð4:26Þ

Sulfate respiration Sulfate-reducing bacteria use the reduction of sulfate to H2S or other sulfur compounds for respiration. The organic substances are not completely oxidized. Often acetate remains as reduced organic residual. 8ðHÞ þ SO4 2 - → H2 S þ 2H2 O þ 2OH -

ð4:27Þ

Fermentation Fermentation is a process of gaining energy through splitting organic molecules into a reduced and an oxidized fragment. First polymers are split by hydrolysis into simple monomers, e.g., sugars, amino acids, and fatty acids. The oxidized end product of splitting those monomers is CO2, while the reduced end products are either organic substances such as organic acids and alcohols or reduced gases such as hydrogen, methane, or hydrogen sulfide. Fermentation of amino acids also produces NH4+ as reduced end product. Compared to respiration, fermentation is energetically not very efficient. Aerobic respiration of 1 mol glucose gains 2802 kJ. Fermentation to lactic acid gains 111 kJ and fermentation to ethanol 67 kJ. Methanogenesis Methanogenesis is a form of anaerobic metabolism of methanogenic Archaea which use CO2 as terminal electron acceptor. Methanogenic Archaea are strictly anaerobic. There are biochemical several pathways in the different groups, but only one-C compounds and acetate can be used as substrates. CO2 þ 4H2 → CH4 þ 2H2 O

ð4:28Þ

CH3 COOH → CH4 þ CO2

ð4:29Þ

The second pathway starting from acetic acid is responsible for ca. 2/3 of the microbially produced methane (Vogels et al. 1984). The dependence on compounds with only a few C atoms or on H2 makes the methanogens either dependent on fermenting microbes or on volcanic sources in hydrothermal vents.

Glossary

159

Animal Anaerobiosis Contrary to earlier assumptions, seome animals can also survive anaerobically for extended periods. Often, they rely on fermentation during which glycogen is split into propionate, acetates, and CO2 (Urich 1990). Since endobenthic bivalves have only limited storage pools of glycogen (5–12% of dry mass) sustained aerobic survival needs a strong reduction of metabolism. The anaerobic maintenance metabolism of Astarte borealis amounts to π/2: sustained oscillation around K with a period length of ca. 4τ. At very high levels of rmax τ there will be short, sharp peaks and long valleys. Effects of stepwise growth Similar and even more complex dynamics result from stepwise growth. Here, the product of R (geometric growth rate) and T (time length of discrete steps between growth events) decides about temporal dynamics. • Rmax T < 1: gradual approach to K • 1 < Rmax T < 2: dampened oscillations • 2 < Rmax T < 2.4495: persistent oscillation with values approaching 2 attractors, one above K, one below K, and N jumping between both attractors • 2.4495 < Rmax T < 2.6699: in this range the number of attractors doubles to 4 attractors, then (at 2.5) to 8 attractors, and further to 16 attractors (at 2.569) • Rmax T < 2.6699: deterministic chaos with seemingly irregular fluctuation. The temporal pattern depends strongly on initial conditions. Even slight difference in N0 may lead to completely different trajectories (Fig. 5.4).

Positive Density Dependence Minimal population size The exponential and the logistic growth curves do not require a minimal population size. But is there such a minimum, except for the trivial case that at least one couple is needed in sexually reproducing species? Conservation biologists use the term minimal viable population size (MVP, defined as the minimum needed to avoid inbreeding, random extinction, and genetic impoverishment by genetic drift (Sect. 5.5.2). In spite of the overall plausibility of this concept, it is not possible to define uniform MVPS for all species and circumstances. Cowley (2008) used a modeling approach for the NW American salmonid fish Oncorhynchus clarkii virginalis and estimated an MVP of 2750 fish, requiring ca. 2.2 ha at their median density in New Mexican streams. Conversely, Jager et al. (2010) found it difficult to assess a meaningful value of MVP for the white sturgeon Acipenser transmontanus. Moreover, they concluded that MVP has little relevance for conservation purposes and suggested minimal viable recruitment as better early warning value for conservation.

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Fig. 5.4 Temporal dynamics of populations following the stepwise version (n = number of steps) of the logistic growth function depending on the product Rmax T. Blue: N approaching 2, brown: 2 attractors, green: deterministic chaos (source: https://upload.wikimedia.org/wikipedia/commons/ thumb/b/b8/Discrete_logistic_equation-time_evolutions.svg/640px-Discrete_logistic_equationtime_evolutions.svg.png; Creative Commons Zero, Public Domain Dedication)

Quorum sensing Populations with the ability to perform a “division of labor” obviously also need minimal population sizes to do so. They have evolved mechanisms of quorum sensing, i.e., estimating their own abundance with the help of signaling substances. Quorum sensing is not only found in social insects and other animals of complex behavior; it is also found in bacteria. It enables bacteria to restrict the expression of certain genes in order to produce a distribution of phenotypes most beneficial for the population. In marine sciences, bacterial quorum sensing was studied most often in biofilms, including the identification of signaling substances (Hmelo 2017). Recently, there has also been an increasing interest in the role of quorum sensing for bacterial fish diseases. The bacterium Vibrio campbellii needs quorum sensing for being fully virulent for fish larvae (Noor et al. 2019).

5.3.3

Disentangling the Components of Population Dynamics

Modelers make assumptions about the different parameters of population growth and analyze their effects on patterns. Empirical population ecologists have the reverse problem. They observe changes in abundance and want to know how these changes have been driven by birth rates, death rates, etc. because these different components of population dynamics respond to different sets of environmental conditions.

5.3 The Mathematical Treatment of Population Growth

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Net Growth Rates Calculating net growth rates form time series of abundance is the easy part, although sampling errors might be vast, especially if there is a clumped distribution of individuals (Fig. 5.1). Calculation between the time point t1 and t2 can be performed by solving Eq. (5.4) for r: r = ðln N 2 – ln N 1 Þðt 2 –t 1 Þ - 1

ð5:9Þ

However, such a two-point calculation is not wise if there is too much sampling error. The scatter of data around the real trend leads to a zigzag of calculated r-values without much reality behind it. If samples are taken at sufficiently dense intervals and a semi-logarithmic plot (abundance in log scale, time in linear scale) indicates exponential growth, a linear regression of ln N on time is recommended. The regression slope b is then the estimate of r. The semi-logarithmic plot also permits quick visual judgment during which time interval we can assume exponential growth.

Gross Growth Rate and Birth Rate At least 2 of the 3 values in Eqs. (5.1) and (5.2) have to be known in order to calculate the third one. Determination methods of loss rates are as diverse as the different processes of loss and can, therefore, not be dealt with in a general textbook. There are, however, several well-established methods to estimate μ or b which shall be presented here. Mitotic index (frequency of dividing cells) The proportion of cells undergoing division ( pD) during a diel cycle is the most direct method to estimate gross growth rates of microorganisms. However, there is an additional need to analyze diel patterns of cell division by sufficiently frequent sampling. Otherwise, no correct estimate of pD is possible. It is further necessary to define the duration of the division stage selected (division time, tD) in order to distinguish whether division stages in a sample represent newly dividing cells or still the cells under division seen already during the previous sampling. Phototrophic microorganisms often have more or less synchronized cell divisions showing a distinctive diel pattern (Weiler and Chisholm 1976; Braunwarth and Sommer 1985; Chisholm 1981). In this case, it is possible to estimate the division time by the time shift between the frequencies of a morphologically defined division stage and its morphologically defined end point (Fig. 5.5). If there are no clear diel peaks in cell division, estimates of td have to be obtained from cultures. Egg ratios Calculating birth rates from the ratio of the number of eggs to the population abundance was initially developed for zooplankton where the mothers carry the eggs with themselves until hatching of the neonates (Paloheimo 1974), like cladoceran zooplankton (e.g., Daphnia). Contrary to Daphnia, many copepods species shed their eggs already before hatching. In this case, the animals have to be sampled alive and kept for several days and precaution has to be taken to avoid

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Fig. 5.5 Diel pattern of cell division of the cryptophycean flagellate Rhodomonas minuta in Lake Constance. The stage with not yet separated cells with two visible nuclei (after staining) was used to calculate growth rates. The stage with a beginning plasmatic division marks the end point of this stage (source: Fig. 5.5 in Sommer 2005, from Fig. 3 in Braunwarth and Sommer 1985, with permission by John Wiley and Sons)

feeding of eggs by adults, e.g., by a screen of plankton gauze, through which the eggs can fall but the adults cannot pass. Besides knowing the egg ratio (E; number of eggs per individual) the developmental time of eggs (D) has to be known to calculate the birth rate (b) B = lnð1 þ EÞ=D

ð5:10Þ

The egg ratio is usually a reflection of the feeding conditions, while D depends on temperature. In the large, boreal to subarctic marine copepod Calanus finmarchicus D is ca. 5 d at 0 °C and 1 d at 20 °C (McLaren 1963). Bottrell (1975) found higher values for freshwater cladocerans and copepods from river Thames, 14 to 23 d at 0 ° C and 3 to 4 d at 20 °C. Cohort analysis If animals reproduce synchronously and cohorts of individuals born at the same time can be followed up (e.g., with the help of size or year rings in mineral structures), the stepwise increase following reproduction represents the birth rate, while the continuous decline at times without reproduction represents mortality (Fig. 5.6).

5.4 Age Structure

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Fig. 5.6 Schematic representation of how birth and death rates can be calculated from the temporal change of abundance of a cohort (source: Fig. 5.7 in Sommer 2005)

Fig. 5.7 The three basic types of survival curves (a) and the age dependence of death rates of these types (b) (Fig. 5.7 on Sommer 2005)

5.4

Age Structure

5.4.1

Survival Curve

The survival curve of a populations describes the probability by which an individual will reach a certain age. Its shape depends on the age dependence of death rates. The fundamental types of survival curves can best be visualized in a semi-logarithmic plot where age is plotted linearly and relative survivorship on log scale (Fig. 5.7). Age independent mortality (type 1 in Fig. 5.7) leads to a straight falling line in semi-logarithmic plots. The probability of survival is the same at each age. This

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pattern is most closely represented by unicellular organisms. If they reproduce by binary fission, the size differences between the daughter cells after division and the mother cells before division are rather small, 1:2 in volumetric terms. Therefore, they share more or less the same spectrum of natural enemies. Predominance of juvenile mortality (type 2 in Fig. 5.7) leads to a downward bent survival curve with a steep decrease initially and a subsequent flattening of the curve. The survival probability of individuals increases with age. Predominance of juvenile mortality is most typically represented by those organisms which produce many offspring and, therefore, invest only few resources into the individual offspring. The more eggs, the smaller eggs usually are. Neonates of such organisms are much smaller than adults. Their smallness leads to an increased vulnerability to predation, because smaller predators are usually much more common than large ones and most small predators feed on small prey. Similarly, the ability of surviving starvation is smaller, the smaller the larvae are. Type 2 is most typically represented by many teleost fish which lay millions of eggs at each spawning event (e.g., cod, Gadus morhua) and have extremely high egg and larval mortalities. Predominance of old age mortality (type 3 in Fig. 5.7) is typical for animals with a small number of offspring, rather large eggs or neonates, high parental investments into the individual offspring, and in the case of birds and mammals parental care, feeding and protecting eggs and/or neonates.

5.4.2

Distribution of Age Classes

Equilibrium The age structure of a population is similar to the survival curve if a population is at equilibrium, i.e., if birth rates and death rates do not change much over time. If birth rates increase the younger age classes become overrepresented in the population and if birth rates decrease the older classes become overrepresented. Strong single age classes Age structure is not only determined by the long-term pattern of age-specific mortality. Also, the effect of singular events can be seen in age distribution of populations. Fish populations often contain single, particularly strong, year classes (Fig. 5.8). One of the usual explanations is the high mortality at the transition from yolk feeding to feeding on planktonic food in fish larvae. Strong year classes develop only when sufficient food of the right size (mainly copepod nauplii) is available at the right time. Such a match (sensu Cushing 1990) between supply and demand is a question of a few days. In many years, either the larval demand comes too early or too late or the right food is in time, but only at suboptimal densities. These conditions are called “mismatch.” Sites with single year classes Sometimes, only individuals of a single year class are found at a site. This may happen if planktonic larvae of benthos are carried to unusual sites by anomalies in water currents and settle where these animals normally have no access. There is also the possibility of negative effects of adults on juveniles, e.g., shading in phototrophs or space competition or feeding on conspecific

5.4 Age Structure

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Fig. 5.8 Age structure of herring catch in the North Sea; only herring >3y show up in the catch because of mesh width of the nets. The strong year class born 1904 can be seen until 1921 (source: Fig. 5.9 in Sommer 2005, after data in Schwerdtfeger 1968)

planktonic larvae by sessile benthic suspension feeders. Such effects are usually rather local and sampling of larger areas will lead to a more balanced age class distribution.

5.4.3

Life History Strategies

Timing of Reproduction The right time for investing energy and matter into reproduction is of utmost importance for the fitness of organisms (Stearns 1992). The timing of reproduction has consequences for the probability of successfully transmitting their own genes to the next generation. Vulnerability to predation, food shortage, and abiotic stress depend on the ontogenetic stage of the organism and vary in space and time. Evolution has found several solutions how to handle those risks. Semelparity. Insects with aquatic larvae, cephalopods, and several fish species (Pacific salmons, Oncorhynchus spp.; eel, Anguilla spp.) reproduce only once, at the end of their lifetime. This means that they can allocate matter and energy entirely to somatic growth and thus relatively quickly pass vulnerable early ontogenetic stages

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when the risk of predation and famine decreases with size. They can build up rich storage pools for investment into the final reproduction during a life without diverting resources into early reproduction. However, this is an “all or nothing” strategy. Microbes which reproduce by cell division are by definition semelparous, but also here there are several options. A microorganism may grow until doubling its initial size and produce 2 offspring or it might grow further and produce 2n offspring by repeated division at the time of reproduction. This means more but smaller offspring. Iteroparity means repeated reproduction during the lifetime. No adult growth: Iteroparous organisms might grow until reaching the mature size and then start reproduction. After first reproduction, there is no or almost no somatic growth; thus, energy and matter allocation into reproduction can be maximal. Among others, copepods, birds, and mammals represent this type. The costs of this reproductive pattern are a relatively late first reproduction and an elongated period risking pre-reproductive mortality. Adult growth is common among cladoceran zooplankton and many fish species. The age at first reproduction is one of the life history traits which varies strongly between species of otherwise similar life expectancy and even within species. It can have far-reaching effects on the fitness, depending on size or age specific environmental risks. Reproducing earlier means smaller mother animals and, therefore, smaller broods. In the case of a long life, this strategy can lead to more but smaller broods. In the case of an early death, this can mean having had at least one brood. The timing of first reproduction is under heavy selective pressure by the prevalent predation regime. Shifts in response to a changed mortality pattern can be by selection of different genes or result from phenotypic plasticity in response to the perception of predators (Stearns 1989). Box 5.1 Optimization of the Timing of First Reproduction Phenotypic plasticity. The freshwater zooplankton Daphnia has to face two types of predators. Most invertebrate predators (e.g., predatory copepods or larvae of the phantom midge Chaoborus) attack primarily small individuals. Fish and some invertebrates (e.g., the water bug Notonecta) prefer larger Daphnia. Daphnia reproduce pathenogenetically with occasional sexual production restricted to the production of resting eggs. This permits cultivation of genetically identical animals. Thus, any change of traits under different experimental conditions can be attributed to phenotypical plasticity and selection effects can be excluded. Stibor and Lüning (1994) exposed Daphnia hyalina to water containing chemical cues (kairomones) released from Chaoborus larvae, fish, and Notonecta. Daphnia perceiving (smelling) Chaoborus started to invest into reproduction only after having reached a body mass > 10 μg. Daphnia smelling fish or Notonecta started to invest into reproduction already at 2–5 μg. In the case of Chaoborus predation, it is better for fitness to pass the size range of vulnerability as fast as possible (fast somatic growth). In the case (continued)

5.4 Age Structure

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Box 5.1 (continued) of fish and Notonecta predation, it is better for fitness to reproduce before increasing size makes you vulnerable. Selection. Fisheries act like size-selective predation on exploited fish populations, e.g., by selectively targeting large fish or by relaxing predation on small fish by using nets of certain mesh size. Exploitation leading to shifts in the traits of fish populations is called “Darwinian fisheries” (Conover 2000; Law 2007). In heavily exploited populations, those individuals contribute more to future generations which mature early in spite of the fact that these small mothers produce less eggs than the older, larger ones. Hutchings (2005) found an earlier maturation of heavily exploited NW Atlantic cod (Gadus morhua) in response to fisheries. A more complicated pattern was reported by Sinclair et al. (2002) for the cod population of the Gulf of St. Lawrence. Sizespecific impacts of fisheries-induced mortality are dome shaped in this region, with maximal mortality at medium sizes. Large individuals escape from mortality by living in deeper waters. During the 1970s length-at-age values were high, indicating fast body growth in order to reach the protected large size refuge as soon as possible. At the end of the 1970s increases in the stock of cod made growth slower because of competition for declining food and fast passing of the most vulnerable intermediate size range became impossible. Therefore, it became more profitable to grow slower and invest more into early reproduction. Fisheries pressure on pike (Esox lucius) in the English freshwater lake Windermere decreased strongly from 1963 until the 2000s. Fisheries targeted mainly large fish. During the decrease of fisheries pressure, somatic growth rates increased and small females produced in the third year had much fewer eggs than their counterparts in 1963, indicating a stronger allocation of energy into somatic growth. At the age of 8 years, this difference was not visible anymore (Fig. 5.9) Law (2007) attempted to estimate how fast Darwinian fisheries would have an impact on life history traits, based on year-to-year differences in quantitative life history traits and a rather low level of heritability. He concluded that the effect of Darwinian fisheries would become clearly visible at a decadal time scale.

Typology of Life History Strategies r- vs. K-selection The concept of r- and K-selection (MacArthur and Wilson 1967) is a historic concept in ecology with some heuristic value, but heavily criticized because of its inherent simplicity. It was named after the two parameters of the logistic growth curve, rmax and K. It is obvious that different sets of traits are favored by selection in an uninhabited habitat open for colonization and in a habitat filled with organisms at or close to the carrying capacity. While initially meant to put all

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Fig. 5.9 Top left: change of fisheries pressure with mean trendline (note the maximum in 1963); top right: somatic growth rate (note the minimum in 1963); bottom left: relationship between gonad weight and body length for 3 years old females; bottom right: relationship between gonad weight and body length for 8 years old females (composed of elements from Figs. 1 and 2 in Edeline et al. 2007, with permission by PNAS)

species or even higher taxa into one of the two categories, it is now rather used to assign relative positions to species along a continuum (Pianka 1970). r-selected species have high maximal growth rates, have early reproduction, are short-lived, and have a high potential to colonize new habitats. These species are also called “opportunistic” or “pioneer” species. K-selected species grow slowly but more safely. They have to invest into conservation in the wide sense, i.e., avoid losses of biomass and mortality, tolerate starvation, maximize the efficiency of resource use, and produce few but well-nourished and well-protected offspring. Stearns (1992) criticized this concept because the traits associated with both types of strategy are not correlated enough to justify a one-dimensional gradient from r- to K-selection. This is particularly evident at the K-end of the gradient because there are many alternative adaptations to a crowded habitat. In spite of its oversimplified nature, the concept of r- and K-selection has inspired a lot of research and is still doing so, although with some decline of interest.

5.5 Genetic Structure

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Grime’s C-S-R typology Grime (1977) attempted to overcome the simplicity of the r- and K-continuum by ordinating species on a triangular plain with the corners R (ruderals), competitors (C), and stress tolerators (S). Ruderals are fast-growing organisms quickly recolonizing the habitat after disturbance (like r-selected species), competitors are productive species able to overgrow and outcompete other species, and stress tolerators are slow-growing species investing into tolerance to stress. Grime made no distinction between stress by abiotic factors and biotic stress, such as predation and competition. Grime developed his concept initially for terrestrial plants. Later it was adapted for phytoplankton by Reynolds (1988). Trait correlations The justified dissatisfaction with preconceived classification schemes motivated suggestions to concentrate on measurable traits and to look for positive and negative correlations among them (McGill et al. 2006; Petchey and Gaston 2006). Traits form an n-dimensional hyperspace in which species can be placed. For practical reasons, dimensionality of the hyperspace can be reduced by positive and negative correlations among traits. Correlations result from functional dependencies, e.g., the dependency of metabolic raters and generation times on size (Sect. 3.3.1, Fig. 3.1). Negative correlations may also result from trade-offs, i.e., from the problem of allocating resources to competing purposes, e.g., the trade-off between few but large or many but small offspring. Traits which explain much of the variance of other traits can be identified as “master traits” with the potential of reducing complexity (Litchman et al. 2010). Body size is currently probably the best investigated master trait. Trait-based ecology is an ongoing enterprise with high potential for the future.

5.5

Genetic Structure

The gene pool of a population is inevitably smaller than the gene pool of the entire species. This might be a simple statistical effect, because there is a higher probability that rare alleles exist in a species than in parts of it. Any new mutation arising in a single population counts for the entire species, but—at least initially—only for the population of origin. Further mechanisms reducing genetic diversity can either be neutral or result from selection. Neutral effects are effects not driven by selection, such as founder effects (only a few individuals establish a new population) and genetic drift (random loss of alleles). Selection effects, i.e., the disappearance of alleles with locally negative fitness effects, result in local adaptation.

5.5.1

Founder Effect

Founding individuals of a new population are often few and, therefore, have a strongly reduced genetic diversity compared to the population of origin and strongly biased allele frequencies. This founder effect (Mayr 1954) may have far-reaching consequences for the future genetic make-up of a population, especially if there is no

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continued flow of individuals from the population of origin into the newly established population. By truncating the original genetic diversity, founder effects may effectively reduce the scope for selection within the newly established population. The increasing interest in species invasions (Sect. 9.5) has also led to an increasing interest in comparing the genetic diversity of newly established populations with the populations of origin. The lionfish Pterois volitans and P. miles are fish from the tropical and subtropical Indo-Pacific region and were detected as invaders in the Western Atlantic Ocean. An analysis of cytochrome b haplotypes revealed a strong decrease of genetic diversity in comparison to the populations of origin (Hamner et al. 2007). Similarly, manmade reservoirs are an excellent opportunity to study founder effects. Haileselasie (2018) analyzed the genetic structure of Daphnia in 10 Ethiopian reservoirs and found strong evidence for founder effects and no correlation of gene identity or genetic diversity with local environmental conditions, suggesting little evidence for selection. Using different statistical approaches, the authors concluded that the numbers of founding individuals were