Progress in Botany Vol. 84 (Progress in Botany, 84) 3031457536, 9783031457531

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Progress in Botany  84

Ulrich Lüttge · Francisco M. Cánovas · María-Carmen Risueño · Christoph Leuschner · Hans Pretzsch   Editors

Progress in Botany

Progress in Botany Volume 84

Series Editors Ulrich Lüttge Department of Biology Technical University of Darmstadt Darmstadt, Germany Francisco M. Cánovas Department of Molecular Biology and Biochemistry University of Málaga Málaga, Spain Hans Pretzsch Chair for Forest Growth and Yield Science School of Life Sciences Weihenstephan Technical University of Munich Freising, Bayern, Germany María-Carmen Risueño Pollen Biotechnology of Crop Plants Group Centro de Investigaciones Biologicas “Margarita Salas” (CIB) CSIC Madrid Madrid, Spain Christoph Leuschner Plant Ecology University of Göttingen Göttingen, Germany

Progress in Botany is devoted to all the colourful aspects of plant biology. The annual volumes consist of invited reviews spanning the fields of molecular genetics, cell biology, physiology, comparative morphology, systematics, ecology, biotechnology and vegetation science, and combine the depth of the frontiers of research with considerable breadth of view. Thus, they establish unique links in a world of increasing specialization. Progress in Botany is engaged in fostering the progression from broad information to advanced knowledge and finally deepened understanding. All chapters are thoroughly peer-reviewed.

Ulrich Lüttge • Francisco M. Cánovas • María-Carmen Risueño • Christoph Leuschner • Hans Pretzsch Editors

Progress in Botany Vol. 84

Editors Ulrich Lüttge Department of Biology Technical University of Darmstadt Darmstadt, Germany María-Carmen Risueño Pollen Biotechnology of Crop Plants Group Centro de Investigaciones Biologicas “Margarita Salas” (CIB) CSIC Madrid, Madrid, Spain

Francisco M. Cánovas Department of Molecular Biology and Biochemistry University of Málaga Málaga, Spain Christoph Leuschner Plant Ecology University of Göttingen Göttingen, Germany

Hans Pretzsch Chair for Forest Growth and Yield Science, School of Life Sciences Weihenstephan Technical University of Munich Freising, Bayern, Germany

ISSN 0340-4773 ISSN 2197-8492 (electronic) Progress in Botany ISBN 978-3-031-45753-1 ISBN 978-3-031-45754-8 (eBook) https://doi.org/10.1007/978-3-031-45754-8 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 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. 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.

Contents

Explorations into the Physiology and Ecology of Grassland Plants and Ecosystems: One Agronomist’s Academic Journey . . . . . . . . . . . . Hans Schnyder

1

Origins of Life: A Proposal for an Alternative Approach . . . . . . . . . . . M. Thellier

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Regulatory Roles of Small RNAs in Forest Trees . . . . . . . . . . . . . . . . . Inês Modesto and Célia M. Miguel

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Serine Metabolic Networks in Plants . . . . . . . . . . . . . . . . . . . . . . . . . . Sara Rosa-Téllez, Rubén Casatejada-Anchel, Andrea Alcántara-Enguídanos, Alejandro Torres-Moncho, Maroua Dohgri, Celia Martínez-Serra, Sergio González-Nebauer, Isabel Arrillaga, Begoña Renau-Morata, Jesús Muñoz-Bertomeu, and Roc Ros

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Reactive Nitrogen Species in Plant Metabolism . . . . . . . . . . . . . . . . . . Lorena Aranda-Caño, Raquel Valderrama, Mounira Chaki, Juan C. Begara-Morales, and Juan B. Barroso

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Molecular Regulation of Starch Metabolism . . . . . . . . . . . . . . . . . . . . . Ángel Mérida

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Photorespiration and Improving Photosynthesis . . . . . . . . . . . . . . . . . . Michael Hodges

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Molecular Regulation of Plant Responses to Shade . . . . . . . . . . . . . . . . Irma Roig-Villanova and Jaime F. Martinez-Garcia

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Photoinhibition of PSI and PSII in Nature and in the Laboratory: Ecological Approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Masaru Kono, Riichi Oguchi, and Ichiro Terashima

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Contents

Distribution and Functions of Calcium Mineral Deposits in Photosynthetic Organisms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . J. A. Raven

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Soil Hydraulic Constraints on Stomatal Regulation of Plant Gas Exchange . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Fabian J. P. Wankmüller and Andrea Carminati

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Tree Mortality: Revisited Under Changed Climatic and Silvicultural Conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . H. Pretzsch and R. Grote

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Pollen: A Key Tool for Understanding Climate, Vegetation, and Human Evolution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . M. F. Sanchez Goñi

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Contributors

Andrea Alcántara-Enguídanos Institut de Biotecnologia i Biomedicina (BIOTECMED), Universitat de València, Valencia, Burjassot, Spain Departament de Biologia Vegetal, Facultat de Farmàcia, Universitat de València, Valencia, Burjassot, Spain Lorena Aranda-Caño Group of Biochemistry and Cell Signalling in Nitric Oxide, Department of Experimental Biology, Faculty of Experimental Sciences, University Institute of Research in Olive Groves and Olive Oils, University Campus Las Lagunillas, University of Jaén, Jaén, Spain Isabel Arrillaga Institut de Biotecnologia i Biomedicina (BIOTECMED), Universitat de València, Valencia, Burjassot, Spain Departament de Biologia Vegetal, Facultat de Farmàcia, Universitat de València, Valencia, Burjassot, Spain Juan B. Barroso Group of Biochemistry and Cell Signalling in Nitric Oxide, Department of Experimental Biology, Faculty of Experimental Sciences, University Institute of Research in Olive Groves and Olive Oils, University Campus Las Lagunillas, University of Jaén, Jaén, Spain Juan C. Begara-Morales Group of Biochemistry and Cell Signalling in Nitric Oxide, Department of Experimental Biology, Faculty of Experimental Sciences, University Institute of Research in Olive Groves and Olive Oils, University Campus Las Lagunillas, University of Jaén, Jaén, Spain Andrea Carminati Department of Environmental Systems Science, Institute of Terrestrial Ecosystems, Physics of Soils and Terrestrial Ecosystems, ETH Zurich, Zurich, Switzerland Rubén Casatejada-Anchel Institut de Biotecnologia i Biomedicina (BIOTECMED), Universitat de València, Valencia, Burjassot, Spain Departament de Biologia Vegetal, Facultat de Farmàcia, Universitat de València, Valencia, Burjassot, Spain vii

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Contributors

Mounira Chaki Group of Biochemistry and Cell Signalling in Nitric Oxide, Department of Experimental Biology, Faculty of Experimental Sciences, University Institute of Research in Olive Groves and Olive Oils, University Campus Las Lagunillas, University of Jaén, Jaén, Spain Maroua Dohgri Institut de Biotecnologia i Biomedicina (BIOTECMED), Universitat de València, Valencia, Burjassot, Spain Departament de Biologia Vegetal, Facultat de Farmàcia, Universitat de València, Valencia, Burjassot, Spain Sergio González-Nebauer Departamento de Producción vegetal, Universitat Politècnica de València, Valencia, Spain R. Grote Institute of Meteorology and Climate Research (IMK-IFU), Karlsruhe Institute of Technology, Garmisch-Partenkirchen, Germany Michael Hodges Université Paris-Saclay, CNRS, INRAE, Université Evry, Université Paris Cité, Institute of Plant Sciences Paris-Saclay (IPS2), Gif sur Yvette, France Masaru Kono Department of Biological Sciences, School of Science, The University of Tokyo, Tokyo, Japan Jaime F. Martinez-Garcia Institute for Plant Molecular and Cell Biology (IBMCP), CSIC-UPV, València, Spain Celia Martínez-Serra Institut de Biotecnologia i Biomedicina (BIOTECMED), Universitat de València, Valencia, Burjassot, Spain Departament de Biologia Vegetal, Facultat de Farmàcia, Universitat de València, Valencia, Burjassot, Spain Ángel Mérida Institute of Plant Biochemistry and Photosynthesis, Consejo Superior de Investigaciones Científicas, University of Sevilla, Sevilla, Spain Célia M. Miguel Faculdade de Ciências, Biosystems and Integrative Sciences Institute, Universidade de Lisboa, Lisbon, Portugal Inês Modesto ITQB NOVA, Universidade Nova de Lisboa, Oeiras, Portugal Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium Faculdade de Ciências, Biosystems and Integrative Sciences Institute, Universidade de Lisboa, Lisbon, Portugal Jesús Muñoz-Bertomeu Departament de Biologia Vegetal, Facultat de Farmàcia, Universitat de València, Valencia, Burjassot, Spain Riichi Oguchi Botanical Gardens, Osaka Metropolitan University, Osaka, Japan

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H. Pretzsch Chair for Forest Growth and Yield Science, TUM School of Life Sciences, Weihenstephan, Technical University of Munich, Freising, Germany Sustainable Forest Management Research Institute iuFOR, University Valladolid, Valladolid, Spain J. A. Raven Division of Plant Science, University of Dundee at the James Hutton Institute, Dundee, UK Climate Change Cluster, University of Technology Sydney, Ultimo, NSW, Australia School of Biological Sciences, University of Western Australia, Crawley, WA, Australia Begoña Renau-Morata Institut de Biotecnologia i Biomedicina (BIOTECMED), Universitat de València, Valencia, Burjassot, Spain Departament de Biologia Vegetal, Facultat de Farmàcia, Universitat de València, Valencia, Burjassot, Spain Irma Roig-Villanova Serra Húnter Fellow, Department of Agri-Food Engineering and Biotechnology, Barcelona School of Agri-Food and Biosystems Engineering, Castelldefels, Spain Roc Ros Institut de Biotecnologia i Biomedicina (BIOTECMED), Universitat de València, Valencia, Burjassot, Spain Departament de Biologia Vegetal, Facultat de Farmàcia, Universitat de València, Valencia, Burjassot, Spain Sara Rosa-Téllez Institut de Biotecnologia i Biomedicina (BIOTECMED), Universitat de València, Valencia, Burjassot, Spain Departament de Biologia Vegetal, Facultat de Farmàcia, Universitat de València, Valencia, Burjassot, Spain M. F. Sanchez Goñi Ecole Pratique des Hautes Etudes, Paris Sciences Lettres (EPHE, PSL), Paris, France UMR EPOC, Université de Bordeaux, CNRS, Pessac, France Hans Schnyder Technische Universität München, Munich, Germany Ichiro Terashima Department of Biological Sciences, School of Science, The University of Tokyo, Tokyo, Japan M. Thellier French Academy of Sciences, Paris, France French Academy of Agriculture, Paris, France Alejandro Torres-Moncho Institut de Biotecnologia i Biomedicina (BIOTECMED), Universitat de València, Valencia, Burjassot, Spain Departament de Biologia Vegetal, Facultat de Farmàcia, Universitat de València, Valencia, Burjassot, Spain

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Contributors

Raquel Valderrama Group of Biochemistry and Cell Signalling in Nitric Oxide, Department of Experimental Biology, Faculty of Experimental Sciences, University Institute of Research in Olive Groves and Olive Oils, University Campus Las Lagunillas, University of Jaén, Jaén, Spain Fabian J. P. Wankmüller Department of Environmental Systems Science, Institute of Terrestrial Ecosystems, Physics of Soils and Terrestrial Ecosystems, ETH Zurich, Zurich, Switzerland

Curriculum Vitae

Prof. em. Dr. Hans Schnyder I am an emeritus professor of grassland science, with long experience in teaching and research of grassland ecology and management, crop and forage plant physiology, and stable isotope uses in physiology, ecology, and environmental studies. Address

Email Researcher ID Homepages

Technical University of Munich School of Life Sciences c/o Crop Physiology Alte Akademie 12, D-85354 Freising-Weihenstephan, Germany [email protected] orcid.org/0000-0002-0139-7535 www.researcherid.com/rid/B-7089-2011 www.researchgate.net/profile/Hans_Schnyder www.professoren.tum.de/schnyder-hans https://scholar.google.de/citations?user=IHb-11oAAAAJ&hl=de

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Curriculum Vitae

Name Date of birth Place of birth Nationality Family status

Johannes (‚Hans‘) Schnyder 25 April, 1954 Morges (VD), Switzerland Swiss, permanent resident of Germany Married in 1979, 4 children

Degrees, Honors, and Awards Since 2017 2001 1999 1997 1990 1985/86 1984 1979

Foreign corresponding member, French Academy of Agriculture Visiting research professor for plant ecophysiology, University of Paris-Orsay Dale Smith lecturer, Department of Agronomy, University of Wisconsin-Madison Visiting professor, AB-DLO, Wageningen Habilitation (Agronomy and Grassland Science), University of Bonn Research scholarship, Swiss National Science Foundation Dr. sc. techn. ETH Zurich Dipl. Ing. Agr. ETH Zurich, Agronomy and Grassland Science

Employment 19942020 19931994 19901994 19851986 19841990 19791984

Full professor (C4), Chair of Grassland Science, Technical University of Munich Lecturer, Institute of Plant Production and Breeding, University of Natural Resources and Life Sciences, Vienna Senior Research Fellow (Oberassistent, C2) and Adjunct Teaching Professor, Institute of Plant Production, University of Bonn Postdoctoral Research Fellow, Department of Agronomy, University of MissouriColumbia Research Fellow (Hochschulassistent, C1) Institute of Plant Production, University of Bonn PhD student and research assistant, Institute of Plant Production, ETH Zurich

Teaching (lectured full courses) 1994-2020

Technical University of Munich

Fall 1993summer 1994 1990-1994

University of Natural Resources and Life Sciences, Vienna University of Bonn

Multiple courses covering the spectrum of grassland ecology and management (including applied grassland phytosociology), forages, grassland plant physiology in diploma, BSc and MSc curricula for students of agriculture Crop physiology and agronomy

Applied grassland phytosociology

Curriculum Vitae

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Supervising Experience I have supervised more than 25 PhD students and a large number of diploma, BSc, and MSc theses. Membership in Professional Societies (current and past): Gesellschaft für Pflanzenbauwissenschaften (German Society of Agronomy), Schweizerische Gesellschaft für Pflanzenbauwissenschaften (Societé Suisse d’Agronomie), European Society of Agronomy, European Geophysical Union, Crop Science Society of America, Agronomy Society of America, American Society of Plant Physiologists. Activity as Reviewer and Editor (current and past) Editorial Boards I have served on the Editorial Boards of European Journal of Agronomy, Journal of Plant Physiology, Journal of Agronomy and Crop Science, Agronomie, Pflanzenbauwissenschaften/German Journal of Agronomy Reviewer for Scientific Journals I have reviewed original research papers for >20 international scientific journals, including: Proceedings of the National Academy of Sciences (PNAS), Global Change Biology, New Phytologist, Plant Cell & Environment, Plant Physiology, Journal of Experimental Botany, Planta, Physiologia Plantarum, Annals of Botany, Plant Methods, Plant Physiology and Biochemistry, Journal of Vegetation Science, Oecologia, Canadian Journal of Botany, Tree Physiology, Trees, European Journal of Agronomy, Agriculture Ecosystems and Environment, Journal of Agricultural Science (Cambridge), Australian Journal of Agricultural Research, Journal of Plant Nutrition and Soil Science, Plant and Soil, Agronomie, Atmospheric Environment, Analytical and Bioanalytical Chemistry, Rapid Communications in Mass Spectrometry. Reviewer for Grant Agencies European Commission, German Research Foundation, USDA, Swiss National Science Foundation, and others. Other International Activities as Reviewer I have been active internationally as a member of visiting groups of major research institutions in the UK and France, as a reviewer of faculty tenure or promotion proposals at Universities and at major research institutions in the US, UK, New Zealand, and Czechia, and as an examiner of PhD theses in France, the Netherlands, and Switzerland, and others. University Service I have served in the School Council and as head or member of several faculty search and evaluation committees at the TUM School of Life Sciences

Explorations into the Physiology and Ecology of Grassland Plants and Ecosystems: One Agronomist’s Academic Journey Hans Schnyder

Contents 1 Prologue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Photorespiration, Oxygen Inhibition of Photosynthesis, Activation State of Rubisco and Onwards . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 On the Leaf Growth Process in Grasses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Experimental Tracer Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 13CO2/12CO2 Labelling and Gas Exchange Facilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 The Role of Stores in Supplying Substrate for Vegetative and Reproductive Growth, and Respiration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Disentangling CO2 Fluxes: Photosynthesis Versus Respiration in Light, and Autotrophic Versus Heterotrophic Ecosystem Respiration . . . . . . . . . . . . . . . . . . . . . . . 5 Stable Isotope Ecology and Biogeochemistry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 Animals as Recorders and Integrators of Environmental and Dietary Isotopic (13C, 15 N, 18O) Signals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Effects of Anthropogenic Climate Change on the Water-Use Efficiency and Stomatal Conductance of Grassland Vegetation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Trying to Understand the 18O Signal in Plant Water Pools and Carbohydrates . . . . . . . . . . . . 7 Epilogue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2 3 8 11 11 15 19 21 24 28 32 35 38

Abstract This review gives an account of one agronomists’ and his teams’ contribution to the understanding of some aspects of the physiology and ecology of grassland plants and ecosystems. The topics span across multiple spatial and temporal scales, from the cellular basis of leaf growth in grasses, to functional components of CO2 exchange at leaf to ecosystem scale, the role of carbohydrate (fructan) stores in recycling of sucrose and supporting respiration and vegetative and reproductive growth in benign and stressful conditions, the multi-seasonal 18 O-ecohydrology of a pasture, last-century climate change effects on intrinsic

Communicated by Ulrich Lüttge and Hans Pretzsch H. Schnyder (✉) Technische Universität München, Munich, Germany e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 Progress in Botany (2024) 84: 1–46, https://doi.org/10.1007/124_2023_72, Published online: 23 June 2023

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water-use efficiency and canopy-integrated stomatal conductance of a range of grassland communities with contrasting nutrient status and plant functional group composition, regional scale changes of the C4/C3 abundance ratio in Inner Mongolia grassland, to ecological fingerprints of cattle based agroecosystems derived from the stable isotope composition of animal tissues, such as hair and milk. Much of the research relied on the development or improvement of methodology, including stable isotope techniques, encompassing 13CO2/12CO2 gas exchange and dynamic (or steady-state) labelling systems from leaf-scale in controlled conditions to ecosystem-scale in natural environments, analysis of tracer kinetics with compartmental models, and interpretations of natural isotope signals in biomass (13C/12C, 15 14 N/ N, 18O/16O) or water pools (18O/16O, 2H/1H) of soil, vegetation, and animals. Keywords Biological archives, C3 and C4 grasses, Carbohydrate stores, Cellulose, Climate change, Compartmental modelling, Ecological fingerprints, Fructan, Isotopes (14C, 13C/12C, 18O/16O, 15N/14N), Leaf growth, Nitrogen uptake and cycling, Photosynthesis, Respiration, Sink physiology, Sucrose, Tracer studies, Water-use efficiency

1 Prologue My streak of luck began when my parents first met on the farm of an old Friesian farmer in Normandy/France some years after the end of the second world war. My mother was a home economics teacher from Friesland/Netherlands and had just graduated. My father was a trainee on the Normandy farm and himself a farmer and future heir of his paternal farm in the hill country of the Canton of Fribourg/ Switzerland near the German-French language border. In my earliest childhood recollection, I am sitting on a patch of dry grass in the bright warm afternoon sun, leaning against the side of a wooden shed. It must have been in late winter; the snow was still deep. I could touch it with my feet from where I was sitting. In another early reminiscence I was lying on my back on grass looking up into a deep blue sky with a few small cumulus clouds. It was fall, all colours were intense, and apples were brilliant red in the orchard of my parents’ farm. I grew up together with five siblings in a hamlet of four farms. We were roaming nearby fields, forests, and the farmstead in any weather. Going to school for the first time brought about an abrupt change of habits. Also, I remember well the essence of a one-sided conversation with a farmhand when I was perhaps 5 years old. He told me that I would never become a true farmer (I must have misused a tool to raise his anger). Initially I was unsettled as I knew little beyond farming. But only in my late teens did I start to really ponder professional options. A career adviser suggested biology. Finally, I chose to study agriculture at ETH Zürich, perhaps because this seemed to connect childhood and youth experiences with an uncertain predicted talent. I was not too fond about lectures in general as I was slow in taking notes. But I liked general botany (Philippe Matile),

Explorations into the Physiology and Ecology of Grassland Plants. . .

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animal breeding (Fritz Weber), crop physiology, and forages and grassland agriculture (Josef ‘Joe’ Nösberger), so – in fact – basic and applied biology topics. It was only after the second study year at ETH, during a 1-year study break, of which I passed a few months as a trainee at the INRAE station of Lusignan/France, that I first grasped a sense of attraction towards scientific and research practice. I was assigned a large set of primary data from a multi-year trial with alfalfa (Medicago sativa), instructed to perform a statistical evaluation of the data and write a report. The trial had been performed with a standard cultivar (‘Europe’) and an experimental variety (‘Maison Celle’) with improved forage quality due to its higher leaf-to-stem ratio. Different plots were subject to different dates of the first cut and cutting intervals, and cut herbage evaluated for feed quality, assessed by measurements of voluntary intake and digestibility by sheep. The main message of the study was that there was a trade-off between forage quality and both yield and perenniality of alfalfa stands. I thoroughly enjoyed the exploratory nature of the work. Learning-by-doing the tools of the trade was my preferred way of acquiring knowledge. My diploma thesis with Joe Nösberger and Peter Thomet was concerned with the dynamic of spring growth of a range of botanically diverse pasture communities in the Swiss Jura mountains. My wife did her thesis in the same project, and had helped to set up my plots. I was loaned a bar mower and a Volkswagen van from the Swiss Army, crisscrossed the region to visit the sites and made weekly cuts on separate plots followed by ‘botanical analysis’ (separation of the herbage by species). I learned a lot about botany (from the Ancient Greek word botanē (βoτάνη), which means ‘pasture’, ‘herbs’, ‘grass’, or ‘fodder’, Wikipedia), especially grassland plant ecology and sociology at the time.

2 Photorespiration, Oxygen Inhibition of Photosynthesis, Activation State of Rubisco and Onwards After my diploma thesis (1979), I was offered a PhD student assistantship by Joe Nösberger at ETH. Nösberger had a very strong group of resourceful PhD students working on different topics of crop physiology and ecophysiology of grassland plant species and wheat. Later, in 1993, the Nösberger group set up the famous Swiss FACE, the first and long-running large-scale free-air carbon dioxide enrichment experiment on managed grassland (Zanetti et al. 1997; Ainsworth and Long 2005). Felix Mächler, a senior researcher in the group of Nösberger, was my advisor. Felix had received his PhD in the same group a few years earlier and passed a postdoctoral stay with Alfred Keys (Rothamsted/England) to study Rubisco (Keys et al. 1978; Mächler et al. 1980). In his PhD studies Felix had found that altitudinal ecotypes of white clover (Trifolium repens L.) collected near Chur (600 m a.s.l.) and Arosa (2,030 m) and grown in the same controlled environment differed in their dependence on temperature of the net rate of photosynthesis (Mächler and Nösberger 1977) and photorespiration, based on 14C labelling of glycine and serine (Mächler

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et al. 1977). Photorespiration was a hot topic at the time (and still is; e.g. Busch 2020), being recognized essentially as an enormously wasteful process. It was thought that suppressing it and the associated oxygen inhibition of photosynthesis could increase net photosynthesis by up to 50% at ambient atmospheric CO2 concentration (Chollet and Ogren 1975; Keys et al. 1977). I was expected to study photorespiration of these altitudinal ecotypes at their field sites and was entrusted with a portable custom-built apparatus which included an infrared gas analyzer, a clamp-on leaf cuvette, constructed after a design of Shimshi (1969), and a compressed air cylinder with a 14CO2/12CO2 mixture in air. The apparatus should permit simultaneous measurements of gross (or true) photosynthesis (Vc, the rate of carboxylation of RuBP) and net photosynthesis (A) by short-term labelling of photosynthetic CO2 incorporation via Rubisco in parallel with net CO2 exchange measurements with an infrared CO2 gas analyzer (Ludwig and Canvin 1971). The difference between Vc and A corresponds to the sum of photorespiration and dark respiration in light (Rd), with photorespiration expressed as half the rate of oxygenation of RuBP (0.5 Vo), thus (Farquhar et al. 1980): A = Vc –0:5 Vo –Rd :

ð1Þ

When measured at high light in ambient conditions, Rd is commonly very small in comparison with photorespiration, and is sometimes neglected (Ludwig and Canvin 1971), as I did then. Estimation of Vc requires that the labelling is very short (e.g. 20 s; Schnyder 1984), so that none of the 14CO2 fixation products have time to be processed and evolved in respiratory metabolism or exported from the labelled leaf. To be accurate, the 14CO2/12CO2 mixture for labelling must have a known constant isotope ratio (or ‘specific activity’) and recovery of the 14C during the analysis (combustion in a sample oxidizer for liquid scintillation counting), and consider 14C discrimination in photosynthesis. For reasons still unknown, however, I was unable to get the apparatus to work properly, despite months-long, tiresome trials and attempts to improve protocols and instrument settings, including rebuilding of our sample oxidizer, which had been ‘optimized’ by prior users. I was frustrated and about to give up, when Felix came to my rescue and suggested to start working with him using a ‘Felix-built’, laboratory-based gas exchange system that permitted short-term 14CO2/12CO2 labelling (Fig. 1a). This was a fantastic machine. We literally worked side-by-side day-by-day, exposed detached white clover leaves to various combinations of CO2 and O2 concentration at different temperatures, waited until net CO2 exchange rates had reached a steady-state and then performed short-term 14CO2/12CO2 labelling to estimate gross photosynthesis, and photorespiration as the difference between gross and net photosynthesis (Schnyder 1984). During waiting times, we read and discussed loads of papers on the physiology and biochemistry of photosynthesis. In preliminary tests we had performed leaf-level 14CO2/12CO2 labelling experiments over periods of 10, 20, and 30 s, and found a linear increase of 14C content of leaves, with the slope of the line passing through the origin of the plot, as it should. I have rarely learned as much as then,

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Fig. 1 Gas exchange and labelling systems, from leaf to field scale. (a) Leaf-scale CO2 gas exchange and 14CO2/12CO2 labelling system for true photosynthesis, net photosynthesis, and photorespiration measurements. Referenzgas, reference gas; Cüvettengas, gas for leaf cuvette; Spülgas, CO2-free gas for purging glass bulb 20. A-E, four-way valves; 1, CO2 gas cylinder; 2, N2 gas cylinder; 3, O2 gas cylinder; 4, Wösthoff gas mixing pump (Type 18); 5, Wösthoff gas mixing pump (Type 27,); 6, electromagnetic piston pump, 7, variable voltage transformer; 8, 2-L gas washing bottle; 9, flow meter; 10, custom-built leaf gas exchange cuvette (0.25 L) made of copper and glass with Micronel ventilator; 11, thermocouple and temperature gauge; 12, temperature controlled water bath; 13, dehumidifier (ice trap in thermos); 14, dehumidifier (magnesium

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thanks to Felix. Later, I used this 14CO2/12CO2 gas exchange system to study the effect of CO2, O2, temperature, and light on in vivo initial activity (‘activation state’) of Rubisco in white clover leaves (Schnyder et al. 1984). The activation state of Rubisco was determined in experiments which did not involve prior short-term 14 CO2/12CO2 labelling as the assay of Rubisco also required 14CO2/12CO2 labelling. For this again, leaves were incubated under different environmental conditions (including CO2 and O2) and then rapidly ground in an ice-cold mortar in a CO2free buffer with 20 mM MgCl, and 100 μL of the enzyme extract assayed by addition to 400 μL of a solution with the substrates of Rubisco at rate saturating concentration (0.4 mM RuBP and 10 mM NaH14CO2, 0.1 Curie mol-1 in the test medium) following the method of Lorimer et al. (1977) as detailed in Mächler and Nösberger (1980). The reaction was stopped after 30 s by adding 100 μL of 0.1 M HCl to the 500 μL test medium, and the amount of acid stable 14C-fixation products determined (Schnyder 1984). These investigations demonstrated a lack of oxygen inhibition of net photosynthesis in cool conditions (10°C) and was associated with a partial inactivation of Rubisco (Schnyder et al. 1984). To dig deeper, I proceeded with experiments in which I also measured temporal changes of RuBP and ATP concentration and Rubisco activity in leaves after a switch from 20 to 2% O2 in cool conditions. This demonstrated that Rubisco inactivation at low temperature (8°C) and 2% O2 was preceded by an abrupt decrease of ATP concentration following the

Fig. 1 (continued) perchlorate filter); 15, infrared gas analyzer (URAS 2); 16, Infrared gas analyzer (BINOS); 17, chart recorder; 18, sodium-vapour lamp; 19, plexiglass tray with water (8 cm deep); 20, glass bulb with rubber stopper; 21, piston pump; 22, reference gas for BINOS (for details, see Schnyder 1984). (b) Stand-scale open steady-state 13CO2/12CO2 labelling system consisting of four main components: a plant growth cabinet equipped for CO2 control, a cylinder containing CO2 with known 13C/12C isotope composition, a screw compressor, which feeds an adsorption dryer with air compressed to approx. 8 MPa. AC, adsorber chamber containing molecular sieve; AR, air receiver; BV, ball valve; C, controller of growth cabinet; CD, condensate drain; DV, discharge valve; FM, flow meter; GA, CO2 analyzer; MF, microfilter; NRV, non-return valve; PG, pressure gauge; PR, pressure regulators; RN, relaxation nozzle; SV, solenoid valve. For details, see Schnyder (1992). (c) 13 CO2/12CO2 gas exchange and labelling system. SC, screw compressor; AD, adsorption dryer; AR, air receiver; F1, oil and water condensate drain, F2 oil, water, and particle filter, F3, universal filter; GMS, gas mixing system; CO2, cylinder containing CO2 of mineral or fossil-organic origin; Growth chamber; SAS, sample air selector; IRGA, CO2 and H2O infrared gas analyzer; IRMS, 13 CO2/12CO2 isotope ratio mass spectrometer; PC, central control and data acquisition systems. For clarity a number of auxiliary components of the system are not depicted here. For details of the system and its operation, see Schnyder et al. (2003). (d) Open top chamber-based 13CO2/12CO2 gas exchange and labelling system. The system consisted of four open-top chambers (OTCs, only one OTC shown for clarity): CB, chamber body; RP, removable plate; FT, frustrum top; BV, buffer volume; SC, soil collar. Air supply unit: COMP, screw compressor; AD, adsorption dryer; MFC1, mass flow controller for air flow; MFC2, mass flow controller for CO2 flow; ADT, air distribution tube. Gas exchange observation unit: STin/STout, sampling tubes for chamber inlet/outlet; CF, coarse filter; SV1 and SV2, three-way solenoid valves for sample selection; P1, sample pump; P2, bypass pump; IRGA, infrared gas analyzer; P3, mass spectrometer sample air pump; MS, gas chromatographic column and isotope ratio mass spectrometer. Thick lines indicate flow to/through the chamber, and thin lines indicate sample air flow. All OTCs had their own gas mixing unit, and gas supply and sampling air lines. For details, see Gamnitzer et al. (2009)

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change from 20 to 2% O2, and a transient decrease of RuBP concentration (Schnyder et al. 1986). Likely, Rubisco activase, which responds to ATP (Portis et al. 2008), was involved in the transient partial inactivation of Rubisco, a mechanism that was unknown to us at the time. Sometime during the final year of my PhD studies, I was offered a position to pursue habilitation from Walter Kühbauch in his new group at the Institute of Agronomy, University of Bonn/Germany. One of the research topics proposed by Kübauch was ‘the determination of the role of carbohydrate stores in vegetative plants parts of wheat for grain filling’. Kühbauch was an authority on the physiology and agronomy of fructans, the most import non-structural carbohydrate reserve of vegetative plants parts in grasses (and other plant families and microorganisms; Versluys et al. 2017), and had an excellent PhD student (Udo Thome; Thome and Kühbauch 1985; Kühbauch and Thome 1989) studying the effects of source–sink manipulations on the accumulation and loss of fructans in different plant parts of wheat using HPLC. The offer by Kühbauch was the first time a possible academic career appeared on my horizon. Joe Nösberger thought about that too, and 1 day invited me for dinner in the roof-top faculty restaurant at ETH. He thought I might succeed; in fact, he had even studied the academic ‘landscape’ of his (or our) discipline (Grassland Science, Crop Physiology, Agronomy) in Germany, thinking also about retirement ages of colleagues in relation to the time it would take me to achieve habilitation! Realizing I was expected to lead a small research group, I thought that I could surely benefit from prior postdoctoral experience on a different research topic to widen my horizon, before starting in Bonn. Kühbauch agreed, and I applied for a postdoc with C. Jerry Nelson at the University of Missouri-Columbia, supported by a scholarship from the Swiss National Science Foundation. I had known Jerry from his sabbatical at ETH. Also, the University of Missouri-Columbia had a very strong Plant Physiology and Biochemistry programme. Ahead of the postdoc, I spent the second half of 1984 with Kühbauch and prepared a research proposal on the role of pre-anthesis reserves for grain filling in wheat, to be submitted to the German Research Foundation (DFG), hoping it would be accepted by the time when I returned to Bonn (I was lucky). Working with Kühbauch, I enjoyed all the academic freedom I could have wished for, and got my habilitation in 1990. In looking back, I realize that in some way or another, all of the topics I touched in my PhD (photosynthesis), in the postdoc with Jerry (sink physiology) and during habilitation with Walter Kühbauch (carbohydrate metabolism in C3 grasses) had an impact on the work that we did subsequently, when I accepted the offer for the Chair of Grassland Science in 1994 at the Technical University of Munich (TUM) in Freising, a post I would hold until my retirement in 2020. This was true even for many research activities in grassland ecology which were initiated and evolved at TUM, as I explain in Sects. 5 and 6.

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3 On the Leaf Growth Process in Grasses Arriving in St Louis shortly after New Year in 1985, Jerry awaited us – my wife Monica and our 5 months old son Simon and me – at the airport and took us to our apartment in Columbia/Mo, a 2.5 h drive over deep-frozen, snowy interstate 70. Our apartment had been completely furnished by Jerry’s students and John Coutts, the technician! My son had two beds! Everything had been thought of! Including a big refrigerator and food. What a surprise! What a welcome! We had not been told. On the next day, a Sunday, Bill Spollen and Terry Vassey, two of Jerry’s PhD students, arrived to help us with shopping of whatever we needed extra. On Monday, Jerry took us to a car dealer in Boonville, and we got our car, ‘Greenie’, a 1976 model Mercury Marquis, in fine shape, for 1800 US dollars, a very good buy, except that it was not fuel-efficient at all. In a few days, virtually all practical matters had been taken care of! This was a real lesson, and a generous and wonderful one at that. Jerry was very interested in the morphophysiological mechanisms that underlie yield potential of tall fescue (Festuca arundinacea) genotypes, and to that end had a unique joint research programme with a breeder, David A. Sleper. This programme involved recurrent restricted phenotypic selection for a range of morphophysiological traits, including the rates of leaf elongation (LER), tiller production, and net photosynthesis. This work had identified LER as a useful selection criterion for increasing yield (Horst et al. 1978; Volenec and Nelson 1982), and therefore sparked an interest in the physiology and cellular dynamics of the leaf growth process in grasses. Jerry had many excellent master and PhD students working on the topic. In particular, the groundwork of Jeffrey ‘Jeff’ J Volenec on the leaf meristem of tall fescue (e.g. Volenec and Nelson 1981, 1984a, b and citations therein) was of immediate relevance to my work. Of equal importance and most timely and consequential was a review by Wendy K. Silk (1984) which provided a mathematical framework for the description of the spatial distribution of substance deposition (or net synthesis rates) inside growing tissue, such as along the meristem and growth zone of individual roots. Wendy was a most helpful guide in the application and interpretation of that framework. Such analyses required a knowledge of both the spatial distributions of growth rates (relative elemental growth rates and displacement velocities) and substance contents in the growth zone. The leaf growth zone of grasses is also a formidable object for such studies: (1) the growth zone is located at the base of the elongating leaf and is enclosed by the sheaths of older leaves; thus the growth zone is heterotrophic and all assimilate demands within it have to be met by import of assimilates (chiefly sucrose and amino acids; Schnyder and Nelson 1987; Gastal and Nelson 1994) either from the exposed part of the elongating leaf itself, or from older leaves, (2) cell division occurs at the base of the leaf, near the point of attachment to the tiller axis (unelongated stem in vegetative grasses), and continued division and expansion cause a displacement of cells away from the leaf base (Schnyder et al. 1990). As cells are displaced they expand and mature/differentiate, so that cells of successively more advanced stages of development are found as one moves away from the leaf

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Fig. 2 Grass tussock after a fire in Palmar National Park, a temperate-humid savanna in Argentine Mesopotamia, Entre Rios Province (Foto: Hans Schnyder)

base towards the location where cells/young leaf tissue become exposed to light. Being located at the base of the leaf and concealed by the sheaths of older leaves, the leaf growth zone of grasses during vegetative development is perfectly protected from grazing and fire, a common natural disturbance in grasslands. Therefore, regrowth/re-foliation of grasses following fire (Fig. 2) or grazing is generally very rapid. As the growth zone is not directly observable (being concealed by sheaths), the goal of my first research was to develop a quantitative method for the assessment of the distribution of growth rates along the leaf growth zone. I used a thin needle constructed from a plain steel guitar string to poke fine holes through the base of tillers with approximately equidistant spacing and perpendicular to the tiller axis. After approx. 6 h, tillers were excised and distances between holes determined with a calibrated ocular, first in the outer non-growing sheath (to provide a reference for the initial spacing of holes) and then along the base of the elongating leaf. These data were then evaluated in terms of segmental elongation rates (or relative elemental growth rates). Although punching holes caused a depression of LER, the relative distribution of growth appeared to be virtually unaffected, so that the growth distribution could be corrected for the reduced LER, to provide an estimate of the growth rate distribution in intact elongating leaves (Schnyder et al. 1987; Schnyder and Nelson 1987). I did not think that this technique merited a separate publication, but Jerry thought otherwise. It was not until 1 day shortly before Christmas in 1985, we were standing in the hall in front of Jerry’s office (he was about to drive to northern Iowa with his family, to visit relatives and go ice fishing with his father-inlaw, if I remember correctly), when I agreed. I did some additional measurements between Christmas and New Year’s Eve, and we wrote the paper (Schnyder et al.

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1987). Jerry was right. Later, in Bonn, we compared growth rate distributions derived from pinning and epidermal cell length patterns of perennial ryegrass (Lolium perenne) plants grown in continuous light and found virtually identical results (Schnyder et al. 1990). Jeff Volenec had observed a very high concentration of fructan (>20% of dry mass) in the bulk growth zone of tall fescue (Volenec and Nelson 1984a, b). This was an intriguing finding, given the high metabolic activity of the growth zone, and we wished to learn more about the phenomenon, in particular on the relationship of assimilate import and use, and fructan metabolism, and also on a putative role of fructans as an (vacuolar) osmoticum. The latter required a separation of fructans according to molecular mass, i.e. degree of polymerization (DP). Based on previous work by Udo Thome (Thome and Kühbauch 1985), Bill Spollen and I optimized a silica gel thin-layer chromatography (TLC) method that enabled a clear-cut separation of mono-, di-, and oligosaccharides up to a DP of ~10 hexose units (Vassey et al. 1985; Spollen and Nelson 1986; Schnyder and Nelson 1987; Schnyder et al. 1993). At the time, this was a real achievement, despite being low-tech (Jerry named it the ‘Midwestern blot’). In first experiments with plants grown in continuous light, the combined determination of the spatial distribution of growth rates and velocities of displacement, and of water, dry matter, and carbohydrate contents in and beyond the leaf growth zone then provided unique insight in carbohydrate metabolism associated with the growth process in the leaf (Schnyder and Nelson 1987): rates of sucrose import and net synthesis of fructan were closely associated with local growth rates, while net rates of sucrose deposition were highest in the zone of cell division – where fructan synthesis is initiated – and those of monosaccharides were highest at the terminal end of the growth zone, where cell elongation terminates. At the location of most active growth ~40% of the imported sucrose was used for fructan synthesis! Subsequent work analysed how growth in day/night-cycles and at low irradiance modified the above patterns in terms of the relationships between local growth rates (and growth-related water deposition), assimilate import and fructan net synthesis and degradation, with the latter associated with low local rates of assimilate import at the terminal end of the leaf growth zone and differentiation zone (Schnyder and Nelson 1988, 1989; Schnyder et al. 1988). Although the stay in Missouri lasted only about 15 months, it was consequential in many ways. First, it continued through work on manuscripts, enriched by regular visits of Jerry in Bonn, to which my wife and children were also looking forward. Then, it led to work on leaf growth with perennial ryegrass – the most important forage grass in temperate-humid climate zones – which stayed a research topic until the end of my active career (see also below).1 The work also evolved into an informal tri-lateral cooperation with Jerry and the forage ecophysiology group at 1

Not everyone acknowledged the importance of research on grass growth, however. A short while after we had returned to Bonn from Columbia, at some social gathering with many people I did not know, I ran into someone who liked to know what I was researching. When I responded: ‘I try to understand how the grass grows’, he seemed to be slightly offended, stating he had asked a serious question. Later, Monika Kavanová told me, that travelling through the Argentinian Pampa one

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INRAE Lusignan. The INRAE team was led by Gilles Lemaire (whom I had first met when I was a trainee there), and included Francois Gastal (who had also done a postdoc with Jerry; Gastal and Nelson 1994), Jean-Louis Durand (who had spent a sabbatical with me in Bonn; Durand et al. 1995) and PhD students, e.g. Rudi Schäufele (Schäufele and Schnyder 2000, 2001) and Ina Rademacher (Schnyder et al. 1990; Rademacher and Nelson 2001). Rudi did a postdoc in Lusignan and then became a long-term research associate and great support in my group at TUM until my retirement. We had occasional workshops, including one with Wendy Silk in Lusignan. Later, the work on leaf growth also inspired Tulio Arredondo’s work on interspecific relationships between leaf growth zones traits and habitat characteristics (Arredondo and Schnyder 2003), the PhD of Agustín Grimoldi about arbuscular mycorrhizal fungi (AMF)-mediated effects of phosphorus nutrition status on leaf morphology, allocation and carbon costs of AMF colonization (Grimoldi et al. 2005, 2006), and the PhD studies of Monika Kavanová of the effects of nitrogen and phosphorus deficiency (including the role of AMF in alleviating that deficiency) on the parameters of cell division and elongation of epidermal cells in leaves of perennial ryegrass (Kavanová et al. 2006a, b, 2008). These studies demonstrated that phosphorus and nitrogen limitation had no effect on the number of mitotic cells in the leaf meristem, or the number of division cycles of the initial cell’s progeny, but slowed the division and growth rates of individual mitotic cells, causing a longer cell cycle duration. Basically, being applicable to both elements independently, this observation identified a fundamental mechanistic element underlying Liebig’s law of the minimum. Understanding of the leaf growth process was also key for understanding the mechanism of re-foliation after cutting of perennial ryegrass and Paspalum dilatatum (C4) (de Visser et al. 1997; Schnyder and de Visser 1999, Lattanzi et al. 2004, see Sect. 4.2). Most recently, work at the leaf growth zone level was also important for characterizing a mechanism of diel cycling between daytime hydraulic and night-time stored growth controls of LER, which buffered completely the effects of atmospheric CO2 concentration and daytime vapour pressure deficit (VPD) on leaf elongation of perennial ryegrass, as shown by Juan C. Baca Cabrera, one of my last PhD students (Baca Cabrera et al. 2020).

4 Experimental Tracer Studies 4.1

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CO2/12CO2 Labelling and Gas Exchange Facilities

In addressing the role of pre-anthesis non-structural vegetative biomass as a source of assimilate for grain filling, I thought it would be most convincing if the analysis was based on quantitative ‘dynamic’ (Ratcliffe and Shachar-Hill 2006) or

could easily find one-self listening to a radio show on grass growth. Different places, different people, different interests!

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‘steady-state’ (Geiger 1980) isotopic labelling of all post-anthesis photosynthetic products, and subsequent determination of the contribution of pre-anthesis reserves as the proportion of non-labelled assimilate in the grains at maturity (Schnyder 1990, 1992, 1993; Gebbing et al. 1998, 1999; Gebbing and Schnyder 1999). To be of any relevance in an agronomic context, these experiments would need to be performed at stand-scale. It seemed impractical (also because of safety regulations) to execute such labelling experiments with a radioactive isotope (14C). Instead, Felix Mächler suggested the 13CO2/12CO2 labelling technique recently published by Eliane Déléens and coworkers (Déléens et al. 1983, 1984), for which there existed no safety concerns as it used stable isotopes at near-natural abundance levels. In late 1984, Udo Thome and I visited Eliane at the then Laboratoire du Phytotron at Gif-sur-Yvette, near Paris/France. Her technique was a whole new world for me in many respects, including the principles of tracer generation and application, isotopic measurements and data evaluation (Schnyder 1990). For labelling, Eliane used an inexpensive, naturally 13C-depleted CO2 source (‘industrial CO2’), with a δ13C2 of CO2 (δ13CCO2) of approx. –25‰ (Déléens et al. 1984). Industrial CO2 originates from industrial processes, e.g. the combustion of fossil fuel or the use of natural gas for ammonia production. The industrial CO2 was added to CO2-free air, generated by passing air through a molecular sieve in a dryer, which was then fed to a growth cabinet at a high flow rate. That is, labelling occurred in a highly ventilated open system, conditions which maximize carbon isotope discrimination (Δ13C)3 in photosynthesis (Farquhar et al. 1989). Thus, Δ13C occurred in a similar way as in natural conditions in the field, as the discriminated isotope (13C) did not accumulate in the surrounding air, if the air was replaced rapidly. In C3 plants, Δ13C is in the order of 20‰, but can vary substantially among plant species and in response to environmental conditions (Farquhar et al. 1989; Körner et al. 1991; Schnyder and Auerswald 2008; Schäufele et al. 2011). By comparison, the maximum range of δ13C of the CO2 (δ13CCO2) sources that we have used in later experiments was between -2‰ and -48‰ (currently ambient CO2 has a δ13C of approx. –10‰), meaning that the maximum labelling signal obtainable when transferring plants from one CO2 source to the other was ~46‰, slightly greater than two-times the Δ13C. Clearly, Δ13C had to be accounted for when evaluating the labelling signal (Schnyder 1990, 1992, Schnyder et al. 2003). Despite the seeming complication, the additional requirement to assess and consider Δ13C during labelling experiments represented an important bonus, as Δ13C is a valuable physiological signal, reporting the ratio of intercellular to ambient CO2 concentration (ci/ca), which is also a proxy for intrinsic water-use efficiency (iWUE) of plants (Farquhar et al. 1982; Farquhar and Richards 1984; see also Ma et al. 2021, and Sect. 5.2 below). Over time, we developed different strategies to quantify and distinguish between labelling and Δ13C effects on the δ13C of plant

δ C = Rsample/Rstandard – 1, and Rsample the 13C/12C abundance ratio in the sample and Rstandard in the international standard, Vienna Pee Dee Belemnite. 3 13 Δ C = (δ13CCO2 – δ13CP)/(1 – δ13CP), with δ13CP the δ13C of the photosynthetic product. 2 13

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material (see Schnyder 1990, 1992, de Visser et al. 1997; Schnyder et al. 2003, 2017). The need to consider (and eventually understand) Δ13C benefitted us greatly later, when we became interested in the effects of environmental drivers, such as global and climate change on C3 vs C4 distribution in grassland and intrinsic water-use efficiency (iWUE) of C3 vegetation (see Sect. 5), or to understand the role of co-occurring fungal symbionts (Epichloë endophytes and AMF) for iWUE, stomatal conductance and nitrogen and phosphorus nutrition status of its host grass (Hordeum comosum, C3) across aridity gradients in the Patagonia steppe (Casas et al. 2022), or for quantification of the effect of altered expression levels of abscisic acid receptors in Arabidopsis lines on their iWUE (Yang et al. 2016b). At TUM, the 13CO2/12CO2 labelling system was set up with four plant growth chambers and was complemented with a CO2 analyzer and an online 13C/12C stable isotope ratio mass spectrometer (Schnyder et al. 2003). Each chamber could be operated independently as a 13CO2/12CO2 gas exchange system. This facility permitted 13CO2/12CO2 measurements at the inlet and outlet of each growth chamber at ~20 min intervals, and therefore enabled quasi-continuous monitoring of Δ13C in conditions with a constant δ13CCO2 as well as following a change of δ13CCO2 in ‘steady state’ (or ‘dynamic’, see Schnyder et al. 2012) labelling experiments. A similar system was later deployed to the field (Schnyder et al. 2004) – a paddock of the Grünschwaige pasture experiment (Fig. 3) – and included open-top chambers as labelling cuvettes and 13CO2/12CO2 gas exchange equipment housed in a nearby van (Fig. 1d) (Gamnitzer et al. 2009, 2011). This facility also permitted quasi-continuous online 13CO2/12CO2 measurements, which was also a useful feature for testing and optimizing the operation. Note that the term ‘open-top chamber’ is really a misnomer in most conditions when they are installed in the field, as they are also typically open at the bottom, a factor to be considered properly in tracer studies (Gamnitzer et al. 2009, 2011)! Our first steps with 13CO2/12CO2 labelling systems benefited hugely from the emergence of online 13C/12C stable isotope ratio mass spectrometry (IRMS) in the mid-80s (Barrie et al. 1984; Preston and Owens 1985), as this enabled a greatly enhanced performance (and ease!) of stable isotope analysis of plant material. Ute Labusch, the first PhD student whom I co-supervised with Walter Kühbauch, was a great help, as she travelled to visit competitors for online IRMS systems, testing their precision and ease of operation. I think we were one of the first groups that obtained such a system from Europa Scientific, which was a trail blazer in this field at the time (and also had a great telephone support; one could talk directly with the engineers!), a system which was initially operated by Ute and then Thomas Gebbing, also a PhD student (see Sect. 4.2) who would later become a huge help in setting up and operating the isotope facilities at TUM. The Major Research Instrumentation Programme of the DFG was a generous support repeatedly for setting up new isotope facilities. Later, other PhD students, postdocs, and technicians developed invaluable expertise in running the isotope facility, particularly Rudi Schäufele (who followed Thomas Gebbing as the manager of our isotope facility, when Thomas transferred back to the University of Bonn and later became manager of the isotope lab at the

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Fig. 3 The pasture experiment at Grünschwaige research farm, 2000–2012, set up beautifully by Rita Kammerl with assistance of Hans Vogl (for details, see Schnyder and Auerswald 2008). (a) A herd of Limousin cattle suckler cows with their calves and one bull grazing one of the paddocks of the pasture experiment (Foto: Laszlo Maczky, fotoart-maczky.eu). (b) Pasture paddocks were situated on soils with different plant available water (PAW) capacities. (c) δ13C of cattle hair grown during the grazing seasons of 2000–2004 as related to the season-mean PAW of peat soils (closed symbols) and mineral soils (open symbols)

Macaulay Land Use Research Institute, MLURI/Aberdeen), but also Markus Lötscher, Wolfgang Feneis, Ulrike ‘Ulli’ Ostler (née Gamnitzer), Richard Wenzel, and Xiaoying Gong. A somewhat scaled-down, but very mobile, field-ready 13CO2/12CO2 labeling system was also constructed for experiments in Campos grassland in Uruguay and Pampa grassland in Argentina by Fernando Lattanzi and Wolfgang Feneis (Lattanzi et al. 2012b). Markus Lötscher and Wolfgang Feneis built a system that enabled separate measurements of whole plant root and shoot respiration (Lötscher et al. 2004), which was later also used by Katja Klumpp and Fernando Lattanzi to study 13 C discrimination in root and shoot respiration (Klumpp et al. 2005; Schnyder and Lattanzi 2005). Xiaoying Gong, Rudi Schäufele and Wolfgang Feneis optimized a clamp-on leaf cuvette system to minimize artifacts during measurements of 13CO2/12CO2 exchange fluxes (Gong et al. 2015, 2017). Quite certainly, in the field of methodology (see also Sect. 4.3), the most important contributions of my group have been developments of new or improvements of existing 13CO2/12CO2

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gas exchange and labeling techniques from leaf-scale in controlled environments to ecosystem-scale in the field.

4.2

The Role of Stores in Supplying Substrate for Vegetative and Reproductive Growth, and Respiration

Probably the most important contribution of my research group to the field of plant physiology in general was our work on understanding the functioning of assimilate stores (Schnyder 1993), and particularly their importance in supplying substrate to vegetative and reproductive growth and respiration at organ-, plant-, and stand-scale in controlled environments (e.g. de Visser et al. 1997; Schnyder and de Visser 1999; Gebbing et al. 1998, 1999, Gebbing and Schnyder 1999; Lötscher et al. 2004; Lattanzi et al. 2005, 2012a, b; Lehmeier et al. 2005, 2008, 2010a, b; Gong et al. 2017) or in a temperate pasture ecosystem (Gamnitzer et al. 2009, 2011; Ostler et al. 2016). In these endeavours, we were standing on the shoulders of many predecessors. Individuals and groups which come to mind immediately include D. Geiger and coworkers (e.g. Geiger 1980; Fondy and Geiger 1982), J. F. Farrar and coworkers who also worked with C3 grasses (e.g. Farrar 1980) and A. J. Gordon, G. J. A. Ryle and coworkers (e.g. Gordon et al. 1980), who worked with barley, among other species. This list is by no means complete (for a more comprehensive review of the state of the art at the time, see Schnyder 1993). In general, I would say, that much more was known about the physiology of diurnal carbohydrate stores (starch in chloroplasts, and sucrose in vacuoles), and their integration in the synthesis or supply of cytoplasmic sucrose for export, than about long-term non-structural carbohydrate stores. In grasses, the latter include in particular fructans (Wagner et al. 1983; Nelson and Spollen 1987; Pollock and Cairns 1991), which are mainly stored in the internodes and leaf sheaths. To my knowledge, the first account of a characterization of fructan was given by Rose (1804) in a note About a peculiar substance of plant origin (Kühbauch and Schnyder 1989). Until the late 1970s, a relatively small number of individuals and groups had actively worked on fructan (Nelson and Smith 1986). The first occasion at which a larger number of fructan scientists met was at the Fifth Annual Plant Biochemistry and Physiology Symposium at the University of Missouri-Columbia in 1986, in the frame of a session on Fructan: Function and Metabolism organized by Jerry Nelson. Thereafter, with support from the DFG and help and advice from Jerry, Walter Kühbauch and myself organized the First International Symposium on Fructan in the summer of 1988, unwittingly starting a series. Participants were invited to submit papers ahead of the symposium, to be considered for publication in a special issue of the Journal of Plant Physiology. Invited speakers were asked to arrive ahead of the symposium, to help review the submitted papers, sitting outside the conference venue, the Wissenschaftszentrum of the DFG in Bonn, in the cafeteria, on a sunny day. Participants received their referee reports at the

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conference. The special issue contained 23 papers (including 3 short communications), was published within 9 months of the symposium, and until April 2023 was cited more than 1,600 times. An important role of assimilate ‘reserves’ or ‘stores’ (that is biomass stored in mobilizable form in the vegetative plant parts) for grain filling had been assumed at least since the observations of Pierre (1869), who suggested that the dry weight increase of the ear of wheat during the last 2–3 weeks of grain development resulted from the redistribution to the grain of dry matter stored in the leaves and stem parts. Pierre (1869) drew his conclusion from the weight loss of the vegetative plant parts. More direct evidence of an actual delayed transfer to the grains of assimilates temporarily stored and mobilized in vegetative plant parts was obtained by observations of the redistribution of 14C pulse-labelled assimilate (e.g. Austin et al. 1977). Indeed, the potential contribution of reserves to grain growth of wheat (and other cereals) is quite enormous. Thus, one should assume that most of the carbohydrates transferred to the grains passes at least once through a diurnal or longer-term storage pool in vegetative plant parts before reaching the grains (Schnyder 1993). Net mobilization of pre-anthesis vegetative biomass alone can occur at 3 t ha-1, as observed with crops of barley by Gallagher et al. (1975). In that, a significant fraction is associated with the redistribution of amino acids to the grains derived from breakdown of proteins in the vegetative plant parts, that is mainly the senescing leaves. The efficiency of mobilized pre-anthesis protein and carbohydrate conversion into grain protein and carbohydrates was studied by Thomas Gebbing in steadystate labelling experiments with two cultivars of wheat grown at two rates of nitrogen fertilizer addition in 2 years (Gebbing and Schnyder 1999). Thomas had optimized a protocol for extraction and purification of grain protein, which then permitted a comparison of the incorporation of pre-anthesis mobilized carbon into grain protein and – by difference – the carbohydrate fraction of grains. The data supported a mean efficiency of mobilized pre-anthesis protein-carbon use in the synthesis of grain protein-carbon of 56%. Conversely, the efficiency of carbohydrate-carbon use in grain filling (estimated as the mass of pre-anthesis fixed carbon deposited in grain carbohydrates per gram of pre-anthesis carbon mobilized from carbohydrates in vegetative plant parts) was 72%. Interestingly, however, these efficiencies were not constant among the treatments. The efficiency for proteins decreased with increasing residence time of nitrogen in vegetative biomass, probably due to the fact that protein turnover in vegetative biomass is associated with incorporation of currently fixed carbon. Conversely, the efficiency for the carbohydrates increased with the fractional contribution of water-soluble carbohydrates (mainly fructan) mobilization in total pre-anthesis carbohydrate mobilization. These works (see also Gebbing et al. 1998, 1999) supported very strongly the notion that pre-anthesis reserves (and particularly fructans) are used very efficiently in grain filling of wheat. Evidently, this mechanism must be an important factor for explaining the high resilience of grain filling in wheat (e.g. Schnyder and Baum 1992; Schnyder and Weiss 1993). A key role of stores has also long been emphasized for the ability of grasses (and other grassland vegetation) to regrow following severe defoliation. Largely, this role

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was inferred from the observation that stores of fructan (or total non-structural carbohydrates) in the shoot parts remaining after defoliation (the ‘stubble’, which is composed mainly of leaf sheaths) are rapidly depleted following a defoliation event. However, the actual use of reserve-derived imported substrates in the leaf growth zones – the tissue that actually generates the re-foliation – had never been assessed. First work on this topic emerged from a wonderful discussion with Ries de Visser, at the former Centre for Agrobiological Research (CABO-DLO) in Wageningen/Netherlands, following a talk on steady-state 13CO2/12CO2 labelling. I think it was Ries who suggested we should use this technique conjointly with 15N labelling and investigations in the leaf (and root) growth zones of grasses (and other functionally distinct tissues) to assess the actual use of mobilized non-structural carbohydrate- and protein-reserves in the re-foliation process. And we did it (de Visser et al. 1997; Schnyder and de Visser 1999). This investigation provided surprises and new insight and understanding. In a steady-state labelling experiment with perennial ryegrass, reserve-derived carbohydrate-C was a dominant source of assimilates for the growth zone and re-growing tiller tissue only during the first day after defoliation, while nitrogen reserves continued to be the dominant nitrogen source until about 3 days after defoliation. This was true although leaf growth continued rapidly following defoliation: the leaf growth zones, which had a length of 25–30 mm, produced a ~30 mm-long new leaf segment of photosynthetically active tissue on the first day after defoliation, essentially reproducing their own length. In addition, we observed new mechanisms associated with the re-foliation process: axial growth of leaves was transiently enhanced relative to growth in crosssectional area, while water deposition into expanding cells was increased relative to assimilate import into the growth zone. Simultaneously, most of the carbohydrates stored within the growth zone were mobilized within the first day following defoliation. Later, Fernando Lattanzi observed that over the first 2 days after defoliation, leaf area production per unit carbon import into the leaf growth zone was greatly (but variably) increased in a C3 and a C4 grass growing in either a dominant or subordinate position within a mixed stand (Lattanzi et al. 2004). The magnitude of this effect was dependent on the concentration of water-soluble carbohydrates in the leaf growth zone at defoliation. Thus, focusing on the site of leaf growth opened up a whole new perspective on the mechanisms which facilitate the recovery of grasses from severe defoliation (Schnyder et al. 2000). Fernando Lattanzi introduced compartmental modelling (Jacquez 1996; Moorby and Jarman 1975; Prosser and Farrar 1981) of tracer kinetics to our tool kit for evaluating tracer data, when he analysed 13C and 15N tracer import into leaf growth zones of grasses during undisturbed growth (Lattanzi et al. 2005). This was a significant advance, as it enabled inferences on the properties of stores (size and turnover), their importance in supplying substrate to growth processes or respiration, and the residence time of carbon in the system. Later, Ulli Ostler (who has a background in physics) and Christoph Lehmeier contributed much to further development of compartmental modelling in my group. In particular, I remember vividly a discussion with Ulli and Fernando about a conceptual model of central carbohydrate metabolism of a fructan-storing grass leaf. Our question really was, if Ulli could

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compose a compartmental model that would tell us if and in how far fructan metabolism and sucrose hydrolysis/re-synthesis contribute to regeneration/recycling of sucrose in photosynthetically active leaves of perennial ryegrass. Ulli thought she could give it a try, which implied writing a set of differential equations that describe the movement of tracer between the pools composing the system and into and out of the system, and implementation of these equations in a commercial software. Ulli solved the task in no time. The subsequent modelling was based on dynamic labelling data, with leaves sampled at intervals between 1 h from the beginning of labelling up to 16 days, in an experiment with perennial ryegrass grown with either a high or low rate of nitrogen fertilizer addition. The study had been performed by Melanie Wild and Christoph Lehmeier (both PhD students) together with the plant ecophysiology group of the University of Caen/France, led by Marie-Pascale Prud’homme, where also most of the carbohydrate analysis had been performed. The modelling led to a joint-first author publication of Fernando, Ulli, and Melanie (Lattanzi et al. 2012a) and was published in a Special Issue in Journal of Experimental Botany that originated from a Symposium on Pathways and fluxes: analyzing the plant metabolic network at the 2011 Meeting of the Society for Experimental Biology. Over time, we used compartmental models of varying complexity, adapted to specific research questions from leaf- to ecosystem-scale in controlled and field environments, to study the functioning and role of assimilate stores in grassland vegetation (Schnyder et al. 2012; Lattanzi et al. 2012a; Ostler et al. 2016, Hirl et al. 2021). For instance, such works revealed that (1) three kinetically-distinct stores supplied respiration of shoots and roots (Lehmeier et al. 2008), (2) stores supplying root respiration resided in the shoot (Lehmeier et al. 2008), and (3) supplied more than 50% of the respiratory substrate of perennial ryegrass across different environmental conditions (Lehmeier et al. 2010a, b). In the same sense, Lattanzi et al. (2005) found that stores supplied similar to or more than 50% of the carbon and nitrogen to the leaf growth zones of a C3 and a C4 grass during undisturbed growth. In that, carbohydrate stores appeared to buffer mainly short-term or diurnal fluctuations of current photosynthate supply, while (organic) nitrogen pools were turned over more slowly, ‘buffering’ nitrogen supply to leaf growth zones at the scale of multiple days (Lattanzi et al. 2005). Nitrogen-limitation stress had no marked effect on the relative contribution of nitrogen stores to leaf growth, although it affected their turnover and size (Lehmeier et al. 2013). According to the analysis of Fang Yang, the large contribution of nitrogen stores to amino acid supply of the leaf growth zone must have been connected with amino acid exports from mature and senescing leaves during protein turnover and incorporation of de novo synthesized amino acids in photosynthetically active leaves (Yang et al. 2020). Given their importance in supplying growth and respiration following disturbance, in response to stress, and constitutively also in benign environmental conditions, I believe that research on long- and short-term carbohydrate stores and protein stores should be much more active today. Surely, a main reason for why stores are often overlooked in experiments of sink physiology is the wide-spread use of shortterm (or pulse) labelling techniques, which are much easier to accomplish, but

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(over)emphasize the importance of current assimilates in the substrates feeding growth and respiration (Schnyder et al. 2012).

4.3

Disentangling CO2 Fluxes: Photosynthesis Versus Respiration in Light, and Autotrophic Versus Heterotrophic Ecosystem Respiration

Virtually all of the CO2 fixed by plants in photosynthesis is eventually returned back to the atmosphere via respiration, either by photorespiration, mitochondrial plant respiration (autotrophic respiration) in light or in the dark, or by heterotrophic respiration, which is mostly soil respiration. Evidently, understanding the carbon economy of ecosystems and the residence time of carbon in the biosphere requires an ability to assess these fluxes. One key problem in this endeavour lies in the fact that several functionally distinct CO2 fluxes (‘flux components’; e.g. autotrophic and heterotrophic respiration in ecosystems, or photosynthesis and mitochondrial respiration) occur conjointly, making it impossible to measure the individual CO2 flux by classical CO2 exchange techniques alone. Quantitative tracer techniques are a powerful tool for disentangling CO2 flux components (Schnyder et al. 2003, 2012), as already mentioned for the case of photorespiration measurements by short-term 14C labelling in Sect. 2. The latter however, required destruction of the plant samples. In contrast, the 13CO2/12CO2 exchange-based techniques that we established subsequently did not require destructive methods to disentangle flux components. For separation of stand-scale photosynthesis and dark respiration in light, we used the growth chamber-based 13CO2/12CO2 gas exchange and labelling technique shown in Fig. 1c. In that, we followed 13CO2/12CO2 gas exchange following a switch of the δ13CCO2 in chamber air. Figure 4 shows the results from such a manipulation: immediately following the change of δ13CCO2 the δ13C of the CO2 exchanged by the canopy in light changed by about 1.2-times(!) the δ-difference between the two CO2 sources. This perhaps counterintuitive result is explained by the fact that opposing CO2 fluxes (photosynthesis and dark respiration in light) generate a δ13C of the net flux (δ13CN, stand-scale net photosynthesis in the case of Fig. 4) which is outside the δ-range of its component fluxes, photosynthesis (δ13CP) and dark respiration in light (δ13CR), irrespectively of the direction of the switch of δ13CCO2. The magnitude of the labelling-induced deviation is a function of the degree of ‘contamination’ of the photosynthetic flux by concurrent dark respiration. In particular, even in natural (non-labelled) conditions, if δ13CP ≠ δ13CR, and the rates of photosynthesis and dark respiration in light are similar in magnitude, the resultant δ13CN would deviate extremely from the range delimited by δ13CP and δ13CR. Given the fact that deviations between δ13CP and δ13CR are quite common – for instance, due to time-lags in substrate transfer at ecosystem scale (Wingate et al.

H. Schnyder

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Time after start of labeling (h) Fig. 4 Carbon isotope composition (δ13C) of CO2 exchanged by L. perenne stands grown in the presence of a CO2 source with δ13CCO2 of -2.6‰ and then shifted to -46.8‰ (closed symbols), or grown in the presence of a CO2 source with δ13CCO2 –46.8‰ and then shifted to -2.5‰ (open symbols) at time 0. Means ± SD of hourly values of two growth chambers. The white and black horizontal bars indicate the light and dark periods, respectively. Note that the δ13C of the CO2 exchanged in the light period and that respired in the following dark period diverge following the switch of δ13CCO2 and gradually approach each other as the substrate feeding respiration is replaced by new (labelled) photosynthetic products. The time taken for the ‘equilibration’ is a function of the participation of stores in supplying substrate for respiration. For further explanation, see text and Schnyder et al. (2003)

2010) – one should actually expect to find extremely varying δ13CN in natural conditions (see also discussion in Zobitz et al. 2006). Xiaoying Gong used the above labelling principle (explained in Schnyder et al. 2003) also to estimate leaf-scale dark (i.e. mitochondrial’) respiration in light in different C3 and C4 species (Gong et al. 2015, 2018). In addition, Xiaoying used the technique to make measurement-based corrections to ‘conventional’ carbon-use efficiency (CUE) estimates (Gong et al. 2017), which have extrapolated dark respiration in light by extrapolation of dark respiration data collected in the dark. A different strategy was used by Ulli (Gamnitzer et al. 2009) to partition autotrophic and heterotrophic respiration of a temperate pasture ecosystem based on respired carbon age. Ulli performed 16 days-long dynamic 13CO2/12CO2 labelling experiments with open-top chambers and observed the increase of the fraction of newly fixed carbon ( fnew), i.e. labelled carbon, in ecosystem respired CO2 in the dark. fnew reached an asymptotic value of ~48% after approx. 10 days of continuous labelling. This asymptotic value was interpreted as the autotrophic component of ecosystem respiration, and the remainder as soil (minus root and rhizosphere) respiration. This conclusion was corroborated by the fact that the metabolic pool feeding autotrophic respiration was saturated with label after ~10 days, while the substrate for heterotrophic respiration, dead structural plant biomass passing into the

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soil carbon pool as litter, stayed unlabelled for much longer due to the life span (Schleip et al. 2013; see also Hirl et al. 2021, Sect. 6) of the labelled tissues. In other words, structural carbon entering the soil carbon pool had not incorporated any label within the 16 days-long duration of the labelling experiments (Ostler et al. 2016).

5 Stable Isotope Ecology and Biogeochemistry When I took the offer for the TUM Chair of Grassland Science in 1994, teaching activities in grassland ecology and agronomy for BSc and MSc students of agriculture suddenly became a very important part of my work. In that I liked to start the introductory lecture with some explanations on the evolution/expansion of grassland in the last ~15–30 MYA in different regions and the climatic conditions that are thought to have shaped it (Strömberg 2011) (Fig. 5). I also taught crop physiology initially, an activity which was later taken over by Rudi Schäufele. I liked teaching, although over time I reduced and eventually eliminated lectures completely in MSc classes, as I preferred more interactive formats. The teaching activity that I liked most (as students did also) was ‘an applied phytosociology of grassland’. Attendance was limited to 12 participants, and often

Fig. 5 Petrified tree in the Patagonia steppe at Estancia Pilcañeu (Rio Negro Province, northern Patagonia), with year rings clearly visible in the inset. Forests thrived in this region until approx. 66 MYA, the end of the Upper Cretaceous. Steppe vegetation replaced forests when the region became drier due to a rain shadow effect which resulted from the Andes uplift (Foto: Hans Schnyder)

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also included students from other MSc courses, especially landscape ecology and planning. Students were assigned a heavy dose of home reading of the subject, and classes took place outdoors virtually completely (even in rain). Students learned to identify all plant species in grassland communities, make relevés, discuss them in a phytosociological, environmental, ecological, agronomical, and animal-nutrition context, and to make recommendations for rational management, across almost the complete range of grassland vegetation types in southern Bavaria, from wet to dry, oligotrophic to eutrophic, grazed or cut, extensively to intensively managed, and strongly disturbed grassland sites. In this activity I received fine support by technicians with botanical expertise (Angela Ernst-Schwärzli, Anja Schmidt, Hans Vogl). It was important, a lot of fun, and a great reward to see students make progress. At the same time, my research interests and the groups’ experimental activities expanded gradually into a greater range of themes. This development was motivated by new opportunities and necessities (such as teaching) and also met an old interest in the ecology of managed grassland. Shortly after arriving at TUM, I was invited to join the Forschungsverbund Agrarökosysteme München (FAM, funded by the German Ministry of Education and Research) by its director Jörg Pfadenhauer. FAM was a very large and long-running (1990–2003) transdisciplinary research project dedicated to the development of environmentally friendly, site adapted and sustainable farming systems, and integrated research groups across a wide range of disciplines, including hydrology, micrometeorology, soil science, faunal and plant community ecology, plant nutrition, agronomy, grassland science, agricultural engineering, economics and sociology, a truly fascinating project. Here, I first met Karl Auerswald, one of the leaders of FAM, who joined my group in 2001. With his background in soil science, hydrology, agroecology, and geostatistics, Karl came with much complementary expertise and had a big influence on subsequent developments of stable isotope ecology at the Chair. Also, shortly after my arrival at TUM, I was invited to join the preparation of a collaborative research centre (a large multidisciplinary research programme by the DFG), which would address the regulatory mechanisms of resource allocation and partitioning between and within agricultural and forest plants, and was led superbly by Rainer Matyssek (TUM Chair of Plant Ecophysiology). The project (SFB 607) won long-term funding (1998–2010), supported several of my PhD students (Katja Klumpp, Agustin Grimoldi, Ulli Ostler, Melanie Wild, Christoph Lehmeier) and contributed much to our understanding of carbon allocation, and particularly the role of carbohydrate and nitrogen stores in supplying growth and respiration under nutrient-limitation stress, disturbance, and competition, including colonization with arbuscular mycorrhizal fungi. SFB 607 was the most internationally visible research activity of the TUM School of Life Sciences at the time (for a synthesis, see Matyssek et al. 2012). Additionally, a few years later, our group became involved in NETCARB (Network for Ecophysiology closing Terrestrial Carbon Budget), an EU funded Marie Curie research and training network (2000–2004), led by Jaleh Ghashghaie (Paris-Sud University), which supported postdocs and assembled expert colleagues in stable isotope applications in the fields of plant physiology and biogeochemistry (Franz Badeck, Enrico Brugnoli, Manuela Chaves, Howard

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Fig. 6 Participants and teachers of the first Stable Isotope Course of TUM at Grünschwaige research farm (2002). First row (from left to right): Gustavo Luedemann, Agustin Grimoldi, Dajana ‘Dani’ Wieland (now Maranhao), Monika Kavanova, Rudi Schäufele. Second: Nina Koch, Ali Khalvati, Ilja Reiter, Norka Fuentes, Armin Vikari, Hans Schnyder. Third and fourth: Ute Raeder, Frank Fleischmann, J. Barbro Winkler, Iris Lange, Mathias Herbst, Michael Schwertl, Jürgen Geist, Katja Klumpp, Karl Auerswald, Arnoud Boom. Missing on foto: Fernando Lattanzi

Griffiths, Jean-Marc Guehl, Cristina Máguas, Ries de Visser, and Dan Yakir) (Tcherkez et al. 2010). These joint network and research activities at the beginning of my career at TUM also had a very important influence on research at my Chair. In the fall of 2002, the Chair of Grassland Science held its first Stable Isotope Course: An introduction to uses in ecology and plant physiology (Fig. 6), with Arnoud Boom (our NETCARB postdoc), Rudi Schäufele, Fernando Lattanzi, Karl Auerswald, and myself as teachers. The course format included lectures on methods, instrumentation, theory, and applications in the mornings and practical projects – with not more than three students per project – in the afternoons, and took place at the Grünschwaige grassland research farm. Projects involved sample collection, preparation, analysis, and interpretation, and students’ talks about their projects on the final day. All in 1 week! It was intense, but also invigorating, for everybody involved. One of the projects even developed into a publication (Geist et al. 2005), as did others later on. By now, the group was in full swing. The next year we teamed up with the research groups of Hana Šantrůčková and Jiří Šantrůček at the University of Budweis/Czechia, the course was publicized for attendance internationally, run every year as the Freising-Budweis isotope course,

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except for a pause (2020 and 2021) during the COVID-19-pandemic, and even included a stint in Balcarce/Argentina in 2008.

5.1

Animals as Recorders and Integrators of Environmental and Dietary Isotopic (13C, 15N, 18O) Signals

Our research activities on stable isotopes in animal tissues began in 2001 with the diploma thesis of Michael Schwertl (Carbon and nitrogen isotope signatures along cattle hair – ecological fingerprints?). This work used tail switch hair obtained from cattle grazing pasture at the recently established pasture experiment at Grünschwaige (Fig. 3). It established a protocol for the determination of hair growth rate and timeposition assignment of isotopic signals incorporation into 5 or 10 mm-long sections of hair by using wiggle-matching statistics on hair sampled from the same individual at two moments in time (Schwertl et al. 2003). Although isotopic signal incorporation in hair is buffered somewhat by the metabolic pool of the animal, position-time inference of isotopic signals in hair is a powerful tool for reconstructions of dietary histories and is being used widely in forensics, medicine, and ecology, not least due to the methodology developed by Schwertl et al. (2003). Below, I illustrate the wiggle-matching method (Fig. 7b) using unpublished data from one yak cow sampled in summer of 2012 and 2013 in the Tso Kar lake region (Ladakh/India). Intra-annual variation of δ15N and δ13C signals extracted from tail switch hair of two individuals of yak from each of two herds is shown in Fig. 7c. Theses herds were owned by Changpa families which used a traditional nomadic system with approx. 8–10 camps in each year, at altitudes ranging between 4,500 and about 5,200 m a.s.l., and winter grazing on the saline, sandy marshes around the lake of Tso Kar between November–December and along Tasabuk lake, which is a fresh water lake, between January–March (personal communication, Rikako Kimura, Tokyo Agricultural University). As evidenced by Fig. 7c, the signal patterns show strong similarity between the two individuals from one herd, but strong seasondependent dissimilarity between the herds, clear proof of the fact that herds had used (isotopically) different nomadic tracks. I was initially surprised to find these two pairs of patterns, as people asked for sampling hair were instructed to collect samples from four individuals (cows of a given age group) in one herd. The young Changpa woman sampling these hairs had decided on her own to split the sampling between two herds, one her own, and the other a neighbours’ herd. Only when I was confused by the data and got back to the colleague working at the site (Rikako Kimura), I did learn the fact. Notably, isotopic signals of each herd (Fig. 7c) were similar in July of both years, a feature of a recurrent annual cycle, and also between herds when the herds were sampled at the same site in different years, evidence of relative signal ‘stability’ at site level. While we have no camp site-level information of vegetation composition or soil, hydrology and bioclimatology, it is known that δ15N increases with pH,

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Fig. 7 Dietary isotopic history of transhumant Yak in Tibet reconstructed from segmental analysis of tail switch hair. (a) Yak cow with its calf near Yushu, Qinghai/China (Foto: Nobumi Hasegawa, University of Miyazaki/Japan); (b) Illustration of the isotopic wiggle-matching procedure for estimation of hair growth rate and position-time assignment of isotopic signals from samples collected at different times. Arrows mark the root of the hair, which is the youngest hair section, formed just before sampling. Hair growth rate is obtained by dividing the length of the non-matching portion of the hair (the region between the two arrows) by the temporal sampling interval (for details, see Schwertl et al. 2003); (c) Interannual variation (July 2011 to July 2012) of nitrogen isotope composition (δ15N) (left-hand panels) and carbon isotope composition (δ13C) (right-hand panels) of tail switch hair segments collected from an adult female yak. Black (upper row) and blue symbols (bottom row) refer to two different herds. Open and closed symbols identify different individuals within one herd

salinity, and aridity, and is close to 0 in legumes, while δ13C becomes less negative with drought, altitude, and proportion of C4 biomass in vegetation.

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The isotopic signals in hair are well conserved. Auerswald et al. (2011) found that natural wear did not cause significant changes of the carbon, nitrogen, oxygen, and hydrogen isotope composition of cattle hair. So, hair represents a durable, faithful record of the dietary signals ingested by cattle and incorporated in hair. Moreover, the comparatively uniform chemical composition of hair, which is largely keratin (a structural protein), is also a useful feature as variation in isotopic fractionation associated with digestion and metabolism associated with hair synthesis is minimized due to the relative uniformity of its biochemical composition. Earlier, Tobias Männel found that the change of δ13C of grassland vegetation with altitude was accurately reflected in the δ13C of the hair of sheep and cattle, if the same trophic shift of ~3‰ was applied (Männel et al. 2007). This work was most helpful later on (see below), but was really borne out of an ‘accident’, as Tobias, Karl Auerswald, and myself were actually supposed to sample soil, vegetation, and wool in the Inner Mongolia steppe in the frame of a DFG project, a sampling activity that was suddenly blocked because of the SARS4 outbreak in spring of 2003 in China, and had to be postponed (Fig. 8). Actually, the trophic shift-altitude relationship characterized by Tobias Männel also held across the Alps and Tibet altitude range, when cattle, sheep, and yak hair data were combined (Hans Schnyder, unpublished data). The same principles apply to the horn of many Bovidae species, such as yak (Bos mutus) (Fig. 9), chamois (Rupicapra rupicapra rupicapra), and alpine ibex (Capra ibex) that we have studied (Barbosa et al. 2009; Schnyder et al. 2014). The strongest effect on the δ13C of grazer tissues (including hair or bone collagen) and excretions (such as milk and excrements) emanates from the relative proportions of C3 and C4 photosynthetic type vegetation (Fig. 10) in the diet (Jones et al. 1981; Minson et al. 1975). Thus, with data from Stephan Schneider, Alex Braun modelled the buffering effect of metabolic pools and delays in the incorporation of a dietary isotopic signal – originating from a switch from a C3-grass/maize diet to a pure C3 grass diet – into milk components (lactose, casein, milk fat) and faeces (Braun et al. 2013b, see also Braun et al. 2013a). The strong carbon isotopic contrast between C3 and C4 also means that the nutritional ecology of termites and mammalian herbivores in mixed C3-C4 ecosystems can be reliably characterized by carbon isotopes, such as in the Serengeti tropical savanna, where trees are C3 (supporting browsers) and the herbaceous stratum is dominated by C4 grasses (supporting large gazers and termites) (Ambrose and DeNiro 1986; de Visser et al. 2008). In the MAGIM project (‘Matter fluxes in grasslands of Inner Mongolia as influenced by stocking rate’, a research unit funded by the German Research Foundation, 2004–2010), we used this principle to assess shifts in C3-C4 vegetation composition based on sampling and 13C analysis of soil organic carbon, vegetation at community and species level, and modern and old wool samples (Wittmer et al. 2010a, b; Auerswald et al. 2009, 2012). These investigations confirmed that hair was a faithful spatio-temporal integrator and recorder of C3-C4 vegetation composition grazed over

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Fig. 8 Tobias Männel sampling vegetation and soil in the Inner Mongolia steppe (Foto: Karl Auerswald)

the period of hair growth (Auerswald et al. 2009), particularly, if effects of altitude (Männel et al. 2007) and precipitation during the growing season (Wittmer et al. 2008) on the δ13C of the C3 vegetation component were accounted for in the analysis. This work also supported the notion that shifts in C4 proportion were driven by temperature-moisture interaction and not grazing pressure. In that, remarkably, observed recent increases in the C4/C3 abundance ratio across a wide range of Inner Mongolia grassland (Fig. 8) conflicted with our expectations. Based on the (anthropogenic) increase of atmospheric CO2 concentration [CO2] in the last century, one would have predicted a decrease (Collatz et al. 1998). Earlier, Michael Schwertl et al. (2005) had used the contrast in δ13C between C3 and C4 plants (see also Fig. 10) to characterize cattle farms in Southern Bavaria in terms of the share (proportion) of maize (C4) in comparison to C3 forages, including mainly grassland, in total forage use at farm scale. In addition, Michael Schwertl also discovered a close relationship between stocking rate and the δ15N of cattle hair which was connected with surplus nitrogen fertilizer application on the farmland (nitrogen fertilizer applied in excess of nitrogen harvested in forages). Most probably, excess nitrogen fertilizer application provoked an ‘opening’ of the agroecosystems’ saturated soil nitrogen pool, with excess addition balanced by losses via volatilization and denitrification, and associated 15N fractionation effects causing an enrichment of 15N in the soil N pool. This work demonstrated clearly that

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Fig. 9 Horn of a 16 years-old yak cow showing sampling scars within year rings (see inset). The animal was found dead in 2011, in Yushu district (Tibetan Autonomous Prefecture, Qinghai/China), after a heavy snow disaster (Rende Song, personal communication) (Foto: Richard Wenzel)

the use of carbon and nitrogen isotope analysis can provide an ecological fingerprint of cattle operations at a regional scale, an information criterion useful for consumer choices and (agro)ecological and environmental assessment. While the 13C and 15N signatures of animal tissues are essentially determined by the organic component of the diet (Schwertl et al. 2005; Auerswald et al. 2010), the oxygen isotope signal (δ18O) in animal biomass components and water pools is primarily determined by water intake by drinking or ingestion of feed moisture (Sun et al. 2010, 2014), both of which are influenced by meteoric water (precipitation) (Chen et al. 2017) and provide another dimension to the ecological fingerprint spectrum that is useful for authenticity or forensic investigation (Rossmann 2001; Cerling et al. 2016; Camin et al. 2017).

5.2

Effects of Anthropogenic Climate Change on the Water-Use Efficiency and Stomatal Conductance of Grassland Vegetation

Quantitative understanding of the physiological significance of carbon isotope discrimination (Δ13C) of C3 vegetation was first conveyed in virtually full mechanistic detail by Farquhar et al. (1982). Particularly its significance for estimating ci/ca and hence the ratio of net assimilation (A) to stomatal conductance (gs), which

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Fig. 10 Frequency distribution of 13C discrimination (Δ13C) of grassland plants (a). The bimodal distribution of Δ13C is due to the presence of two photosynthetic types with different carbon isotope discrimination: C4 plants (left hump) and C3 plants (right hump). Both photosynthetic types occur in the grasses (b), chenopods (c), and other plant families (not shown). The data were compiled from >40 references with a total of >3,000 entries (from Schnyder and Auerswald 2008)

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reflects the physiological component of WUE, termed intrinsic WUE (iWUE = A/ gs) – with simplifying assumption as specified (Farquhar et al. 1982) – had a big impact on physiological, ecological, and biogeochemical research (e.g. Cornwell et al. 2018). This provided a precious framework for analyses of the physiological information, which is embedded in the carbon isotope signal of tree rings (Francey and Farquhar 1982). Such investigations indicated mostly significant increases of iWUE during the last century (e.g. Saurer et al. 2004), even though uncertainties remained, e.g. concerning the effect of mesophyll conductance on the relationship between Δ13C and ci/ca (Seibt et al. 2008; Ma et al. 2021) or of leaf-to-air vapour pressure difference (VPD) when interpreting data in terms of transpiration efficiency. Also, the literature revealed strong variation between taxa and sites in the

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different studies. At the time, these works really motivated my interest in the iWUE response of grassland vegetation, also with regard to the question if site conditions and plant functional group composition could have altered the iWUE response of grassland communities to last-century atmospheric [CO2] increase, thus potentially changing the coupling of terrestrial water and carbon cycles. As it turned out, it also affected the coupling with nitrogen cycles (see below). The question was also of practical interest, particularly with regard to plant functional type responses, as site conditions and plant community composition are managed by farmers, e.g. via the adaptation of grazing/cutting regimes (timing and frequency of defoliation) and fertilizer addition, and also have important effects on the quantity and quality of forage. Yet, chronologies of Δ13C of grassland are not as accessible as in mature trees (with their multidecadal or centuries-long tree-ring archives), as grassland vegetation is short-lived. No living grass tissue persists for much longer than 1 year, even if it remains un-grazed. Thus, information on grassland iWUE responses to last-century climate change has been scant, scattered, and essentially limited to analyses of herbarium species. Therefore, the Park Grass Experiment at Rothamsted/ England (established in 1856) is a unique resource, as cut herbage from a large range of fertilizer treatments has been stored every year in the Rothamsted sample archive since the beginning of the experiment, a resource to which we were granted access for investigations of Δ13C, δ18O and community nutrient status for nitrogen and phosphorus (Storkey et al. 2015; Köhler et al. 2016; Baca Cabrera et al. 2021a, b). At the same time, I started to wonder, if collections/archives of horns of Alpine ibex (Fig. 11) could be found from which to reconstruct the last-century changes of iWUE of alpine grassland. New research ideas were often first explored in the frame of Bachelor, Master, or Diploma theses, often connected with a methodical question, as was also the case here for the works of Maximiliane Kley, Inês Barbosa, and Iris Köhler (Barbosa et al. 2009, 2010, Köhler et al. 2010). Both the alpine grassland – based on 13C analyses of the horn of Alpine ibex from Augstmatthorn, sampled from the collection of the Natural History Museum of Bern/Switzerland – and the unfertilized, un-limed ‘control’ treatment of the Park Grass Experiment demonstrated marked increases of iWUE in the last century (Barbosa et al. 2010, Köhler et al. 2010). In addition, the Park Grass grassland revealed a strong sensitivity of Δ13C (and hence iWUE) to interannual variation in plant available soil water (Köhler et al. 2010), similar to the site- and year-dependent variation of Δ13C of grassland, as estimated from the δ13C of cattle hair at Grünschwaige (Schnyder and Auerswald 2008). Later, in the frame of a DFG project prepared jointly with Iris Köhler, and later another one with Regina Hirl, more comprehensive studies comparing fertilizer treatments at Park Grass revealed a significant positive relationship between the proportion of grass in the community and the increase of iWUE (Köhler et al. 2012, 2016; Baca Cabrera et al. 2021a, b). A key question in studies of climate change effects on past increases of iWUE is whether the increase was due to an increase of net photosynthesis or a decrease of stomatal conductance, or a combination of both. Based largely and originally on the model of Scheidegger et al. (2000), the combination of oxygen isotope composition

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Fig. 11 Male Alpine ibex near the summit of Augstmatthorn, 2,137 m a.s. l. (Emmental Alps/ Switzerland) on August 4, 2011 (Foto: Hans Schnyder)

(δ18O) and δ13C of biomass – or rather the 18O-enrichment of cellulose above source water (Δ18OCellulose ≈ δ18OCellulose – δ18OSource water) and Δ13C – has been used widely to assign the driver (net photosynthesis or stomatal conductance) of longterm changes of iWUE in trees (e.g. Guerrieri et al. 2019, Mathias and Thomas 2021). Although mechanistic understanding of the relationship between Δ18OCellulose and stomatal conductance is far from complete (see also Sect. 6), a compilation of published data by Regina Hirl confirmed the predicted overall negative relationship between Δ18OCellulose and stomatal conductance across a wide range of experimental scenarios, albeit with large variation of the sensitivity between the studies (Baca Cabrera et al. 2021a). Most importantly, using two independent approaches, Juan Baca found a much stronger reduction of (canopyand growing season-integrated) stomatal conductance in grass-rich than dicot-rich communities, which also determined the greater increase of iWUE in the grass-rich communities (Baca Cabrera et al. 2021a). This effect of last-century climate change on stomatal conductance was connected with reductions in nitrogen acquisition in

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grass-rich plots, an effect not generally observed in the dicot-rich communities. Clearly, at Park Grass, last-century climate change has interacted strongly with fertilizer and liming treatment effects on yield and forage quality (protein concentration) via effects on plant community functional group composition (Baca Cabrera et al. 2021a).

6 Trying to Understand the 18O Signal in Plant Water Pools and Carbohydrates In most plants leaf sucrose is the central player in cellulose synthesis, being the primary photosynthetic product, translocated sugar and hence universal carbohydrate substrate in sink tissue. Therefore, to understand the relationship between Δ18OCellulose and stomatal conductance, it is important to comprehend the factors which determine the 18O composition of sucrose (δ18OSucrose), and particularly its 18 O enrichment above source water (Δ18OSucrose = δ18OSucrose – δ18OSource Water), the photosynthetic 18O signal in the primary substrate. It has long been assumed that all oxygen in sucrose derives from water, based on the observation of DeNiro and Epstein (1979) that the oxygen isotope composition of CO2 had no influence on the 18 O signal in cellulose of wheat plants, a result confirmed by us also for Cleistogenes squarrosa, a C4 grass (Liu et al. 2016). Very recently, we have first confirmed experimentally the expectation that virtually all oxygen in leaf sucrose of perennial ryegrass must derive from water (Baca Cabrera et al. 2022). In these experiments, plants were grown in the presence of CO2 with different δ18O in contrasting conditions of atmospheric CO2 concentration [CO2], and humidity. Given the central role of sucrose, it is surprising that very few studies have actually addressed δ18OSucrose. Cernusak et al. (2003, 2005) used the δ18O of phloem sap dry matter (δ18OPhloem DM) as a proxy for δ18OSucrose in Ricinus communis and Eucalyptus globulus and found a good agreement between δ18OPhloem DM and the δ18O of average lamina water (δ18OLamina Water) – that is bulk water minus the water in major veins – provided that they considered an average biosynthetic fractionation (εbio) of ~27‰, similar to the average enrichment of cellulose in aquatic plants. So, essentially, δ18OSucrose could be estimated as δ18OLamina Water + 27‰, a practice that has become very popular, since isotopic measurements of lamina (or leaf) water are undemanding in comparison to sucrose. Only Lehmann et al. (2017) had purified leaf sucrose in two grasses (Lolium perenne and Dactylis glomerata) and found a significant, although humidity-dependent underestimation of δ18OSucrose by the δ18O of bulk leaf water (δ18OLW) in the grasses, if εbio was set to 27‰. Particularly at low humidity δ18OSucrose was much greater than δ18OLW + 27‰, a finding that Juan Baca recently confirmed for L. perenne grown at different atmospheric [CO2] (Baca Cabrera et al. 2022). Whether or not a discrepancy would be observed relative to lamina water, is not known. However, clearly, δ18OLW + 27‰ is not a reliable proxy of δ18OSucrose in these grasses.

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Earlier, Barbour and Farquhar (2000) have summarized understanding of the relationship between Δ18OSucrose and Δ18OCellulose in a quantitative model. In this they replaced Δ18OSucrose by Δ18OLW + εbio. Thus, Δ18 OCellulose = Δ18 OLW ð1–pex px Þ þ εbio ,

ð2Þ

with pex the proportion of oxygen in cellulose which has exchanged with water at the site of cellulose synthesis, and px the proportion of source water at this location. Thus, (1 – pex px) is an attenuation factor, which results from the fact that metabolites of sucrose used in cellulose synthesis have oxygen atoms in the form of carbonyl groups, which exchange with water also at the site of cellulose synthesis (there are no carbonyl oxygens in sucrose). This process reduces the 18O-enrichment of the metabolites. Note that in the hypothetical case for which pex px = 1, Eq. 2 predicts that Δ18OCellulose is completely independent of Δ18OSucrose, which means that there is no photosynthetic signal in Δ18OCellulose. The most reliable estimates of pex come from heterotrophic systems, e.g. tissue cultures with a substrate with known Δ18O (e.g. Sternberg et al. 1986). If the substrate is sucrose, a pex of ~0.4–0.5 (Cernusak et al. 2005) has been widely assumed, although variation could be much bigger (Barbour 2007). Unfortunately, pex cannot be measured in intact, autotrophic systems, which means that pex must be estimated by solving Eq. 2. Thus, the veracity of a pex estimate is dependent on the accuracy of every parameter in that equation. In particular, an error results if Δ18OSucrose ≠ Δ18OLW + εbio or if true εbio differs from that assumed in Eq. 2. Actually, there is debate on whether εbio is constant, e.g. at 27‰, or dependent on temperature as shown by Sternberg and Ellsworth (2011). Indeed, Regina Hirl found a much better agreement between modelled and observed Δ18OCellulose in a multi-seasonal analysis of leaf cellulose data of a grassland ecosystem at Grünschwaige, when she used a temperature-dependent εbio (Hirl et al. 2021). Also, estimation of pex in grass leaves relies on knowledge of px, which was first measured in the leaf growth-and-differentiation zone of several C3 and C4 grasses in a controlled environment study by Haitao Liu et al. (2017a) and yielded a value of ~0.95, indicating a δ18O of water at the site of leaf cellulose synthesis close to that of source water. A very similar value was obtained by Juan Baca in perennial ryegrass across contrasts of atmospheric [CO2] and humidity (Baca Cabrera et al. 2022). In this study, which was performed in a thermal environment for which the temperature-dependent εbio of Sternberg and Ellsworth (2011) converged approximately with the 27‰ assumption, Juan estimated an average pex = 0.52, when solving Eq. 2 for pex with Δ18OLW replaced by Δ18OSucrose – εbio (Baca Cabrera et al. 2021b). Remarkably, however, when based on Δ18OLW, the estimate of pex became strongly sensitive to both atmospheric humidity and [CO2], an artefact resulting from the unreliability of Δ18OLW as a proxy of Δ18OSucrose – εbio. Accordingly, the atmospheric humidity-dependence of pex observed by Regina Hirl likely also resulted from the same (or similar) humidity-dependent underestimation of Δ18OSucrose by Δ18OLW + εbio (Hirl et al. 2021). Indeed, based on our recent work

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(Hirl et al. 2021; Baca Cabrera et al. 2021b, 2022), we hypothesize that the real postphotosynthetic attenuation of the 18O signal, given by (1 – pex px) observed in the conjoint analysis of Δ18OSucrose and Δ18OCellulose, is actually virtually constant at ~0.5 in grasses. According to our most recent analyses, the deviation between Δ18OSucrose and 18 Δ OLW + εbio is connected with the fact that the non-photosynthetic water pool of grass leaves comprises a very large fraction of total leaf water (similar to 53% or more) and displays an 18O enrichment that tends to oppose that of the photosynthetic water pool (Baca Cabrera et al. 2022). Moreover, we found that Δ18OSucrose was well predicted by theoretical estimates of leaf water at the evaporative site, with small deviations that correlated with stomatal conductance and total conductance for CO2 (Baca Cabrera et al. 2022). Given that chloroplasts tend to be appressed to the outer wall of mesophyll cells (which faces the intercellular air space), this result does make much sense. Estimation of Δ18OLW, Δ18OSucrose, and Δ18OCellulose requires a good knowledge of δ18OSource Water, which is relatively easily determined in experiments in controlled environments with irrigation water of constant isotopic composition (Liu et al. 2017a; Baca Cabrera et al. 2021b). However, determination of δ18OSource Water can be really challenging in natural conditions, if the δ18O of soil water varies dynamically in space and time, as is commonly the case. Already in summer of 2005, we had started to analyse the 18O signal in water compartments of a grassland ecosystem, pasture paddock no. 8 at Grünschwaige (Fig. 3b). This activity was inspired by the so-called MIBA (moisture isotopes in biosphere and atmosphere) initiative launched by IAEA in 2005. Again, a diploma thesis was at the origin of the adventure. With help of Ulli Ostler, Inga Schleip (née Müller; Müller 2006) devised a methodology for soil, vegetation, and atmospheric humidity sampling, set up and tested a cryogenic distillation unit for water extraction (after a design of Rolf Siegwolf, then at Paul Scherrer Insitut, Villigen/Switzerland), and analysed the diurnal variation of δ18O in different ecosystem compartments. These included soil at different depths, leaves, dew on leaves if present, and atmospheric humidity. Also, Inga and Ulli designed a scheme for the following sampling which proceeded at fortnightly intervals during the vegetation period between spring of 2006 and fall of 2012 (Hirl et al. 2019), when the TUM Grünschwaige grassland research farm was closed. This data set contributed a very large proportion of the grassland data in the recent global scale analysis of leaf water 18 O and 2H (Cernusak et al. 2022). Two people were key for our eventual quantitative understanding of the propagation of the 18O signal from meteoric water (precipitation), through soil water, 18O of water absorbed by the root system, 18O enrichment of leaf water, and eventually imprinting the enriched 18O signal in leaf cellulose: Regina Hirl, who had a genuine mathematical talent and was adventurous enough to agree on tackling her MSc thesis with a physically based, 18O-enabled soil–plant–atmosphere model (for which there was no expertise within or outside my group at TUM) and Jerôme Ogée (INRAE ISPA EcoFun, Bordeaux/France), the author of such a model, MuSICA (Ogée et al. 2003), who was happy to welcome Regina in his group, guide her with MuSICA in

Explorations into the Physiology and Ecology of Grassland Plants. . .

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her MSc thesis and later became her co-advisor during her PhD. This work brought a tremendous boost to our mechanistic understanding of the water isotope data at Grünschwaige. Regina parameterized MuSICA for Grünschwaige pasture paddock no. 8, in great detail (see supplement to Hirl et al. 2019), and used the model to predict the spatio-temporal variation of δ18O in the soil, the depth-distribution of root water uptake, and the depletion and refilling dynamics (by meteoric inputs) of the soil water pool, δ18OSource Water (termed δ18Ostem), δ18OLW and Δ18OLW. Predictions were then compared with the series of observations made in this pasture ecosystem between spring of 2006 and fall of 2012 (Hirl et al. 2019). Remarkably, both model predictions and observations indicated that water uptake occurred predominantly from shallow ( 60. Furthermore, total SS activity was increased in Atss3 mutants, and plants had greater starch content in the leaves during the light period. Those results suggested that SS3 may have a negative regulatory function in the synthesis of transitory starch in Arabidopsis (Zhang et al. 2005). It is also proposed that SS3 might contribute to the elongation of short chains and the generation of long, cluster-spanning chains (Szydlowski et al. 2011; Cuesta-Sejio et al. 2016). SS1-4 enzymes are usually called as soluble starch synthases, in contrast to the GBSS. However, these enzymes are not widespread in the chloroplast stroma. In fact, each class shows a specific pattern of localization in the stroma. Thus, in Arabidopsis chloroplasts, SS1 is localized throughout the stroma. SS2 is localized both soluble in the stroma and associated with the starch granule and the chloroplast membrane fraction. SS3 is found around the starch granule, and SS4 is found in discrete dots within the chloroplast, associated with specific points on the thylakoid membranes (Gámez-Arjona et al. 2014; Gámez-Arjona and Mérida 2021). It would be interesting to determine whether these patterns might be extrapolated to other plant species and to starch-storing organs, such as tubers and seed endosperms. Little is known about whether posttranslational modifications of SSs might regulate their activities. The Arabidopsis SS3 (Heazlewood et al. 2008) and the maize GBSS (Grimaud et al. 2008) were proposed to be phosphorylated, but it remains to be determined whether this modification is involved in the regulation of the enzyme activity. Protein–protein interactions appear to be the most frequent mechanism for regulating SS activities. This mechanism is illustrated with studies on GBSS. It was thought that this protein was solely responsible for amylose synthesis, although the reason why GBSS is exclusively within the starch granule remained unsolved. It has been shown that GBSS requires the interaction with another protein, PROTEIN TARGETING TO STARCH (PTST1), to be delivered to starch granules (Lohmeier-Voget et al. 2008; Seung et al. 2015). PTST1 interacts with GBSS via C-terminal coiled-coils and with starch via an N-terminal carbohydrate-binding

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domain. Without PTST1, GBSS cannot bind efficiently to starch and is degraded in the stroma (Seung et al. 2015). Protein–protein interactions also modulate the initiation of the starch granule. SS4 provides the enzymatic activity necessary to initiate the granule, but SS4 does not act alone. It has been shown that PROTEIN TARGETING TO STARCH 2 (PTST2) interacts with SS4, and its elimination leads to a phenotype similar to that of the ss4 mutant (Seung et al. 2017). In addition, PTST2 interacts with other plastidial polypeptides: MAR-BINDING FILAMENT-LIKE (MFP1) and PROTEIN INVOLVED IN STARCH INITIATION (PII1). PII1 also interacts with SS5, a non-canonical SS isoform that lacks catalytic activity (Abt et al. 2020). It is thought that these interactions might facilitate the access of SS4 to its substrates and ensure the correct folding of the enzyme (for a review, see Mérida and Fettke 2021 and references therein). Finally, protein–protein interactions between several enzymes in the starch biosynthesis pathway have been well documented in the endosperms of wheat, maize, barley, and rice (Tetlow et al. 2004, 2008; Hennen-Bierwagen et al. 2008; Liu et al. 2009; Ahmed et al. 2015; Crofts et al. 2017). In particular, SS2a has been shown to associate with SS1 and SBE2b (Tetlow et al. 2004, 2008; Hennen-Bierwagen et al. 2008), and within this complex, SBE2b is phosphorylated (Liu et al. 2009). Within this trimeric heteromeric enzyme complex, SS2a is responsible for the association of SSI and SBE2b with the granule (Liu et al. 2012). More recently, it has been shown that, in this complex, SS2a is phosphorylated, and upon phosphorylation, SS2a activity increases; moreover, SS2a phosphorylation determines the type of complex to be formed (Mehrpouyan et al. 2021). The circadian clock also regulates the expression of some SS genes, such as GBSS of Antirrhinum (Mérida et al. 1999) and Arabidopsis (Tenorio et al. 2003). Intriguingly, GBSS mRNA levels oscillate in different phases in these two species. In Arabidopsis, GBSS mRNA peaks at the beginning of the day, and in Antirrhinum it peaks at the end of the day (Mérida et al. 1999; Tenorio et al. 2003). Further studies are necessary to ascertain whether this difference might reflect different metabolic requirements. The expression of the other SS genes, except SS2, does not seem to be regulated by the circadian clock in Arabidopsis (Smith et al. 2004).

3.3

Starch Branching Enzymes

SBE (α-1,4-glucan branching enzyme, EC 2.4.1.18) typically acts, in vitro, on linear chains longer than 12 or 13 glucoses, transferring terminal sections of six or more glucoses to the same or an adjacent chain. Most plants have two classes of SBEs, SBE1 and SBE2. These classes differ considerably in their substrate preferences and products. SBE1 is highly active on long linear chains, and it cleaves α-1,4 linkages behind existing branch points. SBE2 isoforms preferentially act on the outer chains of branched structures (Guan and Preiss 1993). Two isoforms of the SBE2 class (SBE2a and SBE2b) are present in most of the plant species studied so far. In rice and maize, SBE2a is essential for normal starch synthesis in leaves, but not in

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endosperm, and SBE2b is essential for starch synthesis in the endosperm (Blauth et al. 2001; Nishi et al. 2001; Nakamura et al. 2010). Amylose-extender is a maize mutant that lacks SBE2b and is the basis of the commercial high-amylose cultivars of this crop (Hedman and Boyer 1982, 1983; Stinard et al. 1993). In maize, the SBE2b isoform has several functional phosphorylation sites. However, the physiological significance of this modification is not well understood (Makhmoudova et al. 2014). As mentioned for the SSs, the SBEs of maize, wheat, barley, and rice endosperms seem to operate by forming multiprotein complexes. In addition to the trimeric complex of SS2a, SS1, and SBE2b in maize, rice endosperm contains two other multiprotein complexes. One complex comprises SS2a, SS3a, SS4b, SBE1, SBE2b, and pullulanase (PUL). The other complex comprises SS1, SS3a, SBE1, SBE2b, isoamylases 1 (ISA1), PUL and phosphorylase 1 (PHO1) (Crofts et al. 2015). It remains to be explained how these complexes affect the synthesis of starch. Unlike findings in long-term starch storing organs, such as the seed endosperm of cereals, no multiprotein complexes of starch metabolism enzymes have been found in photosynthetic tissues, where transitory starch is synthesized. Thus, the question remains as to whether this mechanism of regulation might be specific to the starch synthesis for long-term storage.

3.4

Debranching Enzyme

The highly branched glucan created by SSs and SBEs must be selectively debranched (trimmed) by debranching enzymes to allow the establishment of double helices and the formation of crystalline regions in the amylopectin molecule (Ball et al. 1996; Myers et al. 2000; Wattebled et al. 2008). Plant debranching enzymes are classified as isoamylases (ISAs, EC 3.2.1.68) type (containing 3 classes, ISA1, ISA2, and ISA3) and PUL (EC3.2.1.41, also termed limit dextrinase). All are hydrolases specific for the α-1,6 linkage but they differ in their substrate preferences (Kobayashi et al. 2016). ISA3 and PUL are monomeric enzymes and are primarily involved in starch degradation, although they may also contribute to debranching during synthesis (Dinges et al. 2003; Fujita et al. 2009). ISA1 forms heterodimers with ISA2 and is inactive or unstable in its absence. However, in cereal endosperms, ISA1 can form active homomultimeric complexes in addition to heteromultimeric complexes with ISA2 (Delatte et al. 2005; Kubo et al. 2010). ISA2 is inactive due to nonconservative substitutions in amino acids essential for catalysis; thus, it seems to have a regulatory function (Hussain et al. 2003). It is still unclear the physiological consequences of the appearance of ISA1 in homo- or heteromultimeric complexes in some species. Mutants deficient in isoamylase activity accumulate a soluble, highly branched glucan called phytoglycogen, which resembles glycogen (Mouille et al. 1996). The extent of phytoglycogen accumulation in isoamylase-deficient mutants depends on the species considered. In Chlamydomonas, starch synthesis is abolished and phytoglycogen is synthesized in its place (Mouille et al. 1996). However, in

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plants, isa mutants more commonly synthesize both phytoglycogen and some starch with altered amylopectin structure (Delatte et al. 2005; Lin et al. 2013).

3.5

Phosphorylases

Phosphorylase (EC 2.4.1.1) catalyzes the reversible reaction: α
1, 4
glucan ðnÞ þ Glc1P⟺α
1, 4
glucan ðn þ 1Þ þ Pi Therefore, phosphorylase can participate in starch synthesis and/or degradation. Higher plants possess two distinct starch phosphorylase activities, a plastidial form (PHO1) and a cytosolic form (PHO2) (Hwang et al. 2020). The plastidial PHO1 form is directly involved in starch metabolism (Satoh et al. 2008), while the cytoplasmic PHO2 is required for the metabolism of maltose, the main product of starch degradation, in the cytoplasm (Lu et al. 2006). The exact roles of plastidial phosphorylase in higher plants have been controversial for years. The analysis of single knockout mutants of PHO1 and double knockout mutants of PHO1 with a second gene involved in maltose metabolism (the cytosolic disproportionating enzyme 2 (DPE2, EC 2.4.1.25) or the maltose transporter (MEX1) suggested that PHO1 played a role in transitory starch degradation in Arabidopsis leaves (Malinova et al. 2014). In contrast to those findings in leaves, cumulative evidence has suggested that phosphorylase plays a synthetic role in algae and sink organs of higher plants (for a review, see Hwang et al. 2020 and references therein). As mentioned above, PHO1 is found in multiprotein complexes with SSs and/or SBEs in rice (SBE2a/Pho1 and SBE1/SBE2a/SBE2b/PHO1) (Crofts et al. 2015; Nakamura et al. 2017) and in maize and wheat (SBE1/SBE2b/Pho1 and SS1/SS2a/ SBE1/SBE2a/PHO1). In maize and wheat, the formation of these complexes depends on both the phosphorylation of their components (Tetlow et al. 2004; Liu et al. 2009) and the oligomeric state of PHO1. Thus, both SBE1 and SBE2b interact with the monomeric form of PHO1, but only SBE1 interacts with the tetrameric form of PHO1 (Subasinghe et al. 2014). It has been suggested that, in addition to its regulatory activity, via the formation of multiprotein complexes, PHO1 could be a potential target of thioredoxins (Xu et al. 2010). However, the in vitro starch biosynthetic activity of barley PHO1 is not affected by reduced or oxidized DTT or by a barley thioredoxin system, which suggests that the catalytic activity of this enzyme is not sensitive to the redox status (Cuesta-Seijo et al. 2017). In wheat and maize, PHO1s were reported to be phosphorylated, and the phosphorylated protein could form multiprotein complexes with SBEs (Tetlow et al. 2004; Walley et al. 2013; Subasinghe et al. 2014). However, it remains to be determined whether phosphorylation affects the enzymatic properties of Pho1.

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More recently, it has been suggested that Pho1 is involved in the initiation of the starch granule in Arabidopsis, providing suitable substrates for the activity of SS4 (see references in Mérida and Fettke 2021).

4 Starch Mobilization Many aspects of the current knowledge on starch synthesis in leaves (determined mainly in Arabidopsis) may be extrapolated to starch synthesis in sink tissues, such as cereal endosperms. However, starch mobilization is radically different between Arabidopsis leaves and cereal endosperms. In Arabidopsis leaves, the starch granule is attacked by two types of hydrolytic enzymes, the β-amylases (BAMs, EC 3.2.1.2), which are exoamlyases that cleave α-1,4 linkages, and the debranching enzymes (ISA3 and PUL), which cleave α-1,6 linkages. Two BAMs are essential for normal starch degradation rates: BAM3 and BAM4, but BAM1 can also contribute to starch degradation. BAM4 is not an active enzyme, and its function is unknown, although it has been discarded that modulates the activity of BAM3 or BAM1 (Fulton et al. 2008; Li et al. 2009). The disaccharide maltose is the major product of BAM and DBE activities on the starch granule. Some maltotriose is also produced from the hydrolysis of chains with an odd number of glucose residues. This malto-oligosaccharide cannot be further hydrolyzed by BAM; instead, it is metabolized by the plastidial disproportionating enzyme (DPE1 or D-enzyme, 1,4-α-D-glucan:1,4-α-D-glucan, 4-α-Dglucanotransferase, EC 2.4.1.25), which transfers glucan moieties between nonreducing ends of chains, and thus, it converts two maltotrioses to one maltopentaose (which is a substrate for BAMs) and one free glucose (Lin and Preiss 1988; Takaha et al. 1998; Critchley et al. 2001). The rate at which the starch granule is degraded by hydrolytic enzymes depends on the activities of proteins that influence the crystalline structure of the amylopectin surface. Two sets of enzymes respectively phosphorylate and dephosphorylate glucose residues within amylopectin molecules. GWD (EC 2.7.9.4) and phosphoglucan water dikinase (PGWD, EC 2.7.9.5) phosphorylate the glucose residues at the C6- and C3-positions, respectively (Ritte et al. 2002; Kötting et al. 2005; Baunsgaard et al. 2005; Ritte et al. 2006). Both enzymes are essential for normal starch degradation. Their actions destabilize the structure of amylopectin, which allows BAM and DBE to degrade it. The glucose residues phosphorylated by GWD and PGWD must also be dephosphorylated for normal starch degradation, because the phosphate groups do not allow the progressive degradation of linear chains by BAMs. Two phosphatases, SEX4 and LIKE SEX4 2 (LSF2) (EC 3.1.3.48) are responsible for these dephosphorylations. SEX 4 can remove both C6- and C3-phosphates from glucose residues, and LSF2 removes only C3-phosphates (Sokolov et al. 2006; Comparot-Moss et al. 2010; Santelia et al. 2011). Another phosphatase, LSF1, closely related to SEX4 and LSF2, is also essential for normal starch degradation via a different mechanism. Recent studies suggest that LSF1 is a

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starch-binding protein that forms granule-surface-located complexes with either BAM1 or BAM3 (Schreier et al. 2019). Another protein (EARLY-STARVATION 1, ESV1) has been found to be necessary for the normal rate of starch degradation. This protein binds to the starch granule and seems to modulate the activities of GWD and PGWD on the surface of the granule (Malinova et al. 2018). Those data indicate that, similar to starch synthesis, protein–protein interactions play an essential role in the regulation of starch degradation. The rate of starch degradation is finely adjusted to the length of the dark period This adjustment is necessary to avoid plant starvation before it can perform photosynthesis. A considerable number of studies indicate that this adjustment is exerted through the control of the starch degradation rate by the circadian clock (Graf et al. 2010). We have mentioned that some transcripts of the starch metabolism pathway are regulated by the circadian clock. However, in general, the enzymes themselves show little diel changes in abundance. Thus, the circadian control of starch metabolism is likely exerted through posttranslational modifications of the enzymes, although the mechanisms remain unknown. As mentioned above, cereal grain endosperms have a physiological context and starch degradation pathway radically different from those in Arabidopsis leaves. During grain maturation, the endosperm cells die, leaving the starch granules encapsulated in a matrix of cell walls. During germination, starch granules are hydrolyzed by the action of α-amylases (AMY, EC 3.2.1.1, an endoamylase capable of attacking α-1,4 linkages throughout the amylopectin molecule), which is secreted from the living scutellum and aleurone cells surrounding the endosperm. The products of the α-amylase are glucose, maltose, and short oligosaccharides containing α-1,6 linkages (α-limit dextrins). These oligosaccharides are further attacked by BAM, maltase, and PUL, which produce glucose as the final product. Finally, this glucose is taken up by the scutellum for use in embryo growth (Fincher 1989).

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Photorespiration and Improving Photosynthesis Michael Hodges

Contents 1 Increasing Agricultural Productivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 A Brief Overview of How to Improve Photosynthesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 The Light Reactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Improving the Dark Reactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 On-going Strategies for Improving Photosynthesis: Light Capture, Photoprotection, CO2 Concentrating Mechanisms, and RuBP Regeneration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Light Capture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Photoprotection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 CO2 Concentrating Mechanisms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 RuBP Regeneration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Photorespiration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Why Is Photorespiration Bad for Photosynthesis and Crop Yield? . . . . . . . . . . . . . . . . . . 4.2 What Is Photorespiration? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Regulation of the Photorespiratory Cycle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Characterization of Photorespiratory Mutants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5 Over-Expression of Photorespiratory Cycle Enzymes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.6 Photorespiratory Bypasses to Improve Photosynthesis and Plant Productivity . . . . . 5 The Future: Alternative Theoretical and On-Going Photorespiratory Bypasses . . . . . . . . . . . 6 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract Improving photosynthesis has become a strategy to increase plant productivity. Current photosynthetic targets dealing with light and CO2 capture will be briefly described and major breakthroughs dealing with photoprotection kinetics, CO2-concentrating mechanisms, and ribulose-1,5-bisphosphate regeneration will be highlighted before focusing on photorespiration. This metabolic process

Communicated by Francisco M. Cánovas M. Hodges (*) Université Paris-Saclay, CNRS, INRAE, Université Evry, Université Paris Cité, Institute of Plant Sciences Paris-Saclay (IPS2), Gif sur Yvette, France e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 Progress in Botany (2024) 84: 171–220, https://doi.org/10.1007/124_2022_64, Published online: 23 July 2022

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occurs when ribulose-1,5-bisphosphate carboxylase/oxygenase, the major CO2assimilatory enzyme, uses O2 thereby producing toxic 2-phosphoglycolate that has to be removed. This is achieved by the photorespiratory cycle, a high energy cost pathway that competes with photosynthetic CO2 assimilation and releases both CO2 and ammonium that can be lost to the atmosphere if not re-assimilated. This wasteful metabolic pathway cannot be knocked out, as photorespiratory mutants are unable to develop normally in air and require high CO2 atmospheres that limit photorespiration for normal growth. Surprisingly, little is known about the regulation of this important metabolic cycle even though photorespiratory enzymes are associated with several post-translational modifications. Current progress in the use of photorespiratory mutants to better understand photorespiration and its interactions with other metabolic pathways, and in proteomics to identify potential regulatory mechanisms will be described before moving onto how manipulating the photorespiratory cycle has led to the improvement of photosynthesis and plant productivity. This has been achieved either by over-expressing photorespiratory proteins or by creating alternative glycolate catabolism routes within the chloroplast.

1 Increasing Agricultural Productivity In the past, the development of new breeding techniques and the green revolution enabled food production to mirror population growth but these advances have reached their limits and new strategies are required to feed the growing world population. A 25–70% increase in productivity is necessary to meet the predicted food requirements in 2050. This goal could be hampered by farmland losses, bio-economical requirements (such as feed for animals, bioenergy, and biopharmaceuticals) (Tilman et al. 2011), and the need to protect the environment by reducing pesticide and fertilizer uses as well as limiting greenhouse gas emissions (Sayer et al. 2013; Hunter et al. 2017). Future crop production will also be limited by extended periods of drought and high temperatures (Battisti and Naylor 2009) that are predicted from climate change models. Plant yield is determined by the efficiencies of light capture and conversion of intercepted light into biomass and then the proportion of biomass partitioned into harvested plant parts. Both light capture and biomass partitioning are near to theoretical expectations due to plant breeding over the past decades. The determinant that has not yet reached its biological limit is light conversion to biomass. Since this is mainly dependent on photosynthesis, it has become a target for improving yield potential (Long et al. 2006; Ort et al. 2015). It is known that energy from sunlight is lost for a number of reasons. Not all wavelengths of light can be absorbed by photosynthetic pigments, a proportion of light is either reflected by or transmitted through the leaves, photosynthetic photochemistry is not 100% efficient, and a number of primary metabolic pathways (including carbohydrate synthesis,

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photorespiration, and respiration) have a relatively high energy cost and/or lead to CO2 losses (Zhu et al. 2010). Knowledge and tools are now available to help achieve future global food sustainability by improving photosynthesis. Based on in silico modelling, potential bottlenecks related to key photosynthetic-related processes predicted to limit photosynthetic efficiency and biomass production were identified (Zhu et al. 2007, 2008), and targets to improve plant photosynthesis and productivity were selected, and some have been tested already. Amongst the principal limitations of efficient photosynthesis, plants absorb more light in full sunlight than they can use and they contain an inefficient ribulose-1,5-bisphosphate (RuBP) carboxylase/ oxygenase (Rubisco) carboxylating enzyme that has an extremely slow catalytic rate. Both the “dark” reactions (CO2 fixation by Rubisco, the regeneration of RuBP by the Calvin cycle and the production of starch and sugars) and the “light” reactions of photosynthesis (light absorption, photosynthetic electron transfer leading to the production of NADPH and ATP, as well as electrons for redox regulations of enzymes required for Calvin cycle functioning) contain potential targets for improvement (Long et al. 2006; Zhu et al. 2010; Raines 2011; Ort et al. 2015; Betti et al. 2016; Simkin et al. 2019).

2 A Brief Overview of How to Improve Photosynthesis Before focusing on the major topic of this chapter which is photorespiration and how it is being manipulated to favour photosynthesis and yield, a brief overview of current strategies targeting specific photosynthesis-associated processes to improve photosynthesis, crop yield, and biomass will be given. They can be divided into different categories depending on the physiological processes to be optimized and they will be briefly mentioned below, after which a number of tested targets will be described in more detail.

2.1

The Light Reactions

“Light reaction” strategies are mainly aimed at improving the absorption and utilization of light and they are associated with the concept of “smart canopies”: Designer plants that interact together at the canopy level to maximize light harvesting and biomass production per area of land (see Zhu et al. 2010; Ort et al. 2015). • Canopy optimization: The idea is to create plants with vertical leaves in the upper canopy where high light intensities prevail, and horizontal leaves within the canopy where light is low. This also requires a redistribution of Rubisco with differing properties where upper leaves contain Rubisco with a high catalytic rate,

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and lower leaves a Rubisco with a high CO2 specificity. A redistribution of antenna and reaction centre complexes is also needed with upper canopy leaves containing reduced light harvesting antenna systems and more reaction centres, and a reversed situation in lower canopy leaves. It might be advantageous to make upper canopy leaves lighter with less chlorophyll (Chl) while making lower leaves with more Chl and with far red-shifted absorption properties since lower canopy leaves receive more infra-red light and so this will help increase lightharvesting capacity. Such canopies would allow higher levels of photosynthesis to occur throughout the plant. • Photoprotection: When light absorption by photosynthetic antenna complexes exceeds photosynthetic electron transfer capacity (for example, in high light situations), excess excitation energy is dissipated as heat (qE) within a process called non-photochemical quenching (NPQ) (see Murchie and Ruban 2020). This involves conformational changes within the light harvesting antenna of PSII and requires a combination of a transmembrane proton gradient, the PSII subunit S (PsbS), and the xanthophyll cycle. Optimizing qE relaxation kinetics is important since photosynthetic efficiency decreases as a plant readjusts to low light intensities after periods of high light (see Kromdijk et al. 2016). This will be described further in Sect. 3.2 Photoprotection.

2.2

Improving the Dark Reactions

“Dark reaction” strategies are mainly aimed at improving the capacity of Rubisco to fix CO2. Rubisco is an inefficient enzyme (Carmo-Silva et al. 2015) with a low kcat for CO2 and so plants produce extremely high amounts of Rubisco protein to sustain adequate photosynthesis but this represents a large N investment (Zhu et al. 2007). Furthermore, Rubisco has an oxygenase activity competing with the CO2 assimilatory carboxylase activity. This is the starting point for an energy consuming metabolic process called photorespiration, the major topic of this chapter. • Improving Rubisco: This includes the identification of natural Rubisco forms or engineered Rubisco with kinetic properties that improve carboxylation rate and reduce oxygenase activity (Parry et al. 2007). The improvement of Rubisco activation could also help increase crop productivity (Carmo-Silva et al. 2015). • CO2 concentrating mechanisms (CCM) (see Hennacy and Jonikas 2020): This involves creating plants that can substantially increase CO2 concentrations in the vicinity of Rubisco thus improving its carboxylation activity. One strategy is based on cyanobacterial CCMs and requires the engineering of active bicarbonate pumps, carbonic anhydrases, and carboxysome structures in C3 plants. However, many proteins are required to form carboxysomes and active pumps and therefore it is a high-risk strategy. Another excessively challenging strategy is to express a C4 photosynthetic pathway in C3 plants by manipulating both anatomical and biochemical traits to introduce a Kranz anatomy and specific enzymes. If

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successful, a functional CCM in C3 plants would eventually allow endogenous Rubisco to be replaced by a Rubisco with a lower CO2 affinity, but a higher kcat (Zhu et al. 2004). This strategy would eventually require lower amounts of Rubisco and thus improve N-use-efficiency (NUE). Further details concerning recent advances in engineering CCM mechanisms into C3 plants are given below in Sect. 3.3 CO2 concentrating mechanisms. Mesophyll Conductance: This targets components involved in CO2 diffusion into (stomatal conductance) and within the leaf to improve CO2 availability for Rubisco. RuBP Regeneration: RuBP limitations can be lowered by manipulating ratelimiting Calvin cycle enzymes (see Simkin et al. 2019) and details concerning recent advances in this area are given below in Sect. 3.4 RuBP regeneration. Photorespiratory bypasses: To date, this has involved the engineering of artificial glycolate catabolism pathways in the chloroplast to lower the energy cost of photorespiration by removing N losses and limiting C-losses (for example, see South et al. 2018). Section 4.6 is focused on this topic. Source-sink relationships: The idea is to improve the export of photosynthetic products from source leaves to sink organs. The build-up of carbohydrates in the leaf can feed-back inhibit photosynthesis as seen by photosynthetic acclimation under elevated CO2 conditions (Moore et al. 1999).

It is recommended to check out Ort et al. 2015 for an interesting perspective about improving photosynthetic efficiency and performance by redesigning plant systems at various scales to improve plant yield. These designs range from rather straightforward modifications, already supported by a proof-of-concept, to substantial conceptual changes that might become possible 1 day with the development of synthetic biology. A number of review papers are available that describe and discuss specific strategies to improve photosynthesis (examples include Zhu et al. 2010; Maurino and Peterhansel 2010; Raines 2011; Maurino and Weber 2013; Betti et al. 2016; Maurino 2019; Simkin et al. 2019; Baslam et al. 2020). Finally, on-going research projects aimed at improving photosynthesis using the strategies mentioned above can be visited at: https://ripe.illinois.edu/ (RIPE), https://www.capitalise.eu (Capitalise), http://www.photoboost.org/ (Photoboost), https://gain4crops.eu/ (Gain4crops) and https://c4rice.com/ (C4rice).

3 On-going Strategies for Improving Photosynthesis: Light Capture, Photoprotection, CO2 Concentrating Mechanisms, and RuBP Regeneration Before focusing on photorespiration, recent advances within a selection of current targets for improving photosynthesis will be described. While some of this work is still on-going, some strategies have been quite successful whereas others have not yet produced the expected improvements.

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Light Capture

It has been postulated that low Chl containing leaves could be beneficial for overall canopy photosynthesis. The effects of reduced Chl on leaf and canopy photosynthesis were measured in the field using two Chl-deficient soybean (Glycine max) mutants (Y11y11 and Y9y9) and compared to the wild-type (WT) cultivar. Despite a >50% reduction of Chl, biomass accumulation and yield over the complete growing period was hardly impacted whereas photosynthetic efficiency (leaf-level photosynthesis per absorbed photon) appeared to be dependent on the time during the growing season (Slattery et al. 2017). Therefore, this study was unable to confirm an earlier published work where the Y11y11 mutant significantly out-yielded WT plants (Pettigrew et al. 1989). The strategy of reducing leaf Chl amounts was evaluated further using 67 soybean accessions with large variations in leaf Chl content including the soybean Y11y11 mutant. Leaf Chl amounts, leaf optical properties, and photosynthetic capacities were measured and modelled simulations suggested that canopy photosynthesis did not increase when Chl was reduced because of increased reflectance and a non-optimal N distribution within the canopy (Walker et al. 2018). Chl reduction did not improve net canopy CO2 fixation capacity although higher net photosynthetic rates were suggested in lower canopy layers. Overall, photosynthesis was maintained in Chl-deficient canopies with a 9% saving in leaf N (Walker et al. 2018).

3.2

Photoprotection

Photosynthesis and crop productivity have been improved under fluctuating light conditions by accelerating leaf recovery from qE-associated NPQ photoprotection. Under full sunlight, leaves dissipate excess absorbed light energy as heat but when leaves become shaded, energy dissipation continues for many minutes and a lower photosynthesis is maintained. It had been calculated that the lag between changes in NPQ and irradiance can lead to a 20% yield penalty. By bioengineering tobacco (Nicotiana tabacum) to bring about an accelerated response to natural shading events, an increase of leaf net CO2 uptake and biomass production of up to 15% was observed under fluctuating light conditions. This was achieved by targeting the xanthophyll cycle by over-expressing Arabidopsis thaliana violaxanthin de-epoxidase, zeaxanthin epoxidase, and PsbS in tobacco leaves. This led to an accelerated attenuation of NPQ after transfer from high light to shade and gave a more rapid restoration of maximum CO2 assimilation efficiency (Kromdijk et al. 2016).

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CO2 Concentrating Mechanisms Incorporating a C4 Plant CMM into a C3 Plant

Nature has evolved several strategies to suppress the Rubisco oxygenation reaction by sequestering the enzyme into compartments that can concentrate CO2. This includes C4 plants that have different biochemical and anatomical properties when compared to C3 plants. C4 leaves contain two distinct layers of photosynthetic tissues (the so-called Kranz leaf anatomy) where mesophyll cells are in contact with atmospheric CO2 whereas bundle sheath (BS) cells are less CO2 permeable. Bicarbonate is assimilated in mesophyll cells via phosphoenolpyruvate (PEP) carboxylase (PEPc) and oxaloacetate (OAA) is produced which is then converted to a more stable 4C organic acid (malate or aspartate depending on the type of C4 plant). After diffusion to BS cells, CO2 is produced close to Rubisco by the decarboxylation of the mobile C4 acid. A coordinated international effort to introduce C4 metabolism into rice has begun to give some interesting results (see Hibberd et al. 2008; Von Caemmerer et al. 2012; Ermakova et al. 2020). To introduce Kranz anatomy into rice, vein spacing patterns must be altered so that leaf veins are closer together and chloroplast development in BS cells must be activated since they are non-photosynthetic in rice. However, the regulation of Kranz anatomy development in a C4 plant is still unknown and current work is aimed at identifying the regulatory genes in maize. Once identified, engineering in rice can begin. Recently it was found that BS chloroplast biogenesis was enhanced when the transcriptional activator, OsCGA1, was driven by a vascular specific promoter (Lee et al. 2021). Furthermore, a mutant screen of Setaria viridis (an NADP-malic enzyme (NADP-ME) type C4 monocot) has provided evidence that a functional suberin lamellae is an essential anatomical feature for efficient C4 photosynthesis in NADP-ME C4 plants like S. viridis (Danila et al. 2021). Manipulation of C4 pathway biochemistry is perhaps more straightforward because genes encoding C4 pathway enzymes and metabolite transporters are known. However, they must be turned on at the correct time, to the required level, and in specific cell types. It has been demonstrated that a promoter sequence of the C4-type PEPc gene from three different C4 plants can drive mesophyll-cell-specific reporter gene expression in rice (Gupta et al. 2020). Introducing C4 biochemistry into rice with a C3 anatomy is being carried out and a partial flux through the carboxylation part of NADP-ME C4 metabolism in transgenic rice has been demonstrated when transformed with maize NADP-ME, PEPc, NADPmalate dehydrogenase, and pyruvate phosphate dikinase (Lin et al. 2020). The expression of C4 photosynthesis enzymes (carbonic anhydrase, PEPc, NADPmalate dehydrogenase, pyruvate orthophosphate dikinase and NADP-ME from maize and driven by cell-preferential promoters) has also been achieved in rice using a single construct (Ermakova et al. 2021). Such encouraging results suggest that a functional C4 pathway will be 1 day achievable.

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Incorporating a Cyanobacterial CMM or a Green Algal CMM into a C3 Plant

An alternative approach to creating C4 photosynthesis inside a C3 plant is to copy a cyanobacterial CCM composed of bicarbonate transporters and a Rubiscocontaining proteinaceous compartment called a carboxysome (see Price et al. 2013). The cyanobacterial CCM is a system that generates a high HCO3 pool through the action of inorganic carbon transporters and CO2-converting complexes. Bicarbonate and RuBP both diffuse into the carboxysome where the bicarbonate is converted back to CO2 via a carboxysome localized carbonic anhydrase. To date, it has been demonstrated that β-carboxysome shell proteins can be assembled in tobacco (Nicotiana benthamiana) chloroplasts producing structures suggestive of self-assembled carboxysomes (Lin et al. 2014). The introduction of a functional CCM in C3 plants would allow native Rubisco to be replaced with the cyanobacterial enzyme that has a higher catalytic rate although at the expense of a lower affinity for CO2 and a lower specificity factor when compared to plant Rubisco (Price and Howitt 2014). Simplified carboxysomes formed after the expression of two key α-carboxysome structural proteins have also been successfully produced in tobacco chloroplasts where the endogenous Rubisco large subunit gene was replaced by cyanobacterial form-1A Rubisco large and small subunits. Albeit demonstrating the formation of fully functional α-carboxysomes within chloroplasts using this reduced gene set, the tobacco plants had poor growth and a low CO2 assimilation rate. Autotrophic growth was possible only at elevated CO2 (Long et al. 2018). Attempts to increase tobacco plant photosynthetic efficiency and biomass by expressing and integrating individual components of a Chlamydomonas reinhardtii CCM (either carbonic anhydrase CAH3 or the bicarbonate transporter LCIA) into their chloroplasts demonstrated that biomass production could be increased in this way. This suggests that combining multiple CCM components could further increase the productivity and yield of C3 crops (Nölke et al. 2019).

3.4

RuBP Regeneration

The accelerated rate of Rubisco-catalysed carboxylation at current atmospheric CO2 levels (>400 ppm in 2021) has led to a kinetic limitation in the regeneration of RuBP, the CO2 acceptor molecule, under non-limiting light conditions. This problem is expected to become more important in the future due to the continual increase in atmospheric CO2 levels, a hallmark of the Anthropocene epoch and the significant impact of man on the climate and ecosystems of our planet. A proven strategy to limit this limitation has been the over-expression of rate-limiting enzymes of the Calvin cycle. Improvement of photosynthesis and yield using this approach has been reviewed recently (see, for example, Simkin et al. 2019; Baslam et al. 2020) and therefore only a brief account with be given. In 2005, it was shown that when sedoheptulose-1,7-bisphosphatase (SBPase) activity was increased in transgenic

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N. tabacum plants expressing Arabidopsis SBPase both photosynthesis and growth were stimulated (Lefebvre et al. 2005). This has held true in other plant species where over-expression (OE) of SBPase has led to plants exhibiting increased photosynthetic activities and biomass. This includes Arabidopsis thaliana (Simkin et al. 2017), tobacco (Lefebvre et al. 2005; Rosenthal et al. 2011; Simkin et al. 2015), tomato (Ding et al. 2016), and wheat (Driever et al. 2017). However, beneficial effects were often dependent on plant developmental stage and/or growth conditions. For instance, higher photosynthetic rates were only seen in young tobacco leaves and they were found under short day periods and low light intensities (Lefebvre et al. 2005). The OE of cyanobacterial and green algal enzymes in higher plants has also been studied. OE of Chlamydomonas reinhardtii SBPase or cyanobacterial fructose1,6-bisphosphatase (FBPase) led to increases in photosynthesis and biomass (Tamoi et al. 2006). A cyanobacterial bi-functional SBPase/FBPase enzyme has been overexpressed in tobacco (Miyagawa et al. 2001), lettuce (Ichikawa et al. 2010), and soybean (Köhler et al. 2017) with all transformed plants showing improved photosynthetic CO2 assimilation rates and biomass production. When Arabidopsis fructose bisphosphate aldolase (FBPA) was over-expressed in the photosynthetic tissues of Arabidopsis using a Rubisco small subunit 2A promoter, similar increases in photosynthesis, dry weight (DW), and seed yield occurred (Simkin et al. 2017). Perhaps surprisingly, Arabidopsis plants over-expressing both SBPase and FBPA exhibited no additional increases in their maximal CO2 assimilation rate, DW, and seed yield when compared to lines over-expressing the individual transgenes (Simkin et al. 2017).

4 Photorespiration This chapter will now focus on photorespiration (see Bauwe et al. 2010; Eisenhut et al. 2019) as a target for improving plant performance. Before describing the photorespiratory cycle, its regulation, the use of photorespiratory mutants, and how photorespiration has been manipulated to improve photosynthesis, a concise explanation as to why photorespiration is bad for photosynthesis and crop yield will be given.

4.1

Why Is Photorespiration Bad for Photosynthesis and Crop Yield?

Photorespiration is essential for C3 (and C4) plant growth in air containing current CO2 concentrations (normal air). However, this high flux metabolic process has an energy cost estimated to reduce the theoretical C3 photosynthetic efficiency by 48% at 30 C and an atmospheric CO2 concentration of 0.038% (Zhu et al. 2008). In

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normal air at 25 C, Rubisco undertakes approximatively 2 oxygenation reactions for every 5 carboxylation reactions and the photorespiratory cycle requires 3.5 ATP and 2 NADH equivalents per oxygenation reaction to process the 2-phosphoglycolate (2PG) and 3-phosphoglycerate (3PGA) into RuBP (see Foyer et al. 2009; Walker et al. 2016). The energetic demands calculated for photorespiration suggests that 32% of total ATP and 28% of total NADH equivalents are consumed in an illuminated C3 leaf at 25 C and 0.035% CO2 containing air (Walker et al. 2016). Of course, this will depend on environmental conditions that change chloroplast O2 and CO2 concentrations such as temperature. In the USA, photorespiration has been estimated to reduce wheat and soybean yields by 20% and 36%, respectively, and this is predicted to increase with expected higher temperatures and longer drought periods due to climate change (Walker et al. 2016). On the other hand, higher CO2 concentrations should improve photosynthesis and C3 plant growth as photorespiration will be reduced due to an altered competition between O2 and CO2 at the active site of Rubisco in favour of CO2 and a reduced waste of Calvin cycle flux to produce RuBP for Rubisco oxygenase activity (see Ainsworth and Long 2005 who reviewed 15 years of free-air CO2 enrichment data). That said, photorespiration will continue to negatively impact crop yield under predicted future climates even though models suggest a 12–55% improvement in photosynthesis under different climate change scenarios in the absence of photorespiration (Walker et al. 2016). However, models predict photorespiratory yield penalties of 8% and 19% (for wheat and soybean, respectively) will occur at 0.1% CO2 and with a 3.7 C increase in temperature (Walker et al. 2016). In conclusion, as both atmospheric CO2 and temperature levels increase with the progression of climate change, crop yield losses due to photorespiration will remain significant. It is therefore not surprising that re-engineering the photorespiratory cycle has become a wide-spread strategy to improve photosynthesis and yield in both model plants and crops (see, for example, Hagemann and Bauwe 2016; South et al. 2018; Eisenhut et al. 2019), even though it is tightly embedded in a complex network of metabolic processes (Hodges et al. 2016) (see Fig. 1). That said photorespiration is believed to be an energy sink that can limit over-reduction of the photosynthetic electron transfer chain and thus protect against photoinhibition, especially under stress conditions that lead to stomatal closure (drought, salinity) and a reduction of photosynthetic CO2 assimilation. It also produces glycine that can be used to make glutathione which is involved in the protection against reactive oxygen species that are often generated when plants are exposed to environmental stresses (see Wingler et al. 2000; Voss et al. 2013). A functional photorespiratory cycle is also important for plant tolerance against biotic stress, as seen from the reduced resistance to pathogens of certain photorespiratory mutants (Moreno et al. 2005; Rojas et al. 2012).

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Chloroplast

PHOTOSYNTHESIS

NITROGEN & AMINO ACID METABOLISM

Calvin Cycle

CO2

RuBP

ATP

O2

Rubisco 3-PGA GLYK1 Glycerate

GLN

T

2PG

NH4+ GS2

ADP

PGLP1

GLU

ADP

DiT2

Fd-GOGAT

Glycolate 2OG

Mal

Fdred

Mal

Fdox

ATP

DiT1 PLGG1

BASS6

Glycerate HPR1

Glycolate NAD+ GOX1/2 NADH

Hydroxypyruvate

O2

REDOX HOMEOSTASIS & SIGNALING CAT2

H2O2

O2 H2O

Glyoxylate GLU GGAT1

SGAT1

2OG

Serine

Serine

Glycine

AMINO ACID METABOLISM SHMT1

Peroxisome CO2

Glycine

5,10-CH2-THF

SULPHUR METABOLISM

THF

C1 METABOLISM

P T GDC L H

NAD+

NH4+

NADH

Mitochondrion

BOU

Fig. 1 The photorespiratory cycle and its interactions with other metabolic processes. Rubisco oxygenase activity produces 2PG that is transformed to 3PGA by the action of eight core photorespiratory enzymes. The photorespiratory cycle takes place in four cell compartments: chloroplasts, peroxisomes, mitochondria, and the cytosol. It interacts with photosynthesis, nitrogen and amino acid metabolisms, redox homeostasis and signalling, C1 and sulphur metabolisms. BASS6 plastidial glycolate transporter, CAT2 catalase 2, DiT1 plastidial 2OG/malate transporter, DiT2 plastidial glutamate-malate transporter, Fd-GOGAT ferredoxin-dependent glutamate synthase, GGAT1 glutamate glyoxylate aminotransferase 1, GDC glycine decarboxylase complex (composed of P, T, L, H subunits), GLYK1 glycerate kinase 1, GOX1/2 glycolate oxidase 1/2, GS2 plastidial glutamine synthetase, HPR1/2 hydroxypyruvate reductase 1/2, PGLP1 2PG phosphatase 1, PLGG1 plastidial glycolate/glycerate transporter, Rubisco RuBP carboxylase/oxygenase, RuBP ribulose-1,5-bisphosphate, SGAT1 serine glyoxylate aminotransferase 1, SHMT1 serine hydroxymethyltransferase 1, THF tetrahydrofolate, 2OG 2-oxoglutarate, 2PG 2-phosphoglycolate, 3PGA 3-phosphoglycerate

4.2

What Is Photorespiration?

Photorespiration is a high flux metabolic pathway, essential to all O2-producing photosynthetic organisms living in aerobic environments. It is often seen as a closed metabolic cycle that removes and recycles toxic 2PG to make 3PGA to fuel the Calvin-Benson cycle but this view is over-simplified since this C2-cycle interacts with several primary metabolic pathways. These include photosynthesis, N-assimilation, amino acid metabolism, C1 metabolism, sulphur metabolism, the Krebs cycle, respiration, cell redox balance, and signalling (see Fig. 1, and Eisenhut

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et al. 2019). Indeed, as mentioned below in Sect. 4.3, a dysfunctional photorespiratory cycle leads to a reduction of photosynthetic CO2 assimilation and an increase in NPQ when photorespiratory mutants are transferred from high CO2 (low photorespiration) to normal air (see, for example, Dellero et al. 2015, 2016a). The accumulation of photorespiratory 2PG inhibits the Calvin cycle and reduces starch production (Flügel et al. 2017). A reduction in photorespiratory activity under elevated CO2 has been shown to reduce nitrate uptake and assimilation (Rachmilevitch et al. 2004; Bloom et al. 2010). Photorespiratory ammonium is re-assimilated by the glutamine synthetase/glutamine oxoglutarate aminotransferase (GS/GOGAT) cycle in the chloroplast. The importance of plastid GS2 in photorespiratory ammonium assimilation and ferredoxin (Fd)-GOGAT in Glu production for both GS2 activity and photorespiratory cycle aminotransferase activity is highlighted by the respective mutant phenotypes (Somerville and Ogren 1980a; Wallsgrove et al. 1987; Coschigano et al. 1998; Ferreira et al. 2019). Photorespiration is a major source of leaf Gly and Ser production and their levels are modulated with photorespiratory flux as seen, for instance, under low 0.01–0.02% CO2 levels (Dellero et al. 2021). It was also observed that glutamate glyoxylate aminotransferase (GGAT) activity is important for Ser homeostasis (Dellero et al. 2015). Photorespiration is also linked to C1 metabolism because tetrahydrofolate (THF) is needed for Gly decarboxylase (GDC) activity. Indeed, the accumulation of extremely high Gly levels and severe developmental phenotypes were observed in air-grown Arabidopsis 10-formyl tetrahydrofolate [THF] deformylase mutants (Collakova et al. 2008). A link with sulphur metabolism has been identified during the phenotypic characterization of a bou mutant that exhibits a low GDC activity and lacks a mitochondrial carrier of unknown function. There was also a down-regulation of Calvin Cycle and N-assimilation genes, whereas key enzymes of glycolysis and the TCA pathway were up-regulated and the accumulation of sugars and TCA intermediates was modified (Samuilov et al. 2018). Photorespiration produces NADH in mitochondria that can be used for respiration but if NADH accumulates this can lead to the inhibition of TCA cycle dehydrogenases (Tcherkez et al. 2008; Nunes-Nesi et al. 2013). Photorespiratory glycolate oxidase (GOX) produces H202, an important redox signal and component of cell redox homeostasis (Foyer and Noctor 2020), and low GOX activities reduce plant resistance to pathogens (Rojas et al. 2012). These examples clearly highlight the complex interactions between the photorespiratory cycle and other plant primary metabolisms that could hinder the successful re-engineering of photorespiration to improve plant performance. As stated several times already, photorespiration begins when Rubisco oxygenase activity produces a molecule of 2PG (and a molecule of 3PGA) from the oxygenation of RuBP. 2PG is toxic to the cell because it inhibits the Calvin-Benson cycle enzymes triosephosphate isomerase (TPI) and SBPase and the glycolytic enzyme phosphofructokinase (PFK) (Anderson 1971; Kelly and Latzko 1976; Flügel et al. 2017). Therefore, it must be removed and its carbon salvaged as 3PGA by the photorespiratory cycle, a pathway that spans four cell compartments: chloroplasts, peroxisomes, mitochondria, and the cytosol (see Fig. 1). The photorespiratory cycle recovers three quarters of the carbon contained in two molecules of 2PG by making

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one 3PGA molecule. It is composed of eight core enzymes excluding Rubisco. First, 2PG is dephosphorylated to glycolate by phosphoglycolate phosphatase (PGLP, Schwarte and Bauwe 2007) in the chloroplast. Glycolate is then exported by two transporters, PLGG1 (a glycolate-glycerate transporter, Pick et al. 2013) and BASS6 (a glycolate transporter, South et al. 2017) and oxidized to glyoxylate in peroxisomes by GOX (Dellero et al. 2016a, b) that also produces a molecule H202 which is subsequently removed by the action of a catalase. In Arabidopsis leaves this is carried out by CAT2 (Queval et al. 2007). Peroxisomal glyoxylate is then converted to Gly by a glutamate glyoxylate aminotransferase (GGAT, Igarashi et al. 2006; Liepman and Olsen 2003; Dellero et al. 2015) that also produces 2-oxoglutarate (2OG) from Glu. This reaction links photorespiration to the chloroplast GS2/FdGOGAT cycle. Glycine is imported into mitochondria where two Gly molecules are converted to one molecule of Ser by the joint action of GDC and serine hydroxymethyltransferase (SHMT). GDC catalyses the oxidative decarboxylation and deamination of Gly and generates CO2, ammonium and NADH. The remaining methylene carbon of Gly is transferred to THF to form methyl-THF that reacts with a second Gly in a reaction catalysed by SHMT to form Ser. GDC is a multimeric complex composed of four subunits (H, P, T and L). H is a lipoamide-containing protein that has a pivotal role in the complete sequence of GDC reactions as it undergoes a cycle of reductive methylamination (catalysed by the P-protein), methylamine transfer (catalysed by the T-protein), and electron transfer (catalysed by the L-protein). The P-protein is responsible for the decarboxylation of Gly and the liberation of CO2, the T-protein produces ammonium and methyl-THF and the L-protein generates NADH from NAD (see Douce et al. 2001). Serine then enters the peroxisome to be converted to hydroxypyruvate (with the production of Gly) by serine glyoxylate aminotransferase (SGAT, Liepman and Olsen 2001) and subsequently to glycerate by hydroxypyruvate reductase (HPR, Timm et al. 2008, 2011) that oxidizes NADH to NAD. Glycerate is imported into the chloroplast via PLGG1 where it is converted to 3PGA by glycerate kinase (GLYK, Boldt et al. 2005). The complete photorespiratory cycle and interacting metabolisms are shown in Fig. 1.

4.3

Regulation of the Photorespiratory Cycle

To date, little is known about the regulation of the photorespiratory cycle. That said, recent reviews dealing with the redox regulation of photorespiration (Keech et al. 2016) and the role of regulatory proteins and metabolites (Timm and Hagemann 2020) are available. Advances in proteomics have led to the identification of a large number of peptides containing putative post-translational modifications (PTM) including protein phosphorylation, ubiquitination, acetylation, and different redox modifications such as nitrosylation, glutathionylation, methionine oxidation, cysteine sulfenylation, and reversible cysteine oxidation. Potential PTMs associated with photorespiratory enzymes can be found by examining public databases that include PhosPhAt (https://phosphat.uni-hohenheim.de/), Athena (http://athena.proteomics.

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wzw.tum.de) and the Plant PTM viewer (https://www.psb.ugent.be/webtools/ptmviewer/). Certain data concerning the phosphorylation and redox regulation of core photorespiratory enzymes have been extracted from these three databases and presented in Table 1. It can be seen that photorespiratory enzymes are associated with many putative phosphorylation sites (see Table 1 and Hodges et al. 2013). All of them appear to undergo protein phosphorylation at multiple phosphorylation sites (Table 1). However, these potential phosphorylations have not been confirmed either in vitro or in planta by non-proteomic approaches and their roles remain unknown. The production and characterization of phospho-mimetic recombinant proteins have been used to study the impact on the enzyme kinetics of several photorespiratory enzymes. In such experiments, identified phospho-amino acids were replaced by a negatively charged Asp molecule to mimic the negative charge of the phosphate group. It was found that Arabidopsis HPR1-T335D (where Thr335 was replaced by an Asp) exhibited a lower NADH-dependent HPR activity and an improved NADPHdependent activity. When introduced into the Arabidopsis hpr1-1 mutant line under the control of an SHMT1 promoter, HPR1-T335D was unable to fully complement the hpr1-1 growth phenotype in normal air. HPR1-T335D-containing hpr1-1 plants remained smaller and had lower photosynthetic CO2 assimilation rates. Rosette leaf metabolite analyses of the transformed lines suggested that there were subtle perturbations in photorespiratory cycle functioning when compared to WT plants and HPR1-T335A (where Thr335 was replaced with an Ala, as a control) expressing lines (Liu et al. 2020). In a similar approach, the Arabidopsis shm1-1 mutant was complemented with a phospho-mimetic SHMT1-S31D protein to generate Compl-S31D lines. In response to either a salt or a drought stress, Compl-S31D lines showed a lower tolerance when compared to WT and the control Compl-S31A plants. The poorer salt sensitivity of Compl-S31D plants appeared to correlate with their lower SHMT1-S31D protein amounts and SHMT activities that led to Pro under-accumulation. The phospho-mimetic S31D mutation of Compl-S31D lines also led to a reduction in salt-induced and ABA-induced stomatal closure (Liu et al. 2019). Several putative GOX phosphorylation sites (Thr4, Thr158, Ser212, and Thr265) were tested using recombinant Arabidopsis GOX1 and GOX2, and maize GO1 and three different substrates (glycolate, lactate and 2-hydroxy-octanoate) (Jossier et al. 2020). The phosphopeptides had been identified either in PhosPhAt or in the literature (Thr4 (Reiland et al. 2009 and PhosPhAt), Thr158 (PhosPhAt, Umezawa et al. 2013; Choudhary et al. 2015; Abadie et al. 2016), Ser212 (Umezawa et al. 2013 and PhosPhAt) and Thr265 (Aryal et al. 2012)). Several phospho-mimetic mutations (T4D, T158D, and T265D) led to a severe inhibition of recombinant enzyme activity without altering the Km values for the tested substrates. This was associated with a loss of flavin mononucleotide (FMN) cofactor within the T4D and T158D proteins. Phospho-dead versions exhibited different modifications according to the phospho-site and/or the GOX mutated. All T4V and T265A enzymes had kinetic parameters similar to WT GOX, all T158V proteins showed reduced activities while S212A and S212D mutations had no effect on GOX1 activity but GOX2 and GO1 activities were 50% reduced (Jossier et al. 2020). Taken together, these

S140 S141 S21 S30 S32 S121 S141 S142

S44 S47 S1008

S19 S190 S211 T318 S319

S190 T318 S319 S426

S140 S141

S141 S142

GDC-P2 At2g26080

GDC-L1 At1g48030

GDC-L2 At3g17240

GDC-H1 At2g35370

S19 S31 S190 S319

S46 S47

S48 S69 S85 S476

S267 Y557 S1002

GDC-P1 At4g33010

S393 S268 S330 S331

S174 S268 S330 S331 S337 S339 S393

S21 S30 S121 S142

S120 S140 S141

S190 T318 S319

S19 S31 S190 T318 S319

S46 S47 S1008

T49 T92 S476 S1002

S174 S268 S331 S337 S393

S275 T399

S275 T399

Y8 S275 T339

S201 S212 T355 T360 S364 T158 S201 S212

S197 S201 S364 T61 T355 T360

T4 T155 T158 T355

S38 T122 S356

S212

S121 T122 S356

T322 S356

GDC-T At1g11860

PGLP1 At5g36700 GOX1 At3g14420 GOX2 At3g14415 GGAT1 At1g23310

C372 C483

C372

C98 C245 C463 C777 C943 C251 C783 C949

C75 C151

C226 C377 C382 C417

C239 C320

NO

PTM

PhosPhAt

Athena

REDOX

Phosphorylation

Table 1 Potential phosphorylated and redox modified amino acids of photorespiratory core enzymes

N195

N195

GO

C87 C372

C463 C777 C943 C783 C949 C1028 C87 C372

C149 C226 C239 C417 C75

SO

C159

C71 C82 C87 C372 C71 C82 C87 C372 C158

C783

C75 C88 C151 C276 C777

C149

CYS OX

(continued)

M150

M149

M423 M437

M423

M125 M869

M120 M863

M163 M367

M106

MET OX

Photorespiration and Improving Photosynthesis 185

S12 S13 S24 S26 Y28 S232 T348 S37 S6 S228 S229 S365 T41 S45

S12 S13 S26 Y28 S31 S34 T46 T470

S37 S215 S387 T388

S178 S229

S45 T222 T223

S45

S228 S229 S365

S37 S215

S12 S13 S26 T46 S232

C271 C38

C142 C297

C125

GO

C86

SO

C181

CYS OX

M261 M262

MET OX

Data was retrieved from PhosPhAt, Athena, and Plant PTM Viewer (PTM) NO nitrosylation, GO glutathionylation, SO sulphenylation, CYS OX reversible cysteine oxidation, MET OX oxidized methionine. Enzyme abbreviations are given in the text. Note that PGLP1 is also annotated as At5g36790

GDC-H3 At1g32470 SHMT1 At4g37930 SGAT At2g13360 HPR1 At1g68010 HPR2 At1g79870 GLYK At1g80380

NO

PTM

PhosPhAt

Athena

REDOX

Phosphorylation

Table 1 (continued)

186 M. Hodges

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observations suggest that phosphorylation of photorespiratory enzymes has the potential to modulate their activities and impact plant growth and response to abiotic stresses. Proteomics have also indicated that photorespiratory enzymes can be redox regulated and acetylated. GDC-P, GDC-H, GDC-T, GDC-L, and SHMT1 were found in analyses aimed at identifying thioredoxin (Trx)-regulated proteins in mitochondria isolated from pea and spinach leaves, and potato tubers using Trx-affinity chromatography and mass spectroscopy (Balmer et al. 2004). In a similar study using Arabidopsis extracts, GDC-H1 was identified (Marchand et al. 2004). Arabidopsis PGLP1 was found to interact with two chloroplastic redox actors, a 2-Cys-peroxiredoxin (2-Cys PRX) (Cerveau et al. 2016) and the NADPH-Trx reductase NTRC (González et al. 2019). The oxidation of 3,845 cysteines within the proteome of Phaeodactylum tricornutum was quantified and PGLP, GDC-P, and SHMT were amongst the identified H202-sensitive proteins (Rosenwasser et al. 2014). A Lys acetylome of Arabidopsis mitochondrial proteins identified SHMT1, and SHMT2, GDC-H1, GDC-P1, GDC-P2, and GDC-T subunits (König et al. 2014) whereas all core photorespiratory enzymes are found annotated as Lys acetylated in Plant PTM Viewer. A modified biotin-switch method was used to detect Arabidopsis proteins modified by S-sulfhydration under physiological conditions and this led to the identification of GGAT1, GDC-L1, GDC-H1, and SHMT1 (Aroca et al. 2015). A site-specific nitrosoproteomic approach allowed the identification of 1,195 endogenously S-nitrosylated peptides in 926 proteins from Arabidopsis thaliana including nitrosylated HPR1 and PGLP1 (Hu et al. 2015). Arabidopsis PGLP1 was also identified in the guard cell nitrosoproteome after flg22treatment (Lawrence et al. 2020). A site-specific nitrosoproteomic approach allowed the identification of 1,195 endogenously s-nitrosylated peptides in 926 proteins from Arabidopsis thaliana including C320-nitrosylated PGLP1 (Hu et al. 2015). On the other hand, when genomes of nine representative model species from streptophyte algae to angiosperms were analysed, no photorespiratory enzymes were identified in the plastid glutathione-dependent redox network (Müller-Schüssele et al. 2021). Peroxisomal GOX1 and GOX2 are both annotated as glutathionylated in the plant PTM viewer (Table 1). The impact of mitochondrial Trx (Trxo1 and Trxh2) on photorespiration has been studied (Reinholdt et al. 2019; Da Fonseca-Pereira et al. 2020). Combining in vitro enzymatic activity measurements and metabolomics, a redox-regulation of GDC-L activity by either a dithiothreitol treatment or by an NTRA-TRXo1 or NTRATRXh2 system were observed, that led to a reduced activity in vitro (Reinholdt et al. 2019; Da Fonseca-Pereira et al. 2020). However, single trxo1 and trxh2 T-DNA mutants did not display a growth phenotype, although there was evidence of altered photorespiration based on Gly accumulation. In vitro studies of recombinant GDC proteins revealed that Trxo1 and Trxh2 modulated the activity of mitochondrial lipoamide dehydrogenase (GDC-L) (Reinholdt et al. 2019; Da FonsecaPereira et al. 2020). A double mutant lacking TRXo1 and up to 95% of GDC-T protein exhibited a severe growth phenotype whereas the original gldt1 knockdown line showed only a mild growth reduction (Reinholdt et al. 2019). It was proposed

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that TRXo1 regulation of GDC was necessary to allow for the rapid induction of mitochondrial photorespiratory cycle steps to facilitate the light-induction of photosynthesis (Reinholdt et al. 2019). However, other regulatory processes or regulators cannot be excluded, and more work is still required to elucidate whether the functions of Trxo1 and Trxh2 are redundant or have specific targets controlled by specific environmental and physiological cues. Indeed Arabidopsis plants lacking TRXh2 also showed delayed seed germination, reduced respiration, impaired stomatal and mesophyll conductance without impacting photosynthesis, alterations in key metabolites of photorespiration, respiration and amino acid metabolism as well as a decreased abundance of SHMT and GDC-H and -L subunits (Da FonsecaPereira et al. 2020). This work has recently been reviewed in the wider context of Trx-mediated regulation of (photo)respiration and central metabolism (Da FonsecaPereira et al. 2021). A C4-specific Trx-dependent regulation of maize GLYK has also been reported (Bartsch et al. 2010). A short C-terminal extension containing two strategically positioned Cys residues forms a disulphide bridge at night when GLYK becomes less active, whereas this bridge is reduced by a chloroplastic Trx-f and full activity is restored in the light. When Arabidopsis leaf mitochondria were S-nitrosoglutathione (GSNO)-treated, the biotin-switch method coupled to nano-liquid chromatography and mass spectrometry allowed the identification of GDC-H1, GDC-L1/2, and GDC-P1/2 subunits as well as SHMT as either S-nitrosylated and/or glutathionylated (Palmieri et al. 2010). A GSNO treatment of a partially purified Arabidopsis GDC-P protein led to a 70% inhibition of GDC activity and showed multiple Cys glutathionylations rather than nitrosylations. A decrease in activity was also observed in the presence of sodium nitroprusside (a NO donor), thus suggesting that nitrosylation could also be responsible for GDC-P protein inhibition (Palmieri et al. 2010). Two independent studies with pea have also shown that several photorespiratory enzymes can be subject to S-nitrosylation. In a study of salt-stress and mitochondrial protein nitrosylation, GDC-P, GDC-T, GOX, and SHMT were identified (Camejo et al. 2013). When pea peroxisome proteins were treated with GSNO, HPR, GDC-L, GDC-H, SGAT, and GOX were found to be S-nitrosylated and this inhibited GOX activity (Ortega-Galisteo et al. 2012). It can be seen from these studies that when photorespiratory enzymes undergo a PTM (either phospho-mimetic, Trx-associated or S-nitrosylation) their respective activities are always reduced. Further work is required to validate the potential PTMs identified by proteomics (Table 1) and to understand the in planta roles of such PTMs. Perhaps in the future, verified PTMs could be manipulated to modify photorespiratory cycle flux and thus impact favourably plant metabolism and performance.

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4.4

189

Characterization of Photorespiratory Mutants

Photorespiratory cycle mutants have been identified in many plant species from plant models like Arabidopsis thaliana to crops including rice, barley, pea, and potato (Timm and Bauwe 2013). For the model C3 plant Arabidopsis thaliana, an almost complete set of genetically defined mutant lines (by chemical treatment using ethyl methanesulfonate (EMS), by the insertion of a T-DNA, and by the use of antisense and RNAi strategies) for core photorespiratory enzyme genes and for several transporter genes is now available (see Table 2). It should be noted that Table 2 only contains core photorespiratory enzyme mutants whereas mutants involved in “associated processes” such as ammonium assimilation can be found elsewhere (Timm and Bauwe 2013; Eisenhut et al. 2019). The characterization of mutants was primordial in identifying photorespiratory genes and highlighting the presence of redundant gene functions and compensatory pathways. Mutants have also indicated that photorespiration is important even in CCM-containing plants (Zelitch et al. 2009; Levey et al. 2019), cyanobacteria (Eisenhut et al. 2008), and green algae (Suzuki et al. 1990). Above all, the identification and characterization of photorespiratory mutants showed that it was not possible to improve plant performance by knocking out (or slowing down) the photorespiratory cycle. Indeed, mutations of photorespiratory core cycle genes are characterized by either lethality or stunted growth when grown under normal air although most of them become viable when grown under elevated CO2 conditions (see Fig. 2 and Table 2). This comportment has been described as “the photorespiratory phenotype” and it was used by Somerville and Ogren in the late 1970s and early 1980s to isolate the first photorespiratory mutants of Arabidopsis thaliana (see Somerville 2001). Indeed, to accomplish this they took advantage of the photorespiratory phenotype. EMS-treated Arabidopsis seeds were produced; they were germinated under high 1% CO2 conditions and then transferred to ambient air that led to leaf bleaching. Recovery under high CO2 was then carried out and this led to the identification of mutants affected in the following core photorespiratory functions: PGLP (Somerville and Ogren 1979), SGAT (Somerville and Ogren 1980b), SHMT (Somerville and Ogren 1981), and GDC (Somerville and Ogren 1982). This strategy also led to the identification of mutants lacking associated photorespiratory functions: Fd-GOGAT (Somerville and Ogren 1980a) and a plastid dicarboxylate transporter (Somerville and Ogren 1983). Since these pioneering experiments, photorespiratory mutants have continued to be isolated from a multitude of plant species (see Timm and Bauwe 2013) mainly by homology searches using model plant gene sequences but also more recently by co-expression analyses. This has highlighted distinct photorespiratory phenotypes according to the place of the protein within the cycle and this has often been studied by comparative analyses after transferring mutants from elevated CO2 to normal air (see, for example, Timm et al. 2012b; Timm and Bauwe 2013; Dellero et al. 2015, 2016a). The precise reasons for mutant-specific phenotypes are mostly unknown; however, they could be associated with photorespiratory cycle interactions with other metabolic pathways (as discussed

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Table 2 Arabidopsis thaliana photorespiratory genes and their corresponding mutant lines Arabidopsis locus At5g36700

Growth recovery % CO2 2

Mutant type/comment EMS T-DNA Antisense

Enzyme PGLP

Mutant pcoA pglp1-1

GOX

gox1–1

At3g14420

0.038

T-DNA

gox2-1

At3g14415

0.038

T-DNA

gox2-2

At3g14415

0.038

T-DNA

0.3

RNAi

gox1gox2 GGAT

aoat1-1 ggt1-1 ggt1-2

At1 g23310

0.3

T-DNA

GDC-T

gldt1-1

At1g11860

0.038

T-DNA KD & RNAi

GDC-P

gldp1-1

At4g33010

0.038

T-DNA

gldp2-2

At2g26080

0.038

T-DNA

Lethal

T-DNA/>2% CO2 does not recover mutant phenotype Proposed photorespiratory gene T-DNA

gldp11gldp2-2 GDC-L

No mutant lines mtlpd2

GDC-H

No mutant lines

SHMT

shm1-1 (shm) shm1-2

LPD1 At1g48030 LPD2 At3g17240 GDH1 At2g35370 GDH3 At1g32470 At4g37930

0.038

References Somerville and Ogren (1979) Schwarte and Bauwe (2007) Flügel et al. (2017) Dellero et al. (2016a, b) Rojas et al. (2012) Dellero et al. (2016a) Dellero et al. (2016a) Rojas et al. (2012) Dellero et al. (2016a) Igarashi et al. (2003) Dellero et al. (2015) Engel et al. (2008) Engel et al. (2007) Engel et al. (2007) Engel et al. (2007)

Lutziger and Oliver (2001)

Potential photorespiratory GDC-H genes 0.15–0.3

(EMS) T-DNA

Somerville and Ogren (1981) Voll et al. (2006) (continued)

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Table 2 (continued)

Enzyme

Mutant

shm2-2

SAGT

HPR

Arabidopsis locus

Growth recovery % CO2

Mutant type/comment

At5g26780

0.038

T-DNA

At2g13360

Lethal (soil) 1%

Viable in vitro 0.9% CO2 and sucrose EMS

hpr1-1 hpr1-2

At1g68010

0.3–1

T-DNA

hpr2-1 hpr2-2 hpr3-1 hpr3-2 hpr1-1hpr2-1

At1g79870

0.04

T-DNA

At1g12550

0.04

T-DNA

0.3–1

T-DNA

hpr1-1hpr3-1

0.3–1

T-DNA

hpr2-1hpr3-1

0.04

T-DNA

hpr1hpr2hpr3

0.3–1

T-DNA

shm1-2shm22 sat1 (agt1)

GLYK

glyk1-1

At1g80380

0.12–0.2

T-DNA

PLGG

plgg1-1

At1g32080

0.2

T-DNA

BASS6

bass6-1

At4g22840

0.2

T-DNA

BOU

bou-2

At5g46800

0.3

T-DNA/impaired GDC activity

References Engel et al. (2011) Engel et al. (2011) Engel et al. (2011) Somerville and Ogren (1980a, b) Liepman and Olsen (2001) Timm et al. (2008) Liu et al. (2020) (hpr1–1) Timm et al. (2008) Timm et al. (2011) Timm et al. (2008) Timm et al. (2011) Timm et al. (2011) Timm et al. (2011) Boldt et al. (2005) Pick et al. (2013) South et al. (2017) Eisenhut et al. (2013) Samuilov et al. (2018)

above, and Fig. 1). Interestingly, mutant phenotypes can also be modulated by environmental factors other than atmospheric CO2 levels, including photoperiod, light intensity, and pathogens. Photorespiratory core enzyme mutants have been classed into several categories based on the severity of their phenotypes in normal air (Timm and Bauwe 2013).

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Normal Air 0.038 % CO2

High CO2 Air 0.3% CO2

Wild-type Col-0

RNAi gox1gox2 (amiRgox1/gox2)

Fig. 2 The photorespiratory phenotype. The RNAi suppressed Arabidopsis thaliana gox1gox2 mutant (amiRgox1/gox2) shows a severe retarded growth phenotype in normal air (0.038% CO2) whereas this is absent when grown under high 0.3% CO2-containing air. This CO2-dependent phenotype is not observed with WT Arabidopsis Col-0 plants. This is an example of a photorespiratory phenotype. It should be noted that these photos were used in Dellero et al. (2016a)

However in this chapter, photorespiratory core enzyme mutants will be described in order of their appearance within the C2-cycle and this will be followed by known photorespiratory transporter protein mutants. PGLP1: Identification of the Arabidopsis photorespiratory PGLP gene was achieved by the characterization of plants with a T-DNA inserted at the At5g36700 locus. The mutant was not viable in normal air but grew better in 0.9% CO2-enriched air; however, it required 2% CO2 for a complete phenotypic complementation (Schwarte and Bauwe 2007). It was also shown that the high CO2requiring phenotype of the EMS-derived pcoA mutant (Somerville and Ogren 1979) was due to the aberrant splicing of At5g36700 pre-mRNA (Schwarte and Bauwe 2007). When the original pglp1 mutant line (pcoA) was transferred from high CO2 conditions to normal air, net CO2 assimilation decreased within minutes, while this was not observed in air containing 2% O2 (Somerville and Ogren 1979). Extremely low photosynthetic CO2 assimilation rates were also observed in pglp11 plants transferred to air (Timm et al. 2012b; Flügel et al. 2017). Radiolabelled 14 CO2 feeding showed that rosette leaf 2PG became highly labelled while glycolate,

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Ser, and Gly were far less labelled compared to the WT (Somerville and Ogren 1979). It was suggested that most of the properties of the pcoA mutant could be explained by the inhibitory effect of 2PG on TPI activity thus blocking the conversion of glyceraldehyde-3-phosphate (GAP) to dihydroxyacetone phosphate (DHAP) (Somerville and Ogren 1979). Leaf transpiration rates were also seen to be lower in pglp1-1 plants transferred to air from 1% CO2 when compared to WT leaves. Furthermore, leaf transpiration was higher in pglp1-1 plants under high CO2 conditions when compared to the WT. These observations suggest an effect of photorespiratory cycle functioning on stomatal movements (Eisenhut et al. 2017). Low or absent PGLP1 activities (using antisense lines and a T-DNA mutant, respectively) showed a modified C-allocation between RuBP regeneration and starch synthesis and this was attributed to 2PG inhibiting not only TPI but also SBPase (Flügel et al. 2017). The importance of removing toxic 2PG was also seen in CCM-containing photosynthetic organisms with limited photorespiration. PGLP RNAi lines of the C4 plant Flaveria bidentis showed a photorespiratory stunted growth phenotype when 40% increase of total biomass in field trials. AP3 either with or without the PLGG1 RNAi module increased leaf glyoxylate (6 to 7-fold) and pyruvate (around 4-fold) levels, and reduced Ser and glycerate amounts compared to WT plants, suggesting an altered endogenous photorespiratory cycle due to bypass pathway flux. AP3 plant lines also exhibited improved maximal rates of photosynthetic CO2 assimilation with increased maximum Rubisco carboxylation rates without alterations in photosynthetic electron transfer rates (South et al. 2019). AP3 (with RNAi PLGG1) tobacco lines were used to test their resilience to high (+5 C) temperatures in the field (Cavanagh et al. 2021). They produced 26% more total biomass than WT plants under hot conditions thus sustaining lower yield losses under the high temperature condition compared to WT tobacco.

4.6.3

A Cyanobacterial Glycolate Decarboxylation Pathway

When individual cyanobacterial glycolate decarboxylation pathway proteins were addressed to chloroplasts there was an improved biomass production in Arabidopsis thaliana (Bilal et al. 2019; Abbasi et al. 2021). A complete bypass would transform glycolate to glyoxylate to oxalate to formate and to CO2; however, this has not yet been tested. To date, transgenic Arabidopsis plants expressing either cyanobacterial

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GLCD1 (GlcDH) (GD), HDH (hydroxyacid dehydrogenase) (HD), or ODC (oxalate decarboxylase) (OX) alone, and a double transformed HDH::ODC (HX) line have been studied. Phenotypic characterization showed that the different transgenic lines showed similar improvements in developmental parameters. Rosette diameter of GD, HD, OX, and HX was 20%, 22%, 17%, and 16% higher and total leaf number was 32%, 35%, 37%, and 34% higher than WT plants after 32 days of sowing. They produced more cauline branches, and plants were higher when compared to the WT after 42 days of growth except for HX transgenic plants. Vegetative DW biomass was 43% (GD), 35% (HD), 42% (OX), and 36% (HX) higher than in the WT (Bilal et al. 2019). GD, HD, and OX lines were further analysed by Abbasi et al. (2021) and observed changes were more variable. Only GD plants exhibited a significant 16% increase in net photosynthesis rate compared to WT controls. Stomatal conductance and soluble sugars were found to be higher in GD and HD plants while starch levels were higher in all transgenic plants. GD, HD, and OX plants produced approximately 35% more biomass and a two-fold higher seed weight. Based on these promising results, it would be worthwhile to generate plants containing the complete cyanobacterial glycolate decarboxylation pathway.

4.6.4

An Alternative Peroxisomal Glyoxylate Metabolism Pathway

Not all attempts to generate photorespiratory bypasses have been success stories. To avoid photorespiratory ammonium release, an alternative peroxisomal glyoxylate metabolism pathway was designed and tested in tobacco (Carvalho et al. 2011). The idea was to generate plants containing E. coli genes encoding GCL and hydroxypyruvate isomerase targeted to peroxisomes. It was presumed that these enzymes would compete with photorespiratory aminotransferases that convert glyoxylate to Gly and in doing so reduce the production of GDC-derived ammonium. However, transgenic lines only contained GCL and they exhibited distinctive atmospheric CO2-dependent necrotic lesions close to their leaf veins that were only present in normal air. Peroxisomal GCL expression led to higher leaf Gln and Asn levels but less soluble sugars when compared to WT tobacco. To explain these observations, it was proposed that a diversion of glyoxylate away from Gly conversion produced a deleterious short-circuit of the photorespiratory N cycle (Carvalho et al. 2011).

5 The Future: Alternative Theoretical and On-Going Photorespiratory Bypasses In 2015, systems-modelling of three published photorespiratory bypass strategies (Kebeish et al. 2007; Maier et al. 2012; Carvalho et al. 2011) suggested that photosynthesis could be enhanced by lowering photorespiratory energy demands

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and by relocating photorespiratory CO2 release to chloroplasts (Xin et al. 2015). Models indicated that photorespiratory bypass benefits would be improved by increasing SBPase activity and/or increasing the flux through the alternative bypass. However, the effectiveness of such approaches would depend on the complex interactions between photorespiration and other metabolic pathways (Xin et al. 2015). So far, photorespiratory bypass strategies have been restricted to relatively simple modifications of plant metabolism that have taken into consideration some factors predicted to be beneficial from systems-modelling. Next generation solutions will probably require a major rewiring of plant central metabolism. The visionary Arren Bar-Even wrote that this could include shared-enzyme Rubisco catalysis, replacing Rubisco by alternative carboxylation reactions and/or the Calvin Cycle with alternative pathways, and engineering photorespiration bypass routes that no longer release carbon. Innovative engineering strategies will be required to achieve such metabolic routes (Bar-Even 2018). With this in mind, several on-going strategies and hypothetical solutions will now be briefly described. A synthetic photorespiratory bypass based on the prokaryotic 3-hydroxypropionate bi-cycle has been engineered into the model cyanobacterium, Synechococcus elongatus sp. PCC 7942, and tested (Shih et al. 2014). This cycle was designed to function both as a photorespiratory bypass and an additional CO2 fixing pathway. Bicarbonate is fixed to acetyl-CoA by a biotin-dependent acetylCoA carboxylase to form malonyl-CoA which is converted to propionyl-CoA by two further enzymatic steps. Propionyl-CoA and photorespiratory glyoxylate are then converted to β-methylmalonyl-CoA which is then converted to pyruvate and acetyl-CoA via four more enzymatic steps. In transformed cyanobacterial cells, the six introduced enzymes were shown to be active but no cell growth improvement was observed in normal air. However, bottlenecks were identified as targets for future bioengineering (Shih et al. 2014). Since pyruvate cannot be easily re-assimilated by the Calvin cycle, the utility of such a bypass has been questioned (Weber and Bar-Even 2019). The β-hydroxyaspartate cycle (BHAC) is a primary glycolate assimilation pathway in marine proteobacteria (Schada von Borzyskowski et al. 2019). Glycolate is first oxidized to glyoxylate which is further converted into OAA via the activity of four enzymes: aspartate glyoxylate aminotransferase, β-hydroxyaspartate aldolase, β-hydroxyaspartate dehydratase, and iminosuccinate reductase. This cycle allows the direct formation of a C4 compound (OAA) from glycolate without any C and N losses. This makes it more efficient than photorespiration and all of the in planta photorespiratory bypasses tested so far. A functional BHAC has been engineered into Arabidopsis thaliana peroxisomes of WT and ggt1–1 mutant plants to create a photorespiratory bypass independent of both 3PGA regeneration and photorespiratory decarboxylations (Roell et al. 2021). In planta BHAC activity was demonstrated by β-hydroxyaspartate formation under photorespiratory conditions. Ambient air-grown BHAC plants showed a 20% reduction of ammonium and they accumulated soluble amino acids involved in the urea cycle (Glu and ornithine) or dependent on OAA (Lys and Met). However, BHAC plants had reduced growth compared to WT plants in normal air with decreased rosette diameter (50%) and leaf

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area (70%) that probably reflected the 25–30% reduction of their maximal CO2 assimilation capacity. Inefficient OAA conversion appeared to limit the full potential of the BHAC plants. The next step is to design strategies that use BHAC-derived OAA to create a synthetic C4 cycle CCM in C3 plants (Roell et al. 2021). By developing kinetic-stoichiometric models, promising routes to assimilate photorespiratory 2PG into the Calvin Cycle without C-losses have been identified (Trudeau et al. 2018). Glycolate reduction to glycolaldehyde appeared an interesting route but it did not occur in nature. Using computational design and directed evolution, the required activity was achieved by two sequential reactions. An acetyl-CoA synthetase was engineered for better stability and glycolate-use and a propionyl-CoA reductase was engineered for improved glycolyl-CoA selectivity and NADPH-use. This glycolate reduction module was then combined with three existing downstream enzymes (an aldolase, an isomerase, and a kinase) to convert glycolaldehyde to RuBP via an arabinose-5-phosphate shunt (see also Weber and Bar-Even 2019). Conversion of glycolate to RuBP using the glycolate-toglycolaldehyde module was successfully shown to take place in vitro using recombinant proteins (Trudeau et al. 2018). In this way it should be possible to bypass natural photorespiration without producing CO2 and ammonium. In a similar strategy to that used for the glycolate-glycolaldehyde module, another C-conserving photorespiratory bypass was designed using the tartronyl-CoA (or TaCo) pathway (Scheffen et al. 2021). This hypothetical pathway starts with glycolate that is converted by the activity of glycolyl-CoA synthetase (GCS) to glycolyl-CoA that is then converted to tartronyl-CoA by glycolyl-CoA carboxylase (GCC) and this is finally made into glycerate by the action of tartronyl-CoA reductase (TCR). By applying rational design and high-throughput evolution, GCS was made from a mutated Erythrobacter acetyl-CoA synthetase to improve glycolate-dependent activity and GCC was created by selected mutations and directed evolution from a propionyl-CoA carboxylase from Methylorubrum extorquens. TCR was a naturally occurring bi-functional malonyl-CoA reductase from Chloroflexus aurantiacus. The reconstitution of a functional TaCo pathway interfaced with photorespiration was successfully achieved in vitro with the addition of PGLP and GLYK leading to the conversion of 2PG into 3PGA (Scheffen et al. 2021). This chapter will close with a few words about a very hypothetical alternative CO2-assimilatory pathway (the crotonyl-CoA/ethylmalonyl-CoA/hydroxybutyrylCoA (CETCH) cycle) that fixes CO2 more efficiently than the native Calvin cycle. It is composed of 17 enzymes (16 are naturally occurring and one is synthetically designed) from nine different organisms. It has been coupled with the AP3-plgg1RNAi photorespiratory bypass (South et al. 2019) in an in silico metabolic model to predict the eventual beneficial outcome for CO2 fixation and energy use (Osmanoglu et al. 2021). The two pathways are coupled by CETCH cycle produced glyoxylate that is metabolized by the photorespiratory bypass to produce CO2 that can be re-assimilated by the CETCH pathway. Estimated calculated fluxes showed that the combined CETCH and AP3-plgg1RNAi pathways gave a higher CO2-harvesting potential when compared to other tested pathways (Osmanoglu et al.

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2021). This alternative strategy to improve plant CO2 assimilation is still hypothetical and it will be very difficult to instore and test in a plant system due to the number of genes that must be incorporated and the fact that the Calvin cycle (if removed) is central to cell metabolism.

6 Conclusions Many strategies have been proposed to improve photosynthesis, some appear quite simple to carry out and to test while others appear complex and excessively challenging (for instance, installing a CMM in C3 plants, or producing smart canopies). To date, an improvement of photosynthetic performance that favourably impacts plant biomass and yield has been achieved by improving NPQ relaxation kinetics, improving RuBP regeneration, and implementing chloroplast photorespiratory bypasses. The potential of rerouting photorespiratory glycolate catabolism to reduce energy costs and to increase CO2 concentration at the site of Rubisco has been clearly shown. These success stories must now be transferred to crop species and tested under current field conditions and climate change-predicted situations. Pyramiding successful strategies should also be tested to see whether yield can be further increased. At the same time, new future-proofed plants should be designed, created, and tested. Perhaps they will contain one of the mentioned theoretical or on-going photorespiratory bypasses or a C4 or algal CCM. With respect to photorespiration as an important interconnected metabolic process, future efforts should be focused on understanding its regulation. From proteomics studies, all photorespiratory enzymes appear as targets for multiple PTMs including protein phosphorylation and redox-controls. There is now a need to validate such modifications by other methods, to understand their physiological functions and to investigate if and when they are occurring in planta. Such PTMs might become future targets to modulate photorespiration and to thus impact plant metabolism to favour plant performance under future climate change conditions. Acknowledgments MH is supported by public grants overseen by the French National Research Agency as part of the « Investissement d’Avenir» program, through the “Lidex-3P” project and a French State grant (ANR-10-LABX-0040-SPS) funded by the IDEX Paris-Saclay, ANR-11-IDEX0003-02. MH was also supported by the ANR-14-CE19-0015 grant REGUL3P. MH would like to thank past (especially Younès Dellero, Yanpei Liu, Pauline Duminil) and present (especially Mathieu Jossier, Nathlaie Glab, Céline Oury) team members who contributed to works described in the chapter.

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Molecular Regulation of Plant Responses to Shade Irma Roig-Villanova and Jaime F. Martinez-Garcia

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Vegetation Proximity Signals and Plant Perception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 How Vegetation Announces Itself: The Signal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Mimicking Plant Proximity and Shade in the Laboratory . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 How Plants Perceive Nearby Vegetation: The Role of Phytochromes . . . . . . . . . . . . . . 3 Basic SAS Molecular Components: The Shade-Induced Hypocotyl Elongation . . . . . . . . . . 4 Spatial Level of SAS Regulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 SAS Responses in Seedlings: More Than Just Changes in Elongation . . . . . . . . . . . . . . . . . . . . 5.1 Interaction Between Shade and Biotic Stresses: Plant Defense . . . . . . . . . . . . . . . . . . . . . . 5.2 Trade-off Between Shade and Defense Responses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 Molecular Confluence of the Growth and Defense Signaling Pathways . . . . . . . . . . . . 5.4 Uncoupling Growth and Defense . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Future Directions in Shade Research and the Growth-Defense Balance . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract In sun-loving plants, detection of the proximity of nearby competitors triggers a set of responses known as the shade-avoidance syndrome (SAS). These responses will help the plant to acclimate to the proximity of vegetation that might compromise light availability and limit plant development. Plants sense the presence of nearby competitor vegetation as changes in the light quality, i.e. a reduced red (R) to far-red light (FR) ratio (R:FR). Among the various responses to neighboring plants, one of the best studied and characterized is the promotion of the hypocotyl elongation in seedlings of the model plant Arabidopsis thaliana that might help them

Communicated by Francisco M. Cánovas

I. Roig-Villanova Serra Húnter Fellow, Department of Agri-Food Engineering and Biotechnology, Barcelona School of Agri-Food and Biosystems Engineering, Castelldefels, Spain J. F. Martinez-Garcia (*) Institute for Plant Molecular and Cell Biology (IBMCP), CSIC-UPV, València, Spain e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 Progress in Botany (2024) 84: 221–240, https://doi.org/10.1007/124_2022_66, Published online: 21 September 2022

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to outcompete neighboring seedlings and reach better light conditions. In addition to this and other developmental changes, shade perception affects photosynthetic capacity and reduces plant defense. In this chapter, we will review the main molecular aspects that control the regulation of hypocotyl elongation, including the role of the phytochrome photoreceptors, that sense the signal, and the best known genetic and hormonal components that participate downstream shade perception. Because of the obvious interest for translating this knowledge to agriculture, we will also explore what is known about the molecular interaction between shade perception, defense responses, and the growth-defense trade-off observed in high planting density. Keywords Arabidopsis thaliana, Jasmonic acid (JA), Plant defense, Plant development, Plant proximity, Shade avoidance, Vegetation proximity

1 Introduction High planting density might reduce the availability for light, favoring the competition between individual plants to reach better light environments. As a consequence, for many plant species, perception of plant proximity induces a set of responses known as the shade avoidance syndrome (SAS) that strongly affects plant development and metabolism. Although the SAS responses might vary between plant species, they usually result in an increase in elongation, altered architecture, promotion of flowering, a reduced seed set, and altered fruit development. They also acclimate the plant to grow under environments with lower light intensities. These SAS responses, that might get initiated even before the plant is shaded, can be viewed as the optimum strategies to adapt to eventual shading in natural environments. By contrast, as crops are typically grown at high densities, activation of SAS is generally detrimental for crop production: SAS responses induce reallocation of resources into elongation growth at the expense of harvestable organs (usually leaves, fruits, and seeds). Therefore, one key research challenge that will certainly have a major impact in agriculture is to identify the mechanisms that underlie plant development in response to vegetation proximity. In this chapter, we will summarize the current knowledge about the response to shade in seedlings with a focus on the promotion of elongation. Most of this information has been obtained after research in the model system Arabidopsis thaliana, whose hypocotyls strongly respond to those signals that mimic the proximity of other plants. In addition to developmental changes, plants also have to deal with changes in their ability to defend from herbivore attacks. This aspect will also be addressed herein.

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2 Vegetation Proximity Signals and Plant Perception In both natural and agricultural plant communities, light might become a limiting resource under high plant density, leading to grow under low light intensities. In such a situation, plants have evolved to either tolerate or avoid shade. In general, under low light intensities, shade-tolerant species tend to adapt to a highly conservative utilization of resources, commonly accompanied by low growth rates, thinner leaves, reduced apical dominance (increased branching), and low elongation response (Casal 2012; Gommers et al. 2013; Martinez-Garcia et al. 2010). By contrast, shade-avoiding (or sun-loving) species generally tend to adapt to their development to favor elongation at the expense of leaf development, and to increase apical dominance (reduced branching), allowing young and growing tissues to rapidly escape from shade.

2.1

How Vegetation Announces Itself: The Signal

In open conditions, i.e., when a plant grows under low vegetation density, the light coming from the sun (or sunlight) is relatively constant in quality, and the red (R, about 600-700 nm) to far-red light (FR, about 700-800 nm) ratio (R:FR) is higher than 1.2. When sunlight impacts plant tissues, photosynthetic pigments (such as chlorophylls and carotenoids) specifically absorb light from the photosynthetic active radiation (PAR, between 400-700 nm) region whereas FR, which is poorly absorbed by plant tissues, is reflected from or transmitted through vegetation. Therefore, the proximity of other plants (e.g., prairies or agricultural monocultures) enriches with FR the sunlight and results in an intermediate or moderate reduction in the R:FR. By contrast, under a plant or leaf canopy (e.g., inside the forest), sunlight is strongly depleted in the PAR region but not so much in FR, which is poorly absorbed by plant tissues and is reflected from or transmitted through vegetation. This results in the reduction of both the amount of PAR and R:FR (low and very low R:FR). In summary, in environments of high vegetation density, two related but different situations that lower the R:FR can occur: plant proximity, without direct shading by neighboring plants, and direct plant canopy shade, that also results in major reductions in light intensity that might compromise photosynthesis (Casal 2013; Martinez-Garcia et al. 2010; Smith 1982) (Fig. 1).

2.2

Mimicking Plant Proximity and Shade in the Laboratory

Simulated shade refers to those laboratory conditions or treatments that mimic the proximity or shade of vegetation. However, this term does not always differentiate between the proximity shade, before actual canopy shading occurs, and canopy

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Fig. 1 Different characteristics of the light and shade conditions found in nature. When plants grow unshaded (isolated from other plants), sunlight contains high amounts of PAR but low FR, which results in a relatively high R:FR (left). When vegetation density increases, FR reflected from neighboring plants (dark red arrows) mixes with sunlight, resulting in a reduction of R:FR to intermediate or low levels. This signal informs of the presence of nearby competing plants, which allows neighbor detection (center). Under the canopy of other plants, sunlight filtered through the leaves is strongly depleted in the PAR spectrum, including R (red arrows), but not so much in FR (dark red arrows), which is transmitted. This results in a low or very low R:FR, which helps individual plants growing in the understory to detect canopy shade (right)

shade, when canopy closure occurs (Possart et al. 2014; Roig-Villanova and Martinez-Garcia 2016). To avoid ambiguities and to compare the different conditions, in this chapter we will employ the terms (1) simulated shade, to refer to any conditions that lower the R:FR and have not been defined by the authors as mimicking either vegetation proximity or shade; (2) proximity shade, to those conditions that simulate plant or vegetation proximity; and (3) canopy shade, to those conditions that mimic natural direct plant shade (Fig. 2). These treatments are obtained in the laboratory by applying increasing intensities of FR to a fixed amount of white light (W), usually provided by fluorescent tubes: for a given amount of PAR, intermediate R:FR (about 0.50–0.30) results in proximity shade treatments, and low and very low R:FR (4 h of exposure to deep shade), and is phyA-dependent (Ciolfi et al. 2013). Hypocotyls of the hy5 mutant seedlings elongate more than the wildtype ones under low R:FR (Bou-Torrent et al. 2015; Ortiz-Alcaide et al. 2019; van Gelderen et al. 2018), particularly to shade signals in response to inhibitory daily sun flecks (unfiltered light gaps that occur in the vegetation canopies) given in the afternoon (Sellaro et al. 2011). HY5 may inhibit elongation by negatively regulating gibberellin (GA) signaling, as it is required for the expression promotion of GA2OXIDASES (which encode GA-inactivating enzymes) in seedlings exposed with UV-B light and either W or W + FR, a process that also results in the accumulation of DELLA proteins (Hayes et al. 2014). However, the precise role of HY5 activity in the current SAS working model is unclear. Treatment with low R:FR light increases the levels of the bioactive GA4 (Bou-Torrent et al. 2014). Transcriptomic analyses suggested that these changes might take place because of the promotion of GA biosynthetic genes (e.g., GA20OX and/or GA3OX) and the repression of GA2OX. Because GAs cause the degradation of DELLA proteins, the reduced stability of DELLAs observed after exposure to canopy shade could be a consequence of increased GA levels (Djakovic-Petrovic et al. 2007). As DELLAs are direct interactors of PIFs and their binding prevents DNA-binding activity of PIF proteins, shade-induced removal of DELLAs is expected to release the suppression of PIFs, hence activating the transcription of target genes. Consistently, the GA-insensitive gain-of-function mutant gai, which has a stable GAI (DELLA) protein, shows a reduced hypocotyl elongation in response to shade (Djakovic-Petrovic et al. 2007), suggesting that DELLA proteins constrain the SAS. Simulated shade treatments were shown to rapidly and transiently increase endogenous levels of auxins (Hornitschek et al. 2012; Li et al. 2012; MolinaContreras et al. 2019; Tao et al. 2008). SHADE AVOIDANCE 3 / TRYPTOPHAN AMINOTRANSFERASE OF ARABIDOPSIS 1 (SAV3/TAA1) encodes an enzyme required for the shade-induced biosynthesis of indole-3-acetic acid (IAA), a bioactive auxin (Tao et al., 2008). YUCCA (YUC) genes encode flavin monooxygenaselike proteins that catalyze a rate-limiting step in IAA biosynthesis. Indeed, TAA and YUC families function in the same IAA biosynthetic pathway, known as the indole2-pyruvic acid (IPA) pathway (Fig. 4) (Mashiguchi et al. 2011; Zhao 2014). PIF4, PIF5, and PIF7 were shown to directly regulate the shade-induced expression of some YUC genes; in addition, the shade-mediated increase of auxin was much

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Fig. 4 Phytochrome regulation of auxins (biosynthesis, transport, and sensitivity) in the response of seedlings to plant proximity. Shade perception is integrated with auxins at multiple levels, affecting both auxin biosynthesis and sensitivity. The two steps in auxin biosynthesis (enclosed in black dotted squares and represented by thick empty arrows) are indicated together with the involved enzymes (SAV3/TAA1 and YUC). Black and purple lines indicate that the role of known regulators may be either direct (continuous) or indirect (discontinuous), and positive (arrow heads) or negative (flat ends)

reduced both in pif4pif5 and pif7 mutant seedlings. These results led to establish that PIF4, PIF5, and PIF7 directly control auxin biosynthesis. PIFs also directly regulate several auxin-responsive genes, such as several INDOLE-3-ACETIC ACID INDUCIBLE (e.g., IAA3, IAA19, or IAA29) or SMALL AUXIN UP-REGULATED RNA (e.g., SAUR15) genes, indicating as well an involvement of PIFs in modulating auxin sensitivity (Hornitschek et al. 2012; Li et al. 2012). Genetic analyses indicate that several PAR factors, such as ATBH4, PAR1, BIM, and BEE proteins, provide entry points by which shade- and auxin-regulated networks are integrated (CifuentesEsquivel et al. 2013; Sorin et al. 2009). In summary, there is abundant evidence for the involvement of several factors in controlling auxin levels and sensitivity in the hypocotyl elongation response. How auxin and other hormones are integrated in controlling shade-induced hypocotyl elongation is currently unclear. The IPA pathway, that involves the role of phyB action, takes place whenever the R:FR is reduced, either in the case of proximity, canopy or deep shade. However, as mentioned, the antagonist role of phyA enters in action under very low R:FR (canopy or deep shade), conditions in which the photolabile phyA protein can accumulate to enough levels to inhibit hypocotyl elongation. Consistently, only under these conditions phyA mutant hypocotyls display an exaggerated elongation (Martinez-Garcia et al. 2014; Molina-Contreras et al. 2019; Yang et al. 2018). In this

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case, the enhanced elongation does not seem to depend on auxin biosynthesis only but on auxin signaling via the IAA proteins. The ability of phyA to interact with IAA proteins, such as IAA17, results in their stabilization that can inhibit growth. In the phyA mutant background, the absence of the photoreceptor results in the destabilization of IAA proteins which leads to an enhanced elongation (Yang et al. 2018). Genetic analyses indicate that full shade-avoidance responses also require CONSTITUTIVE PHOTOMORPHOGENIC 1 (COP1), an E3 ligase involved in targeting proteins to degradation by the proteasome, as the cop1 mutant lines display an attenuated shade-induced elongation response (McNellis et al. 1994; Roig-Villanova et al. 2006). Natural or deep shade signals (that strongly reduce both PAR intensity and R:FR) increase the nuclear abundance of COP1 (Pacin et al. 2013). This results in an enhanced degradation of HFR1 that would increase the activity of PIFs. Consistently, the cop1 mutant does respond to deep shade in the hfr1 mutant background (Pacin et al. 2016). The cop1 mutant also responds to shade in the bbx21 bbx22 double-mutant background (Crocco et al. 2010). BBX21 and BBX22 are negative regulators of shade-avoidance responses whose expression is also mildly and rapidly up-regulated in response to simulated shade (Crocco et al. 2010). In addition, COP1 interaction with other BBX proteins led in some cases to their degradation by the proteasome (Datta et al. 2008). Together, these observations suggest that the increased COP1 nuclear abundance under shade impacts on the abundance of several components that regulate shade avoidance.

4 Spatial Level of SAS Regulation The physical separation between the sites of shade perception and response is highlighted by a miscellany of experimental approaches in different species that employed localized shade irradiation (EOD-FR or low R:FR) of cotyledons or primary leaves combined with molecular or physiological analyses in the responding organs (hypocotyls or epicotyls) (Bou-Torrent et al. 2008). Detailed analyses in Brassica rapa seedlings suggested that cotyledons are the site of photoperception of this signal in the seedlings that triggers local synthesis of IAA that then is transported to the hypocotyl. In there, auxin induces the up-regulation of auxin-related genes associated with the SAS hypocotyl response. Together, the results show that cotyledon-generated auxin regulates hypocotyl elongation (Procko et al. 2014). Treatment of A. thaliana seedlings with the auxin transport inhibitor N-1-naphthylphthalamic acid (NPA) or mutations in the PINFORMED 3 auxin efflux transporter both result in reduced hypocotyl growth in shade. This suggested that auxin transport is also necessary for shade responses in this species (Keuskamp et al. 2010). In addition, the auxin biosynthesis gene SAV3/ TAA1, which is required for growth responses to shade, is predominantly expressed in the margins and vasculature of cotyledons and emerging leaves (Tao et al. 2008) further supporting that cotyledons are the primary site of shade perception. Organspecific transcriptomic analyses using micro-samples prepared from the topmost part

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of the hypocotyls (shoot apex samples) and cotyledons from A. thaliana young seedlings differentially irradiated with or without EOD-FR identified specific and shared EOD-FR-induced genes in both types of samples, which suggested the existence of tissue-specific and common regulatory components involved in the implementation of the SAS responses in the different tissues. In addition, localized EOD-FR spotlight irradiation also indicated that EOD-FR-induced gene expression depends on both organ-autonomous (i.e., HFR1 and ATHB2) and interorgan mechanisms, which involve the role of auxins and PIFs (Nito et al. 2015). Indeed, cotyledons are the major site of shade perception that controls several apexresponsive genes, including those that are auxin-responsive and/or PIF7-dependent. This is consistent with the known role of PIF7 predominantly regulating the seedlings SAS response by controlling auxin biosynthesis in cotyledons (Fig. 4).

5 SAS Responses in Seedlings: More Than Just Changes in Elongation Shade-avoider (sun-loving) species, such as A. thaliana, showed a weak photosynthetic performance when moved to low light (low PAR) conditions that usually follow when a plant is shaded by neighboring vegetation. Therefore, avoiding shade involves much more than promoting elongation growth. Indeed, while plants activate the mechanisms of elongation to reach better light environments, the levels of photosynthetic pigments (chlorophylls and carotenoids) drop. In addition, exposure to canopy shade improved the photo-acclimation to low PAR by triggering changes in photosynthesis-related gene expression, pigment accumulation, and chloroplast ultrastructure. Therefore, exposure to low R:FR results in molecular, metabolic, and developmental responses that allow shade-avoider plants to adjust their photosynthetic capacity in anticipation of eventual shading by nearby vegetation (Morelli et al. 2021).

5.1

Interaction Between Shade and Biotic Stresses: Plant Defense

Plant proximity also has side effects in shade-avoider plants. It facilitates the dispersal of attackers not only because of the close proximity of neighboring plants but also by the increased relative humidity of dense vegetation, that buffers extreme weather. Indeed, apart from triggering the SAS elongation responses, high plant density (and the low R:FR conditions associated) favors the attack of pathogens and herbivorous insects (Ballare and Pierik 2017). In this section we will focus on the interaction between SAS and defense responses in order to have a more inclusive perspective of the regulation of plant development in crowded situations.

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Plants continuously face the risk of losing part of their biomass to consumer organisms (attackers, usually herbivore insects) and defend themselves by displaying different defense responses. These responses can be either direct (with an immediate impact on the attacker) or indirect (attracting natural enemies of the attacker). Direct defenses consist of the production of secondary metabolites and proteins with repellent or toxic effects, while indirect defenses usually consist of the production and release of volatile compounds (Ballare 2009). The activation of the plant defense starts with the recognition of attackers followed by the activation of signaling cascades and finishes with a phenotypic response. Salicylic acid (SA) and Jasmonic acid or jasmonates (JAs) are the main hormones regulating different aspects of the mechanisms of plant defense (Ballare 2009; Ballare 2014; de Wit et al. 2013). The SA response pathway is activated by microbial pathogens and involves the synthesis of SA, although it is not clear how pathogen recognition induces SA synthesis. As a consequence of the SA biosynthesis many defense-related genes are activated. A central regulator of SA-induced responses is the NONEXPRESSOR OF PR GENES 1 (NPR1) protein. In the presence of SA, the cytosolic and inactive NPR1 oligomers are monomerized and translocated to the nucleus. Once in the nucleus, NPR1 monomers function as cofactors of TGA transcription factors that activate the expression of SA-responsive, defense-related genes, including PATHOGENESIS RELATED (PR) genes and genes encoding several WRKY transcription factors (Fig. 5a). These changes are part of a response that protects the plant from successive infections that is known as systemic acquired resistance (Ballare and Pierik 2017). JAs play a key role in the orchestration of plant defense responses against necrotrophic pathogens and herbivorous insects. JAs are lipid-derived molecules whose production in the plant is rapidly induced after attack. This induction is the signal that regulates the expression of many genes involved in plant defense against herbivorous insects. In the absence of JAs, positive regulators of JA target genes, such as the bHLH MYC2 transcription factor, are repressed by JASMONATE ZIM-domain (JAZ) transcriptional repressors. Upon attack, JAs are produced and conjugated with amino acids to form bioactive JAs, being jasmonoyl-L-isoleucine (JA-Ile) the major one. This molecule is perceived by co-receptors formed by the JAZs and the F-box protein CORONATINE INSENSITIVE 1 (COI1) and promotes the degradation of JAZs through the activity of the E3 ubiquitin ligase SCFCOI1 and the proteasome (Ballare 2009). Therefore, JAZs degradation is a rapid activation mechanism of the defense response (Fig. 5a). On the other hand, JAZ genes are rapidly induced by JA. This starts a negative feedback loop that represses the JA signaling cascade when the attack finishes. Mutants impaired in either JA synthesis, conjugation or JAZ degradation have been shown to be more susceptible to herbivore attack in bioassays. JAs act as an informative signal from the site of the attack to other tissues. Apart from inducing the defense response and providing information within the plant, JAs inhibit cell division and elongation. This results in the repression of plant growth that may be necessary to save resources for defense. The fact that JAs control

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Fig. 5 Simplified representation of the interplay between the signaling pathways that activate defense and shade responses. (a) Attackers perception activates biosynthesis of JAs and SA that, by means of different components, induce the defense responses. (b) Shade caused by neighbor proximity inactivates phyB that results in elongation responses with the participation of specific regulators and plant hormones. (c) Key points of the crosstalk between defense and shade response networks (red lines) are: (i) the repression of JA biosynthesis by PIFs; (ii) the negative interaction between DELLA and JAZ proteins; (iii) the COP1-dependent degradation of MYCs in shaded conditions; iv) the induction of HY5 transcription by MYCs, that reduces elongation; (v) the induction of PIF activity by JAZ that promotes elongation when the JA pathway is inactive; and (vi) the inhibition of the phosphorylation of NPR1 in the nucleus in the presence of SA triggered by phyB inactivation. Colored boxes and circles indicate hormonal pathways. Circles indicate hormones. Arrows indicate promotion or activation; truncated lines indicate repression, inactivation, or degradation. Adapted from Pierik and Ballare (2021)

both defense and growth responses points them as key regulators of resource when plants face, simultaneously, competition with other plants and attackers (Ballare 2009).

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Trade-off Between Shade and Defense Responses

Ecologically, in high plant density, the responses activated when plants compete for light and when they defend themselves against attackers are contrary forces that have a reciprocal cost. In addition to the shade-induced elongation responses, the SAS also includes a reduction in leaf thickness and strength as well as changes in metabolism, such as a reduction in photosynthetic pigments and defense-related specialized metabolites. Therefore, resource allocation to promote elongation to avoid shade and the possible reduction in the photoassimilates caused by shading may compromise the investment in defenses. This conflict is known as the growth– defense trade-off and in high densities where shade-avoider plants display rapid elongation responses this trade-off is key to define survival and yield (Ballare 2014; Pierik and Ballare 2021). This topic has been the focus of many researchers in the past recent years. The light regulation of plant defense and its ecological consequences have been nicely reviewed in different recent articles (Ballare 2014; Ballare and Austin 2019; Ballare and Pierik 2017; Fernandez-Milmanda and Ballare 2021; Yang and Li 2017). In this section we will center our attention on the molecular players of the so-called growth–defense trade-off identified in A. thaliana in response to changes in R:FR.

5.3

Molecular Confluence of the Growth and Defense Signaling Pathways

As described earlier in this chapter, phyB is the main phytochrome responsible for the control of SAS responses triggered after perception of simulated shade. Briefly, low or very low R:FR ratios inactivate phyB and initiate elongation responses by removing the repression on the PIFs. In addition, the activity of COP1 and SUPPRESSOR OF PHYA-105 (SPA) ubiquitin E3 ligase complex is also enhanced (Fiorucci and Fankhauser 2017). Whereas PIFs induce auxin biosynthesis and the expression of growth-promoting genes, resulting in the elongation of the plant, the COP1/SPA complex regulates the degradation of HY5, HFR1, and BBX proteins. In non-shaded conditions HY5 inhibits elongation by negatively regulating gibberellin (GA) signaling via DELLA proteins (Fig. 5b). Removal of the growth repressor HY5 in the shade contributes to PIF-mediated promotion of elongation growth. Apart from hypocotyl elongation, low R:FR also induces other SAS morphological responses (including petiole elongation, leaves hyponasty, increased shoot:root ratio, and accelerated flowering and senescence). Moreover, the R:FR ratio is also a key modulator of the SA and JA signaling pathways controlling defense responses (Fernandez-Milmanda and Ballare 2021; Pierik and Ballare 2021) (Fig. 5c). phyB inactivation has been correlated with an inhibition of the phosphorylation of NPR1 in the nucleus in the presence of SA. NPR1 phosphorylation leads to its degradation via proteasome, impeding the activation of the expression of SA-responsive,

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defense-related genes. This mechanism partly explains how shade reduces SA-dependent disease resistance, although further research has to be done to investigate the crosstalk between plant proximity responses and the defense against microbial pathogens (Fernandez-Milmanda and Ballare 2021; Yang and Li 2017). Moreover, under shade conditions plants also display a weak defense against herbivores and necrotrophic pathogens (Gommers et al. 2017; Moreno et al. 2009). It has been shown that shade down-regulates the JA biosynthesis through the phyB-PIF transcriptional module, that important regulators of the interaction shade-JA defense are the JAZs and the DELLA proteins, and that PIFs play a central role in this crosstalk. In non-shaded conditions, DELLAs negatively regulate growth-related genes by binding PIFs. DELLAs also positively regulate JA signaling by interacting with JAZs, and this interaction weakens the ability of JAZs to repress MYC2. Shade conditions induce GA biosynthesis and the degradation of DELLAs, increase PIF-dependent growth, and impair JAZ-dependent defense. In addition, mutant studies indicate that phyB inactivation reduces MYC stability in a COP1dependent manner, but the details of this regulation remain to be elucidated (Chico et al. 2014; Pierik and Ballare 2021) (Fig. 5c). As already introduced, JA signaling also affects elongation responses at multiple levels. It has been described that MYCs and JAZs can regulate SAS responses in seedlings, in which MYCs inhibit shade-avoidance responses by activating HY5 expression. How MYCs regulate growth in older plants is still not clear. Other investigations showed that when defense response is activated, JAZs degradation indirectly increases the repression of PIF action, attenuating seedling elongation. Therefore, different mutants deficient in JA biosynthesis and signaling display exaggerated shade-induced hypocotyl responses to low R:FR (Fernandez-Milmanda and Ballare 2021; Pierik and Ballare 2021).

5.4

Uncoupling Growth and Defense

Research on the effects of shade on JA signaling suggests that this plant hormone can use different signaling components to act on growth and defense. Therefore, their effects on these two responses are not cause-effect. Consistently, it has been described how some JAZ proteins are involved in the suppression by shade of JA-induced defense, but not in the suppression of growth. In addition, it has been postulated that the effects of shade on JA-regulated growth and defense responses can work through different COI1–JAZ co-receptor subtypes, which subsequently control different transcriptional outputs. Finally, experiments done in laboratory conditions using plant species different from A. thaliana also suggested that the effects of JA on growth and defense can be easily uncoupled (Ballare and Austin 2019). Altogether, these evidences argue against an oversimplified perspective of a growth-defense trade-off where allocation of resources into defense reduces the ones to allow rapid growth. Instead, growth restriction can be considered part of the defense response that will be positive in the presence of attackers and negative in

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conditions of strong competition for light, where plants prioritize elongation responses over defense against herbivores and pathogens (Ballare and Austin 2019; Fernandez-Milmanda and Ballare 2021).

6 Future Directions in Shade Research and the Growth-Defense Balance Understanding the mechanisms that link photoreceptors with growth and defense has been and still is an important field of research. These studies, that during years have been mostly done in A. thaliana, recently disclosed new points of regulation of the JA signaling pathway (Fernandez-Milmanda et al. 2020). Overall, they point out that the interplay between the JA and phyB signaling pathways could be targeted in future breeding programs. To breed healthy crops adapted to high-density plantings, comparative studies between A. thaliana and crops are required to determine to what extent current knowledge can be translated to species of agricultural interest. Results of experiments performed in other model plants, such as rice or tomato (not mentioned in this book chapter), will also help to establish the base for breeding programs. Another important aspect will be to analyze growth and defense responses in realistic ecological conditions that will take into consideration biotic and environmental complexity. Finally, mechanistic simulation models could be useful tools to predict the effects of altering light and defense pathways in cultivated species (Ballare and Austin 2019). Altogether, these different approaches will establish the base for new breeding programs or for manipulation by means of photobiotechnological technology (Ganesan et al. 2017) aimed to improve plant productivity, stress tolerance, and health of agricultural crops, as well as to design optimal light environments in protected agriculture. Finally, in high densities plants compete for resources not only above (such as the competition for light that we discuss in this book chapter) but also below (water availability and nutrients) ground. In order to adapt to this competition, plants synergistically modify the development of their shoots and roots, suggesting a communication between these organs for an orchestrated growth response (Pierik and Testerink 2014). Until now, research has not focused either on the root system and its plasticity or on the root–shoot integration with the purpose of increasing plant yield. An integrative research beyond single-stress and single-organ is a challenge that researchers are beginning to face. Acknowledgments The authors are supported by grant PID2020-115782GB-I00 from Spanish MCIN/AEI (10.13039/501100011033), by the EU PRIMA project UToPIQ (MCIN/AEI code PCI2021-121941), the Generalitat Valenciana project ENIGmA (PROMETEU/2021/056), and the Consejo Superior de Investigaciones Cientificas (CSIC code 202040E256).

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Photoinhibition of PSI and PSII in Nature and in the Laboratory: Ecological Approaches Masaru Kono, Riichi Oguchi, and Ichiro Terashima

Contents 1 Prologue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 PSII Photoinhibition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Simple Mathematical Expression of Photoinhibition and Repair Proposed by Kok 2.2 PAM Fluorometry and Alternative Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Roots of the Two-Step or Mn Hypothesis and Excess-Y(NO) Hypothesis . . . . . . . . . . 2.4 Both Mn/(Two-Step) and Excess-Y(NO) Mechanisms Parallelly Occur Under Relatively Mild Experimental Conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5 Separate Determination of PSII Damaged by the Mn/(Two-Step) Mechanism from Those by the Excess-Y(NO) Mechanism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.6 Does PSII Repair Occur in Strong Light? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 PSI Photoinhibition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Cucumber as a Chilling Sensitive Model Plant for PSI Photoinhibition at Low Temperature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 PSI Photoinhibition in the pgr5 Mutant . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 PSI Is Susceptible to “Artificial” Fluctuating Light . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 Shade Plant PSI Is Resistant to Sudden Sunflecks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5 Need for More Attention to Far-Red Light . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Immediate and Future Scopes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Immediate Scopes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Future Scopes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

244 244 245 246 250 256 258 261 263 263 271 272 273 277 278 278 280 281

Abstract Light is indispensable for plants to photosynthesize organic matters. Almost all the organisms including animals on our planet eventually rely on this

Communicated by Ulrich Lüttge

M. Kono (*) and I. Terashima (*) Department of Biological Sciences, School of Science, The University of Tokyo, Tokyo, Japan e-mail: [email protected]; [email protected] R. Oguchi Botanical Gardens, Osaka Metropolitan University, Osaka, Japan e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 Progress in Botany (2024) 84: 241–292, https://doi.org/10.1007/124_2022_67, Published online: 29 September 2022

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plant function for their energy as well as the materials forming their bodies. Paradoxically, light often damages the photosynthetic apparatus. This phenomenon is called photoinhibition and has been attracting attention of many photosynthesis researchers. Although the term photoinhibition had been used almost synonymously to refer to photoinhibition of photosystem II (PSII), it was recently shown that PSI is susceptible to fluctuating light. First, we compare two PSII photoinhibition hypotheses: the Mn/(Two-step) hypothesis and Excess-Y(NO) hypothesis. The former claims that the oxygen-evolving complex (OEC) is primarily damaged, while the latter claims excess excitation energy in PSII directly damages D1 function. Both can be induced in the laboratory and may parallelly occur in the same leaf. Because OEC is damaged by ultraviolet (UV) or blue light, UV screening substances in the leaf epidermis plays a crucial role. It is also indicated that the rate of PSII repair in PSII damaged by the Mn/(Two-step) mechanism is much slower than that by the Excess-Y(NO) mechanism. It appears then plants should avoid PSII photoinhibition by the Mn/(Two-step) hypothesis. Photoinhibition of photosystem I (PSI) in cucumber, a model chilling sensitive plant, and that in the mutant of PROTON GRADIENT 5 are compared. The effects of fluctuating light, which naturally occurs in the field, on PSI photoinhibition are also discussed. The PSI photoinhibition in these three cases can be explained by similar scenarios. When reduced P700 donates electrons to O2, oxidative damage is induced. The mechanisms that protect PSI from photoinhibition all contribute to oxidation of P700 to P700+, a safe quencher. When a leaf is suddenly exposed to strong light, spillover of excitation energy from PSII to PSI protects both PSII and PSI from photoinhibition. In all these situations, far-red (FR) light plays essential roles in PSI protection. As FR light not only protects PSI but also enhances photosynthesis, especially in low light phases in the fluctuating light, the roles of FR light in photosynthesis should be fully examined. Other ecologically important problems that should be solved in the future are also pointed out. Keywords Excess-Y(NO) mechanism, Fluctuating light, Mn/(Two-step) hypothesis, Non-photochemical quenching, Photooxidative stress, Repair, Spillover

Abbreviations APX CBB CF0 CF1 Cyt b6/f Cyt f DCIP DCMU DPC

Ascorbate peroxidase Calvin-Benson-Bassham (cycle) Membrane-embedded part of the thylakoid H+-ATPase Catalytic component of the thylakoid H+-ATPase Cytochrome b6/f complex Cytochrome f Dichloro-indophenol Dichlorophenyl dimethylurea Diphenylcarbazide

Photoinhibition of PSI and PSII in Nature and in the Laboratory:. . .

EPR FA FB FL FR FX Kpi kpi krec LHCII MAP MTSF MV NDH NPQ OEC OJIP PAM PFD pgr5 PPFD PR PSI-CEF QA QB Y (NPQ) RISE S Chl* STSF T Chl* TyrZ UV-A WWC Y(I) Y(II) Y(NA) Y(ND) Y(NO)

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Electron spin resonance Iron-sulfur cluster A in PSI Iron-sulfur cluster B in PSI Fluctuating light Far-red (light) Iron-sulfur cluster X in PSI Rate constant of PSI photoinhibition Rate constant of PSII photoinhibition Rate constant of PSII repair Light-harvesting chlorophyll-protein complex of PSII Mehler ascorbate peroxidase (pathway) Multiple turnover saturating flash Methyl viologen NADH DEHYDROGENASE-LIKE complex Non-photochemical quenching Oxygen-evolving complex Analysis based on the fluorescence increasing pattern upon strong actinic light illumination Pulse-amplitude modulated (fluorometry) Photon flux density (mol m-2 s-1) A mutant of PROTON GRADIENT 5/PROTON GRADIENT LIKE 1 cyclic electron transport system around PSI Photosynthetically active photon flux density (400–700 nm, mol m-2 s1 ) Photorespiration (pathway) Cyclic electron transport around PSI Quinone electron acceptor A Quinone electron acceptor B Quantum yield of regulated thermal dissipation in PSII PQ reduction-induced suppression of electron flow Excited chlorophyll in the singlet state Single turnover saturating flash Excited chlorophyll in the triplet state A Tyr residue involving in electron transport in D1 Ultraviolet A, ranging from 315 or 320 nm to 400 nm Water to water cycle Quantum yield of PSI photochemistry Quantum yield of PSII photochemistry Quantum yield of non-photochemical energy dissipation due to limitation of electron acceptors from PSI Quantum yield of non-photochemical energy dissipation due to limitation of electron donors to PSI Quantum yield of non-regulated energy dissipation in PSII

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1 Prologue There are numerous reviews on photoinhibition. If this review has some uniqueness, it would be that the approach is ecological. In his comprehensive review on PSII photoinhibition, Tyystjärvi (2013) pointed out that there are two main routes to photoinhibition. In one route, researchers focus on interesting mechanisms without considering natural or realistic conditions. Since biological organisms and their various parts, including chloroplasts, are fine machines, the organisms and their parts respond not only to ecologically realistic stimuli but also to other artificial stimuli. Although it is true that ecologically important mechanisms have been sometimes disclosed through examinations of responses to ecologically unrealistic stimuli, there are numerous studies which do not have ecological meanings. In the other route, ecological realism is of primary importance and the present authors have been taking the ecological or Darwinian approach. This does not mean that we have been conducting our studies in the fields (for good examples of field studies, see Körner 2021; Krause and Winter 2021). Research can be ecological in the laboratories as well. Because plants have been evolving in the field mostly by means of natural selection, various photosynthesis mechanisms must be outcomes of natural selection. We, at least sometimes, need to see the plants and chloroplasts from such an ecological viewpoint. The present review is not aiming at summarizing the current status of our understanding of photoinhibition mechanisms. We do not aim for a comprehensive review, either. For example, we hardly touch some ecologically important aspects, like non-photochemical quenching (NPQ) or roles of carotenoid cycle. We instead discuss some relatively unexplored problems in relation to the ecologically relevant mechanisms of photoinhibitions in photosystems I and II (PSI and PSII), taking a historical approach. When researchers newly join some research field, it is hard to know whether one can trust the results of the preceding papers. To judge whether the old results, theories, or hypotheses are still relevant or had been abandoned, the researchers need to follow some history of the research field. Light is indispensable for plants to photosynthesize organic matters, while light often gives damage to photosystems. Photoinhibition was defined as the lightinduced damage to photosystems (Kok 1956). Although studies on photoinhibition of PSI have been activated by the recent finding that PSI is sensitive to the fluctuating light (Suorsa et al. 2012; Kono et al. 2014; Li et al. 2018; Roach 2020), the main target of photoinhibition studies has been PSII. Thus, we start with PSII.

2 PSII Photoinhibition PSII, the type II reaction center of the oxygenic photosynthetic organisms, is a redox enzyme, which is composed of about 20 polypeptides and several cofactors and contains a reaction center and an oxygen-evolving complex (OEC). The cofactors

Photoinhibition of PSI and PSII in Nature and in the Laboratory:. . .

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involved in charge separation and water oxidation are associated with two homologous proteins, D1 and D2, which are largely embedded in the thylakoid membrane. D1 protein provides most of the ligands to OEC, the Mn4CaO5 cluster, which occurs at the lumenal side of D1 (Cox et al. 2019). In the light, the electrons, released from water, flow through the redox cofactors including TyrZ, P680, and pheophytin in D1, and reduce the primary quinone acceptor, QA, bound to D2. Upon accepting two electrons from QA and two protons from the stroma, the secondary electron acceptor QB is released from the dock in D1 as a plastoquinol molecule. In this way, the electrons flow to the cytochrome b6/f complex (Cyt b6/f ), PSI, and reduce NADP+ to NADPH (Tikhonov 2014).

2.1

Simple Mathematical Expression of Photoinhibition and Repair Proposed by Kok

It is useful to introduce the mathematical expression of the rates of photodamage and repair of PSII according to Kok (1956). The rate of photodamage and that of repair is expressed as the first-order reactions proportional to the fractions (or concentrations) of active and inactivated PSII, respectively. Let the fraction of active PSII be a, then, the derivative of a with respect to time, t, can be expressed as: da=dt = - kpi ∙ a þ krec ∙ ð1 - aÞ

ð1Þ

where kpi and krec are the first-order rate constants for photodamage and repair, respectively. This differential equation can be solved and a is expressed as: a=

krec þ kpi  exp - k rec þ kpi  t krec þ kpi

ð2Þ

When an inhibitor of the plastid protein synthesis, such as lincomycin, is added, krec is zero and the above equation is simplified to: a = exp - k pi ∙ t

ð3Þ

Lincomycin is most frequently used. Chloramphenicol, a popular inhibitor of 70S-type protein synthesis, should not be used because it acts as an electron acceptor from PSI (Okada et al. 1991). Because Eq. 1 is a highly simplified expression of the overall forward and backward reactions including damages to and synthesis/assembly of a number of cofactors and proteins, not just the D1 protein, the rate constants obtained should be regarded as rough estimations. Keeping such limitations in mind, these rate constants are used hereafter. The units frequently used for these rate constants are s-1 and min-1. Oguchi et al. (2021) applied Eq. 3 to PSI photoinhibition. In this review, the

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rate constant for PSI photoinhibition is expressed using a capital K as Kpi (see Sect. 3.1). We will not discuss the slow recovery process of PSI.

2.2

PAM Fluorometry and Alternative Methods

In 1985, the pulse-amplitude modulated (PAM) fluorometer became commercially available from Walz, Germany, and PSII photoinhibition studies bloomed in many laboratories. In PAM fluorometry, the measuring beam consists of 1–2 μs square waves emitted at 1.6 or 100 kHz and the changes in fluorescence levels responding to these pulses are monitored. In this way, signals proportional to the quantum yield of fluorescence can be monitored without interference by non-modulated actinic light. By applying this technique, various PSII activities can be assessed non-invasively and thus the technique has been commonly used for nearly 40 years (Baker 2008; Lazár 2015). Based on the QA model, the quantum yield of chlorophyll fluorescence of PSII changes depending on the redox state of QA and the heat dissipation processes such as NPQ (Schansker et al. 2014). Here, we use the conventional PAM fluorometry parameters and assume that decay of the excited chlorophylls in PSII [Chl*] is expressed as a sum of first-order reactions: d½Chl =dt = - kF þ kD þ k isc þ k NPQ þ qopen ∙ kP ∙ ½Chl :

ð4Þ

where the first-order rate constants are as follows: kF radiative (fluorescence) deexcitation, kD thermal deexcitation to the ground state via pathways other than NPQ (non-photochemical quenching), kisc intersystem crossing leading to formation of triplet Chl* (TChl*), kNPQ thermal deexcitation via NPQ, and kP photochemistry, qopen denotes the fraction of open PSII reaction center. Fluorescence parameters frequently used are as follows, where M is a constant depending on the measuring system. F0 and Fm are minimal and maximum fluorescence yields in the dark-treated sample. F00 and Fm0 are minimal and maximum fluorescence yields in the illuminated sample. Fs0 is fluorescence yield in the light. Fv and Fv0 are variable fluorescence yields in the dark-treated sample and illuminated sample. F0 =

M ∙ kF , k F þ kD þ k isc þ kP

ð5Þ

M ∙ kF , kF þ kD þ kisc

ð6Þ

Fm =

Photoinhibition of PSI and PSII in Nature and in the Laboratory:. . .

M ∙ kF , k F þ kD þ k isc þ kNPQ þ k P

ð7Þ

M ∙ kF , kF þ kD þ k isc þ k NPQ

ð8Þ

M ∙ kF , k F þ kD þ kisc þ kNPQ þ qopen ∙ k P

ð9Þ

F 00 =

F 0m =

F 0s =

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Fv = Fm - F0 ,

ð10Þ

F 0v = F 0m - F 00 :

ð11Þ

and

The maximum quantum yield of PSII photochemistry (Fv/Fm, Kitajima and Butler 1975a), quantum yield of PSII photochemistry in the light (Genty et al. 1989), and NPQ (Bilger and Björkman 1990) are the most frequently used ratios of the above parameters: kp , kF þ k D þ kisc þ kP

ð12Þ

qopen ∙ kp F 0m - F 0s = , kF þ kD þ k isc þ k NPQ þ qopen ∙ kp F 0m

ð13Þ

F m - F 0m kNPQ = : kF þ k D þ kisc F 0m

ð14Þ

F v =F m =

Y ðII Þ = and

NPQ =

Kramer et al. (2004) and Hendrickson et al. (2004) independently proposed the method for quantifying the quantum yield of non-photochemical quenching, Y(NPQ), and that of other processes including non - regulated heat dissipation and fluorescence emission, Y(NO), in addition to Y(II). Y ðNPQÞ = and

F 0s ∙ F m - F 0m k NPQ = , 0 k þ k þ k Fm  Fm F D isc þ k NPQ þ qopen ∙ k p

ð15Þ

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Y ðNOÞ =

F 0s kF þ k D þ kics = : F m k F þ kD þ k isc þ kNPQ þ qopen ∙ k p

ð16Þ

qopen is expressed as (Kramer et al. 2004): qopen =

1=F 0s - 1=F 0m F 0m - F 0s F 00 =  : 1=F 00 - 1=F 0m F 0m - F 00 F 0s

ð17Þ

The use of NPQ needs caution because NPQ is equal to Y(NPQ)/Y(NO) (Klughammer and Schreiber 2008; Lazár 2015) and thus is affected by Y(NO). For example, the proportion of open PSII (qopen) and Y(NO) varies in an anti-parallel fashion during photosynthetic induction. Thus, NPQ is lowered (Zhang et al. 2018). In such a case, Y(NPQ) would be more indicative of the energy-dependent non-photochemical quenching than NPQ (W.S. Chow, personal communication; Ishida et al. 2011, 2014). For calculations of fluorescence parameters, see Hendrickson et al. (2004), Kramer et al. (2004), and Klughammer and Schreiber (2008). The inverse fluorescence parameters such as (F0)-1 are very useful in calculations because the denominator, M ∙ kF, is common (Kasajima et al. 2009). For more comprehensive knowledge including historical background, the readers should refer to a book edited by Papageorgiou and Govindjee (2004). Very recently, however, the QA model has been challenged (Laisk and Oja 2020; Sipka et al. 2021). Sipka et al. (2021) gave single turnover saturating flashes (STSFs) successively to spinach thylakoids or PSII core complexes prepared from Thermosynechococcus vulcanus and found that the yield of fluorescence increased even after the full reduction of QA. Analyzing the time-resolved rapid-scan Fourier transformed infrared (FTIR) difference spectra, Sipka et al. (2021) argued that the increase in the fluorescence yield could be attributed to the structural changes in PSII core. The high fluorescent PSII configuration, or light-induced charge-separated state, decayed in the dark. After a train of 20 STSFs, the highly fluorescent state is attained and returns to the low fluorescent state with τ of 15 s. The high fluorescent PSII configuration affects fluorescence only when PQ is reduced. To incorporate the findings of Sipka et al. (2021), we may need to have the rate constant for fluorescence for F 0 ðkF 0 Þ and a variable rate constant for closed PSII reaction center (k 0F ). F 0s =

kF0

M ∙ ½k F0 þ ð1 - qopen Þ ∙ k0F  : þ kD þ kisc þ k NPQ þ qopen ∙ k P þ ð1 - qopen Þ ∙ k0F

ð18Þ

When we use PAM fluorometry with multiple turnover saturating flashes (MTSFs) of 500–1,000 ms, PSII would become in the highly fluorescent mode in a single MTSF. The chlorophyll fluorescence yield would increase during an MTSF and decrease in the dark. The rapid fluorescence increases in the so-called OJIP analysis (Strasser et al. 2004) would, at least partly, reflect the increase in the fluorescence yield of closed PSII, as has been pointed out by Laisk and Oja (2020)

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and Sipka et al. (2021). In this review, we use the conventional fluorescence equations, although close side by side examinations of the effects of a train of STSFs, an MTSF and MTSFs on PAM fluorometry should be made promptly. In photoinhibition studies, maximum quantum yield, Fv/Fm, is most frequently used. Havaux et al. (1991) deduced that 1/F0–1/Fm expresses the rate constant for excitation trapping. Thus, this parameter is also used. When light-emitting diode (s) (LED) of strong light absorption (blue or red) is used as the measuring beam, the system detects fluorescence emitted mostly from the chloroplasts near the illuminated surface of the leaf. The green measuring beam has been used to avoid this bias (Zhang et al. 2018). Far-red light transmits more than green light and therefore the P700+ signal measured at 830 nm has been used for assessment of PSII activity: P700 is oxidized by far-red light and a transient decrease in P700+ by a short flash (for example, a 0.1 ms flash at 7,000 μmol m-2 s-1 white light) is integrated with time. The resultant integral is proportional to the concentration of active PSII reaction centers per leaf area (Kou et al. 2013). For quantification of active PSII, oxygen evolved by repetitive STSFs has been also used (Chow et al. 1991). When optically dense leaves are used, STSFs should be sufficiently intense. Since the Xenon flash has a rather long tailing, it is better to use the laser flash or LED flash to avoid the “double hit” problem. It is better to measure the oxygen evolution rate in an open system with a slow but strictly regulated air flow than in a closed system to avoid the effects of transient temperature changes (the authors’ unpublished observation). It is also popular to isolate thylakoids membrane from the photoinhibited leaves and measure oxygen evolution rates in the thylakoids with appropriate electron acceptors such as dimethyl benzoquinone (Hakala-Yatkin et al. 2010). The lightsaturated rate of oxygen evolution is usually measured for the assessment of the PSII quantum yield. However, it is the initial slope that is proportional to the maximum quantum yield. It is necessary to check whether the light-saturated rate is proportional to the initial slope obtained at low light levels. When the PSI activity from diaminodurene to NADP+ via PSI and ferredoxin was assessed in the thylakoid suspension as an increase in absorbance at 340 nm (due to NADPH formation), the initial slope at low light levels was proportional to the photooxidizable P700 level, whereas the light-saturated rates were not (Terashima et al. 1994). At the leaf level, it has been shown that the maximum quantum yield of O2 evolution or CO2 fixation measured at low photon flux densities (PFDs; mol m2 -1 s ) is linearly dependent on Fv/Fm (Björkman and Demmig 1987, Hikosaka et al. 2004), while the regression line for the light-saturated rate tends to show a large positive interception at Fv/Fm = 0 (Hikosaka et al. 2004). When photoinhibition in leaves is examined, we have to note that there are considerable intra-leaf gradients of photoinhibition depending on the color of photoinhibitory light and/or on leaf mesophyll anatomy, as has been clarified with a microfiber PAM (Oguchi et al. 2011a, b; Terashima et al. 2016; also see Sect. 2.4).

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Roots of the Two-Step or Mn Hypothesis and Excess-Y(NO) Hypothesis

Since the 1950s, several hypotheses for PSII inactivation have been proposed. According to Tyystjärvi (2013), these include the acceptor-side mechanism, donor-side mechanism, 1O2 production outside the PSII electron transfer path, manganese mechanism, 1O2 production from P680+Pheo- recombination, 1O2 production from recombination of QA- with P680+, and 1O2 production from SnQBrecombinations (see Table 1 in Tyystjärvi 2013). Although all these mechanisms occur under special conditions, particularly in vitro, we focus on two ecologically relevant hypotheses: The Two-step hypothesis or Mn-hypothesis and the acceptorside hypothesis. In this review, we refer to these as the Mn/(Two-step) hypothesis and Excess-Y(NO) hypothesis, respectively. Both visible light (400–700 nm) and UV light (220–400 nm) give damages to PSII (Jones and Kok 1966; Takahashi and Badger 2010) and the Mn/(Two-step) hypothesis claims that the first step of PSII photodamage is inactivation of OEC. When OEC absorbs light, Mn ions are released from OEC (Hakala et al. 2005; Ohnishi et al. 2005). Mn (III/IV) ions show high absorbance in UV and blue wavebands (Bodini et al. 1976; Hakala et al. 2005). Thus, this hypothesis well explains the fact that the photoinhibitory quantum yields of these wavebands are higher than those at the wavebands such as green and red (Jones and Kok 1966; Hakala et al. 2005; Ohnishi et al. 2005). With respect to the Mn/(Two-step) hypothesis, there were some preceding hypotheses. For selective inactivation of OEC, various treatments including heating (Katoh and San Pietro 1967), Tris washing (Yamashita and Butler 1969), chilling in the dark (relevant only in chilling sensitive plants, see Sect. 2.5), high salt treatment (Åkerlund et al. 1982), etc. were developed. Then, under strong light, due to the slow or nil electron flow from H2O to PSII, PSII reaction center is oxidized (P680+), photochemistry is suppressed, and intersystem crossing occurs. The intersystem crossing converts the singlet excited chlorophyll (SChl*) to triplet Chl* (TChl*) and leads further to 1O2 formation (Vass 2011). These mechanisms of PSII photoinhibition are called the donor-side mechanism (Cleland and Melis 1987; Jegerschöld et al. 1990). Inactivation of OEC by UV or blue light in vivo then brings about the damage to D1 by the donor-side mechanism. The OEC activity is affected by pH (Krause and Weis 1991). At low pH in the thylakoid lumen, OEC is prone to be inactivated (Krieger et al. 1993). Thus, the low pH, which occurs in strong light, might increase susceptibility of OEC. In the late 1990s, based on examinations of light dependence of photoinhibition in various materials including Pisum sativum (pea), the photon counter hypothesis was put forward (Anderson et al. 1997, 1998). This hypothesis claimed that, in the presence of an inhibitor of plastid protein synthesis such as lincomycin, photoinhibition occurs in response to the photon exposure, also called dose or fluence (mol photons m-2), irrespective of PFD (mol photons m-2 s-1) levels. Thus, kpi, having a unit of time-1, would be proportional to PFD. Tyystjärvi and

Potato

Cucumber

Barley

Cucumber

Cotton Cotton Ox APX Cotton ox GR

A. thaliana WT Winter rye

Havaux and Davaud (1994)

Terashima et al. (1998)

Tjus et al. (1998)

Sonoike (1999)

Kornyeyev et al. (2003b)

Zhang and Scheller (2004) Ivanov et al. (1998)

Kornyeyev et al. (2003c)

Species Cucumber

Paper Terashima et al. (1994)

100% natural light GH (30/26° C) 100–120 (20°C) 800 (20°C)

100% natural light GH (30/26° C)

220 (25–30°C)

25% (25°C) 30 (RT)

Cucumber 100% light GH (25°C)

350 (23/15°C)

Growth PFD (T) 350 (22–30°C)

Leaf Detached leaf

Leaf disc

Leaf disc Leaf disc

Attached leaf Attached leaf Leaf disc Leaf disc Detached leaf Detached leaf

Leaf disc

Sample Leaf disc

C C C

5 5 4

4 5

10

C C

C

C C C C

C

5

0 4 10 10

C/F C C C C C C C

T 5 7.5 10 3 2 2 5

150 1,600

500

110 110 500 500

200 200 100

200

PFD 220 220 220 3,500 900 3,700 200

2.7 23.04

7.2

1.98 1.98 7.2 7.2

1.44 1.44 2.88

2.16

Exposure 5.94 5.94 5.94 4.2 8.1 6.66 4.32

71.2 92.2

66

38 42 50 67

51 41 80

60

PSI % 18.4 63 83 75 57.1 64 40

(continued)

0.126 0.004

0.058

0.489 0.438 0.096 0.056

0.468 0.619 0.077

0.236

Kpi/ PFD 0.425 0.116 0.047 0.068 0.069 0.067 0.212

Table 1 PSI photoinhibition data. Experimental conditions: species, sample, growth PFD and temperature, photoinhibition temperature (T°C), photoinhibition light type (constant, C, or fluctuating, F), photoinhibition PFD (μmol m-2 s-1), photoinhibition photon exposure (mol m-2), remaining PSI activity (PSI %), and the ratio of the rate constants of photoinhibition to PFD (Kpi/PFD, mol-1 photons m2) of PSI

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Cucumber

A. thaliana WT A. thaliana pgr5

Munekage et al. (2002)

Spinach

Sonoike (1999)

Cucumber

Sonoike et al. (1995)

Potato

Local market

Spinach

Satoh (1970a)

Havaux and Davaud (1994)

350 (22–30°C)

A. thaliana WT

50 (23°C)

350 (22–30°C)

350 (23/15°C)

150 (23/18°C) 150 (5/5°C) Local market (?)

50 (5°C)

250 (5°C)

50 (20°C)

Ivanov et al. (2012)

Growth PFD (T) 250 (20°C)

Species

Paper

Table 1 (continued) Sample Detached leaf Detached leaf Detached leaf Detached leaf Leaf Leaf Thylakoids Thylakoids Thylakoids Thylakoids Thylakoids Thylakoids Leaf disc Leaf disc Detached leaf Leaf Leaf RT RT

5 5 4 25 5 25 5 25 23 25 20

5

5

5

T 5

C C

C C C C C C C C C C C

C

C

C

C/F C

1,500 1,500

600 600 170 170 200 200 100 100 3,500 3,700 60

1,600

1,600

1,600

PFD 1,600

0.9 0.9

4.32 4.32 0.61 0.61 3.6 1.08 1.8 0.54 4.2 6.66 1.08

23.04

23.04

23.04

Exposure 23.04

91 32

32.5 63 88 42 40 70 30 30 96 81.7 100

59.4

108

65.6

PSI % 69.1

0.10 1.26

0.260 0.107 0.209 1.42 0.255 0.33 0.669 2.23 0.010 0.030 0

0.023

0

0.018

Kpi/ PFD 0.016

252 M. Kono et al.

700–800 (25/10°C) 50–60 (25/10°C)

300 (20/16°C) Local market 135 (23°C) 120 (unspecified)

100 (23°C)

60 (23°C)

300 (24/21°C)

120 (unspecified)

Leaf Leaf

Leaf Leaf Leaf Thylakoids Leaf Leaf

Leaf Leaf + Linco Leaf Leaf + Linco Leaf intact Leaf intact Leaf Leaf

25 25

RT RT RT 25 RT RT

RT RT RT RT

RT RT

RT RT

F F

F-R F-R F F F-R F

C C-B F F

C C

C C

240/30 240/30 15,000/0 20,000/0 1,200/0 5,000 /100/ 80 20,000/0 20,000/0

950 950 8,000/60 8,000/60

800 800

800 800

2.16 2.16

0.34 0.34 0.41 2.16 0.64 3.73

4.56 4.56 12.34 12.34

5.76 5.76

5.76 5.76

35 46

89 62 45 15 63 30

96 92 72 32.8

50 80

100 100

0.486 0.638

0.3.43 1.41 1.972 0.878 0.722 0.323

0.009 0.018 0.027 0.090

0.12 0.039

0 0

Photoinhibition treatments were conducted with white lights such as white fluorescence lamps, and white LED, unless otherwise stated. B (Oguchi et al. 2021) and R (Kono et al. 2014, 2017) denote blue and red LEDs, respectively. The light used in the photoinhibitory condition of Satoh (1970a) was 12,000 lux, which was converted to PFD. The fluctuating lights (including intermittent lights), PFD levels used are listed from highest to lowest WT, wild type; pgr5, a mutant of the PGR5/PGRL1 cyclic electron transport pathway of PSI; and crr2-2, a mutant of the NDH cyclic electron transport pathway of PSI. Cotton ox APX and GR denote cotton plants overexpressing stromal ascorbate peroxidase and stromal glutathione reductase, respectively RT means room temperature

Takagi et al. (2019)

Zivcak et al. (2015) Takagi et al. (2016) Kono et al. (2017) Tikkanen and Grebe (2018)

Wheat 6 varieties

A. thaliana WT A. thaliana crr2-2 A. thaliana WT A. thaliana pgr5 Wheat Spinach A. thaliana WT A. thaliana WT

Tsuyama and Kobayashi (2009)

Kono et al. (2014)

Capsicum

A. thaliana pgr5

A. thaliana WT

Oguchi et al. (2021)

Tikkanen et al. (2014)

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Aro (1996) grew Cucurbita pepo (pumpkin) in a growth chamber at 500–700 μmol m-2 s-1 and obtained a very linear relationship between kpi measured in the leaves and the PFD level of the photoinhibitory light. The regression line nearly went through the origin. Unfortunately, neither the light source for plant growth nor that for photoinhibition treatment was detailed in this paper. Because the damage to the manganese cluster occurs depending on the absorption of light by Mn ions, the light source should have had some UV or blue bands. Hakala et al. (2005) showed that PSII of pea leaves treated with lincomycin was photoinhibited in a manner depending on the photon exposure. They also detected release of Mn ions from PSII earlier than the decrease in Fv/Fm. Ohnishi et al. (2005) used thylakoids of Thermosynechococcus elongatus, a cyanobacterium, and found that the electron transport rate from H2O to dichloro-indophenol (DCIP) declined faster than the rate from diphenylcarbazide (DPC) to DCIP. DPC is an electron donor to PSII, bypassing OEC (see Sect. 2.5). They also obtained an action spectrum of PSII photoinhibition. The spectrum indicates strong effects of UV and blue light. The strong effects of UV-A in photoinhibition in Cucurbita pepo (pumpkin) were also shown by Hakala-Yatkin et al. (2010). The term, the Two-step mechanism, was proposed by Ohnishi et al. (2005). On the other hand, Tyystjärvi and coworkers regard this term misleading because it implies the requirement of two steps (E. Tyystjärvi, personal communication, see also Tyystjärvi 2013). Sarvikas et al. (2010) exposed pumpkin and Capsicum annuum leaves to strong light in the presence of lincomycin and measured Fv/Fm and 1/F0-1/Fm. They also isolated thylakoids from these leaves and measured oxygen evolution rates in the thylakoids with dimethyl benzoquinone as an electron acceptor. Further, they isolated thylakoids and PSII membranes and illuminated them with strong light or UV. The decreases in PSII activities with time in all their experiments followed the first-order kinetics. Taking account of the strict sense of the first-order kinetics, they argue that there should not be any room for reversible processes in PSII photoinhibition. Thus, they propose the Mn-mechanism. They claim that the inactivation of the reaction center after the inactivation of the Mn complex is an integral part of the manganese mechanism rather than a separate process. Since the damage to OEC is of primary importance in both Two-step and Mn hypotheses, we denote these hypotheses as the Mn/(Two-step) hypothesis. Although Tyystjärvi and coworker believe that the damage to the Mn complex must be irreversible, we believe otherwise and are currently attempting to show reversibility. Thus, we keep the term Two-step, though in parentheses. Excess was defined as the excitation energy approaching the closed PSII. This fraction was expressed using fluorescence parameters (Demmig-Adams et al. 1996). This hypothesis was based on the acceptor-side hypothesis, which claims that excess energy causes over-reduction of PSII. Because QA- is stable, P680+Pheo- charge recombination occurs to form TChl*. Also excited chlorophylls (Chl*) near the closed PSII reaction centers tend to be converted to TChl* (Vass 2011). Excess introduced by Demmig-Adams et al. (1996) is:

Photoinhibition of PSI and PSII in Nature and in the Laboratory:. . .

E=

F 0m - F 00 F0 - F0 ∙ ð 1 - qP Þ = s 0 0 , 0 Fm Fm

255

ð19Þ

where qP is the fraction of open PSII in the puddle model. qP and (1-qP) had been widely used to express the open and closed fractions of PSII. The latter is specifically called excitation pressure (Maxwell et al. 1995; Gray et al. 1996): qP =

F 0m - F 0s F 0m - F 00

ð20Þ

However, as mentioned above, if the Eq. 9 is generally valid, the fraction of open PSII, qopen, is expressed by Eq. 17. qopen has been called qL, which denotes the fraction of open PSII in the lake model (Kramer et al. 2004). If the qopen linearly decreases with the increase in Fs’ like qP, Eq. 9 does not hold. This is the fundamental difference between the puddle model and lake model. Then, Excess of the lake model version may be expressed as: E0 =

F 0m - F 00 F0 - F0 ∙ 1 - qopen = s 0 0 : 0 Fm Fs

ð21Þ

The measurement of F0’ is not feasible. The measurement of F0’ can be eliminated by using the equation of Oxborough and Baker (1997) F 00 =

F0 , F v =F m þ F 0 =F 0m

ð22Þ

or by using the relationship below (Stefanov and Terashima 2008). F 0v =F 0m = ðF v =F m Þ= F v =F m þ F 0 =F 0m :

ð23Þ

F0/Fm0 was referred to LNP, which reflects non-photochemical energy dissipation loss in PSII: LNP =

k F þ kD þ k isc þ kNPQ F0 : 0 = k þk þk Fm F D isc þ k p

ð24Þ

Kato et al. (2003) grew Chenopodium album plants in two light levels. They also manipulated nitrogen availability to produce leaves showing similar photosynthetic capacity per unit leaf area. When kpi of these leaves were plotted against absorbed PPFD, slopes of the regression lines were different by twofold, while, when kpi were plotted against Excess energy (Demmig-Adams et al. 1996, the unit is μmol m-2 s1 ), regression lines largely overlapped. Kornyeyev et al. (2003a) took account of the changes in the Excess energy during the photoinhibition treatment. Decreases in Fv/

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Fm were linearly related to Excessive light exposure or the cumulated Excess energy in mol m-2. These studies support the Excess theory. If excited chlorophylls around the closed reaction center cause PSII photoinhibition, Y(NO) would be a more appropriate parameter than Excess because it includes kisc. Y(NO) expresses the quantum yield of energy dissipation in PSII by combined pathways of radiative and non-radiative deexcitation reactions which neither lead to photochemical energy conversion, Y(II), nor involve the NPQ-mechanism, Y(NPQ). Indeed, Miyata et al. (2015) found that kpi values in several field-grown plants as well as growth chamber-grown plants were more strongly dependent on Y(NO) ∙ PFD (400–700 nm) than E ∙ PFD. The determination coefficient (R2) for 26 data points for kpi vs. Y(NO) ∙ PFD was 0.84, while that for kpi vs. E ∙ PFD was 0.73.

2.4

Both Mn/(Two-Step) and Excess-Y(NO) Mechanisms Parallelly Occur Under Relatively Mild Experimental Conditions

Oguchi et al. (2009) showed that PSII was photoinhibited by both the Mn/ (Two-step) mechanism and the Excess-Y(NO) mechanism at the same time under rather mild physiological conditions (the mixed hypothesis). Intact Capsicum annuum (capsicum) leaves, which were treated with lincomycin, were photoinhibited in low (30 μmol m-2 s-1), medium (60 μmol m-2 s-1), and high light (950 μmol m-2 s-1) using four different color LEDs: blue (460 nm), green (530 nm), red (640 nm), and white. The leaves were illuminated for different durations so that the photon exposure was uniform in all the experiments. The extent of photoinhibition per photon exposure was greatest in blue, followed by white, green, and red in this order. The order corresponds to the order predicted based on the absorbance spectrum of Mn (III/IV) ions in OEC and differs from that based on the absorbance spectrum of chlorophyll. The results also showed that capsicum leaves were photoinhibited even in low light, where most of the light energy was utilized by photosynthesis and excess energy was negligible. These results support the notion that the Mn/(Two-step) mechanism was involved in the photoinhibition, although it should be noted that Y(NO) is not zero even in the low light. On the other hand, the results also showed that the extent of photoinhibition per photon exposure was higher in high light than in low or medium light, irrespective of the light colors. According to the Mn/(Two-step) mechanism, the Mn release from OEC should be proportional to the photon number absorbed by the Mn cluster and thereby should depend on the photon exposure and should not differ irrespective of the PPFD levels. Thus, the results cannot be explained solely by the Mn/(Two-step) mechanism. Taken together, these results indicate that both mechanisms were parallelly involved in photoinhibition.

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The differences in the gradient of photoinhibition inside a leaf caused by different light qualities reported by Oguchi et al. (2011a, b) also suggested that both mechanisms occurred under mild physiological conditions. Capsicum and Spinacia oleracea (spinach) leaves treated with lincomycin were photoinhibited in blue (400–500 nm), green (500–600 nm), red (600–700 nm), and white (400–700) light at a PPFD of 1,000 μmol m-2 s-1. Because the leaves received light on their adaxial surfaces, extents of photoinhibition were greater near the adaxial surfaces and lower toward the abaxial surfaces. The intra-leaf gradient of photoinhibition was analyzed by inserting a tapered optical fiber (30 μm diameter) connected to a microfiber PAM system. With this system it was shown that the gradient of photoinhibition caused by green light was less steep than that caused by blue or red light. Near the adaxial surfaces of the leaves, the extent of photoinhibition was strongest in blue followed by red and then green, which corresponds to the order predicted based on the absorbance spectrum of chlorophyll and differs from that based on the absorbance spectrum of Mn (III/IV) ions. This result, thus, indicates the involvement of the Excess-Y(NO) mechanism. However, the extent of photoinhibition was highest in blue light even in deeper tissues, where blue light was weaker than green or red light because of the greater absorption by chlorophylls in shallow tissues. The extent of photoinhibition of whole leaf was greatest in blue and followed by white, green, and red in this order, the same order found in Oguchi et al. (2009). These results cannot be explained solely by the Excess-Y(NO) mechanism. Therefore, the analyses of the intra-leaf photoinhibition gradients also support the conclusion that both mechanisms are involved in photoinhibition. Action spectra of PSII photoinhibition in the wild type and chlorophyll b-less mutant of Hordeum vulgare by He et al. (2015) supported occurrence of PSII photoinhibition by these two mechanisms at the same time. Relative contribution of these mechanisms differed depending on the experimental conditions. Zavafer et al. (2015) showed that the addition of an electron donor (DPC) to a suspension of spinach PSII particles reduced the extent of photoinhibition of PSII reaction center. As DPC donates electrons to P680+ via TyrZ, bypassing OEC, the results can be explained by the suppression of the second step of the Two-step mechanism, the D1 inhibition by the donor-side mechanism by the light absorbed by PSII antennae. But the effect of the electron donor was partial, thus the result would indicate involvement of both mechanisms. Schreiber and Klughammer (2013) measured photoinhibition action spectra of dilute suspensions of Chlorella sp. By using dilute suspensions of the unicellular alga, complications with the leaf, such as the intra-leaf gradient of photoinhibition and the difference in the “target depth” depending on the wavelengths of the measuring beam (Oguchi et al. 2011a, b), can be avoided. The result obtained with lincomycin treated Chlorella showed that the action spectra of photoinhibition (at 1,750 μmol m-2 s-1 light) closely followed the PSII absorption spectra above 540 nm, which supports that light absorption by chlorophyll causes photoinhibition (Excess-Y(NO) mechanism). However, below 540 nm the action spectra of photoinhibition did not overlap with the PSII absorption spectra and the extent of photoinhibition under blue light was distinctly higher. The authors suggested that a

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damage to OEC via absorption by Mn ions is a candidate for the cause of photoinhibition.

2.5

Separate Determination of PSII Damaged by the Mn/(Two-Step) Mechanism from Those by the Excess-Y(NO) Mechanism

There have been no simple methods to distinguish PSII damaged by the Mn/ (Two-step) mechanisms from that damaged by Excess-Y(NO) hypothesis. If PSII damage occurs by the Mn/(Two-step) theory in rather weak light, there may be some PSII having inactivated OEC and functional D1 retaining the QA reducing activity. Then, it is possible to detect such PSII. When leaves are kept in the dark for a sufficient period, QA is oxidized and NPQ is fully relaxed. If such leaves are illuminated with a weak measuring beam, the fluorescence level remains minimal (F0). An MTSF given to the leaf reduces all QA in the functional PSII and leads to the maximum fluorescence (Fm). In the conventional PAM fluorometry, reduction of the whole plastoquinone pool and QB by the MTSF is prerequisite for full reduction of QA. However, if there are some PSII with inactivated OEC and active D1, Fm induced by an MTSF would underestimate the QA-reducing capacity in PSII, because the inactivated OEC cannot supply electrons to P680+. However, as already mentioned in Sect. 2.3, referring to Ohnishi et al. (2005) and in Sect. 2.4 referring to Zavafer et al. (2015), by applying DPC, which donates electrons to P680+ (Izawa 1980), QA would be reduced by active D1 by an MTSF even when the OEC is inactivated. Alternatively, in the presence of DCMU, an inhibitor of the electron flow from QA to QB (Trebst 2007), QA would be fully reduced even when the OEC is inactive. Concerning the recent challenge to the QA theory by Sipka et al. (2021), whether QA is reduced by an STSF would be a key experiment. However, we can use an MTSF to get QA reduced even when the OEC is inactive. For artificial electron donors and acceptors, see Izawa (1980), a treasure in this research field. For inhibitors, see Trebst (2007) and his earlier reviews. We employed two experimental models in which OEC is inactivated. In both models, Cucumis sativus (cucumber) grown under white fluorescent lamps were used. In chilling sensitive plants including cucumber, Solanum lycopersicum (tomato) and Phaseolus vulgaris (bean), a treatment of detached leaves at 4°C for 2 or 3 days in the dark selectively inactivates OEC (Margulies 1972; Kaniuga et al. 1978; Terashima et al. 1989; Shen et al. 1990; Higuchi et al. 2003; Kono et al. 2022a). Although the dark-chilling treatment of the detached leaves for 2–3 days is not ecological, this treatment provides a useful model. For detailed effects of various pre-treatments, see Kaniuga et al. (1978). Shen et al. (1990) compared polypeptides of thylakoids and those of PSII particles (Berthold et al. 1981) and found that, after the dark-chilling treatment of leaves, two (PsbP and PsbQ) out of the three extrinsic proteins (PsbO) were

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dissociated from the inner surface of the thylakoid membrane. These proteins were not degraded but remained in the thylakoid lumen. The absence of PsbP and PsbQ in planta causes the Mn cluster to become unstable in the dark (Ifuku et al. 2005). In fact, about two Mn ions out of four per OEC were released from the PSII (Shen et al. 1990). All the electron transport activities other than the water oxidation activity remained unaffected (Shen et al. 1990; Terashima et al. 1991b). The concentration of free linoleic acid (C18:3) in the chloroplasts increased during the dark-chilling treatment of the leaves and decreased again during a subsequent light treatment at 25°C (Kaniuga and Michalski 1978). Thus, in dissociation of the extrinsic proteins and Mn ions, chilling temperature-induced membrane processes would be involved. In cucumber leaf segments infiltrated with water, after the dark-chilling treatment of the leaf segments for 48 h, Fv/Fm measured in the conventional way was 0.47. When 1 mM DCMU solution was infiltrated into the intercellular space, Fv/Fm of 0.65 was obtained. But with 1 mM DPC, Fv/Fm was not different from the water control (Kono et al. 2022a). Perhaps, by infiltration of DPC into the intercellular spaces, the DPC concentration in the thylakoid lumen was not high enough to support the electron donation to PSII bypassing OEC. The method for infiltration is as follows. The leaf segment and the solution were placed in a disposable syringe without a needle. A piston is inserted, and keeping the syringe vertically with the needle port above, air is eliminated by pushing a piston. Then, pressing the needle port against a rubber cap, the piston was pulled and pushed several times until the leaf segment looked transparent. When thylakoids were prepared from the leaves immediately after the dark-chilling treatment, addition of either DCMU or DPC to the thylakoid suspension increased the Fv/Fm levels considerably (Kono et al. 2022a). The increase in Fv/F by these reagents indicates the presence of PSII with inactivated OEC and active D1 with QA reducing activity. We also used a UV-A lamp peaked at 365 nm (half band width was ca. 10 nm) at a PFD of 50 μmol m-2 s-1 to induce damage to OEC. When the light was given from the adaxial side of cucumber leaves for up to 6 h at 25°C, Fv/Fm measured in the water- and DCMU-infiltrated leaves remained unchanged and were both about 0.8. When UV-A was given from the abaxial side, Fv/Fm measured on the abaxial surface decreased with time and became 0.6 at 6 h. Fv/Fm values in water-infiltrated leaf segments were significantly lower than those in DCMU-infiltrated leaf segments; therefore, there must be some PSII with inactivated OEC but with active D1. The results suggest that DCMU-infiltration method can be used to detect PSII with inactivated OEC and active D1 (Kono et al. 2022a). It is known that there are UV screening substances like flavonoids in the leaf epidermis and that synthesis of such substances is induced by UV (Day et al. 1993; Lois 1994 and the references therein). Although we grew cucumber leaves in a growth chamber using white fluorescent tubes having only a small UV-band, the adaxial epidermis obviously had UV screening substances. Referring to some preceding studies such as Pfündel et al. (2007) and Hakala-Yatkin et al. (2010), we set up a simple system to assess whether leaf epidermises have UV screening substances. Using a spectrofluorometer, the excitation spectrum of the PSII chlorophyll fluorescence at 690 nm was measured. A leaf segment was placed obliquely by

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Fig. 1 A simple detection system of UV screening substances in the epidermis and traces for cucumber and spinach. Left diagram: Arrangement of a leaf segment and a cutoff filter eliminating light (λ < 650 nm) in a spectrofluorometer. Right: Excitation spectra for cucumber and spinach leaves normalized at 436 nm. If the epidermis contains much UV screening substances, PSII fluorescence at 690 nm will be small. Note that the fluorescence levels were higher when the abaxial sides of the leaves were illuminated. The cucumber and spinach plants were grown in continuous light from white fluorescence tubes at PPFD levels 400 and 100 μmol m-2 s-1for 12 h/ day. Spinach plants were also grown in a home garden of the last author

the aid of 1 mm thick acrylic plate in an optical cell having four transparent surfaces (Fig. 1). Then, the abaxial or adaxial side of the leaf segment was illuminated with monochromatic light incident on the leaf surface at 45°. Fluorescence emitted from the leaf segment was detected at 90° to the excitation beam. The photomultiplier was protected with a filter that transmits waveband >650 nm (Fig. 1). Cucumber leaves grown at 400 μmol m-2 s-1 contained UV screening substances in the adaxial epidermis. PSII fluorescence emission at 690 nm was hardly detected with the excitation beam (< 360 nm) from the adaxial side. By contrast, the abaxial epidermis transmitted considerable UV even at 300 nm and excited PSII chlorophyll. Then, Mn ions in PSII of mesophyll cells would absorb UV-A and be released from the PSII. In leaves grown at 100 μmol m-2 s-1, the adaxial epidermis transmitted UV-A and thereby PSII was appreciably excited. Spinach leaves also showed a similar dependence on the growth PPFD levels (Fig. 1). Hakala-Yatkin et al. (2010) compared photoinhibition by UV-A between pumpkin plants grown in a glasshouse and those grown in the field. The photoinhibition induced by UV-A was much smaller in the leaves from the field than in those from the glasshouse. The difference was attributed

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to the difference in the abundance of UV screening substance, detected as PSII fluorescence excited at 365 nm. In studies of PSII photoinhibition, leaves, thylakoid preparations, and PSII particles have been used. When the leaf epidermis contains sufficient UV screening materials, OEC would be protected to a considerable extent (Hakala-Yatkin et al. 2010; see also Fig. 1). The sensitivity of PSII in leaves must be dependent on growth conditions, and whether the species accumulate UV screening substances rather constitutively or in response to UV and/or high light. When thylakoid membranes or PSII particles are used, measurements are not interfered by the UV screening substances. However, the results showing high UV sensitivity of thylakoids, PSII particles, etc. should not be simply extended to leaves as has been clearly shown by Hakala-Yatkin et al. (2010). OEC is indeed susceptible to UV and blue light. Thus, when leaf materials that do not have much UV screening substances are used, PSII photoinhibition by the Mn/ (Two-step) hypothesis would occur appreciably. By contrast, when the leaf epidermis has sufficient UV screening substances, PSII photoinhibition by the Mn/ (Two-step) mechanism is greatly reduced. It should be noted, however, that PSII was excited considerably by blue light at 400 nm illuminated from the adaxial side of cucumber leaves even though their adaxial epidermis had UV screening substances (Fig. 1). Thus, illumination of the lincomycin treated leaves with weak blue light at 400 nm for a long time, and detection of PSII with inactivated OEC and active D1 by the DCMU-infiltration method (Kono et al. 2022a), may be an efficient way to detect the possible involvement of the Mn/(Two-step) mechanism in an ecological context.

2.6

Does PSII Repair Occur in Strong Light?

It is frequently mentioned that photoinhibited PSII in the leaves is repaired in high light (He and Chow 2003; Chow et al. 2005). As outlined below, it is probable that this statement may be only relevant to the PSII damaged by the Excess-Y(NO) mechanism. Miyata (Doctoral dissertation 2015, unpublished), and subsequently Kono et al. (2022a) selectively inactivated OEC in cucumber leaves by the dark-chilling treatment, rewarmed these leaves to 25°C in complete darkness, and illuminated them with light at various PPFD levels for 30 min. After the dark-chilling treatment, Fv/Fm measured in the leaf segments infiltrated with water was around 0.45. The maximum increase in Fv/Fm up to 0.7 was observed when the leaves were illuminated at 5–10 μmol m-2 s-1 at 25°C. The light stronger than this range caused further decreases in Fv/Fm probably due to PSII photoinhibition by the donor-side mechanism (Kono et al. 2022a). A recent study using the rapid-scan time-resolved Fourier transform infrared (FTIR) spectroscopy combined with the attenuated total reflection (ATR) technique (Sato et al. 2021), showed that, in reactivation of OEC, two light reactions are involved and there is a slow dark process between them, which is responsible for a

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low quantum yield of the whole reactivation. This is consistent with the fact that reactivation occurred only in weak constant light. It is also worth mentioning that the PPFD levels that induce maximum OEC reactivation ranged from 5 to 10 μmol m2 -1 s , the level of ordinary lighting for the laboratory benches. Thus, to study OEC repair, we need to conduct experiments in nearly complete darkness. Kono et al. (2022a) illuminated cucumber leaves with UV-A at 50 μmol m-2 s-1 from the abaxial side for 90 min to damage OEC. Then, these leaves were illuminated with strong red light at 2,000 μmol m-2 s-1 for 30 min to induce PSII photoinhibition by the Mn/(Two-step) mechanism. In these leaves, Fv/Fm was around 0.4 and no recovery was observed by illumination with red light at PPFD levels ranging from 50 to 200 μmol m-2 s-1 for 120 min. On the contrary, in the leaves illuminated with strong red light for 90 min to induce PSII photoinhibition by the Excess-Y(NO) mechanism, Fv/Fm recovered considerably by the illumination with red LED at 50 to 200 μmol m-2 s-1 for 120 min. These lines of evidence may indicate that, when OEC is firstly inactivated, rapid PSII repair does not occur (Kono et al. 2022a). When the UV-A treatment was replaced by the chilling treatment in the dark for 48 h, and PSII was photodamaged by strong red light, a rapid PSII recovery was not observed either (Unpublished data of the authors and S. Matsuzawa, a former master student). PSII photoinhibition is accelerated at high or low temperatures (Powles 1984). Tsonev and Hikosaka (2003) examined whether this was due to the increase in kpi or the decreases in krec in Chenopodium album. kpi showed minimum value at around growth temperature and increase with the decrease or increase in the temperature during the photoinhibition treatments. kpi was positively related to Excess energy. However, when the regression line was extended to zero Excess energy, there was a large positive interception. Thus, for different temperature ranges, the Excess-Y(NO) hypothesis cannot be directly applied. More importantly, krec was more sensitive to temperature. It was highest around growth temperature and decreased with the decrease in the treatment temperature. krec at 11°C was lower than the maximum by one order of magnitude. Mattila et al. (2020a) examined PSII photoinhibition temperature at 4°C and 22°C in four ecotypes of Arabidopsis thaliana. They found that values of kpi at 4°C were largely comparable to those at 22°C. By acclimation of A. thaliana plants at 4°C, kpi measured at 4°C decreased in two ecotypes which might relate to accumulation of flavonoids in the epidermis in these ecotypes. Several studies reported that krec is affected by the growth light level (He and Chow 2003; Miyata et al. 2012, 2015). In such studies, the difference in the temperature between the growth temperature and the temperature during photoinhibition/repair measurement should be considered. Miyata et al. (2015) calculated Q10 for the recovery based on the temperature dependence of krec reported by Tsonev and Hikosaka (2003) for Chenopodium album. Because mean outdoor air temperature during the study using field-grown plants of Miyata et al. (2015) was within the same range, an exponential curve was fitted to their data ranging from 11 to 30°C. When T1 and T2 are the air temperature during the photoinhibition/repair treatment and the mean air temperature at the field site, respectively, the krec corrected for the field temperature T2 is called k0 rec:

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Determination coefficients for k0 rec vs. daily PPFD (400–700 nm) were 0.70 (n = 20) and 0.82 (n = 18) for the plants photoinhibited at 400 and 1,200 μmol m-2 s-1, while corresponding values for krec vs. daily PPFD (400–700 nm) were 0.54 and 0.52 (Miyata et al. 2015).

3 PSI Photoinhibition PSI is a plastocyanin/ferredoxin photooxidoreductase. The core complex is formed as a pseudo homodimer (PsaA and PsaB) having a reaction center chlorophyll dimer (chlorophyll a and chlorophyll a’). Each of PsaB and PsaA has cofactors, namely Trp, three chlorophyll a molecules including (A0), and phylloquinone (A1). Unlike PSII, charge separation occurs on either side. The two routes merge at the iron-sulfur center FX which is embraced by the PsaB and PsaA proteins, while FA and FB are cofactors in a third subunit PsaC protein (Rutherford et al. 2012). Although there had been some in vitro studies showing photoinhibition of PSI (Satoh 1970a, b, c; Inoue et al. 1986, 1989), there were few studies showing PSI photoinhibition in vivo (Powles 1984; Öquist et al. 1987) until 1994.

3.1

Cucumber as a Chilling Sensitive Model Plant for PSI Photoinhibition at Low Temperature

As mentioned in Sect. 2.5, cucumber, tomato, bean, etc. have been used as the models of chilling sensitive plants. When these plants are exposed to the light at low temperatures, photosynthesis is irreversibly damaged. Accidental exposure to low temperatures of these plants grown in greenhouses in winter causes severe damages. However, the irreversibly damaged site had not been identified until 1994. In search for the primary irreversible damage site, it was found that, at low temperatures below 10°C, a moderate light at 100 μmol m-2 s-1 PPFD caused photoinhibition of PSI in cucumber leaves (Terashima et al. 1994; for reviews, see Sonoike 1996, 2011). As this damage does not occur at low O2, PSI photoinhibition is a photooxidative damage. Table 1 compiles the data of PSI photoinhibition. In this list, cucumber and Gossypium hirsutum (cotton) are chilling sensitive. The Kpi/PFD value in cotton is large, comparable to cucumber at 10 °C. Appreciable PSI photoinhibition occurred at low temperatures in intact attached cucumber leaves (Terashima et al. 1998). The plants were placed in a showcase type refrigerator kept at 5°C. However, the leaf temperature would be higher than 5°C, which might explain the lower Kpi/PFD value than that in the leaf discs floated on water. It is noted that PSI of chilling-tolerant

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species can be also photoinhibited at low temperatures (Ivanov et al. 1998). When chilling-tolerant species are hardened by growing at chilling temperatures in high light, the extent of PSI photoinhibition may become smaller (Ivanov et al. 1998; Teicher et al. 2000). It is also interesting to point out that the Kpi/PFD of PSI photoinhibition becomes remarkably greater when thylakoids were isolated from chilling-tolerant spinach leaves and photoinhibited at a room temperature (Satoh 1970a, b, c; Sonoike 1996). When thylakoids are prepared in the absence of ascorbate, ascorbate peroxidase, the key enzyme of Asada cycle (see below), is inactivated. Even at a room temperature, PSI photoinhibition can be observed with intact capsicum leaves illuminated with blue or white LED at 950 μmol m-2 s-1 (Oguchi et al. 2021). Therefore, we should not consider that PSI photoinhibition occurs only in chilling sensitive species or at low temperatures. It has been also known that treatment of the leaves with repetitive hypersaturating flashes induces remarkable PSI photoinhibition in A. thaliana (Tsuyama and Kobayashi 2009), Helianthus annuus (Sejima et al. 2014), and Triticum aestivum (Zivcak et al. 2015; Takagi et al. 2019). The high efficiency for induction of PSI photoinhibition is reflected to high Kpi/PFD values. This system has been used for exploring mechanisms for protection of PSI from photooxidative stresses (Sejima et al. 2014; Takagi et al. 2019). For the effects of more moderate fluctuating light treatments, see Sect. 3.3. Kpi/PFD values are also high in such moderate fluctuating light treatments. The primary damage site in PSI in cucumber leaves was identified by ESR spectroscopy (Sonoike et al. 1995). After the treatment of cucumber leaves at chilling temperatures in the light, thylakoids were prepared and their ESR spectra were examined. The spectra indicate that the iron-sulfur centers, FA/FB and FX on the acceptor side of PSI were damaged. When more severe treatments were applied, destruction of P700 and chlorophyll-protein complexes followed (Sonoike and Terashima 1994; Tiwari et al. 2016). The consequence was similar to that found in a preceding in vitro study by Inoue et al. (1989). In many studies using thylakoid membranes, methyl viologen (MV) has been used as an electron acceptor from PSI. Worse, the rates at saturating light have been assessed. However, this reagent accepts electrons not only from FA/AB at the membrane/protein surface, but also from FX in the membrane because of its lipophilic nature (Fujii et al. 1990; Sonoike and Terashima 1994). Because MV was used in the previous studies including ours (Terashima et al. 1989, 1991b), PSI photoinhibition at FA/FB was not noticed. By contrast, Terashima et al. (1994) added ferredoxin to the thylakoid suspension and used NADP+ as an electron acceptor; in that case, PSI photoinhibition was indeed observed. When electron acceptors on the reducing side of PSI are mostly reduced due to suppression of CO2-fixation by low temperature and/or scarcity of ATP (see below), the electrons from PSI tend to reduce O2 to form O2- (superoxide). Disproportionation of superoxide occurs spontaneously or is catalyzed by superoxide dismutase to produce H2O2 and O2. H2O2 is readily reduced by ascorbate peroxidase. Dehydroascorbate and monodehydroascorbate are reduced by NADPH. Chemical formulae of these reactions are as follows (Asada 1999; Miyake 2010)

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O2 þ e - → O2 2 O2 - þ 2Hþ → H2 O2 þ O2 ascorbate þ H2 O2 → dehydroascorbate þ 2 H2 O 2 ascorbate þ H2 O2 → 2 monodehydroascorbate þ 2 H2 O NADPH þ dehydroascorbate ðor 2 monodehydroascorbateÞ → NADPþ þ ascorbate ðor 2 ascorbateÞ The ultimate electron donor of these reactions is H2O split in PSII. By a train of the above reactions via PSII, Cyt b6/f, and PSI, electrons are transferred from water to water. Thus, this is called the water-to-water cycle (WWC). This is also called Asada cycle and the pathway from PSI to water is called Mehler ascorbate peroxidase (MAP) pathway. Since these reactions use one NADPH per two electrons, the cycle is useful not only in safely scavenging reactive oxygen species but also in alleviation of over-reduction of the electron transport pathway. The net flux of this electron flow could be 10–20% that in the linear electron transport pathway (Miyake 2010). However, at low temperatures, the activity of the Asada cycle may not be enough to scavenge these reactive oxygen species (Miyake 2010). In cucumber leaves illuminated at a PPFD level of 100 μmmol m-2 s-1 at 5°C, PSII quantum yield, Y(II), was around 0.2 and the electron transport rate from PSII to PSI was ~7 μmol e- m-2 s-1. The rate corresponds to 20 mmol e- (mol Chl) –1 s-1. Assume that the electron acceptor from PSI is solely O2, H2O2 production rate will be 10 mmol H2O2 (mol Chl) –1 s-1. Thylakoid APX activity measured at 5°C was less than this value (Terashima et al. 1998). When H2O2 accumulates, the Fenton reaction occurs at the reduced iron-sulfur centers, FA, FB, and/or FX (Asada 1999): Fe2þ þ H2 O2 → Fe3þ þ OH･ þ OH OH･ (hydroxyl radical) is a strong oxidant and destroys iron-sulfur centers (Yordanov and Velikova 2000; Sonoike 2011). PSI photoinhibition is completely suppressed by addition of DCMU. Thus, the electron donation to PSI is a prerequisite for PSI photoinhibition to occur. With the increase in the PPFD level, the electron transport rate toward PSI initially increases and then attains the saturation level. With the increase in H+ concentration in the thylakoid lumen, the electron transfer through Cyt b6/f, or the reaction:

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PQH2 → PQ þ 2 e - þ 2Hþ , which occurs in the lumen side in the thylakoids, is suppressed. This is called “photosynthetic control,” which was first proposed by West and Wiskish (1968). An unavailability of PQ would also limit Cyt b6/f turnover in high light. This putative mechanism has been termed the reduction-induced suppression of electron flow, RISE, by Shaku et al. (2016). This can be regarded as another side of the photosynthetic control (Shimakawa and Miyake 2018b). Importance of the photosynthetic control has been argued (Tikhonov 2014; Miyake 2020; Malone et al. 2021). Why are chilling sensitive plants more susceptible to PSI photoinhibition? We have been examining the reversible damage to H+-ATPase as a trigger of PSI photoinhibition (Terashima et al. 1989, 1991a, b, 1998). When chilling sensitive cucumber leaves were illuminated at low temperatures, the head part of the H+ATPase (CF1) was detached from the thylakoids or association to the thylakoid membrane was weakened. Thus, when the thylakoids were prepared immediately after the chilling treatment of leaves in the light, considerable amounts of CF1 polypeptides were lost from the thylakoids to the supernatant. When the leaves were treated in the light at chilling temperature, NPQ was largely suppressed. Under such conditions, a rapid decay of the electrochromic shift at 515 nm might be expected because the H+-channel of CF0 was exposed to the stroma. However, the decay was accelerated only to a limited extent. Thylakoids isolated from light-chilled cucumber leaves lost considerable CF1. In the thylakoid preparation, however, decay of the electrochromic shift at 515 nm was not accelerated. When a protonophore/ ionophore such as carbonyl cyanide m-chlorophenylhydrazone (CCCP) or gramicidin was added, the decay was greatly accelerated, while with methyl amine, a potent amine-type uncoupler, the decay was not accelerated appreciably (data not shown). We claimed that the thylakoids are uncoupled by the light-chilling treatment and that the leakage through the CF0 channel is rather slow (Terashima et al. 1989, 1991a, b). However, mainly because the unmistakably fast decay at 515 nm was not observed, this view was not accepted yet by some groups (Wise et al. 1990, Oxborough and Ort 1995). In Fig. 2, quenching analysis (Q-analysis) curves measured in the leaf segments in the course of the light-chilling treatment at 4°C and the PPFD of 100 μmol m-2 s1 (white light from RBG LEDs) are shown. It is noted that NPQ development was suppressed by the treatment only for 60 min (Fig. 2c). This can be explained by the uncoupling of CF1 of H+-ATPase from the thylakoids. The quantum yield of PSII photochemistry, Y(II), measured at 23 °C decreased from 0.68 (Fig. 2a) to 0.1 at 2 h with the increasing damage to PSI (Fig. 2d). In Fig. 3, the rise and decay of 515 nm absorbance induced by a single turnover flash are compared. The trace obtained in an untreated control leaf kept in the dark showed some increase of 515 nm absorbance at first and then a slow decay (Fig. 3a). The increase has been attributed to an increase in the transmembrane potential difference caused by H+ translocation via a Q cycle in Cyt b6/f (Chow and Hope

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Fig. 2 Quenching analysis curves in the leaf segments after the light-chilling treatment. Cucumber leaf segments were treated at 4°C and a PPFD of 100 μmol m-2 s-1. (a) Control leaf segment kept in the dark at 23°C (RTD); (b) leaf segment treated at 4 °C in the light for 30 min (LTL-30 min); (c) LTL- 60 min; and d, LTL-120 min. Fluorescence was measured with a Dual PAM (Walz, Germany) at 23°C. The PPFD level of the actinic light (red LEDs at 635 nm) was 100 μmol m-2 s-1. As Fm0 levels were nearly constant in C and D, development of NPQ was suppressed by the chilling treatment in the light for 60 to 120 min. This may be explained by the detachment of CF1 of H+ATPase from the thylakoids. The quantum yield of PSII photochemistry, Y(II) = (Fm0 – Fs’)/Fm0 , measured at 23°C decreased from 0.68 (control) to 0.1 at 2 h with the increasing damage to PSI

2004). By irradiating the same cucumber leaf at 100 μmol m-2 s-1 for 20 min and 23°C, H+-ATPase was activated, and the decay was markedly accelerated, indicating a rapid H+ efflux though H+-ATPase (Fig. 3b). H+-ATPase was de-activated by the subsequent dark treatment for another 20 min (Fig. 3c). In the leaf treated at 4°C in the light at 100 μmol m-2 s-1 for 30 min, some de-activation effect of H+-ATPase by the dark treatment for 20 min at 23°C was observed as a small peak at 10 ms (Fig. 3d). The reactivation effect was not detected in the leaf treated for 2 h (Fig. 3e).

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Time (ms) Fig. 3 Changes in 515 nm absorbance in the leaf segment induced by a 10 μs single turnover flash measured at 23°C. (a) Control leaf segment kept in the dark (RTD); (b) RTD leaf segment was activated in the light at 100 μmol m-2 s-1 for 20 min at 23°C (RTD-L); (c) RTD-L leaf segment was again kept in the dark for 20 min (RTD-L-D); (d) leaf segment treated at 4°C in the light at 100 μmol m-2 s-1 for 30 min and kept in the dark for 20 min at 23°C (LTL-30 min-D); (e) leaf segment treated at 4°C in the light at 100 μmol m-2 s-1 for 2 h was kept in the dark for 20 min at 23° C (LTL-2h-D). The activation and de-activation of H+-ATPase were observed in the untreated control leaf. Although some de-activation by 20 min dark treatment was observed in D, the effect of dark inactivation was largely eliminated in (e)

The loss of the slow 515 nm absorbance increase could be attributed to the rapid efflux of H+ from the lumen due to the uncoupling of CF1 of H+-ATPase, overwhelming any uptake of H+ from the stroma in a Q cycle at Cyt b6/f. The results shown in Figs. 2 and 3 indicate that, compared with ionophoremediated transport of protons across the thylakoid membranes, the leakage of H+ through CF0 is slow as we argued previously (Terashima et al. 1991a). When the intact H+-ATPase is activated, the decay is accelerated considerably (Fig. 3b), but still much slower than the decay in the presence of the protonophores. The “slow” H+ leakage through the exposed CF0 would be sufficient to prevent ΔpH formation, which explains the absence of NPQ formation (Fig. 2). Then, we need to carefully conduct diagnoses based on the 515 nm absorbance changes (Cruz et al. 2005; Klughammer et al. 2013), particularly in plants in which H+-ATPase is damaged. The apparently “slow” H+ leakage might be a consequence that could be explained as follows (W.S. Chow, personal communication). After uncoupling of CF1 from CF0, rapid efflux of H+ from the lumen may not be matched by rapid movement of other ions, in which case a diffusion potential is set up (tending to make the lumen more negative), thereby inducing an influx of K+ from the stroma via some potassium channels near the ATP synthase. Charge compensation from K+ could then slow the decay of the 515 nm electrochromic signal, thereby giving the impression

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that the efflux of protons from the lumen was not rapid. This working hypothesis should be tested soon. TPK3 was once postulated as such K+ ion channel (Carraretto et al. 2013). However, the presence of TPK3 in the thylakoids has been doubted. Höhner et al. (2019) claimed that TPK3 would be a vacuolar channel. Nevertheless, K+ channels in thylakoid membranes have been directly measured (Tester and Blatt 1989). At low temperatures, the rates of Calvin-Benson-Bassham (CBB) cycle/photorespiration (PR) pathway and the Asada cycle are generally lowered. In chilling sensitive cucumber, CF1 of H+-ATPase is detached and suppresses ATP synthesis. Then, both CBB cycle and PR pathway stop. Thus, electron acceptors from PSI are scarce in chilling sensitive cucumber. Then, O2 would be a major electron acceptor. Concerning the donor side of PSI, the electron flow to PSI may not be suppressed in chilling sensitive cucumber, because the photosynthetic control does not work due to the uncoupling of the thylakoid, while, in chilling-tolerant plants, the photosynthetic control functions and electron flow to PSI is suppressed. These would cause the difference in PSI sensitivity between the chilling sensitive cucumber and tolerant plants. Whether the uncoupling occurs should be tested in other chilling sensitive plants. An examination of PSI quantum yields for photochemistry, non-photochemical energy dissipation due to limitation of electron donors, Y(ND) and for non-photochemical energy dissipation due to limitation of electron acceptors, Y(NA), and the conventional Q analyses will be useful for such a survey (see Klughammer and Schreiber 1994). When used carefully, analyses of the electrochromic shift decay at 515 nm (Cruz et al. 2005; Klughammer et al. 2013) would be also useful. If the photosynthetic control is strong, the electron flow from Cyt b6/f to PSI will be suppressed and P700+ will be formed. Under such conditions, Y(ND) should be much greater than Y(NA). Very recently, Takeuchi et al. (2022) successfully categorized cucumber varieties which are resistant to light treatment at 4°C by analyzing Y(ND) and Y(NA). The varieties that showed high Y(ND) and Y(NA) after the light treatment at 4°C turned out to be chilling resistant. The causes and consequences of PSI photoinhibition in chilling sensitive plants are summarized as follows (Fig. 4). The low temperature and light together induce uncoupled conditions of H+-ATPase, thereby suppressing both development of ΔpH and ATP synthesis. Then, neither the development of NPQ nor the suppression of the electron transport by the photosynthetic control occurs. In moderate light, the electron flow to PSI is not suppressed. Then, P700 is reduced, and PSI drives the electron flow to O2. Because CBB cycle and PR pathway are suppressed, not only by low temperatures but also by the scarcity of ATP, O2 would be virtually a sole electron acceptor. Since the rate of Asada cycle is suppressed by low temperatures, H2O2 is not scavenged completely. In the presence of H2O2 and the reduced FeS centers (Fe2+), the hydroxyl radical is formed and readily destroys FeS centers such as FA/FB and FX. The uncoupling of the H+-ATPase would not occur in the chilling-tolerant varieties/species, in particular, when they are hardened. Then, the photosynthetic control would work in chilling-tolerant plants and the electron flow from Cyt b6/f to PSI will be suppressed and P700+ will be formed. P700+ acts as a safe quencher of

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Low temperature CBB PR ASADA Cycle

CBB ASADA Cycle PR PSI H2O2

H+Î Strong photosynthec control Fig. 4 Schematic diagrams of PSI photoinhibition and protection. Effects of the chilling treatment in the light on thylakoids in chilling sensitive plants (above) and effects of sudden exposure to strong light in chilling-tolerant plants at an ordinary temperature (below). Dissociation of CF1 suppresses ATP synthesis and development of ΔpH. No photosynthetic control occurs. Because low temperature and scarcity of ATP suppress CBB cycle and PR pathway, O2 is the main electron acceptor from PSI. There is a considerable electron flow from Cyt b6/f to O2 via PSI. Low temperature also suppressed Asada cycle activity, then H2O2 accumulates near the Fe-S centers. When the leaf is suddenly exposed to strong light, bursts of the linear electron transport, PSI CEF, and coupled H+ pumping occur. Since accumulation of H+ is much faster than the H+ efflux through H+-ATP synthesis, ΔpH is built up and the photosynthetic control mechanism operates to suppress the electron flow. In the sudden strong light, PSII tends to be closed and the spillover of excitation from PSII to PSI occurs. The low rate of electron transport from Cyt b6/f to PSI and increased excitation spillover to PSI, P700 tends to be oxidized (P700+) to be the safe quencher. In the pgr5 mutant, the burst of PSI CEF is weak and ΔpH is not large enough to suppress the electron flow by the photosynthetic control. Then, there will be considerable electron flow from Cyt b6/f to O2 via PSI. For the role of spillover, see Sect. 3.4

the excess excitation energy (Trissl 1997; Barth et al. 2001; Shimakawa and Miyake 2018a; Furutani et al. 2020) and thereby protects PSI from photoinhibition. It has been shown that β-carotene in PSI plays a crucial role in protection of PSI from photoinhibition. Depletion of β-carotene from the PSI core severely impairs photoprotection (Cazzaniga et al. 2012). These may explain why PSI in the chilling-tolerant plants is more resistant to PSI photoinhibition. For reviews, see Karapetyan (2008), Rutherford et al. (2012) and Miyake (2020).

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271

PSI Photoinhibition in the pgr5 Mutant

When excess energy in PSII antennae is dissipated as heat, leaf fluorescence level decreases. The PROTON GRADIENT DEFICIENT 5 mutant was found through screening of A. thaliana mutants emitting high fluorescence for up to 1 min after the onset of high light illumination (Munekage et al. 2002). Munekage et al. (2002) characterized the mutant grown at a PPFD level of 50 μmol m-2 s-1 and found that, in the mutant, PSI was photoinhibited during high light illumination at 1,500 μmol m-2 s-1 for 10 min even at a room temperature. In the pgr5, P700 was reduced in the moderate light. In high light it is largely reduced. Given that NPQ develops in response to low pH in the thylakoid lumen, pH in the pgr5 mutant, at least immediately after the start of strong light illumination, would not be low enough to suppress the electron flow in Cyt b6/f by the photosynthetic control. This inversely highlights a critical function of the PGR5 in the photoprotection of PSI: the burst of the cyclic electron flow and H+ pumping by the PGR5 pathway upon the shift to strong light (Fig. 4). It has been argued that the PSI cyclic electron transport is needed in the steady state to supplement the ATP to meet the ATP/NADPH ratios for CBB cycle (3ATP/ 2NADPH) and photorespiration (3.5 ATP/2NADPH, for simulations, see Kramer and Evans 2011). It is established that one rotation of CF1 leads to production of 3 ATPs (Adachi et al. 2007). On the other hand, whether the number of protons needed for one rotation of CF1 is the same as the number of c subunits of CF0, namely 14, has not been settled (Steigmiller et al. 2008; Noji et al. 2017). Steigmiller et al. (2008) measured the H+/ATP ratios for the H+-ATPases from chloroplasts and Escherichia coli embedded in the liposome. Although the numbers of c subunits are 14 and 10, for chloroplast and E. coli H+-ATPase, respectively, H+/ATP measures were 4.0 for both ATPases. If 14 H+ is needed, H+/ATP ratio would be 14/3 = 4.67. Given that the net increase in H+ in the thylakoid lumen in linear electron transport from water to NADP+ is 6 H+ (2 from H2O oxidation and 4 by PQH2 oxidation plus the Q cycle), then ATP/NADPH ratio will be 1.29, smaller than the ratio of 1.5 for the CBB cycle. However, if 4 H+/ATP is applied, ATP/NADPH ratio will be 1.5. Whether cyclic electron transport is needed to supplement steady-state linear electron flow has been also argued based on non-destructive measurements of electron transport activities. Furutani et al. (2022) claimed that the cyclic electron transport is not necessary in steady-state photosynthesis in continuous light. Besides the above problem, cyclic electron transport is useful as a sudden brake of the electron flow from Cyt b6/f to PSI by lowering pH in the thylakoid lumen by means of the photosynthetic control. Thus, the role of PGR5 can be understood as a factor that suddenly enhances the photosynthetic control in the scenarios shown in Fig. 4. In the pgr5 mutant, the bursts of PSI-CEF and H+ pumping are weak, and thereby, the electron flow to PSI is not sufficiently suppressed by the photosynthetic control, which keeps P700 in the reduced form and increases the electron flow to O2.

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PSI Is Susceptible to “Artificial” Fluctuating Light

In natural environments, intensity and spectral composition of light fluctuate. Although several effects of the fluctuating light on photosynthesis have been studied (for reviews, see Pearcy 1990; Kono and Terashima 2014; Yamori 2016), many problems remain unsolved. In the Excess/Y(NO) hypothesis, NPQ plays an important role in preventing photoinhibition of PSII. One is to lower excess energy or Y(NO). The other is to suppress ROS production. However, when they are grown under constant light, none of the single mutants of important players of NPQ formation, such as xanthophyll cycle and PsbS, shows dramatic phenotype. In contrast, when these mutants were grown in the field, or in the growth chamber with the alternating high- and low-light periods (hereafter termed fluctuating light), performances of these mutants were markedly suppressed (Külheim et al. 2002). It has been also known that, when grown in constant light, any single mutant of the cyclic electron transport pathways, irrespective of PGR5/PGRL1 or NADH DEHYDROGENASE-LIKE (NDH), shows only weak phenotype, if any. Tikkanen et al. (2010) grew several mutant lines of A. thaliana in fluctuating light and found that the pgr5 mutant did not grow well and eventually died. The lethal phenotype was due to the damage to PSI (Suorsa et al. 2012). PSI photoinhibition by fluctuating light, however, can be observed in much shorter terms. Moreover, PSI photoinhibition occurs not only in the pgr5 mutant but also in the wild type. Kono et al. (2014) treated leaves of A. thaliana with the light from red LEDs alternating every 2 min at PPFD levels of 240 and 30 μmol m2 -1 s for 40 min. In this experiment, plants were grown at 90–100 μmol m-2 s-1 constant light provided by white fluorescent tubes in 8 h light/16 h night cycle. Thus, the PPFD levels used in the fluctuating light were moderate. We observed PSI photoinhibition not only in the pgr5 mutant but also in the wild type. At low O2 levels such as 2.7% and 0%, PSI photoinhibition hardly occurred not only in the wild type but also in the pgr5 mutant. Thus, PSI photoinhibition induced by the fluctuating light is a photooxidative stress. When the light changed from low light to high light, a gush of the electron flow to PSI would occur. Although the electron flow from Cyt b6/f is suppressed with the ΔpH development by linear electron transport and cyclic electron transport boosted particularly by PGR5/PGRL1 pathway in the wild type, the sudden brake was weak in the pgr5 mutant, which explains the difference in the degree of photoinhibition between the wild type and pgr5 mutant (Kono and Terashima 2016). These features are all understood by the mechanisms for PSI photoinhibition and protection shown in Fig. 4. It is well known that the D1 protein that carries the PSII reaction center turns over rapidly (for quantitative assessments, see Miyata et al. 2012; Murata and Nishiyama 2018; Yi et al. 2022). By contrast, as mentioned already, the turnover of PSI is much slower (Sonoike and Terashima 1994; Kudoh and Sonoike 2002; Li et al. 2018; for reviews, see Yordanov and Velikova 2000; Sonoike 2011). Because light in natural

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environments fluctuates, the very susceptible nature of PSI indicates that PSI in plants in natural fluctuating light would suffer from photoinhibition. Yet, it does not appear that plants in natural environments severely suffer from PSI photoinhibition. We, thus, tested the effects of far-red (FR) light, which is abundant in natural light but almost nil in red LEDs, and found that the PSI photoinhibition was mostly suppressed by addition of FR light to the fluctuating light (Kono et al. 2017). Therefore, PSI photoinhibition in natural environments with abundant FR would not be serious. Interestingly, in the protection of PSI from the fluctuating lightinduced photoinhibition by FR light, NDH pathway was more important than PGR5/ PGRL1 pathway. The similar trends have been also confirmed in Oryza sativa and Nicotiana tabacum (unpublished observation of the authors). At this stage, we cannot explain why the PGR5 pathway suppresses PSI photoinhibition in the fluctuating light provided by red LEDs more effectively than the NDH pathway (Kono and Terashima 2016), whereas NDH pathway is more important in the alleviation of PSI photoinhibition by FR light (Kono et al. 2017). Suppression of PSI photoinhibition by FR light may not be only attributable to the acceleration of PSI-CEF. For example, the activity of KEA3, a K+-H+ antiporter, is regulated by FR light (see Sect. 3.5). In cyanobacteria, various functions including HCO3- transport are coupled to the cyclic electron transport mediated by the NDH pathway (Ogawa and Mi 2007; Battchikova et al. 2011). Thus, in the suppression of fluctuating light-induced PSI photoinhibition by FR, some other factors associated with the NDH pathway may be involved.

3.4

Shade Plant PSI Is Resistant to Sudden Sunflecks

We conducted a survey to clarify whether PSI is generally susceptible to the fluctuating light. Indeed, PSI photoinhibition was readily induced by fluctuating light from red LEDs in many plants. However, PSI in the leaves of Alocasia odora, a shade-tolerant plant, was resistant to the fluctuating light, especially when the plants were grown at very low light at 10 μmol m-2 s-1. Concerning PSII photoinhibition, it is established that high light-grown leaves are more resistant (Öquist et al. 1987; Anderson and Aro 1993; Miyata et al. 2012, 2015), although there are some exceptions (Öquist et al. 1992). Various photosynthetic properties have been compared between sun and shade plants or between high- and low-light grown plants (for reviews, see Boardman 1977; Björkman 1981; Anderson 1986; Terashima and Hikosaka 1995; Schöttler and Tóth 2014; Flannery et al. 2021). Based on a meta-analysis of data on the photosynthetic components in relation to growth light conditions, Hikosaka and Tersahima (1995) categorized the photosynthetic components. Among the thylakoid components, the contents of cytochrome f (Cyt f ) and H+-ATPase on a leaf area basis (Cyt farea and H+-ATPasearea) are proportional to the maximal CO2 fixation rate on a leaf area basis and the contents of such components on a chlorophyll (Chl) basis increase with the growth PPFD level. On the other hand, P700/Chl is virtually

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constant irrespective of the growth light levels. Schöttler and Tóth (2014) have also recognized the same trends. As mentioned above, PSI photoinhibition occurs when the PSI photochemistry is limited by the electron flow on the acceptor side (reducing side) rather than by the electron donation from the donor side (oxidizing side): Y(ND) < Y(NA) (Klughammer et al. 2013). The redox state of P700 is sensitively influenced by the balance of these limitations. When electron transport is limited on the donor side or Y(ND) is large, P700 tends to be oxidized. As mentioned above, P700+ would act as a safe quencher of the excess excitation energy. We grew A. odora at several PPFD levels and examined their photosynthetic traits to clarify the factors which make the low light-grown A. odora resistant to the fluctuating light-induced PSI photoinhibition. Regression analyses revealed that leaves of high Chl content (Chlarea), high P700area, and low Cyt f/Chl were resistant to PSI photoinhibition by the fluctuating light. Electron flow to the respective P700 molecules should decrease with the increase in P700area and with the decrease in Cyt f/P700. These would contribute to maintaining a high [P700+] in high light (HL) phases of the fluctuating light. Chow et al. (1988) reported that, with the decrease in the growth PPFD level, P700/Chl decreased only slightly while Cyt f/ Chl decreased considerably in Alocasia macrorrhiza. Hikosaka and Terashima (1996) compared the trends between Chenopodium album, a sun plant, and A. odora. Cyt f/Chl and P700/Chl in C. album, and Cyt f/Chl in A. odora decreased with the decrease in the growth PPFD level, while P700/Chl in A. odora hardly decreased. P700/Chl ratio tends to be unchanged irrespective of the growth light conditions, whereas Cyt f/P700 decreases with the decrease in the growth PPFD level (Hikosaka and Tersahima 1995; Schöttler and Tóth 2014). These traits are important for the tolerance to sudden sunflecks and/or fluctuating light in the shadetolerant species. Another intriguing possibility is that the large granal stacks in lowlight-acclimated Alocasia odora may have a tight lumenal space that slows plastocyanin diffusion to and from PSI, thereby promoting the formation of P700+ which acts as an effective quencher in PSI during a light burst. This should also be tested. Whether the constancy of P700/Chl is more favored in shade plants grown in low light awaits further close analyses. Regression analyses also indicate that low Chl a/b and low PSII/PSI fluorescence emission ratio measured at 77 K contributed to the resistance to the fluctuating lightinduced PSI photoinhibition. It is noteworthy that low light-grown A. odora showed low Chl a/b ratios, implying that the leaves had abundant LHCII as has been reported for other plants (for a review, see Anderson 1986). However, such chloroplasts showed low PSII/PSI fluorescence ratios measured at 77 K. In the short high-light phase or after the sudden shift to high light, the PSII reaction centers were largely closed and NPQ hardly developed. The slower formation of NPQ in low light-grown leaves has been shown for Vicia faba (Stefanov and Terashima 2008), though this would be partly attributed to the increase in Y(NO) as mentioned above. When the leaf is suddenly exposed to strong light and Y(NPQ) is still low, another key process is spillover, the energy overflow from PSII to PSI. Locations

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of PSII and PSI are separated in the thylakoids. PSII is found in the appressed membranes, whereas PSI is mostly found in the non-appressed membranes (Andersson and Anderson 1980). Dynamic changes of the shape of grana in response to light occur (Rozak et al. 2002; Anderson et al. 2012; Iwai et al. 2018). However, the results of these studies are not necessarily consistent (see Wood et al. 2019). For spillover to occur, it may be prerequisite for PSI and PSII complexes to associate each other. In shade-type chloroplasts, the appressed membranes are abundant. Thus, the spillover from PSII to PSI may not be facilitated, at least apparently. Recent studies using the time-resolved fluorescence analysis showed that the PSII to PSI spillover increased with the decrease in the number of thylakoids per granum in Scots pine, Pinus sylvestris (Bag et al. 2020). Association of LHCII to PSI and the excitation energy transfer from LHCII to PSI have been shown for several PSI-carrying chlorophyll-protein complexes, prepared in various ways, with a time-resolved fluorescence-streak camera (Bos et al. 2017). Apart from the energy transfer in these complexes, the spillover from the PSII core complex to PSI occurs in the PSI-PSII megacomplex. In spillover, the excitation energy that could not reach open PSII reaction centers or that produced by the charge recombination in PSII is transferred from PSII to PSI via the deep-trap Chl a in the PSI-PSII megacomplex. Occurrence of the PSI-PSII megacomplex has been examined across several green plants (Yokono et al. 2015, 2019). Yokono et al. (2019) suggested that sun plants accumulate the PSI-PSII megacomplexes. Figure 5 compared fluorescence inductions in leaf discs of A. odora measured at 690 and 760 nm at 77 K. The plants were grown at PPFD of 10 μmol m-2 s-1 (12 h light). At 77 K, fluorescence detected at 760 nm is attributed to the PSI fluorescence. It is worth mentioning that this is not the case at room temperature. PSII fluorescence from the vibration levels is observed in the FR waveband (Franck et al. 2002). With the closure of PSII, fluorescence level increased at 690 nm. At 760 nm, high F0 level (mostly intrinsic PSI fluorescence) was observed and, with the closure of PSII, the increase in fluorescence due to spillover was observed. The share of spillover component from PSII to the total PSI fluorescence at the end of induction (Fm) attained up to 40%. The magnitude of the spillover was greater in low-light grown plants than in high-light grown plants in A. odora and cucumber. The similar shares were obtained for high- and low-light grown spinach. Namely, spillover is not suppressed in shade-type chloroplasts. Spillover also occurred in Chl b-less mutant (chlorine-f2) of barley (data not shown). Chlorophyll-protein complexes of A. odora were separated using the method of Kim et al. (2020): solubilization of chlorophyll-protein complexes with dodecyl α-maltoside followed by centrifugation in the presence of amphipol A8–35, a potent protectant. It was found that the content of the PSI-PSII megacomplex was greater in A. odora, particularly in low light-grown plants, than in A. thaliana. However, relative abundance of PSI-PSII megacomplex is not large (unpublished data of the authors: collaboration with Professor J. Minagawa, Dr. R. Tokutsu, Dr. E. Kim, and Dr. A Watanabe at National Institute for Basic Biology, Japan). Given that the large spillover occurs in many plants including the b-less mutant lacking in LHCII, spillover may not exclusively occur in the PSI-PSII megacomplexes. We propose

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Fig. 5 Effects of state transition on PSI and PSII fluorescence induction at 77 K in a low light grown leaf of A. odora. Leaf discs, placed on wet paper, were illuminated for at least 30 min with either 720 nm or 470 nm LEDs at PFD of about 10 μmol m-2 s-1. Then, the leaf disc was attached to a quartz rod with silicone grease, covered with an aluminum cup and frozen at 77 K. The pulse modulated 470 nm measuring beam (also used as an actinic light) at 50 μmol m-2 s-1 was delivered to the quartz rod at 0 s and fluorescence was detected either at 690 nm or 760 nm with a PAM 101 fluorometer (Walz, Germany), whose emitter and detector parts were modified in the laboratory. F0 of the PSI fluorescence was lower in state 1 (the conditions in the light preferentially exciting PSI) than in state 2 (the conditions in the light preferentially exciting PSII), while the spillover from PSII is larger in state 1. Each trace is the average of four measurements. The contribution of the spillover from PSII to Fm of PSI is 30–40%. Shares of the spillover from PSII to Fm of PSI in the low light grown (shade-type) leaves tend to be greater than that in the high light grown (sun type) leaves (data not shown). The spillover of excitation from PSII to PSI not only protects PSII by preventing excitations staying around closed PSII reaction centers but also contributes to oxidizing P700 to P700+, the safe quencher, by reducing electron flow from PSII to PSI and enhancing the excitation of P700

that simple Förster resonance excitation transfer across various chlorophyll protein complexes may be also responsible for the spillover (see Sect. 4.1). We have shown the presence of deep-trap Chl a, absorbing light at wavelengths longer than 700 nm, by 77 K spectroscopy and the considerable energy flow from Chl b to PSI in A. odora (Terashima et al. 2021). It should be also noted that the deep-trap Chl a is involved in the safe quenching of excess energy by P700+ (Karapetyan 2008). When spillover from PSII to PSI is active, PSII would be also protected because Chl* near the PSII reaction center decreases considerably. It is interesting to examine whether the shade-tolerant plants grown in low light generally construct their thylakoid membranes in such a way that their PSI is resistant to fluctuating light-induced photoinhibition. Such thylakoids may be also resistant to

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sudden strong sunflecks. Given that shade-tolerant plants are frequently exposed to strong sunflecks in their natural habitats, such thylakoids are adaptive. To a first approximation, PSI fluorescence may be proportional to the abundance of Chl* in PSI. The appreciable spillover from PSII to PSI means allocation of Chl* to PSII decreased with the increase in closed PSII. If this occurs at physiological temperatures as well, we need to introduce another rate constant for spillover, kII → I, to Eq. 9. F 0s =

3.5

M ∙ kF  k F þ kD þ k isc þ kNPQ þ k II → I þ qopen ∙ k P

ð26Þ

Need for More Attention to Far-Red Light

We now know that PSI is intrinsically susceptible to photoinhibition. However, by several mechanisms, it is protected. Suppression of the electron transport in Cyt b6/f (photosynthetic control/RISE) by boosted input of H+ into the lumen by the cyclic electron transport, and spillover of Chl* from PSII to PSI upon the shift to high light conditions, both cause accumulation of P700+. Thus, the excess Chl* is safely dissipated by charge recombination or quenched. When these mechanisms function, the activity of Asada cycle is high enough to eliminate H2O2. It is also important that FR light, abundant in natural light, suppresses PSI photoinhibition. Between the two PSI-CEF pathways, the NDH pathway is more important in alleviation of PSI photoinhibition by FR light. In addition to alleviation of PSI photoinhibition, we recently found that FR light enhances photosynthesis in the low-light phase of fluctuating light given to A. thaliana, N. tabacum, and A. odora (Kono et al. 2020). When applied solely, the FR light we used did not drive CO2 fixation. When the FR light was added to red light, however, FR light enhanced CO2 assimilation after the transition from the high- to low-light phases in fluctuating light by accelerating NPQ relaxation and Y (II) increase. For rapid NPQ relaxation, activation of KEA3, a H+/K+ antiporter (Armbruster et al. 2014) by FR light is involved (Kono et al. in revision). By keeping the membrane potential component of the proton motive force by importing K+, on the one hand, the efflux of H+ accelerates the decrease in ΔpH and thereby relaxation of NPQ. This should not be confused with the Emerson enhancement (Emerson and Lewis 1943; Emerson et al. 1957; Brody and Emerson 1959). The Emerson enhancement is seen upon addition of light of shorter wavelength such as 650 nm, which corresponds to Chl b absorbance peak in vivo, to the background FR light. In summary, FR light plays an important role in rapid adjustments of the photosynthetic systems to the fluctuating light in addition to alleviation of PSI photoinhibition. It is highly probable that there are some other functions of FR light. Also, roles of the NDH pathway in the presence of FR light should be fully revealed.

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Recently, Mattila et al. (2020b) measured action spectra of redox state of PQ pool. Sharp peaks for PQ reduction correspond to absorbance peaks of Chl b and the absorbance minimum of Chl a, where Chl b shows some absorbance. More importantly, natural light containing FR light generally oxidizes PQ pool, implying important roles of natural light in redox dependent reactions and gene expressions. Sunlight contains FR light (FR; 700–800 nm) as well as visible light (400–700 nm). In an open site, the PFD per unit wavelength of FR light is comparable to that of the visible light (Gates 1980). In a canopy shade PFD per unit wavelength of FR light is much greater than that of visible light, because green leaves absorb more visible light than FR (Tasker and Smith 1977; Smith 1982). However, in many instruments for photosynthesis measurement systems, red and/or blue LEDs are used for actinic light sources. Omission of FR light is spurious for understanding photosynthesis in nature. We need to pay more attention to roles of FR light. The data obtained with the illumination systems, in which FR light is absent, should be carefully reexamined.

4 Immediate and Future Scopes As has been discussed above, there are various problems which should be solved. In this section we propose several ecologically important projects.

4.1

Immediate Scopes

It is generally important to describe spectra of growth light, photoinhibitory light, and measuring light. It is rather surprising that we cannot get enough information for these light sources from many preceding papers including the so-called classics. In these 40 years, tungsten lamps, metal halide lamps, fluorescent lamps of numerous spectral variants, and LEDs have been used. For tungsten lamps, water or CuSO4 solution was used as heat absorber. Then, optical filters of the absorption type and the reflection type became available. The spectra of these light sources + heat-cut filters are all different. As mentioned above, the roles of FR light should be examined in detail. For such purposes, full description of the spectra of light sources is indispensable. As a non-invasive technique, the PAM fluorometry will be probably used in the future as well. However, as mentioned in Sect. 2.2, the QA hypothesis has been challenged (Laisk and Oja 2020; Sipka et al. 2021). We need to re-examine the PAM fluorescence parameters to properly describe photosynthetic performance. Numerous parameters have been proposed for the OJIP analyses, and these parameters have been claimed to be useful in diagnosing photosynthetic activities (Strasser et al. 2004). However, it is also necessary to re-examine these parameters, paying attention to the fluorescence rise due to D1 structural changes (Sipka et al. 2021).

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Assembly of PSI and PSII complexes have been intensively studied particularly with the models such as Thermosynechococcus vulcanus, a cyanobacterium, and Chlamydomonas reinhardtii, a green alga (Nickelsen and Rengstl 2013; Nellaepalli et al. 2021). The roles of auxiliary proteins have been gradually clarified (Nellaepalli et al. 2021; Zabret et al. 2021). Also, the repair cycle of D1 protein has been attracting attention (Järvi et al. 2015; Kato et al. 2018; Murata and Nishiyama 2018). In C. reinhardtii, it has been reported that PSII assembly and repair occur in different places in one cell (Uniacke and Zerges 2007). Although the assembly and repair have common pathways, there must be some differences as well. Thus, studies of the repair cycle paying attention to the fate of OEC should be conducted separately from the assembly studies, though these studies would progress synergistically. Based on our studies, we have hypothesized that the recovery of PSII photoinhibited by the Mn/(Two-step) mechanisms is slower than that of PSII photoinhibited by the Excess-Y(NO) mechanism. This hypothesis should be promptly tested. The roles of the NDH complex in relation to FR light should be fully clarified as mentioned in Sect. 3.3. Preceding studies using cyanobacteria (Ogawa and Mi 2007; Battchikova et al. 2011) may provide good models. Studies of spillover of excitation from PSII to PSI have been conducted, paying attention to structural changes of chloroplasts. As mentioned in Sect. 3.4, in Scots pine, PSII to PSI spillover increased with the decrease in the number of thylakoids per granum, which occurred in response to the seasonal changes of temperature and irradiance (Bag et al. 2020). However, as we have shown in Sect. 3.4, the contribution of spillover to PSI fluorescence at 77 K was comparable or even greater in low-light grown leaves than in high-light grown leaves in A. odora and cucumber. We also observed large spillover in Chl b-less mutant of barley, consistent with the shorter lifetime of fluorescence emitted by PSII (Searle et al. 1979). Whether this mutant, which lacks in LHCII, has PSI-PSII megacomplexes has not been examined, and thus the spillover pathway of excitation is unknown. However, since the Förster resonance excitation transfer mechanism works when the distance between chlorophylls is small enough (Şener et al. 2011), excitation transfer may not necessarily occur in tightly connected antenna chlorophyll proteins or in the megacomplexes. Association of PSII and PSI in neighboring thylakoid membranes may be weakened in the poorly stacked thylakoids in the Chl b-less barley mutant. On the other hand, lateral association of PSII and PSI in a thylakoid membrane may be enhanced in the mutant. As spillover in the wild-type barley was comparable to that in Chl b-less mutant, thylakoid stacking might not suppress spillover while loose thylakoid stacking would not facilitate spillover. The PSII-PSI megacomplex per chlorophyll was more abundant in thylakoids from low-light grown leaves than that in high-light grown leaves in A. odora (unpublished data of the authors). Because 30 to 40% of PSI fluorescence at Fm level is attributed to the spillover from PSII, the pathway for the spillover should be broad enough. It appears that the abundance of the megacomplex is too small to be responsible for all the spillover. Live imaging techniques of chloroplasts (Iwai et al.

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2018) may be applied to this problem to identify the positions emitting PSI variable fluorescence. If spillover also occurs at physiological temperatures, we have to incorporate kII → I into the fluorescence model. Such studies were already conducted in the 1970s by Kitajima and Butler (1975b, c). However, unfortunately, progress has been stopped. Judging from the very high maximum quantum yields of photosynthetic oxygen evolution measured in low light for various leaves (Björkman and Demmig 1987), allocation of excitation between PSI and PSII may be nearly even. Indeed, the fraction of excitation partitioned to PSII was estimated to be 0.50 (spinach), 0.47 (poplar), 0.50 (rice), and 0.47 (cotton) in low to moderate actinic light from a halogen lamp (Zhang et al. 2018). In other words, when F0 level fluorescence is measured at physiological temperatures, PSI and PSII are equally excited. Conversely, at Fm, the allocation of excitation to PSII would decrease accordingly, if the spillover of excitation at physiological temperatures occurs similarly to that at 77 K. In the conventional calculation of the quantum yield of PSII (Eq. 12), this is totally ignored. Because PSI fluorescence yield is low and largely masked by the vibrational level PSII fluorescence at physiological temperatures (Franck et al. 2002), it is hard to separately detect PSI fluorescence from PSII fluorescence. It is necessary to overcome this problem to examine phenomena at physiological temperatures.

4.2

Future Scopes

Recently, we proposed the mixed population hypothesis (Kono et al. 2022b), in which three different populations of photoinhibited PSII, namely PSII with inactivated OEC and functional D1 (competent in reduction of QA), PSII with active OEC and damaged D1, and PSII with inactivated OEC and inactive D1, are considered. Changes of the quenching efficiency during degradation processes in the repair cycle would be also important (Matsubara and Chow 2004; Zavafer et al. 2019; Nawrocki et al. 2021). Thus, we need to develop a more comprehensive model of thylakoid dynamics, considering not only newly photoinhibited PSII but also their degradation processes showing changes in the quenching efficiency. This would be one of the ultimate destinations of this research field. Cost and benefit analyses of this dynamism throughout a life of single leaf would be another destination. There is a very large gap between the molecular studies and phenomenological studies at larger scales up to satellite remote sensing. Moreover, the gap is enlarging. Ecophysiologists should play an important role in filling this large gap, because we can test various findings made at the molecular level using various techniques at the leaf level (Adams and Terashima 2018). Also, we can scale up the photosynthetic performance from the leaf level to the canopy level (Hikosaka et al. 2015). To pursue these tasks, more close communications of the ecophysiologists with researchers working at different scales are needed.

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Acknowledgments Professor Barry Osmond recommended us as potential authors of a Progress in Botany article to Professor Ulrich Lüttge, who then kindly invited us to write this review and closely edit our drafts. We are grateful to both. We thank two reviewers Professors W.S. Chow and E. Tyystjärvi for critical reviews and useful suggestions. We incorporate their useful suggestions to this review, acknowledging their contributions. We also thank many colleagues for collaborations, discussions, and encouragements. Our photoinhibition studies have been only sporadically supported by the grants from the Japan Society for Promotion of Science (JSPS) and the Ministry of Education, Culture, Sports, and Technology (MEXT). Thus, two recent grants from MEXT (17H05718 and 19H04718) are appreciated. More importantly, we highly appreciate Continuous Ordinary Operating/Management Expenses Grants from our universities. Without these ordinary grants, our studies might have been interrupted or severely delayed. It is regrettable that the amount of such ordinary operating grants is gradually decreasing in Japan. This is due to the governmental policy to concentrate research grants to selected scientists, which obviously suppresses ordinary operations of ordinary scientists like us.

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Distribution and Functions of Calcium Mineral Deposits in Photosynthetic Organisms J. A. Raven

Contents 1 2 3 4 5

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Distribution of CaCO3 Deposition Among Photosynthetic Organisms . . . . . . . . . . . . . . . . . . . . Distribution of Ca(COO)2 Deposition Among Photosynthetic Organisms . . . . . . . . . . . . . . . . Boring into Solid CaCO3 by Photoautotrophic Cyanobacteria and Algae . . . . . . . . . . . . . . . . . Outcomes of the Production of CaCO3 and Ca(COO)2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 Acid-Base Changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Ca Accumulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 Light Scattering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4 Increased Density . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.5 Defence from Herbivores and Pathogens . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.6 Pollen Release from Anthers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Outcome of Alternating Synthesis and Breakdown of CaCO3 and Ca(COO)2 . . . . . . . . . . . . 6.1 Alarm Photosynthesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Outcome of Boring into CaCO3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.1 Dissolution of CaCO3 as a Source of CO2 for Rubisco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract CaCO3 precipitates occur inside a few cyanobacteria and green algae. More common is precipitation on the surface of cyanobacteria, a range of algae and aquatic plants, and in invaginations of the cell wall in terrestrial plants (cystoliths). In coccolithophores and calcified dinoflagellates, CaCO3 is precipitated with organic matter in intracellular vesicles and the resulting structures are externalised. The precipitation of CaCO3 on the surface of photosynthesising structures is related to

Communicated by Ulrich Lüttge J. A. Raven (✉) Division of Plant Science, University of Dundee at the James Hutton Institute, Dundee, UK Climate Change Cluster, University of Technology Sydney, Ultimo, NSW, Australia School of Biological Sciences, University of Western Australia, Crawley, WA, Australia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 Progress in Botany (2024) 84: 293–326, https://doi.org/10.1007/124_2023_71, Published online: 30 June 2023

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the consumption of CO2 in photosynthesis. CO2 production by root respiration can solubilise soil CaCO3. A few cyanobacteria and eukaryotic algae can bore through solid CaCO3 by removing Ca2+ and adding H+ at the site of boring, generating soluble inorganic C that can be used in photosynthesis. Ca(COO)2 is precipitated in the vacuoles of many algae and plants, and the cell walls of some plants. An outcome of precipitation of CaCO3 using CO3= produced from CO2, and 2+ Ca , is the production of H+; the same is the case for precipitation of Ca(COO)2 from (COOH)2 and Ca2+. The H+ produced by Ca(COO2) can be used to neutralise OH- produced in NO3- assimilation in the shoot without increasing cell osmolarity. There is no evidence of CaCO3 fulfilling this role. Another outcome of CaCO3 and Ca(COO)2 precipitation is Ca2+ immobilisation, though with little evidence of remobilisation of Ca2+ under Ca2+ deficiency. Other consequences of CaCO3 and Ca(COO)2 precipitation are light scattering and increased density, and ‘alarm photosynthesis’. Defence against herbivores and pathogens is better established for Ca (COO)2 than for CaCO3, and pollen release from anthers is a function of Ca(COO)2 but not CaCO3. Keywords Acid-base regulation, Alarm photosynthesis, Calcium, Carbonate, Interactions with photons, Oxalate

1 Introduction CaCO3 precipitates occur widely in association with photosynthetic (and other) organisms (Fig. 1 of Hendry et al. 2018). Ca2+ and CO32- occur in the ocean and many inland waters as a supersaturated solution stabilised by inhibitors of crystallisation and of crystal growth; CaCO3 precipitation from these supersaturated solutions generally involves removing the inhibitors of crystallisation and crystal growth through biological activity. The possibility of precipitation of CaCO3 on aquatic photoautotrophs is increased in the light by removal of CO2, directly by diffusive CO2 influx, or indirectly by HCO3- influx, CO2 assimilation by Rubisco, and OH- efflux, increases in the pH in the boundary layer and to a smaller extent in the bulk medium. This alters the dissolved inorganic C speciation in favour of CO32and away from CO2, favouring CaCO3 precipitation, provided that inhibitors of crystallisation and crystal growth are absent. Ca(COO)2 deposits are also widely in association with photosynthetic (and other) organisms (Fig. 1 of Hendry et al. 2018). (COOH)2 is produced abiologically in the atmosphere by oxidation of alkenes (Martinelango et al. 2007; Turekian et al. 2003; Aggarwal and Kawamura 2008) or glyoxal (Carlton et al. 2007), and oxalate also occurs in diagenetic and hydrothermal fluids (Hoffmann and Bernasconi 1998), but the rest of the oxalate in the biosphere is, as is discussed later, of biological origin. Table 1 shows that these sources cannot be invariably distinguished by natural abundance carbon isotope ratios.

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Table 1 δ13C values (%O) of oxalate from various sources. n = number of species examined for biological specimens

C4 plant (1) Lichens Atmosphere Atmosphere

δ13C oxalate -27.8, -29.3 -7.3 to -8.7 -19.5 -11.9 to 27.9 -7.06 -15.2 -21 to -22 -18.8

Diagenetic and hydrothermal fluids

-31.7 to +33.7

Source C3 plant (1) CAM plants (n = 5) C3 plant (1) C3 plants (7)

δ13C bulk organic C ND -9.2 to -14.1 -25.7 -22.3 to -31.0 -19.98 -21.7 ND ND -25 to -30

References Hoefs (1969) Rivera and Smith (1979) Rivera and Smith (1979) Raven et al. (1982) Tooulakou et al. (2016a) Beazley et al. (2002) Turekian et al. (2003) Agagami and Kawamura (2008) Hoffmann and Bernasconi (1998)

Definition of δ13C: δ13C = [(13C/12C)sample/(13C/12C)standard) – 1] × 1,000, units of %o, where the standard is the 13C/12C of the Vienna Pee-Dee Belemnite

2 Distribution of CaCO3 Deposition Among Photosynthetic Organisms Amorphous CaCO3 (ACC) is deposited intracellularly in some cyanobacteria (e.g. Gloeomargarita species; Cyanothece; Chroococcidiopsis thermalis; strains of Synechococcus) in particles surrounded by a 2.5 nm envelope that is either a lipid monolayer or a protein layer (Couradeau et al. 2012; Benzerara et al. 2014; Li et al. 2016; Blondeau et al. 2018; Segovia-Campos et al. 2022). In the freshwater cyanobacterium Gloeomargarita lithophora the range of diameters of the spherical ACC particles is 30–370 nm (Li et al. 2016). Benzerara et al. (2022) found a gene and gene family unique to intracellular ACC-precipitating cyanobacteria. Intracellular ACC can also incorporate the alkali earth metals Sr, Ba, and Ra as well Ca (Mehta et al. 2022; Segovia-Campos et al. 2022). De Wever et al. (2019) have quantified Ca uptake by cyanobacteria with and without intracellular ACC deposits, and showed that the growth rate of some ACC-depositing cyanobacteria is limited by the concentration of Ca2+ in the BG11 growth medium. De Wever et al. (2019) also showed that cyanobacteria with intracellular ACC deposits all have Ca2+ mechanosensitive channels that could be involved in Ca2+ entry, and active Ca2+ transporters that could be involved in Ca2+ efflux and/or Ca2+ movement into intracellular compartments that deposit ACC, the latter depending on nature of the organic layer surrounding ACC particles. However, De Wever et al. (2019) do not report the occurrence of these channels and transporters in cyanobacteria lacking intracellular ACC. As to how the supersaturation of Ca2+ CO32- in the cytosol that is needed for ACC precipitation in cyanobacteria is attained, the steady-state free Ca2+ concentration in the cytosol of the non-ACC precipitating cyanobacteria Anabaena sp. PCC 7120 and Synechococcus elongatus PCC 7942 is 100–200 μmol m-3

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(Torrecilla et al. 2000; Leganés et al. 2009). If this is the case in cyanobacteria with intracellular ACC deposits, the required supersaturation of Ca2+ CO32- depends on the internal inorganic carbon concentration and pH. HCO3- is accumulated in all of the cyanobacteria that have been examined as part of the inorganic carbon concentrating mechanism at an intracellular pH above 7 (Rae et al. 2013). It may be relevant that carbonate-boring cyanobacteria that are not known to contain intracellular ACCs have much higher free Ca2+ concentration in the cytosol of some cells (‘calcicytes’) (100 mmol Ca2+ m-3: Guida and Garcia-Pichel 2016), at least 500 times the steady-state free Ca2+ concentration in the cytosol of the non-ACC precipitating cyanobacteria Anabaena sp. PCC 7120 and Synechococcus elongatus PCC 7942 is 100–200 μmol m-3 (Torrecilla et al. 2000; Leganés et al. 2009). Sr-rich intracellular (cytosolic) ACC (micro pearls) are produced by some species in the genera Tetraselmis and Scherffelia (Chlorodendrophyceae: Chlorophyta) (Martignier et al. 2017, 2018). As is the case for cyanobacteria lacking ACC deposits (Torrecilla et al. 2000; Leganés et al. 2009), the chlorophyte alga Chlamydomonas reinhardtii that does not precipitate ACC in the cytosol has cytosolic concentrations of free Ca2+ of 100–200 μmol m-3 (Pivata and Ballotari 2021). Similar values are found for the other N (electrically negative) compartments (Mitchell 2011), the mitochondrial matrix and the chloroplast stroma, of Chlamydomonas reinhardtii (Pivata and Ballotari 2021), and for the cytosol, matrix, and stroma of flowering plants (Logan and Knight 2003; Costa et al. 2018). Free Ca2+ concentrations are higher in P (electrically positive) compartments (Mitchell 2011), e.g. lysosomes, vacuoles, cell walls, xylem (Resentini et al. 2021). Extracellular CaCO3 precipitation is associated with cyanobacteria, both benthic (Bume and Moore 1987; Aloisi 2008; Riding 2000; Bosak et al. 2013) and planktonic (Thompson et al. 1997; Kranz et al. 2010; Fang et al. 2022). Benthic precipitation occurs in cyanobacterial mats/microbialites/stromatolites (Bume and Moore 1987; Aloisi 2008; Riding 2000; Bosak et al. 2013). It is not clear that all fossil stromatolites are biogenic: Bosak et al. (2013) suggest that the oldest stromatolites that could be biogenic are from the 3.43 Ga (Archean) Strelley Pool deposits. It is of interest that Gloeomargarita species, which has internal ACC precipitation, also lives in external CaCO3 precipitation (Moreira et al. 2017). Planktonic CaCO3 depositions by cyanobacteria, together with abiological planktonic CaCO3 precipitation, are known as ‘whitings’ (Thompson et al. 1997; Kranz et al. 2010). Thompson et al. (1997) relate the biogenic whitings in the freshwater Fayetteville Green Lake, New York to the small size (picoplanktonic) of the Synechococcus where photosynthesis increases the pH, particularly in the diffusion boundary layer of the cells, and the large surface area per unit volume of the cyanobacterial cells on which precipitation can occur. The marine precipitation related to the larger colonies of the diazotrophic Trichodesmium (Kranz et al. 2010) occurs despite the smaller surface area per unit volume of Trichodesmium than of Synechococcus. As with external CaCO3 precipitation by cyanobacteria, there is a fossil record of planktonic precipitation, which can be related to atmospheric changes and corresponding cyanobacterial evolution in the Proterozoic (Riding 2006; Kah and Riding 2007). This precipitation is limited to coastal shelves

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in the Proterozoic since there is very little Proterozoic ocean crust remaining (Hynes 1982; Shervais et al. 1988; Cavosie and Silvesterstone 2003) to carry evidence of CaCO3 precipitation or cyanobacterial structural fossils or biomarkers, and molecular phylogenetic evidence shows that extant clades of open ocean cyanobacteria did not evolve until late in the Proterozoic (Sanchez-Báracaldo 2015). Crystalline CaCO3 as coccoliths is deposited in an endomembrane compartment (the coccolith forming vesicle) of marine coccolithophores (Coccolithophyceae, Haptophyta), followed by externalisation (Monteiro et al. 2016; Durak et al. 2016, 2017; Gal et al. 2018; Kadan et al. 2021; Langer et al. 2021). Calcification involves entry of Ca2+ and 2 HCO3- and CaCO3 formation in the coccolith forming vesicle according to Ca2+ + 2HCO3- → CaCO3 + CO2 + H2O. The role, if any, of acidicalcisomes, membrane-bounded vesicles in coccolithophores and many other eukaryotic algae containing polyphosphate bound to Ca and other cations, and similar membrane-bounded Ca-phosphate vesicles, is unclear (Gal et al. 2018). Cells of the haploid phase of the life cycle, if they are calcified, produce holococcoliths, which have simple rhomboid calcite crystals with organic material (Langer et al. 2021). While it used to be thought that holococcoliths were produced extracellularly, it is now clear that holococcoliths are produced, like heterococcoliths, in an endomembrane compartment followed by externalisation (Langer et al. 2021). Some widely investigated coccolithophores, e.g. Emiliania huxleyi and Chrysotila carterae (formerly Pleurochrysis carterae) have uncalcified haploid phases (Langer et al. 2021). The genetic basis of this difference in calcification between life cycle phases has been investigated in Emiliania huxleyi, where there is a less transcript production from genes encoding Ca2+, H+, and HCO3transporters in the haploid phase than in the diploid phase (von Dassow et al. 2009; Rokitta et al. 2012). Holococcoliths have a little-explored organic carbon component (Skeffington and Scheffel (2018). Heterococcoliths are produced by the diploid phase of all coccolithophores and are produced in an endomembrane compartment (the coccolith forming vesicle), followed by externalisation (Langer et al. 2021). Heterococcoliths have intricately shaped calcite crystals with organic material (Langer et al. 2021). The extent to which coccoliths formation is essential for coccolithophores growth varies; strains of Emiliania huxleyi can grow in the absence of calcification, but Coccolithus braarudii cannot grow in the absence of a coccosphere (Walker et al. 2018). There is no evidence that calcification is essential for photosynthesis in Coccolithus braarudii., for example, necessarily using the CO2 produced in the calcification reaction Ca2++ 2HCO3- → CaCO3 + CO2 + H2O. Acidic polysaccharides (uronates) are important organic components of coccoliths and help to direct calcite crystallisation (Henrickson et al. 2004; Henrickson and Stipp 2009). Monteiro et al. (2016) discuss the energy cost production of heterococcoliths; there are energy costs of coccolith production that are not involved in direct deposition of CaCO3 outside cells and organisms. Many of the coccolithophores examined, and also the non-calcified haptophytes examined, have diatom-like silicic acid transporters (Durak et al. 2016), and the cytoskeleton is involved in both silicification and calcification in haptophytes (Durak

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et al. 2017). Si is involved in the production of heterococcolith in many species, but is not involved in holococcolith production (Langer et al. 2021; Mock 2021). Furthermore, silica can stabilise ACC (Kellermeier et al. 2010). The Si requirement is very small, and the rate of Si(OH)4 influx using the SITL Na+-Si(OH)4 symporter, is very low, and the role of Si is presumably in supporting calcification rather than as a structural component of coccoliths (Ratcliffe et al. 2022). Brownlee et al. (2021) point out that coccolithophores that do not require Si are the later-evolving species, such Emiliania huxleyi, and that this might be related to decreased surface ocean Si (OH)4 concentrations resulting from the rise of the diatoms; the increase in diatoms post-dated the rise in coccolithophores. Coccolithophores have a good fossil record, largely as isolated heterococcoliths, with a bias towards oceanic rather than coastal species; this is unfortunate for the study of the evolution of coccolithophores, since the available data suggest that coastal habitats are important for the evolution of coccolithophores (Bown and Young 2019). Crystalline CaCO3 (calcite) is also deposited by a few dinoflagellates (Van de Waal et al. 2013; Taylor et al. 2017; Jantschke et al. 2020; Riding et al. 2023). The structural and chemical pathway of CaCO3 production in dinoflagellates is incompletely understood, but could involve multifunctional vacuoles containing anhydrous beta-form guanine crystals and MgCaP mineral bodies (Jantschke et al. 2020). The distribution of calcification among dinoflagellates is consistent with polyphyly; monophyly with multiple losses is less parsimonious (Gottschling et al. 2005). Calcification involves the haploid asexual phase in Thoracosphaera helmii and Leonella granifera and as diploid calcareous cysts in the sexual cycle of Calcidiodinellum levantinum (Meier et al. 2007). The calcified dinoflagellates mentioned so far are marine; there is also a freshwater calcified dinoflagellate (Craveiro et al. 2019). A calcified dinoflagellate is known from the Cretaceous (Wendler and Bown 2012). Four Orders of the Rhodophyta (Corallinales, Peyssoneliales; Sporolithales, and Nemaliales) have extracellular CaCO3 (Smith et al. 2012; Peña et al. 2020). Over the Corallinales, Peyssoneliales, and Sporolithales most of the calcification is as calcite (97% be weight), with a mean of 13.1% by weight of MgCO3 in the calcite; aragonite is 3% of the calcification (Smith et al. 2012). The Nemaliales precipitates aragonite (Borowitzka et al. 1974). These algae are almost all marine, a few inhabit brackish waters, and one species (the crustose Pneophilum cetinaensis) lives in freshwater, probably having invaded freshwaters during sea level changes in the last glacial period (Žuljević et al. 2016). Coralline algae are either articulate (geniculate) or non-articulate; the articulate corallines evolved from non-articulate ancestors, although there are cases of reversion of the articulate to the non-articulate state (Peña et al. 2020). The articulate coralline algae are haptophytes, i.e. attached to a solid substrate (Raven 1981, 2018), and are erect and branched. The calcified regions (intergenicula) are interrupted by uncalcified articulations (genicula) that allow deformation of the thalli under wave or current water movements and limit breakage by the water movement (Martone 2006). At least in Calliarthron (Martone 2006), the strengthening of the genicula

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with growth of the fronds fails to keep pace with the increased drag forces on the larger fronds, and breakage occurs. However, this is not unique to articulate corallines, and Calliarthron is not an outlier when compared with five non-calcified erect macroalgae with respect to a suite of biomechanical properties (Martone et al. 2012), and genicula are strong, extensible, and resistant to fatigue (Guenther et al. 2022). Non-articulate corallines can be haptophytic and crustose, with thalli growing over, and closely adherent to, the solid substrate (Littler and Littler 2013). Any protrusions above the crust are non-articulate. As well as growing on coral reefs, crustose coralline algae produce chemicals that act as settlement cues for coral larvae (Tebbon et al. 2015). Crusts of Clathromorphum compactum can be 100–400 m thick, with only the upper parts living, and an age of 640–830 years (Adey et al. 2015; Williams et al. 2018). Non-articulate corallines can also be pleustophytic (Raven 1981, 2018) as rhodoliths, with the crust starting with a nucleation particle (Foster et al. 2013). Rhodoliths can be spheroidal, discoidal, or ellipsoidal in overall shape, often with protrusions or (non-geniculate) branches within the overall shape (de Sousa et al. 2014). Growth rates of rhodoliths have been estimated at 0.6–0.7 mm per year (Darrenougue et al. 2013; McConnico et al. 2014). The age of rhodoliths has been estimated at 100–300 years (McConnico et al. 2014) to 1,600–1,800 years (Vale et al. 2022). Rhodoliths are important in the life cycle of micro- and macro-algae (Fredricq et al. 2019), and rhodoliths hollowed out by boring molluscs increase biodiversity (Teichert 2014). These three life forms are not mutually exclusive for a given species of coralline alga. Corallina officinalis is heterotrichous, with a crustose horizontal component and a geniculate erect component (Littler and Kauker 1984). The geniculate portion has a greater growth rate on substrate area basis than the crustose portion, while the crustose portion is more resistant to grazing than the erect portion, and so allows the organism as a whole to survive a given level of grazing, with the possibility of regeneration of the erect phase (Littler and Kauker 1984). Clathromorphum compactum and Lithothamnion species can occur as crusts or rhodoliths (Adey et al. 2015; Williams et al. 2018). Extracellular CaCO3 deposition occurs on some unicellular (acellular) macroscopic rhizophytic (Raven 1981, 2018) marine members of the Bryopsidales and Dasycladales in the Ulvophyceae (Chlorophyta). Among the extant Bryopsidales, the genera Halimeda, Penicillus, Tydemania, and Udotea are calcified, while among the extant Dasycladales, the genera Acetabularia, Cymopolia, and Neomeris are calcified (Granier 2012). More calcified genera of these two Orders are known from the Phanerozoic fossil record (Granier 2012). A feature of Halimeda is that the thallus above the rhizoids is composed of calcified segments connected by uncalcified genicula (Neustupa and Nemcova 2022), giving the thallus flexibility as is the case for geniculate coralline red algae. Calcification, with small amounts of Mg, Sr, and Ba in addition to Ca, also occurs in the freshwater microalga Gloeotaenium loitlesbergianum (Prasad and Chowdary 1982; Ramos et al. 2021). The streptophytes include algal Charophyta and the Embryophyta (higher plants). Among the Charophyta, calcification occurs in the freshwater desmid Oocardium

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(Zygnematophyceae, the closest algal class to the Embryophyta) (Rott et al. 2010) and freshwater and brackish water Charophyceae, macroalgae composed of giant internodal cells of the main axis and branches, and small rhizoidal and (where present) corticating cells surrounding the giant internodal cells (Walker et al. 1980; Raven and Giordano 2009; Kawahata et al. 2013; Beilby and Casanova 2014; Sand-Jensen et al. 2018). Ecorticate Charophyceae has alternating acid and alkaline bands on their internodal and branch cells, each band of the order of a mm long (Walker et al. 1980; Beilby and Casanova 2014). The alkaline bands are sometimes encrusted in CaCO3 (Walker et al. 1980; Beilby and Casanova 2014). The functional significance of the acid and alkaline bands is that there is H+ efflux by the P-type H+-ATPase in the acid bands, where external HCO3- is converted to CO2, catalysed by H+ and cell wall carbonic anhydrase, with the CO2:HCO3- ratio at or approaching the equilibrium value for the cell wall pH (Walker et al. 1980; Beilby and Casanova 2014). This combination of kinetic and equilibrium effects allows the use of external HCO3- by conversion to CO2 with diffusive entry of CO2 (Walker et al. 1980; Beilby and Casanova 2014). This mechanism that involves a net H+ efflux in the acid zones requires that there is a compensating H+ influx (or OHefflux) that allows charge and internal acid-base balance; this occurs in the alkaline zones; this flux is probably catalysed by OH- channels related to the SLC4 family of animal pH regulators (Quade et al. 2022). There are no obvious mechanical benefits of these calcified zones in ecorticate species of, e.g. Chara corallina, and the other, all ecorticate, genera of the Charophyceae. Ecorticate species of Chara, e.g. Chara globularis, can be calcified all over, with acid and alkaline zones only recognised with difficulty (Kawahata et al. 2013), although the mechanical benefits of overall calcification are more obvious. Padina and Newhousia are the only calcified genera in the Phaeophyceae (Padina: Okazaki et al. 1986; Iluz et al. 2017; Newhousia: Kraft et al. 2004). The mineral is typically CaCO3, but acidification of the seawater leads to replacement of CaCO3 by CaSO4 (Iluz et al. 2017). Among the embryophytes, CaCO3 is deposited on the surface of some submerged freshwater flowering plants, specially the alkaline adaxial leaf surface of Elodea (Hydrocharitaceae) and Potamogeton (Potamogetonaceae) as part of the mechanism of use of external HCO3- in photosynthesis (Walker et al. 1980; Elzenga and Prins 1989; Miedema and Prins 1992; Bauer et al. 1996). The alkalinised adaxial leaf surface functions as the equivalent of the alkaline zones of the Charophyceae, with acidification of the abaxial side of the leaf equivalent to the acid zones of the Charophyceae (Walker et al. 1980; Elzenga and Prins 1989; Miedema and Prins 1992; Bauer et al. 1996). Leaf polarity with respect to pH related to photosynthesis also occurs in Hydrilla verticillata (Hydrocharitaceae), but with no reports of CaCO3 precipitation on the adaxial surface of the leaf (van Ginkel et al. 2001). CaCO3 is also precipitated on the surface of the pleustophytic (Raven 1981, 2018) freshwater flowering plant with varying density and hence buoyancy, Stratiotes aloides (Hydrocharitaceae) (Prins and DeGuia 1986; Harpenslager et al. 2015). Aragonite deposits occur internally in leaf cell walls and on the leaf surface of the seagrass Thalassia testudinum (Enríquez and Schubert 2014). More commonly reported is the

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occurrence of calcified epiphytes, e.g. coralline red algae, on seagrass leaves (Perry and Beavington-Penney 2005). CaCO3 is also precipitated on the surface of some terrestrial plants. Ca2+ can be extruded from leaves in hydathode fluid (e.g. Islam and Kawasaki 2015), and is sometimes precipitated there in CaCO3, including as the rare (on Earth) mineral vaterite (Whiteman et al. 2018). CaCO3 can also be precipitated in the rhizosphere (Cramer and Hawkins 2009; Lambers et al. 2009), although the general role of roots is to solubilise CaCO3 through root CO2 production (Raven and Edwards 2000). CaCO3 can also be precipitated within the plant, but outside the plasmalemma. Thus, ACC is deposited, as cystoliths, in invaginations of the apoplasm of cells within tissues of some terrestrial flowering plants. Gal et al. (2012a) show that cystoliths are comprised of four phases, two dominated by SiO2 and two consisting of amorphous CaCO3 (ACC). The stalk anchoring the cystolith in the cell wall is almost pure SiO2 at the base and SiO2 plus Mg further up. Most of the cystolith volume is ACC, with a relative stable core surrounded by a bulky, less stable ACC phase (Gal et al. 2012a; see also Kellermeier et al. 2010; Giordano et al. 2020). Cystoliths occur in only five families of flowering plants, the Acanthaceae, Cucurbitaceae, Moraceae, Ulmaceae, and Urticaceae (Okazaki et al. 1991). Less well characterised is the occurrence of intracellular (vacuolar) calcite in root cortical cells in high-Ca2+ root environments (Jaillard 1992; Huguet et al. 2021). These observations were made in the context of progressive calcification of the root system, so it is likely that the intracellular calcite precipitation is an early stage of cell death.

3 Distribution of Ca(COO)2 Deposition Among Photosynthetic Organisms Ca(COO)2 crystals occur in a range of eukaryotic algae (Friedmann et al. 1977; Pueschel 2019, 2002; Pueschel and West 2002, 2007a, b, 2011). Most of the described Ca(COO)2 crystals in algae are in the Archaeplastida, specially those of the Ulvophyceae (Chlorophyta) (Friedmann et al. 1977; Pueschel and West 2002, 2011;Pueschel 2019). In the Dasycladales (Ulvophyceae) bipyramidal Ca(COO)2 crystals form spontaneously from vacuolar (COO)22- when the vacuolar concentration of Ca2+ is high enough to cause supersaturation with respect to Ca(COO)2 (Pueschel 2019). By contrast, in the Bryopsidales (Chlorophyta) acicular Ca(COO)2 crystals form constitutively without vacuolar accumulation of free (COO)22- (Prince 2012; Pueschel 2019). Among the Bryopsidales Ca(COO)2 crystals occur in the calcified genera Penicillus, Rhipocephalus, and Udotea; Ca(COO)2 does not occur in the non-calcified Avrainvillea and Cladostephus (Friedmann et al. 1977). Callipsygma wilsonis has Ca(COO)2 crystals in the parietal cytoplasm where they move at 2.8 μm s-1 with amyloplasts, chloroplasts, and other cytoplasmic components; it is not known if the crystals occur in small vacuoles (Pueschel and West

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2007a). Ca(COO)2 crystals also occur in the Cladophorales (Chlorophyta) (Pueschel 2019); in the case of the Chaetomorpha coliformis (formerly Chaetomorpha darwinii) the Ca(COO)2 crystals occur in small vacuoles in the layer of cytoplasm between the organelle-rich cytoplasmic layer close to the cell wall, and the large central vacuole (Pueschel and West 2011). The only other chlorophyll b-containing Archaeplastida known to have Ca (COO)2 crystals are those of Spirogyra sp. (Zygnematophyceae: Charophyta) (Pueschel 2001; Pueschel and West 2002); the Zygnematophyceae is the algal clade most closely related to the Embryophyta (Cheng et al. 2019). The Ca(COO)2 crystals in Spirogyra occur in cytoplasmic strands crossing the central vacuole; the crystals move in a cytochalasin-inhibited process, implying involvement of actomyosin (Pueschel 2001; Pueschel and West 2002). The other clade of Archaeplastida with Ca(COO)2 crystals is the Florideophyceae (Rhodophyta) (Pueschel 1995, 2019). The Florideophyceae order known to have Ca (COO)2 crystals is the Ceramiales (Pueschel 1995, 2019; Pueschel and West 2007b). Antithamnium contains acicular Ca(COO)2 crystals (cf. Bryopsidales) in the parietal cytoplasm of determinate axes, while Spyridia deposits bipyramidal Ca(COO)2 crystals from vacuolar (COO)2=, as occurs in the Dasycladales. It is not clear if the cytoplasmic Ca(COO)2 crystals of Antithamnium are each surrounded by a membrane. The only algae outside the Archaeplastida known to contain Ca(COO)2 crystals are Vaucheria (Xanthophyceae: Ochrophyta) (Pueschel 2019), and some members of the Dinophyceae (Alveolata) contain Ca(COO)2 crystals, such as the Symbiodiniaceae (Taylor 1968; Kevin et al. 1969; Fankboner 1971; Muller-Parker et al. 1996; Wakefield et al. 2000; Lajeunesse 2017), and some species that are also calcified (Zinssmeister et al. 2013). Ca(COO)2 precipitation is common in the embryophytes, the most speciose of the Streptophyta (Archaeplastida) (Franceschi and Horner 1980; Monje and Baran 2002; Hudgins et al. 2003; Franceschi and Nakata 2005; Hartl et al. 2007; Monje and Baran 2010; Bernardino-Nicanor et al. 2012; Cuellar-Cruz et al. 2020). Ca(COO)2 occurs in lycophytes and pteridophytes (Anthoons 2017), and, among gymnosperms, in cycads (Coiro et al. 2021), Ginkgo (Chen et al. 2013), Ephedra (Carlquist 1990), Gnetum (Duthie 1912), and Welwitschia (Shewin and Gowns 1995). Among conifers, the Pinaceae have intracellular Ca(COO)2 crystals in the secondary phloem, while all other conifer families have extracellular Ca(COO)2 in the secondary phloem (Hudgins et al. 2003). Among flowering plants, Broadley et al. (2003) showed that Ca(COO)2 is most prevalent in the Caryophyllales, including the families Cactaceae, Caryophyllaceae, Chenopodiaceae (now a part of the Amaranthaceae) and Polygonaceae. Among the monocotyledons, Ca(COO)2 is absent from the commelinid families Cyperaceae and Juncaceae (Broadley et al. 2003). Ca(COO)2 is absent from the submerged freshwater flowering plants from Taiwan analysed by Kuo-Huang et al. (1994), although it is known from seagrasses (Brack-Hanes and Greco 1988; Benzecry and BrackHanes 2008; Troyo et al. 2021). Ca(COO)2 has been found in fossil conifers, and in

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fossil flowering plants including seagrasses (Brack-Hanes and Greco 1988; de Seoane 1998; Malekhosseini et al. 2022).

4 Boring into Solid CaCO3 by Photoautotrophic Cyanobacteria and Algae Boring into solid CaCO3, e.g. corals, mollusc shells, and coralline algae and by photoautotrophs is less phylogenetically common, and globally significant, than CaCO3 precipitation by photoautotrophs. The photoautotrophs that bore into solid CaCO3 are cyanobacteria, e.g. Cyanococcus, Hyella, Leptolyngbya, and Plectonema and, more broadly, members of the Nodosilineaceae, Nostocaceae, Phormidiaceae, and Xenococcaeae (Akpan and Farrow 1984; Pantazidou et al. 2006; Wyness et al. 2022), the haploid (Conchocelis) phase of bangiophycean red algae (Campbell 1980; Clokie and Boney 1980; Akpan and Farrow 1984), and some members of the Ulvophyceae (Chlorophyta), e.g. Gumontia, Ostreobium, Phaeophila, and the rhizoids of Acetabularia (Radtke et al. 1997; Pantazidou et al. 2006; Iha et al. 2021). The mechanism of boring has been most thoroughly investigated in cyanobacteria, especially Mastigocoleus testarum (Garcia-Pichel et al. 2010; Ramírez-Reinet and Garcia-Pichel 2012; Guida et al. 2017). The basis of the mechanism is removal of Ca2+ from the solid CaCO3 substrate at the growing apex of the boring filament, movement of Ca2+ from cell to cell along the filament, and efflux of Ca2+ to the medium at the non-growing end of the filament using a Ca2+-ATPase, and a flux of H+ in the opposite direction since the Ca2+-ATPase catalyses 2H+:1 Ca2+ antiport (Garcia-Pichel et al. 2010; Ramírez-Reinet and Garcia-Pichel 2012; Guida and Garcia-Pichel 2016; Guida et al. 2017). The Ca2+ flux along the filament involves a much higher free Ca2+ concentration in the cytosol of some cells (‘calcicytes’) of Mastigocoleus testarum (100 mmol Ca2+ m-3: Guida and Garcia-Pichel 2016), at least 500 times the steady-state free Ca2+ concentration in the cytosol of the non-ACC precipitating, non-endolithic cyanobacteria Anabaena sp. PCC 7120 and Synechococcus elongatus PCC 7942 is 100–200 μmol m-3 (Torrecilla et al. 2000; Leganés et al. 2009). How the cells of Mastigocoleus testarum tolerate these high free Ca2+ concentrations, and impact of the return flux of H+ along the filament on cytosol pH, is not clear (Raven 1977). It may be relevant that external Ca2+ increases tolerance of low external and internal pH in Anabaena sp. PCC 7120 (Giraldo-Ruiz et al. 1997, 1999). There is currently no information on the mechanism of boring into CaCO3 by members of the Bangiophyceae or Ulvophyceae, but it seems unavoidable that boring involves Ca2+ removal from, and H+ addition to, the CaCO3.

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5 Outcomes of the Production of CaCO3 and Ca(COO)2 5.1

Acid-Base Changes

One unavoidable consequence of CaCO3 deposition in the shoots of terrestrial vascular plant shoots using atmospheric CO2 and H2O is the production of H+. In the absence of a biochemical sink for H+ in the shoot (Raven 1986) including the absence of shoot NO3- assimilation with its necessary OH- production (Raven and Smith 1976; Raven and Andrews 2023), and a negligible capacity of the phloem to transport H+ (Raven 1977), to the root whence it could be pumped into the root medium using a P-type ATPase accompanied the anion (e.g. Cl-) that accompanied Ca2+ up the xylem, the shoot acidifies according to Eq. 1: Ca2þ ðroot mediumÞ þ 2 Cl - ðroot mediumÞ þ CO2 ðatmosphereÞ þ H2 O ðroot mediumÞ → CaCO3 ðleaf apoplasmÞ þ 2 Hþ ðshoot cellsÞ þ 2 Cl - ðshoot cellsÞ

ð1Þ

Since the cystoliths are in invaginations of the apoplasm, the H+ acidifies the apoplasm, initially at least. Alternatively, Ca2+ could move up the xylem with a doubly-charged organic anion (e.g. malate2-) leaving 2 H+ in the root medium, whose catabolism to neutral organic C, 2 CO2, and 2 OH- in the shoot permits (Eq. 2): Ca2þ ðroot mediumÞ þ Cxþ2 Hy Ozþ4 2 - ðroot cellsÞ þ 2Hþ ðroot mediumÞþ → CaCO3 ðshoot apoplasmÞ þ Cx Hy Oz ðshoot cellsÞ þ CO2 ðshoot cellsÞ

ð2Þ

Production of the dicarboxylate2- in the roots from neutral carbohydrate plus CO2 involves excretion to the root medium of 2 H+. There appears to be no evidence of whether the mechanisms in Eq. (1) or in Eq. (2) predominate in cystolith production. For CaCO3 production by organisms in aquatic environments, including seawater, the overall reaction producing CaCO3 from the dominant dissolved inorganic C species at the pH of most surface waters (predominantly seawater) is shown in Eq. (3); (see also Frankignoule et al. 1994). 2 HCO3 - þ Ca2þ → CaCO3 þ H2 O þ CO2

ð3Þ

Re-equilibration of the inorganic carbon system causes acidification. Ca(COO)2 deposition in plant shoots with photosynthetic production of oxalate (other from oxidation of photorespiratory glycolate: Raven and Andrews 2023) requires photosynthetic production of carbohydrate (Eq. 4), followed by oxidation to oxalic acid via one of the three pathways outlined by Raven and Andrews (2023) with the overall Eq. (5)

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2 CO2 þ 4 H2 O þ ≥ 16 photons ð400–700 nmÞ → 2 CH2 O þ 2H2 O þ 2 O2 

ð4Þ

2 CH2 O þ 1:5 CO2 → ðCOOHÞ2 þ H2 O

ð5Þ

The Ca2+ is supplied from soil and movement up the xylem of Ca2+ + 2 Cl(Eq. 6): ðCOOHÞ2 þ Ca2þ þ 2 Cl - → CaðCOOÞ2 þ 2 Hþ þ 2 Cl -

ð6Þ

Deposition of Ca(COO)2 in shoots could also result from oxalate synthesis in roots from sucrose translocated moved from the shoot in the phloem. The occurrence of oxalate in roots (Morita and Tuji 2002; Morita et al. 2004; Rahman et al. 2010b; Ikka et al. 2013), and the efflux of oxalate from roots (Ma and Miyasaki 1998; Kidd et al. 2001; Yang et al. 2005; Tao et al. 2016; Wu et al. 2016), is consistent with oxalate synthesis in roots. The possibility that root oxalate is translocated from the shoot is inconsistent with (almost) all of the available evidence showing a negligible concentration of oxalate in phloem sap (Canny 1973). The suggestion of oxalate transport in the phloem comes from Richardson et al. (1982) who found 0.1 mol m-3 oxalate (and 42.9 mol m-3 malate) in cucurbit ‘phloem’ exudate. However, Fiehn (2003) found no detectable oxalate (and only 1.6 mol m-3 malate) in such exudate, and Zhang et al. (2012) showed that part of the ‘phloem’ exudate of cucurbits is from a source other than the sap exuded from sieve tubes. Accordingly, the conclusion stands that oxalate is not phloem-mobile. The occurrence of oxalate in some xylem saps (Larbi et al. 2010; Tooulakou et al. 2016a, b; cf. Morita et al. 2004) is, then, a result of oxalate synthesis in roots. There are four mechanisms of conversion of photosynthate to oxalate (Raven and Andrews 2023). One of these, oxidation of glycolate produced from phosphoglycolate resulting from the oxygenase activity of Rubisco, cannot occur in (non-photosynthetic) roots. Here the oxidation of ascorbate to oxalate plus threonate is assumed (Eq. 7): Ca2þ ðfrom root mediumÞ þ C6 H7 O6 - ðroot cellsÞ þ 3 H2 O ðfrom root mediumÞ þ O2 ðfrom root mediumÞ → Ca2þ ðroot cellsÞ þ 2 Hþ ðroot mediumÞ þ C4 H7 O5 - ðroot cellsÞ ðCOOÞ2 2 - ðroot cellsÞ þ 2 H2 O

ð7Þ

Synthesis of these insoluble Ca compounds in the aerial shoots, without organic anion transport from the roots, is a means of neutralising the OH- generated by NO3- assimilation into organic N without increasing the osmolarity of shoot cells (Raven and Smith 1976; Raven and Farquhar 1990; Raven and Andrews 2023). In this case, Ca2+ moves up the xylem with 2 NO3-. In the shoot 1 NO3- is reduced to 1 NH4+ that is then assimilated into neutral organic N (with -NH3+ = -COO-) with

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production of 1 OH- (Raven and Smith 1976; Raven and Farquhar 1990; Raven and Andrews 2023). The OH- -neutralising role of oxalic acid is the same regardless of whether the resulting (COO)22- remains in solution in the vacuole (e.g. as 2 K+ (COO)22-) or is precipitated as Ca(COO)2, possibly in the vacuoles of cells other than those in which the NO3- assimilation occurs. The OH- -neutralising role of oxalic acid is demonstrated by the greater content of oxalate2- (soluble and as Ca (COO)2, less commonly Mg(COO)2) in plants supplied with NO3- rather than NH4+ as the N source (Joy 1964 Beta vulgaris; Oka and Kagawa 1996; Zhang et al. 2005 Spinacia oleracea; Morita and Tuji 2002; Morita et al. 2004 Camellia sinensis; Tian et al. 2008 Oryza sativa (based on total oxalate, not just Ca(COO)2; Al Daini et al. 2013 Atriplex nummularia; Rahman et al. 2010a Pennisetum purpureum). A contrary finding is that of Franceschi (1987) who found more Ca(COO)2 in Lemna minor grown of NH4+ than with NO3- as N source. However, Lemna minor is a small (1–8 mm long, 0.6–5 mm wide, roots 10–20 mm long) pleustophyte (Raven 1981, 2018) living at the interface of air and water, so the H+ from NH4+ assimilation, and Ca(COO)2 production, can be lost to the aqueous medium, as can OHfrom NO3- assimilation. The content of Ca(COO)2 on a leaf dry matter or fresh matter content increases with leaf age in Eucalyptus diversicolor (O’Connell et al. 1993) but Ca(COO)2 on a dry matter basis decreased slightly with leaf age in Colocasia esculenta (Oscarson and Savage 2007) and was the same on a dry matter basis for young and mature leaves of Beta vulgaris (Simpson et al. 2009); either correlation with leaf age is consistent with the OH- removal role (Raven and Andrews 2023). Tian et al. (2008) showed for Oryza sativa that NO3--increased oxalate content was dependent on NO3- reductase, consistent with the OH- removal role of increased oxalic acid synthesis with NO3- rather than NH4+ as N source. Raven and Andrews (2023) point out that a potential advantage of accumulating Ca(COO)2 rather than soluble 2K+ (COO)22- or 2K+ malate2- as the product of organic acid synthesis employed in OH- neutralisation is that there is no requirement for K+ salts at higher concentration than is needed for leaf cell expansion and the hydraulic skeleton. Raven and Smith (1976) suggested that production of CaCO3 in cystoliths might, like Ca(COO)2 deposits, act as an osmotically inactive means of disposing of OHproduced in NO3- assimilation in shoots. However, there appears to be no published evidence on the occurrence of variation in cystolith production as a function of NH4+ or NO3- as N source.

5.2

Ca Accumulation

A second outcome of Ca(COO)2 production is sequestration of Ca2+: Franceschi and Nakata (2005) and Paiva (2019) discuss the use of Ca(COO)2 in a high capacity Ca2+ regulation in plant cells. It is important to note that synthesis and breakdown of Ca (COO)2 in accumulating and releasing Ca2+ may temporally conflict with the acidbase regulation role of Ca(COO)2 mentioned in the previous paragraphs. Paiva

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(2019) points out that, although there is a good correlation of Ca2+ availability and Ca(COO)2 deposition in Ca(COO)2 producing plants, and some evidence of crystal dissolution when external Ca2+ is decreased (Franceschi 1989), there is very little evidence of use of the released Ca2+ in other metabolic processes (Paiva 2019). A major problem is the phloem immobility of Ca2+, restricting movement to Ca2+ from Ca(COO)2 to seeds and vegetative storage organs (Raven 1977; White and Broadley 2003; Paiva 2019). The suggestion that cystoliths act as Ca2+ stores goes back to Chareyre (1885), with variable subsequent results as to Ca2+ release from cystoliths (Ajello 1941). As with the use of Ca(COO)2 as a reversible Ca2+ store, releasing Ca2+ from CaCO3 would have consequences for the acid-base regulation.

5.3

Light Scattering

A third outcome of the occurrence of the Ca-containing particles is increased light scattering (Tyrell et al. 1999; Gal et al. 2012b; von Dassow et al. 2012; Balch 2018; Karabourniotis et al. 2020, 2021). Light scattering occurs at boundaries between phases of different refractive index, e.g. at the interface of intercellular gas spaces and cell walls, of starch grains and the surrounding plastid stroma, Ca oxalate (druse) crystals in cell vacuoles, amorphous CaCO3 particles (cystoliths) in invaginations of plant cell walls, and extracellular aragonite or calcite crystals and the aqueous medium (Vogelmann 1993; DeLucia et al. 1996; Raven 1996; Kuo-Huang et al. 2007; Xiao et al. 2016; Pierantoni et al. 2017; Raven 2017; Balch 2018; Pierantoni et al. 2018; Karabourniotis et al. 2020, 2021; Pierantoni et al. 2020 (unrefereed)). The global significance of light scattering by calcite crystals is shown by the satellite imaging of coccolithophore blooms in the surface ocean, usually specially after viral infection of the algae with coccolith release (Balch et al. 1991; Gordon et al. 2009; Raven 2017; Balch 2018). Pierantoni et al. (2020), in a non-refereed paper, show that cystoliths of Ficus enhance photosynthesis by light scattering within the leaf even at saturating irradiances. Fournier and Neukermans (2017) separated backscattering of heterococcoliths of the diploid phase of the life cycle of the coccolithophore Emiliania huxleyi into diffraction, refraction, and reflection. Quinitero-Torres et al. (2006) demonstrated coherent scattering of potentially damaging ultraviolet radiation converting the radiation into longer, photosynthetically active, wavelengths by holococcoliths of the haploid phase of the life cycle of coccolithophores. Monteiro et al. (2016) and Balch (2018) discuss the impact of light scattering by coccoliths on photosynthesis in coccolithophores, and suggest that since species that grow deep in the photic zone have an urn-shaped arrangement of coccoliths; the cells are oriented as the cell sinks through the water column so that their coccoliths reflect light into the cell, although this suggestion has not yet been tested. At high light it has been suggested that coccoliths over the surface of spherical cells, by reflecting light incident on the cell, limit photoinhibitory damage; however, in the case of Emiliania huxleyi, even

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uncalcified cells are very resistant to photoinhibition (Monteiro et al. 2016; Balch 2018). Since calcification has a significant energy cost, it is possible that producing additional coccoliths at high irradiances can act in light energy dissipation (Monteiro et al. 2016). Raven (2017) emphasises the role of coccoliths, in the coccosphere and especially after release as individual coccoliths, e.g. after viral lysis of cells, in the surface ocean in increasing the albedo of the ocean. However, the small increase in the global albedo, and the resulting small limitation on the increase in global temperature, is offset by the greenhouse effect of the CO2 released in the production of CaCO3 from Ca2+ and HCO3- (Raven 2017). Raven (2017) points out that about 0.68 mole CO2 is produced per mole CO3= precipitated at 20°C in seawater in equilibrium with present atmospheric CO2 (Frankignoule et al. 1994).

5.4

Increased Density

A further consequence of calcification is an increase in density of the organism. For planktonic organisms, this increases the sinking rate of a calcified cell relative to that of an otherwise identical uncalcified cell (Monteiro et al. 2016). Monteiro et al. (2016) point out that the effect of calcification on sinking rate is greater for larger coccolithophores that would have faster sinking rate even if uncalcified. Raven and Waite (2004) contrast the acclimatory changes in mineralisation of planktonic diatoms (silica) with that of coccolithophores (calcite). While diatoms increase mineralisation, and hence sinking rate, with limitation of growth rate by low light or low concentration of phosphate or combined nitrogen, coccolithophores have increased mineralisation at low concentrations of phosphate or combined nitrogen (Paasche 1998), but decreased mineralisation at low light (Paasche 1999). Granted the inverse gradients of light and nutrients in the surface ocean, increased coccolith production under nutrient limitation increases the rate of sinking to higher nutrient concentrations, while the decreased coccolith production under low light decreases the rate of sinking to even lower irradiances (Raven and Waite 2004). Monteiro et al. (2016) provide a more detailed account of the relevance of calcification to the hydrodynamics of coccolithophores to their ecology. For flowering plants, the calcified freshwater pleustophyte (Raven 1981, 2018) Stratiotes aloides typically shows annual vertical migration, to the surface of the water body in spring and to the sediment in autumn, with the extent of calcification playing a role in the migration (Prins and DeGuia 1986; Harpenslager et al. 2015).

5.5

Defence from Herbivores and Pathogens

Stromatolites, i.e. laminated calcified microbial mats typically involving cyanobacteria photosynthesis resulting in CaCO3 precipitation, co-exist with grazing metazoan (Rishworth et al. 2016, 2017a, b). It now seems clear that it was not the

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evolution and diversification of grazers that caused the global decline of stromatolites since the Mesoproterozoic 1,000 Ma ago (Garrett 1970; Pratt 1982; Grotzinger 1990; Rishworth et al. 2016, 2017a, b). The occurrence of grazers of stromatolites means that any defence by stromatolites is incomplete; what is not clear is whether the continued existence of stromatolites is the result of their defence against grazing (bottom up control) or the result of control of limitation of the grazer population by a higher trophic level (top down control). Calcified marine benthic macroalgae include the coralline red algae and calcified members of the Ulvophyceae. Most of the work on herbivory on calcified marine macroalgae has been carried out on crustose coralline red algae (Steneck 1983, 1985, 1986; Steneck et al. 1991). The timing of the evolution of calcification in red algae (Peña et al. 2020) has been related to the diversification of grazing metazoans (molluscs, echinoids, fish capable of attacking CaCO3), with non-calcified algae more vulnerable to grazing than calcified algae (Steneck 1983, 1985, 1986; Steneck et al. 1991). However, there are no data on the extent, if any, to which calcification limits grazing of calcified macroalgae. Monteiro et al. (2016) cite a number of reasons why coccoliths should limit herbivory of coccolithophores, e.g. the frequent occurrence of protrusions from coccoliths, and the possible metabolic cost of removing the coccosphere before digestion of the organic matter of the coccolithophore. However, restricted defence against herbivory is indicated by three lines of evidence that coccoliths have a limited, if any, role in defence against herbivores One line of evidence suggesting a limited role of coccoliths in limiting herbivory comes from analysis of zooplankton faecal pellets, which are often rich in a range of coccoliths (Hattin 1975; Silver and Bruland 1981). Another line of evidence is the absence of a difference in grazing of calcified and non-calcified strains of Emiliania huxleyi and of Hymenomonas carterae by the copepod Calanus finmarchicus: however, these data only involve two species of coccolithophore and a single manner of feeding by a single species of grazer (Sikes and Wilbur 1982). A third line of evidence comes from a meta-analysis of mesocosm experiments showing that there is no significant difference in the ratio of grazing rate to growth rate for Emiliania huxleyi to the ratios for non-calcified eukaryotic picophytoplankton and nanophytoplankton (Mayers et al. 2020). Clearly more data are needed, involving a range of coccolithophores. Monteiro et al. (2016) also discuss the possible role of coccoliths in limiting viral and bacterial attack on coccolithophores. Clearly the calcified diploid phase of Emiliania huxleyi, the most common eukaryotic phytoplankton organism (Emiliani 1992), is subject to viral infection and lysis (Frada et al. 2008), while the uncalcified haploid phase can be infected by the virus but is not lysed (Mondecai et al. 2017). Data are needed for other coccolithophore species that are less common and so less likely to be encountered by virus particles. Again for Emiliania huxleyi, the bacterium Phaeobacter inhibens infects and can kill both the diploid calcified phase and the haploid uncalcified phase of a calcified strain, but not the diploid phase of several uncalcified strains (Bramucci et al. 2018). These results are not consistent with coccolith inhibition of infection by bacteria: more data are needed.

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There seems to be no direct evidence of cystoliths in limiting herbivory. Evidence against anti-herbivory action of cystoliths would be the occurrence cystoliths in faeces. It might be expected that cystoliths would not survive passage through the gut, especially if some place along the gut is acidic. However, CaCO3 occurs in spherolites in the faeces of some mammals and birds (Canti 1997, 1998, 1999), with the highest spherolite content in faeces in ruminant herbivores, with none in the faeces of caecum-fermenting herbivores. Omnivores have a low spherolite content in their faeces, with even less in faeces of carnivores (Canti 1997, 1998, 1999). However, spherolites are not cystoliths, or formed from cystoliths, but are formed to different extents in the gut of mammals and birds (Canti 1997, 1998, 1999). As for plant pathogens, the limited available evidence shows that the pathogen Pseudomonas syringae associates with cystoliths, rather than avoiding them, in Morus leaves (Gupta et al. 1995). Franceschi and Nakata (2005) and He et al. (2014) discuss the use of Ca(COO)2 in protection against herbivory. Molano-Flores (2001) mimicked herbivory seen in the field on Sida (Malvaceae) by removing half of leaf blades and showed that Ca (COO)2 increased in the remainder of the plant. Korth et al. (2006) showed that Medicago truncatula mutants lines with decreased Ca(COO)2 content were preferred relative to wild-type by caterpillar larvae of the beet armyworm Spodoptera exigua, and that larvae feeding on the wild-type showed slow growth and greater mortality than those feeding on mutant lines. Korth et al. (2006) and Park et al. (2009) also showed that Ca(COO)2 crystals of Medicago truncatula abraded caterpillar mouthparts and decreased digestibility of the ingested plant material. However, some phytopathogenic fungi (e.g. Sclerotinia sclerotiorum) that attack Medicago truncatula secrete oxalate as part of pathogenesis, and activity of an enzyme that catabolises oxalate can also decrease Ca(COO)2 content (Foster et al. 2016). For vertebrate herbivores, Ward et al. (1997), Ruiz et al. (2002a, b) investigated the effect of variations in the Ca(COO)2 content of the desert lily Pancratium sickenbergeri on herbivory by dorcas gazelle (Gazella dorcas) in the Negev Desert. This detailed study showed the defence by Ca(COO)2 is constitutive rather than inducible, and that no evidence could be found of a trade-off between growth and defence (Ward et al. 1997; Ruiz et al. 2002a, b). Troyo et al. (2021) show that clownfish (Amphiprion spp.) do not consume seagrass fruits that, like those of Thalassia testudinum, contain calcium oxalate. Lev-Yadun and Halpern (2008) suggest that Ca(COO)2 crystals can introduce bacterial or fungal pathogens into herbivores by piercing the external surface or gut epithelium of the herbivore; further work is needed on the time scale of effects of the pathogen on the herbivore and the extent to which the plant that bears the sharp crystals is protected. Finally, Paiva (2021) counsels against predictions of anti-herbivory effects of Ca (COO)3 crystals based on structure of the crystals without observational or experimental data on their effectiveness in limiting herbivory.

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311

Pollen Release from Anthers

Horner and Wagner (1980) and Horner and Wagner (1992) showed that synthesis of Ca(COO)2 in anthers of Capsicium annuum (Solanaceae) weakens cell walls and aids pollen release. However, Liu et al. (2022) found that calcium oxalate is involved in anther dehiscence of Nicotiana bacon (Solanaceae) via calcium oxalate catabolism with H2O2 production.

6 Outcome of Alternating Synthesis and Breakdown of CaCO3 and Ca(COO)2 6.1

Alarm Photosynthesis

A relatively recent finding is that crystals of Ca(COO)2 (Tooulakou et al. 2016a, b, 2019; Karabourniotis et al. 2020) and CaCO3 (Gianopoulos et al. 2019; Karabourniotis et al. 2020; Gómez-Espínoza et al. 2020, 2021) can act as an internal CO2 source in photosynthetic structures when water is scarce and stomata are closed in the light, the so-called Alarm Photosynthesis. Here the Ca(COO)2 and CaCO3 are produced in the dark with the stomata open, and CO2 is released in the light as Ca (COO)2 and CaCO3 are catabolised with closed stomata and are assimilated in photosynthesis (Tooulakou et al. 2016a, b; Gianopoulos et al. 2019; Tooulakou et al. 2019; Karabourniotis et al. 2020). Diel measurements of Ca(COO)2 and CaCO3 show the changes consistent with the alarm photosynthesis hypothesis in the organisms tested under water-limited conditions (Tooulakou et al. 2016a, b, 2019; Gianopoulos et al. 2019; Karabourniotis et al. 2020). This use of CaCO3 and Ca (COO)2 would impact on and/or reverse the physicochemical outcomes of Ca (COO)2 and CaCO3 synthesis. Alarm photosynthesis has parallels with Crassulacean Acid Metabolism in which external CO2 is stored at night as malic acid and refixed in photosynthesis in the day with closed stomata (Osmond 1978; Lüttge 2004; Heyduk 2022; Winter and Smith 2022). Raven (1984) and Raven and Spicer (1996) suggested a CaCO3-based analogue of Crassulacean Acid Metabolism, but without observational or experimental support. Tooulakou et al. (2016a) showed that the δ13C natural abundance stable isotope ratio (defined in Table 1) is -7.06 ± 0.12 (n = 3)%O for oxalate and -16.98 ± 0.22 (n = 3)%O for total leaf organic matter in the leaves of the C4 plant Amaranthus hybridus, and suggest that this shows that the C source for oxalate synthesis is respired CO2 rather than photosynthesis. The rationale here seems to be that net synthesis of oxalate under the experimental conditions occurs in the dark. However, the known pathways of dark synthesis of oxalate, i.e. excluding the light-dependent pathway from phosphoglycolate produced in photorespiration, that only supported a limited C flux in C4 plants, use solely organic carbon (ascorbate pathway) or organic carbon plus anaplerotically assimilated inorganic C (glyoxylate pathway,

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oxaloacetate lyase). While dark respiration in leaves generates CO2 that is 13 C-enriched (higher δ13C) relative to bulk leaf δ13C (meta-analysis of Ghashghaie and Badeck 2014; for more detail on a C4 plant see Ghashghaie et al. 2016), this cannot, alone, explain the δ13C of oxalate in A. hybridus.

7 Outcome of Boring into CaCO3 7.1

Dissolution of CaCO3 as a Source of CO2 for Rubisco

Guida et al. (2017) showed that solid CaCO3 acts as the CO2 substrate for RuBisCO in photosynthesis by endolithic Mastigocoleus testarum, especially under conditions of photosynthetic limitation by the external (to the solid carbonate) dissolved inorganic carbon. It is not clear how much energy is needed for Mastigocoleus testarum to mine dissolved inorganic carbon from the solid CaCO3 by removing Ca2+, and adding H+. This additional energy cost of photoautotrophic growth would be particularly important in the endolith was shaded by some other phototroph, e.g. by Symbiodiniaceae in the case of a coral endolith.

8 Conclusions CaCO3 precipitates occur inside a few cyanobacteria and green algae. More common is precipitation on the surface of cyanobacteria, and on the surface of a diversity of algae; in the case of coccolithophores and the few calcified dinoflagellates, CaCO3 is precipitated with organic matter in intracellular vesicles and the resulting structures are externalised. CaCO3 is precipitated as cystoliths in invaginations of the cell wall of a few cells in the shoots of some terrestrial flowering plants, and on the surface of a few submerged freshwater flowering plants and a seagrass. The precipitation of CaCO3 on the surface of photosynthesising structures from Ca2+ and HCO3- is related to the consumption of CO2 in photosynthesis. By contrast, precipitation of CaCO3 from Ca2+ and HCO3- in intracellular vesicles before externalisation in coccolithophores and some dinoflagellates generates CO2 that is usable in photosynthesis. CaCO3 is precipitated around roots of some flowering plants by an incompletely understood mechanism; CO2 production by root respiration typically solubilises soil CaCO3. A few cyanobacteria and eukaryotic algae can bore through solid CaCO3 by removing Ca2+ and adding H+ at the site of boring, generating soluble inorganic C that can be used in photosynthesis. Ca(COO)2 is precipitated in the vacuoles of some algae and in the vacuole of many, and the cell wall of some, vascular plants. In many cases, the precipitation is controlled by the organism, in other cases it appears to be accidental as product of oxalate= and Ca2+ accumulation in the vacuole.

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An inevitable outcome of precipitation of CaCO3 using CO3= produced from CO2 and Ca2+ is the production of H+; the same is the case for precipitation of Ca (COO)2 from (COOH)2 and Ca2+. The H+ could be used to neutralise OH- produced in NO3- assimilation in the shoot without increasing cell osmolarity. There is evidence for this function of Ca(COO)2 in neutralising some of the OH- reproduced in NO3- assimilation in land plant shoots, but not of CaCO3 fulfilling this role. Another inevitable outcome of CaCO3 and Ca(COO)2 precipitation is Ca2+ immobilisation, though with little evidence of remobilisation of Ca2+ under Ca2+ deficiency. Any such remobilisation would reverse the OH- neutralisation from NO3- assimilation. Other inevitable consequences of CaCO3 and Ca(COO)2 precipitation are light scattering with implication for photosynthesis and photoprotection, and increased density of the structure in which precipitation occurs. Defence against herbivores and pathogens is better established as a function of Ca (COO)2 precipitates than for those of CaCO3. Pollen release from anthers in some flowering plants is related to Ca(COO)2; there is no evidence of such a role for CaCO3. A recently discovered role of CaCO3 and Ca(COO)2 is ‘alarm photosynthesis’, in which atmospheric CO2 is fixed into CaCO3 and Ca(COO)2 with open stomata in the scotophase when evaporative water loss is limited, and CaCO3 and Ca (COO)2 are catabolised in the photophase with release of CO2 and refixation by photosynthesis with closed stomata and restricted water loss. Acknowledgements Discussions with Mitchell Andrews, Mary Beilby, Colin Brownlee, Dianne Edwards, Graham Farquhar, Mario Giordano*, Andrew Smith, Alison Taylor, Anya Waite, Glen Wheeler, and Philip White have been very useful. *Deceased: 15-5-1964 – 29-12-2019. The University of Dundee is a registered Scottish charity, No SC051096. Competing Interests No competing interests are declared.

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Soil Hydraulic Constraints on Stomatal Regulation of Plant Gas Exchange Fabian J. P. Wankmüller and Andrea Carminati

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Transpiration and its Regulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Hydraulic Components of the Soil-Plant Continuum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Modelling Soil-Plant Hydraulics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Optimal Stomatal Regulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Plant Water Use Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

328 329 331 334 337 340 342 343

Abstract Terrestrial water fluxes are dominated by transpiration, with stomata exerting an important control by regulating transpirational water loss. Transpiration and stomatal conductance are in turn constrained by the hydraulic properties of the soil-plant-atmosphere continuum, thus providing a link between the physics of water flow (soil-plant hydraulics) and the gas exchange between vegetation and atmosphere (via stomatal regulation). In this article, we review the principles of water flow in soil and plants and the links to stomatal responses to decreasing soil water availability. We make use of a soil-plant hydraulic framework to define the physical constraints on transpiration and predict stomatal responses. We then discuss the role of soil-plant hydraulics for different plant water use strategies (i.e. degree of iso/anisohydry) with changing soil hydraulic properties, root hydraulic distribution and xylem vulnerability.

Communicated by Christoph Leuschner F. J. P. Wankmüller and A. Carminati (✉) Department of Environmental Systems Science, Institute of Terrestrial Ecosystems, Physics of Soils and Terrestrial Ecosystems, ETH Zurich, Zurich, Switzerland e-mail: [email protected]; [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 Progress in Botany (2024) 84: 327–350, https://doi.org/10.1007/124_2023_68, Published online: 8 August 2023

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1 Introduction Land plants are hydraulic engineers capable to thrive in an inherently dry atmosphere which tends to dehydrate plant tissues. Land plants can benefit from this persistent atmospheric dryness as the low water potential ψ [MPa] of the atmosphere drives the total soil-plant water flow. This is a passive process where no metabolic energy is required to absorb and lift up soil water. The long-standing explanation for plant water transport is the cohesion-tension mechanism (Böhm 1893; Dixon and Joly 1895; Askenasy 1895): It states that the tension (negative water potential) of the liquid water stream caused by the air-water interface at the leaf evaporating sites is mediated and continued through hydrogen bonds in the water column downwards in the xylem. In a sense, the persistent driving force between soil and atmosphere requires plants to provide ‘only’ a water conducting system in which water is passively extracted from the soil and pulled up to the canopy. Yet, there is a downside to the persistent atmospheric dryness driving plant water transport, as it exerts a high tension on the liquid water phase (Böhm 1893). As plant water potentials fall, water may enter a metastable state at the risk of embolism (Tyree and Sperry 1989). Xylem vulnerability to embolism spans a wide range across species and biomes (Choat et al. 2012) – roughly from -1 to -15 MPa (P50 values) with lower water potential thresholds (greater tensions to induce xylem cavitation) typically occuring in species and biomes in arid environments (Brodribb and Hill 1999). To cope with the risk of embolism and hydraulic failure, plants have evolved safety mechanisms, such as stomatal closure, to operate at less negative water potentials, thus delaying embolism formation (Jones and Sutherland 1991; Anderegg et al. 2017). Although water is essential for plant metabolism, such as photosynthesis, the overarching amount of water molecules are lost through transpiration exiting the stomatal pores. Thus, the soil-plant continuum needs efficient hydraulic transport capacity to conduct the large amounts of transpirational water. On the one hand, this makes transpiration dominating average terrestrial evapotranspiration, giving land plants a key role in the global water cycle (Jasechko et al. 2013). On the other hand, the carbon-for-water use efficiency of plants is very low and ranges between 10-3 and 10-2 molCO2 molH2O-1 (Nobel 1991). Despite our understanding of the drivers of transpiration, estimates and predictions of terrestrial gas exchange during drought are poorly accurate and often overestimated (Anderegg et al. 2017). A key reason for this is the uncertainty in precisely predicting stomatal responses to declining soil and plant water status (Sperry et al. 2017). Soil-plant hydraulics provides both explanatory and predictive value for stomatal regulation of plant gas exchange. Aiming to fully exploit soilplant hydraulics for better predictions of leaf gas exchange, we review fundamental concepts and model approaches that link the physical constraints of soil-plant water flow to stomatal responses during drought as well as discuss the role of soil-plant hydraulics for plant water use strategies (iso/anisohydry).

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2 Transpiration and its Regulation Transpiration (per unit leaf area) Eleaf [mmol m-2 s-1] can be described by Fickian diffusion where (1) the water potential gradient is the driving force and (2) the leafto-atmosphere conductance is the diffusion coefficient (Manzoni et al. 2013). (1) The driving force of transpiration originates from the water potential differences between the dry atmosphere and the wet stomatal air space. It equals the atmospheric vapour pressure deficit VPD [kPa], which depends on temperature and air humidity, assuming that stomata are saturated with vapour (RHair-stomata ~ 100%, Farquhar and Raschke 1978) and that the temperature difference between leaf and ambient air is small (Tleaf ~ Tair) (Manzoni et al. 2013). (2) The conductance of water vapour is determined by the flow path through the leaf intercellular air spaces, the stomatal pore itself and the outside-leaf boundary layer. The conductance through the stomatal pore (per unit leaf area) gs [mmol m-2 s-1] is determined by the number and opening width of the stomatal pores, which occupy 0.2 to 2% of the leaf surface (Nobel 2020). Under typical field conditions (well-coupled canopy), stomatal conductance is the lowest conductance within this flow in series, and therefore has the largest control on the transpiration flux (Nobel 2020). Therefore, leaf transpiration rate is well regulated by the plant and can typically be simplified to Eleaf = gs × VPD/ patm (where patm [Pa] is atmospheric pressure). The opening and closing of stomata regulates the transpirational water loss and the CO2 uptake required for photosynthesis. Regulation of transpiration at the leaf level (stomatal opening/closing) is most effective because the gradient in water potential between leaves and the atmosphere dominates the total water potential gradient in the soil-plant-atmosphere-continuum (Fig. 1) (Manzoni et al. 2013). Thus, small changes in stomatal conductance are sufficient to cause effective changes in transpirational water loss. In turn, a change in transpiration rate induced by stomatal movement also affects the driving force for liquid water flow, which is the difference between leaf and soil water potential ψleaf – ψsoil. Conversely, small changes in leaf water potential can cause effective changes in stomatal conductance as most plants need to keep relatively high (slightly negative) water potentials in their tissues. At moderate VPD levels (Scots pine>European beech>sessile oak. The development of the portion of annual gross stem volume growth that ends up in standing stock over time is shown in Fig. 7. It indicates in particular, how much of the wood remains unused in unmanaged stands. This net growth proportion shows a strong variation as it depends on various environmental impacts, including sitespecific stressors or disturbances that caused continuous or immediate mortality increases. Site quality played only a minor role. A statistically indicative increase of net growth proportion with increasing site index was only found for Scots pine. However, the ratio between net and gross stem volume growth of the stand declined with stand age for all four tree species and was on average high in the early stand development phase and close to zero in old stands.

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Fig. 5 Yield (upper row), growth (medium row), and the proportion of net growth related to total annual gross growth (lower row) of selected long-term experimental plots in South Germany: Norway spruce (Schongau 2/1), Scots pine (Schnaittenbach 57/1), European beech (Fabrikschleichach 15/1) and, sessile oak (Rohrbrunn 90/1) (from left to right). The abbreviations

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Relationship Between Growth and Mortality

This section demonstrates that tree mortality in unmanaged stands is closely linked to growth and thus can strongly increase under improved growing conditions. Many environmental changes such as the extension of the growing period due to climate change (Kauppi et al. 2014; Qi et al. 2015) and the eutrophication by long-term nutrient deposition (Etzold et al. 2020; Krause et al. 2012) have been shown to accelerate tree and stand growth, especially on sites with ample water supply. The effects may differ between species (Condés and del Río 2015; Schwarz and Bauhus 2019; Zimmermann et al. 2015), affecting the relationship between species in mixed stands (e.g., drought-tolerant species such as pine or oak may take advantage over more sensitive species as spruce or beech). Indeed, growth trend analyses showed a growth acceleration of the quadratic mean tree diameter by 20–30% since the beginning of systematic measurements in the nineteenth century for Norway spruce (Picea abies [L.] KARST.), European beech (Fagus sylvatica L.), and sessile oak (Quercus petraea (Matt.) Liebl. and Quercus robur L.); however, it hardly affected the self-thinning line (Pretzsch et al. 2022b). Thus, the mean stem diameter develops along the same self-thinning line (N-dq trajectory, with N being tree number per hectare and dq quadratic mean stem diameter) as in the past, but the progress is much faster. This phenomenon has been theoretically explained in Fig. 3. Various studies showed that tree growth has actually increased in Europe since the 1960s (Elfving and Tegnhammar 1996; Pretzsch 2020; Pretzsch et al. 2014; Spiecker et al. 2012). Therefore, we split the dq-age records into observations before and after 1960 (Figs. 8 and 9). First, we investigated the relationship for European beech, using the dataset described under Sect. 4.1.2. We found that mean stem diameter was significantly higher after 1960 than before; over the whole age range covered by stands, we found an acceleration of stem growth (Fig. 8a). The linear regression lines in Fig. 8b show the well-known decrease of the relative growth rate, RGR with progressing stand age. However, the level of RGR significantly increased from the period before to after 1960. This growth acceleration is associated with an increase in mortality (Fig. 8c). We estimate that the acceleration of stem diameter growth at age 60 is 23% while the mortality increase at the same age is 16%. Figure 8d shows that the mortality rate MR increases proportionally with a growth rate consistently throughout the rotation period. Under constant maximum stand density conditions, the relative growth rate RGR determines MR because the increase in tree size also increases space demand per tree. It is important to notice that the carrying capacity and thus the slope and intercept of the self-thinning line did not significantly change (SDI = 628±13 trees (of dq = 25 cm reference stem  ⁄ Fig. 5 (continued) SON 2/1, SNA 57/1, FAB 15/1, and ROH 90/1 indicate the names of the experimental plots (Schongau, Schnaittenbach, Fabrikschleichach, and Rohrbrunn, respectively), the numbers of the experiments (2, 57, 15, and 90, respectively), and the number of the respective plots (the unthinned plots no. 1 in all cases) that were selected for this analysis

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Table 1 Overview of the total volume growth, standing stock, and dropout proportion of unthinned monospecific stands of Norway spruce, Scots pine, European beech, and sessile oak when older than 120 years

Species Norway spruce

Mean

Scots pine

Mean

Na 15

±SE

a

Mean

Sessile oak

Mean

Standing stock (m3 ha-1) 1,107 98

Dropout (m3 ha-1) 571 43

Dropout proportion (%) 34.4 1

134 2

882 50

628 35

254 25

27.9 2

28

148 4

1,135 56

797 40

338 23

29.4 1

26

165 7

951 30

622 20

329 14

34.5 1

±SE ±SE

Total growth (m3 ha-1) 1,678 137

21

±SE European beech

Age (years) 135 5

N number of stands

diameter) per hectare) despite the faster growth and mortality in more recent times (Fig. 8b, c). For the sake of simplicity, the age-dependency of RGR and MR is expressed with a linear model although an inverse j-shaped curve would have slightly improved the R2. The results from the larger dataset described under 4.1.2 are presented in Fig. 9. Similar to the findings for beech only, all four species show a larger stem diameter increase after 1960 than before (Fig. 9a–d). The larger stem diameter growth is accompanied by an increase in mortality and tree dropout although this is particularly expressed in younger ages (Fig. 9e–h). In other words, the growth acceleration causes an acceleration of competition-based mortality in the stands of all four species (Fig. 9i–l). The number of dropout trees in younger to medium ages increased by 20 to more than 100%. For example, in an oak stand with a mean stem diameter of 20 cm, a stand age of 80 years, and a tree number of 700 trees per hectare, the annual dropout of trees by competition-driven mortality is about 15 trees per hectare in the period before 1960 and 22 trees per hectare (about 50% higher) in the years after 1960. The effects of growth acceleration on the dropout in young and medium-aged stands were similar for the other tree species. Due to the accelerated growth and mortality after 1960, the stands also arrive earlier in the mature phase with low dropout (see also Sect. 3.2). For the whole dataset, it is apparent that the mortality rate increases with growth speed, as it is represented by RGR of the mean stem diameter (Fig. 10). The relationship was similar before and after 1960. This confirms the assumption that the mortality rate in unmanaged forests follows the competition development due to ground coverage which in turn is driven by tree dimensional increase.

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Fig. 6 Dropout of stand volume by natural thinning depending on stand age shown for unthinned stands of Norway spruce, Scots pine, European beech, and sessile oak. (SI, site index in terms of mean tree height in metre at age of 100 years)

4.4

Mortality in Mixed vs. Monospecific Stands

It is well established that gross stand growth in mixed forests is often increased compared to monospecific stands (del Río et al. 2022; Jactel et al. 2018) and also the stand density can be considerably higher (Jucker et al. 2015; Pretzsch and Biber 2016). For the age series and the triplets we used in this study (see Sects. 4.1.2 and

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Fig. 7 Continuous decrease of the net stand growth proportion with increasing stand age shown for unthinned stands of Norway spruce, Scots pine, European beech, and sessile oak

4.1.3), advantages of mixed forests have been reported particularly for mixtures with light-demanding and shade-tolerant species such as Scots pine and European beech (Heym et al. 2017; Pretzsch et al. 2015) or Scots pine and sessile oak (Pretzsch et al. 2020; Steckel et al. 2020). Thus, it can be expected that tree mortality is also different in the two types of forests and that overyielding will only partly be accumulated in the stand. To present this effect, we first demonstrate the impact of self-thinning in monospecific and mixed stands with trees from databases A and B (Figs. 11, 12, 13, and 14). A comparison of gross and net overyielding is then presented using the temporarily established triplets from database C (Fig. 15).

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Fig. 8 Growth and mortality of European beech before and after 1960 in South Germany. Relationships between (a) quadratic mean stem diameter, dq, and stand age, (b) relative rate of stem diameter growth, RGR, and stand age, (c) Mortality rate, MR, and stand age, and (d) MR and RGR. The empty and filled circles represent observations in periods before and after 1960, respectively. The straight lines represent linear regressions: (a) ln(dq) = 0.659 + 0.818 × ln (age) + 0.104 × factor, R2 = 0.93, (b) RGR = 0.029 - 0.0002 × age + 0.004 × factor, R2 = 0.46, (c) MR = 0.032 - 0.0002 × age + 0.008 × factor, R2 = 0.11, and (d) MR = 0.002 + 1.620 × RGR, R2 = 0.59. All correlation coefficients are significant at least at the level p < 0.05. dq quadratic mean stem diameter, RGR the relative growth rate of stem diameter growth, MR mortality rate

Natural thinning in mixed forests was generally higher than in monocultures except at young age and the difference between monospecific and mixed stands increased with stand development (Fig. 11). There is not much difference at the species level (b-d). Interestingly, the self-thinning slopes of the monospecific stands (red lines) were mostly close to the generalized Reineke slope of dNddq = 1.605 (Fig. 11, horizontal lines). Since above a mean diameter of about 10–20 cm, alienthinning (green lines) were always more intense, the competition in mixed forests seems to have more rigorous effects compared to monospecific stands. The mortality per stem diameter was not significantly different between mixed and monospecific stands for the pooled dataset with all investigated tree species (Fig. 12). However, mortality was slightly higher for Scots pine and Norway spruce when growing in a mixture (Fig. 12b, c). This indicates that even if there is no

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Fig. 9 Diameter development before and after the year 1960 over age (a–d), dropout rate relative to diameter (e–h), and relative dropout (i–l) for Norway spruce, Scots pine, European beech and sessile oak

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Fig. 10 Relationship between relative growth rate, RGR, and mortality rate, MR, for unthinned stands of Norway spruce, Scots pine, European beech, and sessile oak in Central Europe. Observations before 1960 are shown as empty circles and those after 1960 with filled circles

significant species-overarching effect at the stand level, a species-specific modification of mortality of one species at the expense of the other may still occur. (Note, that the mortality rate is a relative measure related to tree number; i.e. it does not consider that the absolute number of the dropout trees or their mean size may be different and result in a different dropout volume.) Considering the dimension of the trees that died, dropout trees in mixed stands had a higher mean diameter compared to monospecific stands (Fig. 13). The differences were significant when over all mixtures and also for Scots pine or European beech separately and mounted up to 10–20% (stem diameter, stem volume, mass). Thus, mortality in mixed forests is extended further into higher stem diameter classes compared to monospecific stands. Even if the mortality rates in terms of the number of individuals are equal, tree mass can be different. This is illustrated by the dropout mass compared between mixed and monospecific stands displayed over stem dimension (Figs. 14 and 15).

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Fig. 11 Self-thinning slopes dNdd in monospecific stands (red) vs. alien-thinning slopes dNdd in mixed stands (green) for (a) the stands in total and (b–d) Scots pine, Norway spruce, and European beech separately. The horizontal line represents Reineke’s generalized slope of dNdd = -1.605

The maximum of mass dropout occurs at a mean stem diameter of around 30 cm, which is equivalent to a stand age of 50–70 years (Fig. 14a). On average of all stands the dropout amounts to 2–4 t ha-1 year-1 in mixed and 1–2 t ha-1 year-1 in monospecific stands, i.e. alien thinning removes twofold the biomass compared to self-thinning in monospecific stands. The particular effect is species-specific (Fig. 14b–d) with Scots pine responding particularly sensitively to alien thinning (Fig. 14b) while Norway spruce is even less sensitive to alien-thinning than to selfthinning (Fig. 14c). The considerably higher dropout in mixed compared to mono-specific stands means that mixed stands may perform overyielding regarding gross growth, but that net overyielding may be much smaller or even negative. In this case, natural thinning causes that most of the overyielding ends up as turnover if not extracted by harvesting, which is demonstrated using 23 triplets of Scots pine (S. pi) and European beech (E. be). Figure 15a shows an overyielding (ratio of mixed to monospecific stand growth >1) of gross stem volume growth (OG) for the mixed stands as a whole. However, it also shows an underyielding (ratio < 1) of net stem volume growth (ON). The overyielding in terms of gross growth amounted to OGS. pi,E.be = 1.12±0.08 (mean ±SE) and the net growth showed an underyielding of ONS.pi,E.be = 0.39±0.25. The gross overyielding was significantly different from the net underyielding. At the species level (Fig. 15b) Scots pine (first and second box

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Fig. 12 Mortality rates in mixed (green) compared with monospecific (red) stands. The development of the mortality rates is shown for (a) the stands as a whole and (b–d) Scots pine, Norway spruce, and European beech separately

from the left) showed neither a significant overyielding of gross growth (OGS.pi,(E. be) = 1.11±0.15) nor a significant underyielding of net growth (ONS.pi,(E.be) = 0.62 ±0.22). European beech in contrast (Fig. 15b, third and fourth box from the left) showed a significant gross overyielding (OG(S.pi),E.be = 1.22±0.10) but no significant net underyielding (ON(S.pi),E.be = 0.99±0.16). The upper part of Table 2 summarizes that the mixing effects at the stand level are only partially reflected when quantified by the gross growth. The mean observed gross stem volume growth was 13.35 m3 ha-1 year-1 in mixed stands whereas the weighted mean of the monospecific stands was 12.15 m3 ha-1 year-1, i.e. higher than the mean expected gross growth (relation between the observed and expected gross growth of S.pi., E.be., 110%). The observed net growth was 28% lower than expected (respective relation between the observed vs. expected net growth 72%). The reason for this discrepancy is the 113% higher dropout in the mixed stand (relation between the observed and expected dropout of 213%). From the gross yield in monospecific stands, 73% is allocated in the standing stock, whereas it is only 48% in the mixed stands. In mixed stands, we observed that 52% of the gross growth dropped out, whereas the expected dropout based on the weighted mean of the monocultures was only 27%. The lower part of Table 2 shows that the responses of Scots pine and European beech to mixing differed in gross yield but even more so in net yield. The gross yield

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Fig. 13 The ratio between the mean stem diameter of the dropout fraction and the remaining stand is displayed for pure (p) vs. mixed (m) stands for all stands, and separately for Scots pine, Norway spruce, and European beech (dratio). The horizontal line indicates equality of dropout and remaining stem diameter (p all = all pure stands pooled; m all = all mixed stands pooled; p pi = pure pine; m pi = mixed pine; p sp = pure spruce; m sp = mixed spruce; p be = pure beech; m be = mixed beech)

of Scots pine indicates an overyielding of 2% (relation between S.pi., (E.be.) and S. pi. mono, 102%) and the gross yield of European beech an overyielding of 18%. The picture changes when we look at the average response to mixing. The high dropout of Scots pine of 11.53 m3 ha-1 year-1 resulted in a very low net growth of 0.48 m3 ha-1 year-1, while the moderate dropout of only 4.19 m3 ha-1 year-1 of European beech only reduced the overyielding of gross growth of 18% to 10%. In essence, we found at the stand level an overyielding of gross growth, but due to the dropout of Scots pine (removal by alien-thinning), an underyielding of net growth.

5 Discussion 5.1

Mortality as a Result of Gross Growth and Maximum Density

As total production increases linearly to sigmoidally with progressing stand age but maximum standing stock increases only degressively, competition-based natural thinning is inevitable. With increasing stand age, increasingly less gross growth is accumulated as standing stock and higher proportions end up as deadwood for decomposition. For the four investigated species, the ranking in terms of dropout volume at 100 years was Norway spruce > Scots pine > European beech > sessile

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Fig. 14 Dropout of stem mass (t ha-1 year-1) depending on the mean diameter for mixed (green) vs. monospecific (red) stands displayed for (a) the stand level and (b–e) the species level for Scots pine, Norway spruce, and European beech

oak. If this ranking is weighted by the different wood densities of these species (Norway spruce 0.38 t m-3, Scots pine 0.43 t m-3, European beech 0.55 t m-3, sessile oak 0.56 t m-3), the differences in drop out mass are smaller but the order of species still remains. The proportion of dropout volume from gross growth is independent of site conditions, indicating that the relationship is actually linked to natural thinning. In other words, resource depletion, i.e. light availability, is driving the mortality independent of other site conditions (Harper 1977). Nevertheless, the variation across sites is large, which is likely related to mortality that is not caused by natural thinning but on the one hand by varying site conditions and on the other hand by the occurrence of various biotic and abiotic disturbances indicated in Sect. 2. For example, rising temperatures may contribute to increasing drought stress damages in most European regions, in particular the southern and eastern areas, but not in cool moutainous regions (Fronzek et al. 2019; SánchezSalguero et al. 2017). By focusing the analyses on the growth and mortality of medium-aged forests, susceptability might not be particularly strong because disturbances are more likely in very mature stands when resistance declines (Ryan et al. 1997). However, these disturbance effects are getting more important under climate change and resulting younger stands and higher turnover (McDowell et al. 2020). The most important stresses that need to be considered are risks due to drought and

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Fig. 15 Relative over- and underyielding of both gross and net stem volume growth (m3 ha-1 year-1) visualized for (a) the total stand and (b) the species level. The y-axis represents the ratio between the growth in mixed compared with monospecific stands. The ratio is shown for gross and net overyielding (more details and further elaborations are given in Pretzsch et al. (2023a)). (Abbreviations pi and be: Scots pine and European beech; g and n: gross and net overyielding, respectively) Table 2 Partitioning of the gross stand volume growth (m3 ha-1 year-1) into dropout and net growth (from left to right) and comparison of mono with mixed stand growth (from top to bottom), details about elaborating these values in Pretzsch et al. (2023a)

Group S.pi., E.be., exp. S.pi., E.be., obs. S.pi. mono S.pi., (E.be.) E.be. mono (S.pi.), E.be.

abs rel abs rel abs rel abs rel abs rel abs rel

Gross (m3 ha-1 year-1) abs SE 12.15 0.72 100 13.35 1.26 110 11.76 0.92 100 12.02 1.57 102 13.13 1.16 100 15.44 1.69 118

rel 100 100 100 100 100 100

Dropout (m3 ha-1 year-1) abs SE rel 3.26 0.60 27 100 6.96 1.17 52 213 3.42 0.94 29 100 11.53 3.45 96 337 2.89 0.91 22 100 4.19 1.03 27 145

Net (m3 ha-1 year-1) abs SE 8.89 0.98 100 6.40 1.68 72 8.34 1.24 100 0.48 3.64 6 10.23 1.64 100 11.25 2.26 110

rel 73 48 71 4 78 73

All fractions are given in m3 ha-1 year-1 (abs) as well as in percentage (rel) with values of gross growth and monospecific stands set to 100%

insect predation (Erbilgin et al. 2021; Yi et al. 2022), which are strongly speciesspecific and differ in their sensitivity to climate changes (Maringer et al. 2021). Since stands in this investigation were even-aged mixed-species plantations within one

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rotation, the tree number in early stages is low and the self-thinning line (or natural thinning) is often not reached. Thus, the dropout by self- or alien-thinning is also low and the role of disturbance-related mortality is dominant (Larson et al. 2015). In this respect, the impacts of extreme heat and drought events are particularly important, because a larger height generally increases the vulnerability to hydraulic failure (Bennett et al. 2015; Gora and Esquivel-Muelbert 2021; Olson et al. 2018). This general picture, however, may be contradicted at sites that provide deep water access only for the larger trees with an extended rooting system (Colangelo et al. 2017; Kahmen et al. 2022), or at sites where vulnerable species are preferably occurring in the understory (Stephenson and Das 2020). Knowledge of stand structure, site conditions and the species-specific behaviour is essential as extreme heat and drought events are expected to be more frequent in the future (Gazol and Camarero 2022; Ridder et al. 2022). That the effect of tree size affects both growth as well as mortality has been shown several times e.g. (Fien et al. 2019; Yang and Titus 2002). However, not only the effect of immediate intensive stresses is difficult to distinguish from natural thinning, but also the impact of size asymmetric competition on the one hand and speciesspecific influences on the other (Dekker et al. 2009; Luo and Chen 2011). Even-aged mixed-species stands are particularly suitable to investigate the effects of alienthinning, since competition is mostly related to species effects in such stands. This is, in particular, true when coupled with triplet investigations, where also speciesspecific effects in a mixture can be defined. These results might be further analyzed concerning climate effects on natural thinning that have been previously shown to be species-specific (Archambeau et al. 2020; Condés et al. 2017).

5.2

Consequences for Tree Mortality Modelling

Statistical tree and stand models frequently use the natural thinning line for predicting mortality but depend on a representative mortality database (Monserud et al. 2004). The relationship between mortality and growth, depicted here, together with the multiple environmental changes that affect growth differently at the site level, implies a major challenge for such models since both processes generally rely on separate statistical relations (Thrippleton et al. 2020). In particular, the differentiation between self-thinning and alien-thinning requires sophisticated approaches based on a wide array of experimental sites that render most of these approaches not appropriate (Bigler and Bugmann 2004). A step further to a general relationship is the application of logistic models that link growth as well as mortality to site conditions (Eid and Tuhus 2001) that could also consider species composition and relationships to environmental conditions such as site index or primary production potentials (Salas-Eljatib and Weiskittel 2020). Still, it is challenging that the observed relationships to the environment are changing. For example, water availability increases in importance for growth and mortality under a future hotter climate, while nutrient supply may get less important

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with continuing high anthropogenic deposition. Thus, competition effects should be based on resource limitation, which at the same time also affects growth responses. For this objective, process-based or better physiologically-oriented models have been developed (Tague et al. 2013) and are highlighted as the most promising (Davi and Cailleret 2017). These models are generally concentrating on carbon acquisition and have all major resource limitations included. Mortality can then be linked to a low net primary production or to a threshold of mobile internal carbon that defines carbon starvation (Bugmann et al. 2019). In such models, resource related mortality can in principle be combined with stress related mortality, i.e. drought stress (Davi and Cailleret 2017; Liu et al. 2021). However, the degree of complexity already applied to represent the responses of one species, makes it difficult to also consider the interaction between different tree sizes and species within a mixed forest. Regarding the importance of these impacts, it would be particularly promising to further develop mechanistic mortality approaches and implement them into physiological-oriented individual models (Holtmann et al. 2021; Jonard et al. 2020; Rötzer et al. 2005). The dependency between growth and dropout on site conditions and mixture type would then be inherently integrated.

5.3

Consequences for Forest Management

Our results indicate that a withdrawal of forest management in order to increase carbon sequestration would result in the loss of a third of total stand production in monospecific stands and even more in mixed stands. This loss would remain unexploited and end up as litter that would be subject to relatively fast turnover rather than being used for long-term carbon sequestration. This does not necessarily mean that the accelerated deadwood production by natural thinning is completely lost in decomposition but might increase humus content, nutrition status, and water storage capacity of the soil, which depends in turn on nutrient status and temperature development (Lal 2005). However, it supports the view that old-growth natural forests do not store as much carbon as previously assumed (Gundersen et al. 2021). These findings are supported by investigations that indicate a loss by natural thinning of 25–35% of the total stem volume also in unthinned monospecific stands (Assmann 1970), pp. 227–228, (Pretzsch 2009), pp. 59–61. To use a higher fraction of gross growth for carbon sequestration, adapted thinning guidelines and felling budgets would thus be required (Marland and Schlamadinger 1997; Nunes et al. 2020). It is also apparent that due to the relation between growth and mortality, environmental changes need to be considered. For example, atmospheric nitrogen deposition modifies stand dynamics similar to fertilization (Pretzsch and Biber 2021), increasing growth (passing faster through the N ~ dq trajectories) but also accelerating competition and thus mortality. In order to anticipate the accelerated self-thinning and drop-out of trees, thinning frequency and intensity may need considerable adjustment. Thinning guidelines thus need to be based on achieved

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stand height or diameter instead of stand age. Whereas the allometric and dendrometric relationships between, e. g., mean tree height and tree number or mean tree diameter and stand volume are still valid, the relationship between age and dendrometric stand characteristics certainly changes towards an accelerated stand development. Appropriate silvicultural prescriptions require knowledge of the maximum stand density in mixed stands and the density growth relationship. Management also needs to consider that the relationship between growth and mortality is species-specific and thus could result in a demixing if one species loses more than another. For example, silvicultural interventions may be needed in favour of Scots pine mixed with European beech to maintain the facilitation effect of Scots pine (Pretzsch 2022a). For example, the establishment and maintenance of a group mixture or planting Scots pine ahead of European beech for about 10 to 20 years would reduce the inter-specific competition. However, both measures would reduce the mixing intensity and probably also the beneficial interactions and overyielding. Such interventions also need to consider that the density of mixed stands can be 5–10% higher than in monospecific stands (Pretzsch and Biber 2016; Pretzsch and del Río 2020). Any management recommendations should be species- and sitespecific, as mixed forests can be less exposed to disturbance (namely drought) in some regions but not in others due to minor complementarity (or no facilitation) between co-occurring species (Conte et al. 2018; Grossiord et al. 2014; Versace et al. 2020).

6 Conclusions For understanding and managing forest stands, it is essential to consider growth but also mortality at both the stand and species levels. Our study showed higher gross growth, mortality and turnover for mixed stands than for monospecific stands. This underpins that the common studies that concentrate on the gross growth of mixed stands, only provide half of the story and need to be complemented by analyses of mortality. A better insight into the relationship between gross growth and mortality at the stand- and species level is needed to determine where the carbon surplus gained by overyielding actually ends up. It is also necessary to support exploiting the growth and yield of forest stands according to the required services, i.e. to maintain or increase species diversity. Unfortunately, any wood harvest is accounted for as immediate emission in the forest sector by most international agreements. The presented results might shed new light on the discussion about withdrawing from active management of forests to increase carbon sequestration, highlighting the finding that in such cases about a third of the total stand production in monospecific stands and even more of mixed stands would end up in deadwood. In this form, the assimilated carbon might be returned quickly back to the atmosphere rather than being long-term sequestered.

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Acknowledgement The publication is part of the OptFORESTS project entitled “Harnessing forest genetic resources for increasing options in the face of environmental and societal challenges” that has received funding from the European Union’s HORIZON-CL6-2022-BIODIV-01 research programme under the grant agreement GA 101081774. The first author also wishes to thank the German Science Foundation (Deutsche Forschungsgemeinschaft) for funding the project “From near-death back to life: Mixed stands of spruce and beech under drought stress and stress recovery. From pattern to process (# DFG PR 292/22-1). We are grateful to the Bayerische Staatsforsten (BaySF) for supporting the establishment and maintenance of the underlying long-term experiments and to the Bavarian State Ministry for Nutrition, Agriculture and Forestry for permanent support of the project W07, entitled,” Long-term experimental plots for forest growth and yield research (# 7831-22209-2013). We further thank all national funding institutions for establishing, measuring and analyzing data from the long-term experiments and triplets across Europe. We also wish to thank Monika Bradatsch for the graphical artwork.

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Pollen: A Key Tool for Understanding Climate, Vegetation, and Human Evolution M. F. Sanchez Goñi

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 From Pollen Preserved in Terrestrial and Marine Sediments to the Vegetation Source . . . 3 Deep-Sea Pollen Records for Understanding Earth’s Climate Evolution . . . . . . . . . . . . . . . . . . 3.1 European Vegetation Response to Long-Term and Rapid, Millennial-Scale, Climate Changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 The Entering in Glaciation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Pollen, Deglaciation, and Atmospheric CO2 Concentrations . . . . . . . . . . . . . . . . . . . . . . . . 4 Pollen for Tracking Past Tree Refugia, Migration Routes, and Speed of Colonisation . . . 4.1 Fagus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Picea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Pollen and Human Evolution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 The Origin of the Genus Homo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 The Emergence of Modern Humans (H. sapiens) in Africa . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 Cultural Evolution of H. sapiens in Europe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Conclusions and Perspectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract The analysis of ancient pollen (and spores) preserved in sedimentary sequences is a classical approach used in paleoclimatology, paleoecology and archaeology since the beginning of the twentieth century. Yet, pollen analysis is the most powerful tool to reconstruct past vegetation changes affording more precise documentation of distribution, composition and land vegetation cover than geochemical tracers only providing the wet/dry-loving plants ratio through time. Communicated by Maria Carmen Risueño Supplementary Information The online version contains supplementary material available at [https://doi.org/10.1007/124_2022_63]. M. F. Sanchez Goñi (*) Ecole Pratique des Hautes Etudes, Paris Sciences Lettres (EPHE, PSL), Paris, France UMR EPOC, Université de Bordeaux, CNRS, Pessac, France e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 Progress in Botany (2024) 84: 395–434, https://doi.org/10.1007/124_2022_63, Published online: 9 July 2022

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Ancient pollen from deep-sea cores has allowed the direct comparison of vegetation and atmospheric conditions on land with changes in ocean and ice sheet dynamics, identifying, for instance, a strong air-sea thermal contrast at orbital and millennial time scales in the European margin favouring moisture production and transport to northern hemisphere high latitudes and the last entering in glaciation. The study of ancient pollen along with plant macro remains and modern and ancient DNA has revealed the location of cryptic refugia for temperate and boreal trees during cold periods and reduced the original velocity estimations for tree migration highlighting the difficulty for certain trees to keep pace with the on-going climate change. Pollenbased vegetation changes are of most relevance to understand human evolution as past populations were tightly dependent on plant and animal resources. Repeated and strong savannah expansion in eastern Africa contemporaneous with the onset of large northern hemisphere glaciations provided enough animal resources that allowed hominin brain increase and the emergence of early Homo. In Europe, the successive and rapid steppe-dominated cold periods punctuating the last glacial period triggered repeated increases of ungulate biomass and human demography that may explain the increase and accumulation of innovations in Homo sapiens populations. Keywords Deglaciation, Glacial-interglacial climate changes, Glaciation, Origin and evolution of Homo sapiens, Past atmospheric CO2 concentration, Rapid climate changes, Refugium zones for trees

1 Introduction Pollen is defined as the structure produced by plants containing the male haploid gametes to be used in reproduction. The outer wall of all pollen grains called exine is composed of sporopollenin that protects the gametes against a wide range of environmental assaults until the pollen grain is capable of fertilising the female stigma (Erdtman 1969). Sporopollenin, also protecting land-plant spores, is a ubiquitous and extremely chemically inert biopolymer that is considered a prerequisite for the migration of early plants onto land (Li et al. 2019). Sporopollenin also warrants the good preservation of ancient pollen grains in oxygen-poor marine, lacustrine and peat bog sedimentary sequences. The scientific branch devoted to the study of pollen is called Palynology, a term derived from the Greek word “palynos” (flour/dust), that refers to the appearance of the pollen grains when they are dispersed in the atmosphere. A substantial quantity of pollen grains produced, released and dispersed from terrestrial higher plants (as well as spores of lower plants) reaches lakes, peat bogs and the ocean by fluvial and atmospheric transport processes, incorporates in the sediments and accumulates through time (Tauber 1967; Bonny 1978; Koreneva 1966; Stanley 1966). The pollen assemblages found in the successive sediment layers allow the reconstruction of the evolution of past vegetation and climate.

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Thus, not only alive pollen is crucial for maintaining life in our planet. Ancient pollen, and particularly that preserved in Quaternary sediments, representing the Earth’s history of the last 2.58 million years, is a key tool for: (a) understanding modern ecology and biogeography (e.g. (Seppä and Bennett 2003; Magri et al. 2007, 2017; Birks 2019; Tinner and Kaltenrieder 2005; Tinner and Lotter 2001)), (b) identifying the mechanisms underlying climate changes (e.g. (Margari et al. 2010; Sanchez Goñi et al. 2008, 2013), and (c) discussing the potential impact of environmental changes on human evolution (Bonnefille 2010; Sanchez Goñi 2020). The seminal work of Von Post (von Post 1916) used pollen as mainly a geological tool for identifying herbaceous or forest-dominated periods, inferring climate conditions and sea-level changes, and dating the sediments. Following the courses he organised in 1933 two botanists – Knut Fægri from Norway and Johannes Iversen from Denmark wrote a small monograph about pollen analysis presenting their new vision of pollen analysis as an ecological tool for studying long-term vegetation dynamics, i.e. spreading, extinction, persistence, adaptation and, particularly, for identifying the location of tree refugia during the periods of ice growth and permafrost expansion. But also they introduced new ecological concepts such as potential niches and no-analogue vegetation communities, and the response of vegetation to human impact ((Birks 2019) for a relevant synthesis). Another turning point of pollen analysis was initiated by a series of seminal works on Marine Palynology published in the 1960s in a special issue of Marine Geology (e.g. (Groot and Groot 1966; Traverse and Ginsburg 1966; Zagwijn and Veenstra 1966)), followed by those of Heusser, Hooghiemstra, Rossignol-Strick, Van Campo, and Turon in the 1970 and 1980s in the North Pacific and the Atlantic Oceans and the Mediterranean and Arabian Seas (e.g. (Heusser and Balsam 1977; Hooghiemstra et al. 1988; Rossignol-Strick 1983; Turon 1984; Van Campo 1982)). These palynologists worked on deep-sea sedimentary sequences to directly compare, without chronological ambiguities, pollen assemblages with marine proxies of oceanographic conditions and ice-volume changes to identify the timing and nature of the different Earth’s reservoir response (atmosphere, ocean, ice, vegetation and terrestrial surfaces) to long-term, glacial-interglacial, climate changes during the Quaternary (Sanchez Goñi et al. 2018). In the most recent decades the deep-sea pollen approach has been instrumental for documenting the possible impact of rapid, millennial to centennial, climate changes, originally detected in the North Atlantic Ocean and Greenland, on terrestrial environments and human evolution. Deep-sea sequences provide marine stratigraphical constraints to the pollen record that they preserve, improving the chronology of the inferred rapid vegetation changes. Thus, the well-chronologically constrained vegetation changes can be also accurately compared with the archaeological record (e.g. (d'Errico and Sánchez Goñi 2003)). This article aims to highlight the interest of studying ancient pollen for the advancement of climate, vegetation and human sciences. It focuses mainly on the European continent and the last 1 million years (Myrs), this spatiotemporal boundary is justified by my own research experience and the fact that it is also the time span for which a large number of pollen records are available. Moreover, this region is one of

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the world’s most documented in terms of Quaternary climate and vegetation changes. It is particularly affected by the strong advances and retreats of the northern hemisphere ice-sheets of the last 1 Myrs and very much influenced by the North Atlantic and Greenland rapid, millennial to centennial, climatic variability of the last glacial period (115,000–15,000 years before present, 115–15 ka). After introducing the main principles of the pollen analysis in sedimentary sequences (Sect. 2), Sect. 3 presents the contribution of marine palynology to document past vegetation and atmospheric climate changes and understand the processes behind these changes such as the entering in glaciation and the contribution of the terrestrial biosphere in atmospheric CO2 concentrations. Section 4 focuses on the relevance of pollen studies in terrestrial sequences for identifying glacial refuge zones for temperate trees, and their migration routes and speeds following a warming. The velocity of which trees are able to move in response to past climate changes is crucial to anticipate their future distribution face to the present-day global warming. Finally, Sect. 5 tackles the potential impact of climate changes on the biological and cultural human evolution.

2 From Pollen Preserved in Terrestrial and Marine Sediments to the Vegetation Source On land, the pollen rain, i.e. the pollen that falls in a particular site, is deposited and preserved in lake and peat bog sedimentary sequences. The pollen assemblages found in these sediments represent, depending on the size of these deposits and the relative influence of riverine input, local or regional plant communities. In close big lakes surrounded by forest, with a diameter larger than 250 m and without river entrance, most of the pollen comes from the regional vegetation mainly transported by relatively high speed winds above the canopy (Jacobson and Bradshaw 1981; Tauber 1965). In contrast, smaller lakes preserve pollen grains from the forest communities surrounding them and arriving through the trunk space. In both small and large lakes a weak proportion of extra-regional pollen is deposited through rainfall (rainout) (Tauber 1967). When river input exists (open lakes), a high proportion of all pollen supplied to the lake is stream borne (Bonny 1978) and, therefore, it represents the vegetation of the related hydrographic basin. In the ocean, the relative contribution of fluvial or atmospheric transport vector is regionally-dependent (Dupont 2011). Marine sediments located further than 300 km offshore are weakly influenced by rivers and the dominant pollen transport is aeolian (e.g. (Hooghiemstra et al. 1988)) while those located under the influence of the river plumes (nepheloid layers) is mainly of fluvial origin (e.g. (Heusser and Balsam 1977)). Once it arrives in the ocean surface waters, pollen is ingested by planktonic organisms and later integrated into their faecal pellets or agglomerated with clays (Mudie and McCarthy 2006). Due to these processes, pollen buoyancy decreases and is little influenced by ocean currents. It thus becomes an integral part of the marine

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snow and crosses the water column with a relatively high speed (estimated at ~100 m/day in the Atlantic water column) before being deposited at the bottom of the oceans (Hooghiemstra et al. 1992). Furthermore, sediments under the influence of upwelling are particularly rich in pollen for two reasons: the intensification of the downward particle transport through the water column (Ratmeyer et al. 1999) and the better preservation in almost anoxic sediments (Dupont 2011). Pollen studies on modern deep ocean surface sediments from many regions showed that pollen assemblages from top ocean floor sediments reflect an integrated image of the regional vegetation of the adjacent continent and, consequently, the climatic parameters under which this vegetation has developed (Sanchez Goñi et al. 2018). In particular, Naughton et al. (2007) and, more recently, the statistical study of Morales-Molino et al. (2020) demonstrate that the modern pollen assemblage from the deep ocean of the southwestern Iberian margin is similar, albeit a higher amount of Pinus pollen due to its good dispersion already observed in other world’s region (Heusser and Balsam 1977; Hooghiemstra et al. 1988), to those of the Tajo estuary that accurately represent the regional vegetation of the related hydrographic basin (Fig. 3). Thus, while small lakes and peat bogs preserved a local pollen signal, big lake and deep-sea sediments contain pollen assemblages providing an integrated image of the vegetation at regional, sub-continental scale. Reconstructing past vegetation and climate from the analysis of ancient pollen is based on five main principles (Birks and Birks 1980; Faegri and Iversen 1964): (a) the specificity of the pollen grain morphology (single or multiple grains, circular; elliptical, elongate. . . shapes; circular and/or elongate apertures; granulate, verrucate, clavulate, echinulate ornamentation. . .) (Fig. 1), (b) the strong pollen resistance to degradation, (c) the pollen rain faithfully represents the amount and floristic composition of the vegetation source, (d) the extraction, identification under optical microscope and counting of pollen faithfully reconstruct the pollen rain, (e) the ecology of each pollen taxon or group of taxa has not changed through time (the uniformitarianism principle). Unfortunately, these principles are not completely fulfilling and while the identification up to the genus level is possible for trees and shrubs, many of the herbs are only determined up to the family level. There is also a differential preservation of pollen with some of them very resistant (e.g. Taraxacumtype), and a differential pollen production, release and transport with windpollinated plants dispersing high amounts of pollen (e.g. Pinus) compared to animal-pollinated plants (e.g. Tilia). Finally, not all ancient pollen assemblages have modern analogues (Anderson et al. 1989; Huntley 1990; Overpeck et al. 1985). Despite these pit-falls, worldwide studies on the modern pollen representation of the present-day plant communities, i.e. warm and temperate forests, boreal forest, tropical forest, open forests, grasslands, steppe and tundra, show that the pollen assemblages represent relatively well the amount and floristic composition of these different types of vegetation (e.g. (Bradshaw and Webb III 1985; Lutgerink et al. 1989; Prentice 1978, Prentice 1992)). More recently, studies based on the comparison between modern pollen records and forest composition data in conjunction with modelling show that pollen can act as a robust proxy for vegetation turnover, thereby supporting the use of pollen-based estimates of turnover to predict temporal changes

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Fig. 1 Pollen morphotypes of different trees and herbs under light-transmitted optical microscope at 1,000 magnification. Black line indicates 10 μm. Courtesy of S. Desprat. (a) Pinus (pine), (b) Betula (birch), (c) deciduous Quercus-type (deciduous oak), (d) Carpinus betulus-type (hornbeam), (e) Fagus (beech), (f) Alnus (alder), (g) Corylus (hazel), (h) Ericaceae (heather), (i) Taraxacum-type (Cichoriaceae), (j) Cyperaceae (sedges), (k) Poaceae (grasses), (l) Plantago (plantains), (m) Artemisia (sagebrush), (n) Amaranthaceae (amaranths), (o) Ephedra distachya-type (sea-grape)

in vegetation (Nieto-Lugilde et al. 2015). Furthermore, regional vegetation is directly linked to climate conditions as the present-day distribution of the major biomes is tightly related with climatic parameters (Bailey 1998). For southwestern Europe, Gouveia et al. (2008) have recently shown the rapidity with which vegetation in this region responds to North Atlantic atmospheric processes, i.e. the westerlies. Moreover, the abundance of pollen grains (usually between 1,000 and 50,000 grains cm
3 in the ocean and 10–100 times higher in terrestrial sequences) and their taxonomical diversity are in general high enough to allow the quantitative estimation of annual and, more importantly, seasonal temperatures and precipitations (e.g. (Combourieu Nebout et al. 2009; Desprat et al. 2007; Sánchez Goñi et al. 2021)). The knowledge about past climate seasonality is crucial to understand

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natural climate variability (Carre and Cheddadi 2017) and the sensitivity of vegetation to changes in this parameter makes pollen data particularly well-suited to track shifts in seasonality through time. Quantitative pollen-based climatic estimates are based on different techniques. One of the most frequently used is the Modern Analogue Technique (MAT) based on a comparison of past assemblages to modern pollen assemblages through the calculation of the shortest weighted distance (Guiot 1990). The modern database includes different continental pollen spectra (moss polsters, soil surface samples and lacustrine sediments) from Eurasia and northern Africa (Davis et al. 2020). Since potential errors would be similar for adjacent samples of the same record, we consider that this approach is still valid for the quantification of climate change anomalies.

3 Deep-Sea Pollen Records for Understanding Earth’s Climate Evolution Climate is defined as the mean state of the atmosphere, i.e. temperature, precipitation and Greenhouse Gas Concentrations, over 30 years that depends in turn on the dynamics of the other Earth’s reservoirs, the hydrosphere, the cryosphere, the biosphere and the terrestrial surfaces (Claussen 2007). Climate is regionally specific as the result of the insolation, or incident solar radiation, defined as the amount of solar energy that the Earth receives from the sun by season and latitude (Milankovitch 1941; Ruddiman 2001). Insolation is controlled by the distance between the Earth and the Sun that depends on eccentricity (the shape of the Earth’s orbit), obliquity (the tilt of the Earth’s axis) and precession (the orientation of the Earth’s axis); the latter determines the amplitude of the seasons (Fig. 2a, b). These orbital parameters vary over time and trigger Quaternary glacial-interglacial cycles (Shackleton and Opdyke 1973), revealed by geochemical measurements from deepsea cores and geomorphological data revealing advances and retreats of the northern hemisphere ice-sheets. These glacial-interglacial cycles occurred with quasiperiodicities lying between tens and hundreds of thousands of years (Berger and Loutre 2004) (Fig. 2c). A change in insolation affects the Earth’s five main climatic reservoirs and each of them affects, in turn, the Earth’s other reservoirs through feedback mechanisms that amplify or reduce the original climate change, its frequency and duration (Ruddiman 2001). Thus, climate is a non-linear and complex system and vegetation as a part of the terrestrial biosphere plays an important role in two main feedback mechanisms: vegetation-albedo and vegetation-greenhouse gas (water vapour and CO2) exchanges (Ruddiman 2001). An example of the first mechanism is the southward expansion of the tundra triggered by the decrease in boreal summer insolation, the consequent albedo increase (the snow over the tundra double the albedo compared to the snow over the taiga), and the additional cooling leading to glaciation (positive feedback). The second positive feedback is the consequence of the increase in insolation and low latitude precipitation that initially lead to forest expansion, increasing evapotranspiration, and therefore precipitation.

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Fig. 2 Orbital and long-term climatic and vegetation changes over the last 1 Myrs: (a) Insolation variations in July at 65 N (Berger and Loutre 1991), (b) Precession index (red) and obliquity (blue) (Berger and Loutre 1991), (c) δ18O benthic foraminiferal LR04 stack record (Lisiecki and Raymo 2005), (d) CO2 concentrations (Luthi et al. 2008), (e) Temperate forest pollen record from Lake Ohrid (Albania) (Wagner et al. 2019), (f) Mediterranean forest pollen record from the SW Iberian margin (composite record from sites U1385, MD01-2443, and MD95-2042) (Oliveira et al. 2016; Roucoux et al. 2006; Sánchez Goñi et al. 2019; Sanchez Goñi et al. 2008, 2016). MIS: Marine Isotope Stage. Grey intervals 1–23 indicate the interglacials of the last 1 Myrs. MBE: Mid-Brunhes Event

Superimposed to this long-term climatic variability, millennial-scale changes are registered in the North Atlantic sea surface temperature records (Voelker et al. 2002; Martrat et al. 2007) as well as in the air temperature archives of Greenland (Barker

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et al. 2011; North Greenland Ice-Core Project (NorthGRIP) 2004) and Antarctica (EPICA 2004). These changes occur independently of the boundary climate state, i.e. in the glacial and interglacial periods, and are generally associated with changes in ice volume (Siddall et al. 2003), Greenhouse Gas concentrations (Knutti et al. 2004; Loulergue et al. 2008; Spahni et al. 2005), and in the intensity of the Atlantic surface waters transporting warmth towards the northern latitudes from the Gulf of Mexico (Oppo et al. 2006; Lynch-Stieglitz 2017). Yet, pollen-derived reconstruction of past vegetation and climate from deep-sea sedimentary sequences offer the luxury of combining marine, ice and terrestrial (atmosphere) climatic indicators, without chronological uncertainties, and thus documenting the response of the different Earth’s reservoirs to a given climate change. Then, we will be able to identify potential leads and lags in the response of the different Earth’s reservoirs and discuss the feedback mechanisms that modulate the environmental response compared to the original forcing. The following sub-sections illustrate three examples of the contribution of pollen analysis of deep-sea sedimentary sequences to document the European vegetation response to long-term (orbital) and millennial-scale climatic variability detected in the atmosphere of Greenland and the North Atlantic Ocean and, on the other hand, the processes entering in glaciation and deglaciation.

3.1

European Vegetation Response to Long-Term and Rapid, Millennial-Scale, Climate Changes

The last 0.8 Myrs were characterised by 10 glacial-interglacial cycles, represented by 20 Marine Isotope Stages (MIS) from MIS 20 to MIS 1 (including the present interglacial) (Lisiecki and Raymo 2005). Odd and even numbers broadly correspond to interglacial and glacial periods, respectively. MIS 19 to MIS 5, ~781–126 ka, represent the Middle Pleistocene while the Upper Pleistocene encompasses the interval 126–11.7 ka, i.e. MIS 5 to the onset of MIS 1 (Cohen et al. 2013) (Fig. 2c). Within interglacials, an alternation of three or five warm and cold sub-stages can be identified, related with ice-volume minima during sub-stages “a”, “c” and “e”, and maxima, sub-stages “d” and b” (Railsback et al. 2015). Excluding MISs 17, 13 and 7, all the interglacials experienced their warmest conditions at the beginning, just after the deglaciation concomitant with the highest sea level (Railsback et al. 2015). Eastern North Atlantic deep-sea and European pollen records show that within interglacial periods a succession of maximum forest expansions alternated with forest contractions (Fig. 2e, f). Following a south north latitudinal transect, Mediterranean, temperate, and boreal forests were developed (Figs. 3 and 4a, b). However, the magnitude of the forest expansions differs depending on the interglacial and the region. For instance, the forest expansion during MIS 17, ~700 ka, is the strongest of the last 800, 000 years in the western Mediterranean region (Fig. 2e) (Sánchez Goñi et al. 2019) and much stronger than

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Fig. 3 Pollen records representing vegetation changes in middle and southern Europe and the near East (32–48 N) during the last climatic cycle. (a) Greenland ice core δ18O record (Rasmussen et al. 2014). Dansgaard-Oeschger (D-O) warming events (red). (b) Ice-rafting debris (IRD) events (black) of the last climatic cycle from the Bay of Biscay (western France) (Sanchez Goñi et al. 2008), (c) Atlantic temperate (green) and boreal (dark blue) forests pollen percentages from La Grande Pile (W Europe) (de Beaulieu and Reille 1992), (d) Atlantic temperate forest pollen from W France

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that recorded in north-eastern regions (Lake Ohrid) (Fig. 2f) (Wagner et al. 2019). The opposite is registered for the MIS 11 interglacial, ~420 ka. During glacials the dominance of herbaceous vegetation was marked by the expansion of Mediterranean (dominated by Artemisia, Ephedra, and Amaranthaceae) and Centro-European (dominated by Poaceae, Cyperaceae and Artemisia) steppes and shrub-tundra in more northern regions (Helmens 2014; Sánchez Goñi et al. 1999; Tzedakis et al. 1997). So far, the best studied millennial-scale climate variability is that observed during the last glacial period (MIS 5d to MIS 2, i.e. ~115–14.7 ka) characterised by a series of warming and cooling events called Dansgaard-Oeschger (D-O) cycles that were first identified in the atmosphere of Greenland and usually lasted 500–2,000 years (Dansgaard et al. 1984) (Fig. 3a). These cycles recorded in the δ18O of the ice cores were characterised by large, 7–16 C, and rapid, within few decades, warming events followed by a progressive decrease in temperature preceding a final abrupt cooling (Wolff et al. 2010). The warming and progressive cooling phase is termed Greenland Interstadial (GI), and the final cooling lead to the cold phase termed Greenland Stadial (GS). The GI phases lasted between 100 and 2,600 years (Wolff et al. 2010). Also during the last glacial period, repeated iceberg discharges cooled the surface of the North Atlantic (Bond et al. 1993; Heinrich 1988). On the one hand, massive iceberg discharges from the Laurentide ice sheet, the so-called Heinrich events (HE), occurred with a cyclicity of 7,000–10,000 years while, on the other hand, weaker discharges coincided with iceberg fragmentation from the British-Icelandic-Scandinavian (BIS) ice cap (Elliot et al. 2001) (Fig. 3b). We define a HE as the time period synchronous with the deposition of the Heinrich layer in a given region following the iceberg discharge while the Heinrich Stadial (HS) the North Atlantic cold interval associated with the HE that lasted up to 3,000 years (Sanchez Goñi and Harrison 2010). Some GSs encompass the HSs while the others are associated with the BIS minor iceberg discharges. These cold intervals are related to decreases in the intensity of the North Atlantic warm and salty surface waters (Lynch-Stieglitz 2017; McManus et al. 2004). Until the end of the 1990s European pollen records (Fig. 1) showed no substantial changes in the steppe-dominant vegetation through the last glacial period (e.g. (Reille and de Beaulieu 1990; Follieri et al. 1988; Pons and Reille 1988)). In

 ⁄ Fig. 3 (continued) margin directly compared with the Sea Surface Temperature (SST) record during summer (July, August, September, JAS) in the Bay of Biscay ((Sanchez Goñi et al. 2008) and unpublished data), (e) Atlantic temperate forest pollen record from the NW Iberian margin (Sanchez Goñi et al. 2008) and obliquity (green) (Berger and Loutre 1991), (f) Central-eastern mixed forest pollen record from Lake Ohrid (Albania) (Sadori et al. 2016), (g) Mediterranean forest pollen record from the SW Iberian margin (Sanchez Goñi et al. 2008) and precession index (red) (Berger and Loutre 1991), Wet W: wet winter, Dry S: dry summer, (h) Eastern Mediterranean woodland pollen record from off Israel (32 N, 35 E) (Langgut et al. 2011). Light blue intervals indicate the HS 1 to 6, i.e. the periods of massive iceberg discharges from the North American ice-sheets (Bond and Lotti 1995; McManus et al. 1994)

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Fig. 4 Maps with the distribution of the present-day and reconstructed past vegetation communities. Red dots refer to the location of the pollen records used for the conceptual reconstruction of past vegetation occupying Europe during different climatic periods of the last climatic cycle (the last 130,000 years). This reconstruction is based on 32 pollen records unevenly distributed over Europe and mainly coming from middle and southern regions. Names and references of the sites can be found in Table 1 of the Supplementary Material. Vegetation distribution during: (a) present-day potential vegetation (https://www.britannica.com/place/Europe/Plant-life), (b) the warm periods of the MIS 5 interglacial sensu lato (~130–73 ka): Eemian, St Germain Ia, St Germain Ic, and St Germain II. Hatched Scandinavian and Icelandic ice caps indicate that these regions were ice free during the Eemian but not during MIS 5c and MIS 5a, (c) the Greenland Interstadials (GI) of MIS 3 (ice-sheet configuration at 45 ka), and (d) the Greenland Stadials (GS), including the HSs, of MIS 3 (ice-sheet configuration at 40 ka). Black dots refer to speleothem records that support the climatic interpretation of the pollen records. Ice-sheet configurations for the different periods are reconstructed from model and data (Batchelor et al. 2019)

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1999 Allen et al. (1999) published the first pollen record from southern Italy showing millennial-scale changes between forest expansion and contraction that roughly corresponded to the rapid climate variability detected in Greenland and the North Atlantic Ocean. However, the chronological uncertainties between ice, terrestrial, and marine sequences precluded to demonstrate whether forest expansions corresponded to North Atlantic and Greenland warming or, inversely, to cooling events. Deep-sea pollen records from the western European margin and the Mediterranean Sea located below 45 N (Fig. 4a) directly compared with ice and ocean climatic indicators have unequivocally shown that sub-orbital North Atlantic and Greenland cooling events corresponded in western Europe and the Mediterranean borderlands with herbaceous community expansion, and warming events with forest development (Combourieu-Nebout et al. 2002; Langgut et al. 2011; Roucoux et al. 2001; Sánchez Goñi et al. 2000, 2002, 2008, Sánchez Goñi et al. 2021) (Figs. 3 and 4c, d). They also demonstrate that vegetation responded rapidly, within 100 years to the D-O cycles and HEs and that there was a dynamical equilibrium between vegetation response and climate change for short periods of forcing. Interestingly, the increase of both the Atlantic and Mediterranean forest covers starts when summer SST reaches 12 C. This temperature seems to be, as today, the threshold value for forest expansion. At present, we observe that the full development of deciduous forest in both sides of the North Atlantic is related to summer SST between 12 and 18 C (Van Campo 1984). Furthermore, below 40 N the maximum expansion of Western Mediterranean forest occurred during GI 17-16 and GI 8 synchronous with low precession values that promote marked seasonality, enhanced hot-dry summers and wet-cool winters (Fig. 3g) (Sanchez Goñi et al. 2008). Thus, there was an optimal development of woodlands associated with a strong richness in sclerophyllous plants such as evergreen Quercus, Olea, Cistus, Phillyrea, Coriaria myrtifolia, and Pistacia (Fletcher and Sanchez Goñi 2008). GIs occurring during precession maxima were marked in turn by the abundance of the less drought-tolerant Ericaceae (heaths) typical of a weak seasonal climate (Fletcher and Sanchez Goñi 2008). Moreover, Mediterranean pines (Pinus pinaster, P. pinea, P. halepensis) characterised the warm phases although highland pine species (P. nigra and P. sylvestris) and particularly P. nigra were dominant throughout the last glacial period (Desprat et al. 2015). The Atlantic sites, above 40 N, showed a contrasting pattern: at D-O 12 and D-O 14 the Atlantic forest, mainly Betula, deciduous Quercus and Pinus, experienced a strong development coincident with a maximum in obliquity that particularly warm up high latitudes (Sanchez Goñi et al. 2008) (Fig. 3d, e). In the southeasternmost part of the Mediterranean at 32 N the last glacial period was dominated by semi-desert and desert vegetation, mainly Artemisia, with some slightly more humid fluctuations identified based mainly on the increase of evergreen Quercus between 56.3 and 43.5 ka (Langgut et al. 2011) (Fig. 3h). Despite the chronological uncertainties associated with terrestrial pollen sequences, north-central European pollen records, specifically Sokli in Northern Finland show that shrub-tundra developed during the warming GIs, while steppe expanded in the NE Europe. The expansion of open birch-pine woodlands marked

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the central-eastern regions between 50 and 55 N (Helmens 2014). Further south, between 45 and 48 N, Betula, deciduous Quercus and conifers (Pinus, Abies, Picea) expanded slightly in the landscape during warming episodes, mainly during GI 12 and GI 14 (Fletcher et al. 2010) (e.g. Figure 3c). In Southern Germany, pollen evidence shows the expansion at low altitudes of Betula, deciduous Quercus, Cupressaceae, and Pinus during GIs (Duprat-Oualid et al. 2017) and the recent pollen analysis of the Nesseltalgraben Alpine site (Stojakowits et al. 2020) shows the development of Pinus sylvestris-type, with admixtures of Picea, Betula, Alnus, and Salix. In the southeastern part of the Alps a persistence of mixed forests dominated by conifers but with significant Tilia and other broad-leaved species is detected. These coniferous-deciduous woodlands in the lowlands of NE Italy contrast with a boreal and continental landscape in the northern alpine foreland (Pini et al. 2010). Further east and south, ~40–41 N, deciduous Quercus woodlands with Carpinus and Abies developed in Albania, Greece, and Italy (Allen et al. 1999; Sadori et al. 2016; Tzedakis et al. 2002). This compilation shows that there was a spatial variability in the amplitude and floristic composition of the forest expansions for any given D-O warming of the last glacial period (Fig. 3). During cooling events regional differences are also observed in terms of floristic composition and amplitude of the cooling. Regarding the floristic composition, GSs in the SW Mediterranean region were characterised by semi-desert plants (mainly Artemisia, Amaranthaceae, and Ephedra) and the dominance of P. nigra (Desprat et al. 2015) while simultaneously, Ericaceae and Poaceae dominated the vegetation of NW Iberia (Sanchez Goñi et al. 2008). Western France and eastern regions were occupied by a central-European steppe-like vegetation, dominated by Artemisia, Cyperaceae, Calluna, and Poaceae (Sanchez Goñi et al. 2008) (Fig. 4d)). Regarding the magnitude of the cooling, the NW Mediterranean borderlands (SE France and NE Iberia) experienced colder and drier conditions during HS 5 compared to HS 4 leading to a higher expansion of steppe vegetation, dominated by Artemisia (Sánchez Goñi et al. 2021). By contrast during HS 4, the massive freshwater input in the North Atlantic may have led to the stratification of the Mediterranean water column and consequently limited upward mixing of cold water, resulting in regional atmospheric warming and wetting compared to HS 5 that allowed the maintenance of some temperate deciduous Quercus woodland stands (Sánchez Goñi et al. 2021). Similarly, in NE Greece at 41 N, HS 5 appears to be particularly cold and dry characterised by high amounts of Amaranthaceae and Artemisia (Müller et al. 2011). In contrast, further south and west an area of relative ecological stability has been identified in SW Greece at 39.8 N, where temperate tree populations survived throughout the last glacial period. Continued moisture availability and varied topography accounted for the existence of these wooded ecosystems (Tzedakis et al. 2002). These pollen sequences suggest that the boundary that separates the present-day temperate and Mediterranean domains (40 –45 N depending on the region) has been a pervasive feature throughout the last climatic cycle. The combination of the aforementioned evidence, in agreement with recent projections (Krapp et al. 2019), also highlights the strong instability of most of the European ecosystems at

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orbital and millennial time scales marked by an alternation of afforestation and herbaceous vegetation development concomitant with substantial ice-sheet contraction and expansion, respectively. Interestingly, these pollen records show successive formation and disappearance of non-analogue vegetation communities throughout the last glacial period.

3.2

The Entering in Glaciation

Changes in insolation roughly explain the timing of deglaciation and glacial inception (Hays et al. 1976; Milankovitch 1941; Shackleton and Opdyke 1973). However, internal feedback processes are needed to explain the ice age cycles, and previous research has mostly focused on those loops related to atmospheric and oceanic circulation (e.g. (Bar-Or et al. 2008; Risebrobakken et al. 2007), GHG concentrations (e.g. (Ganopolski et al. 2016)), and vegetation-albedo feedback (Crucifix and Loutre 2002; Desprat et al. 2005; Sánchez Goñi et al. 2005). So far little attention has been paid to the interactions between shorter (millennial-scale) and longer (10,000 to 100,000 years) term climate variability that may amplify the original orbital forcing (Hodell 2016). Here, we focus on the specific mechanisms linking changes in Earth’s orbit to ice ages taking as a test bed the onset of the last glaciation (i.e., MIS 5a/4 transition: ~80–70 ka), when one of the largest ice accumulations of the last 250,000 years occurred. In 1979, Ruddiman and McIntyre (1979) showed unequivocally that the ice growth in the northern hemisphere was contemporaneous with persistent warmth and high salinity in the subpolar North Atlantic (44–54 N) when boreal summer insolation was decreasing. This apparent paradox was interpreted as the development of a strong thermal gradient between a warm subpolar North Atlantic and a cold nearby land leading to an increase of moisture. This moisture was transported towards the north by storm tracks and fell as snow following the decrease in boreal summer insolation. However, this theoretical model involving a warm ocean-cold land thermal contrast was not confirmed at that time due to the lack of data. Also, the interglacial/glacial transitions were then thought to be gradual but we know now that they were punctuated by millennial-scale events. Thus, one may wonder whether the sub-orbital climatic variability, i.e. D-O cycles and HEs, has affected this orbitallycontrolled ice growth. The direct comparison between pollen (land) and marine climatic records from core MD04-2845 and MD99-2331, located in the southern part of the subpolar North Atlantic, shows that at orbital scale the increase in ice volume was contemporaneous with a progressive cooling in western Europe during the MIS 5a/4 transition. During this transition, the pollen record revealed the replacement of temperate with boreal forest (mainly Abies and Picea). The simultaneous stabilisation of warm SST at around 18 C in the Bay of Biscay demonstrates for the first time a long-term increase of the thermal warm sea-cold land gradient towards the MIS 4 glacial (Sanchez Goñi

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et al. 2013) (Fig. 5). At sub-orbital scale, a decoupling with cooling on land synchronous with warming in SST is further observed. Three successive episodes of strong land-sea thermal gradient and other three with weak gradients occurred during the MIS 5a/4 transition superimposed to the long-term increasing trend in the thermal gradient (Sanchez Goñi et al. 2013). The three strong land-sea thermal gradients coincided with the North Atlantic cold events C20, C19, and C18’ marked by moderate North American iceberg discharges in the western side of the North Atlantic (McManus et al. 1994) (Fig. 5). These events are related to the Greenland cold episodes GS 21, GS 20, and GS 19 (Rasmussen et al. 2014), while the weak gradients coincided with the warm episodes in the North Atlantic and Greenland, GI 20, GI 19, and GI 18. Whereas the events C20, C19, and C18’ were cold in the subpolar gyre and cold conditions installed in western Europe, the European margin remained warm. Increased snowfall in northern Europe and subsequent ice growth resulted from the high rates of moisture production resulting from the above-mentioned strong land-sea thermal gradient and its transport by northward-tracking storms. Southward displacement of tundra by 10 in latitude during cold phases C20, C19, and C18’, suggested by boreal forest colonisation of western Europe, probably amplified ice growth owing to the increase in surface albedo (Crucifix and Loutre 2002). Weak gradients slowed down the process but still allowed ice accumulation. In summary, the direct comparison between marine and terrestrial palaeoclimatic records from the European margin demonstrates for the first time a long-term increase in the thermal gradient between the cold air and warmer sea and three short intervals of even more pronounced thermal gradients during the last entering in glaciation. This synergy between orbital and millennial-scale variability provided a substantial source of moisture that was transported, through northward-tracking storms, to feed ice-sheets in colder Greenland, northern Europe, and the Arctic.

3.3

Pollen, Deglaciation, and Atmospheric CO2 Concentrations

Among the five major short-term carbon reservoirs of the climate system (ocean, atmosphere, terrestrial biosphere, surface sediments, permafrost), terrestrial biosphere (including vegetation and soils) is considered as an essential component of current anthropogenic climate change mitigation strategies (Harris et al. 2021). Terrestrial biosphere interacts with global climate through the photosynthesis/respiration feedback involving CO2 exchanges and consequent changes in the carbon cycle. However, the contribution of terrestrial vegetation in CO2 atmospheric concentration is still far from being understood and quantified. This section presents a recent study (Hes et al. 2021) highlighting the relevance of pollen studies to identify the role of terrestrial vegetation in the past atmospheric CO2 concentration changes revealed by the air bubbles preserved in the Antarctic ice cores. This study focuses

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Fig. 5 The last entering in glaciation (MIS 5a/4, 84.2–68 ka) in the Bay of Biscay and western France revealed by the direct comparison of land and sea palaeoclimatic records from two western

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on the deglaciation that occurred 430,000 years ago, called the Mid-Brunhes Event (MBE, ~430 ka), that marks, despite the weak orbital forcing (Berger and Loutre 1991), the beginning of warmer interglacials and higher CO2 atmospheric concentrations compared to the previous interglacials of the last 800,000 years (EPICA 2004; Luthi et al. 2008) (Fig. 2). Data and models show that past changes in the carbon cycle cannot be explained solely by oceanic changes (Barth et al. 2018; Bouttes et al. 2020). Therefore, other climate mechanisms could have had a role in this transition 430 ka ago. A recent study by Brandon et al. (2020) suggests that terrestrial biosphere productivity could have delayed by at around 10,000 years the atmospheric CO2 maximum increase during the MBE. So far, the hypothesis of terrestrial biosphere contribution to the change in atmospheric CO2 across the MBE by change in vegetation composition or geographical distribution remains open. Hes et al.’s (2021) study is based on a threestep data-model integrated approach and provides: (a) a new pollen record of the Iberian Margin showing for the first time the detailed evolution of the Mediterranean forest during the MBE in southern Iberia, (b) the first global pollen database for this deglaciation to understand terrestrial biosphere evolution at global scale, and (c) new model simulations to be confronted to the database to first evaluate the quality of terrestrial biosphere representation, and secondly to improve our understanding of the role of terrestrial biosphere in the carbon cycle. Figure 6 illustrates the results of this study by comparing the simulated tree fraction (thick lines of the panels) and the forest pollen percentages (thin lines of the panels), a simple approach for estimating the forest cover (Zanon et al. 2018), by region across the MBE. The new high-resolution pollen record from the southwestern Iberian margin, located in the northern subtropical region, shows a moderate Mediterranean forest expansion during this deglaciation (maximum forest pollen percentage of ~50%) in line with seminal work by Oliveira et al. (2016) indicating that the maximum of the forest cover occurred at around 410 ka (Mediterranean panel). In the eastern part of the Mediterranée, the pollen record of Ioannina (Greece) shows a more extensive forest cover likely due to the role of this region as refugium zone for temperate trees during multiple glacial periods (Tzedakis 1993). However, the maximum expansion of the forest also occurred at around 410 ka (Mediterranean panel). Close to this site, lake Van (Turkey, data not available) also records a

Fig. 5 (continued) European margin cores (Sanchez Goñi et al. 2013). (a) Greenland ice core δ18O (black) (Rasmussen et al. 2014) and temperature (red) records compared with (Landais et al. 2004), (b) δ18O curve of benthic foraminifer from core MD04-2845 (dark blue), and reconstructed sea-level changes (light blue) (Waelbroeck et al. 2002), (c) core MD04-2845 (Bay of Biscay): foraminifer-based summer SST curve (red) with the minima and maxima values found in the set of the five selected analogues (grey surface), Atlantic forest pollen percentage curves (green), (d) MD99-2331 (NW Iberian margin) the same as core MD04-2845 and Uk0 37-based SST (black). Grey bands indicate warm intervals in western France. C20, C19, and C180 : cooling events in the western North Atlantic Ocean. GI 21, GI 20, GI 19, and GI 18: warm phases in Greenland. (Bottom) Schematic representation of the cold air-warm ocean contrast in the western European margin at the time of moderate iceberg discharges in the western North Atlantic Ocean

Fig. 6 Each plot shows the simulated tree fraction average (%, solid line) over the corresponding regional box (coloured contours) and associated forest pollen records (%, pale dotted lines) and record average (%, bold dotted line) when available. Locations of the available pollen records are marked by coloured stars ((Hes et al. 2021), in review)

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moderate expansion of the oak forest (Litt et al. 2014). In the pollen record from the China Sea (data not available), another northern subtropical region, we similarly observe a moderate and progressive forest expansion during the MBE with the rainforest maximum at ~405 ka (Cheng et al. 2018), and the southwestern North American pollen record of Valle Calderas, below 40 N, also shows a weak forest expansion during the MBE (Fawcett et al. 2011) (North America (S) panel). Outside these subtropical regions, the pollen records, albeit very sparse, reveal different forest developments varying with latitude and highlighting the strong and earlier expansion of temperate and boreal forests at around 420 ka (Siberia and Europe panels) (Fig. 6). The comparison of global simulated forests, using the Earth Model of Intermediate Complexity iLOVECLIM, to the pollen records described above features overall similar but weaker trends than the pollen-based ones. This first assessment of global forest evolution during MBE points out different driving mechanisms: a strong impact of ice sheet retreat on forests is observed at high latitudes while lower latitude forests are probably more affected by temperature and precipitation changes consistent with other studies (Oliveira et al. 2018; Yin and Berger 2012). The strong high latitude warming (De Vernal and Hillaire-Marcel 2008; Jouzel et al. 2007; Melles et al. 2012) results in both a strong increase of high latitude terrestrial biosphere productivity and a rise in atmospheric CO2 concentration probably driven by ocean physical and chemical degassing processes. Because of the exceptionally high ice sheet melt characterising the MBE (Dutton et al. 2015), forests can develop northwards. Hes et al. (2021) suggest that this strong expansion, observed in the temperate and boreal forests, allows carbon removal by terrestrial biosphere to compensate the oceanic carbon losses, resulting in a long and unique CO2 plateau from ~425 to ~415 kyr BP (Fig. 7). These results would support the mitigation role of the northern hemisphere high latitude forests in the CO2 atmospheric concentration during the MBE. However, additional studies focusing on terrestrial biosphere during the MBE are needed to assess the above-mentioned hypothesis and to clarify the role of tropical and subtropical forests.

4 Pollen for Tracking Past Tree Refugia, Migration Routes, and Speed of Colonisation Identifying the location of past refugia for trees and their routes and speeds of migration in response to climate change is essential to understand the current distribution of trees and anticipates how ecosystems will respond to future climate change (Gavin et al. 2014; Tinner et al. 2013). Past refugia are also key sites for the preservation of biodiversity (Taberlet and Cheddadi 2002). Bennett and Provan (2008) have defined the term refugium zone or refugia as a region in which elements of present-day (interglacial) flora and fauna have survived ice ages with a sharp reduction in numbers and distribution leading to a genetic drift, i.e. the loss of genetic variability. This term includes the term “bottleneck”, i.e. the reduction in

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Fig. 7 Comparison of forest pollen composite curves and observed global biosphere productivity inferred from Δ17O of O2 (solid green line (Brandon et al. 2020)) and CO2 (solid black line (Nehrbass-Ahles et al. 2020)) over the MBE. Forest pollen composite curves from the individual pollen records shown in Fig. 6 are grouped by bioclimatic regions: dashed blue (EurosiberianBoreoamerican region following (Braun-Blanquet 1930), including the pollen records from Europe, Siberia, and high altitudes of central Asia), yellow (Subtropical-N, including the pollen records from the Mediterranean region and North America (S)), purple (Tropical, including the pollen records from Amazon and Tropical Africa), red (Subtropical-S, including only one pollen record from the east of South Africa), and grey (record average) lines

population size followed by an increase in population size following a warming and wetting event. These authors have also enlarged this definition to “interglacial” refugia when present-day cold species have survived to warm climates reducing their population and distribution, as for instance the isolated modern microrefugia, i.e. highly spatially restricted populations, of Cedrus atlantica in the Rif Mountains at elevations above 1,400 m (Cheddadi et al. 2017). Other types of refugia have been proposed (see discussion in (Gavin et al. 2014; Tzedakis et al. 2013) and among them, the so-called cryptic refugia are microrefugia with a weak probability of being detected by fossil records, as it is the case of the persistence of small temperate and boreal tree populations north of the Alps. The identification of cryptic refugia, supported by molecular studies (McLachlan et al. 2005), has recently challenged the paradigm of the classic southern refugia (south of the Alps) and encouraged revisiting postglacial migration histories, spatial organisation of genetic diversity, and conservation priorities to ensure long-term sustainability of temperate and boreal ecosystems. Particularly, cryptic refugia would have enriched northern European genetic diversity and substantially reduced the estimated migration speed of

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temperate and boreal trees from northern refugia. Consequently, these species would be unable to keep pace with projected anthropogenic climate change, although local expansion from small refugia could counterbalance this effect (Pearson 2006). Until the development of genetic studies at the end of the twentieth century, detecting refugium zones was mainly based on the analysis of plant remains, pollen, and macrofossils (macro-charcoal, seeds, fruits, leaves), preserved in sedimentary sequences (e.g. (Huntley and Birks 1983)). Nowadays, the combination of genetic (phylogeographic) and palaeoecological analyses in conjunction with species distribution models (SDM) has been generalised to robustly identify refugium zones, migration routes, and to estimate the speed of tree colonisation (Gavin et al. 2014). Thus, palaeoecological data will provide, on the one hand, the location and timing of refugia based on the radiometric dating of sediments and plant remains, and the tree population abundance. On the other hand, genetic data of modern populations will also indicate the tree population abundance and help to differentiate the populations through time and possibly assess the time of their divergence. For instance, a present-day population with strong genetic diversity suggests an old and dense population compared to a population with weak genetic diversity caused by genetic drift and resulting in a small population size. The genetic diversity is obtained by measuring the allelic richness, i.e. the number of alleles by locus related to isozyme markers in the DNA of the chloroplasts (cp-DNA). The heterozygosity, defined as the number of different alleles in a locus, is measured in the nuclear DNA and is the parameter used to estimate the genetic distance between populations that are characterised by the type of haplotypes. The DNA of mitochondria, mt-DNA, is only maternally inherited and consequently it is considered as the genetic signature of the location of glacial refugia. The third complementary approach to predict species occurrence across space and/or time, the SDMs, is based on statistical or process-based models, i.e. the mathematical representation of one or several processes characterising the functioning of well-delimited biological systems that may be used with the past and future climatic simulations. The greatest strength of this approach is generating hypothesis of the potential location and dynamics of the past and future refugia (Gavin et al. 2014). The three approaches, i.e. fossil remains, genetics, and SDMs, have limitations such as the spatial and temporal discontinuous pollen and plant macroremain records, the spatially- and temporally-smoothed climate data that fail to capture climatic variance and the effects of topography on microclimate and the mismatch between the timescale represented by the observed genetic variation and the period of interest ((Gavin et al. 2014) for a detailed review about strengths, limitations, and advances of these three approaches). In the next sections, I will show two examples related with the contribution of pollen studies to detect European refugia for temperate (Fagus) and boreal (Picea) trees during the most extreme conditions of the last glacial period including the HS 2 and HS 1 and the Last Glacial Maximum (LGM, 23–19 ka) when large ice-sheets close to Atlantic moisture sources, i.e. the western European Ice Sheet (EIS), reached their maximum extent (Batchelor et al. 2019; Hughes et al. 2013).

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Fagus

Based on limited European pollen records and cp-DNA analysis of 389 present-day Fagus populations and 12 isozymes loci, refugium zones for Fagus were believed to be southeastern Europe from where Fagus spread following the onset of postglacial conditions (~10 ka) (Comps et al. 2001) (Fig. 8a). However, the pollen data synthesis performed by Magri et al. (2006) including over 400 fossil-pollen sites and 80 plant-macrofossil sites has confirmed the persistence of scattered low populations of Fagus in several European locations between 37 N and 48 N as early as the onset of the Holocene (10–9 ka) (Fig. 8b). These data combined with

Fig. 8 The history of Fagus in Europe since the last glacial period. (a) Old hypothesis based on the first results for standardised allelic richness in European population of Fagus (Comps et al. 2001). Each point on the map represents the average value for seven populations. Orange dots indicate groups of populations characterised by higher than average allelic richness, blue dots stand for below average values. Contour lines indicate the distribution of beech in the past (6,000, 4,000, and 2,000 years ago), based on the pollen data. These first results suggested that refugia for Fagus were restricted to southeastern Europe contrasting with new findings and additional genetic data (Magri et al. 2006). (b) New pollen and plant macroremain data showing the occurrence of Fagus between 37 N and 48 N as early as the beginning of the Holocene (10–9 ka) (Magri et al. 2006). (c) Spatial analysis of variance (SAMOVA) on isozyme data showing the groups of populations that are geographically homogeneous and maximally differentiated from each other (Magri et al. 2006). (d) Tentative location of refuge areas for Fagus sylvatica during the last glacial maximum and main colonisation routes during the postglacial period (Magri et al. 2006)

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new genetic studies, 450 and 600 modern beech populations for chloroplast and nuclear markers, respectively, show complementary results and support pollen and plant macroremains hypothesis that beech survived the last glacial period in multiple refuge areas (Fig. 8c, d). Moreover, heterozygosity presents an opposite trend: the younger populations (low allelic richness) are characterised by higher heterozygosity, i.e. strong genetic distance with weaker distance covered since the refugia. So heterozygosity does increase despite founding events, which lead to allele losses (Fig. 8c). These results indicate that the central-European refugia were separated from the Mediterranean refugia, which did not contribute to the colonisation of central and northern Europe. They also show that some populations expanded considerably during the postglacial period, while others experienced only a limited expansion and that the mountain chains facilitated, paradoxically, the spread of beech. Finally, this study evidences that cryptic refugia existed for Fagus and that the modern genetic diversity was shaped over multiple glacial-interglacial cycles (Magri et al. 2006).

4.2

Picea

As temperate trees, boreal trees survived the glacial periods in south and east European ice-free macrorefugia and recolonised northern areas when the ice retreated at the end of the last glaciation. However, genetic evidence for extant populations based on the analysis of mt-DNA shows that two haplotypes of Picea are present in Scandinavia, one in the westernmost part of Scandinavia and the other present in central and eastern Europe. Ancient DNA (aDNA) from Picea preserved in 22,000-year-old sediments of lake Andøya (northwest Norway) supports genetic findings on modern DNA and indicates, in turn, that this boreal tree survived in northern Scandinavia during the LGM, when ice covered the entire region (Parducci et al. 2012a, b). The authors propose that Picea survived in the highest summits and plateaus as ice-free nunataks. A hotly debate followed the publication of Parducci et al. paper and among the criticisms Birks et al. (2012) advance potential pollution, bad preservation of aDNA, the lack of evidence that Picea responded to deglacial warming with increases in pollen percentages, and the inability of Picea to persist on exposed nunataks. Parducci et al. (2012a, b) argued, however, that pollution is an unlikely explanation to their findings and that current understanding of LGM glacial limits places northern Andøya outside those limits. Therefore, Picea growth would not have been confined to mountain peaks but it could grow at lower elevations in a wide range of topoclimates. Local temperature reconstruction shows marked fluctuations through the LGM and Late Glacial, including episodes when the mean temperature of the warmest month exceeded 10 C, compatible with the establishment and survival of this boreal tree.

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5 Pollen and Human Evolution Long-term climate changes have been proposed as one of the main driving mechanisms of speciation, extinction, adaptation, and changes in the distribution of animals and plants (Cowling et al. 2008). Evaluating the role of climate and ecosystem changes on human evolution requires well-documented evidence for connections between global climate and hominin regional environments and evolution. So far research has often been limited to proposing a causal link based on the presumed contemporaneity between a climatic event or series of events and biological (extinction or emergence of new species, biogeographic distribution) or cultural phenomena (appearance or decline of technical systems, modes of social organisation, changes in the geographical distribution of these features). If the contemporaneity between a climatic and a cultural/biological event does not constitute per se a proof that the former is the cause of the latter, a synchronism between environmental and archaeological changes is necessary a priori to test the climatic hypothesis. However, inferring causal links between, on the one hand, environmental and biological/cultural changes, and, on the other, environmental changes and migration waves is hampered by the uncertainties of the different radiometric dating methods applied to palaeoclimatic and archaeological records and the debated molecular clock in genetics based on constant rate of mutations. Moreover, the paucity and low resolution of most palaeoenvironmental and archaeological evidence still preclude firm conclusions on the processes underlying adaptation, biological and cultural evolution and exit routes of the genus Homo since the last 2 Myrs (e.g. (d’Errico et al. 2020)). In recent decades, different modelling approaches have been developed to help us in deciphering the possible climatic processes underlying biological and cultural human evolution, such as the replacement of H. neanderthalensis by H. sapiens (e.g. (Banks et al. 2008)) and the dispersal of Homo sapiens out of Africa (e.g. (Timmermann and Friedrich 2016)). In the following sub-sections, the possible impact of climate changes on three key events in human evolution is addressed using the causal link approach implying putative contemporaneous changes between pollen-based vegetation and climate changes and human evolution.

5.1

The Origin of the Genus Homo

Pollen analysis of sedimentary sequences from Africa (Hadar, Ethiopia) and the adjacent Atlantic (offshore the Niger delta) and Indian (Gulf of Aden) margins has provided relevant information to document regional changes in the vegetation and climate associated with human evolution during the last 10 million years (Bonnefille 2010; Bonnefille et al. 2004). The period between 3.4 and 2.9 million years ago (Ma), preceding the emergence of genus Homo, was characterised by strong

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environmental variability to which Australopithecus afarensis, a hominin which had a wide geographical distribution, adapted well. The strongest and abrupt decline of forest pollen accompanied by an increase in the grass pollen was found at 2.7 Ma, more pronounced in the West than in East Africa. It was accompanied by a significant increase in C4 grass proportions, well indicated in the Turkana region and likely explained by an increase in dry season length. Such marked changes correspond to the global climate change of the onset of the Quaternary period, at 2.58 Ma, marked by the establishment of the first large ice-sheets in the northern hemisphere high latitudes that induced strong aridity in the tropics. Savanna expanded at the expense of rainforest, both in West and East Africa, whereas sub-desertic steppe expanded over savanna areas in the North. Mountain forests moved down slopes, closer to lowland sites in the Rift (Bonnefille 2010). During the alternation of Quaternary glacial-interglacial cycles, marine and terrestrial records reveal furthermore the increase of climatic variability in Africa with repeated periods of strong dryness coincident with the appearance of new morphological traits in grassland bovid species, and hominin speciation and extinction and, particularly, the emergence in Africa of the small-brained Homo (H. erectus) at c. 2 Ma (deMenocal 2011). The opening of the landscape likely allowed early Homo populations to improve their hunting strategies (Aiello and Antón 2012). The dental evidence is consistent with increased meat eating (or eating other non-brittle foods) and tool use in food preparation (perhaps even cooking) over the condition in Australopithecus. These results suggest, on the one hand, the dietary and behavioural plasticity of early Homo to face the increased climate variability associated with the northern hemisphere ice growth, and, on the other hand, an increased energy budget resulting in larger brain and body growth and reproduction (Aiello and Antón 2012).

5.2

The Emergence of Modern Humans (H. sapiens) in Africa

The synthesis of deep-sea and terrestrial pollen records from Africa and its margins of the last 1 million years combined with projections shows that northern and southern Africa as well as extratropical eastern Africa were marked by unstable environments (Sanchez Goñi 2020), repeated habitat fragmentation, isolation, and admixture. These unstable environments seem to be optimal places for cultural and biological evolution of Homo leading to the multi-regional origin of H. sapiens as early as 300 ka, as shown by anthropological and genetic data (Scerri et al. 2018; Vidal et al. 2022). Following this speciation, several migration waves of H. sapiens towards Eurasia have been proposed but the strongest evidence of migration, based on palaeogenetic, archaeological, and anthropological data, is dated at around c. 65–55 ka (Bergström et al. 2021) constraining the primary out-of-Africa event during a purported cold and dry time. However, regional pollen analysis has revealed that this period encompasses two distinct main phases in the North Atlantic

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borderlands: the very cold and dry HS 6 (64–60 ka) and the warmer and wetter GIs 17 and 16 (c. 59–56 ka). During this latter phase, the near East (Levant) and the Mediterranean region experienced an amplified increase in winter precipitation and forest development at the time of minima in precession (Bar-Matthews et al. 1999; Fletcher et al. 2010; Langgut et al. 2011; Sanchez Goñi et al. 2008) (Fig. 3). A recent numerical human dispersal model, forced by spatiotemporal estimates of climate and sea-level changes over the past 125 kyr, suggests that, in line with pollen data, repeated orbitally-driven wetting of northern Africa around 106–94, 89–73, 59–47 and 45–29 ka favoured the development of vegetated corridors and, therefore, the recurrent exit of H. sapiens towards Eurasia (Timmermann and Friedrich 2016). Contrasting with this hypothesis, a comparison between the demographic structure of African hominins and environmental changes between 140 ka and 30 ka indicates that during arid intervals between 120 and 80 ka, relative site abundances in tropical Africa increase, perhaps tracking the local effects of forest fragmentation and grassland expansion (Blome et al. 2012). Processes of forest fragmentation may explain population isolation, but also contact between populations and human dispersal as the result of corridor formation as suggested by regional genetic data. Both the drying and wetting-driven development of corridors indicate a complex intertwining of climate and human population movement between the African regions and out of Africa.

5.3

Cultural Evolution of H. sapiens in Europe

H. sapiens reached western Europe at c. 42 ka and subsequently developed a series of Upper Palaeolithic industries, i.e. Aurignacian, Gravettian, Solutrean, and Magdalenian (d’Errico and Banks 2015), during the highly variable period between 42 and 12 ka. Based on the palaeoecological data Richerson et al. (2005) have proposed that during the GSs, large areas of the world were either very dry or very cold and therefore human populations were absent or reduced to small numbers. This weak human population would have produced few innovations. In turn, warm and humid GIs probably created large areas of moist steppe-forest mosaic biomes that would sustain fair densities of human big game hunters and, therefore, a high number of innovations. We tested this hypothesis for Europe and compared the distribution of the number of European Palaeolithic sites dated between 8,000 and 36,500 14C AMS years BP, with well-dated deep-sea pollen records and the benthic foraminiferal δ18O record, proxies for regional environmental changes and global ice-volume variations, respectively. The comparison of the temporal distribution of sites, at 500-year intervals, with the benthic foraminiferal δ18O record shows long-term, orbital, close general patterns (Fig. 9). The increase in ice volume is concomitant with the decrease in the number of sites indicating a population contraction due to the reduced extent of areas with resources exploitable by Palaeolithic hunters (d’Errico et al. 2006). This hypothesis is confirmed by taking into account the latitudes and altitudes

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Fig. 9 Comparison between palaeoenvironmental changes in western Europe and the number of dated archaeological sites by 500-year intervals during the last 37,000 14C years before present (BP) (Sanchez Goñi 2020). Note that archaeological and marine palaeoclimatic records are plotted against no calibrated 14C ages. (a) Number of dated archaeological sites (d’Errico et al. 2006). (b) Mediterranean forest pollen record from the SW Iberian margin (Sanchez Goñi et al. 2008). (c) Atlantic temperate forest pollen record from the NW Iberian margin (Sanchez Goñi et al. 2008). (d) Relative sea-level changes as an indicator for ice-volume changes (Waelbroeck et al. 2002). (e) Changes in insolation in July at 65 N (Berger and Loutre 1991). LGM Last Glacial Maximum

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of the archaeological sites (d’Errico et al. 2006). The reduction in the number of sites during the LGM corresponds to the compression towards lower latitudes and altitudes of their distribution. This compression clearly reflects the effect on the biosphere of increasing ice volume. The population reduction during the LGM is certainly overestimated because we lack information on the colonisation of large areas of land caused by sea level lowering. Located at low altitude and often consisting of plains, these areas could support steppe vegetation suitable for certain species of ungulates and their predation by Palaeolithic populations. At the millennial timescale, the comparison of the number of European Upper Palaeolithic sites with the GI and GS phases dated, as the archaeological sites, by 14C AMS in the deep-sea pollen records MD95-2042 (Shackleton et al. 2004) and MD99-2331 (Naughton et al. 2009) (Fig. 9), in 2006 no curve of calibration was available going back to 40 ka, shows that the population density decreased during warming events and contemporaneous forest development. Studies on historical hunter-gatherer populations show that low biomass temperate steppes are associated with high ungulate biomass and strong human demography. Forested landscapes are, on the contrary, characterised by high plant biomass and low fauna and human populations (d’Errico et al. 2006). Therefore, each afforestation reduced the biomass of ungulates, the main resource of Palaeolithic hunters (Bocherens et al. 2005). By reducing the forest cover and leaving steppes to develop, the periods of cooling and drying were characterised in the mid-latitudes by an increase in ungulate biomass, causing of a human demographic boom. The increase in the number of sites seen in the early part of the Bølling-Allerød interstadial warm phase (GI 1, 14.7–12.8 14C ka) is likely related to the recolonisation of high latitudes and altitudes at the time of the retreat of glacial and periglacial zones (Fig. 9). However, as soon as forest was well established, at around 12,000 14C AMS years BP, a further reduction in the number of sites is seen, brought about by a reduction in the ungulate biomass. Shortly halted by the deforestation produced by the cold episode of the Younger Dryas Stadial (GS 1, 12.8–11.7 14C ka), this tendency to reduce the number of sites seems to be repeated as soon as warming resumes, in the early Holocene. The increase in the number of sites in the early postglacial period, in a very forested environment, can be related to new modes of adaptation, such as intensive harvesting, that exploit the entire terrestrial and marine resources and makes the demography of human groups independent of ungulate biomass. These results further show that GS marked by a drop in temperature and rainfall, considered of high ecological risk for historical hunter-gatherer populations (Collard and Foley 2002; Nettle 1998), should stimulate the maintenance of the same cultural and linguistic features over larger areas, while GI warm periods are expected to lead fragmentation of these ethno-linguistic units. In conclusion, the long-term variation in the number of Upper Palaeolithic sites would reflect the population demography, and that the high population demography depends both on the ice-free surface area offering hunting resources and, on a finer timescale, the development of steppes during the GS cold phases offering a higher ungulate biomass. Richerson et al. (2005) have hypothesised that the increase of steppe-forest produced more resources allowing the increase in populations and

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therefore in innovations. Contrasting with this hypothesis, innovations in Europe will be produced rather during steppe-dominated cold and dry periods. Furthermore, a more recent study (Schmidt et al. 2012) comparing calibrated 14C eastern North Atlantic and southwestern European palaeoclimatic records with a comprehensive Iberian record of technocomplexes, from the late Middle Palaeolithic, early Upper Palaeolithic, Gravettian, and Solutrean (152 archaeological cave sites and rock shelters), shows that regional major cultural changes coincide with the environmental impact of North Atlantic HEs. However, this hypothesis has to be confirmed by quantifying the degree of breakdown between the different “cultures” that are only qualitatively defined so far.

6 Conclusions and Perspectives This article presents a review, albeit no exhaustive, of how the study of ancient pollen preserved in marine and terrestrial sedimentary sequences may contribute to the understanding of the Earth’s climate and vegetation dynamics and human evolution. Throughout this work, several examples of issues I have been interested in over the last few years are shown. For climate, the study of ancient pollen and, particularly that preserved in deepocean sedimentary sequences also containing oceanic and ice volume proxies, is relevant to understand the leads and lags in the response of the different Earth’s reservoirs (hydrosphere, cryosphere, atmosphere, terrestrial surfaces, vegetation) to global climate changes. The identification of both leads and lags and interactions between the orbital, long-term, and millennial, short-term, climatic variability has allowed, for instance, going a step forward in the knowledge of the processes underlying the entering in glaciation. Additionally, pollen records reveal strong regionalisation of vegetation and climate responses to global climate changes. Changes in vegetation distribution and composition, specifically the different magnitude and timing of regional forest expansions during the deglaciation around ~420 ka, seem to play a certain role in the observed atmospheric CO2 concentration changes. In terms of vegetation dynamics, pollen studies along with plant macro remains and DNA analyses have documented the location of cryptic refugia for temperate and boreal tree populations and, therefore, substantially reduced the original estimations of tree migration velocity from these refugia. This lower velocity put into question the ability of trees to keep pace with the on-going climate change. Finally, the comparison of pollen-based vegetation reconstructions along with anthropological, paleontological, and archaeological data shows that hominins were able to adapt to new and variable environments. Particularly, the repeated development of vegetation corridors in Africa during glacial and interglacial periods favoured isolation, fragmentation, and admixture of populations leading to the multi-regional origin of H. sapiens and successive wave migrations towards Eurasia. In Europe, the rapid warming (wetting)/cooling (drying) of the last glacial period

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triggered repeated steppe-dominant periods of increasing ungulate biomass resources and human demography. The rapid changing environments along with large human populations during steppe-dominant periods could trigger the successive technological and cultural innovations characterising H. sapiens over the last 40,000 years. There are three major research perspectives I foresee regarding the contribution of the pollen analysis to understand the Earth’s climate, vegetation, and human evolution. First, a necessary step to achieve an accurate picture of terrestrial biosphere evolution through time is to increase the marine and terrestrial pollen record coverage, especially in poorly documented regions such as the American continent, Siberia, and central and southern Asia (tropical forests), associated with the development of pollen databases. Second, an integrated understanding of the past carbon cycle, when anthropogenic CO2 and CH4 emissions were negligible, will require improving the forest cover quantification from pollen data at global and regional scales to evaluate terrestrial biosphere simulations. The REVEALS model was conceived to obtain quantitative reconstructions of regional vegetation cover around large lakes from pollen data, which somehow resembles the spatial scale of marine pollen samples (Sugita 2007). Nevertheless, this model only considers atmospheric pollen dispersal and deposition, thus disregarding the importance of pollen input from inlet streams and surface run-off (Sugita 2007), which are often the main vectors delivering pollen to the marine environment. An alternative approach, based on the coupling of modern terrestrial pollen samples with the corresponding satellite-based forest cover data, assigns to every fossil sample the average forest cover of its closest modern analogues (Zanon et al. 2018). This approach has produced a series of maps detailing the evolution of European forest cover during the last 12,000 years that are most of the time in good agreement with the REVEALS method at a trend level. Although MAT regularly underestimates the occurrence of densely forested situations, this approach should be applied, after bias correction, to other regions and time periods. MAT should also include marine pollen assemblages to better estimate past changes in regional to sub-continental land vegetation cover to directly compare them with changes in other Earth’s reservoirs. The third perspective I foresee is to improve the quantitative estimations of climate parameters from deep-sea pollen records by integrating marine modern pollen assemblages in the database. Finally and complementary to the increase of pollen coverage data, the study of the possible impact of environmental changes on human evolution should go beyond the climate-human causal link approach. Increased efforts towards processmodelling approaches are needed to evaluate if and how environmental changes significatively contribute to human evolution. Acknowledgements I am grateful to Donatella Magri for the critical reading of the manuscript and Gabriel Hes for useful comments. I also thank Vincent Hanquiez for drawing Figs. 4, 5, and 8.

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