Author: "Potsdam Institute for Climate Impact Research ( PIK )" / Topic: 15. life on land - Searchworks@Jio Institute Digital Library Search Results

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147 results on '"Potsdam Institute for Climate Impact Research ( PIK )"'

1. The uncertainty of crop yield projections is reduced by improved temperature response functions

Author: Alex C. Ruane, Peter J. Thorburn, Mikhail A. Semenov, Joost Wolf, Claudio O. Stöckle, Pramod K. Aggarwal, Gerard W. Wall, Margarita Garcia-Vila, Matthew P. Reynolds, Eckart Priesack, Jørgen E. Olesen, Enli Wang, Bruce A. Kimball, Jordi Doltra, Iurii Shcherbak, Ehsan Eyshi Rezaei, Jeffrey W. White, Leilei Liu, L. A. Hunt, Senthold Asseng, Frank Ewert, Yan Zhu, Fulu Tao, Christoph Müller, Daniel Wallach, Christian Biernath, Davide Cammarano, Mohamed Jabloun, Zhigan Zhao, Michael J. Ottman, Pierre Martre, Sebastian Gayler, Garry O'Leary, Zhimin Wang, Jakarat Anothai, Elias Fereres, Claas Nendel, Bruno Basso, Thilo Streck, Curtis D. Jones, Andrea Maiorano, Phillip D. Alderman, Andrew J. Challinor, Reimund P. Rötter, Taru Palosuo, Iwan Supit, Katharina Waha, Giacomo De Sanctis, Kurt Christian Kersebaum, Soora Naresh Kumar, Gerrit Hoogenboom, Dominique Ripoche, Pierre Stratonovitch, Ann-Kristin Koehler, Roberto C. Izaurralde, Commonwealth Scientific and Industrial Research Organisation (Australia), Chinese Academy of Sciences, China Scholarship Council, Ministry of Education of the People's Republic of China, Institut National de la Recherche Agronomique (France), European Commission, International Food Policy Research Institute (US), CGIAR (France), Department of Agriculture (US), Federal Ministry of Education and Research (Germany), Deutsche Gesellschaft für Internationale Zusammenarbeit, Danish Council for Strategic Research, Federal Ministry of Food and Agriculture (Germany), Finnish Ministry of Agriculture and Forestry, National Natural Science Foundation of China, Helmholtz Association, Grains Research and Development Corporation (Australia), Texas AgriLife Research, Texas A&M University, National Institute of Food and Agriculture (US), CSIRO, Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), College of Agronomy and Biotechnology, Southwest University, Institute of Crop Science and Resource Conservation, Division of Plant Nutrition-University of Bonn, Institute of Landscape Systems Analysis, Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research (ZALF), Department of Crop Sciences, University of Goettingen, Centre of Biodiversity and Sustainable Land Use (CBL), United States Department of Agriculture - Agricultural Research Service, The School of Plant Sciences, University of Arizona, Global Wheat Program, International Maize and Wheat Improvement Center (CIMMYT), CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), Washington State University (WSU), Department of Earth and Environmental Sciences and W.K. Kellogg Biological Station, Michigan State University [East Lansing], Michigan State University System-Michigan State University System, Institute of Biochemical Plant Pathology (BIOP), German Research Center for Environmental Health - Helmholtz Center München (GmbH), Agricultural and Biological Engineering Department, Purdue University [West Lafayette], Institute for Climate and Atmospheric Science [Leeds] (ICAS), School of Earth and Environment [Leeds] (SEE), University of Leeds-University of Leeds, GMO Unit, European Food Safety Authority = Autorité européenne de sécurité des aliments, Cantabrian Agricultural Research and Training Centre, Dep. Agronomia, University of Córdoba [Córdoba], Spanish National Research Council (CSIC), Institute of Soil Science and Land Evaluation, University of Hohenheim, Department of Plant Agriculture, University of Guelph, Department of Geographical Sciences, University of Maryland [College Park], University of Maryland System-University of Maryland System, Texas A&M AgriLife Research and Extension Center, Texas A&M University System, Department of Agroecology, Aarhus University [Aarhus], National Engineering and Technology Center for Information Agriculture, Nanjing Agricutural University, Potsdam Institute for Climate Impact Research (PIK), Centre for Environment Science and Climate Resilient Agriculture (CESCRA), Indian Agricultural Research Institute (IARI), Department of Economic Development, Department of Economic Development, Jobs, Transport and Resources (DEDJTR), Natural Resources Institute Finland, Institute of Crop Science and Resource Conservation (INRES), Rheinische Friedrich-Wilhelms-Universität Bonn, UE Agroclim (UE AGROCLIM), Institut National de la Recherche Agronomique (INRA), NASA Goddard Institute for Space Studies (GISS), NASA Goddard Space Flight Center (GSFC), Computational and Systems Biology Department, Rothamsted Research, Biological Systems Engineering, University of Wisconsin-Madison, PPS and WSG &CALM, Wageningen University and Research Center (WUR), Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences [Beijing] (CAS), Agriculture and Food, Universidad de La Rioja (UR), UMR : AGroécologie, Innovations, TeRritoires, Ecole Nationale Supérieure Agronomique de Toulouse, China Agricultural University, Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro), China Agricultural University (CAU), Institute of Crop Science and Resource Conservation [Bonn], Georg-August-University [Göttingen], Arid-Land Agricultural Research Center, Consultative Group on International Agricultural Research [CGIAR] (CGIAR)-Consultative Group on International Agricultural Research [CGIAR] (CGIAR), CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), Department of Agricultural and Biological Engineering [Gainesville] (UF|ABE), Institute of Food and Agricultural Sciences [Gainesville] (UF|IFAS), University of Florida [Gainesville] (UF)-University of Florida [Gainesville] (UF), University of Leeds, European Food Safety Authority (EFSA), Catabrian Agricultural Research and Training Center (CIFA), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), AgWeatherNet Program, Texas A and M AgriLife Research, Jiangsu Collaborative Innovation Center for Modern Crop Production, Landscape and Water Sciences, Natural Resources Institute Finland (LUKE), Agroclim (AGROCLIM), Wageningen University and Research [Wageningen] (WUR), Chinese Academy of Agricultural Sciences (CAAS), AGroécologie, Innovations, teRritoires (AGIR), Institut National de la Recherche Agronomique (INRA)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, European Project: 267196,EC:FP7:PEOPLE,FP7-PEOPLE-2010-COFUND,AGREENSKILLS(2012), Écophysiologie des Plantes sous Stress environnementaux ( LEPSE ), Institut National de la Recherche Agronomique ( INRA ) -Centre international d'études supérieures en sciences agronomiques ( Montpellier SupAgro ) -Institut national d’études supérieures agronomiques de Montpellier ( Montpellier SupAgro ), Leibniz Centre for Agricultural Landscape Research, International Maize and Wheat Improvement Center ( CIMMYT ), CGIAR Research Program on Climate Change, Agriculture and Food Security ( CCAFS ), Washington State University ( WSU ), Michigan State University, Institute of Biochemical Plant Pathology ( BIOP ), Institute for Climate and Atmospheric Science, School of Earth and Environment, European Food Safety Authority, Spanish National Research Council ( CSIC ), Texas A and M University ( TAMU ), Potsdam Institute for Climate Impact Research ( PIK ), Centre for Environment Science and Climate Resilient Agriculture ( CESCRA ), Indian Agricultural Research Institute ( IARI ), Department of Economic Development, Jobs, Transport and Resources ( DEDJTR ), University of Bonn (Rheinische Friedrich-Wilhelms), UE Agroclim ( UE AGROCLIM ), Institut National de la Recherche Agronomique ( INRA ), NASA Goddard Institute for Space Studies ( GISS ), NASA Goddard Space Flight Center ( GSFC ), University of Wisconsin-Madison [Madison], Wageningen University and Research Center ( WUR ), Chinese Academy of Sciences [Beijing] ( CAS ), Universidad de La Rioja ( UR ), University of Bonn-Division of Plant Nutrition, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), USDA-ARS : Agricultural Research Service, Consultative Group on International Agricultural Research [CGIAR]-Consultative Group on International Agricultural Research [CGIAR], Natural resources institute Finland, Georg-August-University = Georg-August-Universität Göttingen, Universidad de Córdoba = University of Córdoba [Córdoba], Biotechnology and Biological Sciences Research Council (BBSRC)-Biotechnology and Biological Sciences Research Council (BBSRC), and Université de Toulouse (UT)-Université de Toulouse (UT)
Subjects: Crops, Agricultural, 010504 meteorology & atmospheric sciences, [SDV]Life Sciences [q-bio], Yield (finance), Water en Voedsel, Growing season, Climate change, klim, Plant Science, Agricultural engineering, Models, Biological, 01 natural sciences, [SHS]Humanities and Social Sciences, Crop, Life Science, Computer Simulation, Productivity, 0105 earth and related environmental sciences, 2. Zero hunger, [ SDE.BE ] Environmental Sciences/Biodiversity and Ecology, WIMEK, Water and Food, Food security, business.industry, Crop yield, Temperature, Agriculture, 04 agricultural and veterinary sciences, 15. Life on land, Climate Resilience, Agronomy, Klimaatbestendigheid, 13. Climate action, [SDE]Environmental Sciences, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Environmental science, Water Systems and Global Change, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, business
Abstract: Increasing the accuracy of crop productivity estimates is a key element in planning adaptation strategies to ensure global food security under climate change. Process-based crop models are effective means to project climate impact on crop yield, but have large uncertainty in yield simulations. Here, we show that variations in the mathematical functions currently used to simulate temperature responses of physiological processes in 29 wheat models account for >50% of uncertainty in simulated grain yields for mean growing season temperatures from 14 °C to 33 °C. We derived a set of new temperature response functions that when substituted in four wheat models reduced the error in grain yield simulations across seven global sites with different temperature regimes by 19% to 50% (42% average). We anticipate the improved temperature responses to be a key step to improve modelling of crops under rising temperature and climate change, leading to higher skill of crop yield projections., E.W. acknowledges support from the CSIRO project ‘Enhanced modelling of genotype by environment interactions’ and the project ‘Advancing crop yield while reducing the use of water and nitrogen’ jointly funded by CSIRO and the Chinese Academy of Sciences (CAS). Z.Z. received a scholarship from the China Scholarship Council through the CSIRO and the Chinese Ministry of Education PhD Research Program. P.M., A.M. and D.R. acknowledge support from the FACCE JPI MACSUR project (031A103B) through the metaprogram Adaptation of Agriculture and Forests to Climate Change (AAFCC) of the French National Institute for Agricultural Research (INRA). A.M. received the support of the EU in the framework of the Marie-Curie FP7 COFUND People Programme, through the award of an AgreenSkills fellowship under grant agreement No. PCOFUND-GA-2010-267196. S.A. and D.C. acknowledge support provided by the International Food Policy Research Institute (IFPRI), CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), the CGIAR Research Program on Wheat and the Wheat Initiative. C.S. was funded through USDA National Institute for Food and Agriculture award 32011-68002-30191. C.M. received financial support from the KULUNDA project (01LL0905 L) and the FACCE MACSUR project (031A103B) funded through the German Federal Ministry of Education and Research (BMBF). F.E. received support from the FACCE MACSUR project (031A103B) funded through the German Federal Ministry of Education and Research (2812ERA115) and E.E.R. was funded through the German Federal Ministry of Economic Cooperation and Development (Project: PARI). M.J. and J.E.O. were funded through the FACCE MACSUR project by the Danish Strategic Research Council. K.C.K. and C.N. were funded by the FACCE MACSUR project through the German Federal Ministry of Food and Agriculture (BMEL). F.T., T.P. and R.P.R. received financial support from the FACCE MACSUR project funded through the Finnish Ministry of Agriculture and Forestry (MMM); F.T. was also funded through the National Natural Science Foundation of China (No. 41071030). C.B. was funded through the Helmholtz project ‘REKLIM-Regional Climate Change: Causes and Effects’ Topic 9: ‘Climate Change and Air Quality’. M.P.R. and PD.A. received funding from the CGIAR Research Program on Climate Change, Agriculture, and Food Security (CCAFS). G.O'L. was funded through the Australian Grains Research and Development Corporation and the Department of Economic Development, Jobs, Transport and Resources Victoria, Australia. R.C.I. was funded by Texas AgriLife Research, Texas A&M University. B.B. was funded by USDA-NIFA Grant No: 2015-68007-23133.
Published: 2017
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2. Multi-wheat-model ensemble responses to interannual climate variability

Author: Carlos Angulo, Frank Ewert, Tom M. Osborne, Pramod K. Aggarwal, Senthold Asseng, Pasquale Steduto, Kurt Christian Kersebaum, Eckart Priesack, Patrick Bertuzzi, Roberto C. Izaurralde, Dominique Ripoche, Thilo Streck, Joost Wolf, Pierre Stratonovitch, Alex C. Ruane, Richard Goldberg, Robert F. Grant, Taru Palosuo, Iurii Shcherbak, Kenneth J. Boote, Christian Biernath, Garry O'Leary, J. Hooker, Peter J. Thorburn, Joachim Ingwersen, Soora Naresh Kumar, Lee Heng, Maria I. Travasso, Pierre Martre, Katharina Waha, Nicholas I. Hudson, Claas Nendel, Fulu Tao, Christoph Müller, Andrew J. Challinor, Jørgen E. Olesen, Reimund P. Rötter, Davide Camarrano, L. A. Hunt, Sebastian Gayler, Nadine Brisson, Daniel Wallach, Mikhail A. Semenov, Claudio O. Stöckle, Iwan Supit, Jordi Doltra, Jeffrey W. White, Bruno Basso, NASA Goddard Institute for Space Studies (GISS), NASA Goddard Space Flight Center (GSFC), Center for Climate Systems Research [New York] (CCSR), Columbia University [New York], Agricultural & Biological Engineering Department, University of Florida [Gainesville], The James Hutton Institute, Institute of Crop Science and Resource Conservation, Rheinische Friedrich-Wilhelms-Universität Bonn, Leibniz-Zentrum für Agrarlandschaftsforschung (ZALF), Leibniz Association, Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Génétique Diversité et Ecophysiologie des Céréales (GDEC), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP), Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), Research Program on Climate Change, Agriculture and Food Security, International Water Management Institute, International Water Management Institute, Department of Geological Sciences and W. K. Kellogg Biological Station, Michigan State University [East Lansing], Michigan State University System-Michigan State University System, UE Agroclim (UE AGROCLIM), Institut National de la Recherche Agronomique (INRA), Institute of Biochemical Plant Pathology, German Research Center for Environmental Health - Helmholtz Center München (GmbH), Agronomie, AgroParisTech-Institut National de la Recherche Agronomique (INRA), Institute for Climate and Atmospheric Science [Leeds] (ICAS), School of Earth and Environment [Leeds] (SEE), University of Leeds-University of Leeds, CGIAR-ESSP Program on Climate Change, Agriculture and Food Security, International Center for Tropical Agriculture, Cantabrian Agricultural Research and Training Centre, Institute of Soil Science and Land Evaluation, University of Hohenheim, Department of Renewable Resources, University of Alberta, International Atomic Energy Agency [Vienna] (IAEA), School of Agriculture, Policy and Development, University of Reading (UOR), Department of Plant Agriculture, University of Guelph, Department of Geographical Sciences, University of Maryland [College Park], University of Maryland System-University of Maryland System, Centre for Environment Science and Climate Resilient Agriculture (CESCRA), Indian Agricultural Research Institute (IARI), Potsdam Institute for Climate Impact Research (PIK), Landscape & Water Sciences, Department of Environment of Victoria, Department of Agroecology, Aarhus University, National Centre for Atmospheric Science, Department of Meteorology, Environmental Impacts Group, Natural Resources Institute Finland, Georg-August-Universität Göttingen, Computational and Systems Biology Department, Rothamsted Research, Biotechnology and Biological Sciences Research Council, Institute for Future Environments, Queensland University of Technology, Food and Agriculture Organization, Biological Systems Engineering, Washington State University (WSU), Earth System Science-Climate Change and Adaptive Land-use and Water Management, Wageningen University and Research Center (WUR), Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences [Changchun Branch] (CAS), Institute for Climate and Water [Castelnar], Instituto Nacional de Tecnología Agropecuaria (INTA), UMR : AGroécologie, Innovations, TeRritoires, Ecole Nationale Supérieure Agronomique de Toulouse, USDA-ARS, Arid-Land Agricultural Research Center, United States Department of Agriculture, Plant Production Systems, Modelling European Agriculture with Climate Change for Food Security (MACSUR), JPI FACCE, Department of Agricultural and Biological Engineering [Gainesville] (UF|ABE), Institute of Food and Agricultural Sciences [Gainesville] (UF|IFAS), University of Florida [Gainesville] (UF)-University of Florida [Gainesville] (UF), Institute of Crop Science and Resource Conservation [Bonn], Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Agroclim (AGROCLIM), Aarhus University [Aarhus], Natural resources institute Finland, Georg-August-University [Göttingen], Wageningen University and Research [Wageningen] (WUR), AGroécologie, Innovations, teRritoires (AGIR), Institut National de la Recherche Agronomique (INRA)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Natural Resources Institute Finland (LUKE), Georg-August-University = Georg-August-Universität Göttingen, Biotechnology and Biological Sciences Research Council (BBSRC), Queensland University of Technology [Brisbane] (QUT), Institute of geographical sciences and natural resources research [CAS] (IGSNRR), Chinese Academy of Sciences [Beijing] (CAS), Université de Toulouse (UT)-Université de Toulouse (UT), USDA Agricultural Research Service [Maricopa, AZ] (USDA), United States Department of Agriculture (USDA), NASA Goddard Institute for Space Studies ( GISS ), NASA Goddard Space Flight Center ( GSFC ), Center for Climate Systems Research [New York] ( CCSR ), University of Florida, University of Bonn (Rheinische Friedrich-Wilhelms), Leibniz Centre for Agricultural Landscape Research (ZALF), Écophysiologie des Plantes sous Stress environnementaux ( LEPSE ), Institut National de la Recherche Agronomique ( INRA ) -Centre international d'études supérieures en sciences agronomiques ( Montpellier SupAgro ) -Institut national d’études supérieures agronomiques de Montpellier ( Montpellier SupAgro ), Génétique Diversité et Ecophysiologie des Céréales ( GDEC ), Institut National de la Recherche Agronomique ( INRA ) -Université Blaise Pascal - Clermont-Ferrand 2 ( UBP ), Commonwealth Scientific and Industrial Research Organisation, Department of Geological Sciences and Kellogg Biological Station, Michigan State University, UE Agroclim ( UE AGROCLIM ), Institut National de la Recherche Agronomique ( INRA ), Institut National de la Recherche Agronomique ( INRA ) -AgroParisTech, Institute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, International Atomic Energy Agency [Vienna] ( IAEA ), University of Reading ( UOR ), University of Maryland, Centre for Environment Science and Climate Resilient Agriculture ( CESCRA ), Indian Agricultural Research Institute ( IARI ), Potsdam Institute for Climate Impact Research ( PIK ), Washington State University ( WSU ), Wageningen University and Research Center ( WUR ), Chinese Academy of Sciences [Changchun Branch] ( CAS ), Institute for Climate and Water, and Instituto Nacional de Tecnología Agropecuaria
Subjects: [SDV.SA]Life Sciences [q-bio]/Agricultural sciences, Temperature sensitivity, 010504 meteorology & atmospheric sciences, Precipitation, 01 natural sciences, modèle de croissance, wheat, uncertainty, [ SDV.SA ] Life Sciences [q-bio]/Agricultural sciences, climate impacts, 2. Zero hunger, Multi-model ensemble, changement climatique, Ecological Modeling, Temperature, Uncertainty, 04 agricultural and veterinary sciences, PE&RC, Plant Production Systems, Climatology, PRECIPITATION, Climate impacts, Environmental Engineering, interannual variability, Yield (finance), australie, variation interannuelle, Growing season, Climate change, multi-model ensemble, Earth System Science, Interannual variability, blé, température, pays bas, global change, 0105 earth and related environmental sciences, [ SDE.BE ] Environmental Sciences/Biodiversity and Ecology, WIMEK, précipitation, business.industry, argentine, Simulation modeling, temperature, Global change, 15. Life on land, inde, Climate Resilience, 13. Climate action, Agriculture, Klimaatbestendigheid, Plantaardige Productiesystemen, 040103 agronomy & agriculture, AgMIP, 0401 agriculture, forestry, and fisheries, Environmental science, Leerstoelgroep Aardsysteemkunde, Crop modeling, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, business, Software
Abstract: We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981-2010 grain yield, and we evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models' climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal common characteristics of yield response to climate; however models rarely share the same cluster at all four sites indicating substantial independence. Only a weak relationship (R2???0.24) was found between the models' sensitivities to interannual temperature variability and their response to long-term warming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts. Compares interannual climate response of 27 wheat models at four locations.Calculates the diminishing return of constructing multi-model ensembles for assessment.Identifies similarities and major differences of model responses.Differentiates between interannual temperature sensitivity and climate change response.
Published: 2016
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3. Fire evolution in the radioactive forests of Ukraine and Belarus: future risks for the population and the environment

Author: Patricia Cadule, Sergiy Zibtsev, Nikolaos Evangeliou, Anders Pape Møller, Benjamin Poulter, Florent Mouillot, Wei Min Hao, Alexander Petkov, Ronan Paugam, Brigitte Koffi, Timothy A. Mousseau, Anne Cozic, Yves Balkanski, Kirsten Thonicke, Rong Wang, Chao Yue, Johannes W. Kaiser, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université Paris-Saclay-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS), Climat et fonctionnement des agro-écosystèmes, rôle de l'agrodiversité dans la stabilité de la production (CLIFA), Potsdam Institute for Climate Impact Research (PIK), Montana State University (MSU), Air and Climate Unit [Ispra], JRC Institute for Environment and Sustainability (IES), European Commission - Joint Research Centre [Ispra] (JRC)-European Commission - Joint Research Centre [Ispra] (JRC), Laboratoire de Modélisation et Simulation Multi Echelle (MSME), Centre National de la Recherche Scientifique (CNRS)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Université Paris-Est Marne-la-Vallée (UPEM), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Modelling the Earth Response to Multiple Anthropogenic Interactions and Dynamics (MERMAID), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Calcul Scientifique (CALCULS), USDA Forest Service Rocky Mountain Forest and Range Experiment Station, United States Department of Agriculture (USDA), Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Université Paul-Valéry - Montpellier 3 (UPVM)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), King‘s College London, National University of Life and Environmental Sciences of Ukraine (NUBiP), University of South Carolina [Columbia], Modélisation INVerse pour les mesures atmosphériques et SATellitaires (SATINV), European Centre for Medium-Range Weather Forecasts (ECMWF), Max-Planck-Institut für Biophysikalische Chemie - Max Planck Institute for Biophysical Chemistry [Göttingen], Max-Planck-Gesellschaft, Ecologie Systématique et Evolution (ESE), AgroParisTech-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Université Paul-Valéry - Montpellier 3 (UPVM)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] ( LSCE ), Université de Versailles Saint-Quentin-en-Yvelines ( UVSQ ) -Commissariat à l'énergie atomique et aux énergies alternatives ( CEA ) -Université Paris-Saclay-Centre National de la Recherche Scientifique ( CNRS ), Climat et fonctionnement des agro-écosystèmes, rôle de l'agrodiversité dans la stabilité de la production ( CLIFA ), Potsdam Institute for Climate Impact Research ( PIK ), Montana State University ( MSU ), JRC Institute for Environment and Sustainability ( IES ), European Commission - Joint Research Centre [Ispra] ( JRC ) -European Commission - Joint Research Centre [Ispra] ( JRC ), Laboratoire de Modélisation et Simulation Multi Echelle ( MSME ), Centre National de la Recherche Scientifique ( CNRS ) -Université Paris-Est Créteil Val-de-Marne - Paris 12 ( UPEC UP12 ) -Université Paris-Est Marne-la-Vallée ( UPEM ), and Université Paul-Valéry - Montpellier 3 (UPVM)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-École Pratique des Hautes Études (EPHE)
Subjects: [ SDU.OCEAN ] Sciences of the Universe [physics]/Ocean, Atmosphere, Cesium-137, Population, Climate change, Firefighting, Chernobyl, redistribution, Altitude, litter, Environmental protection, [ SDU.ENVI ] Sciences of the Universe [physics]/Continental interfaces, environment, education, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, Ecology, Evolution, Behavior and Systematics, ComputingMilieux_MISCELLANEOUS, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Radionuclide, education.field_of_study, Fire regime, Ecology, carbon stock, 15. Life on land, climate change, 13. Climate action, Litter, wildfires, Environmental science, fire risk, Woody plant
Abstract: International audience; In this paper, we analyze the current and future status of forests in Ukraine and Belarus that were contaminated after the nuclear disaster in 1986. Using several models, together with remote‐sensing data and observations, we studied how climate change in these forests may affect fire regimes. We investigated the possibility of 137Cs displacement over Europe by studying previous fire events, and examined three fire scenarios that depended on different emission altitudes of 137Cs, assuming that 10% of the forests were affected by fires. Field measurements and modeling simulations confirmed that numerous radioactive contaminants are still present at these sites in extremely large quantities.Forests in Eastern Europe are characterized by large, highly fire‐prone patches that are conducive to the development of extreme crown fires. Since 1986, there has been a positive correlation between extreme fire events and drought in the two contaminated regions. Litter carbon storage in the area has doubled since 1986 due to increased tree mortality and decreased decomposition rates; dead trees and accumulating litter in turn can provide fuel for wildfires that pose a high risk of redistributing radioactivity in future years. Intense fires in 2002, 2008, and 2010 resulted in the displacement of 137Cs to the south; the cumulative amount of 137Cs re‐deposited over Europe was equivalent to 8% of that deposited following the initial Chernobyl disaster. However, a large amount of 137Cs still remains in these forests, which could be remobilized along with a large number of other dangerous, long‐lived, refractory radionuclides. We predict that an expanding flammable area associated with climate change will lead to a high risk of radioactive contamination with characteristic fire peaks in the future. Current fire‐fighting infrastructure in the region is inadequate due to understaffing and lack of funding. Our data yield the first cogent predictions for future fire incidents and provide scientific insights that could inform and spur evidence‐based policy decisions concerning highly contaminated regions around the world, such as those of Chernobyl.
Published: 2015
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4. Statistical analysis of large simulated yield datasets for studying climate change effects

Author: David Makowski, Senthold Asseng, Frank Ewert, Simona Bassu, Jean-Louis Durand, Pierre Martre, Myriam Adam, Pramod K. Aggarwal, Carlos Angulo, Christian Baron, Bruno Basso, Patrick Bertuzzi, Christian Biernath, Hendrik Boogaard, Kenneth J. Boote, Nadine Brisson, Davide Cammarano, Andrew J. Challinor, Sjakk J. G. Conijn, Marc Corbeels, Delphine Deryng, Giacomo De Sanctis, Jordi Doltra, Sebastian Gayler, Richard Goldberg, Patricio Grassini, Jerry L. Hatfield, Lee Heng, Steven Hoek, Josh Hooker, Tony L. A. Hunt, Joachim Ingwersen, Cesar Izaurralde, Raymond E. E. Jongschaap, James W. Jones, Armen R. Kemanian, Christian Kersebaum, Soo-Hyung Kim, Jon Lizaso, Christoph Müller, Naresh S. Kumar, Claas Nendel, Garry J. O'Leary, Jorgen E. Olesen, Tom M. Osborne, Taru Palosuo, Maria V. Pravia, Eckart Priesack, Dominique Ripoche, Cynthia Rosenzweig, Alexander C. Ruane, Fredirico Sau, Mickhail A. Semenov, Iurii Shcherbak, Pasquale Steduto, Claudio Stöckle, Pierre Stratonovitch, Thilo Streck, Iwan Supit, Fulu Tao, Edmar I. Teixeira, Peter Thorburn, Denis Timlin, Maria Travasso, Reimund Rötter, Katharina Waha, Daniel Wallach, Jeffrey W. White, Jimmy R. Williams, Joost Wolf, Agronomie, Institut National de la Recherche Agronomique (INRA)-AgroParisTech, University of Florida [Gainesville] (UF), Rheinische Friedrich-Wilhelms-Universität Bonn, Unité de Recherche Pluridisciplinaire Prairies et Plantes Fourragères (P3F), Institut National de la Recherche Agronomique (INRA), Génétique Diversité et Ecophysiologie des Céréales (GDEC), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP), Université Blaise Pascal - Clermont-Ferrand 2 (UBP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), Michigan State University [East Lansing], Michigan State University System, Agroclim (AGROCLIM), German Research Center for Environmental Health, Centre for Geo-Information, University of Leeds, International Center for Tropical Agriculture, Wageningen University and Research [Wageningen] (WUR), Chinese Academy of Sciences [Changchun Branch] (CAS), University of East Anglia, Catabrian Agricultural Research and Training Center (CIFA), University of Tübingen, NASA Goddard Institute for Space Studies (GISS), NASA Goddard Space Flight Center (GSFC), University of Nebraska [Lincoln], University of Nebraska System, National Laboratory for Agriculture and Environment, International Atomic Energy Agency [Vienna] (IAEA), University of Reading (UOR), University of Guelph, University of Hohenheim, Joint Global Change Research Institute, Instituto Nacional de Investigación Agropecuaria (INIA), Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research (ZALF), University of Washington, Universidad Politécnica de Madrid (UPM), Potsdam Institute for Climate Impact Research (PIK), Indian Agricultural Research Institute (IARI), Department of Environment and Primary Industries, Landscape and Water Sciences, Aarhus University [Aarhus], Agrifood Research Finland, Pennsylvania State University (Penn State), Penn State System, Rothamsted Research, FAO Sub-regional Office for Eastern Africa [Addis Ababa, Ethiopie] (FAO), Food and Agriculture Organization of the United Nations [Rome, Italie] (FAO), Washington State University (WSU), Plant & Food Research, Ecosystem Sciences, Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), USDA-ARS : Agricultural Research Service, Institute for Climate and Water, AGroécologie, Innovations, teRritoires (AGIR), Institut National de la Recherche Agronomique (INRA)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Arid-Land Agricultural Research Center, Texas A&M University System, Hillel, D., Rosenzweig, C., Institut National de la Recherche Agronomique ( INRA ) -AgroParisTech, University of Florida, University of Bonn (Rheinische Friedrich-Wilhelms), Unité de Recherche Pluridisciplinaire Prairies et Plantes Fourragères ( P3F ), Institut National de la Recherche Agronomique ( INRA ), Génétique Diversité et Ecophysiologie des Céréales ( GDEC ), Université Clermont Auvergne ( UCA ), Université Blaise Pascal (Clermont Ferrand 2) ( UBP ), Centre de Coopération Internationale en Recherche Agronomique pour le Développement, CGIAR Research Program on Climate Change, Agriculture and Food Security ( CCAFS ), Michigan State University, UE Agroclim ( UE AGROCLIM ), Wageningen University and Research Center ( WUR ), Chinese Academy of Sciences [Changchun Branch] ( CAS ), Catabrian Agricultural Research and Training Center ( CIFA ), NASA Goddard Institute for Space Studies ( GISS ), NASA Goddard Space Flight Center ( GSFC ), University of Nebraska Lincoln ( UNL ), International Atomic Energy Agency [Vienna] ( IAEA ), University of Reading ( UOR ), Instituto Nacional de Investigación Agropecuaria, Leibniz Centre for Agricultural Landscape Research, Universidad Politécnica de Madrid ( UPM ), Potsdam Institute for Climate Impact Research ( PIK ), Indian Agricultural Research Institute ( IARI ), Aarhus University, PennState University [Pennsylvania] ( PSU ), Food and Agricultural Organization ( FAO ), Washington State University ( WSU ), New Zealand Institute for Plant and Food Research Limited, Commonwealth Scientific and Industrial Research Organisation, United States Department of Agriculture - Agricultural Research Service, UMR : AGroécologie, Innovations, TeRritoires, Ecole Nationale Supérieure Agronomique de Toulouse, Texas A and M University ( TAMU ), AgroParisTech-Institut National de la Recherche Agronomique (INRA), University of Florida [Gainesville], Génétique Diversité et Ecophysiologie des Céréales - Clermont Auvergne (GDEC), Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne (UCA), Université Blaise Pascal (Clermont Ferrand 2) (UBP), UE Agroclim (UE AGROCLIM), Wageningen University and Research Center (WUR), Food and Agricultural Organization (FAO), Helmholtz Zentrum München = German Research Center for Environmental Health, University of East Anglia [Norwich] (UEA), University of Nebraska–Lincoln, Biotechnology and Biological Sciences Research Council (BBSRC), and Université de Toulouse (UT)-Université de Toulouse (UT)
Subjects: analyse de données, [SDV.SA]Life Sciences [q-bio]/Agricultural sciences, Earth Observation and Environmental Informatics, 010504 meteorology & atmospheric sciences, Yield (finance), data analysis, Climate change, 01 natural sciences, Agro Water- en Biobased Economy, statistical analysis, Effects of global warming, Aardobservatie en omgevingsinformatica, Life Science, Alterra - Centrum Bodem, [ SDV.SA ] Life Sciences [q-bio]/Agricultural sciences, global change, 0105 earth and related environmental sciences, 2. Zero hunger, changement climatique, WIMEK, Mathematical model, analyse statistique, Crop yield, Soil Science Centre, Global change, Statistical model, 04 agricultural and veterinary sciences, 15. Life on land, PE&RC, Climate resilience, Climate Resilience, Plant Production Systems, Klimaatbestendigheid, 13. Climate action, Plantaardige Productiesystemen, Climatology, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Environmental science
Abstract: Many studies have been carried out during the last decade to study the effect of climate change on crop yields and other key crop characteristics. In these studies, one or several crop models were used to simulate crop growth and development for different climate scenarios that correspond to different projections of atmospheric CO2 concentration, temperature, and rainfall changes (Semenov et al., 1996; Tubiello and Ewert, 2002; White et al., 2011). The Agricultural Model Intercomparison and Improvement Project (AgMIP; Rosenzweig et al., 2013) builds on these studies with the goal of using an ensemble of multiple crop models in order to assess effects of climate change scenarios for several crops in contrasting environments. These studies generate large datasets, including thousands of simulated crop yield data. They include series of yield values obtained by combining several crop models with different climate scenarios that are defined by several climatic variables (temperature, CO2, rainfall, etc.). Such datasets potentially provide useful information on the possible effects of different climate change scenarios on crop yields. However, it is sometimes difficult to analyze these datasets and to summarize them in a useful way due to their structural complexity; simulated yield data can differ among contrasting climate scenarios, sites, and crop models. Another issue is that it is not straightforward to extrapolate the results obtained for the scenarios to alternative climate change scenarios not initially included in the simulation protocols. Additional dynamic crop model simulations for new climate change scenarios are an option but this approach is costly, especially when a large number of crop models are used to generate the simulated data, as in AgMIP. Statistical models have been used to analyze responses of measured yield data to climate variables in past studies (Lobell et al., 2011), but the use of a statistical model to analyze yields simulated by complex process-based crop models is a rather new idea. We demonstrate herewith that statistical methods can play an important role in analyzing simulated yield data sets obtained from the ensembles of process-based crop models. Formal statistical analysis is helpful to estimate the effects of different climatic variables on yield, and to describe the between-model variability of these effects.
Published: 2015
Full Text: View/download PDF

5. A statistical analysis of three ensembles of crop model responses to temperature and CO2 concentration

Author: Joost Wolf, Xinyou Yin, Pierre Martre, Zhengtao Zhang, H. K. Soo, Manuel Marcaida, Nadine Brisson, Patrick Bertuzzi, Soo-Hyung Kim, Yan Zhu, Roberto C. Izaurralde, L. A. Hunt, Maria I. Travasso, Christian Baron, James W. Jones, R.E.E. Jongschaap, T. Palosuo, Daniel Wallach, Jerry L. Hatfield, Christian Biernath, G. De Sanctis, Senthold Asseng, H. Yoshida, Donald S. Gaydon, Edmar Teixeira, Davide Cammarano, Alex C. Ruane, C. Nendel, T. Hasegawa, Thilo Streck, Garry O'Leary, Upendra Singh, Frank Ewert, Delphine Deryng, R. Goldberg, Bas A. M. Bouman, Peter J. Thorburn, Tao Li, Roberto Confalonieri, Myriam Adam, Jes Olesen, Reimund P. Rötter, Tamon Fumoto, Patricio Grassini, Joachim Ingwersen, Robert F. Grant, Katharina Waha, James Williams, Fulu Tao, Eckart Priesack, Pramod K. Aggarwal, Liang Tang, Sebastian Gayler, Jordi Doltra, L. Heng, Christoph Müller, J.G. Conijn, Iwan Supit, S. Naresh Kumar, Iurii Shcherbak, Jeffrey W. White, Hendrik Boogaard, Kenneth J. Boote, David Makowski, Federico Sau, Jean-Louis Durand, Mikhail A. Semenov, Claudio O. Stöckle, Marc Corbeels, Steven Hoek, Simone Bregaglio, Hiroshi Nakagawa, Philippe Oriol, Anthony Challinor, R. A. Kemanian, Carlos Angulo, Pasquale Steduto, Bruno Basso, Kurt Christian Kersebaum, Cynthia Rosenzweig, Dennis Timlin, J. Hooker, Samuel Buis, Maria Virginia Pravia, Françoise Ruget, Dominique Ripoche, Simona Bassu, Pierre Stratonovitch, Jon I. Lizaso, Balwinder Singh, Tom M. Osborne, Paul W. Wilkens, Agronomie, Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Department of Agricultural and Biological Engineering [Gainesville] (UF|ABE), Institute of Food and Agricultural Sciences [Gainesville] (UF|IFAS), University of Florida [Gainesville] (UF)-University of Florida [Gainesville] (UF), Institute of Crop Science and Resource Conservation [Bonn] (INRES), Rheinische Friedrich-Wilhelms-Universität Bonn, Unité de Recherche Pluridisciplinaire Prairies et Plantes Fourragères (P3F), Institut National de la Recherche Agronomique (INRA), International Rice Research Institute [Philippines] (IRRI), Consultative Group on International Agricultural Research [CGIAR] (CGIAR), Int Rice Res Inst, Los Banos, Philippines, Université Paris Diderot - Paris 7 (UPD7), Génétique Diversité et Ecophysiologie des Céréales (GDEC), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP), Amélioration génétique et adaptation des plantes méditerranéennes et tropicales (UMR AGAP), Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), International Water Management Institute, Research Program on Climate Change, Agriculture and Food Security, CGIAR, Institute of Crops Science and Resource Conservation INRES, Territoires, Environnement, Télédétection et Information Spatiale (UMR TETIS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Department of Geological Sciences and W. K. Kellogg Biological Station, Michigan State University [East Lansing], Michigan State University System-Michigan State University System, Department of Geological Sciences [East Lansing], Agroclim (AGROCLIM), German Research Center for Environmental Health, Institute of Soil Ecololgy, Helmholtz-Zentrum München (HZM), Center for Geo-information, Alterra, Department of Agronomy, University of Florida [Gainesville] (UF), Cassandra Lab, University of Milan, Environnement Méditerranéen et Modélisation des Agro-Hydrosystèmes (EMMAH), Avignon Université (AU)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), The James Hutton Institute, CGIAR ESSP Program on Climate Change, Agriculture and Food Security, International Center for Tropical Agriculture, School of Earth and Environment [Leeds] (SEE), University of Leeds, Plant Research International, Wageningen University and Research [Wageningen] (WUR), Embrapa Cerrados, Agroécologie et Intensification Durables des cultures annuelles (UPR AIDA), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Tyndall Centre for Climate Change Research, School of Environmental Science, University of East Anglia [Norwich] (UEA), European Commission - Joint Research Centre [Ispra] (JRC), Cantabrian Agricultural Research and Training Centre, Tsukuba, National Institute of Agro-Environmental Sciences (NIAES), Agriculture Flagship, Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), WESS Water and Earth System Science Competence Cluster, Eberhard Karls Universität Tübingen = Eberhard Karls University of Tuebingen, NASA Goddard Institute for Space Studies (GISS), NASA Goddard Space Flight Center (GSFC), Departement of Renewable Resources, University of Alberta, Department of Agronomy and Horticulture, University of Nebraska [Lincoln], University of Nebraska System-University of Nebraska System, National Laboratory for Agriculture and Environment, International Atomic Energy Agency [Vienna] (IAEA), Centre for Geo-Information, Agriculture Department, University of Reading (UOR), Department of Plant Agriculture, University of Guelph, Institute of Soil Science and Land Evaluation, University of Hohenheim, Department of Geographical Sciences, University of Maryland [College Park], University of Maryland System-University of Maryland System, AGroécologie, Innovations, teRritoires (AGIR), Institut National de la Recherche Agronomique (INRA)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Instituto Nacional de Investigación Agropecuaria (INIA), Institute of Landscape System Analysis, Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research (ZALF), College of the Environment, School of Environmental and Forest Sciences, University of Washington, Department Produccion Vegetal, Fitotecnia, Universidad Politécnica de Madrid (UPM), Potsdam Institute for Climate Impact Research (PIK), National Agriculture and Food Research Organization (NARO), Centre for Environment Science and Climate Resilient Agriculture (CESCRA), Indian Agricultural Research Institute (IARI), Institute of Landscape Systems Analysis, Department of Economic Development Jobs, Transport and Resources, Grains Innovation Park, Department of Agroecology, Aarhus University [Aarhus], Walker Institute, NCAS Climate, Natural Resources Institute Finland, Department of Plant Science, Pennsylvania State University (Penn State), Penn State System-Penn State System, German Research Center for Environmental Health, Institute of Soil Ecology, Department Biologia Vegetal, Computational and Systems Biology Department, Rothamsted Research, Department of Geological Sciences and W.K. Kellogg Biological Station, International Maize and Wheat Improvement Centre [Inde] (CIMMYT), International Maize and Wheat Improvement Center (CIMMYT), Consultative Group on International Agricultural Research [CGIAR] (CGIAR)-Consultative Group on International Agricultural Research [CGIAR] (CGIAR), International Fertilizer Development Center (IFDC), College of the Environment, School of Environmental and Forest Science, University of Washington [Seattle], FAO Sub-regional Office for Eastern Africa [Addis Ababa, Ethiopie] (FAO), Food and Agriculture Organization of the United Nations [Rome, Italie] (FAO), Biological Systems Engineering, Washington State University (WSU), Plant Production Systems and Earth System Science, National Engineering and Technology Center for Information Agriculture, Nanjing Agricultural University, Sustainable Production, Plant & Food Research, ARS Crop Systems and Global Change Laboratory, United States Department of Agriculture, CIRN, Institute for Climate and Water, Instituto Nacional de Tecnología Agropecuaria (INTA), Agriculture, Agrosystèmes Cultivés et Herbagers (ARCHE), Institut National de la Recherche Agronomique (INRA)-École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National Polytechnique (Toulouse) (Toulouse INP), Arid-Land Agricultural Research Center, Texas AgriLife Research and Extension, Texas A&M University System, Centre for Crop Systems Analysis, State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University (BNU), Metaprogramme ACCAF, Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Helmholtz Zentrum München = German Research Center for Environmental Health, Università degli Studi di Milano = University of Milan (UNIMI), University of Nebraska–Lincoln, Université de Toulouse (UT)-Université de Toulouse (UT), Natural Resources Institute Finland (LUKE), Biotechnology and Biological Sciences Research Council (BBSRC)-Biotechnology and Biological Sciences Research Council (BBSRC), Nanjing Agricultural University (NAU), Institut National de la Recherche Agronomique (INRA)-École nationale supérieure agronomique de Toulouse (ENSAT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National Polytechnique (Toulouse) (Toulouse INP), AgroParisTech-Institut National de la Recherche Agronomique (INRA), Agricultural and Biological Engineering Department, University of Florida [Gainesville], Institute of Crop Science and Resource Conservation INRES, International Rice Research Institute, Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro), UE Agroclim (UE AGROCLIM), Wageningen University and Research Centre [Wageningen] (WUR), Agroécologie et Intensification Durables des cultures annuelles (Cirad-Persyst-UPR 115 AIDA), Département Performances des systèmes de production et de transformation tropicaux (Cirad-PERSYST), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Eberhard Karls Universität Tübingen, Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA), National Agriculture and Food Research Organization, International Maize and Wheat Improvement Centre (CIMMYT), Food and Agricultural Organization (FAO), New Zealand Institute for Plant and Food Research Limited, Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure Agronomique de Toulouse-Institut National Polytechnique (Toulouse) (Toulouse INP), Beijing Normal University, Institut National de la Recherche Agronomique ( INRA ) -AgroParisTech, University of Bonn (Rheinische Friedrich-Wilhelms), Unité de Recherche Pluridisciplinaire Prairies et Plantes Fourragères ( P3F ), Institut National de la Recherche Agronomique ( INRA ), Génétique Diversité et Ecophysiologie des Céréales ( GDEC ), Institut National de la Recherche Agronomique ( INRA ) -Université Blaise Pascal - Clermont-Ferrand 2 ( UBP ), Amélioration génétique et adaptation des plantes méditerranéennes et tropicales ( UMR AGAP ), Institut national de la recherche agronomique [Montpellier] ( INRA Montpellier ) -Centre international d'études supérieures en sciences agronomiques ( Montpellier SupAgro ) -Centre de Coopération Internationale en Recherche Agronomique pour le Développement ( CIRAD ) -Institut national d’études supérieures agronomiques de Montpellier ( Montpellier SupAgro ), Territoires, Environnement, Télédétection et Information Spatiale ( UMR TETIS ), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture ( IRSTEA ) -AgroParisTech-Centre de Coopération Internationale en Recherche Agronomique pour le Développement ( CIRAD ), Department of Geological Sciences, W.K. Kellogg Biological Station, Michigan State Univ, Dept Geol Sci, E Lansing, MI 48823 USA, UE Agroclim ( UE AGROCLIM ), Helmholtz-Zentrum München ( HZM ), Environnement Méditerranéen et Modélisation des Agro-Hydrosystèmes ( EMMAH ), Université d'Avignon et des Pays de Vaucluse ( UAPV ) -Institut National de la Recherche Agronomique ( INRA ), Invergowrie, School of Earth and Environment [Leeds] ( SEE ), Wageningen University and Research Centre [Wageningen] ( WUR ), Agro-ecologyand Sustainable Intensification of Annual Crops, Centre de Coopération Internationale en Recherche Agronomique pour le Développement ( CIRAD ), University of East Anglia [Norwich] ( UEA ), European Commission - Joint Research Centre [Ispra] ( JRC ), National Institute for Agro-Environmental Sciences, Commonwealth Scientific and Industrial Research Organisation, NASA Goddard Institute for Space Studies ( GISS ), NASA Goddard Space Flight Center ( GSFC ), University of Nebraska-Lincoln, International Atomic Energy Agency [Vienna] ( IAEA ), University of Reading ( UOR ), UMR 1248 Agrosystèmes et Développement Territorial (AGIR), Agro-ecology and Sustainable Intensification of Annual Crops, Instituto Nacional de Investigación Agropecuaria, Leibniz Centre for Agricultural Landscape Research, Universidad Politécnica de Madrid ( UPM ), Potsdam Institute for Climate Impact Research ( PIK ), Centre for Environment Science and Climate Resilient Agriculture ( CESCRA ), Indian Agricultural Research Institute ( IARI ), PennState University [Pennsylvania] ( PSU ), W.K. Kellogg Biological Station, Department of Geological Sciences, International Maize and Wheat Improvement Centre ( CIMMYT ), International Fertilizer Development Center ( IFDC ), Food and Agricultural Organization ( FAO ), Washington State University ( WSU ), Instituto Nacional de Tecnología Agropecuaria, Agrosystèmes Cultivés et Herbagers ( ARCHE ), Institut National Polytechnique [Toulouse] ( INP ) -Institut National de la Recherche Agronomique ( INRA ) -Ecole Nationale Supérieure Agronomique de Toulouse, and Texas A and M University ( TAMU )
Subjects: [SDV.SA]Life Sciences [q-bio]/Agricultural sciences, Atmospheric Science, 010504 meteorology & atmospheric sciences, F62 - Physiologie végétale - Croissance et développement, 01 natural sciences, Statistics, Aardobservatie en omgevingsinformatica, Climate change, Crop model, [ SDV.SA ] Life Sciences [q-bio]/Agricultural sciences, Triticum, Mathematics, 2. Zero hunger, Global and Planetary Change, Mathematical model, Air, Forestry, Regression analysis, 04 agricultural and veterinary sciences, PE&RC, [ SDE.MCG ] Environmental Sciences/Global Changes, Rendement des cultures, Plant Production Systems, Statistical model, Modèle mathématique, Atmosphère, Earth Observation and Environmental Informatics, Yield, Crop Physiology, P40 - Météorologie et climatologie, [SDE.MCG]Environmental Sciences/Global Changes, Oryza sativa, Zea mays, Earth System Science, Emulator, Agro Water- en Biobased Economy, Alterra - Centrum Bodem, Precipitation, Croissance, 0105 earth and related environmental sciences, Meta-model, Changement climatique, Hydrology, Modélisation des cultures, Crop yield, Simulation modeling, Soil Science Centre, 15. Life on land, Température, Laboratorium voor Phytopathologie, Climate Resilience, 13. Climate action, Klimaatbestendigheid, Yield (chemistry), Plantaardige Productiesystemen, Laboratory of Phytopathology, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Leerstoelgroep Aardsysteemkunde, Plante de culture, Agronomy and Crop Science, Dioxyde de carbone
Abstract: Ensembles of process-based crop models are increasingly used to simulate crop growth for scenarios of temperature and/or precipitation changes corresponding to different projections of atmospheric CO2 concentrations. This approach generates large datasets with thousands of simulated crop yield data. Such datasets potentially provide new information but it is difficult to summarize them in a useful way due to their structural complexities. An associated issue is that it is not straightforward to compare crops and to interpolate the results to alternative climate scenarios not initially included in the simulation protocols. Here we demonstrate that statistical models based on random-coefficient regressions are able to emulate ensembles of process-based crop models. An important advantage of the proposed statistical models is that they can interpolate between temperature levels and between CO2 concentration levels, and can thus be used to calculate temperature and [CO2] thresholds leading to yield loss or yield gain, without rerunning the original complex crop models. Our approach is illustrated with three yield datasets simulated by 19 maize models, 26 wheat models, and 13 rice models. Several statistical models are fitted to these datasets, and are then used to analyze the variability of the yield response to [CO2] and temperature. Based on our results, we show that, for wheat, a [CO2] increase is likely to outweigh the negative effect of a temperature increase of +2 degrees C in the considered sites. Compared to wheat, required levels of [CO2] increase are much higher for maize, and intermediate for rice. For all crops, uncertainties in simulating climate change impacts increase more with temperature than with elevated [CO2]. (C) 2015 Elsevier B.V. All rights reserved.
Published: 2015
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6. Sustainable land use in Mountain Regions under global change synthesis across scales and disciplines

Author: Fridolin S. Brand, Ché Elkin, Robert Huber, Andreas Rigling, Willi Zimmermann, Alexandre Buttler, Thomas Spiegelberger, Harald Bugmann, Ariane Walz, Roland W. Scholz, Christian Hirschi, François Gillet, Heike Lischke, Adrienne Grêt-Regamey, Peter Bebi, Simon Briner, Roman Seidl, Swiss Federal Institute for Forest, Snow and Avalanche Research WSL, Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology in Zürich [Zürich] (ETH Zürich), Laboratoire des Systèmes d'Information Géographique [Lausanne] (LASIG), Ecole Polytechnique Fédérale de Lausanne (EPFL), Laboratoire Chrono-environnement - UFC (UMR 6249) (LCE), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Centre National de la Recherche Scientifique (CNRS)-Université de Franche-Comté (UFC), Ecosystèmes montagnards (UR EMGR), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Potsdam Institute for Climate Impact Research (PIK), Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Laboratoire Chrono-environnement - CNRS - UBFC (UMR 6249) (LCE), Centre National de la Recherche Scientifique (CNRS)-Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC), Centre National de la Recherche Scientifique (CNRS)-Université de Franche-Comté (UFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC), Swiss Federal Institute for Forest, Snow and Avalanche Research ( WSL ), Eidgenössische Technische Hochschule [Zürich] ( ETH Zürich ), Laboratoire des Systèmes d'Information Géographique [Lausanne] ( LASIG ), Ecole Polytechnique Fédérale de Lausanne ( EPFL ), Laboratoire Chrono-environnement ( LCE ), Université Bourgogne Franche-Comté ( UBFC ) -Centre National de la Recherche Scientifique ( CNRS ) -Université de Franche-Comté ( UFC ), Ecosystèmes montagnards ( UR EMGR ), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture ( IRSTEA ), and Potsdam Institute for Climate Impact Research ( PIK )
Subjects: 0106 biological sciences, adaptive management, Institut für Erd- und Umweltwissenschaften, 010504 meteorology & atmospheric sciences, Process (engineering), QH301-705.5, ADAPTATIVE MANAGEMENT, Vulnerability, GESTION ADAPTATIVE, 01 natural sciences, 12. Responsible consumption, [ SDE ] Environmental Sciences, land-use change, Goods and services, 11. Sustainability, Biology (General), Socioeconomic status, Spatial planning, QH540-549.5, 0105 earth and related environmental sciences, Land use, Ecology, AMENAGEMENT DU TERRITOIRE, business.industry, ECOSYSTEM SERVICE, Environmental resource management, Capacity building, transdisciplinary research, Global change, ALPES SUISSES, modeling, experiments, 15. Life on land, 010601 ecology, Geography, climate change, 13. Climate action, CHANGEMENT CLIMATIQUE, [SDE]Environmental Sciences, interdisciplinary research, SERVICE ECOSYSTEMIQUE, business, ecosystem services, ZONE DE MONTAGNE, LAND USE CHANGE
Abstract: Mountain regions provide essential ecosystem goods and services (EGS) for both mountain dwellers and people living outside these areas. Global change endangers the capacity of mountain ecosystems to provide key services. The Mountland project focused on three case study regions in the Swiss Alps and aimed to propose land-use practices and alternative policy solutions to ensure the provision of key EGS under climate and land-use changes. We summarized and synthesized the results of the project and provide insights into the ecological, socioeconomic, and political processes relevant for analyzing global change impacts on a European mountain region. In Mountland, an integrative approach was applied, combining methods from economics and the political and natural sciences to analyze ecosystem functioning from a holistic human-environment system perspective. In general, surveys, experiments, and model results revealed that climate and socioeconomic changes are likely to increase the vulnerability of the EGS analyzed. We regard the following key characteristics of coupled human-environment systems as central to our case study areas in mountain regions: thresholds, heterogeneity, trade-offs, and feedback. Our results suggest that the institutional framework should be strengthened in a way that better addresses these characteristics, allowing for (1) more integrative approaches, (2) a more network-oriented management and steering of political processes that integrate local stakeholders, and (3) enhanced capacity building to decrease the identified vulnerability as central elements in the policy process. Further, to maintain and support the future provision of EGS in mountain regions, policy making should also focus on project-oriented, cross-sectoral policies and spatial planning as a coordination instrument for land use in general.
Published: 2013
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7. Uncertainty in simulating wheat yields under climate change

Author: J. Hooker, Pramod K. Aggarwal, Joost Wolf, Pierre Martre, Iurii Shcherbak, L. A. Hunt, Kenneth J. Boote, L. Heng, James W. Jones, Jerry L. Hatfield, Katharina Waha, Christian Biernath, Iwan Supit, Eckart Priesack, Pasquale Steduto, S. Naresh Kumar, Davide Cammarano, Joachim Ingwersen, Kurt Christian Kersebaum, Fulu Tao, Christoph Müller, Jordi Doltra, Thilo Streck, Senthold Asseng, Alex C. Ruane, Jeffrey W. White, Roberto C. Izaurralde, Tom M. Osborne, Patrick Bertuzzi, Sebastian Gayler, Andrew J. Challinor, Taru Palosuo, Reimund P. Rötter, Jørgen E. Olesen, Peter J. Thorburn, Nadine Brisson, Mikhail A. Semenov, Claudio O. Stöckle, Maria I. Travasso, Daniel Wallach, James Williams, Garry O'Leary, Cynthia Rosenzweig, Carlos Angulo, Bruno Basso, R. Goldberg, Robert F. Grant, Frank Ewert, Dominique Ripoche, Pierre Stratonovitch, Claas Nendel, Agricultural and Biological Engineering Department, University of Florida [Gainesville], Institut für Nutzpflanzenwissenschaften und Ressourcenschutz (INRES), Rheinische Friedrich-Wilhelms-Universität Bonn, NASA Goddard Institute for Space Studies (GISS), NASA Goddard Space Flight Center (GSFC), National Laboratory for Agriculture and Environment, Department of Agronomy, Ecosystem Sciences, Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), Plant Production Research, Agrifood Research Finland, Agronomie, AgroParisTech-Institut National de la Recherche Agronomique (INRA), Department of Geological Sciences and W. K. Kellogg Biological Station, Michigan State University [East Lansing], Michigan State University System-Michigan State University System, Génétique Diversité et Ecophysiologie des Céréales (GDEC), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP), CCAFS, IWMI, NASC Complex, DPS Marg, UE Agroclim (UE AGROCLIM), Institut National de la Recherche Agronomique (INRA), Institute of Soil Ecology, Helmholtz-Zentrum München (HZM), Institute for Climate and Atmospheric Science [Leeds] (ICAS), School of Earth and Environment [Leeds] (SEE), University of Leeds-University of Leeds, CGIAR-ESSP Program on Climate Change, Agriculture and Food Security, International Center for Tropical Agriculture, Centro de Investigaciòn y Formenta Agrario (CIFA), WESS-Water and Earth System Science Competence Cluster, Eberhard Karls Universität Tübingen, Department of Renewable Resources, University of Alberta, International Atomic Energy Agency [Vienna] (IAEA), Agriculture Department, University of Reading (UOR), Department of Plant Agriculture, University of Guelph, nstitute of Soil Science and Land Evaluation, University of Hohenheim, Joint Global Change Research Institute, University of Maryland [College Park], University of Maryland System-University of Maryland System, Institute of Landscape Systems Analysis, Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research (ZALF), Potsdam Institute for Climate Impact Research (PIK), Centre for Environment Science and Climate Resilient Agriculture (CESCRA), Indian Agricultural Research Institute (IARI), Landscape and Water Sciences, Department of Primary Industries, Department of Agroecology, Aarhus University [Aarhus], NCAS-Climate, Walker Institute, Computational and Systems Biology Department, Rothamsted Research, Food and Agriculture Organization, Biological Systems Engineering, Washington State University (WSU), Institute of Soil Science and Land Evaluation, Plant Production Systems and Earth System Science-Climate Change, Wageningen University and Research Centre [Wageningen] (WUR), Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences [Beijing] (CAS), Institute for Climate and Water, Instituto Nacional de Tecnología Agropecuaria (INTA), Agrosystèmes Cultivés et Herbagers (ARCHE), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure Agronomique de Toulouse-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Arid-Land Agricultural Research Center, Texas A&M University System, Department of Agricultural and Biological Engineering [Gainesville] (UF|ABE), Institute of Food and Agricultural Sciences [Gainesville] (UF|IFAS), University of Florida [Gainesville] (UF)-University of Florida [Gainesville] (UF), University of Florida [Gainesville] (UF), Agroclim (AGROCLIM), Eberhard Karls Universität Tübingen = Eberhard Karls University of Tuebingen, Wageningen University and Research [Wageningen] (WUR), Institut National de la Recherche Agronomique (INRA)-École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National Polytechnique (Toulouse) (Toulouse INP), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Institut für Nutzpflanzenwissenschaften und Ressourcenschutz ( INRES ), University of Bonn (Rheinische Friedrich-Wilhelms), NASA Goddard Institute for Space Studies ( GISS ), NASA Goddard Space Flight Center ( GSFC ), Commonwealth Scientific and Industrial Research Organisation, Institut National de la Recherche Agronomique ( INRA ) -AgroParisTech, Génétique Diversité et Ecophysiologie des Céréales ( GDEC ), Institut National de la Recherche Agronomique ( INRA ) -Université Blaise Pascal - Clermont-Ferrand 2 ( UBP ), UE Agroclim ( UE AGROCLIM ), Institut National de la Recherche Agronomique ( INRA ), Helmholtz-Zentrum München ( HZM ), Institute for Climate and Atmospheric Science [Leeds] ( ICAS ), University of Leeds, Centro de Investigaciòn y Formenta Agrario ( CIFA ), University of Alberta [Edmonton], International Atomic Energy Agency [Vienna] ( IAEA ), University of Reading ( UOR ), Leibniz Centre for Agricultural Landscape Research, Potsdam Institute for Climate Impact Research ( PIK ), Centre for Environment Science and Climate Resilient Agriculture ( CESCRA ), Indian Agricultural Research Institute ( IARI ), Washington State University ( WSU ), Wageningen University and Research Centre [Wageningen] ( WUR ), Chinese Academy of Sciences [Beijing] ( CAS ), Instituto Nacional de Tecnología Agropecuaria, Agrosystèmes Cultivés et Herbagers ( ARCHE ), Institut National Polytechnique [Toulouse] ( INP ) -Institut National de la Recherche Agronomique ( INRA ) -Ecole Nationale Supérieure Agronomique de Toulouse, Texas A and M University ( TAMU ), Helmholtz Zentrum München = German Research Center for Environmental Health, Biotechnology and Biological Sciences Research Council (BBSRC)-Biotechnology and Biological Sciences Research Council (BBSRC), Institute of geographical sciences and natural resources research [CAS] (IGSNRR), Institut National de la Recherche Agronomique (INRA)-École nationale supérieure agronomique de Toulouse (ENSAT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National Polytechnique (Toulouse) (Toulouse INP), and Université de Toulouse (UT)-Université de Toulouse (UT)
Subjects: 010504 meteorology & atmospheric sciences, [SDV]Life Sciences [q-bio], Climate change, projection, crop production, adaptation, Environmental Science (miscellaneous), 01 natural sciences, Greenhouse effect, Uncertainty analysis, 0105 earth and related environmental sciences, 2. Zero hunger, model, [ SDV ] Life Sciences [q-bio], food, Simulation modeling, ensemble, temperature, 04 agricultural and veterinary sciences, 15. Life on land, Transient climate simulation, scenario, 13. Climate action, Greenhouse gas, Climatology, 040103 agronomy & agriculture, impact, 0401 agriculture, forestry, and fisheries, Environmental science, co2, Climate model, Crop simulation model, Social Sciences (miscellaneous)
Abstract: Projections of climate change impacts on crop yields are inherently uncertain1. Uncertainty is often quantified when projecting future greenhouse gas emissions and their influence on climate2. However, multi-model uncertainty analysis of crop responses to climate change is rare because systematic and objective comparisons among process-based crop simulation models1, 3 are difficult4. Here we present the largest standardized model intercomparison for climate change impacts so far. We found that individual crop models are able to simulate measured wheat grain yields accurately under a range of environments, particularly if the input information is sufficient. However, simulated climate change impacts vary across models owing to differences in model structures and parameter values. A greater proportion of the uncertainty in climate change impact projections was due to variations among crop models than to variations among downscaled general circulation models. Uncertainties in simulated impacts increased with CO2 concentrations and associated warming. These impact uncertainties can be reduced by improving temperature and CO2 relationships in models and better quantified through use of multi-model ensembles. Less uncertainty in describing how climate change may affect agricultural productivity will aid adaptation strategy development andpolicymaking. Projections of climate change impacts on crop yields are inherently uncertain1. Uncertainty is often quantified when projecting future greenhouse gas emissions and their influence on climate2. However, multi-model uncertainty analysis of crop responses to climate change is rare because systematic and objective comparisons among process-based crop simulation models1, 3 are difficult4. Here we present the largest standardized model intercomparison for climate change impacts so far. We found that individual crop models are able to simulate measured wheat grain yields accurately under a range of environments, particularly if the input information is sufficient. However, simulated climate change impacts vary across models owing to differences in model structures and parameter values. A greater proportion of the uncertainty in climate change impact projections was due to variations among crop models than to variations among downscaled general circulation models. Uncertainties in simulated impacts increased with CO2 concentrations and associated warming. These impact uncertainties can be reduced by improving temperature and CO2 relationships in models and better quantified through use of multi-model ensembles. Less uncertainty in describing how climate change may affect agricultural productivity will aid adaptation strategy development and policymaking.
Published: 2013
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8. Predicting pan-tropical climate change induced forest stock gains and losses—implications for REDD

Author: Marlies Gumpenberger, Kirsten Macey, Wolfgang Cramer, Ursula Heyder, Katrin Vohland, Alexander Popp, Benjamin Poulter, Anja Rammig, Institute on Ecosystems and Department of Ecology [Bozeman], Montana State University (MSU), Potsdam Institute for Climate Impact Research (PIK), Institute for Computational Mechanics, Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne] (TUM), Institut méditerranéen de biodiversité et d'écologie marine et continentale (IMBE), Avignon Université (AU)-Aix Marseille Université (AMU)-Institut de recherche pour le développement [IRD] : UMR237-Centre National de la Recherche Scientifique (CNRS), Montana State University ( MSU ), Potsdam Institute for Climate Impact Research ( PIK ), Technische Universität München [München] ( TUM ), Institut méditerranéen de biodiversité et d'écologie marine et continentale ( IMBE ), and Centre National de la Recherche Scientifique ( CNRS ) -Institut de recherche pour le développement [IRD] : UMR237-Aix Marseille Université ( AMU ) -Université d'Avignon et des Pays de Vaucluse ( UAPV )
Subjects: [ SDE.BE ] Environmental Sciences/Biodiversity and Ecology, 010504 meteorology & atmospheric sciences, Renewable Energy, Sustainability and the Environment, Natural resource economics, Public Health, Environmental and Occupational Health, Climate change, 15. Life on land, 010501 environmental sciences, Carbon sequestration, 01 natural sciences, Biosequestration, 13. Climate action, United Nations Framework Convention on Climate Change, Climatology, Greenhouse gas, 11. Sustainability, Tropical climate, Climate change scenario, Environmental science, Land use, land-use change and forestry, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, General Environmental Science
Abstract: Deforestation is a major threat to tropical forests worldwide, contributing up to one-fifth of global carbon emissions into the atmosphere. Despite protection efforts, deforestation of tropical forests has continued in recent years. Providing incentives to reducing deforestation has been proposed in the United Nations Framework Convention on Climate Change (UNFCCC) Bali negotiations in 2007 to decelerate emissions from deforestation (REDD—reduced emissions from deforestation and forest degradation). A number of methodological issues such as ensuring permanence, establishing reference emissions levels that do not reward business-as-usual and having a measuring, reporting and verification system in place are essential elements in implementing successful REDD schemes. To assess the combined impacts of climate and land-use change on tropical forest carbon stocks in the 21st century, we use a dynamic global vegetation model (LPJ DGVM) driven by five different climate change projections under a given greenhouse gas emission scenario (SRES A2) and two contrasting land-use change scenarios. We find that even under a complete stop of deforestation after the period of the Kyoto Protocol (post-2012) some countries may continue to lose carbon stocks due to climate change. Especially at risk is tropical Latin America, although the presence and magnitude of the risk depends on the climate change scenario. By contrast, strong protection of forests could increase carbon uptake in many tropical countries, due to CO2 fertilization effects, even under altered climate regimes.
Published: 2010
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9. Tackling unresolved questions in forest ecology: The past and future role of simulation models

Author: Alessio Collalti, Kirsten Thonicke, Fanny Langerwisch, Friedrich J. Bohn, Manfred J. Lexer, Xavier Morin, Edna Rödig, Heike Lischke, Franziska Taubert, Isabelle Maréchaux, Martin Gutsch, Giorgio Vacchiano, Boris Sakschewski, Anja Rammig, Christopher P. O. Reyer, Harald Bugmann, Andreas Huth, Rupert Seidl, Mateus Dantas de Paula, Rico Fischer, Botanique et Modélisation de l'Architecture des Plantes et des Végétations (UMR AMAP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Palacky University Olomouc, Osnabrück University, Helmholtz Zentrum für Umweltforschung = Helmholtz Centre for Environmental Research (UFZ), German Centre for Integrative Biodiversity Research (iDiv), Institute of Terrestrial Ecosystems (ITES), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Université Paul-Valéry - Montpellier 3 (UPVM)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Potsdam Institute for Climate Impact Research (PIK), University of Natural Resources and Life Sciences (BOKU), University of Tuscia, Senckenberg Biodiversity and Climate Research Centre (SBiK-F), Goethe-Universität Frankfurt am Main-Senckenberg – Leibniz Institution for Biodiversity and Earth System Research - Senckenberg Gesellschaft für Naturforschung, Leibniz Association-Leibniz Association, Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Technical University of Munich (TUM), Università degli Studi di Milano [Milano] (UNIMI), COST Action FP1304 PROFOUND, German Federal Ministry of Science and Education. Grant Number: 01LS1711A, Austrian Science Fund. Grant Number: Y895‐B25, ANR-10-LABX-0025,CEBA,CEnter of the study of Biodiversity in Amazonia(2010), Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne] (TUM), Universität Osnabrück - Osnabrück University, Université Paul-Valéry - Montpellier 3 (UPVM)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Universität für Bodenkultur Wien = University of Natural Resources and Life [Vienne, Autriche] (BOKU), Università degli studi della Tuscia [Viterbo], Università degli Studi di Milano = University of Milan (UNIMI), and Lehrstuhl für Ökosystemdynamik und Waldmanagement in Gebirgslandschaften
Subjects: 0106 biological sciences, Reviews, Context (language use), Review, [SDV.BID.SPT]Life Sciences [q-bio]/Biodiversity/Systematics, Phylogenetics and taxonomy, 010603 evolutionary biology, 01 natural sciences, Dynamic global vegetation model, 03 medical and health sciences, [SDV.EE.ECO]Life Sciences [q-bio]/Ecology, environment/Ecosystems, Forest ecology, ddc:630, Ecology, Evolution, Behavior and Systematics, QH540-549.5, 030304 developmental biology, Nature and Landscape Conservation, Pace, Gap model, 0303 health sciences, Forest dynamics, Ecology, business.industry, Forest modelling, Simulation modeling, Environmental resource management, Species distribution model, Vegetation, 15. Life on land, [SDV.BV.BOT]Life Sciences [q-bio]/Vegetal Biology/Botanics, ddc, Geography, 13. Climate action, Complementarity (molecular biology), [SDE.BE]Environmental Sciences/Biodiversity and Ecology, business
Abstract: Understanding the processes that shape forest functioning, structure, and diversity remains challenging, although data on forest systems are being collected at a rapid pace and across scales. Forest models have a long history in bridging data with ecological knowledge and can simulate forest dynamics over spatio‐temporal scales unreachable by most empirical investigations.We describe the development that different forest modelling communities have followed to underpin the leverage that simulation models offer for advancing our understanding of forest ecosystems.Using three widely applied but contrasting approaches – species distribution models, individual‐based forest models, and dynamic global vegetation models – as examples, we show how scientific and technical advances have led models to transgress their initial objectives and limitations. We provide an overview of recent model applications on current important ecological topics and pinpoint ten key questions that could, and should, be tackled with forest models in the next decade.Synthesis. This overview shows that forest models, due to their complementarity and mutual enrichment, represent an invaluable toolkit to address a wide range of fundamental and applied ecological questions, hence fostering a deeper understanding of forest dynamics in the context of global change., Forest models can help understanding the processes that shape forest functioning, structure and diversity, since they can can simulate forest dynamics over spatio‐temporal scales unreachable by most empirical investigations. Here we describe the development of three widely applied but contrasting forest mo−delling approaches — species distribution models, individual‐based models and dynamic global vegetation models. We provide an overview of recent model applications and pinpoint ten key questions that could, and should, be tackled with forest models in the next decade.
Published: 2021
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10. Narrowing uncertainties in the effects of elevated CO2 on crops

Author: Kenneth J. Boote, Franz Badeck, Thomas A. M. Pugh, Andrej Ceglar, Gerard W. Wall, Remi Lecerf, Raúl López-Lozano, Matteo Zampieri, Andrea Toreti, Håkan Pleijel, Jean-Louis Durand, Frank Dentener, Remy Manderscheid, Francesco N. Tubiello, Gerald Moser, Christoph Müller, Bruce A. Kimball, Senthold Asseng, Erik Mencos Contreras, Garry O'Leary, Xuhui Wang, Eline Vanuytrecht, Cynthia Rosenzweig, Delphine Deryng, Stefano Galmarini, Heidi Webber, Maurits van den Berg, Petra Hoegy, European Commission - Joint Research Centre [Ispra] (JRC), NewClimate Institute, IRI THESys, Humboldt State University (HSU), Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research (ZALF), Food and Agriculture Organization of the United Nations [Rome, Italie] (FAO), Potsdam Institute for Climate Impact Research (PIK), USDA Agricultural Research Service [Maricopa, AZ] (USDA), United States Department of Agriculture (USDA), Justus-Liebig-Universität Gießen (JLU), University of Florida [Gainesville] (UF), University of Birmingham [Birmingham], Lund University [Lund], Flemish Institute for Technological Research (VITO), Catholic University of Leuven - Katholieke Universiteit Leuven (KU Leuven), University of Gothenburg (GU), Unité de Recherche Pluridisciplinaire Prairies et Plantes Fourragères (P3F), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University [Beijing], Consiglio per la Ricerca in Agricoltura e l’analisi dell’economia agraria (CREA), University of Hohenheim, Environnement Méditerranéen et Modélisation des Agro-Hydrosystèmes (EMMAH), Avignon Université (AU)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Agriculture Victoria (AgriBio), Thünen Institute of Biodiversity, NASA Goddard Institute for Space Studies (GISS), NASA Goddard Space Flight Center (GSFC), Center for Climate Systems Research [New York] (CCSR), Columbia University [New York], Justus-Liebig-Universität Gießen = Justus Liebig University (JLU), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), and Consiglio per la Ricerca in Agricoltura e l’analisi dell’economia agraria = Council for Agricultural Research and Economics (CREA)
Subjects: 0106 biological sciences, CARBON-DIOXIDE ENRICHMENT, PROTEIN-CONCENTRATION, 010504 meteorology & atmospheric sciences, Natural resource economics, Climate change, Nutritional quality, 01 natural sciences, Crop, WHEAT-GRAIN QUALITY, FUTURE CO2, USE EFFICIENCY, Sustainable agriculture, Precipitation, ATMOSPHERIC CO2, Agricultural productivity, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, 0105 earth and related environmental sciences, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, 2. Zero hunger, Carbon dioxide in Earth's atmosphere, Science & Technology, FACE EXPERIMENT, business.industry, FOOD SECURITY, fungi, food and beverages, 15. Life on land, CLIMATE-CHANGE IMPACT, MODEL, 13. Climate action, Agriculture, Food Science & Technology, Environmental science, Animal Science and Zoology, business, Life Sciences & Biomedicine, Agronomy and Crop Science, 010606 plant biology & botany, Food Science
Abstract: International audience; Plant responses to rising atmospheric carbon dioxide (CO2) concentrations, together with projected variations in temperature and precipitation will determine future agricultural production. Estimates of the impacts of climate change on agriculture provide essential information to design effective adaptation strategies, and develop sustainable food systems. Here, we review the current experimental evidence and crop models on the effects of elevated CO2 concentrations. Recent concerted efforts have narrowed the uncertainties in CO2-induced crop responses so that climate change impact simulations omitting CO2 can now be eliminated. To address remaining knowledge gaps and uncertainties in estimating the effects of elevated CO2 and climate change on crops, future research should expand experiments on more crop species under a wider range of growing conditions, improve the representation of responses to climate extremes in crop models, and simulate additional crop physiological processes related to nutritional quality.Understanding of the effects of elevated CO2 on crops has improved sufficiently that modelling future climatic effects on agriculture should eliminate 'no CO2' simulations. Further advancement in the estimation of the effects can be realized by studying a wider variety of crop species under a wider range of growing conditions, improving the representation of responses to climate extremes in crop models and simulating additional crop physiological processes related to nutritional quality.
Published: 2020
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11. Report on ICDP Deep Dust workshops: probing continental climate of the late Paleozoic icehouse–greenhouse transition and beyond

Author: Cindy V. Looy, Lily S. Pfeifer, Linda A. Hinnov, Kathleen C. Benison, Nicholas G. Heavens, Stéphane Pochat, Gerilyn S. Soreghan, Mehrdad Sardar Abadi, James J. Zambito, Georg Feulner, Sylvie Bourquin, Adam K. Huttenlocker, Natsuko Hamamura, Michael A. Hamilton, Laurent Beccaletto, University of Oklahoma (OU), Bureau de Recherches Géologiques et Minières (BRGM) (BRGM), West Virginia University [Morgantown], Géosciences Rennes (GR), Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES), Potsdam Institute for Climate Impact Research (PIK), Kyushu University [Fukuoka], University of Toronto, Space Science Institute [Boulder] (SSI), George Mason University [Fairfax], University of Southern California (USC), University of California [Berkeley], University of California, Laboratoire de Planétologie et Géodynamique [UMR 6112] (LPG), Université d'Angers (UA)-Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST), Université de Nantes (UN)-Université de Nantes (UN)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Beloit College, Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR), Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS), Kyushu University, University of California [Berkeley] (UC Berkeley), and University of California (UC)
Subjects: Pangaea, 010504 meteorology & atmospheric sciences, Paleozoic, Permian, Mechanical Engineering, Earth science, lcsh:QE1-996.5, Energy Engineering and Power Technology, Biosphere, 15. Life on land, 010502 geochemistry & geophysics, 01 natural sciences, lcsh:Geology, Earth system science, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, 13. Climate action, [SDU.STU.ST]Sciences of the Universe [physics]/Earth Sciences/Stratigraphy, Paleoclimatology, Period (geology), Paleoecology, Geology, 0105 earth and related environmental sciences
Abstract: Chamberlin and Salisbury's assessment of the Permian a century ago captured the essence of the period: it is an interval of extremes yet one sufficiently recent to have affected a biosphere with near-modern complexity. The events of the Permian – the orogenic episodes, massive biospheric turnovers, both icehouse and greenhouse antitheses, and Mars-analog lithofacies – boggle the imagination and present us with great opportunities to explore Earth system behavior. The ICDP-funded workshops dubbed “Deep Dust,” held in Oklahoma (USA) in March 2019 (67 participants from nine countries) and Paris (France) in January 2020 (33 participants from eight countries), focused on clarifying the scientific drivers and key sites for coring continuous sections of Permian continental (loess, lacustrine, and associated) strata that preserve high-resolution records. Combined, the two workshops hosted a total of 91 participants representing 14 countries, with broad expertise. Discussions at Deep Dust 1.0 (USA) focused on the primary research questions of paleoclimate, paleoenvironments, and paleoecology of icehouse collapse and the run-up to the Great Dying and both the modern and Permian deep microbial biosphere. Auxiliary science topics included tectonics, induced seismicity, geothermal energy, and planetary science. Deep Dust 1.0 also addressed site selection as well as scientific approaches, logistical challenges, and broader impacts and included a mid-workshop field trip to view the Permian of Oklahoma. Deep Dust 2.0 focused specifically on honing the European target. The Anadarko Basin (Oklahoma) and Paris Basin (France) represent the most promising initial targets to capture complete or near-complete stratigraphic coverage through continental successions that serve as reference points for western and eastern equatorial Pangaea.
Published: 2020
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12. Understanding the uncertainty in global forest carbon turnover

Author: T. A. M. Pugh, T. Rademacher, S. L. Shafer, J. Steinkamp, J. Barichivich, B. Beckage, V. Haverd, A. Harper, J. Heinke, K. Nishina, A. Rammig, H. Sato, A. Arneth, S. Hantson, T. Hickler, M. Kautz, B. Quesada, B. Smith, K. Thonicke, School of Geography, Earth and Environmental Sciences [Birmingham], University of Birmingham [Birmingham], Birmingham Institute of Forest Research (BIFoR), Department of Organismic and Evolutionary Biology [Cambridge] (OEB), Harvard University [Cambridge], School of Informatics, Computing, and Cyber Systems (SICCS), Northern Arizona University [Flagstaff], Center for Ecosystem Science and Society (ECOSS), Geosciences and Environmental Climate Change Science Center, United States Geological Survey [Reston] (USGS), Senckenberg Biodiversity and Climate Research Centre (SBiK-F), Goethe-Universität Frankfurt am Main-Senckenberg – Leibniz Institution for Biodiversity and Earth System Research - Senckenberg Gesellschaft für Naturforschung, Leibniz Association-Leibniz Association, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Universidad Austral de Chile, University of Vermont [Burlington], CSIRO Oceans and Atmosphere, CISRO Oceans and Atmosphere, College of Engineering, Mathematics and Physical Sciences [Exeter] (EMPS), University of Exeter, Potsdam Institute for Climate Impact Research (PIK), National Institute for Environmental Studies (NIES), Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne] (TUM), Japan Agency for Marine-Earth Science and Technology (JAMSTEC), DEPARTMENT OF EARTH SYSTEM SCIENCES UNIVERSITY OF CALIFORNIA IRVINE CA USA, Partenaires IRSTEA, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Forest Research Institute Baden-Württemberg - Forstliche Versuchs- und Forschungsanstalt Baden-Württemberg, Universidad del Rosario [Bogota], DEPARTMENT OF PHYSICAL GEOGRAPHY AND ECOSYSTEM SCIENCE LUND UNIVERSITY SWE, Western Sydney University, Seventh Framework Programme, FP7: 50 603542 European Research Council, ERC: 758873 Centre National de la Recherche Scientifique, CNRS Svenska ForskningsrÃ¥det Formas: 211-2009-1682 Helmholtz Association Centre National de la Recherche Scientifique, CNRS, Financial support. This research has been supported by the Euro, pean Commission, European Research Council (TreeMort – grant no. 758873), Seventh Framework Programme (LUC4C – grant no. 50 603542), the Svenska Forskningsrådet Formas (Dnr. 211-2009-1682 and the strategic research areas BECC and MERGE), the Helmholtz Association ATMO programme, the Centre National de la Recherche Scientifique (CNRS) of France through the programme 'Make Our Planet Great Again', the U.S. Geological Survey Land Change Science Program, and the Helmholtz Alliance 'Remote Sensing and Earth System Dynamics'., Harvard University, and Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)
Subjects: 0106 biological sciences, 010504 meteorology & atmospheric sciences, Environmental change, lcsh:Life, 01 natural sciences, Carbon cycle, lcsh:QH540-549.5, ddc:550, Baseline (configuration management), Ecology, Evolution, Behavior and Systematics, 0105 earth and related environmental sciences, Earth-Surface Processes, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Biomass (ecology), lcsh:QE1-996.5, Biosphere, Soil carbon, 15. Life on land, Plant functional type, lcsh:Geology, Earth sciences, lcsh:QH501-531, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, 13. Climate action, Turnover, lcsh:Ecology, Physical geography, 010606 plant biology & botany
Abstract: The length of time that carbon remains in forest biomass is one of the largest uncertainties in the global carbon cycle, with both recent historical baselines and future responses to environmental change poorly constrained by available observations. In the absence of large-scale observations, models used for global assessments tend to fall back on simplified assumptions of the turnover rates of biomass and soil carbon pools. In this study, the biomass carbon turnover times calculated by an ensemble of contemporary terrestrial biosphere models (TBMs) are analysed to assess their current capability to accurately estimate biomass carbon turnover times in forests and how these times are anticipated to change in the future. Modelled baseline 1985–2014 global average forest biomass turnover times vary from 12.2 to 23.5 years between TBMs. TBM differences in phenological processes, which control allocation to, and turnover rate of, leaves and fine roots, are as important as tree mortality with regard to explaining the variation in total turnover among TBMs. The different governing mechanisms exhibited by each TBM result in a wide range of plausible turnover time projections for the end of the century. Based on these simulations, it is not possible to draw robust conclusions regarding likely future changes in turnover time, and thus biomass change, for different regions. Both spatial and temporal uncertainty in turnover time are strongly linked to model assumptions concerning plant functional type distributions and their controls. Thirteen model-based hypotheses of controls on turnover time are identified, along with recommendations for pragmatic steps to test them using existing and novel observations. Efforts to resolve uncertainty in turnover time, and thus its impacts on the future evolution of biomass carbon stocks across the world's forests, will need to address both mortality and establishment components of forest demography, as well as allocation of carbon to woody versus non-woody biomass growth.
Published: 2020
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13. The PROFOUND Database for evaluating vegetation models and simulating climate impacts on European forests

Author: C. P. O. Reyer, R. Silveyra Gonzalez, K. Dolos, F. Hartig, Y. Hauf, M. Noack, P. Lasch-Born, T. Rötzer, H. Pretzsch, H. Meesenburg, S. Fleck, M. Wagner, A. Bolte, T. G. M. Sanders, P. Kolari, A. Mäkelä, T. Vesala, I. Mammarella, J. Pumpanen, A. Collalti, C. Trotta, G. Matteucci, E. D'Andrea, L. Foltýnová, J. Krejza, A. Ibrom, K. Pilegaard, D. Loustau, J.-M. Bonnefond, P. Berbigier, D. Picart, S. Lafont, M. Dietze, D. Cameron, M. Vieno, H. Tian, A. Palacios-Orueta, V. Cicuendez, L. Recuero, K. Wiese, M. Büchner, S. Lange, J. Volkholz, H. Kim, J. A. Horemans, F. Bohn, J. Steinkamp, A. Chikalanov, G. P. Weedon, J. Sheffield, F. Babst, I. Vega del Valle, F. Suckow, S. Martel, M. Mahnken, M. Gutsch, K. Frieler, Potsdam Institute for Climate Impact Research (PIK), Karlsruhe Institute of Technology (KIT), University of Regensburg, Fachagentur Nachwachsende Rohstoffe, Partenaires INRAE, Technical University of Munich (TUM), Northwest German Forest Research Station, Thünen Institute, University of Helsinki, University of Eastern Finland, Istituto per i Sistemi Agricoli e Forestali del Mediterraneo (ISAFOM), Consiglio Nazionale delle Ricerche [Roma] (CNR), Università degli studi della Tuscia [Viterbo], Institute for agriculture and forestry systems in the Mediterranean (CNR-ISAFOM), Global Change Research Institute CAS, Biosystems Division [Roskilde], Risø National Laboratory for Sustainable Energy (Risø DTU), Technical University of Denmark [Lyngby] (DTU)-Technical University of Denmark [Lyngby] (DTU), Interactions Sol Plante Atmosphère (UMR ISPA), Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Boston University [Boston] (BU), Centre for Ecology and Hydrology [Wallingford] (CEH), Natural Environment Research Council (NERC), Centre for Ecology and Hydrology, Auburn University (AU), Universidad Politécnica de Madrid (UPM), Korea Advanced Institute of Science and Technology (KAIST), University of Antwerp (UA), Helmholtz Zentrum für Umweltforschung = Helmholtz Centre for Environmental Research (UFZ), Senckenberg Biodiversity and Climate Research Centre (SBiK-F), Goethe-Universität Frankfurt am Main-Senckenberg – Leibniz Institution for Biodiversity and Earth System Research - Senckenberg Gesellschaft für Naturforschung, Leibniz Association-Leibniz Association, University of Library Study and Information Technology, Met Office Hadley Centre for Climate Change (MOHC), United Kingdom Met Office [Exeter], Princeton University, Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Micrometeorology and biogeochemical cycles, INAR Physics, Ecosystem processes (INAR Forest Sciences), Institute for Atmospheric and Earth System Research (INAR), Department of Forest Sciences, Viikki Plant Science Centre (ViPS), Forest Modelling Group, and Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne] (TUM)
Subjects: 0106 biological sciences, SILVICULTURAL ALTERNATIVES, 010504 meteorology & atmospheric sciences, BIAS CORRECTION, Flat file database, Relational database, Geography & travel, Climate Change, Eddy covariance, Climate change, computer.software_genre, 01 natural sciences, Ecology and Environment, Profound, Data file, USE EFFICIENCY, SDG 13 - Climate Action, Temporal scales, ATMOSPHERIC CHEMISTRY, lcsh:Environmental sciences, 0105 earth and related environmental sciences, ddc:910, lcsh:GE1-350, Data, 4112 Forestry, OAK QUERCUS-PETRAEA, Database, ISIMIP, NET ECOSYSTEM EXCHANGE, INTERCOMPARISON PROJECT, Physics, Forest Model, lcsh:QE1-996.5, Representative Concentration Pathways, PINUS-SYLVESTRIS, Vegetation, 15. Life on land, 113 Computer and information sciences, EDDY-COVARIANCE, lcsh:Geology, Chemistry, 13. Climate action, FAGUS-SYLVATICA L, [SDE]Environmental Sciences, General Earth and Planetary Sciences, Environmental science, computer, 010606 plant biology & botany
Abstract: Process-based vegetation models are widely used to predict local and global ecosystem dynamics and climate change impacts. Due to their complexity, they require careful parameterization and evaluation to ensure that projections are accurate and reliable. The PROFOUND Database (PROFOUND DB) provides a wide range of empirical data on European forests to calibrate and evaluate vegetation models that simulate climate impacts at the forest stand scale. A particular advantage of this database is its wide coverage of multiple data sources at different hierarchical and temporal scales, together with environmental driving data as well as the latest climate scenarios. Specifically, the PROFOUND DB provides general site descriptions, soil, climate, CO2, nitrogen deposition, tree and forest stand level, and remote sensing data for nine contrasting forest stands distributed across Europe. Moreover, for a subset of five sites, time series of carbon fluxes, atmospheric heat conduction and soil water are also available. The climate and nitrogen deposition data contain several datasets for the historic period and a wide range of future climate change scenarios following the Representative Concentration Pathways (RCP2.6, RCP4.5, RCP6.0, RCP8.5). We also provide pre-industrial climate simulations that allow for model runs aimed at disentangling the contribution of climate change to observed forest productivity changes. The PROFOUND DB is available freely as a “SQLite” relational database or “ASCII” flat file version (at https://doi.org/10.5880/PIK.2020.006/; Reyer et al., 2020). The data policies of the individual contributing datasets are provided in the metadata of each data file. The PROFOUND DB can also be accessed via the ProfoundData R package (https://CRAN.R-project.org/package=ProfoundData; Silveyra Gonzalez et al., 2020), which provides basic functions to explore, plot and extract the data for model set-up, calibration and evaluation.
Published: 2020
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14. What we talk about when we talk about seasonality – A transdisciplinary review

Author: Tobias Braun, Cameron A. Petrie, Thomas Opel, Cinthya Nava-Fernandez, Sebastian F. M. Breitenbach, Patrick Faulkner, Julie A. Hoggarth, Monica Ionita, Jessica L. Oster, Aurel Perşoiu, Keith M. Prufer, Carole Nehme, Saige Kelmelis, Camilla Francesca Brunello, Saija Saarni, Niklas Hausmann, Annabel Wolf, Ola Kwiecien, Chris Jazwa, Norbert Marwan, Gerd Helle, University of Northumbria at Newcastle [United Kingdom], Potsdam Institute for Climate Impact Research (PIK), Earth Surface Geochemistry [Postdam], GeoForschungsZentrum - Helmholtz-Zentrum Potsdam (GFZ), The University of Sydney, Römisch-Germanisches Zentralmuseum Mainz, Leibniz-Forschungsinstitut für Archäologie, Baylor University, Emil Racoviță Institute of Speleology (ERIS), Romanian Academy, University of Nevada [Reno], University of South Dakota [Vermillion] (USD), Ruhr University Bochum (RUB), Identités et Différenciation de l'Environnement des Espaces et des Sociétés (IDEES), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-Université Le Havre Normandie (ULH), Normandie Université (NU)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche Interdisciplinaire Homme et Société (IRIHS), Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Normandie Université (NU)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU), Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research (AWI), Vanderbilt University [Nashville], University Stefan cel Mare of Suceava (USU), University of Cambridge [UK] (CAM), The University of New Mexico [Albuquerque], University of Helsinki, Identité et Différenciation de l’Espace, de l’Environnement et des Sociétés (IDEES), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche Interdisciplinaire Homme et Société (IRIHS), and Normandie Université (NU)-Université de Caen Normandie (UNICAEN)
Subjects: Historical climatology, 010504 meteorology & atmospheric sciences, Stalagmite, F800, Permafrost, 01 natural sciences, [SHS]Humanities and Social Sciences, 03 medical and health sciences, Ice core, medicine, ComputingMilieux_MISCELLANEOUS, 030304 developmental biology, 0105 earth and related environmental sciences, 0303 health sciences, geography, Humid continental climate, geography.geographical_feature_category, Varve, Global warming, 15. Life on land, Seasonality, medicine.disease, [STAT]Statistics [stat], 13. Climate action, [SDE]Environmental Sciences, General Earth and Planetary Sciences, Environmental science, Physical geography
Abstract: The role of seasonality is indisputable in climate and ecosystem dynamics. Seasonal temperature and precipitation variability are of vital importance for the availability of food, water, shelter, migration routes, and raw materials. Thus, understanding past climatic and environmental changes at seasonal scale is equally important for unearthing the history and for predicting the future of human societies under global warming scenarios. Alas, in palaeoenvironmental research, the term ‘seasonality change’ is often used liberally without scrutiny or explanation as to which seasonal parameter has changed and how.\ud \ud Here we provide fundamentals of climate seasonality and break it down into external (insolation changes) and internal (atmospheric CO2 concentration) forcing, and regional and local and modulating factors (continentality, altitude, large-scale atmospheric circulation patterns). Further, we present a brief overview of the archives with potentially annual/seasonal resolution (historical and instrumental records, marine invertebrate growth increments, stalagmites, tree rings, lake sediments, permafrost, cave ice, and ice cores) and discuss archive-specific challenges and opportunities, and how these limit or foster the use of specific archives in archaeological research.\ud \ud Next, we address the need for adequate data-quality checks, involving both archive-specific nature (e.g., limited sampling resolution or seasonal sampling bias) and analytical uncertainties. To this end, we present a broad spectrum of carefully selected statistical methods which can be applied to analyze annually- and seasonally-resolved time series. We close the manuscript by proposing a framework for transparent communication of seasonality-related research across different communities.
Published: 2022
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15. Global irrigation contribution to wheat and maize yield

Author: Joshua Elliot, Erwin Schmid, Thomas A. M. Pugh, Feng Zhou, Jonas Jägermeyr, Xuhui Wang, David Makowski, Laurent Li, Wenfeng Liu, Delphine Deryng, Philippe Ciais, Hui Yang, Christoph Müller, Nathaniel D. Mueller, Chenzhi Wang, Stefan Olin, Su-Jong Jeong, Christian Folberth, James S. Gerber, Shilong Piao, Ashwan Reddy, Patrice Dumas, Peking University [Beijing], Potsdam Institute for Climate Impact Research (PIK), University of Chicago, Colorado State University [Fort Collins] (CSU), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), ICOS-ATC (ICOS-ATC), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Centre International de Recherche sur l'Environnement et le Développement (CIRED), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-École des hautes études en sciences sociales (EHESS)-AgroParisTech-École des Ponts ParisTech (ENPC)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Ludwig-Maximilians-Universität München (LMU), China Agricultural University (CAU), Agronomie, AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Lund University [Lund], University of Maryland [College Park], University of Maryland System, Seoul National University [Seoul] (SNU), Chinese Academy of Sciences [Beijing] (CAS), Mathématiques et Informatique Appliquées (MIA-Paris), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), and Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-AgroParisTech-Université Paris-Saclay
Subjects: Irrigation, 010504 meteorology & atmospheric sciences, Science, Yield (finance), [SDE.MCG]Environmental Sciences/Global Changes, 0208 environmental biotechnology, General Physics and Astronomy, Climate change, Water supply, 02 engineering and technology, Agricultural engineering, 01 natural sciences, Article, General Biochemistry, Genetics and Molecular Biology, Rainfed agriculture, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, 2. Zero hunger, [STAT.AP]Statistics [stat]/Applications [stat.AP], Multidisciplinary, business.industry, Crop yield, Yield gap, General Chemistry, 15. Life on land, 6. Clean water, 020801 environmental engineering, Environmental sciences, 13. Climate action, [SDE]Environmental Sciences, Environmental science, business, Agroecology, Water use
Abstract: Irrigation is the largest sector of human water use and an important option for increasing crop production and reducing drought impacts. However, the potential for irrigation to contribute to global crop yields remains uncertain. Here, we quantify this contribution for wheat and maize at global scale by developing a Bayesian framework integrating empirical estimates and gridded global crop models on new maps of the relative difference between attainable rainfed and irrigated yield (ΔY). At global scale, ΔY is 34 ± 9% for wheat and 22 ± 13% for maize, with large spatial differences driven more by patterns of precipitation than that of evaporative demand. Comparing irrigation demands with renewable water supply, we find 30–47% of contemporary rainfed agriculture of wheat and maize cannot achieve yield gap closure utilizing current river discharge, unless more water diversion projects are set in place, putting into question the potential of irrigation to mitigate climate change impacts., There are big uncertainties in the contribution of irrigation to crop yields. Here, the authors use Bayesian model averaging to combine statistical and process-based models and quantify the contribution of irrigation for wheat and maize yields, finding that irrigation alone cannot close yield gaps for a large fraction of global rainfed agriculture.
Published: 2021
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16. Towards a New Generation of Trait-Flexible Vegetation Models

Author: Koen Kramer, Sylvie Oddou-Muratorio, Friedrich J. Bohn, Christopher P. O. Reyer, Ian J. Wright, Florian Hartig, Santiago Sabaté, Fabio Berzaghi, Tanja G. M. Sanders, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Wageningen University, Ecologie des Forêts Méditerranéennes (URFM), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Helmholtz Zentrum für Umweltforschung = Helmholtz Centre for Environmental Research (UFZ), Karlsruhe Institute of Technology (KIT), Potsdam Institute for Climate Impact Research (PIK), University of Barcelona, Centre for Ecological Research and Forestry Applications (CREAF), Thuenen Institute of Forest Ecosystems, Partenaires INRAE, 845265,DP170103410,01LS1711A,FP1304, Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), and Wageningen University and Research [Wageningen] (WUR)
Subjects: 0106 biological sciences, Range (biology), Climate Change, [SDE.MCG]Environmental Sciences/Global Changes, Bos- en Landschapsecologie, Biodiversity, Climate change, Biology, 010603 evolutionary biology, 01 natural sciences, eco-evolution, medicine, Forest and Landscape Ecology, Ecology, Evolution, Behavior and Systematics, Vegetatie, Genetic diversity, Vegetation, Ecology, Biosphere, Global change, Plants, 15. Life on land, plant genetics, PE&RC, Biological Evolution, vegetation modeling, Phenotype, intraspecific variation, 13. Climate action, plant traits, Trait, Vegetatie, Bos- en Landschapsecologie, Vegetation, Forest and Landscape Ecology, medicine.symptom, Vegetation (pathology), 010606 plant biology & botany
Abstract: International audience; Plant trait variability, emerging from eco-evolutionary dynamics that range from alleles to macroecological scales, is one of the most elusive, but possibly most consequential, aspects of biodiversity. Plasticity, epigenetics, and genetic diversity are major determinants of how plants will respond to climate change, yet these processes are rarely represented in current vegetation models. Here, we provide an overview of the challenges associated with understanding the causes and consequences of plant trait variability, and review current developments to include plasticity and evolutionary mechanisms in vegetation models. We also present a roadmap of research priorities to develop a next generation of vegetation models with flexible traits. Including trait variability in vegetation models is necessary to better represent biosphere responses to global change.
Published: 2020
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17. Insights on Nitrogen and Phosphorus Co‐Limitation in Global Croplands From Theoretical and Modeling Fertilization Experiments

Author: Thomas Nesme, Nathaniel D. Mueller, Nicolas Vuichard, Sylvain Pellerin, Bruno Ringeval, Philippe Ciais, Daniel S. Goll, Laurent Augusto, Christoph Müller, Marko Kvakić, Xuhui Wang, Interactions Sol Plante Atmosphère (ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université Paris-Saclay-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS), Department of Earth System Science, University of California Irvine (UCI), Potsdam Institute for Climate Impact Research, Leibniz Association (PIK), Interactions Sol Plante Atmosphère (UMR ISPA), Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), ICOS-ATC (ICOS-ATC), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), Colorado State University [Fort Collins] (CSU), Potsdam Institute for Climate Impact Research (PIK), Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University [Beijing], Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), and Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Subjects: Atmospheric Science, 010504 meteorology & atmospheric sciences, Soil nutrients, Nutrient interaction, [SDV]Life Sciences [q-bio], chemistry.chemical_element, Soil science, Agricultural engineering, [SDV.SA.SDS]Life Sciences [q-bio]/Agricultural sciences/Soil study, 01 natural sciences, Nutrient, Human fertilization, cropland, nutrient interaction, Environmental Chemistry, Ecosystem, Liebig's law of the minimum, 0105 earth and related environmental sciences, General Environmental Science, Mathematics, 2. Zero hunger, nutrient limitation, Global and Planetary Change, Scale (chemistry), Phosphorus, Function (mathematics), 04 agricultural and veterinary sciences, 15. Life on land, Nitrogen, multiple limitation, chemistry, [SDE]Environmental Sciences, Liebig's law, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries
Abstract: Crossed fertilization additions are a common tool to assess nutrient interaction in a given ecosystem. Such fertilization experiments lead to the definition of nutrient interaction categories: e.g. simultaneous co-limitation, single resource response, etc. (Harpole et al., 2011). However, the implications of such categories in terms of nutrient interaction modeling are not clear. To this end, we developed a theoretical analysis of nitrogen (N) and phosphorus (P) fertilization experiments based on the computation of ratios between plant demand and soil supply for each nutrient. The theoretical analysis is developed following two mathematical formalisms of interaction: Liebig's law of minimum and multiple limitation hypothesis. As results of the theoretical framework, we defined the corresponding between most Harpole categories and the values of the limitation by each nutrient when considered alone in the control experiment (i.e. without additional nutrient supply). We showed that synergistic co-limitation could occur even using Liebig's formalism under certain conditions as a function of the amount of N and P added in fertilization experiments. We then applied our framework with global maps of soil supply and plant demand for croplands to achieve their potential yield. This allowed us to estimate the global occurrence of each limitation category, for each of the possible interaction formalism. We found that a true co-limitation could affect a large proportion of the global crop area (e.g. ~ 42 % for maize) if multiple limitation hypothesis is assumed. Our work clarifies the conditions required to achieve N and P co-limitation as function of the interaction formalism. Combined with compilation of field trials in cropland, our study would improve our understanding of nutrient limitation in cropland at the global scale.
Published: 2021
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18. Next-generation ensemble projections reveal higher climate risks for marine ecosystems

Author: Jason S. Link, Marta Coll, Eric D. Galbraith, Jérôme Guiet, Jose A. Fernandes-Salvador, Gregory L. Britten, Didier Gascuel, William W. L. Cheung, Julia L. Blanchard, John P. Dunne, Yunne-Jai Shin, Elizabeth A. Fulton, Ryan F. Heneghan, Matthias Büchner, Jasmin G. John, Tyler D. Eddy, Daniele Bianchi, Heike K. Lotze, Charles A. Stock, Camilla Novaglio, Nicolas Barrier, Laurent Bopp, Jeroen Steenbeek, Derek P. Tittensor, Olivier Maury, Jonathan Rault, Kelly Ortega-Cisneros, Lynne J. Shannon, Colleen M. Petrik, Juliano Palacios-Abrantes, Hubert Du Pontavice, Anthony J. Richardson, Jason D. Everett, Andrea Bryndum-Buchholz, Cheryl S. Harrison, Villy Christensen, MARine Biodiversity Exploitation and Conservation (UMR MARBEC), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Institut de Recherche pour le Développement (IRD), Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Massachusetts Institute of Technology (MIT), Interférométrie (LCAR), Laboratoire Collisions Agrégats Réactivité (LCAR), Institut de Recherche sur les Systèmes Atomiques et Moléculaires Complexes (IRSAMC), Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche sur les Systèmes Atomiques et Moléculaires Complexes (IRSAMC), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), Institute for the Oceans and Fisheries, University of British Columbia (UBC), NOAA Geophysical Fluid Dynamics Laboratory (GFDL), National Oceanic and Atmospheric Administration (NOAA), Institució Catalana de Recerca i Estudis Avançats (ICREA), Écologie et santé des écosystèmes (ESE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), NOAA National Marine Fisheries Service (NMFS), Dalhousie University [Halifax], Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER), University of Aberdeen, Institute for Marine and Antarctic Studies and Centre for Marine Socioecology, University of Tasmania [Hobart, Australia] (UTAS), Jarislowsky Foundation, Natural Sciences and Engineering Research Council of Canada, Australian Research Council, European Commission, Ministerio de Ciencia, Innovación y Universidades (España), UK Research and Innovation, Global Challenges Research Fund, One Ocean Hub, Simons Foundation, Belmont Forum, BiodivERsA, Agencia Estatal de Investigación (España), Ocean Frontier Institute, Agence Nationale de la Recherche (France), California Ocean Protection Council, Alfred P. Sloan Foundation, Extreme Science and Engineering Discovery Environment (US), National Oceanic and Atmospheric Administration (US), Institut de Recherche pour le Développement (IRD)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut de Recherche sur les Systèmes Atomiques et Moléculaires Complexes (IRSAMC), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, University of Texas Rio Grande Valley [Brownsville, TX] (UTRGV), Louisiana State University (LSU), Queensland University of Technology [Brisbane] (QUT), University of California [Los Angeles] (UCLA), University of California (UC), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Potsdam Institute for Climate Impact Research (PIK), Instituto de Ciencias del Mar de Barcelona (ICM), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), Centre for Fisheries Ecosystems Research (CFER), Memorial University of Newfoundland = Université Memorial de Terre-Neuve [St. John's, Canada] (MUN), University of Queensland [Brisbane], Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), University of New South Wales [Sydney] (UNSW), Basque Research and Technology Alliance (BRTA), AZTI - Tecnalia, McGill University = Université McGill [Montréal, Canada], Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-INSTITUT AGRO Agrocampus Ouest, University of Cape Town, University of Wisconsin-Madison, Texas A&M University [College Station], Princeton University, and ANR-17-CE32-0008,CIGOEF,Impacts des changements climatiques sur les écosystèmes et les pêcheries océaniques globaux.(2017)
Subjects: 0106 biological sciences, 010504 meteorology & atmospheric sciences, Environmental Science and Management, [SDE.MCG]Environmental Sciences/Global Changes, Climate change, Environmental Science (miscellaneous), 01 natural sciences, Physical Geography and Environmental Geoscience, Article, Atmospheric Sciences, Ecosystem, Marine ecosystem, 14. Life underwater, Life Below Water, 0105 earth and related environmental sciences, Ecological modelling, Marine biology, Coupled model intercomparison project, Biomass (ecology), business.industry, 010604 marine biology & hydrobiology, Environmental resource management, Climate-change ecology, Primary production, 15. Life on land, Climate Action, 13. Climate action, Environmental science, Climate model, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, business, Social Sciences (miscellaneous)
Abstract: 22 pages, 5 figures, 1 table, supplementary information https://doi.org/10.1038/s41558-021-01173-9.-- Data availabilityAll standardized forcing variables from the ESMs are available at https://doi.org/10.48364/ISIMIP.575744.1; all outputs from the MEMs are available via ISIMIP (https://www.isimip.org/gettingstarted/data-access/).-- Code availabilityAll code used to analyse simulations is available at https://github.com/Fish-MIP/CMIP5vsCMIP6, Projections of climate change impacts on marine ecosystems have revealed long-term declines in global marine animal biomass and unevenly distributed impacts on fisheries. Here we apply an enhanced suite of global marine ecosystem models from the Fisheries and Marine Ecosystem Model Intercomparison Project (Fish-MIP), forced by new-generation Earth system model outputs from Phase 6 of the Coupled Model Intercomparison Project (CMIP6), to provide insights into how projected climate change will affect future ocean ecosystems. Compared with the previous generation CMIP5-forced Fish-MIP ensemble, the new ensemble ecosystem simulations show a greater decline in mean global ocean animal biomass under both strong-mitigation and high-emissions scenarios due to elevated warming, despite greater uncertainty in net primary production in the high-emissions scenario. Regional shifts in the direction of biomass changes highlight the continued and urgent need to reduce uncertainty in the projected responses of marine ecosystems to climate change to help support adaptation planning, This work was supported by the Jarislowsky Foundation (D.P.T.), the Natural Sciences and Engineering Research Council of Canada Discovery Grant programme (D.P.T., H.K.L., T.D.E., W.W.L.C., J.P.-A. and V.C.); Australian Research Council (ARC) Discovery Projects DP170104240 (J.L.B. and C.N.), DP190102293 (J.L.B., C.N., A.J.R., J.D.E. and D.P.T.) and DP150102656 (J.D.E.); the European Union’s Horizon 2020 research and innovation programme under grant agreements 817578 (TRIATLAS) (M.C., J.S., L.S., O.M., L.B., Y.-J.S., N.B. and J.R.), 869300 (FutureMARES) (J.A.F.-S.,Y.-J.S. and M.C.) and 862428 (MISSION ATLANTIC (J.A.F.-S, Y.-J.S. and M.C.); the Spanish National Project ProOceans (PID2020-118097RB-I00) (M.C. and J.S.); the Open Philanthropy Project (C.S.H.); the United Kingdom Research and Innovation (UKRI) Global Challenges Research Fund (GCRF) One Ocean Hub (NE/S008950/1) (K.O.-C. and L.S.); the Simons Foundation (nos. 54993, 645921) (G.L.B.); the Belmont Forum and BiodivERsA under the BiodivScen ERA-Net COFUND programme (SOMBEE project, ANR-18-EBI4-0003-01) (Y.-J.S. and N.B.); the MEOPAR Postdoctoral Fellowship Award 2020–2021 and the Ocean Frontier Institute (Module G) (A.B.-B.); the French ANR project CIGOEF (grant ANR-17-CE32-0008-01) (O.M., L.B. and J.R.); the California Ocean Protection Council Grant C0100400, the Alfred P. Sloan Foundation and the Extreme Science and Engineering Discovery Environment (XSEDE) allocation TG-OCE170017 (D.B. and J.G.); the National Oceanographic and Atmospheric Association (NA20OAR4310441, NA20OAR4310442) (C.M.P.). M.C. acknowledges the Severo Ochoa Centre of Excellence accreditation (CEX2019-000928-S) to the Institute of Marine Science (ICM-CSIC)
Published: 2021
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19. Multiple cropping systems of the world and the potential for increasing cropping intensity

Author: Jan Philipp Dietrich, Mario Herrero, Katharina Waha, Philip K. Thornton, Felix T. Portmann, Alberte Bondeau, Stefan Siebert, CSIRO Agriculture and Food (CSIRO), Potsdam Institute for Climate Impact Research (PIK), Goethe-University Frankfurt am Main, Centre for Biodiversity and Sustainable Land-use, University of Göttingen, Göttingen, Germany, Georg-August-University [Göttingen], International Livestock Research Institute [CGIAR, Nairobi] (ILRI), International Livestock Research Institute [CGIAR, Ethiopie] (ILRI), Consultative Group on International Agricultural Research [CGIAR] (CGIAR)-Consultative Group on International Agricultural Research [CGIAR] (CGIAR), Institut méditerranéen de biodiversité et d'écologie marine et continentale (IMBE), Centre National de la Recherche Scientifique (CNRS)-Institut de recherche pour le développement [IRD] : UMR237-Aix Marseille Université (AMU)-Avignon Université (AU), Centre for Biodiversity and Sustainable Land-use [University of Göttingen] (CBL), Georg-August-University = Georg-August-Universität Göttingen, and Avignon Université (AU)-Aix Marseille Université (AMU)-Institut de recherche pour le développement [IRD] : UMR237-Centre National de la Recherche Scientifique (CNRS)
Subjects: 010504 meteorology & atmospheric sciences, Double cropping, Geography, Planning and Development, Land management, Context (language use), 010501 environmental sciences, Management, Monitoring, Policy and Law, Multiple cropping, Global crop production, 01 natural sciences, Article, Harvest frequency, Land use intensity, Agricultural productivity, 0105 earth and related environmental sciences, 2. Zero hunger, Global and Planetary Change, 333,7, Ecology, Land use, Agroforestry, business.industry, Crop yield, Cropping intensity, 15. Life on land, Agriculture, Land sparing, [SDE]Environmental Sciences, Environmental science, business, Cropping
Abstract: Highlights • Global area of different multiple cropping systems quantified for the first time. • Twelve percent of global cropland are used for growing two or three crops in a sequence. • Potential for increasing harvest frequency smaller than previously estimated., Multiple cropping, defined as harvesting more than once a year, is a widespread land management strategy in tropical and subtropical agriculture. It is a way of intensifying agricultural production and diversifying the crop mix for economic and environmental benefits. Here we present the first global gridded data set of multiple cropping systems and quantify the physical area of more than 200 systems, the global multiple cropping area and the potential for increasing cropping intensity. We use national and sub-national data on monthly crop-specific growing areas around the year 2000 (1998–2002) for 26 crop groups, global cropland extent and crop harvested areas to identify sequential cropping systems of two or three crops with non-overlapping growing seasons. We find multiple cropping systems on 135 million hectares (12% of global cropland) with 85 million hectares in irrigated agriculture. 34%, 13% and 10% of the rice, wheat and maize area, respectively are under multiple cropping, demonstrating the importance of such cropping systems for cereal production. Harvesting currently single cropped areas a second time could increase global harvested areas by 87–395 million hectares, which is about 45% lower than previous estimates. Some scenarios of intensification indicate that it could be enough land to avoid expanding physical cropland into other land uses but attainable intensification will depend on the local context and the crop yields attainable in the second cycle and its related environmental costs.
Published: 2020
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20. Climate change impact and adaptation for wheat protein

Author: Mohamed Jabloun, Pierre Martre, Garry O'Leary, Dominique Ripoche, Bruno Basso, Pramod K. Aggarwal, Daniel Wallach, Matthew P. Reynolds, Marijn van der Velde, John R. Porter, Heidi Webber, Enli Wang, Frank Ewert, Joost Wolf, Christian Klein, Belay T. Kassie, Christian Biernath, Margarita Garcia-Vila, M. Ali Babar, Pierre Stratonovitch, Yujing Gao, Glenn J. Fitzgerald, Davide Cammarano, Bing Liu, Peter J. Thorburn, Fulu Tao, Andrew J. Challinor, Reimund P. Rötter, Christine Girousse, Zhigan Zhao, Christoph Müller, Ann-Kristin Koehler, Jørgen E. Olesen, Elias Fereres, Iwan Supit, Andrea Maiorano, Marco Bindi, Sebastian Gayler, Kurt Christian Kersebaum, Giacomo De Sanctis, Alex C. Ruane, Rosella Motzo, Juraj Balkovic, Manuel Montesino San Martin, Roberto Ferrise, Mikhail A. Semenov, Claudio O. Stöckle, Soora Naresh Kumar, Gerrit Hoogenboom, Benjamin Dumont, Ehsan Eyshi Rezaei, Mukhtar Ahmed, Senthold Asseng, Thilo Streck, Yan Zhu, R. Cesar Izaurralde, Katharina Waha, Ahmed M. S. Kheir, Taru Palosuo, Liujun Xiao, Sara Minoli, Eckart Priesack, Heidi Horan, Curtis D. Jones, Francesco Giunta, Zhao Zhang, Claas Nendel, International Food Policy Research Institute (US), CGIAR (France), European Commission, Institut National de la Recherche Agronomique (France), National Natural Science Foundation of China, Federal Ministry of Food and Agriculture (Germany), Biotechnology and Biological Sciences Research Council (UK), Innovation Fund Denmark, China Scholarship Council, Ministero delle Politiche Agricole Alimentari e Forestali, Academy of Finland, Finnish Ministry of Agriculture and Forestry, Federal Ministry of Education and Research (Germany), Department of Agriculture and Water Resources (Australia), University of Melbourne, Grains Research and Development Corporation (Australia), National Institute of Food and Agriculture (US), German Research Foundation, Gorgan University, Department of Agricultural and Biological Engineering [Gainesville] (UF|ABE), Institute of Food and Agricultural Sciences [Gainesville] (UF|IFAS), University of Florida [Gainesville] (UF)-University of Florida [Gainesville] (UF), Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), European Food Safety Authority = Autorité européenne de sécurité des aliments, Tropical Plant Production and Agricultural Systems Modelling (TROPAGS), Georg-August-University = Georg-August-Universität Göttingen, Centre for Biodiversity and Sustainable Land-use [University of Göttingen] (CBL), Department of Economic Drt and Resources, Grains Innovation Park, Agriculture Victoria Research, Department of Economic Development, Jobs, Transport and Resources, Faculty of Veterinary and Agricultural Science [Melbourne], Génétique Diversité et Ecophysiologie des Céréales (GDEC), Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020]), Department of Agricultural Sciences, University of Naples Federico II = Università degli studi di Napoli Federico II, World Food Crops Breeding, Department of Agronomy, IFAS, University of Florida [Gainesville] (UF), International Maize and Wheat Improvement Center (CIMMYT), Consultative Group on International Agricultural Research [CGIAR] (CGIAR), Soils, Water and Environment Research Institute, Agricultural Research Center (ARC), Agriculture and Food, Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), NASA Goddard Institute for Space Studies (GISS), NASA Goddard Space Flight Center (GSFC), International Maize and Wheat Improvement Centre [Inde] (CIMMYT), Consultative Group on International Agricultural Research [CGIAR] (CGIAR)-Consultative Group on International Agricultural Research [CGIAR] (CGIAR), Biological Systems Engineering, University of Wisconsin-Madison, Department of Agronomy, University of El-Tarf, Ecosystem Services and Management Program, International Institute for Applied Systems Analysis (IIASA), Department of Soil Science, Faculty of Natural Sciences, Comenius University in Bratislava, W. K. Kellogg Biological Station (KBS), Michigan State University [East Lansing], Michigan State University System-Michigan State University System, Department of Earth and Environmental Sciences [Ann Arbor], University of Michigan [Ann Arbor], University of Michigan System-University of Michigan System, Institute of Biochemical Plant Pathology, Research Center for Environmental Health, Helmholtz Zentrum München = German Research Center for Environmental Health, Department of Agri‐food Production and Environmental Sciences (DISPAA), Università degli Studi di Firenze = University of Florence (UniFI), The James Hutton Institute, Institute for Climate and Atmospheric Science [Leeds] (ICAS), School of Earth and Environment [Leeds] (SEE), University of Leeds-University of Leeds, Collaborative Research Program from CGIAR and Future Earth on Climate Change, Agriculture and Food Security (CCAFS), International Center for Tropical Agriculture, GMO Unit, European Food Safety Authority, Department Terra & AgroBioChem, Gembloux Agro‐Bio Tech, Université de Liège, Institute of Crop Science and Resource Conservation [Bonn] (INRES), Rheinische Friedrich-Wilhelms-Universität Bonn, Department of Crop Sciences, Instituto de Agricultura Sostenible - Institute for Sustainable Agriculture (IAS CSIC), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), Institute of Soil Science and Land Evaluation, University of Hohenheim, Food Systems Institute [Gainesville] (UF|IFAS), Department of Geographical Sciences, College Park, University of Maryland [College Park], University of Maryland System-University of Maryland System, Texas A and M AgriLife Research, Texas A&M University System, Department of Agroecology, Aarhus University [Aarhus], Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research (ZALF), Institute of Biochemical Plant Pathology [Neuherberg], German Research Center for Environmental Health - Helmholtz Center München (GmbH), National Engineering and Technology Center for Information Agriculture, Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture, Jiangsu Key Laboratory for Information Agriculture, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricutural University, Member of the Leibniz Association, Potsdam Institute for Climate Impact Research (PIK), Department of Plant and Environmental Sciences [Copenhagen], Faculty of Science [Copenhagen], University of Copenhagen = Københavns Universitet (UCPH)-University of Copenhagen = Københavns Universitet (UCPH), Centre for Environment Science and Climate Resilient Agriculture [New Delhi], Indian Agricultural Research Institute (IARI), Natural Resources Institute Finland (LUKE), Fonctionnement et conduite des systèmes de culture tropicaux et méditerranéens (UMR SYSTEM), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Montpellier (CIHEAM-IAMM), Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), University of Lincoln, Agroclim (AGROCLIM), Institut National de la Recherche Agronomique (INRA), Rothamsted Research, Biotechnology and Biological Sciences Research Council (BBSRC), Water & Food and Water Systems & Global Change Group, Wageningen University and Research [Wageningen] (WUR), Institute of geographical sciences and natural resources research [CAS] (IGSNRR), Chinese Academy of Sciences [Beijing] (CAS), Joint Research Centre (IPTS), Commission Européenne, AGroécologie, Innovations, teRritoires (AGIR), Institut National de la Recherche Agronomique (INRA)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université de Toulouse (UT), CSIRO Agriculture and Food (CSIRO), Plant Production Systems, State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University (BNU), Department of Agronomy and Biotechnology, China Agricultural University (CAU), National Research Foundation for the Doctoral Program of Higher Education of China, Grant/Award Number: 20120097110042, International Food Policy, European Project: 267196,EC:FP7:PEOPLE,FP7-PEOPLE-2010-COFUND,AGREENSKILLS(2012), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro), Georg-August-University [Göttingen], Centre of Biodiversity and Sustainable Land Use (CBL), University of Göttingen - Georg-August-Universität Göttingen, University of Naples Federico II, Helmholtz-Zentrum München (HZM), Universtiy of Florence, University of Copenhagen = Københavns Universitet (KU)-University of Copenhagen = Københavns Universitet (KU), Natural Resources Institute Finland, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Wageningen University, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences (CAS), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Agricultural & Biological Engineering Department, University of Florida [Gainesville], Georg-August-Universität Göttingen, University of Goettingen, Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP), Research Program on Climate Change, Agriculture and Food Security, BISA‐CIMMYT, Consultative Group on International Agricultural Research (CGIAR), Comenius University [Bratislava], Helmholtz Zentrum München, Institute of Crop Science and Resource Conservation INRES, University of Bonn, IAS‐CSIC, Universidad de Cordoba, Institute for Sustainable Food Systems, Texas A&M AgriLife Research and Extension Center, Aarhus University, Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Montpellier (CIHEAM-IAMM), Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), UE Agroclim (UE AGROCLIM), UMR : AGroécologie, Innovations, TeRritoires, Ecole Nationale Supérieure Agronomique de Toulouse, Wageningen University and Research Center (WUR), Beijing Normal University, and China Agricultural University
Subjects: [SDV.SA]Life Sciences [q-bio]/Agricultural sciences, 0106 biological sciences, 010504 meteorology & atmospheric sciences, Water en Voedsel, 01 natural sciences, grain protein, adaptation au milieu, climate change adaptation, climate change impact, food security, wheat, Co2 concentration, adaptation to the environment, Triticum, General Environmental Science, 2. Zero hunger, changement climatique, Global and Planetary Change, Food security, Ecology, Temperature, food and beverages, Adaptation, Physiological, Droughts, Nitrogen, Climate Change, Climate change, 010603 evolutionary biology, blé, Crop production, Food Quality, Grain quality, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, Environmental Chemistry, Grain Proteins, global change, 0105 earth and related environmental sciences, WIMEK, Water and Food, Global change, Carbon Dioxide, Models, Theoretical, 15. Life on land, Agronomy, 13. Climate action, Grain yield, Environmental science, Water Systems and Global Change, Protein concentration
Abstract: Wheat grain protein concentration is an important determinant of wheat quality for human nutrition that is often overlooked in efforts to improve crop production. We tested and applied a 32‐multi‐model ensemble to simulate global wheat yield and quality in a changing climate. Potential benefits of elevated atmospheric CO2 concentration by 2050 on global wheat grain and protein yield are likely to be negated by impacts from rising temperature and changes in rainfall, but with considerable disparities between regions. Grain and protein yields are expected to be lower and more variable in most low‐rainfall regions, with nitrogen availability limiting growth stimulus from elevated CO2. Introducing genotypes adapted to warmer temperatures (and also considering changes in CO2 and rainfall) could boost global wheat yield by 7% and protein yield by 2%, but grain protein concentration would be reduced by −1.1 percentage points, representing a relative change of −8.6%. Climate change adaptations that benefit grain yield are not always positive for grain quality, putting additional pressure on global wheat production., B.L received support from the International Food Policy Research Institute (IFPRI) through the Global Futures and Strategic Foresight project, the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) and the CGIAR Research Program on Wheat. A.M. received support from the EU Marie Curie FP7 COFUND People Programme, through an AgreenSkills fellowship under grant agreement no. PCOFUND‐GA‐2010‐267196. PM, A.M., D.R., and D.W. acknowledge support from the FACCE JPI MACSUR project (031A103B) through the metaprogram Adaptation of Agriculture and Forests to Climate Change (AAFCC) of the French National Institute for Agricultural Research (INRA). L.X. and Y.Z. were supported by the National High‐Tech Research and Development Program of China (2013AA100404), the National Natural Science Foundation of China (31271616), the National Research Foundation for the Doctoral Program of Higher Education of China (20120097110042), and the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD). F.T. and Z.Z. were supported by the National Natural Science Foundation of China (41571088, 41571493 and 31561143003). R.R. received support from the German Ministry for Research and Education (BMBF) through project SPACES‐LLL. Rothamsted Research receives support from the Biotechnology and Biological Sciences Research Council (BBSRC) Designing Future Wheat programme [BB/P016855/1]. M.J. and J.E.O. were supported by Innovation Fund Denmark through the MACSUR project. L.X. and Y.G. acknowledge support from the China Scholarship Council. M.B and R.F. were funded by JPI FACCE MACSUR2 through the Italian Ministry for Agricultural, Food and Forestry Policies and thank A. Soltani from Gorgan Univ. of Agric. Sci. & Natur. Resour. for his support. R.P.R., T.P., and F.T. received financial support from the FACCE MACSUR project funded through the Finnish Ministry of Agriculture and Forestry (MMM) and from the Academy of Finland through the projects NORFASYS (decision nos. 268277 and 292944) and PLUMES (decision nos. 277403 and 292836). K.C.K. and C.N. received support from the German Ministry for Research and Education (BMBF) within the FACCE JPI MACSUR project. S.M. and C.M. acknowledge financial support from the MACMIT project (01LN1317A) funded through BMBF. G.J.O. and G.J.F. acknowledge support from the Victorian Department of Economic Development, Jobs, Transport and Resources, the Australian Department of Agriculture and Water Resources, The University of Melbourne and the Grains Research Development Corporation, Australia. P.K.A.'s work was implemented as part of the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), which is carried out with support from the CGIAR Trust Fund and through bilateral funding agreements. For details please visit https://ccafs.cgiar.org/donors. The views expressed in this document cannot be taken to reflect the official opinions of these organizations.. B.B. received financial support from USDA NIFA‐Water Cap Award 2015‐68007‐23133. F.E. acknowledges support from the FACCE JPI MACSUR project through the German Federal Ministry of Food and Agriculture (2815ERA01J) and from the German Science Foundation (project EW 119/5‐1).
Published: 2019
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21. Ensemble modelling of carbon fluxes in grasslands and croplands

Author: Elizabeth Pattey, Ute Skiba, Brian Grant, Gianni Bellocchi, Katja Klumpp, Pete Smith, Matthew T. Harrison, Val Snow, Sylvie Recous, Joanna Sharp, Fiona Ehrhardt, Arti Bhatia, Joël Léonard, Raphaël Martin, Andrew D. Moore, Jordi Doltra, Renata Sándor, Lorenzo Brilli, Jean-François Soussana, Peter Grace, Susanne Rolinski, Ward Smith, Vasileios Myrgiotis, Raia Silvia Massad, Qing Zhang, Miko U. F. Kirschbaum, Lianhai Wu, Nuala Fitton, Luca Doro, Bruno Basso, Christopher D. Dorich, Patricia Laville, Producció Vegetal, Cultius Extensius Sostenibles, Unité Mixte de Recherche sur l'Ecosystème Prairial - UMR (UREP), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Direction scientifique Environnement, Forêt et Agriculture, Institut National de la Recherche Agronomique (INRA), Queensland University of Technology, Fractionnement des AgroRessources et Environnement (FARE), Université de Reims Champagne-Ardenne (URCA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), University of Aberdeen, AgResearch Grasslands, Collège de Direction (CODIR), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Indian Agricultural Research Institute (IARI), Università degli Studi di Firenze = University of Florence [Firenze] (UNIFI), Catabrian Agricultural Research and Training Center (CIFA), Università degli Studi di Sassari, Agriculture and Agri-Food [Ottawa] (AAFC), British Geological Survey (BGS), Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Transfrontalière BioEcoAgro (Transfrontalière BioEcoAgro), Université d'Artois (UA)-Université de Liège-Université de Picardie Jules Verne (UPJV)-Université du Littoral Côte d'Opale (ULCO)-Université de Lille-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Computer Laboratory [Cambridge], University of Cambridge [UK] (CAM), Scotland's Rural College (SRUC), Potsdam Institute for Climate Impact Research (PIK), Plant & Food Research, Natural Environment Research Council (NERC), Rothamsted Research, CN-MIP by Joint Programming Initiative 'FACCE' Models4Pastures by Joint Programming Initiative 'FACCE' MACSUR by Joint Programming Initiative 'FACCE' COMET-Global by Joint Programming Initiative 'FACCE' MAGGNET by Joint Programming Initiative 'FACCE' French Embassy in Budapest (Hungary) by way of 'Make Our Planet Great Again' programme Federal Ministry of Education & Research (BMBF)01LN1317AEuropean Union (EU)EC EVK2-CT2001-00105GOCE-CT-2003-505572017841SRUC, Queensland University of Technology [Brisbane] (QUT), Università degli Studi di Firenze = University of Florence (UniFI), Università degli Studi di Sassari = University of Sassari [Sassari] (UNISS), Agriculture and Agri-Food (AAFC), Transfrontalière BioEcoAgro - UMR 1158 (BioEcoAgro), Université d'Artois (UA)-Université de Liège-Université de Picardie Jules Verne (UPJV)-Université du Littoral Côte d'Opale (ULCO)-Université de Lille-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-JUNIA (JUNIA), Université catholique de Lille (UCL)-Université catholique de Lille (UCL), and Biotechnology and Biological Sciences Research Council (BBSRC)
Subjects: 0106 biological sciences, [SDE.MCG]Environmental Sciences/Global Changes, Soil Science, Growing season, Atmospheric sciences, 01 natural sciences, Grassland, Temperate climate, 2. Zero hunger, Biomass (ecology), geography, geography.geographical_feature_category, Primary production, 04 agricultural and veterinary sciences, Soil carbon, 15. Life on land, Crop rotation, 13. Climate action, [SDE]Environmental Sciences, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Environmental science, Ecosystem respiration, Agronomy and Crop Science, 010606 plant biology & botany
Abstract: Croplands and grasslands are agricultural systems that contribute to land–atmosphere exchanges of carbon (C). We evaluated and compared gross primary production (GPP), ecosystem respiration (RECO), net ecosystem exchange (NEE) of CO2, and two derived outputs - C use efficiency (CUE=-NEE/GPP) and C emission intensity (IntC= -NEE/Offtake [grazed or harvested biomass]). The outputs came from 23 models (11 crop-specific, eight grassland-specific, and four models covering both systems) at three cropping sites over several rotations with spring and winter cereals, soybean and rapeseed in Canada, France and India, and two temperate permanent grasslands in France and the United Kingdom. The models were run independently over multi-year simulation periods in five stages (S), either blind with no calibration and initialization data (S1), using historical management and climate for initialization (S2), calibrated against plant data (S3), plant and soil data together (S4), or with the addition of C and N fluxes (S5). Here, we provide a framework to address methodological uncertainties and contextualize results. Most of the models overestimated or underestimated the C fluxes observed during the growing seasons (or the whole years for grasslands), with substantial differences between models. For each simulated variable, changes in the multi-model median (MMM) from S1 to S5 was used as a descriptor of the ensemble performance. Overall, the greatest improvements (MMM approaching the mean of observations) were achieved at S3 or higher calibration stages. For instance, grassland GPP MMM was equal to 1632 g C m−2 yr-1 (S5) while the observed mean was equal to 1763 m-2 yr-1 (average for two sites). Nash-Sutcliffe modelling efficiency coefficients indicated that MMM outperformed individual models in 92.3 % of cases. Our study suggests a cautious use of large-scale, multi-model ensembles to estimate C fluxes in agricultural sites if some site-specific plant and soil observations are available for model calibration. The further development of crop/grassland ensemble modelling will hinge upon the interpretation of results in light of the way models represent the processes underlying C fluxes in complex agricultural systems (grassland and crop rotations including fallow periods). info:eu-repo/semantics/acceptedVersion
Published: 2020
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22. Mapping the yields of lignocellulosic bioenergy crops from observations at the global scale

Author: W. Li, P. Ciais, E. Stehfest, D. van Vuuren, A. Popp, A. Arneth, F. Di Fulvio, J. Doelman, F. Humpenöder, A. B. Harper, T. Park, D. Makowski, P. Havlik, M. Obersteiner, J. Wang, A. Krause, W. Liu, International Institute for Applied Systems Analysis [Laxenburg] (IIASA), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), ICOS-ATC (ICOS-ATC), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), PBL Netherlands Environmental Assessment Agency, Potsdam Institute for Climate Impact Research (PIK), Institut für Meteorologie und Klimaforschung - Atmosphärische Umweltforschung (IMK-IFU), Karlsruher Institut für Technologie (KIT), College of Engineering, Mathematics and Physical Sciences [Exeter] (EMPS), University of Exeter, College of Life and Environmental Sciences [Exeter], Department of Earth and Environment [Boston], Boston University [Boston] (BU), NASA Ames Research Center (ARC), Bay Area Environmental Research Institute (BAER), Agronomie, AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Institute of Nanotechnology [Karlsruhe] (INT), Karlsruhe Institute of Technology (KIT), TUM School of Life Sciences Weihenstephan, Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne] (TUM), This study is supported by the National Key Research and Development Program of China (grant no. 2019YFA0606604) and European Research Council Synergy Grant ('IMBALANCE-P' (grant no. ERC-2013-SyG-610028))., ANR-16-CONV-0003,CLAND,CLAND : Changement climatique et usage des terres(2016), European Project: 610028,EC:FP7:ERC,ERC-2013-SyG,IMBALANCE-P(2014), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), and Environmental Sciences
Subjects: Willow, 010504 meteorology & atmospheric sciences, 020209 energy, 02 engineering and technology, Agricultural engineering, 01 natural sciences, 7. Clean energy, Crop, Bioenergy, Yield (wine), 0202 electrical engineering, electronic engineering, information engineering, Carbon capture and storage, ddc:550, lcsh:Environmental sciences, 0105 earth and related environmental sciences, lcsh:GE1-350, 2. Zero hunger, biology, Crop yield, lcsh:QE1-996.5, Miscanthus, 15. Life on land, biology.organism_classification, lcsh:Geology, Earth sciences, 13. Climate action, Greenhouse gas, [SDE]Environmental Sciences, General Earth and Planetary Sciences, Environmental science
Abstract: Most scenarios from integrated assessment models (IAMs) that project greenhouse gas emissions include the use of bioenergy as a means to reduce CO2 emissions or even to achieve negative emissions (together with CCS – carbon capture and storage). The potential amount of CO2 that can be removed from the atmosphere depends, among others, on the yields of bioenergy crops, the land available to grow these crops and the efficiency with which CO2 produced by combustion is captured. While bioenergy crop yields can be simulated by models, estimates of the spatial distribution of bioenergy yields under current technology based on a large number of observations are currently lacking. In this study, a random-forest (RF) algorithm is used to upscale a bioenergy yield dataset of 3963 observations covering Miscanthus, switchgrass, eucalypt, poplar and willow using climatic and soil conditions as explanatory variables. The results are global yield maps of five important lignocellulosic bioenergy crops under current technology, climate and atmospheric CO2 conditions at a 0.5∘×0.5∘ spatial resolution. We also provide a combined “best bioenergy crop” yield map by selecting one of the five crop types with the highest yield in each of the grid cells, eucalypt and Miscanthus in most cases. The global median yield of the best crop is 16.3 t DM ha−1 yr−1 (DM – dry matter). High yields mainly occur in the Amazon region and southeastern Asia. We further compare our empirically derived maps with yield maps used in three IAMs and find that the median yields in our maps are > 50 % higher than those in the IAM maps. Our estimates of gridded bioenergy crop yields can be used to provide bioenergy yields for IAMs, to evaluate land surface models or to identify the most suitable lands for future bioenergy crop plantations. The 0.5∘×0.5∘ global maps for yields of different bioenergy crops and the best crop and for the best crop composition generated from this study can be download from https://doi.org/10.5281/zenodo.3274254 (Li, 2019).
Published: 2020
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23. No polarization–Expected Values of Climate Change Impacts among European Forest Professionals and Scientists

Author: Jari Hynynen, Simon Martel, Alexander Borys, Ioan Dutcă, Mariyana Lyubenova, Ján Merganič, Kristina Blennow, Christopher P. O. Reyer, Johannes Persson, Katarína Merganičová, Emilia Janeczko, Mikko Peltoniemi, Fernando Reboredo, Luisa M. S. Gonçalves, Michal Petr, Giorgio Vacchiano, NOVA Information Management School (NOVA IMS), Faculdade de Ciências e Tecnologia (FCT), Lund University [Lund], Swedish University of Agricultural Sciences (SLU), Polytechnic Institute of Leiria, Potsdam Institute for Climate Impact Research (PIK), Transilvania University of Brasov, Natural Resources Institute Finland (LUKE), Warsaw University of Life Sciences (SGGW), University of Sofia, Interactions Sol Plante Atmosphère (UMR ISPA), Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Technical University in Zvolen (TUZVO), Forest Research [Great Britain], New University of Lisbon, and Università degli Studi di Milano [Milano] (UNIMI)
Subjects: Risk perception, Climate Research, homogeneity of expected values, 010504 meteorology & atmospheric sciences, Natural resource economics, strength of expected values, Strength of expected values, Geography, Planning and Development, Biodiversity, Climate change, TJ807-830, 010501 environmental sciences, Management, Monitoring, Policy and Law, TD194-195, 01 natural sciences, Climate change impacts, Renewable energy sources, Ecosystem services, Effects of global warming, risk perception, Value polarization, SDG 13 - Climate Action, GE1-350, SDG 7 - Affordable and Clean Energy, 0105 earth and related environmental sciences, Environmental effects of industries and plants, Renewable Energy, Sustainability and the Environment, Forest Science, Polarization (politics), Economic return, 333.7, climate change impacts, decision-making, 15. Life on land, Environmental sciences, Geography, 13. Climate action, Social Sciences Interdisciplinary (Peace and Conflict Research and Studies on Sustainable Society), [SDE]Environmental Sciences, Homogeneity of expected values, value polarization, Decision-making
Abstract: The role of values in climate-related decision-making is a prominent theme of climate communication research. The present study examines whether forest professionals are more driven by values than scientists are, and if this results in value polarization. A questionnaire was designed to elicit and assess the values assigned to expected effects of climate change by forest professionals and scientists working on forests and climate change in Europe. The countries involved covered a north-to-south and west-to-east gradient across Europe, representing a wide range of bio-climatic conditions and a mix of economic&ndash, social&ndash, political structures. We show that European forest professionals and scientists do not exhibit polarized expectations about the values of specific impacts of climate change on forests in their countries. In fact, few differences between forest professionals and scientists were found. However, there are interesting differences in the expected values of forest professionals with regard to climate change impacts across European countries. In Northern European countries, the aggregated values of the expected effects are more neutral than they are in Southern Europe, where they are more negative. Expectations about impacts on timber production, economic returns, and regulatory ecosystem services are mostly negative, while expectations about biodiversity and energy production are mostly positive.
Published: 2020
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24. Global trends in carbon sinks and their relationships with CO2 and temperature

Author: S. L. Piao, Michael Obersteiner, Josep G. Canadell, Pierre Friedlingstein, Jordi Sardans, Ivan A. Janssens, Ana Bastos, Marcos Fernández-Martínez, Stephen Sitch, Sara Vicca, Frédéric Chevallier, Josep Peñuelas, P. Ciais, University of Antwerp (UA), Consejo Superior de Investigaciones Científicas [Spain] (CSIC), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Modélisation INVerse pour les mesures atmosphériques et SATellitaires (SATINV), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), ICOS-ATC (ICOS-ATC), International Institute for Applied Systems Analysis [Laxenburg] (IIASA), Global Carbon Project (GCP), CSIRO Marine and Atmospheric Research (CSIRO-MAR), Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO)-Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), University of Exeter, Potsdam Institute for Climate Impact Research (PIK), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), and Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)
Subjects: 010504 meteorology & atmospheric sciences, Environmental Science (miscellaneous), Photosynthesis, Atmospheric sciences, 01 natural sciences, 03 medical and health sciences, Nutrient, Negatively associated, Ecosystem, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, Biology, ComputingMilieux_MISCELLANEOUS, 030304 developmental biology, 0105 earth and related environmental sciences, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, 0303 health sciences, Physics, fungi, Global warming, Carbon sink, Vegetation, 15. Life on land, Chemistry, Boreal, 13. Climate action, Environmental science, Social Sciences (miscellaneous)
Abstract: Elevated CO2 concentrations increase photosynthesis and, potentially, net ecosystem production (NEP), meaning a greater CO2 uptake. Climate, nutrients and ecosystem structure, however, influence the effect of increasing CO2. Here we analysed global NEP from MACC-II and Jena CarboScope atmospheric inversions and ten dynamic global vegetation models (TRENDY), using statistical models to attribute the trends in NEP to its potential drivers: CO2, climatic variables and land-use change. We found that an increased CO2 was consistently associated with an increased NEP (1995–2014). Conversely, increased temperatures were negatively associated with NEP. Using the two atmospheric inversions and TRENDY, the estimated global sensitivities for CO2 were 6.0 ± 0.1, 8.1 ± 0.3 and 3.1 ± 0.1 PgC per 100 ppm (~1 °C increase), and −0.5 ± 0.2, −0.9 ± 0.4 and −1.1 ± 0.1 PgC °C−1 for temperature. These results indicate a positive CO2 effect on terrestrial C sinks that is constrained by climate warming. Global net ecosystem production (NEP) from a number of atmospheric inversions and dynamic global vegetation models is analysed to attribute trends to potential drivers. CO2 is found to have a positive effect on NEP that is constrained by climate warming.
Published: 2018
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25. Linked sustainability challenges and trade-offs among fisheries, aquaculture and agriculture

Author: Eric D. Galbraith, Lindsay Davidson, Andrea Bryndum-Buchholz, Julia L. Blanchard, Tyler D. Eddy, Richard S. Cottrell, Elizabeth A. Fulton, William W. L. Cheung, Kirsty L. Nash, Reg Watson, Heike K. Lotze, Matthias Büchner, Olivier Maury, Christoph Müller, John P. Dunne, Joshua Elliott, Simon Jennings, Nicholas K. Dulvy, Derek P. Tittensor, David A. Carozza, Sea Around Us Project (SAUP), University of British Colombia, CSIRO Marine and Atmospheric Research (CSIRO-MAR), Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), Department of Computer Science, Hong Kong Baptist University (HKBU), University of Chicago, Earth to Ocean Research Group (SFU), Simon Fraser University (SFU.ca), NOAA Geophysical Fluid Dynamics Laboratory (GFDL), National Oceanic and Atmospheric Administration (NOAA), MARine Biodiversity Exploitation and Conservation (UMR MARBEC), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Institut de Recherche pour le Développement (IRD), Potsdam Institute for Climate Impact Research (PIK), School of Geography, and University of North London
Subjects: 0106 biological sciences, Conservation of Natural Resources, 010504 meteorology & atmospheric sciences, [SDE.MCG]Environmental Sciences/Global Changes, Climate Change, Fisheries, Aquaculture, 01 natural sciences, 12. Responsible consumption, [SDV.EE.ECO]Life Sciences [q-bio]/Ecology, environment/Ecosystems, 11. Sustainability, 14. Life underwater, Ecology, Evolution, Behavior and Systematics, 0105 earth and related environmental sciences, 2. Zero hunger, Sustainable development, Adaptive capacity, Food security, Ecology, business.industry, 010604 marine biology & hydrobiology, 1. No poverty, Capacity building, Agriculture, Biodiversity, 15. Life on land, Fishery, 13. Climate action, Sustainability, Food systems, Fisheries management, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, business
Abstract: International audience; Fisheries and aquaculture make a crucial contribution to global food security, nutrition and livelihoods. However, the UN Sustainable Development Goals separate marine and terrestrial food production sectors and ecosystems. To sustainably meet increasing global demands for fish, the interlinkages among goals within and across fisheries, aquaculture and agriculture sectors must be recognized and addressed along with their changing nature. Here, we assess and highlight development challenges for fisheries-dependent countries based on analyses of interactions and trade-offs between goals focusing on food, biodiversity and climate change. We demonstrate that some countries are likely to face double jeopardies in both fisheries and agriculture sectors under climate change. The strategies to mitigate these risks will be context-dependent, and will need to directly address the trade-offs among Sustainable Development Goals, such as halting biodiversity loss and reducing poverty. Countries with low adaptive capacity but increasing demand for food require greater support and capacity building to transition towards reconciling trade-offs. Necessary actions are context-dependent and include effective governance, improved management and conservation, maximizing societal and environmental benefits from trade, increased equitability of distribution and innovation in food production, including continued development of low input and low impact aquaculture.
Published: 2017
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26. Adaptive capacity of coupled social-ecological systems to absorb climate extremes

Author: Richard D. Bardgett, Carolina Vera, Sandra Lavorel, Thomas Knoke, Michael Bahn, Anja Rammig, Kirsten Thonicke, Björn Vollan, Carola Paul, Karl-Heinz Erb, Sch Life Sci Weihenstephan, Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne] (TUM), Institute of Ecology, Technische Universität Berlin (TU), Institute of Social Ecology Vienna (SEC), Alpen-Adria-Universität Klagenfurt [Klagenfurt, Austria], Faculty of Life Sciences University of Manchester, University of Manchester [Manchester], Laboratoire d'Ecologie Alpine (LECA ), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), and Potsdam Institute for Climate Impact Research (PIK)
Subjects: 0106 biological sciences, Adaptive capacity, Operationalization, 010504 meteorology & atmospheric sciences, business.industry, Environmental resource management, 15. Life on land, Diversification (marketing strategy), Ecological systems theory, 010603 evolutionary biology, 01 natural sciences, [SDE.ES]Environmental Sciences/Environmental and Society, Ecological resilience, 13. Climate action, [SDE]Environmental Sciences, Economics, Ecosystem management, Asset (economics), business, Resilience (network), ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences
Abstract: Ecosystems and society are strongly interlinked and are, therefore, considered as coupled social-ecological systems (SESs). A promising approach for assessing the impacts of climate extremes is based on the concept of social-ecological resilience (SER), which defines the capacity of a SES to delay the impact, reduce the severity of the impact and enhance recovery from it. The operationalization of the SER concept requires the integration of ecological resilience and of transformational processes of society. In this chapter, we provide examples from five transdisciplinary research projects, in which social and natural scientists have been involved, with a high degree of participation of nonacademic actors. We show how the resilience of coupled SESs is affected by climate extremes in different ways and how a transformation toward future SES and enhanced SER can be achieved. We show that, generally, diversification of ecosystems as well as of societal processes such as ecosystem management and communication strategies is an asset for increased resilience of SES to climate extremes.
Published: 2020
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27. Climate Extreme Versus Carbon Extreme: Responses of Terrestrial Carbon Fluxes to Temperature and Precipitation

Author: Katja Frieler, Sebastian Ostberg, Jia Yang, Kazuya Nishina, Christopher P. O. Reyer, Thomas Hickler, Louis François, Hao Shi, Akihiko Ito, Philippe Ciais, Jinfeng Chang, Shufen Pan, Sibyll Schaphoff, Fang Zhao, Hanqin Tian, Jörg Steinkamp, Bojie Fu, Auburn University (AU), Mississippi State University [Mississippi], Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences [Beijing] (CAS), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), ICOS-ATC (ICOS-ATC), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université de Liège, Potsdam Institute for Climate Impact Research (PIK), State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Senckenberg Biodiversity and Climate Research Centre (SBiK-F), Goethe-Universität Frankfurt am Main-Senckenberg – Leibniz Institution for Biodiversity and Earth System Research - Senckenberg Gesellschaft für Naturforschung, Leibniz Association-Leibniz Association, National Institute for Environmental Studies (NIES), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), and Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)
Subjects: Atmospheric Science, 010504 meteorology & atmospheric sciences, Soil Science, chemistry.chemical_element, Weather and climate, Aquatic Science, Atmospheric sciences, 01 natural sciences, [SDV.EE.ECO]Life Sciences [q-bio]/Ecology, environment/Ecosystems, Ecosystem, Precipitation, 0105 earth and related environmental sciences, Water Science and Technology, Ecology, Paleontology, Biosphere, Primary production, Forestry, 15. Life on land, Arid, chemistry, Productivity (ecology), 13. Climate action, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, Environmental science, Carbon
Abstract: International audience; Carbon fluxes at the land-atmosphere interface are strongly influenced by weather and climate conditions. Yet what is usually known as “climate extremes” does not always translate into very high or low carbon fluxes or so-called “carbon extremes.” To reveal the patterns of how climate extremes influence terrestrial carbon fluxes, we analyzed the interannual variations in ecosystem carbon fluxes simulated by the Terrestrial Biosphere Models (TBMs) in the Inter-Sectoral Impact Model Intercomparison Project. At the global level, TBMs simulated reduced ecosystem net primary productivity (NPP; 18.5 ± 9.3 g C m−2 yr−1), but enhanced heterotrophic respiration (Rh; 7 ± 4.6 g C m−2 yr−1) during extremely hot events. TBMs also simulated reduced NPP (60.9 ± 24.4 g C m−2 yr−1) and reduced Rh (16.5 ± 11.4 g C m−2 yr−1) during extreme dry events. Influences of precipitation extremes on terrestrial carbon uptake were larger in the arid/semiarid zones than other regions. During hot extremes, ecosystems in the low latitudes experienced a larger reduction in carbon uptake. However, a large fraction of carbon extremes did not occur in concert with either temperature or precipitation extremes. Rather these carbon extremes are likely to be caused by the interactive effects of the concurrent temperature and precipitation anomalies. The interactive effects showed considerable spatial variations with the largest effects on NPP in South America and Africa. Additionally, TBMs simulated a stronger sensitivity of ecosystem productivity to precipitation than satellite estimates. This study provides new insights into the complex ecosystem responses to climate extremes, especially the emergent properties of carbon dynamics resulting from compound climate extremes.
Published: 2020
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28. Direct and seasonal legacy effects of the 2018 heat wave and drought on European ecosystem productivity

Author: Julia Pongratz, Atul K. Jain, P. Ciais, Markus Reichstein, Tammas Loughran, Pierre Friedlingstein, Peter Anthoni, Jean-Pierre Wigneron, Zheng Fu, Almut Arneth, Sebastian Lienert, Patrick C. McGuire, Lei Fan, Ana Bastos, Jürgen Knauer, Hanqin Tian, Sönke Zaehle, Emilie Joetzjer, Nicolas Viovy, Stephen Sitch, Ulrich Weber, Vanessa Haverd, Ludwig Maximilian University [Munich] (LMU), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), ICOS-ATC (ICOS-ATC), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), College of Engineering, Mathematics and Physical Sciences [Exeter] (EMPS), University of Exeter, Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Potsdam Institute for Climate Impact Research (PIK), Department of Global Ecology [Carnegie] (DGE), Carnegie Institution for Science, Max Planck Institute for Meteorology (MPI-M), Max-Planck-Gesellschaft, Ludwig-Maximilians-Universität München (LMU), Interactions Sol Plante Atmosphère (UMR ISPA), Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut für Meteorologie und Klimaforschung - Atmosphärische Umweltforschung (IMK-IFU), Karlsruher Institut für Technologie (KIT), Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), University of Illinois at Urbana-Champaign [Urbana], University of Illinois System, Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Climate and Environmental Physics [Bern] (CEP), Physikalisches Institut [Bern], Universität Bern [Bern] (UNIBE)-Universität Bern [Bern] (UNIBE), Department of Meteorology [Reading], University of Reading (UOR), Auburn University (AU), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), Carnegie Institution for Science [Washington], Météo France-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), and Universität Bern [Bern]-Universität Bern [Bern]
Subjects: 010504 meteorology & atmospheric sciences, Summer heat, 530 Physics, 010501 environmental sciences, Atmospheric sciences, 01 natural sciences, Sink (geography), Ecosystem carbon, ddc:550, Ecosystem, [SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology, Water content, Research Articles, 0105 earth and related environmental sciences, 2. Zero hunger, Climatology, geography, Multidisciplinary, geography.geographical_feature_category, Ecology, fungi, SciAdv r-articles, food and beverages, Vegetation composition, 15. Life on land, Heat wave, Earth sciences, 13. Climate action, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, Environmental science, Research Article
Abstract: Ecosystems responded asymmetrically to the 2018 European drought., In summer 2018, central and northern Europe were stricken by extreme drought and heat (DH2018). The DH2018 differed from previous events in being preceded by extreme spring warming and brightening, but moderate rainfall deficits, yet registering the fastest transition between wet winter conditions and extreme summer drought. Using 11 vegetation models, we show that spring conditions promoted increased vegetation growth, which, in turn, contributed to fast soil moisture depletion, amplifying the summer drought. We find regional asymmetries in summer ecosystem carbon fluxes: increased (reduced) sink in the northern (southern) areas affected by drought. These asymmetries can be explained by distinct legacy effects of spring growth and of water-use efficiency dynamics mediated by vegetation composition, rather than by distinct ecosystem responses to summer heat/drought. The asymmetries in carbon and water exchanges during spring and summer 2018 suggest that future land-management strategies could influence patterns of summer heat waves and droughts under long-term warming.
Published: 2020
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29. Emergent constraint on crop yield response to warmer temperature from field experiments

Author: Joshua Elliott, Chuang Zhao, Christoph Müller, S. L. Piao, Senthold Asseng, Ivan A. Janssens, Xuhui Wang, Philippe Ciais, Laurent Li, Yao Huang, Josep Peñuelas, Tao Li, Chenzhi Wang, Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University [Beijing], Potsdam Institute for Climate Impact Research (PIK), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), ICOS-ATC (ICOS-ATC), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), UNIVERSITY OF ANTWERP DEPARTMENT OF BIOLOGY WILRIJK BEL, Partenaires IRSTEA, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Centre de Recerca Ecològica i Aplicacions Forestals, Univ. Autònoma de Barcelona (CREAF), université de Barcelone, Global Ecology Unit CREAF-CEAB-CSIC, Universitat Autònoma de Barcelona (UAB), University of Florida [Gainesville] (UF), University of Chicago Computation Institute, University of Chicago, Institute of Botany of the Chinese Academy of Sciences (IBCAS), Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Institute of Tibetan Plateau Research Chinese Academy of Sciences P.O. Box 2871, 18 Shuang Qing Road Beijing 100085, China (J.L.-Z.) (INSTITUTE OF TIBETAN PLATEAU RESEARCH), Institute of Tibetan Plateau Research, 2019YFA0607300 Chinese Academy of Sciences, CAS, This study was supported by the National Key Research & Development Program of China (2019YFA0607300) and Strategic Priority Research Program (A) of the Chinese Academy of Sciences (grant no. XDA20050101)., Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), École normale supérieure - Paris (ENS-PSL), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL)
Subjects: 010504 meteorology & atmospheric sciences, Yield (finance), Geography, Planning and Development, Climate change, Management, Monitoring, Policy and Law, 01 natural sciences, Crop, 03 medical and health sciences, Still face, Constraint (mathematics), Biology, 030304 developmental biology, 0105 earth and related environmental sciences, Nature and Landscape Conservation, 2. Zero hunger, 0303 health sciences, Global and Planetary Change, Ecology, Renewable Energy, Sustainability and the Environment, Impact assessment, Crop yield, Global warming, food and beverages, 15. Life on land, Urban Studies, Chemistry, Agronomy, 13. Climate action, [SDU]Sciences of the Universe [physics], Environmental science, Engineering sciences. Technology, Food Science
Abstract: Responses of global crop yields to warmer temperatures are fundamental to sustainable development under climate change but remain uncertain. Here, we combined a global dataset of field warming experiments (48 sites) for wheat, maize, rice and soybean with gridded global crop models to produce field-data-constrained estimates on responses of crop yield to changes in temperature (S-T) with the emergent-constraint approach. Our constrained estimates show with >95% probability that warmer temperatures would reduce yields for maize (-7.1 +/- 2.8% K-1), rice (-5.6 +/- 2.0% K-1) and soybean (-10.6 +/- 5.8% K-1). For wheat,S(T)was 89% likely to be negative (-2.9 +/- 2.3% K-1). Uncertainties associated with modelledS(T)were reduced by 12-54% for the four crops but data constraints do not allow for further disentanglingS(T)of different crop types. A key implication for impact assessments after the Paris Agreement is that direct warming impacts alone will reduce major crop yields by 3-13% under 2 K global warming without considering CO(2)fertilization effects and adaptations. Even if warming was limited to 1.5 K, all major producing countries would still face notable warming-induced yield reduction. This yield loss could be partially offset by projected benefits from elevated CO2, whose magnitude remains uncertain, and highlights the challenge to compensate it by autonomous adaptation. Global responses of crops to warmer temperatures will affect agricultural sustainability. This study of maize, rice, soybean and wheat projects yield reductions of 3-13% under 2 degrees C warming.
Published: 2020
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30. Global Carbon Budget 2019

Author: P. Friedlingstein, M. W. Jones, M. O'Sullivan, R. M. Andrew, J. Hauck, G. P. Peters, W. Peters, J. Pongratz, S. Sitch, C. Le Quéré, D. C. E. Bakker, J. G. Canadell, P. Ciais, R. B. Jackson, P. Anthoni, L. Barbero, A. Bastos, V. Bastrikov, M. Becker, L. Bopp, E. Buitenhuis, N. Chandra, F. Chevallier, L. P. Chini, K. I. Currie, R. A. Feely, M. Gehlen, D. Gilfillan, T. Gkritzalis, D. S. Goll, N. Gruber, S. Gutekunst, I. Harris, V. Haverd, R. A. Houghton, G. Hurtt, T. Ilyina, A. K. Jain, E. Joetzjer, J. O. Kaplan, E. Kato, K. Klein Goldewijk, J. I. Korsbakken, P. Landschützer, S. K. Lauvset, N. Lefèvre, A. Lenton, S. Lienert, D. Lombardozzi, G. Marland, P. C. McGuire, J. R. Melton, N. Metzl, D. R. Munro, J. E. M. S. Nabel, S.-I. Nakaoka, C. Neill, A. M. Omar, T. Ono, A. Peregon, D. Pierrot, B. Poulter, G. Rehder, L. Resplandy, E. Robertson, C. Rödenbeck, R. Séférian, J. Schwinger, N. Smith, P. P. Tans, H. Tian, B. Tilbrook, F. N. Tubiello, G. R. van der Werf, A. J. Wiltshire, S. Zaehle, College of Engineering, Mathematics and Physical Sciences [Exeter] (EMPS), University of Exeter, Tyndall Centre for Climate Change Research, University of East Anglia [Norwich] (UEA), New Zealand Centre for Ecological Economics (NZCEE), Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung (AWI), Center for International Climate and Environmental Research [Oslo] (CICERO), University of Oslo (UiO), Wageningen University and Research [Wageningen] (WUR), Department of Global Ecology [Carnegie] (DGE), Carnegie Institution for Science, College of Life and Environmental Sciences [Exeter], School of Environmental Sciences [Norwich], Oceans and Atmosphere Flagship (CSIRO), CSIRO Oceans and Atmosphere Flagship, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), ICOS-ATC (ICOS-ATC), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Woods Hole Oceanographic Institution (WHOI), Karlsruhe Institute of Technology (KIT), Cooperative Institute for Marine and Atmospheric Studies (CIMAS), Rosenstiel School of Marine and Atmospheric Science (RSMAS), University of Miami [Coral Gables]-University of Miami [Coral Gables], Department of Geography [München], Ludwig-Maximilians-Universität München (LMU), Bjerknes Centre for Climate Research (BCCR), Department of Biological Sciences [Bergen] (BIO / UiB), University of Bergen (UiB)-University of Bergen (UiB), Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Physical Research Laboratory [Ahmedabad] (PRL), Indian Space Research Organisation (ISRO), Modélisation INVerse pour les mesures atmosphériques et SATellitaires (SATINV), Department of Geographical Sciences, University of Maryland [College Park], University of Maryland System-University of Maryland System, National Institute of Water and Atmospheric Research [Wellington] (NIWA), NOAA Pacific Marine Environmental Laboratory [Seattle] (PMEL), National Oceanic and Atmospheric Administration (NOAA), Modelling the Earth Response to Multiple Anthropogenic Interactions and Dynamics (MERMAID), Flanders Marine Institute, VLIZ, Institute of Geophysics and Planetary Physics [Los Angeles] (IGPP), University of California [Los Angeles] (UCLA), University of California (UC)-University of California (UC), Commonwealth Scientific and Industrial Research Organisation (CSIRO), Max Planck Institute for Meteorology (MPI-M), Max-Planck-Gesellschaft, Department of Atmospheric Sciences [Urbana], University of Illinois at Urbana-Champaign [Urbana], University of Illinois System-University of Illinois System, Montana State University (MSU), University of Oxford, Oxford, United Kingdom, The Institute of Applied Energy (IAE), PBL Netherlands Environmental Assessment Agency, Max-Planck-Institut für Meteorologie (MPI-M), Austral, Boréal et Carbone (ABC), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Climate and Environmental Physics [Bern] (CEP), Physikalisches Institut [Bern], Universität Bern [Bern] (UNIBE)-Universität Bern [Bern] (UNIBE), National Center for Atmospheric Research [Boulder] (NCAR), Environment and Climate Change Canada, Cycles biogéochimiques marins : processus et perturbations (CYBIOM), University of Wisconsin Whitewater, National Institute for Environmental Studies (NIES), National Institute of Advanced Industrial Science and Technology (AIST), Finnish Environment Institute (SYKE), Princeton University, Met Office Hadley Centre for Climate Change (MOHC), United Kingdom Met Office [Exeter], Max Planck Institute for Biogeochemistry (MPI-BGC), Shandong Agricultural University (SDAU), Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), Food and Agriculture Organization of the United Nations, Regional Office for the Near East and North Africa (FAO), Food and Agriculture Organization of the United Nations [Rome, Italie] (FAO), Faculty of Earth and Life Sciences [Amsterdam] (FALW), Vrije Universiteit Amsterdam [Amsterdam] (VU), Potsdam Institute for Climate Impact Research (PIK), Carnegie Institution for Science [Washington], Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), University of California-University of California, Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Universität Bern [Bern]-Universität Bern [Bern], Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Institut de Recherche pour le Développement (IRD)-Muséum national d'Histoire naturelle (MNHN)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Institut de Recherche pour le Développement (IRD)-Muséum national d'Histoire naturelle (MNHN)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU), Department of Global Ecology [Carnegie Institution], College of Life and Environmental Sciences, University of Exeter, National Institute of Water & Atmospheric Research, Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), ARVE, Sorbonne Université (SU)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD), Food and Agriculture Organization of the United Nations, Met Office Hadley Centre (MOHC), Biogeochemical Systems Department [Jena], Max-Planck-Gesellschaft-Max-Planck-Gesellschaft, Isotope Research, Earth Sciences, and Amsterdam Sustainability Institute
Subjects: Meteorologie en Luchtkwaliteit, ENVIRONMENT SIMULATOR JULES, 010504 meteorology & atmospheric sciences, 010501 environmental sciences, Atmospheric sciences, 01 natural sciences, chemistry.chemical_compound, SDG 13 - Climate Action, Land use, land-use change and forestry, Computer science, information & general works, DIOXIDE EMISSIONS, ComputingMilieux_MISCELLANEOUS, SURFACE-OCEAN, lcsh:Environmental sciences, ddc:910, lcsh:GE1-350, EARTH SYSTEM MODEL, FOSSIL-FUEL, lcsh:QE1-996.5, Biosphere, Carbon dioxide, Meteorology and Air Quality, 530 Physics, [SDE.MCG]Environmental Sciences/Global Changes, Earth and Planetary Sciences(all), chemistry.chemical_element, [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph], Carbon cycle, ANTHROPOGENIC CO2 UPTAKE, Deforestation, Life Science, SDG 14 - Life Below Water, ATMOSPHERIC CO2, 0105 earth and related environmental sciences, LAND-COVER CHANGE, WIMEK, Land use, business.industry, Fossil fuel, LEAF-AREA INDEX, 15. Life on land, lcsh:Geology, OCEAN BIOGEOCHEMICAL MODEL, TheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGES, chemistry, 13. Climate action, ddc:000, General Earth and Planetary Sciences, Environmental science, business, Carbon
Abstract: Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the “global carbon budget” – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFF) are based on energy statistics and cement production data, while emissions from land use change (ELUC), mainly deforestation, are based on land use and land use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2009–2018), EFF was 9.5±0.5 GtC yr−1, ELUC 1.5±0.7 GtC yr−1, GATM 4.9±0.02 GtC yr−1 (2.3±0.01 ppm yr−1), SOCEAN 2.5±0.6 GtC yr−1, and SLAND 3.2±0.6 GtC yr−1, with a budget imbalance BIM of 0.4 GtC yr−1 indicating overestimated emissions and/or underestimated sinks. For the year 2018 alone, the growth in EFF was about 2.1 % and fossil emissions increased to 10.0±0.5 GtC yr−1, reaching 10 GtC yr−1 for the first time in history, ELUC was 1.5±0.7 GtC yr−1, for total anthropogenic CO2 emissions of 11.5±0.9 GtC yr−1 (42.5±3.3 GtCO2). Also for 2018, GATM was 5.1±0.2 GtC yr−1 (2.4±0.1 ppm yr−1), SOCEAN was 2.6±0.6 GtC yr−1, and SLAND was 3.5±0.7 GtC yr−1, with a BIM of 0.3 GtC. The global atmospheric CO2 concentration reached 407.38±0.1 ppm averaged over 2018. For 2019, preliminary data for the first 6–10 months indicate a reduced growth in EFF of +0.6 % (range of −0.2 % to 1.5 %) based on national emissions projections for China, the USA, the EU, and India and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. Overall, the mean and trend in the five components of the global carbon budget are consistently estimated over the period 1959–2018, but discrepancies of up to 1 GtC yr−1 persist for the representation of semi-decadal variability in CO2 fluxes. A detailed comparison among individual estimates and the introduction of a broad range of observations shows (1) no consensus in the mean and trend in land use change emissions over the last decade, (2) a persistent low agreement between the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) an apparent underestimation of the CO2 variability by ocean models outside the tropics. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set (Le Quéré et al., 2018a, b, 2016, 2015a, b, 2014, 2013). The data generated by this work are available at https://doi.org/10.18160/gcp-2019 (Friedlingstein et al., 2019).
Published: 2019
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31. The PROFOUND database for evaluating vegetation models and simulating climate impacts on forests

Author: Christopher P. O. Reyer, Ramiro Silveyra Gonzalez, Klara Dolos, Florian Hartig, Ylva Hauf, Matthias Noack, Petra Lasch-Born, Thomas Rötzer, Hans Pretzsch, Henning Mesenburg, Stefan Fleck, Markus Wagner, Andreas Bolte, Tanja G. M. Sanders, Pasi Kolari, Annikki Mäkelä, Timo Vesala, Ivan Mammarella, Jukka Pumpanen, Alessio Collalti, Carlo Trotta, Giorgio Matteucci, Ettore D'Andrea, Lenka Foltýnová, Jan Krejza, Andreas Ibrom, Kim Pilegaard, Denis Loustau, Jean-Marc Bonnefond, Paul Berbigier, Delphine Picart, Sébastien Lafont, Michael Dietze, David Cameron, Massimo Vieno, Hanqin Tian, Alicia Palacios-Orueta, Victor Cicuendez, Laura Recuero, Klaus Wiese, Matthias Büchner, Stefan Lange, Jan Volkholz, Hyungjun Kim, Graham P. Weedon, Justin Sheffield, Iliusi Vega del Valle, Felicitas Suckow, Joanna A. Horemans, Simon Martel, Friedrich Bohn, Jörg Steinkamp, Alexander Chikalanov, Mats Mahnken, Martin Gutsch, Katja Frieler, Potsdam Institute for Climate Impact Research (PIK), Karlsruhe Institute of Technology (KIT), University of Regensburg, Fachagentur Nachwachsende Rohstoffe, Partenaires INRAE, Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne] (TUM), Research Institute, Thunen Institute of Forest Ecosystems, Thünen Institute, University of Helsinki, University of Eastern Finland, Institute for agriculture and forestry systems in the Mediterranean (CNR-ISAFOM), Tuscia University, Global Change Research Institute CAS, Technical University of Denmark [Lyngby] (DTU), Interactions Sol Plante Atmosphère (UMR ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), Boston University [Boston] (BU), Centre for Ecology and Hydrology, Auburn University (AU), Technical University of Madrid, The University of Tokyo (UTokyo), Met Office Hadley Centre for Climate Change (MOHC), United Kingdom Met Office [Exeter], Princeton University, University of Antwerp (UA), Helmholtz Zentrum für Umweltforschung = Helmholtz Centre for Environmental Research (UFZ), Senckenberg Biodiversity and Climate Research Centre (SBiK-F), Goethe-Universität Frankfurt am Main-Senckenberg – Leibniz Institution for Biodiversity and Earth System Research - Senckenberg Gesellschaft für Naturforschung, Leibniz Association-Leibniz Association, and University of Library Study and Information Technology
Subjects: 0106 biological sciences, 13. Climate action, [SDV]Life Sciences [q-bio], 010604 marine biology & hydrobiology, 15. Life on land, 010603 evolutionary biology, 01 natural sciences
Abstract: Process-based vegetation models are widely used to predict local and global ecosystem dynamics and climate change impacts. Due to their complexity, they require careful parameterization and evaluation to ensure that projections are accurate and reliable. The PROFOUND Database (PROFOUND DB) provides a wide range of empirical data to calibrate and evaluate vegetation models that simulate climate impacts at the forest stand scale. A particular advantage of this database is its wide coverage of multiple data sources at different hierarchical and temporal scales, together with environmental driving data as well as the latest climate scenarios. Specifically, the PROFOUND DB provides general site descriptions, soil, climate, CO2, nitrogen deposition, tree and forest stand-level, as well as remote sensing data for nine contrasting forest stands distributed across Europe. Moreover, for a subset of five sites, time series of carbon fluxes, atmospheric heat conduction, and soil water are also available. The climate and nitrogen deposition data contain several datasets for the historic period and a wide range of future climate change scenarios following the Representative Concentration Pathways (RCP2.6, RCP4.5, RCP6.0, RCP8.5). We also provide pre-industrial climate simulations that allow for model runs aimed at disentangling the contribution of climate change to observed forest productivity changes. The PROFOUND DB is available freely as a SQLite relational database or ASCII flat file version (at https://doi.org/10.5880/PIK.2019.008). The data policies of the individual, contributing datasets are provided in the metadata of each data file. The PROFOUND DB can also be accessed via the ProfoundData R-package (https://github.com/COST-FP1304-PROFOUND/ProfoundData), which provides basic functions to explore, plot, and extract the data for model set-up, calibration and evaluation.
Published: 2019
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32. Human and climate global-scale imprint on sediment transfer during the Holocene

Author: Jean-Philippe Jenny, Irene Gregory-Eaves, Sujan Koirala, Alexandre Normandeau, Nuno Carvalhais, Bernd Zolitschka, Pierre Francus, Bernhard Ahrens, Antti E.K. Ojala, Alexandre Baud, Victor Brovkin, Christoph Niemann, Centre Eau Terre Environnement [Québec] (INRS - ETE), Institut National de la Recherche Scientifique [Québec] (INRS), Department of Biogeochemical Integration [Jena], Max Planck Institute for Biogeochemistry (MPI-BGC), Max-Planck-Gesellschaft-Max-Planck-Gesellschaft, McGill University = Université McGill [Montréal, Canada], Potsdam Institute for Climate Impact Research (PIK), Aix-Marseille Université - Faculté de médecine (AMU MED), Aix Marseille Université (AMU), Geological Survey of Finland = Geologian tutkimuskeskus tuottaa (GKT), Geological Survey of Canada [Québec] (GSC Québec), Geological Survey of Canada - Office (GSC), Natural Resources Canada (NRCan)-Natural Resources Canada (NRCan), University of Bremen, AXA Research Fund, Canada Research Chairs, Natural Sciences and Engineering Research Council of Canada, McGill University, Geological Survey of Finland, and DCEA - Departamento de Ciências e Engenharia do Ambiente
Subjects: FLUX, Global soil erosion, 010506 paleontology, Biogeochemical cycle, EROSION, 010504 meteorology & atmospheric sciences, [SDV]Life Sciences [q-bio], C ages, Land cover, Lake records, 01 natural sciences, varved sediments, C-14 ages, Pollens, SDG 13 - Climate Action, RATES, 14. Life underwater, General, Holocene, 0105 earth and related environmental sciences, SDG 15 - Life on Land, Multidisciplinary, Aquatic ecosystem, Sediment, Varved sediments, 14C ages, 15. Life on land, Sedimentation, lake records, 13. Climate action, Earth and Environmental Sciences, LAKE-SEDIMENTS, Physical Sciences, Erosion, Environmental science, pollens, Physical geography, Water quality, global soil erosion, Environmental Sciences
Abstract: Significance Using a compilation of 14C and pollen data of lake sediment records from over 632 sites globally, we identified the timings of first increase in lake sedimentation. Changes in lake sediment rates at this time are closely linked to increased sediment supply from hillslope erosion. The analysis on the relative roles of the driving factors indicated that a significant portion of the Earth’s surface shifted to human-driven soil erosion already 4,000 y ago following land deforestation. The long-term perspective afforded by this synthesis provides evidence that human beings are a geological force that have altered lateral soil and sediment transfers globally well before the great acceleration in human activity post-World War II and before the start of the Industrial Revolution., Accelerated soil erosion has become a pervasive feature on landscapes around the world and is recognized to have substantial implications for land productivity, downstream water quality, and biogeochemical cycles. However, the scarcity of global syntheses that consider long-term processes has limited our understanding of the timing, the amplitude, and the extent of soil erosion over millennial time scales. As such, we lack the ability to make predictions about the responses of soil erosion to long-term climate and land cover changes. Here, we reconstruct sedimentation rates for 632 lakes based on chronologies constrained by 3,980 calibrated 14C ages to assess the relative changes in lake-watershed erosion rates over the last 12,000 y. Estimated soil erosion dynamics were then complemented with land cover reconstructions inferred from 43,669 pollen samples and with climate time series from the Max Planck Institute Earth System Model. Our results show that a significant portion of the Earth surface shifted to human-driven soil erosion rate already 4,000 y ago. In particular, inferred soil erosion rates increased in 35% of the watersheds, and most of these sites showed a decrease in the proportion of arboreal pollen, which would be expected with land clearance. Further analysis revealed that land cover change was the main driver of inferred soil erosion in 70% of all studied watersheds. This study suggests that soil erosion has been altering terrestrial and aquatic ecosystems for millennia, leading to carbon (C) losses that could have ultimately induced feedbacks on the climate system.
Published: 2019
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33. Parameterization-induced uncertainties and impacts of crop management harmonization in a global gridded crop model ensemble

Author: Alex C. Ruane, Joshua Elliott, Roberto C. Izaurralde, Nikolay Khabarov, Peter Lawrence, James P. Chryssanthacopoulos, Philippe Ciais, Christoph Müller, Almut Arneth, Thomas A. M. Pugh, Xuhui Wang, Juraj Balkovic, Wenfeng Liu, Erwin Schmid, Stefan Olin, Hong Yang, Delphine Deryng, Curtis D. Jones, Rastislav Skalský, Christian Folberth, Ashwan Reddy, Department of Geography, University of Liverpool, University of Chicago, Potsdam Institute for Climate Impact Research (PIK), Ecosystem Services and Management Program, International Institute for Applied Systems Analysis (IIASA), Center for Climate Systems Research [New York] (CCSR), Columbia University [New York], Department of Geographical Sciences [College Park], University of Maryland [College Park], University of Maryland System-University of Maryland System, International Institute for Applied Systems Analysis [Laxenburg] (IIASA), Universität für Bodenkultur Wien [Vienne, Autriche] (BOKU), Soil Science and Conservation Research Institute, Institut für Meteorologie und Klimaforschung - Atmosphärische Umweltforschung (IMK-IFU), Karlsruher Institut für Technologie (KIT), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), ICOS-ATC (ICOS-ATC), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Tyndall Centre for Climate Change Research, University of East Anglia [Norwich] (UEA), Groupe Immunité des Muqueuses et Agents Pathogènes (GIMAP), Université Jean Monnet [Saint-Étienne] (UJM), Department of Physical Geography and Ecosystem Science, Lund University, Institute for Meteorology and Climate Research (IMK), Karlsruhe Institute of Technology (KIT), NASA Goddard Institute for Space Studies (GISS), NASA Goddard Space Flight Center (GSFC), Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-École des Ponts ParisTech (ENPC)-École polytechnique (X)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC), Universität für Bodenkultur Wien = University of Natural Resources and Life [Vienne, Autriche] (BOKU), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université Jean Monnet - Saint-Étienne (UJM), Lund University [Lund], Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)
Subjects: 010504 meteorology & atmospheric sciences, Climate, Plant Science, 01 natural sciences, Soil, Agricultural Soil Science, Edaphology, Econometrics, ddc:550, Plant Growth and Development, 2. Zero hunger, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Multidisciplinary, Uncertainty, Eukaryota, Agriculture, 04 agricultural and veterinary sciences, Plants, Crop Production, Experimental Organism Systems, Agricultural soil science, Erosion, Soil horizon, Medicine, Core model, Agrochemicals, Research Article, Crops, Agricultural, Science, Soil Science, Crops, Research and Analysis Methods, Model Organisms, Hydrology (agriculture), Plant and Algal Models, Grasses, Fertilizers, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, 0105 earth and related environmental sciences, Models, Statistical, Impact assessment, Crop yield, Ecology and Environmental Sciences, Organisms, Biology and Life Sciences, Geomorphology, 15. Life on land, Crop Management, Maize, Earth sciences, 13. Climate action, Animal Studies, Earth Sciences, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Environmental science, Scale (map), Crop Science, Developmental Biology
Abstract: Global gridded crop models (GGCMs) combine agronomic or plant growth models with gridded spatial input data to estimate spatially explicit crop yields and agricultural externalities at the global scale. Differences in GGCM outputs arise from the use of different biophysical models, setups, and input data. GGCM ensembles are frequently employed to bracket uncertainties in impact studies without investigating the causes of divergence in outputs. This study explores differences in maize yield estimates from five GGCMs based on the public domain field-scale model Environmental Policy Integrated Climate (EPIC) that participate in the AgMIP Global Gridded Crop Model Intercomparison initiative. Albeit using the same crop model, the GGCMs differ in model version, input data, management assumptions, parameterization, and selection of subroutines affecting crop yield estimates via cultivar distributions, soil attributes, and hydrology among others. The analyses reveal inter-annual yield variability and absolute yield levels in the EPIC-based GGCMs to be highly sensitive to soil parameterization and crop management. All GGCMs show an intermediate performance in reproducing reported yields with a higher skill if a static soil profile is assumed or sufficient plant nutrients are supplied. An in-depth comparison of setup domains for two EPIC-based GGCMs shows that GGCM performance and plant stress responses depend substantially on soil parameters and soil process parameterization, i.e. hydrology and nutrient turnover, indicating that these often neglected domains deserve more scrutiny. For agricultural impact assessments, employing a GGCM ensemble with its widely varying assumptions in setups appears the best solution for coping with uncertainties from lack of comprehensive global data on crop management, cultivar distributions and coefficients for agro-environmental processes. However, the underlying assumptions require systematic specifications to cover representative agricultural systems and environmental conditions. Furthermore, the interlinkage of parameter sensitivity from various domains such as soil parameters, nutrient turnover coefficients, and cultivar specifications highlights that global sensitivity analyses and calibration need to be performed in an integrated manner to avoid bias resulting from disregarded core model domains. Finally, relating evaluations of the EPIC-based GGCMs to a wider ensemble based on individual core models shows that structural differences outweigh in general differences in configurations of GGCMs based on the same model, and that the ensemble mean gains higher skill from the inclusion of structurally different GGCMs. Although the members of the wider ensemble herein do not consider crop-soil-management interactions, their sensitivity to nutrient supply indicates that findings for the EPIC-based sub-ensemble will likely become relevant for other GGCMs with the progressing inclusion of such processes.
Published: 2019
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34. Global wheat production with 1.5 and 2.0°C above pre‐industrial warming

Author: Mónica Espadafor, Bing Liu, Frank Ewert, Mukhtar Ahmed, Liujun Xiao, Thilo Streck, Senthold Asseng, Soora Naresh Kumar, Gerrit Hoogenboom, John R. Porter, Sara Minoli, Margarita Garcia-Vila, Joost Wolf, Juraj Balkovic, Alex C. Ruane, Giacomo De Sanctis, Pierre Martre, Roberto C. Izaurralde, Marijn van der Velde, Dominique Ripoche, Roberto Ferrise, Davide Cammarano, Fulu Tao, Bruno Basso, Christoph Müller, Heidi Webber, Yujing Gao, Andrea Maiorano, Christian Klein, Ann-Kristin Koehler, Andrew J. Challinor, Reimund P. Rötter, Garry O'Leary, Manuel Montesino San Martin, Eckart Priesack, Peter J. Thorburn, Heidi Horan, Kurt Christian Kersebaum, Iwan Supit, Zhigan Zhao, Taru Palosuo, Belay T. Kassie, Christian Biernath, Pramod K. Aggarwal, Katharina Waha, Sebastian Gayler, Daniel Wallach, Yan Zhu, Marco Bindi, Zhao Zhang, Claas Nendel, Enli Wang, Curtis D. Jones, Ehsan Eyshi Rezaei, Mikhail A. Semenov, Claudio O. Stöckle, Benjamin Dumont, National Science Foundation (US), National Natural Science Foundation of China, International Food Policy Research Institute (US), CGIAR (France), Institut National de la Recherche Agronomique (France), Federal Ministry of Education and Research (Germany), Biotechnology and Biological Sciences Research Council (UK), China Scholarship Council, Department of Agriculture and Water Resources (Australia), Ministero delle Politiche Agricole Alimentari e Forestali, Gorgan University, Victoria State Government, National Institute of Food and Agriculture (US), Federal Ministry of Food and Agriculture (Germany), German Research Foundation, Academy of Finland, LabEx Agro, Natural Resources Institute Finland, National Engineering and Technology Center for Information Agriculture, Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture, Jiangsu Key Laboratory for Information Agriculture, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricutural University, Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro), Institut für Nutzpflanzenwissenschaften und Ressourcenschutz (INRES), Rheinische Friedrich-Wilhelms-Universität Bonn, Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research (ZALF), Fonctionnement et conduite des systèmes de culture tropicaux et méditerranéens (UMR SYSTEM), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Montpellier (CIHEAM-IAMM), Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), University of Copenhagen = Københavns Universitet (KU), Lincoln University, University of Leeds, CGIAR-ESSP Program on Climate Change,Agriculture and Food Security, International Center for Tropical Agriculture, Potsdam Institute for Climate Impact Research (PIK), NASA Goddard Institute for Space Studies (GISS), NASA Goddard Space Flight Center (GSFC), Agriculture and Food, Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), International Maize and Wheat Improvement Centre [Inde] (CIMMYT), International Maize and Wheat Improvement Center (CIMMYT), Consultative Group on International Agricultural Research [CGIAR] (CGIAR)-Consultative Group on International Agricultural Research [CGIAR] (CGIAR), Biological Systems Engineering, Washington State University (WSU), Department of Agronomy, University of El-Tarf, International Institute for Applied Systems Analysis, Ecosystem Services and Management Program, affiliation inconnue, Comenius University in Bratislava, Department of Earth and Environmental Sciences [East Lansing], Michigan State University [East Lansing], Michigan State University System-Michigan State University System, W. K. Kellogg Biological Station (KBS), Institute of Biochemical Plant Pathology (BIOP), German Research Center for Environmental Health - Helmholtz Center München (GmbH), Department of Agrifood Production and Environmental Sciences (DISPAA), Università degli Studi di Firenze = University of Florence [Firenze] (UNIFI), The James Hutton Institute, GMO Unit, European Food Safety Authority = Autorité européenne de sécurité des aliments, Université de Liège, University of Córdoba, Department of Crop Sciences, Georg-August-University [Göttingen], Institute of Soil Science and Land Evaluation, University of Hohenheim, Department of Agricultural and Biological Engineering [Gainesville] (UF|ABE), Institute of Food and Agricultural Sciences [Gainesville] (UF|IFAS), University of Florida [Gainesville] (UF)-University of Florida [Gainesville] (UF), Food Systems Institute [Gainesville] (UF|IFAS), Department of Geographical Sciences, College Park, University of Maryland [College Park], University of Maryland System-University of Maryland System, Texas A and M AgriLife Research, Texas A&M University System, European Food Safety Authority (EFSA), Centre for Environment Science and Climate Resilient Agriculture (CESCRA), Indian Agricultural Research Institute (IARI), Agriculture Victoria Research, Institute for Natural Resources, Agroclim (AGROCLIM), Institut National de la Recherche Agronomique (INRA), Tropical Plant Production and Agricultural Systems Modelling (TROPAGS), Centre of Biodiversity and Sustainable Land Use (CBL), University of Göttingen - Georg-August-Universität Göttingen, Rothamsted Research, Wageningen University and Research Centre (WUR), Institute of geographical sciences and natural resources research, Chinese Academy of Sciences [Changchun Branch] (CAS), European Commission - Joint Research Centre [Ispra] (JRC), AGroécologie, Innovations, teRritoires (AGIR), Institut National de la Recherche Agronomique (INRA)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Plant Production Systems, Wageningen University and Research [Wageningen] (WUR), State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University (BNU), Department of Agronomy and Biotechnology, China Agricultural University (CAU), Agricultural Model Intercomparison and Improvement Project (AgMIP), and Biotechnology and Biological Sciences Research Council (BBSRC), Grant/Award Number: BB/, P016855/1
Subjects: [SDV.SA]Life Sciences [q-bio]/Agricultural sciences, 0106 biological sciences, 010504 meteorology & atmospheric sciences, Food prices, Water en Voedsel, Climate change, Atmospheric sciences, 010603 evolutionary biology, 01 natural sciences, Model ensemble, Extreme low yields, model ensemble, 1.5°C warming, Temperate climate, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, Environmental Chemistry, 0105 earth and related environmental sciences, General Environmental Science, 2. Zero hunger, Global and Planetary Change, WIMEK, Water and Food, Food security, Ecology, business.industry, wheat production, Crop yield, Global warming, food security, 15. Life on land, PE&RC, climate change, Plant Production Systems, 13. Climate action, Agriculture, Plantaardige Productiesystemen, extreme low yields, 8. Economic growth, Environmental science, Wheat production, Water Systems and Global Change, business, Cropping
Abstract: Efforts to limit global warming to below 2°C in relation to the pre‐industrial level are under way, in accordance with the 2015 Paris Agreement. However, most impact research on agriculture to date has focused on impacts of warming >2°C on mean crop yields, and many previous studies did not focus sufficiently on extreme events and yield interannual variability. Here, with the latest climate scenarios from the Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) project, we evaluated the impacts of the 2015 Paris Agreement range of global warming (1.5 and 2.0°C warming above the pre‐industrial period) on global wheat production and local yield variability. A multi‐crop and multi‐climate model ensemble over a global network of sites developed by the Agricultural Model Intercomparison and Improvement Project (AgMIP) for Wheat was used to represent major rainfed and irrigated wheat cropping systems. Results show that projected global wheat production will change by −2.3% to 7.0% under the 1.5°C scenario and −2.4% to 10.5% under the 2.0°C scenario, compared to a baseline of 1980–2010, when considering changes in local temperature, rainfall, and global atmospheric CO2 concentration, but no changes in management or wheat cultivars. The projected impact on wheat production varies spatially; a larger increase is projected for temperate high rainfall regions than for moderate hot low rainfall and irrigated regions. Grain yields in warmer regions are more likely to be reduced than in cooler regions. Despite mostly positive impacts on global average grain yields, the frequency of extremely low yields (bottom 5 percentile of baseline distribution) and yield inter‐annual variability will increase under both warming scenarios for some of the hot growing locations, including locations from the second largest global wheat producer—India, which supplies more than 14% of global wheat. The projected global impact of warming, We thank the Agricultural Model Intercomparison and Improvement Project (AgMIP) for support. B.L., L.X., and Y.Z. were supported by the National Science Foundation for Distinguished Young Scholars (31725020), the National Natural Science Foundation of China (31801260, 51711520319, and 31611130182), the Natural Science Foundation of Jiangsu province (BK20180523), the 111 Project (B16026), and the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD). S.A. and B.K. received support from the International Food Policy Research Institute (IFPRI) through the Global Futures and Strategic Foresight project, the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), and the CGIAR Research Program on Wheat. P.M, D.R., and D.W. acknowledge support from the FACCE JPI MACSUR project (031A103B) through the metaprogram Adaptation of Agriculture and Forests to Climate Change (AAFCC) of the French National Institute for Agricultural Research (INRA). F.T. and Z.Z. were supported by the National Natural Science Foundation of China (41571088, 41571493, 31761143006, and 31561143003). R.R. acknowledges support from the German Federal Ministry for Research and Education (BMBF) through project “Limpopo Living Landscapes” project (SPACES program; grant number 01LL1304A). Rothamsted Research receives grant‐aided support from the Biotechnology and Biological Sciences Research Council (BBSRC) Designing Future Wheat project [BB/P016855/1]. L.X. and Y.G. acknowledge support from the China Scholarship Council. M.B and R.F. were funded by JPI FACCE MACSUR2 through the Italian Ministry for Agricultural, Food and Forestry Policies and thank A. Soltani from Gorgan Univ. of Agric. Sci. & Natur. Resour for his support. K.C.K. and C.N. received support from the German Ministry for Research and Education (BMBF) within the FACCE JPI MACSUR project. S.M. and C.M. acknowledge financial support from the MACMIT project (01LN1317A) funded through BMBF. G.J.O. acknowledges support from the Victorian Department of Economic Development, Jobs, Transport and Resources, the Australian Department of Agriculture and Water Resources. P.K.A. was supported by the multiple donors contributing to the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS). B.B. received financial support from USDA NIFA‐Water Cap Award 2015‐68007‐23133. F.E. acknowledges support from the FACCE JPI MACSUR project through the German Federal Ministry of Food and Agriculture (2815ERA01J) and from the German Science Foundation (project EW 119/5‐1). J.R.P. acknowledges the support of the Labex Agro (Agropolis no. 1501‐003). La. T.P. and F.T. received financial support from the Academy of Finland through the project PLUMES (decision nos. 277403 and 292836) and from Natural Resources Institute Finland through the project ClimSmartAgri.
Published: 2019
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35. Impact of extreme weather conditions on European crop production in 2018

Author: Bernhard Schauberger, P. Ciais, David Makowski, Damien Beillouin, Ana Bastos, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), ICOS-ATC (ICOS-ATC), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), ANR-16-CONV-0003,CLAND,CLAND : Changement climatique et usage des terres(2016), Fonctionnement agroécologique et performances des systèmes de cultures horticoles (UPR HORTSYS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), Potsdam Institute for Climate Impact Research (PIK), Ludwig-Maximilans Universität Munich, Mathématiques et Informatique Appliquées (MIA-Paris), and AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Subjects: 010504 meteorology & atmospheric sciences, Natural resource economics, adaptation aux changements climatiques, drought, Accident climatique, 01 natural sciences, F01 - Culture des plantes, wheat, Extreme Weather, [MATH]Mathematics [math], [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, 2. Zero hunger, Articles, 04 agricultural and veterinary sciences, Crop Production, Droughts, Europe, événements météorologiques extrêmes, Rendement des cultures, yield anomalies, [SDE]Environmental Sciences, General Agricultural and Biological Sciences, Climate extremes, Research Article, Crops, Agricultural, P40 - Météorologie et climatologie, Climate Change, Conditions météorologiques, General Biochemistry, Genetics and Molecular Biology, Production végétale, Extreme weather, Species Specificity, Crop production, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, Perte de récolte, climate extremes, 0105 earth and related environmental sciences, Crop yield, Évaluation de l'impact, Impact sur l'environnement, crop yields, 15. Life on land, Crop failure, 13. Climate action, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Environmental science, random forest
Abstract: International audience; One contribution of 16 to a theme issue 'Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'. Subject Areas: plant science, computational biology Extreme weather increases the risk of large-scale crop failure. The mechanisms involved are complex and intertwined, hence undermining the identification of simple adaptation levers to help improve the resilience of agricultural production. Based on more than 82 000 yield data reported at the regional level in 17 European countries, we assess how climate affected the yields of nine crop species. Using machine learning models, we analyzed historical yield data since 1901 and then focus on 2018, which has experienced a multi-plicity and a diversity of atypical extreme climatic conditions. Machine learning models explain up to 65% of historical yield anomalies. We find that both extremes in temperature and precipitation are associated with negative yield anomalies, but with varying impacts in different parts of Europe. In 2018, Northern and Eastern Europe experienced multiple and simultaneous crop failures-among the highest observed in recent decades. These yield losses were associated with extremely low rainfalls in combination with high temperatures between March and August 2018. However, the higher than usual yields recorded in Southern Europe-caused by favourable spring rainfall conditions-nearly offset the large decrease in Northern European crop production. Our results outline the importance of considering single and compound climate extremes to analyse the causes of yield losses in Europe. We found no clear upward or downward trend in the frequency of extreme yield losses for any of the considered crops between 1990 and 2018. This article is part of the theme issue 'Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'.
Published: 2020
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36. Phenological Model Intercomparison for Estimating Grapevine Budbreak Date (Vitis vinifera L.) in Europe

Author: Marco Bindi, José Dinis Silvestre, Jürgen Junk, Helder Fraga, Christoph Menz, Marco Moriondo, S. Costafreda-Aumedes, Camilla Dibari, Thomas Kartschall, Luisa Leolini, João A. C. Santos, Aureliano C. Malheiro, José Eduardo Eiras-Dias, Daniel Molitor, Paolo Merante, Agnès Destrac-Irvine, Cornelis van Leeuwen, Department of Agriculture, Food, Environment and Forestry (DAGRI), Università degli Studi di Firenze = University of Florence [Firenze], Centro de Investigação e de Tecnologias Agro-Ambientais e Biológicas (CITAB), University of Trás-os-Montes and Alto Douro [Portugal] (UTAD), Potsdam Institute for Climate Impact Research (PIK), Luxembourg Institute of Science and Technology (LIST), Tropical Plant Production and Agricultural Systems Modelling (TROPAGS), Georg-August-University [Göttingen], Ecophysiologie et Génomique Fonctionnelle de la Vigne (UMR EGFV), Université de Bordeaux (UB)-Institut des Sciences de la Vigne et du Vin (ISVV)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Instituto Nacional de Investigação Agrária e Veterinária (INIAV), Istituto di Biometeorologia [Firenze] (IBIMET), Consiglio Nazionale delle Ricerche (CNR), ANR: Climate change impact mitigation for European viticulture: knowledge transfer for an integrated approach,ANR-10-LABX-45, Università degli Studi di Firenze = University of Florence [Firenze] (UNIFI), Instituto Nacional de Investigação Agrária e Veterinária = National Institute for Agrarian and Veterinary Research [Oeiras, Portugal] (INIAV), and ANR-10-LABX-0045,COTE,COntinental To coastal Ecosystems: evolution, adaptability and governance(2010)
Subjects: 0106 biological sciences, dormancy, 010504 meteorology & atmospheric sciences, [SDV]Life Sciences [q-bio], Forcing (mathematics), Biology, lcsh:Technology, Forcing models, 01 natural sciences, phenology, Latitude, lcsh:Chemistry, Chilling-forcing models, forcing models, Yield (wine), Dormancy, General Materials Science, Vitis vinifera, lcsh:QH301-705.5, Instrumentation, 0105 earth and related environmental sciences, Mathematics, 2. Zero hunger, Fluid Flow and Transfer Processes, lcsh:T, Phenology, Process Chemistry and Technology, chilling-forcing models, General Engineering, 15. Life on land, lcsh:QC1-999, Computer Science Applications, Horticulture, lcsh:Biology (General), lcsh:QD1-999, lcsh:TA1-2040, [SDE]Environmental Sciences, lcsh:Engineering (General). Civil engineering (General), lcsh:Physics, 010606 plant biology & botany
Abstract: Budbreak date in grapevine is strictly dependent on temperature, and the correct simulation of its occurrence is of great interest since it may have major consequences on the final yield and quality. In this study, we evaluated the reliability for budbreak simulation of two modeling approaches, the chilling-forcing (CF), which describes the entire dormancy period (endo- and eco-dormancy) and the forcing approach (F), which only describes the eco-dormancy. For this, we selected six phenological models that apply CF and F in different ways, which were tested on budbreak simulation of eight grapevine varieties cultivated at different latitudes in Europe. Although none of the compared models showed a clear supremacy over the others, models based on CF showed a generally higher estimation accuracy than F where fixed starting dates were adopted. In the latter models, the accurate simulation of budbreak was dependent on the selection of the starting date for forcing accumulation that changes according to the latitude, whereas CF models were independent. Indeed, distinct thermal requirements were found for the grapevine varieties cultivated in Northern and Southern Europe. This implies the need to improve modeling of the dormancy period to avoid under- or over-estimations of budbreak date under different environmental conditions. This research was funded by the European Union’s Horizon 2020 Research and Innovation Programme, under the Clim4Vitis project: “Climate change impact mitigation for European viticulture: knowledge transfer for an integrated approach”, grant agreement no. 810176. It was also supported by FCT-Portuguese Foundation for Science and Technology, under the project UIDB/04033/2020 and the French National Research Agency (ANR) in the frame of the Investments for the Future Program, within the cluster of excellence COTE (ANR-10-LABX-45).
Published: 2020
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37. The dimensionality of stability depends on disturbance type

Author: Jens-Christian Svenning, Frederik De Laender, Michael Crawford, Jonathan De Raedt, Viktoriia Radchuk, Cédric Scherer, Kirsten Thonicke, Friedrich J. Bohn, Stephanie Kramer-Schadt, Juliano Sarmento Cabral, Frank M. Schurr, Volker Grimm, Isabelle Boulangeat, IZW LEIBNIZ INSTITUTE FOR ZOO AND WILDLIFE RESEARCH DEU, Partenaires IRSTEA, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Université de Namur [Namur] (UNamur), UNIVERSITY OF WURZBURG DEU, Laboratoire des EcoSystèmes et des Sociétés en Montagne (UR LESSEM), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), UNIVERSITY OF POSTDAM DEU, UFZ HELMHOLTZ CENTRE FOR ENVIRONMENTAL RESEARCH HALLE DEU, Aarhus University [Aarhus], PIK POTSDAM INSTITUTE FOR CLIMATE IMPACT RESEARCH POSTDAM DEU, UNIVERSITY OF HOHENHEIM DEU, Leibniz Institute for Zoo and Wildlife Research (IZW), Leibniz Association, Institute of Life, Earth and Environment, Evolutionary Genomics Center for Computational and Theoretical Biology (CCTB), Section for Ecoinformatics and Biodiversity, Department of Bioscience, Aarhus University, Aarhus, Denmark, Institute of Biochemistry and Biology University of Potsdam, Helmholtz Zentrum für Umweltforschung = Helmholtz Centre for Environmental Research (UFZ), Karlsruhe Institute of Technology (KIT), Laboratory of Environmental Toxicology and Aquatic Ecology, Universiteit Gent = Ghent University [Belgium] (UGENT), Potsdam Institute for Climate Impact Research (PIK), Institute of Landscape and Plant Ecology, Universität Hohenheim, German Centre for Integrative Biodiversity Research (iDiv), University of Berlin, BioMove Research Training Group of the German Research Foundation : DFG-GRK 2118/1, DFG Priority Program 1374, 'Infrastructure-Biodiversity-Exploratories' : DFG-JE 207/5-1, FWO : FWO14/ASP/075, Fonds de la Recherche Scientifique - FNRS : PDR T.0048.16, and VILLUM FONDEN : 16549
Subjects: 0106 biological sciences, Disturbance (geology), [SDV]Life Sciences [q-bio], Population Dynamics, Population, invariability, 010603 evolutionary biology, 01 natural sciences, Stability (probability), disturbance intensity, resistance, recovery, ddc:570, disturbance type, education, Ecosystem, Ecology, Evolution, Behavior and Systematics, Institut für Biochemie und Biologie, Mathematics, Trophic level, Ecological stability, education.field_of_study, Ecology, Resistance (ecology), extinction, 010604 marine biology & hydrobiology, Community model, persistence, 15. Life on land, [SDE]Environmental Sciences, Species richness, Biological system, individual-based model, Curse of dimensionality
Abstract: International audience; Ecosystems respond in various ways to disturbances. Quantifying ecological stability therefore requires inspecting multiple stability properties, such as resistance, recovery, persistence and invariability. Correlations among these properties can reduce the dimensionality of stability, simplifying the study of environmental effects on ecosystems. A key question is how the kind of disturbance affects these correlations. We here investigated the effect of three disturbance types (random, species-speciﬁc, local) applied at four intensity levels, on the dimensionality of stability at the population and community level. We used previously parameterized models that represent ﬁve natural communities, varying in species richness and the number of trophic levels. We found that disturbance type but not intensity affected the dimensionality of stability and only at the population level. The dimensionality of stability also varied greatly among species and communities. Therefore, studying stability cannot be simpliﬁed to using a single metric and multi-dimensionalassessments are still to be recommended.
Published: 2019
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38. The spatio-temporal variability of groundwater storage in the Amazon River Basin

Author: Julia Pfeffer, Javier Tomasella, Frédéric Frappart, Thaise Emilio, J. da Silva Carvalho, L. Seoane, Juliana Schietti, Marie-Paule Bonnet, Andreas Güntner, Fabrice Papa, Frédérique Seyler, D. Medeiros Moreira, Guillaume Ramillien, Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'études en Géophysique et océanographie spatiales (LEGOS), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS), Potsdam Institute for Climate Impact Research (PIK), Center for Weather Forecasting and Climate Studies [São Paulo] (CPTEC), Instituto Nacional de Pesquisas Espaciais (INPE), Institut de physique du globe de Strasbourg (IPGS), Université de Strasbourg (UNISTRA)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), GOHS, Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Géosciences Environnement Toulouse (GET), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD), Laboratoire des Mécanismes et Transfert en Géologie (LMTG), Université Toulouse III - Paul Sabatier (UT3), UMR 228 Espace-Dev, Espace pour le développement, and Université de Guyane (UG)-Université des Antilles (UA)-Institut de Recherche pour le Développement (IRD)-Université de Perpignan Via Domitia (UPVD)-Avignon Université (AU)-Université de La Réunion (UR)-Université de Montpellier (UM)
Subjects: 010504 meteorology & atmospheric sciences, Floodplain, 0208 environmental biotechnology, Hydrological models, Aquifer, 02 engineering and technology, 01 natural sciences, Hydrology (agriculture), Interdisciplinary Centre for Water Research, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, Groundwater, Amazon, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, Water Science and Technology, Hydrology, geography, geography.geographical_feature_category, Amazon rainforest, Water storage, 15. Life on land, 6. Clean water, 020801 environmental engineering, 13. Climate action, Multisatellite, Environmental science, Spatial variability, Surface water
Abstract: In large Tropical River basins such as the Amazon, groundwater plays a major role in the water and ecological cycles with large influences on the rainforest ecosystems and climate variability. However, due to the lack of monitoring networks, Amazon groundwater storage and its variability remain poorly known. Here, we provide an unprecedented direct estimate of the spatio-temporal variations of the anomaly of groundwater storage over the period January 2003 -September 2010 in the Amazon Basin by decomposing the total terrestrial water storage measured by the Gravity Recovery and Climate Experiment (GRACE) mission into the individual contributions of other hydrological reservoirs, using multi-satellite data for the surface waters and floodplains and models outputs for the soil moisture. We show that the seasonal variations of groundwater storage represent between 20 and 35% of the terrestrial water storage seasonal volume variations of the Amazon. Larger seasonal amplitudes of groundwater storage (>450 mm) are found in the Alter do Chao and Ica aquifers in the central part of the Amazon Basin. Anomalies of groundwater storage exhibit a strong interannual variability (STD reaching 120 mm along the central corridor) during the study period in response to hydrologic variability and climatic events such as the extreme drought that occurred in 2005.
Published: 2019
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39. To what extent is climate change adaptation a novel challenge for agricultural modellers?

Author: C. F. E. Topp, André Bannink, Richard P. Kipling, Pytrik Reidsma, A. del Prado, Dave J. Bartley, Renáta Sándor, Giovanna Seddaiu, Anne-Isabelle Graux, Shailesh Shrestha, J.C. van Middelkoop, Daniel L. Sandars, Raffaele Cortignani, Isabelle Weindl, Vera Eory, Gabriele Dono, Nicholas J. Hutchings, Ş. Özkan Gülzari, Isabel Blanco-Penedo, Martin Schönhart, Susanne Rolinski, Ludwig Lauwers, Philippe Faverdin, Margarita Ruiz-Ramos, Aberystwyth University, Scotland's Rural College (SCUR), Wageningen University and Research Center (WUR), Moredun Research Institute, Swedish University of Agricultural Sciences (SLU), Institute of Research and Technology, Food and Agriculture (IRTA), Tuscia University, Basque Center for Climate Change, Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage [Rennes] (PEGASE), AGROCAMPUS OUEST-Institut National de la Recherche Agronomique (INRA), Aarhus University, Flanders Research Institute for Agriculture, Fisheries and Food (ILVO), Ghent University, Norwegian University of Life Sciences (NMBU), Norwegian Institute of Bioeconomy Research (NIBIO), Postdam Institute for Climate Impact Research (PIK), Universidad Politécnica de Madrid (UPM), Cranfield University, Hungarian Academy of Sciences (MTA), University of Natural Resources and Applied Life Sciences (BOKU), Università degli Studi di Sassari, Leibniz Institute for Agricultural Engineering Potsdam-Bornim (ATB), Institut National de la Recherche Agronomique (INRA)-AGROCAMPUS OUEST, Producció Animal, Benestar Animal, Scotland's Rural College (SRUC), Wageningen University and Research [Wageningen] (WUR), Moredun Research Institute [Penicuik, UK] (MRI), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Aarhus University [Aarhus], Research Institute for Agricultural, Fisheries and Food (ILVO), Potsdam Institute for Climate Impact Research (PIK), and University of Natural Resources and Life Sciences (BOKU)
Subjects: [SDV.SA]Life Sciences [q-bio]/Agricultural sciences, Animal Nutrition, 010504 meteorology & atmospheric sciences, Computer science, DECISION-MAKING, modèle, 01 natural sciences, LIVESTOCK PRODUCTION, Climate change, agriculture, 2. Zero hunger, changement climatique, GREENHOUSE-GAS EMISSIONS, Food security, Scope (project management), VDP::Landbruks- og Fiskerifag: 900, Ecological Modeling, FOOD SECURITY, 04 agricultural and veterinary sciences, Adaptation, Agricultural modelling, Research challenges, PE&RC, Diervoeding, CHANGE IMPACTS, Agricultural sciences, Plant Production Systems, front de recherche, Climate change adaptation, Animal Breeding & Genomics, Technology and Engineering, Environmental Engineering, Progressive change, Article, modelling, DAIRY FARMS, Fokkerij & Genomica, Agricultural Science, Adaptation (computer science), Environmental planning, global change, 0105 earth and related environmental sciences, modélisation, FARM-LEVEL ADAPTATION, numerical models, LAND-USE, Land use, business.industry, CROP, 15. Life on land, ADAPTING AGRICULTURE, Agricultrual modelling, 13. Climate action, Agriculture, Earth and Environmental Sciences, Plantaardige Productiesystemen, WIAS, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, business, Sciences agricoles, Software
Abstract: Modelling is key to adapting agriculture to climate change (CC), facilitating evaluation of the impacts and efficacy of adaptation measures, and the design of optimal strategies. Although there are many challenges to modelling agricultural CC adaptation, it is unclear whether these are novel or, whether adaptation merely adds new motivations to old challenges. Here, qualitative analysis of modellers’ views revealed three categories of challenge: Content, Use, and Capacity. Triangulation of findings with reviews of agricultural modelling and Climate Change Risk Assessment was then used to highlight challenges specific to modelling adaptation. These were refined through literature review, focussing attention on how the progressive nature of CC affects the role and impact of modelling. Specific challenges identified were: Scope of adaptations modelled, Information on future adaptation, Collaboration to tackle novel challenges, Optimisation under progressive change with thresholds, and Responsibility given the sensitivity of future outcomes to initial choices under progressive change., Graphical abstract Image 1, Highlights • Modelling plays a key role in adapting agriculture to climate change. • Modellers' views and literature were analysed to identify adaptation-specific issues. • Novel challenges to modelling climate change adaptation were explored. • Challenges related to Responsibility, Scope, Optimisation, Information, Collaboration. • Adaptation to progressive climate change highlights social impacts of model use.
Published: 2019
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40. Incorporating Biodiversity into Biogeochemistry Models to Improve Prediction of Ecosystem Services in Temperate Grasslands: Review and Roadmap

Author: Gianni Bellocchi, Marcel van Oijen, Gaëtan Louarn, Susanne Rolinski, Roberto Confalonieri, Panu Korhonen, Frédérique Louault, Nicolas Viovy, Catherine Picon-Cochard, Thibault Moulin, Zoltán Barcza, György Kröel-Dulay, Stephen Wirth, Raphaël Martin, Eszter Lellei-Kovács, Ermes Movedi, Centre for Ecology and Hydrology (CEH), Natural Environment Research Council (NERC), Eötvös Loránd University (ELTE), Università degli Studi di Milano = University of Milan (UNIMI), Natural Resources Institute Finland (LUKE), MTA Centre for Ecological Research [Tihany], Hungarian Academy of Sciences (MTA), Unité de Recherche Pluridisciplinaire Prairies et Plantes Fourragères (P3F), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Unité Mixte de Recherche sur l'Ecosystème Prairial - UMR (UREP), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS), Potsdam Institute for Climate Impact Research (PIK), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), ANR-16-IDEX-0001,CAP 20-25,CAP 20-25(2016), Università degli Studi di Milano [Milano] (UNIMI), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), and Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)
Subjects: 0106 biological sciences, Biogeochemical cycle, 010504 meteorology & atmospheric sciences, Environmental change, Biodiversity, species, Carbon sequestration, functional types, 010603 evolutionary biology, 01 natural sciences, Ecology and Environment, Ecosystem services, lcsh:Agriculture, [SDV.EE.ECO]Life Sciences [q-bio]/Ecology, environment/Ecosystems, traits, biogeochemistry, process-based modelling, Ecosystem, biodiversity, 0105 earth and related environmental sciences, 2. Zero hunger, Abiotic component, experiments vs non-intrusive studies, business.industry, Environmental resource management, lcsh:S, Biogeochemistry, environmental change, 15. Life on land, 13. Climate action, Environmental science, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, ecosystem services, business, Agronomy and Crop Science, experiments vs. non-intrusive studies
Abstract: International audience; Multi-species grasslands are reservoirs of biodiversity and provide multiple ecosystem services, including fodder production and carbon sequestration. The provision of these services depends on the control exerted on the biogeochemistry and plant diversity of the system by the interplay of biotic and abiotic factors, e.g., grazing or mowing intensity. Biogeochemical models incorporate a mechanistic view of the functioning of grasslands and provide a sound basis for studying the underlying processes. However, in these models, the simulation of biogeochemical cycles is generally not coupled to simulation of plant species dynamics, which leads to considerable uncertainty about the quality of predictions. Ecological models, on the other hand, do account for biodiversity with approaches adopted from plant demography, but without linking the dynamics of plant species to the biogeochemical processes occurring at the community level, and this hampers the models' capacity to assess resilience against abiotic stresses such as drought and nutrient limitation. While setting out the state-of-the-art developments of biogeochemical and ecological modelling, we explore and highlight the role of plant diversity in the regulation of the ecosystem processes underlying the ecosystems services provided by multi-species grasslands. An extensive literature and model survey was carried out with an emphasis on technically advanced models reconciling Agronomy 2020, 10, 259 2 of 25 biogeochemistry and biodiversity, which are readily applicable to managed grasslands in temperate latitudes. We propose a roadmap of promising developments in modelling.
Published: 2020
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41. Achieving High Crop Yields with Low Nitrogen Emissions in Global Agricultural Input Intensification

Author: Karim C. Abbaspour, Philippe Ciais, Rainer Schulin, Wenfeng Liu, Hong Yang, Christoph Müller, Christian Folberth, Swiss Federal Insitute of Aquatic Science and Technology [Dübendorf] (EAWAG), International Institute for Applied Systems Analysis [Laxenburg] (IIASA), Potsdam Institute for Climate Impact Research (PIK), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), ICOS-ATC (ICOS-ATC), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Institute of Terrestrial Ecosystems (ITES), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), and Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)
Subjects: Irrigation, 010504 meteorology & atmospheric sciences, Low nitrogen, Nitrogen, Yield (finance), Agricultural engineering, Environment, 010501 environmental sciences, 01 natural sciences, Irrigation water, Environmental Chemistry, Baseline (configuration management), Irrigation management, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, 2. Zero hunger, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, business.industry, Crop yield, Agriculture, General Chemistry, 15. Life on land, 6. Clean water, 13. Climate action, Environmental science, business
Abstract: Increasing demand for food is driving a worldwide trend of agricultural input intensification. However, there is no comprehensive knowledge about the interrelations between potential yield gains and environmental trade-offs that would enable the identification of regions where input-driven intensification could achieve higher yields, yet with minimal environmental impacts. We explore ways of enhancing global yields, while avoiding significant nitrogen (N) emissions (Ne) by exploring a range of N and irrigation management scenarios. The simulated responses of yields and Ne to increased N inputs (Nin) and irrigation show high spatial variations due to differences in current agricultural inputs and agro-climatic conditions. Nitrogen use efficiency (NUE) of yield gains is negatively correlated with incremental Ne due to Nin additions. Avoiding further intensification in regions where high fractions of climatic yield potentials, ≥ 80%, are already achieved is key to maintain good NUE. Depending on the intensification scenarios, relative increases in Ne could be reduced by 0.3-29.6% of the baseline Ne with this intensification strategy as compared to indiscriminate further intensification, at the cost of a loss of yield increases by 0.2-16.7% of the baseline yields. In addition, irrigation water requirements and Nin would dramatically decrease by considering this intensification strategy.
Published: 2018
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42. Modelling the role of fires in the terrestrial carbon balance by incorporating SPITFIRE into the global vegetation model ORCHIDEE – Part 1: simulating historical global burned area and fire regimes

Author: Stijn Hantson, Benjamin Poulter, Kirsten Thonicke, Nicolas Viovy, Florent Mouillot, Patricia Cadule, P. Ciais, Fabienne Maignan, Chao Yue, Sally Archibald, Pierre Friedlingstein, Wei Min Hao, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), ICOS-ATC (ICOS-ATC), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Potsdam Institute for Climate Impact Research (PIK), University of the Witwatersrand [Johannesburg] (WITS), Council for Scientific and Industrial Research [Pretoria] (CSIR), Montana State University (MSU), USDA Forest Service Rocky Mountain Forest and Range Experiment Station, United States Department of Agriculture (USDA), Institut für Meteorologie und Klimaforschung - Atmosphärische Umweltforschung (IMK-IFU), Karlsruher Institut für Technologie (KIT), Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Université Paul-Valéry - Montpellier 3 (UPVM)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), University of Exeter, Modélisation des Surfaces et Interfaces Continentales (MOSAIC), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), and Université Paul-Valéry - Montpellier 3 (UPVM)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-École Pratique des Hautes Études (EPHE)
Subjects: [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Fire regime, lcsh:QE1-996.5, Biome, Vegetation, 15. Life on land, Seasonality, medicine.disease, lcsh:Geology, Boreal, 13. Climate action, Climatology, Fire protection, medicine, Environmental science, Terrestrial ecosystem, Scale (map), [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment
Abstract: Fire is an important global ecological process that influences the distribution of biomes, with consequences for carbon, water, and energy budgets. Therefore it is impossible to appropriately model the history and future of the terrestrial ecosystems and the climate system without including fire. This study incorporates the process-based prognostic fire module SPITFIRE into the global vegetation model ORCHIDEE, which was then used to simulate burned area over the 20th century. Special attention was paid to the evaluation of other fire regime indicators such as seasonality, fire size and fire length, next to burned area. For 2001–2006, the simulated global spatial extent of fire agrees well with that given by satellite-derived burned area data sets (L3JRC, GLOBCARBON, GFED3.1), and 76–92% of the global burned area is simulated as collocated between the model and observation, depending on which data set is used for comparison. The simulated global mean annual burned area is 346 Mha yr−1, which falls within the range of 287–384 Mha yr−1 as given by the three observation data sets; and is close to the 344 Mha yr−1 by the GFED3.1 data when crop fires are excluded. The simulated long-term trend and variation of burned area agree best with the observation data in regions where fire is mainly driven by climate variation, such as boreal Russia (1930–2009), along with Canada and US Alaska (1950–2009). At the global scale, the simulated decadal fire variation over the 20th century is only in moderate agreement with the historical reconstruction, possibly because of the uncertainties of past estimates, and because land-use change fires and fire suppression are not explicitly included in the model. Over the globe, the size of large fires (the 95th quantile fire size) is underestimated by the model for the regions of high fire frequency, compared with fire patch data as reconstructed from MODIS 500 m burned area data. Two case studies of fire size distribution in Canada and US Alaska, and southern Africa indicate that both number and size of large fires are underestimated, which could be related with short fire patch length and low daily fire size. Future efforts should be directed towards building consistent spatial observation data sets for key parameters of the model in order to constrain the model error at each key step of the fire modelling.
Published: 2018
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43. A generic pixel-to-point comparison for simulated large-scale ecosystem properties and ground-based observations: an example from the Amazon region

Author: Anja Rammig, Jens Heinke, Florian Hofhansl, Hans Verbeeck, Timothy R. Baker, Bradley Christoffersen, Phillipe Ciais, Hannes De Deurwaerder, Katrin Fleischer, David Galbraith, Matthieu Guimberteau, Andreas Huth, Michelle Johnson, Bart Krujit, Fanny Langerwisch, Patrick Meir, Phillip Papastefanou, Gilvan Sampaio, Kirsten Thonicke, Celso von Randow, Christian Zang, Edna Rödig, Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne] (TUM), Potsdam Institute for Climate Impact Research (PIK), International Institute for Applied Systems Analysis [Laxenburg] (IIASA), Universiteit Gent = Ghent University (UGENT), School of Geography [Leeds], University of Leeds, University of Texas Rio Grande Valley [Brownsville, TX] (UTRGV), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), ICOS-ATC (ICOS-ATC), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Universiteit Gent = Ghent University [Belgium] (UGENT), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), and Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)
Subjects: [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, 0106 biological sciences, MODEL DESCRIPTION, CARBON EMISSIONS, WIMEK, 010504 meteorology & atmospheric sciences, MORTALITY, TROPICAL FORESTS, PLANT GEOGRAPHY, Biology and Life Sciences, FOREST STRUCTURE, 15. Life on land, 01 natural sciences, 13. Climate action, Earth and Environmental Sciences, DENSITY, WATER-BALANCE, cavelab, Life Science, Water Systems and Global Change, VEGETATION, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, ABOVEGROUND BIOMASS, 010606 plant biology & botany, 0105 earth and related environmental sciences
Abstract: International audience; Comparing model output and observed data is an important step for assessing model performance and quality of simulation results. However, such comparisons are often hampered by differences in spatial scales between local point observations and large-scale simulations of grid cells or pixels. In this study, we propose a generic approach for a pixel-to-point comparison and provide statistical measures accounting for the uncertainty resulting from landscape variability and measurement errors in ecosystem variables. The basic concept of our approach is to determine the statistical properties of small-scale (within-pixel) variability and observational errors, and to use this information to correct for their effect when large-scale area averages (pixel) are compared to small-scale point estimates. We demonstrate our approach by comparing simulated values of aboveground biomass, woody productivity (woody net primary productivity, NPP) and residence time of woody biomass from four dynamic global vegetation models (DGVMs) with measured inventory data from permanent plots in the Amazon rainforest, a region with the typical problem of low data availability, potential scale mismatch and thus high model uncertainty. We find that the DGVMs under-and overestimate aboveground biomass by 25 % and up to 60 %, respectively. Our comparison metrics provide a quantitative measure for model-data agreement and show moderate to good agreement with the region-wide spatial biomass pattern detected by plot observations. However , all four DGVMs overestimate woody productivity and underestimate residence time of woody biomass even when accounting for the large uncertainty range of the observational data. This is because DGVMs do not represent the Published by Copernicus Publications on behalf of the European Geosciences Union. 5204 A. Rammig et al.: Pixel-to-point comparison for simulated large-scale ecosystem properties relation between productivity and residence time of woody biomass correctly. Thus, the DGVMs may simulate the correct large-scale patterns of biomass but for the wrong reasons. We conclude that more information about the underlying processes driving biomass distribution are necessary to improve DGVMs. Our approach provides robust statistical measures for any pixel-to-point comparison, which is applicable for evaluation of models and remote-sensing products.
Published: 2018
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44. The use of biogeochemical models to evaluate mitigation of greenhouse gas emissions from managed grasslands

Author: Marco Carozzi, Lutz Merbold, Kate Gongadze, Susanne Rolinski, Pete Smith, Christopher D. Dorich, Paul C. D. Newton, Kathrin Fuchs, Mark A. Liebig, Nuala Fitton, Renáta Sándor, Robert M. Rees, Val Snow, Katja Klumpp, Sylvie Recous, Fiona Ehrhardt, Raphaël Martin, Gianni Bellocchi, Lorenzo Brilli, Jean-François Soussana, Unité Mixte de Recherche sur l'Ecosystème Prairial - UMR (UREP), Institut National de la Recherche Agronomique (INRA)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS), Centre for Agricultural Research [Budapest] (ATK), Hungarian Academy of Sciences (MTA), Collège de Direction, Institut National de la Recherche Agronomique (INRA), Dipartimento di Scienze delle Produzioni Agroalimentari e dell’Ambiente (DISPAA ), Climate Agriculture Group, Agroscope, Fractionnement des AgroRessources et Environnement - UMR-A 614 (FARE), Université de Reims Champagne-Ardenne (URCA)-Institut National de la Recherche Agronomique (INRA)-SFR Condorcet, Université de Reims Champagne-Ardenne (URCA)-Université de Picardie Jules Verne (UPJV)-Centre National de la Recherche Scientifique (CNRS)-Université de Reims Champagne-Ardenne (URCA)-Université de Picardie Jules Verne (UPJV)-Centre National de la Recherche Scientifique (CNRS), School of Biological Sciences [Aberdeen], University of Aberdeen, Lincoln Research Centre, AgResearch Ltd, Colorado State University [Fort Collins] (CSU), Department of Environmental Systems Science, Institute Agricultural Science (ETH Zurich), Sustanaible soils and grassland Department, Rothamsted Research, NGPRL, United States Department of Agriculture - Agricultural Research Service, Scotland's Rural College (SCUR), Postdam Institute for Climate Impact Research (PIK), ADEME, Collège de Direction (CODIR), Fractionnement des AgroRessources et Environnement (FARE), Université de Reims Champagne-Ardenne (URCA)-Institut National de la Recherche Agronomique (INRA), USDA-ARS : Agricultural Research Service, Scotland's Rural College (SRUC), and Potsdam Institute for Climate Impact Research (PIK)
Subjects: 010504 meteorology & atmospheric sciences, [SDV]Life Sciences [q-bio], chargement en betail, GHG emision intensity, simulation models, 01 natural sciences, Grassland, cycle de l'azote, Grazing, gaz à effet de serre, méthane, Waste Management and Disposal, 2. Zero hunger, geography.geographical_feature_category, Livestock density, prairie, nitrogen fertilization, 04 agricultural and veterinary sciences, Pollution, fertilisation azotée, Process-based model, France, Sensitivity analysis, Cycling, GHG emission intensity, cycle du carbone, Biogeochemical cycle, Environmental Engineering, modèle de simulation, suisse, Nitrogen fertilization, greenhouse gases, carbon cycle, nitrogen cycle, Environmental Chemistry, Ecosystem, 0105 earth and related environmental sciences, geography, royaume uni, Primary production, 15. Life on land, états-unis, united kingdom, Arid, grazing intensity, Agronomy, 13. Climate action, marsh gas, Greenhouse gas, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Environmental science, intensité de pâturage, grassland, usa
Abstract: Simulation models quantify the impacts on carbon (C) and nitrogen (N) cycling in grassland systems caused by changes in management practices. To support agricultural policies, it is however important to contrast the responses of alternative models, which can differ greatly in their treatment of key processes and in their response to management. We applied eight biogeochemical models at five grassland sites (in France, New Zealand, Switzerland, United Kingdom and United States) to compare the sensitivity of modelled C and N fluxes to changes in the density of grazing animals (from 100% to 50% of the original livestock densities), also in combination with decreasing N fertilization levels (reduced to zero from the initial levels). Simulated multi-model median values indicated that input reduction would lead to an increase in the C sink strength (negative net ecosystem C exchange) in intensive grazing systems: −64 ± 74 g C m−2 yr−1 (animal density reduction) and −81 ± 74 g C m−2 yr−1 (N and animal density reduction), against the baseline of −30.5 ± 69.5 g C m−2 yr−1 (LSU [livestock units] ≥ 0.76 ha−1 yr−1). Simulations also indicated a strong effect of N fertilizer reduction on N fluxes, e.g. N2O-N emissions decreased from 0.34 ± 0.22 (baseline) to 0.1 ± 0.05 g N m−2 yr−1 (no N fertilization). Simulated decline in grazing intensity had only limited impact on the N balance. The simulated pattern of enteric methane emissions was dominated by high model-to-model variability. The reduction in simulated offtake (animal intake + cut biomass) led to a doubling in net primary production per animal (increased by 11.6 ± 8.1 t C LSU−1 yr−1 across sites). The highest N2O-N intensities (N2O-N/offtake) were simulated at mown and extensively grazed arid sites. We show the possibility of using grassland models to determine sound mitigation practices while quantifying the uncertainties associated with the simulated outputs.
Published: 2018
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45. Modeling vegetation and carbon dynamics of managed grasslands at the global scale with LPJmL 3.6

Author: Susanne Rolinski, Christoph Müller, Jens Heinke, Isabelle Weindl, Anne Biewald, Benjamin Leon Bodirsky, Alberte Bondeau, Eltje R. Boons-Prins, Alexander F. Bouwman, Peter A. Leffelaar, Johnny A. te Roller, Sibyll Schaphoff, Kirsten Thonicke, Geochemistry, Bio-, hydro-, and environmental geochemistry, Potsdam Institute for Climate Impact Research (PIK), Humboldt University of Berlin, Leibniz Institute for Agricultural Engineering and Bioeconomy, Institut méditerranéen de biodiversité et d'écologie marine et continentale (IMBE), Centre National de la Recherche Scientifique (CNRS)-Institut de recherche pour le développement [IRD] : UMR237-Aix Marseille Université (AMU)-Avignon Université (AU), Wageningen University and Research, Plant Production Systems, Department of Earth Sciences – Geochemistry [Utrecht], Utrecht University [Utrecht], Alterra, Wageningen Environmental Research, Humboldt University Of Berlin, and Avignon Université (AU)-Aix Marseille Université (AMU)-Institut de recherche pour le développement [IRD] : UMR237-Centre National de la Recherche Scientifique (CNRS)
Subjects: 2. Zero hunger, Earth Observation and Environmental Informatics, 010504 meteorology & atmospheric sciences, Earth and Planetary Sciences(all), 020206 networking & telecommunications, 02 engineering and technology, 15. Life on land, PE&RC, 01 natural sciences, Plant Production Systems, 13. Climate action, Plantaardige Productiesystemen, Modelling and Simulation, Aardobservatie en omgevingsinformatica, [SDE]Environmental Sciences, 0202 electrical engineering, electronic engineering, information engineering, Life Science, 0105 earth and related environmental sciences
Abstract: International audience; Grassland management affects the carbon fluxes of one-third of the global land area and is thus an important factor for the global carbon budget. Nonetheless, this aspect has been largely neglected or underrepresented in global carbon cycle models. We investigate four harvesting schemes for the managed grassland implementation of the dynamic global vegetation model (DGVM) Lund–Potsdam– Jena managed Land (LPJmL) that facilitate a better representation of actual management systems globally. We describe the model implementation and analyze simulation results with respect to harvest, net primary productivity and soil carbon content and by evaluating them against reported grass yields in Europe. We demonstrate the importance of accounting for differences in grassland management by assessing potential livestock grazing densities as well as the impacts of grazing, grazing intensities and mowing systems on soil carbon stocks. Grazing leads to soil carbon losses in polar or arid regions even at moderate livestock densities (< 0.4 livestock units per hectare – LSU ha −1) but not in temperate regions even at much higher densities (0.4 to 1.2 LSU ha −1). Applying LPJmL with the new grassland management options enables assessments of the global grassland production and its impact on the terrestrial biogeochemical cycles but requires a global data set on current grassland management.
Published: 2018
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46. Model–data synthesis for the next generation of forest free‐air <scp>CO</scp> 2 enrichment ( <scp>FACE</scp> ) experiments

Author: Xiaojuan Yang, Anthony P. Walker, Tomas F. Domingues, A. Rob MacKenzie, Benjamin Smith, Daniel S. Goll, Martin G. De Kauwe, Belinda E. Medlyn, Ryan Pavlick, Anja Rammig, David S. Ellsworth, Rick M. Thomas, David M. Lapola, Soenke Zaehle, Kirsten Thonicke, Richard J. Norby, K. A. Luus, Remko A. Duursma, Universidade de São Paulo (USP), Hawkesbury Institute for the Environment [Richmond] (HIE), Western Sydney University, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Department of Electrical & Computer Engineering [Victoria] (ECE Department), University of Victoria [Canada] (UVIC), Potsdam Institute for Climate Impact Research (PIK), Lund University [Lund], Oak Ridge National Laboratory [Oak Ridge] (ORNL), UT-Battelle, LLC, Biogeochemical Systems Department [Jena], Max Planck Institute for Biogeochemistry (MPI-BGC), Max-Planck-Gesellschaft-Max-Planck-Gesellschaft, Universidade de São Paulo = University of São Paulo (USP), and Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)
Subjects: 0106 biological sciences, Rainforest, 010504 meteorology & atmospheric sciences, Physiology, Climate, Biome, Biodiversity, Plant Science, Subtropics, Forests, 01 natural sciences, Trees, Soil, Temperate climate, Ecosystem, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Eucalyptus, Dehydration, Hemiboreal, Atmosphere, Agroforestry, Australia, Biosphere, Phosphorus, Carbon Dioxide, Models, Theoretical, 15. Life on land, England, 13. Climate action, Environmental science, Brazil, 010606 plant biology & botany
Abstract: The first generation of forest free-air CO2 enrichment (FACE) experiments has successfully provided deeper understanding about how forests respond to an increasing CO2 concentration in the atmosphere. Located in aggrading stands in the temperate zone, they have provided a strong foundation for testing critical assumptions in terrestrial biosphere models that are being used to project future interactions between forest productivity and the atmosphere, despite the limited inference space of these experiments with regards to the range of global ecosystems. Now, a new generation of FACE experiments in mature forests in different biomes and over a wide range of climate space and biodiversity will significantly expand the inference space. These new experiments are: EucFACE in a mature Eucalyptus stand on highly weathered soil in subtropical Australia; AmazonFACE in a highly diverse, primary rainforest in Brazil; BIFoR-FACE in a 150-yr-old deciduous woodland stand in central England; and SwedFACE proposed in a hemiboreal, Pinus sylvestris stand in Sweden. We now have a unique opportunity to initiate a model-data interaction as an integral part of experimental design and to address a set of cross-site science questions on topics including responses of mature forests; interactions with temperature, water stress, and phosphorus limitation; and the influence of biodiversity.
Published: 2015
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47. A framework for the cross-sectoral integration of multi-model impact projections: land use decisions under climate impacts uncertainties

Author: Katja Frieler, Taikan Oki, Qiuhong Tang, Jens Heinke, Almut Arneth, Douglas B. Clark, Jacob Schewe, Simon N. Gosling, Mark R. Lomas, Dominik Wisser, Yoshimitsu Masaki, Balázs M. Fekete, Ingjerd Haddeland, Pete Falloon, P. Ciais, Franziska Piontek, Christoph Schmitz, Kazuya Nishina, Hans Joachim Schellnhuber, Elke Stehfest, Anders Levermann, Andrew D. Friend, Petra Döll, C. Gellhorn, Erwin Schmid, Marc F. P. Bierkens, Tobias Stacke, Ryan Pavlick, Veronika Huber, Christian Folberth, K. Neumann, Delphine Deryng, Nikolay Khabarov, Lila Warszawski, Alex C. Ruane, Joshua Elliott, Hermann Lotze-Campen, Hydrologie, Sub NMR Spectroscopy, Sub FG LGH 3e geldstroom, Landscape functioning, Geocomputation and Hydrology, Max-Planck-Institut für Extraterrestrische Physik (MPE), Potsdam Institute for Climate Impact Research (PIK), Department of Physical Geography and Ecosystems Analysis, Geobiosphere Science Centre, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), ICOS-ATC (ICOS-ATC), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), NASA Goddard Institute for Space Studies (GISS), NASA Goddard Space Flight Center (GSFC), Institute of Physical Geography, Norwegian Water Resources and Energy Directorate (NVE), Centre for Terrestrial Carbon Dynamics: National Centre for Earth Observation (CTCD), University of Sheffield [Sheffield], Department of Life Science, Tokyo Institute of Technology [Tokyo] (TITECH), Institute of Industrial Science, Max Planck Institute for Meteorology (MPI-M), Max-Planck-Gesellschaft, Netherlands Environmental Assessment Agency, Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), and Department of Geosciences
Subjects: lcsh:Dynamic and structural geology, Natural resource economics, Population, Climate change, 7. Clean energy, Robust decision-making, lcsh:QE500-639.5, Laboratory of Geo-information Science and Remote Sensing, 11. Sustainability, ddc:550, Life Science, Laboratorium voor Geo-informatiekunde en Remote Sensing, lcsh:Science, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, education, ComputingMilieux_MISCELLANEOUS, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, 2. Zero hunger, education.field_of_study, Food security, business.industry, lcsh:QE1-996.5, Global warming, Environmental resource management, 15. Life on land, PE&RC, lcsh:Geology, Earth sciences, Climate change mitigation, Agriculture and Soil Science, 13. Climate action, Greenhouse gas, General Earth and Planetary Sciences, Environmental science, lcsh:Q, Climate model, business
Abstract: Climate change and its impacts already pose considerable challenges for societies that will further increase with global warming (IPCC, 2014a, b). Uncertainties of the climatic response to greenhouse gas emissions include the potential passing of large-scale tipping points (e.g. Lenton et al., 2008; Levermann et al., 2012; Schellnhuber, 2010) and changes in extreme meteorological events (Field et al., 2012) with complex impacts on societies (Hallegatte et al., 2013). Thus climate change mitigation is considered a necessary societal response for avoiding uncontrollable impacts (Conference of the Parties, 2010). On the other hand, large-scale climate change mitigation itself implies fundamental changes in, for example, the global energy system. The associated challenges come on top of others that derive from equally important ethical imperatives like the fulfilment of increasing food demand that may draw on the same resources. For example, ensuring food security for a growing population may require an expansion of cropland, thereby reducing natural carbon sinks or the area available for bio-energy production. So far, available studies addressing this problem have relied on individual impact models, ignoring uncertainty in crop model and biome model projections. Here, we propose a probabilistic decision framework that allows for an evaluation of agricultural management and mitigation options in a multi-impact-model setting. Based on simulations generated within the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), we outline how cross-sectorally consistent multi-model impact simulations could be used to generate the information required for robust decision making. Using an illustrative future land use pattern, we discuss the trade-off between potential gains in crop production and associated losses in natural carbon sinks in the new multiple crop- and biome-model setting. In addition, crop and water model simulations are combined to explore irrigation increases as one possible measure of agricultural intensification that could limit the expansion of cropland required in response to climate change and growing food demand. This example shows that current impact model uncertainties pose an important challenge to long-term mitigation planning and must not be ignored in long-term strategic decision making.
Published: 2015
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48. Classifying multi-model wheat yield impact response surfaces showing sensitivity to temperature and precipitation change

Author: Miroslav Trnka, Paola A. Deligios, Alfredo Rodríguez, Pierre Stratonovitch, Françoise Ruget, Ingrid Jacquemin, Marco Moriondo, Louis François, Katharina Waha, Alessia Perego, Mikhail A. Semenov, Fulu Tao, Benjamin Dumont, Christoph Müller, Frank Ewert, Petr Hlavinka, Per Bodin, Margarita Ruiz-Ramos, Marie-France Destain, Lianhai Wu, Marco Acutis, Cezary Sławiński, Senthold Asseng, Nina Pirttioja, Piotr Baranowski, Marco Bindi, Manuel Montesino, Davide Cammarano, Taru Palosuo, M. Ines Minguez, Claas Nendel, Timothy R. Carter, Iwan Supit, Bruno Basso, Kurt Christian Kersebaum, Zhigan Zhao, Samuel Buis, Alex C. Ruane, Thomas Gaiser, Chris Kollas, Jaromir Krzyszczak, Roberto Ferrise, Ignacio J. Lorite, Julien Minet, Holger Hoffmann, Reimund P. Rötter, Enli Wang, Isik Öztürk, Stefan Fronzek, Mattia Sanna, Finnish Environment Institute (SYKE), Università degli Studi di Firenze = University of Florence (UniFI), Rheinische Friedrich-Wilhelms-Universität Bonn, Institut für Nutzpflanzenwissenschaften und Ressourcenschutz (INRES), Natural Resources Institute Finland (LUKE), Centro de Estudios e Investigación para la Gestión de Riesgos Agrarios y Medioambientales (CEIGRAM), Universidad Politécnica de Madrid (UPM), Institute of Agrosystems and Bioclimatology, Mendel University in Brno (MENDELU), Global Change Research Centre (CzechGlobe), Institut de Recherche pour le Développement (IRD [Nouvelle-Calédonie]), University of Florida [Gainesville] (UF), Institute of Agrophysics, Polska Akademia Nauk = Polish Academy of Sciences (PAN), Michigan State University [East Lansing], Michigan State University System, Lund University [Lund], Environnement Méditerranéen et Modélisation des Agro-Hydrosystèmes (EMMAH), Avignon Université (AU)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), The James Hutton Institute, Università degli Studi di Sassari = University of Sassari [Sassari] (UNISS), Université de Liège, Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research (ZALF), Potsdam Institute for Climate Impact Research (PIK), Instituto Andaluz de Investigación y Formación Agraria y Pesquera (IFAPA), University of Copenhagen = Københavns Universitet (UCPH), Istituto di Biometeorologia [Firenze] (IBIMET), National Research Council of Italy | Consiglio Nazionale delle Ricerche (CNR), NASA Goddard Institute for Space Studies (GISS), NASA Goddard Space Flight Center (GSFC), Rothamsted Research, Biotechnology and Biological Sciences Research Council (BBSRC), Wageningen University and Research [Wageningen] (WUR), Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), China Agricultural University (CAU), Tropical Plant Production and Agricultural Systems Modelling (TROPAGS), Georg-August-University = Georg-August-Universität Göttingen, Centre for Biodiversity and Sustainable Land Use (CBL), cademy of Finland 277276 277403 292836, Finnish Ministry of Agriculture and Forestry (FACCE-MACSUR), Polish National Centre for Research and Development BIOSTRATEG1/271322/3/NCBR/2015, BIOSTRATEG2 298782, German Federal Ministry of Food and Agriculture through the Federal Office for Agriculture and Food 2851ERA01J, FACCE MACSUR 2812ERA 147, German Federal Ministry of Education and Research via the 'Limpopo Living Landscapes' project within the SPACES programme 01LL1304A, MACMIT project 01LN1317A, Italian Ministry of Agricultural Food and Forest Policies (AGROSCENARI Project), Italian Ministry of Education, University and Research (FIRB) RBFR12B2K4_004, European Project: 603416,EC:FP7:ENV,FP7-ENV-2013-two-stage,IMPRESSIONS(2013), University of Florence (UNIFI), Natural Resources Institute Finland, CEIGRAM-AgSystems, Mendel University in Brno, University of Florida [Gainesville], Polish Academy of Sciences, Lund University, University of Sassari, Andalusian Agricultural Research Institute (IFAPA), University of Copenhagen = Københavns Universitet (KU), Consiglio Nazionale delle Ricerche (CNR), Aarhus University Hospital, Wageningen University and Research Center (WUR), China Agricultural University, Georg-August-Universität Göttingen, Università degli Studi di Firenze = University of Florence [Firenze] (UNIFI), Natural resources institute Finland, and Georg-August-University [Göttingen]
Subjects: Spatial correlation, ble tendre, 010504 meteorology & atmospheric sciences, modèle multivariable, influence de la température, Water en Voedsel, 01 natural sciences, modèle de culture, Statistics, Range (statistics), Climate change, Crop model, Mathematics, 2. Zero hunger, changement climatique, Mathematical model, Agricultura, 04 agricultural and veterinary sciences, ta4111, Classification, classification des sols, winter wheat, soft wheat, Wheat, rendement agricole, Sensitivity analysis, Meteorology, [SDE.MCG]Environmental Sciences/Global Changes, ta1171, Precipitation, global change, 0105 earth and related environmental sciences, WIMEK, Water and Food, triticum, Simulation modeling, simulation de croissance, 15. Life on land, Hierarchical clustering, Euclidean distance, 13. Climate action, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Animal Science and Zoology, Water Systems and Global Change, soil taxonomy, Agronomy and Crop Science, Ensemble, analyse de sensibilité
Abstract: Crop growth simulation models can differ greatly in their treatment of key processes and hence in their response to environmental conditions. Here, we used an ensemble of 26 process-based wheat models applied at sites across a European transect to compare their sensitivity to changes in temperature (−2 to +9°C) and precipitation (−50 to +50%). Model results were analysed by plotting them as impact response surfaces (IRSs), classifying the IRS patterns of individual model simulations, describing these classes and analysing factors that may explain the major differences in model responses. The model ensemble was used to simulate yields of winter and spring wheat at four sites in Finland, Germany and Spain. Results were plotted as IRSs that show changes in yields relative to the baseline with respect to temperature and precipitation. IRSs of 30-year means and selected extreme years were classified using two approaches describing their pattern. The expert diagnostic approach (EDA) combines two aspects of IRS patterns: location of the maximum yield (nine classes) and strength of the yield response with respect to climate (four classes), resulting in a total of 36 combined classes defined using criteria pre-specified by experts. The statistical diagnostic approach (SDA) groups IRSs by comparing their pattern and magnitude, without attempting to interpret these features. It applies a hierarchical clustering method, grouping response patterns using a distance metric that combines the spatial correlation and Euclidian distance between IRS pairs. The two approaches were used to investigate whether different patterns of yield response could be related to different properties of the crop models, specifically their genealogy, calibration and process description. Although no single model property across a large model ensemble was found to explain the integrated yield response to temperature and precipitation perturbations, the application of the EDA and SDA approaches revealed their capability to distinguish: (i) stronger yield responses to precipitation for winter wheat than spring wheat; (ii) differing strengths of response to climate changes for years with anomalous weather conditions compared to period-average conditions; (iii) the influence of site conditions on yield patterns; (iv) similarities in IRS patterns among models with related genealogy; (v) similarities in IRS patterns for models with simpler process descriptions of root growth and water uptake compared to those with more complex descriptions; and (vi) a closer correspondence of IRS patterns in models using partitioning schemes to represent yield formation than in those using a harvest index. Such results can inform future crop modelling studies that seek to exploit the diversity of multi-model ensembles, by distinguishing ensemble members that span a wide range of responses as well as those that display implausible behaviour or strong mutual similarities.
Published: 2018
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49. Reproducing reproduction: How to simulate mast seeding in forest models

Author: Tanja G. M. Sanders, Ciprian Palaghianu, Manuel Esteban Lucas-Borja, Eliane Schermer, Davide Ascoli, Thomas Wohlgemuth, Giorgio Vacchiano, Paola Mairota, Andrew Hacket-Pain, Alessio Collalti, Thomas Caignard, Fabio Berzaghi, Christopher P. O. Reyer, Università degli Studi di Milano [Milano] (UNIMI), Dipartimento di Agraria, University of Sassari, DIBAF, Tuscia University, Universidad de Castilla-La Mancha (UCLM), Biodiversité, Gènes & Communautés (BioGeCo), Institut National de la Recherche Agronomique (INRA)-Université de Bordeaux (UB), Euro–Mediterranean Center for Climate Change, Impacts on Agriculture, Forests and Ecosystem Services, Partenaires INRAE, Institute for agriculture and forestry systems in the Mediterranean (CNR-ISAFOM), Department of Agri-Environmental and Territorial Sciences, University of Bari Aldo Moro (UNIBA), University Stefan cel Mare of Suceava (USU), Potsdam Institute for Climate Impact Research (PIK), Thunen Institute of Forest Ecosystems, Thünen Institute, Snow and Landscape Research, St. Catherine's College, and University of Oxford [Oxford]
Subjects: 0106 biological sciences, Pollination, Ecology, Ecological Modeling, resource budget model, [SDV]Life Sciences [q-bio], tree reproduction, resource allocation, Masting Seed production Process-based models Resource budget model Resource allocation Tree reproduction, 15. Life on land, 010603 evolutionary biology, 01 natural sciences, masting, Plant population, process-based models, seed production, Resource Acquisition Is Initialization, Environmental science, Forest structure, Seeding, Cascading effects, Mast (botany), Masting, Process-based models, Resource allocation, Resource budget model, Seed production, Tree reproduction, Carbon stock, 010606 plant biology & botany
Abstract: International audience; Masting is the highly variable and synchronous production of seeds by plants. Masting can have cascading effects on plant population dynamics and forest properties such as tree growth, carbon stocks, regeneration, nutrient cycling, or future species composition. However, masting has often been missing from forest models. Those few that simulate masting have done so using relatively simple empirical rules, and lack an implementation of process-based mechanisms that control such events. Here we review more than 200 published papers on mechanistic formulations of masting, and summarize how the main processes involved in masting and their related patterns can be incorporated in forest models at different degrees of complexity. Our review showed that, of all proximate causes of masting, resource acquisition, storage and allocation were the processes studied most often. Hormonal and genetic regulation of bud formation, floral induction, and anthesis were less frequently addressed. We outline the building blocks of a general process-based model of masting that can be used to improve the oversimplified functions in different types of forest models, and to implement them where missing. A complete implementation of masting in forest models should include functions for resource allocation and depletion, and for pollination, as regulated by both forest structure and weather in the years prior to seed production. When models operate at spatio-temporal scales mismatched with the main masting processes, or if calibration data are not available, simulation can be based on parameterizing masting patterns (variability, synchrony, or frequency). Also, observed masting patterns have the potential to be used as “reality checks” for more process-based forest models wishing to accurately reproduce masting as an emergent phenomenon.
Published: 2018
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50. The importance of forest structure for carbon fluxes of the Amazon rainforest

Author: Rico Fischer, Anja Rammig, Andreas Huth, Edna Rödig, Franziska Taubert, Matthias Cuntz, Helmholtz Zentrum für Umweltforschung = Helmholtz Centre for Environmental Research (UFZ), SILVA (SILVA), Institut National de la Recherche Agronomique (INRA)-Université de Lorraine (UL)-AgroParisTech, Sch Life Sci Weihenstephan, Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne] (TUM), Potsdam Institute for Climate Impact Research (PIK), Osnabrück University, German Centre for Integrative Biodiversity Research, Helmholtz Alliance Remote Sensing and Earth System Dynamics, French National Research Agency (ANR) (Lab of Excellence ARBRE) ANR-11 L ABX-0002-01, CDIAC, ICOS Ecosystem Thematic Center, OzFlux office, ChinaFlux office, AsiaFlux office, Helmholtz Centre for Environmental Research (UFZ), Technical University of Munich (TUM), Institut National de la Recherche Agronomique (INRA)-AgroParisTech-Université de Lorraine (UL), and Rödig, Edna
Subjects: 0106 biological sciences, Canopy, 010504 meteorology & atmospheric sciences, scénario climatique, forêt amazonienne, [SDV]Life Sciences [q-bio], productivité forestière, TROPICAL FORESTS, Climate change, DROUGHT SENSITIVITY, Atmospheric sciences, 010603 evolutionary biology, 01 natural sciences, bilan de carbone, WOODY BIOMASS, Ecosystem, 0105 earth and related environmental sciences, General Environmental Science, carbon balance, Biomass (ecology), RESIDENCE TIMES, PRODUCTIVITY, flux de carbone, Renewable Energy, Sustainability and the Environment, Amazon rainforest, SINK, Public Health, Environmental and Occupational Health, Carbon sink, Primary production, 15. Life on land, DENSITY, ECOSYSTEM, GROWTH, DEFORESTATION, ddc, production de biomasse, Productivity (ecology), 13. Climate action, structure forestière, Environmental science
Abstract: Precise descriptions of forest productivity, biomass, and structure are essential for understanding ecosystem responses to climatic and anthropogenic changes. However, relations between these components are complex, in particular for tropical forests.[br/] We developed an approach to simulate carbon dynamics in the Amazon rainforest including around 410 billion individual trees within 7.8 million km(2). We integrated canopy height observations from space-borne LIDAR in order to quantify spatial variations in forest state and structure reflecting small-scale to large-scale natural and anthropogenic disturbances. Under current conditions, we identified the Amazon rainforest as a carbon sink, gaining 0.56 GtC per year. This carbon sink is driven by an estimated mean gross primary productivity (GPP) of 25.1 tC ha(-1) a(-1), and a mean woody aboveground net primary productivity (wANPP) of 4.2 tC ha(-1) a(-1). We found that successional states play an important role for the relations between productivity and biomass. Forests in early to intermediate successional states are the most productive, and woody above-ground carbon use efficiencies are non-linear. Simulated values can be compared to observed carbon fluxes at various spatial resolutions (> 40 m). Notably, we found that our GPP corresponds to the values derived from MODIS. For NPP, spatial differences can be observed due to the consideration of forest successional states in our approach. We conclude that forest structure has a substantial impact on productivity and biomass. It is an essential factor that should be taken into account when estimating current carbon budgets or analyzing climate change scenarios for the Amazon rainforest.
Published: 2018
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