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

1. Effects of model calibration on hydrological and water resources management simulations under climate change in a semi-arid watershed

Author: Koch, Hagen, Silva, Ana Lígia Chaves, Liersch, Stefan, de Azevedo, José Roberto Gonçalves, Hattermann, Fred Fokko, Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, Potsdam, Germany, and Departamento de Eng. Civil, Centro de Tecnologia e Geociências—CTG, Universidade Federal de Pernambuco—UFPE, Recife, Brazil
Subjects: Pajeú watershed, Hydrology, Atmospheric Science, Global and Planetary Change, Watershed, 010504 meteorology & atmospheric sciences, Discharge, 0208 environmental biotechnology, SWIM, 02 engineering and technology, 01 natural sciences, 020801 environmental engineering, Water management, Water resources, Semi-arid, Evapotranspiration, ddc:551.48, Soil water, Climate change, Environmental science, Precipitation, Water cycle, Surface runoff, 0105 earth and related environmental sciences
Abstract: Semi-arid regions are known for erratic precipitation patterns with significant effects on the hydrological cycle and water resources availability. High temporal and spatial variation in precipitation causes large variability in runoff over short durations. Due to low soil water storage capacity, base flow is often missing and rivers fall dry for long periods. Because of its climatic characteristics, the semi-arid north-eastern region of Brazil is prone to droughts. To counter these, reservoirs were built to ensure water supply during dry months. This paper describes problems and solutions when calibrating and validating the eco-hydrological model SWIM for semi-arid regions on the example of the Pajeú watershed in north-eastern Brazil. The model was calibrated to river discharge data before the year 1983, with no or little effects of water management, applying a simple and an enhanced approach. Uncertainties result mainly from the meteorological data and observed river discharges. After model calibration water management was included in the simulations. Observed and simulated reservoir volumes and river discharges are compared. The calibrated and validated models were used to simulate the impacts of climate change on hydrological processes and water resources management using data of two representative concentration pathways (RCP) and five earth system models (ESM). The differences in changes in natural and managed mean discharges are negligible ( 5%) under RCP2.6 for the ESM ensemble mean. In semi-arid catchments, the enhanced approach should be preferred, because in addition to discharge, a second variable, here evapotranspiration, is considered for model validation., BMBF Germany, BMGF Germany
Published: 2020

2. Air quality co-benefits of ratcheting up the NDCs

Author: Rauner, Sebastian, Hilaire, Jérôme, Klein, David, Strefler, Jessica, Luderer, Gunnar, Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, Potsdam, Germany, and Mercator Research Institute on Global Commons and Climate Change (MCC) gGmbH, Berlin, Germany
Subjects: Atmospheric Science, Resource (biology), 010504 meteorology & atmospheric sciences, Natural resource economics, media_common.quotation_subject, Air pollution, Climate change, 010501 environmental sciences, medicine.disease_cause, 7. Clean energy, 01 natural sciences, 12. Responsible consumption, 11. Sustainability, medicine, Co-benefits, Air quality index, 0105 earth and related environmental sciences, media_common, Global and Planetary Change, Social cost, ddc:363.73, 3. Good health, Climate change mitigation, 13. Climate action, Damages, Environmental science, ddc:620, Health impacts, Welfare
Abstract: The current nationally determined contributions, pledged by the countries under the Paris Agreement, are far from limiting climate change to below 2 ∘C temperature increase by the end of the century. The necessary ratcheting up of climate policy is projected to come with a wide array of additional benefits, in particular a reduction of today’s 4.5 million annual premature deaths due to poor air quality. This paper therefore addresses the question how climate policy and air pollution–related health impacts interplay until 2050 by developing a comprehensive global modeling framework along the cause and effect chain of air pollution–induced social costs. We find that ratcheting up climate policy to a 2 ∘ compliant pathway results in welfare benefits through reduced air pollution that are larger than mitigation costs, even with avoided climate change damages neglected. The regional analysis demonstrates that the 2 ∘C pathway is therefore, from a social cost perspective, a “no-regret option” in the global aggregate, but in particular for China and India due to high air quality benefits, and also for developed regions due to net negative mitigation costs. Energy and resource exporting regions, on the other hand, face higher mitigation cost than benefits. Our analysis further shows that the result of higher health benefits than mitigation costs is robust across various air pollution control scenarios. However, although climate mitigation results in substantial air pollution emission reductions overall, we find significant remaining emissions in the transport and industry sectors even in a 2 ∘C world. We therefore call for further research in how to optimally exploit climate policy and air pollution control, deriving climate change mitigation pathways that maximize co-benefits.
Published: 2020

3. 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

4. Similar estimates of temperature impacts on global wheat yield by three independent methods

Author: Frank Ewert, Jakarat Anothai, P. V. Vara Prasad, Davide Cammarano, Curtis D. Jones, Elias Fereres, Margarita Garcia-Vila, Soora Naresh Kumar, Eckart Priesack, Phillip D. Alderman, Andrew J. Challinor, Reimund P. Rötter, Alex C. Ruane, Christian Folberth, Gerrit Hoogenboom, Pierre Martre, Roberto C. Izaurralde, Fulu Tao, Pramod K. Aggarwal, Mohamed Jabloun, Jordi Doltra, Joshua Elliott, Christoph Müller, Bing Liu, Iurii Shcherbak, Jeffrey W. White, Bruno Basso, Senthold Asseng, Pierre Stratonovitch, Peter J. Thorburn, Claas Nendel, Taru Palosuo, Joost Wolf, Ann-Kristin Koehler, Thilo Streck, Jørgen E. Olesen, David B. Lobell, Kurt Christian Kersebaum, Delphine Deryng, L. A. Hunt, Garry O'Leary, Katharina Waha, Giacomo De Sanctis, Daniel Wallach, Yan Zhu, James W. Jones, Elke Stehfest, Mikhail A. Semenov, Christian Biernath, Claudio O. Stöckle, Thomas A. M. Pugh, Matthew P. Reynolds, Enli Wang, Bruce A. Kimball, Erwin Schmid, Iwan Supit, Zhigan Zhao, Michael J. Ottman, Sebastian Gayler, Cynthia Rosenzweig, Ehsan Eyshi Rezaei, Gerard W. Wall, National Engineering and Technology Center for Information Agriculture, Jiangsu Key Laboratory for Information Agriculture, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricutural 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), Potsdam Institute for Climate Impact Research (PIK), Institute of Crop Science and Resource Conservation [Bonn] (INRES), Rheinische Friedrich-Wilhelms-Universität Bonn, Leibniz-Zentrum für Agrarlandschaftsforschung (ZALF), Leibniz Association, Center for Climate Systems Research [New York] (CCSR), Columbia University [New York], Computation Institute, Loyola University of Chicago, Department of Environmental Earth System Science and Center on Food Security and the Environment, Stanford University, Génétique Diversité et Ecophysiologie des Céréales (GDEC), Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-Institut National de la Recherche Agronomique (INRA), NASA Goddard Institute for Space Studies (GISS), NASA Goddard Space Flight Center (GSFC), 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, CGIAR Research Program on Climate Change, Agriculture and Food Security, Borlaug Institute for South Asia, CIMMYT, Consultative Group on International Agricultural Research (CGIAR), Department of Plant and Soil Sciences, Mississippi State University [Mississippi], Department of Plant Science, Faculty of Natural Resources, Prince of Songkla University (PSU), Department of Geological Sciences, University of Oregon [Eugene], W. K. Kellogg Biological Station (KBS), Michigan State University [East Lansing], Michigan State University System-Michigan State University System, Institute of Soil Ecology [Neuherberg] (IBOE), Helmholtz-Zentrum München (HZM), 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, CGIAR-ESSP Program on Climate Change, Agriculture and Food Security, International Center for Tropical Agriculture, European Commission - Joint Research Centre [Ispra] (JRC), Cantabrian Agricultural Research and Training Centre, Department of Agronomy, Purdue University [West Lafayette], Department of Geography, University of Liverpool, Ecosystem Services and Management Program, International Institute for Applied Systems Analysis (IIASA), Institute of Soil Science and Land Evaluation, University of Hohenheim, AgWeatherNet Program, Washington State University (WSU), 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 and M AgriLife Research, Texas A&M University System, Department of Agroecology, Aarhus University [Aarhus], US Arid-Land Agricultural Research Center, United States Department of Agriculture, Centre for Environment Science and Climate Resilient Agriculture (CESCRA), Indian Agricultural Research Institute (IARI), Institute of Landscape Systems Analysis, Leibniz Centre for Agricultural Landscape Research, Landscape & Water Sciences, Department of Environment of Victoria, The School of Plant Sciences, University of Arizona, Natural resources institute Finland, Institute of Ecology, German Research Center for Environmental Health, Institut für Meteorologie und Klimaforschung - Atmosphärische Umweltforschung (IMK-IFU), Karlsruher Institut für Technologie (KIT), School of Geography, Earth and Environmental Sciences [Birmingham], University of Birmingham [Birmingham], Birmingham Institute of Forest Research (BIFoR), International Maize and Wheat Improvement Center (CIMMYT), Consultative Group on International Agricultural Research [CGIAR] (CGIAR), Center for Development Research (ZEF), Environmental Impacts Group, Georg-August-University [Göttingen], Universität für Bodenkultur Wien [Vienne, Autriche] (BOKU), Computational and Systems Biology Department, Rothamsted Research, Biotechnology and Biological Sciences Research Council, Netherlands Environmental Assessment Agency, Department of Biological Systems Engineering, University of Wisconsin-Madison, PPS, WSG and CALM, Wageningen University and Research [Wageningen] (WUR), Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences [Beijing] (CAS), Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), USDA-ARS, Arid-Land Agricultural Research Center, China Agricultural University (CAU), National High-Tech Research and Development Program of China (2013AA100404), the National Natural Science Foundation of China (31271616, 31611130182, 41571088 and 31561143003), the National Research Foundation for the Doctoral Program of Higher Education of China (20120097110042), the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD), China Scholarship Council., IFPRI through the Global Futures and Strategic Foresight project, the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), the CGIAR Research Program on Wheat, the Agricultural Model Intercomparison and Improvement Project (AgMIP), Agricultural & Biological Engineering Department, University of Florida [Gainesville], Institute of Crop Science and Resource Conservation, University of Bonn-Division of Plant Nutrition, Stanford University [Stanford], 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), UMR : AGroécologie, Innovations, TeRritoires, Ecole Nationale Supérieure Agronomique de Toulouse, Prince of Songkla University, Texas A&M AgriLife Research and Extension Center, Natural Resources Institute Finland, Georg-August-Universität Göttingen, Wageningen University and Research Center (WUR), China Agricultural University, Division of Plant Nutrition-University of Bonn, Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro), University of Florida, Potsdam Institute for Climate Impact Research ( PIK ), Leibniz Centre for Agricultural Landscape Research, Institute for Landscape Biogeochemistry, Center for Climate Systems Research [New York] ( CCSR ), 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 ), NASA Goddard Institute for Space Studies ( GISS ), NASA Goddard Space Flight Center ( GSFC ), Consultative Group on International Agricultural Research ( CGIAR ), W.K. Kellogg Biological Station, Institute of Soil Ecology [Neuherberg] ( IBOE ), Helmholtz-Zentrum München ( HZM ), James Hutton Institute, Institute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, European Commission - Joint Research Centre [Ispra] ( JRC ), International Institute for Applied Systems Analysis ( IIASA ), Washington State University ( WSU ), Texas A and M University ( TAMU ), Leibniz Centre for Agricultural Landscape Research (ZALF), Centre for Environment Science and Climate Resilient Agriculture ( CESCRA ), Indian Agricultural Research Institute ( IARI ), Institut für Meteorologie und Klimaforschung - Atmosphärische Umweltforschung ( IMK-IFU ), Karlsruher Institut für Technologie ( KIT ), School of Geography, Earth & Environmental Science and Birmingham Institute of Forest Research, University of Birmingham, International Maize and Wheat Improvement Center ( CIMMYT ), Bonn Universität [Bonn], University of Natural Resources and Life Sciences, University of Wisconsin-Madison [Madison], Wageningen University and Research Center ( WUR ), Chinese Academy of Sciences [Beijing] ( CAS ), Commonwealth Scientific and Industrial Research Organisation, Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP), Université de Toulouse (UT)-Université de Toulouse (UT), Helmholtz Zentrum München = German Research Center for Environmental Health, Natural Resources Institute Finland (LUKE), Georg-August-University = Georg-August-Universität Göttingen, Universität für Bodenkultur Wien = University of Natural Resources and Life [Vienne, Autriche] (BOKU), Biotechnology and Biological Sciences Research Council (BBSRC), and Institute of geographical sciences and natural resources research [CAS] (IGSNRR)
Subjects: 0106 biological sciences, [SDV.SA]Life Sciences [q-bio]/Agricultural sciences, [ SDV.BV ] Life Sciences [q-bio]/Vegetal Biology, régression statistique, 010504 meteorology & atmospheric sciences, impact sur le rendement, klim, Atmospheric sciences, 01 natural sciences, incertitude, wheat, uncertainty, [ SDV.SA ] Life Sciences [q-bio]/Agricultural sciences, 2. Zero hunger, changement climatique, Regression analysis, statistical regression, simulation, PE&RC, [ SDE.MCG ] Environmental Sciences/Global Changes, sécurité alimentaire, Plant Production Systems, modèle de récolte, Yield (finance), comparaison de modèles, [SDE.MCG]Environmental Sciences/Global Changes, Climate change, Environmental Science (miscellaneous), Earth System Science, blé, température, Life Science, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, réchauffement climatique, global change, 0105 earth and related environmental sciences, Hydrology, WIMEK, Global temperature, business.industry, Crop yield, Global warming, Climate Resilience, 13. Climate action, Agriculture, Klimaatbestendigheid, Plantaardige Productiesystemen, Environmental science, Leerstoelgroep Aardsysteemkunde, Climate model, business, Social Sciences (miscellaneous), 010606 plant biology & botany
Abstract: The potential impact of global temperature change on global crop yield has recently been assessed with different methods. Here we show that grid-based and point-based simulations and statistical regressions (from historic records), without deliberate adaptation or CO2 fertilization effects, produce similar estimates of temperature impact on wheat yields at global and national scales. With a 1 °C global temperature increase, global wheat yield is projected to decline between 4.1% and 6.4%. Projected relative temperature impacts from different methods were similar for major wheat-producing countries China, India, USA and France, but less so for Russia. Point-based and grid-based simulations, and to some extent the statistical regressions, were consistent in projecting that warmer regions are likely to suffer more yield loss with increasing temperature than cooler regions. By forming a multi-method ensemble, it was possible to quantify ‘method uncertainty’ in addition to model uncertainty. This significantly improves confidence in estimates of climate impacts on global food security. The potential impact of global temperature change on global crop yield has recently been assessed with different methods. Here we show that grid-based and point-based simulations and statistical regressions (from historic records), without deliberate adaptation or CO2 fertilization effects, produce similar estimates of temperature impact on wheat yields at global and national scales. With a 1 °C global temperature increase, global wheat yield is projected to decline between 4.1% and 6.4%. Projected relative temperature impacts from different methods were similar for major wheat-producing countries China, India, USA and France, but less so for Russia. Point-based and grid-based simulations, and to some extent the statistical regressions, were consistent in projecting that warmer regions are likely to suffer more yield loss with increasing temperature than cooler regions. By forming a multi-method ensemble, it was possible to quantify ‘method uncertainty’ in addition to model uncertainty. This significantly improves confidence in estimates of climate impacts on global food security.
Published: 2016

5. 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

6. 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

7. 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

8. A diagnostic evaluation of precipitation in CORDEX models over Southern Africa

Author: Grigory Nikulin, Bruce Hewitson, Alice Favre, Christopher Lennard, Hans-Jürgen Panitz, Michael Kent, Mxolisi Shongwe, Alessandro Dosio, Matthias Büchner, Izidine Pinto, Evangelia-Anna Kalognomou, University of Cape Town, Laboratory of Heat Transfer and Environmental Engineering, Aristotle University of Thessaloniki, South African Weather Service ( SAWS ), Biogéosciences [Dijon] ( BGS ), Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique ( CNRS ), JRC Institute for Environment and Sustainability ( IES ), European Commission - Joint Research Centre [Ispra] ( JRC ), Rossby Centre, Swedish Meteorological and Hydrological Institute ( SMHI ), Institut für Meteorologie und Klimaforschung, Karlsruher Institut für Technologie ( KIT ), Potsdam Institute for Climate Impact Research ( PIK ), Research supported by the Global Change System for Analysis, Research, and Training (START) in partnership with the University of Cape Town's Climate Systems Analysis Group, the World Climate Research Program, the Climate and Development Knowledge Network, the International Centre for Theoretical Physics, the Swedish Meteorological and Hydrological Institute, and the European Union Seventh Framework Programme (FP7, 2012-2013) under Grant Agreement 316167., Laboratory of Heat Transfer and Environmental Engineering [Thessaloniki] (LHTEE), South African Weather Service (SAWS), Biogéosciences [UMR 6282] [Dijon] (BGS), Centre National de la Recherche Scientifique (CNRS)-Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, JRC Institute for Environment and Sustainability (IES), European Commission - Joint Research Centre [Ispra] (JRC), Rossby Centre, SMHI, Norrköping, 601 76, Sweden, Swedish Meteorological and Hydrological Institute (SMHI), Institute for Meteorology and Climate Research (IMK), Karlsruhe Institute of Technology (KIT), and Potsdam Institute for Climate Impact Research (PIK)
Subjects: Climatology, Atmospheric Science, 010504 meteorology & atmospheric sciences, [SDE.MCG]Environmental Sciences/Global Changes, Ensemble average, 0207 environmental engineering, Regional models, Magnitude (mathematics), 02 engineering and technology, Diagnostic evaluation, Atmospheric sciences, 01 natural sciences, Climate prediction, [ SDE.MCG ] Environmental Sciences/Global Changes, 13. Climate action, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, Environmental science, Climate model, Precipitation, [ SDU.STU.CL ] Sciences of the Universe [physics]/Earth Sciences/Climatology, 020701 environmental engineering, Climate variability, 0105 earth and related environmental sciences, Downscaling
Abstract: 30 pages; International audience; The authors evaluate the ability of 10 regional climate models (RCMs) to simulate precipitation over Southern Africa within the Coordinated Regional Climate Downscaling Experiment (CORDEX) framework. An ensemble of 10 regional climate simulations and the ensemble average is analyzed to evaluate the models' ability to reproduce seasonal and interannual regional climatic features over regions of the subcontinent. All the RCMs use a similar domain, have a spatial resolution of ;50 km, and are driven by the Interim ECMWF Re-Analysis (ERA-Interim; 1989-2008). Results are compared against a number of observational datasets. In general, the spatial and temporal nature of rainfall over the region is captured by all RCMs, although individual models exhibit wet or dry biases over particular regions of the domain. Models generally produce lower seasonal variability of precipitation compared to observations and the magnitude of the variability varies in space and time. Model biases are related to model setup, simulated circulation anomalies, and moisture transport. The multimodel ensemble mean generally outperforms individual models, with bias magnitudes similar to differences across the observational datasets. In the northern parts of the domain, some of the RCMs and the ensemble average improve the precipitation climate compared to that of ERA-Interim. The models are generally able to capture the dry (wet) precipitation anomaly associated with El Nño (La Niña) events across the region. Based on this analysis, the authors suggest that the present set of RCMs can be used to provide useful information on climate projections of rainfall over Southern Africa.
Published: 2013

9. 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

10. 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

11. 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

12. Spatially explicit analysis identifies significant potential for bioenergy with carbon capture and storage in China

Author: Xin Yang, Jianmin Ma, Rong Wang, Guofeng Shen, Olivier Boucher, Siqing Xu, Ivan A. Janssens, Xingnan Ye, Yutao Wang, Xiaofan Xing, Josep Peñuelas, Lin Wang, Daniel S. Goll, Philippe Ciais, James H. Clark, Nico Bauer, Xu Tang, Jianmin Chen, Qing X. Li, Bo Pan, Wei Li, Junji Cao, Gang Luo, Shicheng Zhang, Yves Balkanski, Yechen Yang, Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Fudan University [Shanghai], 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), 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), 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)-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), 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), This work was funded by the National Natural Science Foundation of China (41877506,21925601, 41922057), National Key Research and Development Program of China(No. 2017YFC0212200), the Chinese Thousand Youth Talents Program, Chinese Academyof Science (XDA23010100), the ERC-Synergy IMBALANCE-P, and the ANR CLANDConvergence Institute 16-CONV-0003. The research leading to these results was also supported by the PEGASOS (01LA1826C) project funded by the German Federal Ministry ofEducation and Research (BMBF). We gratefully acknowledge the useful comments offeredby three anonymous referees which are helpful to improve the manuscript., and ANR-16-CONV-0003,CLAND,CLAND : Changement climatique et usage des terres(2016)
Subjects: Marginal cost, 010504 meteorology & atmospheric sciences, Economics, Natural resource economics, 020209 energy, Science, General Physics and Astronomy, Biomass, 02 engineering and technology, 7. Clean energy, 01 natural sciences, Article, General Biochemistry, Genetics and Molecular Biology, 12. Responsible consumption, Engineering, Economic cost, 11. Sustainability, 0202 electrical engineering, electronic engineering, information engineering, Carbon capture and storage, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, Climate-change mitigation, Biology, ddc:910, 0105 earth and related environmental sciences, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Energy, Multidisciplinary, Agriculture, Bio-energy with carbon capture and storage, General Chemistry, Climate change mitigation, Carbon neutrality, 13. Climate action, Greenhouse gas, Environmental science, Climate Change Mitigation, Engineering sciences. Technology
Abstract: As China ramped-up coal power capacities rapidly while CO2 emissions need to decline, these capacities would turn into stranded assets. To deal with this risk, a promising option is to retrofit these capacities to co-fire with biomass and eventually upgrade to CCS operation (BECCS), but the feasibility is debated with respect to negative impacts on broader sustainability issues. Here we present a data-rich spatially explicit approach to estimate the marginal cost curve for decarbonizing the power sector in China with BECCS. We identify a potential of 222 GW of power capacities in 2836 counties generated by co-firing 0.9 Gt of biomass from the same county, with half being agricultural residues. Our spatially explicit method helps to reduce uncertainty in the economic costs and emissions of BECCS, identify the best opportunities for bioenergy and show the limitations by logistical challenges to achieve carbon neutrality in the power sector with large-scale BECCS in China., China has pledged to achieve carbon neutrality in 2060. Here the authors find a promising option to abate 1.0 Gt CO2-eq yr−1 of carbon emissions at a marginal cost of $69 (t CO2-eq)−1 by retrofitting 222 GW of coal power plants to co-fire with biomass and upgrading to CCS operation across 2836 counties in China.
Published: 2021

13. 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

14. 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

15. 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

16. Antarctic ice sheet response to sudden and sustained ice-shelf collapse (ABUMIP)

Author: Sun, Sainan, Pattyn, Frank, Simon, Erika G., Albrecht, Torsten, Cornford, Stephen, Calov, Reinhard, Dumas, Christophe, Gillet-Chaulet, Fabien, Goelzer, Heiko, Golledge, Nicholas R., Greve, Ralf, Hoffman, Matthew J., Humbert, Angelika, Kazmierczak, Elise, Kleiner, Thomas, Leguy, Gunter R., Lipscomb, William H., Martin, Daniel, Morlighem, Mathieu, Nowicki, Sophie, Pollard, David, Price, Stephen, Quiquet, Aurélien, Seroussi, Hélène, Schlemm, Tanja, Sutter, Johannes, Van De Wal, Roderik S.W., Winkelmann, Ricarda, Zhang, Tong, Sub Dynamics Meteorology, Proceskunde, Sub Algemeen Marine & Atmospheric Res, Coastal dynamics, Fluvial systems and Global change, Laboratoire de Glaciologie [Bruxelles], Université libre de Bruxelles (ULB), NASA Goddard Space Flight Center (GSFC), Potsdam Institute for Climate Impact Research (PIK), Swansea University, 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 du climat (CLIM), 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), Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), 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 Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Sub Dynamics Meteorology, Proceskunde, Sub Algemeen Marine & Atmospheric Res, and Coastal dynamics, Fluvial systems and Global change
Subjects: 010504 meteorology & atmospheric sciences, Ice stream, F700, Collapse (topology), Antarctic ice sheet, F800, Present day, 010502 geochemistry & geophysics, Atmospheric sciences, 01 natural sciences, F900, Physical Geography and Environmental Geoscience, Ice shelf, Antarctic glaciology, Meteorology & Atmospheric Sciences, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, ice shelves, 0105 earth and related environmental sciences, Earth-Surface Processes, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, geography, geography.geographical_feature_category, East antarctica, Glaciologie, Radiative forcing, Climate Action, 13. Climate action, ice-sheet modelling, Ice sheet, Geology, Sciences exactes et naturelles
Abstract: Antarctica's ice shelves modulate the grounded ice flow, and weakening of ice shelves due to climate forcing will decrease their ‘buttressing’ effect, causing a response in the grounded ice. While the processes governing ice-shelf weakening are complex, uncertainties in the response of the grounded ice sheet are also difficult to assess. The Antarctic BUttressing Model Intercomparison Project (ABUMIP) compares ice-sheet model responses to decrease in buttressing by investigating the ‘end-member’ scenario of total and sustained loss of ice shelves. Although unrealistic, this scenario enables gauging the sensitivity of an ensemble of 15 ice-sheet models to a total loss of buttressing, hence exhibiting the full potential of marine ice-sheet instability. All models predict that this scenario leads to multi-metre (1–12 m) sea-level rise over 500 years from present day. West Antarctic ice sheet collapse alone leads to a 1.91–5.08 m sea-level rise due to the marine ice-sheet instability. Mass loss rates are a strong function of the sliding/friction law, with plastic laws cause a further destabilization of the Aurora and Wilkes Subglacial Basins, East Antarctica. Improvements to marine ice-sheet models have greatly reduced variability between modelled ice-sheet responses to extreme ice-shelf loss, e.g. compared to the SeaRISE assessments., info:eu-repo/semantics/published
Published: 2020

17. 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

18. 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

19. Historical and future changes in global flood magnitude – evidence from a model–observation investigation

Author: H. X. Do, F. Zhao, S. Westra, M. Leonard, L. Gudmundsson, J. E. S. Boulange, J. Chang, P. Ciais, D. Gerten, S. N. Gosling, H. Müller Schmied, T. Stacke, C.-E. Telteu, Y. Wada, University of Adelaide, Potsdam Institute for Climate Impact Research (PIK), Physics Department [Adelaide], Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Université de Tsukuba = University of Tsukuba, 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), School of Geography [Nottingham], University of Nottingham, UK (UON), Goethe-Universität Frankfurt am Main, Helmholtz-Zentrum Geesthacht (GKSS), International Institute for Applied Systems Analysis [Laxenburg] (IIASA), European Project: 776613,Fighting and adapting to climate change,H2020-EU.3.5.1,EUCP(2017), 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, 0208 environmental biotechnology, Climate change, Context (language use), 02 engineering and technology, lcsh:Technology, 01 natural sciences, lcsh:TD1-1066, Streamflow, lcsh:Environmental technology. Sanitary engineering, [SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology, lcsh:Environmental sciences, 0105 earth and related environmental sciences, lcsh:GE1-350, Flood myth, lcsh:T, lcsh:Geography. Anthropology. Recreation, Radiative forcing, 020801 environmental engineering, lcsh:G, 13. Climate action, Greenhouse gas, Climatology, Spatial ecology, Environmental science, Climate model
Abstract: International audience; To improve the understanding of trends in extreme flows related to flood events at the global scale, historical and future changes of annual maxima of 7 d streamflow are investigated , using a comprehensive streamflow archive and six global hydrological models. The models' capacity to charac-terise trends in annual maxima of 7 d streamflow at the continental and global scale is evaluated across 3666 river gauge locations over the period from 1971 to 2005, focusing on four aspects of trends: (i) mean, (ii) standard deviation, (iii) percentage of locations showing significant trends and (iv) spatial pattern. Compared to observed trends, simulated trends driven by observed climate forcing generally have a higher mean, lower spread and a similar percentage of locations showing significant trends. Models show a low to moderate capacity to simulate spatial patterns of historical trends, with approximately only from 12 % to 25 % of the spatial variance of observed trends across all gauge stations accounted for by the simulations. Interestingly, there are statistically significant differences between trends simulated by global hydrological models (GHMs) forced with observational climate and by those forced by bias-corrected climate model output during the historical period, suggesting the important role of the stochastic natural (decadal, inter-annual) climate variability. Significant differences were found in simulated flood trends when averaged only at gauged locations compared to those averaged across all simulated grid cells, highlighting the potential for bias toward well-observed regions in our understanding of changes in floods. Future climate projections (simulated under the RCP2.6 and RCP6.0 greenhouse gas concentration scenarios) suggest a potentially high level of change in individual regions, with up to 35 % of cells showing a statistically significant trend (increase or de-Published by Copernicus Publications on behalf of the European Geosciences Union. 1544 H. X. Do et al.: Historical and future changes in global flood magnitude crease; at 10 % significance level) and greater changes indicated for the higher concentration pathway. Importantly, the observed streamflow database under-samples the percentage of locations consistently projected with increased flood hazards under the RCP6.0 greenhouse gas concentration scenario by more than an order of magnitude (0.9 % compared to 11.7 %). This finding indicates a highly uncertain future for both flood-prone communities and decision makers in the context of climate change.
Published: 2020

20. 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

21. 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

22. 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

23. Instabilities of low-latitude easterly jets in the presence of moist convection and topography and related cyclogenesis, in a simple atmospheric model

Author: Vladimir Zeitlin, Masoud Rostami, 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), and Potsdam Institute for Climate Impact Research (PIK)
Subjects: [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, SIMPLE (dark matter experiment), Low latitude, 010504 meteorology & atmospheric sciences, [SDU.STU.GP]Sciences of the Universe [physics]/Earth Sciences/Geophysics [physics.geo-ph], Computational Mechanics, Astronomy and Astrophysics, Atmospheric model, [SDU.STU.ME]Sciences of the Universe [physics]/Earth Sciences/Meteorology, Atmospheric sciences, 01 natural sciences, 010305 fluids & plasmas, Geophysics, 13. Climate action, Geochemistry and Petrology, Mechanics of Materials, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, 0103 physical sciences, Cyclogenesis, Moist convection, [PHYS.MECA.MEFL]Physics [physics]/Mechanics [physics]/Fluid mechanics [physics.class-ph], Geology, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences
Abstract: International audience
Published: 2021

24. Predicting the effect of confinement on the COVID-19 spread using machine learning enriched with satellite air pollution observations

Author: Xu Tang, Jianmin Chen, Tun Lu, Haidong Kan, Philippe Ciais, Renhe Zhang, Ivan A. Janssens, Rong Wang, Jordi Sardans, Lin Wang, Xiaofan Xing, Josep Peñuelas, Xiangrong Wang, Didier A. Hauglustaine, Ruipu Yang, Yves Balkanski, Yijing Wang, Weibing Wang, Lidia Morawska, Guy Brasseur, Junji Cao, Yuankang Xiong, Nico Bauer, Dongsheng Li, Yifei Deng, Olivier Boucher, Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Fudan University [Shanghai], Microsoft Research Asia, Institute of Atmospheric Physics [Beijing] (IAP), Chinese Academy of Sciences [Beijing] (CAS), CREAF - Centre for Ecological Research and Applied Forestries, 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), Potsdam Institute for Climate Impact Research (PIK), University of Antwerp (UA), Max Planck Institute for Meteorology (MPI-M), Max-Planck-Gesellschaft, International Laboratory for Air Quality and Health [Brisbane], Queensland University of Technology [Brisbane] (QUT), ANR-15-CE04-0005, European Space Agency, ESA: 725546, ESRIN/4000123002/18/I-NB, National Natural Science Foundation of China, NSFC: 18107, 41877506, Generalitat de Catalunya: AGAUR-2020PANDE00117, ACKNOWLEDGMENTS. We thank H. J. Yu for important comments and J. H. Pan for help in compiling the epidemiological data. This work was supported by the National Natural Science Foundation of China (41877506), the Fudan’s Wangdao Undergraduate Research Opportunities Program (18107), the Chinese Thousand Youth Talents Program, the PolEASIA-ANR project (ANR-15-CE04-0005), and the Australia-China Centre for Air Quality Science and Management. J.P. and J.S. acknowledge financial support from the Catalan Government grant AGAUR-2020PANDE00117. P.C. acknowledges support from the European Space Agency Climate Change Initiative ESA-CCI RECCAP2 project (ESRIN/4000123002/18/I-NB) and the Observation-based system for monitoring and verification of greenhouse gases project (VERIFY, grant 725546)., 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), National Natural Science Foundation of China, Fudan University, Agence Nationale de la Recherche (France), Generalitat de Catalunya, European Space Agency, Xing, Xiaofan [0000-0002-0334-6408], Wang, Rong [0000-0003-1962-0165], Wang, Weibing [0000-0002-4497-5251], Peñuelas, Josep [0000-0002-7215-0150], Ciais, Philippe [0000-0001-8560-4943], Bauer, Nico [0000-0002-0211-4162], Morawska, Lidia [0000-0002-0594-9683], Sardans, Jordi [0000-0003-2478-0219], Wang, Lin [0000-0002-4905-3432], Chen, Jianmin [0000-0001-5859-3070], Zhang, Renhe [0000-0001-7750-8679], Xing, Xiaofan, Wang, Rong, Wang, Weibing, Peñuelas, Josep, Ciais, Philippe, Bauer, Nico, Morawska, Lidia, Sardans, Jordi, Wang, Lin, Chen, Jianmin, and Zhang, Renhe
Subjects: China, 2019-20 coronavirus outbreak, 010504 meteorology & atmospheric sciences, Coronavirus disease 2019 (COVID-19), [SDV]Life Sciences [q-bio], Air pollution, Satellite observation, Pandemic management, medicine.disease_cause, 7. Clean energy, 01 natural sciences, Surrogate data, Troposphere, 03 medical and health sciences, Machine learning, medicine, Humans, Baseline (configuration management), Biology, 030304 developmental biology, 0105 earth and related environmental sciences, 0303 health sciences, Multidisciplinary, Scenario based, COVID-19, 3. Good health, Socioeconomic Factors, 13. Climate action, Climatology, Physical Sciences, Environmental science, Satellite, Engineering sciences. Technology
Abstract: The real-time monitoring of reductions of economic activity by containment measures and its effect on the transmission of the coronavirus (COVID-19) is a critical unanswered question. We inferred 5,642 weekly activity anomalies from the meteorology-adjusted differences in spaceborne tropospheric NO2 column concentrations after the 2020 COVID-19 outbreak relative to the baseline from 2016 to 2019. Two satellite observations reveal reincreasing economic activity associated with lifting control measures that comes together with accelerating COVID-19 cases before the winter of 2020/2021. Application of the near-real-time satellite NO2 observations produces a much better prediction of the deceleration of COVID-19 cases than applying the Oxford Government Response Tracker, the Public Health and Social Measures, or human mobility data as alternative predictors. A convergent cross-mapping suggests that economic activity reduction inferred from NO2 is a driver of case deceleration in most of the territories. This effect, however, is not linear, while further activity reductions were associated with weaker deceleration. Over the winter of 2020/2021, nearly 1 million daily COVID-19 cases could have been avoided by optimizing the timing and strength of activity reduction relative to a scenario based on the real distribution. Our study shows how satellite observations can provide surrogate data for activity reduction during the COVID-19 pandemic and monitor the effectiveness of containment to the pandemic before vaccines become widely available., This work was supported by the National Natural Science Foundation of China (41877506), the Fudan’s Wangdao Undergraduate Research Opportunities Program (18107), the Chinese Thousand Youth Talents Program, the PolEASIA-ANR project (ANR15-CE04-0005), and the Australia-China Centre for Air Quality Science and Management. J.P. and J.S. acknowledge financial support from the Catalan Government grant AGAUR-2020PANDE00117. P.C. acknowledges support from the European Space Agency Climate Change Initiative ESA-CCI RECCAP2 project (ESRIN/4000123002/18/I-NB) and the Observation-based system for monitoring and verification of greenhouse gases project (VERIFY, grant 725546).
Published: 2021

25. No historical evidence for increased vulnerability of French crop production to climatic hazards

Author: Philippe Ciais, David Makowski, Tamara Ben-Ari, Bernhard Schauberger, Julien Boé, Potsdam Institute for Climate Impact Research (PIK), 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), Mathématiques et Informatique Appliquées (MIA Paris-Saclay), AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Agronomie, Climat, Environnement, Couplages et Incertitudes [Toulouse] (CECI), Centre Européen de Recherche et de Formation Avancée en Calcul Scientifique (CERFACS)-Institut national des sciences de l'Univers (INSU - CNRS)-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)-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), Mathématiques et Informatique Appliquées (MIA-Paris), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-AgroParisTech-Université Paris-Saclay, CECI, CERFACS / CNRS (CECI), and Centre National de la Recherche Scientifique (CNRS)
Subjects: 0106 biological sciences, Atmospheric Science, 010504 meteorology & atmospheric sciences, Yield (finance), [SDE.MCG]Environmental Sciences/Global Changes, Vulnerability, Climate change, Multi crop, Historical evidence, 01 natural sciences, Exposure, Crop, Sensitivity, Long-term, Crop production, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], Weather, 0105 earth and related environmental sciences, 2. Zero hunger, Global and Planetary Change, Adverse weather, Agroforestry, fungi, food and beverages, Forestry, Non-parametric, Hazard, 13. Climate action, Environmental science, Agronomy and Crop Science, 010606 plant biology & botany
Abstract: International audience; Recent adverse weather events have questioned the stability of crop production systems. Here, we assessed the vulnerability of eleven major crops in France between 1959 and 2018 as a function of climate, crafting a novel hazard framework that combines exposure and sensitivity to weather-related hazards. Exposure was defined as the frequency of hazardous climate conditions. Sensitivity of crops was estimated by the yield response to single and compound hazards, using observed yields available at département (county) level. Vulnerability was computed as the exposure-weighted average of crop sensitivities. Our results do not reveal any evidence for historically increased vulnerability of French crop production. Sensitivity to adverse weather events, and thus the overall vulnerability, has significantly decreased for six of the eleven crops between 1959 and 2018, and shown no significant decline or remained stable for the other five. Yet compound hazards can induce yield losses of 30% or more for several crops. Moreover, as heat-related hazards are projected to become more frequent with climate change, crop vulnerability may rise again in the future.
Published: 2021

26. 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

27. 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

28. 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

29. Systematic map of the literature on carbon lock-in induced by long-lived capital

Author: Céline Guivarch, Max Callaghan, Felix Creutzig, Jan C. Minx, Vivien Fisch-Romito, 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), Mercator Research Institute on Global Commons and Climate Change (MCC), Potsdam Institute for Climate Impact Research (PIK), and Chaire MPDD
Subjects: 010504 meteorology & atmospheric sciences, Renewable Energy, Sustainability and the Environment, Natural resource economics, 020209 energy, 1. No poverty, Public Health, Environmental and Occupational Health, 02 engineering and technology, [SHS.ECO]Humanities and Social Sciences/Economics and Finance, 01 natural sciences, Carbon lock-in, 12. Responsible consumption, Climate change mitigation, 13. Climate action, Capital (economics), [SDE]Environmental Sciences, 11. Sustainability, 0202 electrical engineering, electronic engineering, information engineering, ddc:333, ddc:500, Business, ComputingMilieux_MISCELLANEOUS, Evidence synthesis, 0105 earth and related environmental sciences, General Environmental Science
Abstract: Long-lived capital-stocks (LLCS) such as infrastructure and buildings have significant and long-lasting implications for greenhouse gas emissions. They contribute to carbon lock-in and may hinder a rapid decarbonization of energy systems. Here we provide a systematic map of the literature on carbon lock-in induced by LLCS. Based on a structured search of the Web of Science and Scopus, we identified 226 publications from 38 095 search results using a supervised machine learning approach. We show biases toward power generation and toward developed countries. We also identify 11 indicators used to quantify carbon lock-in. Quantifications of committed emissions (cumulative emissions that would occur over the remaining operational lifetime of an asset) or stranded assets (premature retirement/retrofitting or under-utilization of assets along a given pathway) are the most commonly used metrics, whereas institutional indicators are scarcely represented. The synthesis of quantifications shows that (i) global committed emissions have slightly increased over time, (ii) coal power plants are a major source of committed emissions and are exposed to risk of becoming stranded, (iii) delayed mitigation action increases stranded assets and (iv) sectoral distribution and amount of stranded assets differ between countries. A thematic analysis of policy implications highlights the need to assure stability and legitimacy of climate policies and to enable coordination between stakeholders. Carbon pricing is one of the most cited policy instrument, but the literature emphasizes that it should not be the only instrument used and should instead be complemented with other policy instruments, such as technical regulations and financial support for low carbon capital deployment. Further research is warranted on urban-scale, in developing countries and outside the electricity generation sector, notably on buildings, where stranded assets could be high.
Published: 2021

30. Potential yield simulated by global gridded crop models: using a process-based emulator to explain their differences

Author: Sylvain Pellerin, Philippe Ciais, Wenfeng Liu, Thomas A. M. Pugh, Christoph Müller, Bruno Ringeval, Christian Folberth, Nathaniel D. Mueller, Philippe Debaeke, 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), Potsdam Institute for Climate Impact Research (PIK), University of Birmingham [Birmingham], Department of Earth System Science [Irvine] (ESS), University of California [Irvine] (UCI), University of California-University of California, 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), International Institute for Applied Systems Analysis [Laxenburg] (IIASA), College of Water Resources and Civil Engineering [Beijing], China Agricultural University (CAU), AGroécologie, Innovations, teRritoires (AGIR), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), University of California [Irvine] (UC Irvine), University of California (UC)-University of California (UC), 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 de Toulouse (UT)-Université de Toulouse (UT)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Subjects: Canopy, 010504 meteorology & atmospheric sciences, Growing season, Grain filling, maize, Atmospheric sciences, Spatial distribution, phenology, 01 natural sciences, computer simulation, yield response, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, 0105 earth and related environmental sciences, Mathematics, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, growing season, lcsh:QE1-996.5, net primary production, Primary production, 04 agricultural and veterinary sciences, Growing degree-day, Grid, lcsh:Geology, agricultural modeling, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, aboveground biomass, Aboveground biomass
Abstract: How global gridded crop models (GGCMs) differ in their simulation of potential yield and reasons for those differences have never been assessed. The GGCM Intercomparison (GGCMI) offers a good framework for this assessment. Here, we built an emulator (called SMM for simple mechanistic model) of GGCMs based on generic and simplified formalism. The SMM equations describe crop phenology by a sum of growing degree days, canopy radiation absorption by the Beer–Lambert law, and its conversion into aboveground biomass by a radiation use efficiency (RUE). We fitted the parameters of this emulator against gridded aboveground maize biomass at the end of the growing season simulated by eight different GGCMs in a given year (2000). Our assumption is that the simple set of equations of SMM, after calibration, could reproduce the response of most GGCMs so that differences between GGCMs can be attributed to the parameters related to processes captured by the emulator. Despite huge differences between GGCMs, we show that if we fit both a parameter describing the thermal requirement for leaf emergence by adjusting its value to each grid-point in space, as done by GGCM modellers following the GGCMI protocol, and a GGCM-dependent globally uniform RUE, then the simple set of equations of the SMM emulator is sufficient to reproduce the spatial distribution of the original aboveground biomass simulated by most GGCMs. The grain filling is simulated in SMM by considering a fixed-in-time fraction of net primary productivity allocated to the grains (frac) once a threshold in leaves number (nthresh) is reached. Once calibrated, these two parameters allow for the capture of the relationship between potential yield and final aboveground biomass of each GGCM. It is particularly important as the divergence among GGCMs is larger for yield than for aboveground biomass. Thus, we showed that the divergence between GGCMs can be summarized by the differences in a few parameters. Our simple but mechanistic model could also be an interesting tool to test new developments in order to improve the simulation of potential yield at the global scale.
Published: 2021

31. Reviewing the scope and thematic focus of 100,000 publications on energy consumption, services and social aspects of climate change: A big data approach to demand-side mitigation

Author: Benjamin K. Sovacool, Leila Niamir, Pauline Scheelbeek, Tania Urmee, Max Callaghan, Helmut Haberl, Felix Creutzig, Mathilde Tessier, Charlie Wilson, Andrew Hook, Dominik Wiedenhofer, Aneeque Javaid, Jan C. Minx, William F. Lamb, Doris Virág, Zakia Afroz, Mark Andor, Kristian S. Nielsen, Anjali Ramakrishnan, Can Wan, Joyashree Roy, Lucia A. Reisch, Diana Ivanova, Andy Gouldson, Nadia Maïzi, Shreya Some, Chioma Daisy Onyige, Miklós Antal, Victor Court, Érika Mata, Maria J. Figueroa, Friederike C. Döbbe, Julio Díaz-José, Mahendra Sethi, Finn Müller-Hansen, Nandini Das, Steven Sorrell, Mercator Research Institute on Global Commons and Climate Change (MCC), Potsdam Institute for Climate Impact Research (PIK), Technical University Berlin, Sustainability Research Institute, School of Earth and Environment, University of Leeds, University of Sussex, Carleton University, College of Science - Health, Engineering and Education - Murdoch University, Murdoch, Western Australia, Australia, Leibniz Institut für Wirtschaftsforschung (RWI), Eötvös Loránd University (ELTE), Institute of Social Ecology Vienna (SEC), Alpen-Adria-Universität Klagenfurt [Klagenfurt, Austria], IFP Energies nouvelles (IFPEN), Jadavpur University, Tecnológico Nacional de México (TecNM), Stockholm School of Economics (SSE), Copenhagen Business School [Copenhagen] (CBS), MINES ParisTech - École nationale supérieure des mines de Paris, Université Paris sciences et lettres (PSL), IVL Swedish Environmental Research Institute Ltd, University of Port Harcourt, Asian Institute of Technology [Pathumthani] (AIT), London School of Hygiene and Tropical Medicine (LSHTM), Ahmedabad University, Centre de Mathématiques Appliquées (CMA), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Tsinghua University [Beijing] (THU), Tyndall Centre for Climate Change Research, University of East Anglia [Norwich] (UEA), International Institute for Applied Systems Analysis [Laxenburg] (IIASA), and Chaire MPDD
Subjects: Knowledge management, 010504 meteorology & atmospheric sciences, Community building, Social norm, Services, Climate change, 010501 environmental sciences, Epistemic community, Collective action, 01 natural sciences, Climate change mitigation, Political science, 11. Sustainability, Machine learning, Demand, Meteorology & Atmospheric Sciences, 0105 earth and related environmental sciences, General Environmental Science, Consumption (economics), Behavior, [SHS.SOCIO]Humanities and Social Sciences/Sociology, [SHS.STAT]Humanities and Social Sciences/Methods and statistics, Renewable Energy, Sustainability and the Environment, business.industry, IPCC, [SPI.NRJ]Engineering Sciences [physics]/Electric power, Public Health, Environmental and Occupational Health, 13. Climate action, Sustainability, business, Centrality, [SDU.OTHER]Sciences of the Universe [physics]/Other
Abstract: As current action remains insufficient to meet the goals of the Paris agreement let alone to stabilize the climate, there is increasing hope that solutions related to demand, services and social aspects of climate change mitigation can close the gap. However, given these topics are not investigated by a single epistemic community, the literature base underpinning the associated research continues to be undefined. Here, we aim to delineate a plausible body of literature capturing a comprehensive spectrum of demand, services and social aspects of climate change mitigation. As method we use a novel double-stacked expert—machine learning research architecture and expert evaluation to develop a typology and map key messages relevant for climate change mitigation within this body of literature. First, relying on the official key words provided to the Intergovernmental Panel on Climate Change by governments (across 17 queries), and on specific investigations of domain experts (27 queries), we identify 121 165 non-unique and 99 065 unique academic publications covering issues relevant for demand-side mitigation. Second, we identify a literature typology with four key clusters: policy, housing, mobility, and food/consumption. Third, we systematically extract key content-based insights finding that the housing literature emphasizes social and collective action, whereas the food/consumption literatures highlight behavioral change, but insights also demonstrate the dynamic relationship between behavioral change and social norms. All clusters point to the possibility of improved public health as a result of demand-side solutions. The centrality of the policy cluster suggests that political actions are what bring the different specific approaches together. Fourth, by mapping the underlying epistemic communities we find that researchers are already highly interconnected, glued together by common interests in sustainability and energy demand. We conclude by outlining avenues for interdisciplinary collaboration, synthetic analysis, community building, and by suggesting next steps for evaluating this body of literature.
Published: 2021

32. Introducing ‘Anthropocene Science’: A New International Journal for Addressing Human Impact on the Resilience of Planet Earth

Author: Patrick J. O’Farrell, Danny Hunter, Pete Smith, Othmane Merah, Saskia Keesstra, Ruth DeFries, Lindsay C. Stringer, Simone Bastianoni, Simron Jit Singh, Weiqiang Chen, Shizuka Hashimoto, Leonardo Fernandes Fraceto, Purushothaman Chirakkuzhyil Abhilash, Billie Turner, Prajal Pradhan, Neven S. Fučkar, Banaras Hindu University [Varanasi] (BHU), Università degli Studi di Siena = University of Siena (UNISI), Chinese Academy of Sciences [Beijing] (CAS), Columbia University [New York], Universidade Estadual Paulista Júlio de Mesquita Filho = São Paulo State University (UNESP), University of Oxford [Oxford], The University of Tokyo (UTokyo), The Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT) [Cali], Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT) [Rome] (Alliance), Consultative Group on International Agricultural Research [CGIAR] (CGIAR)-Consultative Group on International Agricultural Research [CGIAR] (CGIAR), Team Soil Water and Land Use, Wageningen Environmental Research, Wageningen UR, Wageningen University and Research [Wageningen] (WUR), Chimie Agro-Industrielle (CAI), Ecole nationale supérieure des ingénieurs en arts chimiques et technologiques-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), University of Cape Town, Potsdam Institute for Climate Impact Research (PIK), School of Environment, Enterprise and Development [Waterloo] (SEED), University of Waterloo [Waterloo], University of Aberdeen, University of York [York, UK], and Arizona State University [Tempe] (ASU)
Subjects: Sustainable development, 010504 meteorology & atmospheric sciences, [SDV]Life Sciences [q-bio], Environmental ethics, 010501 environmental sciences, 01 natural sciences, Editorial, Anthropocene, Planet, Political science, Earth (chemistry), Resilience (network), ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences
Abstract: International audience
Published: 2021

33. Human well-being in the Anthropocene: limits to growth

Author: David Collste, Sarah E. Cornell, Jorgen Randers, Johan Rockström, Per Espen Stoknes, Stockholm Resilience Centre, Stockholm University, Stockholm, Sweden, Centre d'Études et de Recherches sur le Développement International (CERDI), Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA), BI Norwegian Business School [Oslo], Potsdam Institute for Climate Impact Research (PIK), Stockholm University, and Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)
Subjects: Planetary Boundaries, Global and Planetary Change, [SHS.STAT]Humanities and Social Sciences/Methods and statistics, 010504 meteorology & atmospheric sciences, Integrated Assessment Models, 2030 Agenda, Sustainable Development Goals, 1. No poverty, 010501 environmental sciences, Management, Monitoring, Policy and Law, [SHS.ECO]Humanities and Social Sciences/Economics and Finance, 01 natural sciences, Safe Operating Space, 12. Responsible consumption, Human Needs, Sustainability, IAMs, Capabilities approach, [SHS.ENVIR]Humanities and Social Sciences/Environmental studies, 8. Economic growth, 11. Sustainability, Easterlin paradox, 0105 earth and related environmental sciences
Abstract: Non-technical summary Transformation of the world towards sustainability in line with the 2030 Agenda requires progress on multiple dimensions of human well-being. We track development of relevant indicators for Sustainable Development Goals (SDGs) 1–7 against gross domestic product (GDP) per person in seven world regions and the world as a whole. Across the regions, we find uniform development patterns where SDGs 1–7 – and therefore main human needs – are achieved at around US$15,000 measured in 2011 US$ purchasing power parity (PPP). Technical summary How does GDP per person relate to the achievement of well-being as targeted by the 2030 Agenda? The 2030 Agenda includes global ambitions to meet human needs and aspirations. However, these need to be met within planetary boundaries. In nascent world-earth modelling, human well-being as well as global environmental impacts are linked through economic production, which is tracked by GDP. We examined historic developments on 5-year intervals, 1980–2015, between average income and the advancement on indicators of SDGs 1–7. This was done for both seven world regions and the world as a whole. We find uniform patterns of saturation for all regions above an income threshold somewhere around US$15,000 measured in 2011 US$ PPP. At this level, main human needs and capabilities are met. The level is also consistent with studies of life satisfaction and the Easterlin paradox. We observe stark differences with respect to scale: the patterns of the world as an aggregated whole develop differently from all its seven regions, with implications for world-earth model construction – and sustainability transformations. Social media summary Reaching human well-being #SDGs takes GDP levels of $15k. This may help shape transformation to a world that respects #PlanetaryBoundaries.
Published: 2021

34. Strong regional influence of climatic forcing datasets on global crop model ensembles

Author: Jonas Jägermeyr, Allard de Wit, Alex C. Ruane, Thomas A. M. Pugh, Wenfeng Liu, Joshua Elliott, Toshichika Iizumi, Gen Sakurai, Nikolay Khabarov, Peter Lawrence, Benjamin Sultan, Stefan Olin, Christoph Müller, Xuhui Wang, Hong Yang, A. Arneth, Juraj Balkovic, Delphine Deryng, Erwin Schmid, Christian Folberth, Robert C. Izaurralde, Meridell Phillips, Cynthia Rosenzweig, NASA Goddard Institute for Space Studies (GISS), NASA Goddard Space Flight Center (GSFC), NASA GODDARD INSTITUTE FOR SPACE STUDIES NEW YORK 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), University of Chicago, Potsdam Institute for Climate Impact Research (PIK), Institute of Geography, University of Edinburgh, International Institute for Applied Systems Analysis [Laxenburg] (IIASA), Tyndall Centre for Climate Change Research, University of East Anglia [Norwich] (UEA), Department of Geography, University of Liverpool, National Institute of Agro-Environmental Sciences (NIAES), 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), 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)
Subjects: Atmospheric Science, Earth Observation and Environmental Informatics, 010504 meteorology & atmospheric sciences, Global Gridded Crop Model Intercomparison (GGCMI), Forcing (mathematics), 01 natural sciences, Crop productivity, Crop, 03 medical and health sciences, Crop production, Climatic Forcing Datasets, Aardobservatie en omgevingsinformatica, Precipitation, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, ComputingMilieux_MISCELLANEOUS, 030304 developmental biology, 0105 earth and related environmental sciences, 2. Zero hunger, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, 0303 health sciences, Global and Planetary Change, business.industry, Agroclimate, Extreme events, Forestry, Climate Impacts, PE&RC, Agricultural Model Intercomparison and Improvement Project (AgMIP), 13. Climate action, Agriculture, Climatology, Environmental science, business, Agronomy and Crop Science
Abstract: We present results from the Agricultural Model Intercomparison and Improvement Project (AgMIP) Global Gridded Crop Model Intercomparison (GGCMI) Phase I, which aligned 14 global gridded crop models (GGCMs) and 11 climatic forcing datasets (CFDs) in order to understand how the selection of climate data affects simulated historical crop productivity of maize, wheat, rice and soybean. Results show that CFDs demonstrate mean biases and differences in the probability of extreme events, with larger uncertainty around extreme precipitation and in regions where observational data for climate and crop systems are scarce. Countries where simulations correlate highly with reported FAO national production anomalies tend to have high correlations across most CFDs, whose influence we isolate using multi-GGCM ensembles for each CFD. Correlations compare favorably with the climate signal detected in other studies, although production in many countries is not primarily climate-limited (particularly for rice). Bias-adjusted CFDs most often were among the highest model-observation correlations, although all CFDs produced the highest correlation in at least one top-producing country. Analysis of larger multi-CFD-multi-GGCM ensembles (up to 91 members) shows benefits over the use of smaller subset of models in some regions and farming systems, although bigger is not always better. Our analysis suggests that global assessments should prioritize ensembles based on multiple crop models over multiple CFDs as long as a top-performing CFD is utilized for the focus region.
Published: 2021

35. Exploring the possibility space: Taking stock of the diverse capabilities and gaps in integrated assessment models

Author: Céline Guivarch, Evelina Trutnevyte, Will McDowall, Mathijs Harmsen, Oreane Y. Edelenbosch, Jean-Francois Mercure, Ilkka Keppo, J. Lefèvre, M. Caspani, T. Le Gallic, Roberto Schaeffer, Fabian Wagner, Nicolas Bauer, Johannes Emmerling, Marian Leimbach, Panagiotis Fragkos, Isabela Butnar, Keppo, I [0000-0003-3109-1243], Butnar, I [0000-0001-9908-220X], Edelenbosch, O [0000-0002-6588-5255], Emmerling, J [0000-0003-0916-9913], Fragkos, P [0000-0003-3596-0661], Guivarch, C [0000-0002-9405-256X], Harmsen, M [0000-0001-6755-1569], McDowall, W [0000-0002-4238-0692], Schaeffer, R [0000-0002-3709-7323], Trutnevyte, E [0000-0002-1716-6192], Apollo - University of Cambridge Repository, University College of London [London] (UCL), Potsdam Institute for Climate Impact Research (PIK), University of Geneva [Switzerland], PBL Netherlands Environmental Assessment Agency, European Institute on Economics and the Environment (EIEE), E3-Modelling, 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), Université Paris-Saclay, University of Exeter, Universidade Federal do Estado do Rio de Janeiro (UNIRIO), and International Institute for Applied Systems Analysis [Laxenburg] (IIASA)
Subjects: 010504 meteorology & atmospheric sciences, Computer science, media_common.quotation_subject, policy scenarios, 38 Economics, finance, 010501 environmental sciences, Space (commercial competition), 01 natural sciences, Technology diffusion, Integrated assessment models, Integrated Assessment Model, ddc:550, Model interpretation, International climate policy, Topical Review, 4407 Policy and Administration, Stock (geology), 0105 earth and related environmental sciences, General Environmental Science, media_common, 44 Human Society, ddc:333.7-333.9, Policy scenarios, 13 Climate Action, Energy-economy feedback, Renewable Energy, Sustainability and the Environment, Interpretation (philosophy), Public Health, Environmental and Occupational Health, Representation (systemics), Data science, [SDE.ES]Environmental Sciences/Environmental and Society, energy-economy feedback, model interpretation, 13. Climate action, technology diffusion, [SDE]Environmental Sciences, heterogeneity, Heterogeneity, Capital market, Finance, Diversity (politics)
Abstract: Integrated assessment models (IAMs) have emerged as key tools for building and assessing long term climate mitigation scenarios. Due to their central role in the recent IPCC assessments, and international climate policy analyses more generally, and the high uncertainties related to future projections, IAMs have been critically assessed by scholars from different fields receiving various critiques ranging from adequacy of their methods to how their results are used and communicated. Although IAMs are conceptually diverse and evolved in very different directions, they tend to be criticised under the umbrella of ‘IAMs’. Here we first briefly summarise the IAM landscape and how models differ from each other. We then proceed to discuss six prominent critiques emerging from the recent literature, reflect and respond to them in the light of IAM diversity and ongoing work and suggest ways forward. The six critiques relate to (a) representation of heterogeneous actors in the models, (b) modelling of technology diffusion and dynamics, (c) representation of capital markets, (d) energy-economy feedbacks, (e) policy scenarios, and (f) interpretation and use of model results.
Published: 2021
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36. 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

37. Protecting the poor with a carbon tax and equal per capita dividend

Author: Kevin Kuruc, David Klenert, Wei Peng, Francis Dennig, Maddalena Ferranna, Mark Budolfson, Frank Errickson, Fabian Wagner, Aurélie Méjean, Stéphane Zuber, Marc Fleurbaey, Dean Spears, Simon Feindt, Ulrike Kornek, Noah Scovronick, Rutgers University [Newark], Rutgers University System (Rutgers), Yale-NUS College, Princeton's Woodrow Wilson School of Public and International Affairs, Princeton University, Mercator Research Institute on Global Commons and Climate Change (MCC), Potsdam Institute for Climate Impact Research (PIK), Harvard School of Public Health, Paris Jourdan Sciences Economiques (PJSE), Université Paris 1 Panthéon-Sorbonne (UP1)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École des hautes études en sciences sociales (EHESS)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), European Commission - Joint Research Centre [Seville] (JRC), Kiel University, University of Oklahoma (OU), 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), Pennsylvania State University (Penn State), Penn State System, Emory University [Atlanta, GA], University of Texas at Austin [Austin], International Institute for Applied Systems Analysis [Laxenburg] (IIASA), Paris School of Economics (PSE), École des Ponts ParisTech (ENPC)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Paris 1 Panthéon-Sorbonne (UP1)-Centre National de la Recherche Scientifique (CNRS)-École des hautes études en sciences sociales (EHESS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre d'économie de la Sorbonne (CES), and Université Paris 1 Panthéon-Sorbonne (UP1)-Centre National de la Recherche Scientifique (CNRS)
Subjects: Carbon tax, 010504 meteorology & atmospheric sciences, Inequality, media_common.quotation_subject, Monetary economics, Environmental Science (miscellaneous), 7. Clean energy, 01 natural sciences, 03 medical and health sciences, 11. Sustainability, Per capita, Economics, Revenue, JEL: Q - Agricultural and Natural Resource Economics • Environmental and Ecological Economics/Q.Q5 - Environmental Economics/Q.Q5.Q58 - Government Policy, 030304 developmental biology, 0105 earth and related environmental sciences, media_common, 0303 health sciences, Equity (economics), Poverty, 1. No poverty, [SHS.ECO]Humanities and Social Sciences/Economics and Finance, [SDE.ES]Environmental Sciences/Environmental and Society, 13. Climate action, Dividend, Social Sciences (miscellaneous)
Abstract: International audience; We find that if all countries adopt the necessary uniform global carbon tax and then return the revenues to their citizens on an equal per capita basis, it will be possible to meet a 2 °C target while also increasing wellbeing, reducing inequality and alleviating poverty. These results indicate that it is possible for a society to implement strong climate action without compromising goals for equity and development.
Published: 2021

38. Short-term forecasts of the COVID-19 pandemic: a study case of Cameroon

Author: Jürgen Kurths, C. Hameni Nkwayep, Jean Jules Tewa, S. Bowong, Unité de modélisation mathématique et informatique des systèmes complexes [Bondy] (UMMISCO), Institut de Recherche pour le Développement (IRD [France-Nord])-Institut de la francophonie pour l'informatique-Université Cheikh Anta Diop [Dakar, Sénégal] (UCAD)-Université Gaston Bergé (Saint-Louis, Sénégal)-Université Cadi Ayyad [Marrakech] (UCA)-Université de Yaoundé I-Sorbonne Université (SU), Potsdam Institute for Climate Impact Research (PIK), Humboldt-Universität zu Berlin, Université de Yaoundé I-Institut de la francophonie pour l'informatique-Université Cheikh Anta Diop [Dakar, Sénégal] (UCAD)-Université Gaston Bergé (Saint-Louis, Sénégal)-Université Cadi Ayyad [Marrakech] (UCA)-Sorbonne Université (SU)-Institut de Recherche pour le Développement (IRD [France-Nord]), and Humboldt University Of Berlin
Subjects: COVID-19 Pandemic, Computer science, General Mathematics, Control measures, Population, General Physics and Astronomy, 01 natural sciences, Article, 010305 fluids & plasmas, law.invention, law, 0103 physical sciences, Pandemic, Econometrics, [NLIN]Nonlinear Sciences [physics], education, 010301 acoustics, Short-term forecasts, Mathematical models, education.field_of_study, Social distance, Applied Mathematics, Statistical and Nonlinear Physics, Kalman filter, Basic reproduction number, 3. Good health, Term (time), Transmission (mechanics), Contact tracing
Abstract: Highlights • A COVID-19 model with free coronaviruses in the environment is formulated. • States and unknown parameters of model are estimated using the Ensemble Kalman filter. • The implementation is performed using real data of the current COVID-19 pandemic in Cameroon. • The basic reproduction number in Cameroon R0 ≈ 2:9495. • There is a necessity to maintain the surveillance and sensibilisation of population., In this paper, an Ensemble of Kalman filter (EnKf) approach is developed to estimate unmeasurable state variables and unknown parameters in a COVID-19 model. We first formulate a mathematical model for the dynamic transmission of COVID-19 that takes into account the circulation of free coronaviruses in the environment. We provide the basic properties of the model and compute the basic reproduction number R0 that plays an important role in the outcome of the disease. After, assuming continuous measurement of newly COVID-19 reported cases, deceased and recovered individuals, the EnKf approach is used to estimate the unmeasured variables and unknown COVID-19 transmission rates using real data of the current COVID-19 pandemic in Cameroon. We present the forecasts of the current pandemic in Cameroon and explore the impact of non-pharmaceutical interventions such as mass media-based sensitization, social distancing, face-mask wearing, contact tracing and the desinfection and decontamination of infected places by using suitable products against free coronaviruses in the environment in order to reduce the spread of the disease. Through numerical simulations, we find that at that time (i) R0≈2.9495 meaning that the disease will not die out without any control measures, (ii) the infection from COVID-19 infected cases is more important than the infection from free coronaviruses in the environment, (iii) the number of new COVID-19 cases will still increase and there is a necessity to increase timely the surveillance by using contact tracing and sensibilisation of the population to respect social distancing, face-masks wearing through awareness programs and (iv) the eradication of the pandemic is highly dependent on the control measures taken by governments.
Published: 2020
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39. Reducing Uncertainties of Future Global Soil Carbon Responses to Climate and Land Use Change With Emergent Constraints

Author: Sebastian Ostberg, Thomas Hickler, Bertrand Guenet, Wenfang Xu, Akihiko Ito, Philippe Ciais, Sibyll Schaphoff, Hanqing Tian, Katja Frieler, Matthew Forrest, Nicolas Viovy, Hao Shi, Christopher P. O. Reyer, Jinfeng Chang, 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), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), National Institute for Environmental Studies (NIES), Potsdam Institute for Climate Impact Research (PIK), Auburn University (AU), 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, ANR-16-CONV-0003,CLAND,CLAND : Changement climatique et usage des terres(2016), 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, Atmospheric Science, Global and Planetary Change, 010504 meteorology & atmospheric sciences, Climate change, 04 agricultural and veterinary sciences, Soil carbon, 01 natural sciences, 13. Climate action, Environmental protection, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Environmental Chemistry, Environmental science, Land use, land-use change and forestry, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, General Environmental Science
Abstract: International audience
Published: 2020

40. Editorial: Recurrence Analysis of Complex Systems Dynamics

Author: Charles L. Webber, Norbert Marwan, Peter beim Graben, Christian Uhl, Axel Hutt, Bernstein Center for Computational Neuroscience [Göttingen] (BCCN), Georg-August-University [Göttingen], Computational Anatomy and Simulation for Medicine (MIMESIS), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Potsdam Institute for Climate Impact Research (PIK), Ansbach University of Applied Sciences, Stritch School of Medicine, Georg-August-University = Georg-August-Universität Göttingen, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire des sciences de l'ingénieur, de l'informatique et de l'imagerie (ICube), École Nationale du Génie de l'Eau et de l'Environnement de Strasbourg (ENGEES)-Université de Strasbourg (UNISTRA)-Institut National des Sciences Appliquées - Strasbourg (INSA Strasbourg), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Les Hôpitaux Universitaires de Strasbourg (HUS)-Centre National de la Recherche Scientifique (CNRS)-Matériaux et Nanosciences Grand-Est (MNGE), Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Réseau nanophotonique et optique, Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS)-École Nationale du Génie de l'Eau et de l'Environnement de Strasbourg (ENGEES)-Université de Strasbourg (UNISTRA)-Institut National des Sciences Appliquées - Strasbourg (INSA Strasbourg), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Les Hôpitaux Universitaires de Strasbourg (HUS)-Centre National de la Recherche Scientifique (CNRS)-Matériaux et Nanosciences Grand-Est (MNGE), and Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS)
Subjects: Statistics and Probability, Cognitive science, medicine, lcsh:T57-57.97, Applied Mathematics, Complex system, psychology, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, 01 natural sciences, 010305 fluids & plasmas, neuroscience, recurrence analysis, Dynamics (music), lcsh:Applied mathematics. Quantitative methods, 0103 physical sciences, lcsh:Probabilities. Mathematical statistics, meteorology, lcsh:QA273-280, 010306 general physics, ComputingMilieux_MISCELLANEOUS
Abstract: [No abstract available]
Published: 2020

41. 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

42. Macroeconomic drivers of baseline scenarios in dynamic CGE models: review and guidelines proposal

Author: Angel Aguiar, Jean Fouré, Jean Chateau, Julien Lefevre, Marian Leimbach, Hugo Valin, Ruben Bibas, Luis Rey-Los-Santos, Shinichiro Fujimori, Centre d'études prospectives et d'informations internationales (CEPII), Purdue University [West Lafayette], 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), Potsdam Institute for Climate Impact Research (PIK), European Commission [Brussels], and International Institute for Applied Systems Analysis [Laxenburg] (IIASA)
Subjects: Computable general equilibrium, Consistency (database systems), 010504 meteorology & atmospheric sciences, Computer science, Econometrics, 010501 environmental sciences, Baseline (configuration management), [SHS.ECO]Humanities and Social Sciences/Economics and Finance, 01 natural sciences, Gross domestic product, 0105 earth and related environmental sciences, System dynamics, [SHS]Humanities and Social Sciences
Abstract: International audience; For dynamic computable general equilibrium (CGE) modeling, long-term baseline construction is key and depends on the applied methods and the sources of projections considered. For dynamic CGE models, baseline assumptions and base data are both important determinants of results. This paper reviews the assumptions made by 24 modeling teams on baseline macroeconomic drivers, understood as factor accumulation and gross domestic product (GDP) growth. We critically review the various methods, identifying state-of-the-art practices and propose simple guidelines, particularly focusing on consistency between data sources and models, which is intended to help dynamic CGE modelers build their own baselines.
Published: 2020

43. 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

44. 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

45. 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

46. Temporary reduction in daily global CO2 emissions during the COVID-19 forced confinement

Author: Glen P. Peters, Felix Creutzig, Robert B. Jackson, Josep G. Canadell, Matthew W. Jones, Pierre Friedlingstein, Robbie M. Andrew, David R. Willis, Sam Abernethy, Adam J. P. Smith, Anthony J. De-Gol, Yuli Shan, Corinne Le Quéré, Tyndall Centre for Climate Change Research, University of East Anglia [Norwich] (UEA), School of Environmental Sciences [Norwich], Department of Earth System Science [Stanford] (ESS), Stanford EARTH, Stanford University-Stanford University, Magnetic Resonance (RM ), Modélisation et Exploration des Matériaux (MEM), Institut de Recherche Interdisciplinaire de Grenoble (IRIG), Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Grenoble Alpes (UGA)-Institut de Recherche Interdisciplinaire de Grenoble (IRIG), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Grenoble Alpes (UGA), Center for International Climate and Environmental Research [Oslo] (CICERO), University of Oslo (UiO), University of Groningen [Groningen], CISRO Oceans and Atmosphere, College of Engineering, Mathematics and Physical Sciences [Exeter] (EMPS), University of Exeter, Mercator Research Institute on Global Commons and Climate Change (MCC), Potsdam Institute for Climate Impact Research (PIK), Technical University Berlin, Technical University of Berlin / Technische Universität Berlin (TU), and Energy and Sustainability Research Institute Groni
Subjects: Consumption (economics), 0303 health sciences, 2019-20 coronavirus outbreak, Government, Energy demand, 010504 meteorology & atmospheric sciences, Coronavirus disease 2019 (COVID-19), COVID19, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), coronavirus, emissions, Environmental Science (miscellaneous), 7. Clean energy, 01 natural sciences, CARBON-DIOXIDE EMISSIONS, Agricultural economics, 03 medical and health sciences, 13. Climate action, 8. Economic growth, DRIVERS, [SDE]Environmental Sciences, Environmental science, Social Sciences (miscellaneous), 030304 developmental biology, 0105 earth and related environmental sciences
Abstract: Government policies during the COVID-19 pandemic have drastically altered patterns of energy demand around the world. Many international borders were closed and populations were confined to their homes, which reduced transport and changed consumption patterns. Here we compile government policies and activity data to estimate the decrease in CO2 emissions during forced confinements. Daily global CO2 emissions decreased by –17% (–11 to –25% for ±1σ) by early April 2020 compared with the mean 2019 levels, just under half from changes in surface transport. At their peak, emissions in individual countries decreased by –26% on average. The impact on 2020 annual emissions depends on the duration of the confinement, with a low estimate of –4% (–2 to –7%) if prepandemic conditions return by mid-June, and a high estimate of –7% (–3 to –13%) if some restrictions remain worldwide until the end of 2020. Government actions and economic incentives postcrisis will likely influence the global CO2 emissions path for decades.
Published: 2020
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47. 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

48. Performance evaluation of global hydrological models in six large Pan-Arctic watersheds

Author: Gädeke, Anne, Krysanova, Valentina, Aryal, Aashutosh, Chang, Jinfeng, Grillakis, Manolis, Hanasaki, Naota, Koutroulis, Aristeidis, Pokhrel, Yadu, Satoh, Yusuke, Schaphoff, Sibyll, Müller Schmied, Hannes, Stacke, Tobias, Tang, Qiuhong, Wada, Yoshihide, Thonicke, Kirsten, Potsdam Institute for Climate Impact Research, Member of the Leibniz Association, Potsdam, Germany, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, China, Lab of Geophysical-Remote Sensing & Archaeoenvironment, Institute for Mediterranean Studies, Foundation for Research & Technology Hellas, Rethimnon, Greece, National Institute for Environmental Studies, Tsukuba, Japan, School of Environmental Engineering, Technical University of Crete, Chania, Greece, Department of Civil and Environmental Engineering, Michigan State University, East Lansing, USA, Senckenberg Leibniz Biodiversity and Climate Research Centre (SBiK-F) Frankfurt, Frankfurt am Main, Germany, Helmholtz-Zentrum Geesthacht, Institute of Coastal Research, Geesthacht, Germany, Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Science and Natural Resources Research, Chinese Academy of Sciences, Beijing, China, International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria, 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), Technical University of Crete [Chania], National Institute for Environmental Studies (NIES), 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: Arctic watersheds, Atmospheric Science, 010504 meteorology & atmospheric sciences, 0208 environmental biotechnology, Climate change, 02 engineering and technology, Model performance, Structural basin, Permafrost, 01 natural sciences, Latitude, ddc:551.48, Boruta feature selection, [SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology, Model evaluation, 0105 earth and related environmental sciences, Global and Planetary Change, Pan arctic, Impact assessment, Vegetation, Snow, Global Water Models, 020801 environmental engineering, 13. Climate action, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, Environmental science, Physical geography
Abstract: Global Water Models (GWMs), which include Global Hydrological, Land Surface, and Dynamic Global Vegetation Models, present valuable tools for quantifying climate change impacts on hydrological processes in the data scarce high latitudes. Here we performed a systematic model performance evaluation in six major Pan-Arctic watersheds for different hydrological indicators (monthly and seasonal discharge, extremes, trends (or lack of), and snow water equivalent (SWE)) via a novel Aggregated Performance Index (API) that is based on commonly used statistical evaluation metrics. The machine learning Boruta feature selection algorithm was used to evaluate the explanatory power of the API attributes. Our results show that the majority of the nine GWMs included in the study exhibit considerable difficulties in realistically representing Pan-Arctic hydrological processes. Average APIdischarge (monthly and seasonal discharge) over nine GWMs is > 50% only in the Kolyma basin (55%), as low as 30% in the Yukon basin and averaged over all watersheds APIdischarge is 43%. WATERGAP2 and MATSIRO present the highest (APIdischarge > 55%) while ORCHIDEE and JULES-W1 the lowest (APIdischarge ≤ 25%) performing GWMs over all watersheds. For the high and low flows, average APIextreme is 35% and 26%, respectively, and over six GWMs APISWE is 57%. The Boruta algorithm suggests that using different observation-based climate data sets does not influence the total score of the APIs in all watersheds. Ultimately, only satisfactory to good performing GWMs that effectively represent cold-region hydrological processes (including snow-related processes, permafrost) should be included in multi-model climate change impact assessments in Pan-Arctic watersheds., Bundesministerium für Bildung und Forschung http://dx.doi.org/10.13039/501100002347
Published: 2020

49. The ongoing nutrition transition thwarts long-term targets for food security, public health and environmental protection

Author: Hermann Lotze-Campen, Alexander Popp, Abhijeet Mishra, Jillian Waid, Eleonora Martinelli, Xiaoxi Wang, Antonia Stenstad, Jan Philipp Dietrich, Chantal Le Mouël, Isabelle Weindl, Benjamin Leon Bodirsky, Lavinia Baumstark, Prajal Pradhan, Sabine Gabrysch, Susanne Rolinski, Potsdam Institute for Climate Impact Research (PIK), and Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Subjects: Conservation of Natural Resources, Hunger, lcsh:Medicine, Nutritional Status, 010501 environmental sciences, Overweight, Global Health, 01 natural sciences, Article, 03 medical and health sciences, 0302 clinical medicine, Empty calorie, Thinness, Environmental health, medicine, Nutrition transition, Humans, 030212 general & internal medicine, Obesity, lcsh:Science, 0105 earth and related environmental sciences, 2. Zero hunger, Multidisciplinary, Food security, lcsh:R, digestive, oral, and skin physiology, World population, Models, Theoretical, [SHS.ECO]Humanities and Social Sciences/Economics and Finance, 3. Good health, Diet, Refuse Disposal, Food waste, Environmental social sciences, Risk factors, 13. Climate action, Food Security, JEL: Q - Agricultural and Natural Resource Economics • Environmental and Ecological Economics, Food systems, lcsh:Q, Business, Public Health, medicine.symptom, Underweight, Diet, Healthy, [SDV.AEN]Life Sciences [q-bio]/Food and Nutrition
Abstract: The nutrition transition transforms food systems globally and shapes public health and environmental change. Here we provide a global forward-looking assessment of a continued nutrition transition and its interlinked symptoms in respect to food consumption. These symptoms range from underweight and unbalanced diets to obesity, food waste and environmental pressure. We find that by 2050, 45% (39–52%) of the world population will be overweight and 16% (13–20%) obese, compared to 29% and 9% in 2010 respectively. The prevalence of underweight approximately halves but absolute numbers stagnate at 0.4–0.7 billion. Aligned, dietary composition shifts towards animal-source foods and empty calories, while the consumption of vegetables, fruits and nuts increases insufficiently. Population growth, ageing, increasing body mass and more wasteful consumption patterns are jointly pushing global food demand from 30 to 45 (43–47) Exajoules. Our comprehensive open dataset and model provides the interfaces necessary for integrated studies of global health, food systems, and environmental change. Achieving zero hunger, healthy diets, and a food demand compatible with environmental boundaries necessitates a coordinated redirection of the nutrition transition. Reducing household waste, animal-source foods, and overweight could synergistically address multiple symptoms at once, while eliminating underweight would not substantially increase food demand.
Published: 2020
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50. Development of the Community Water Model (CWatM v1.04) - a high-resolution hydrological model for global and regional assessment of integrated water resources management

Author: P. Burek, Y. Satoh, T. Kahil, T. Tang, P. Greve, M. Smilovic, L. Guillaumot, F. Zhao, Y. Wada, International Institute for Applied Systems Analysis [Laxenburg] (IIASA), National Institute for Environmental Studies (NIES), Géosciences Rennes (GR), 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), East China Normal University [Shangaï] (ECNU), Potsdam Institute for Climate Impact Research (PIK), Universiteit Utrecht, US National Science FoundationNational Science Foundation (NSF) [ICER/EAR-1829999], Austrian Research Promotion Agency (FFG) under the FUSE - Belmont Forum [730254], EUCP (European Climate Prediction System) project - European Union under Horizon 2020 [776613], European UnionEuropean Union (EU), Austrian Federal Ministry of Science, Research and Economy (BMWFW), CO-MICC project, ERA4CS, an ERA-NET initiated by JPI Climate, Université de Rennes 1 (UR1), and Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR)-Centre National de la Recherche Scientifique (CNRS)
Subjects: 010504 meteorology & atmospheric sciences, Computer science, 0207 environmental engineering, 02 engineering and technology, 01 natural sciences, hydrological modeling, Documentation, groundwater, Water model, 020701 environmental engineering, 0105 earth and related environmental sciences, computer.programming_language, business.industry, Environmental resource management, lcsh:QE1-996.5, Integrated water resources management, human activity, Python (programming language), 6. Clean water, integrated approach, Water resources, lcsh:Geology, assessment method, 13. Climate action, [SDU]Sciences of the Universe [physics], Modular programming, Water quality, business, computer, Water use
Abstract: We develop a new large-scale hydrological and water resources model, the Community Water Model (CWatM), which can simulate hydrology both globally and regionally at different resolutions from 30 arcmin to 30 arcsec at daily time steps. CWatM is open source in the Python programming environment and has a modular structure. It uses global, freely available data in the netCDF4 file format for reading, storage, and production of data in a compact way. CWatM includes general surface and groundwater hydrological processes but also takes into account human activities, such as water use and reservoir regulation, by calculating water demands, water use, and return flows. Reservoirs and lakes are included in the model scheme. CWatM is used in the framework of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP), which compares global model outputs. The flexible model structure allows for dynamic interaction with hydro-economic and water quality models for the assessment and evaluation of water management options. Furthermore, the novelty of CWatM is its combination of state-of-the-art hydrological modeling, modular programming, an online user manual and automatic source code documentation, global and regional assessments at different spatial resolutions, and a potential community to add to, change, and expand the open-source project. CWatM also strives to build a community learning environment which is able to freely use an open-source hydrological model and flexible coupling possibilities to other sectoral models, such as energy and agriculture.
Published: 2020

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