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Nóia Júnior RDS, Deswarte JC, Cohan JP, Martre P, van der Velde M, Lecerf R, Webber H, Ewert F, Ruane AC, Slafer GA, Asseng S. The extreme 2016 wheat yield failure in France. Glob Chang Biol 2023; 29:3130-3146. [PMID: 36951185 DOI: 10.1111/gcb.16662] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 12/11/2022] [Accepted: 01/08/2023] [Indexed: 05/03/2023]
Abstract
France suffered, in 2016, the most extreme wheat yield decline in recent history, with some districts losing 55% yield. To attribute causes, we combined the largest coherent detailed wheat field experimental dataset with statistical and crop model techniques, climate information, and yield physiology. The 2016 yield was composed of up to 40% fewer grains that were up to 30% lighter than expected across eight research stations in France. The flowering stage was affected by prolonged cloud cover and heavy rainfall when 31% of the loss in grain yield was incurred from reduced solar radiation and 19% from floret damage. Grain filling was also affected as 26% of grain yield loss was caused by soil anoxia, 11% by fungal foliar diseases, and 10% by ear blight. Compounding climate effects caused the extreme yield decline. The likelihood of these compound factors recurring under future climate change is estimated to change with a higher frequency of extremely low wheat yields.
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Affiliation(s)
- Rogério de S Nóia Júnior
- Department of Life Science Engineering, Digital Agriculture, HEF World Agricultural Systems Center, Technical University of Munich, Freising, Germany
| | | | | | - Pierre Martre
- LEPSE, Univ Montpellier, INRAE, Institut Agro Montpellier, Montpellier, France
| | | | - Remi Lecerf
- European Commission, Joint Research Centre, Ispra, Italy
| | - Heidi Webber
- Leibniz-Centre for Agricultural Landscape Research (ZALF), Müncheberg, Germany
- Brandenburg Technical University (BTU), Cottbus, Germany
| | - Frank Ewert
- Leibniz-Centre for Agricultural Landscape Research (ZALF), Müncheberg, Germany
- Crop Science Group, INRES, University of Bonn, Bonn, Germany
| | - Alex C Ruane
- NASA Goddard Institute for Space Studies, New York, New York, USA
| | - Gustavo A Slafer
- Department of Crop and Forest Sciences, University of Lleida - AGROTECNIO Center, Lleida, Spain
- ICREA, Catalonian Institution for Research and Advanced Studies, Barcelona, Spain
| | - Senthold Asseng
- Department of Life Science Engineering, Digital Agriculture, HEF World Agricultural Systems Center, Technical University of Munich, Freising, Germany
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2
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Lapola DM, Pinho P, Barlow J, Aragão LEOC, Berenguer E, Carmenta R, Liddy HM, Seixas H, Silva CVJ, Silva-Junior CHL, Alencar AAC, Anderson LO, Armenteras D, Brovkin V, Calders K, Chambers J, Chini L, Costa MH, Faria BL, Fearnside PM, Ferreira J, Gatti L, Gutierrez-Velez VH, Han Z, Hibbard K, Koven C, Lawrence P, Pongratz J, Portela BTT, Rounsevell M, Ruane AC, Schaldach R, da Silva SS, von Randow C, Walker WS. The drivers and impacts of Amazon forest degradation. Science 2023; 379:eabp8622. [PMID: 36701452 DOI: 10.1126/science.abp8622] [Citation(s) in RCA: 21] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
Approximately 2.5 × 106 square kilometers of the Amazon forest are currently degraded by fire, edge effects, timber extraction, and/or extreme drought, representing 38% of all remaining forests in the region. Carbon emissions from this degradation total up to 0.2 petagrams of carbon per year (Pg C year-1), which is equivalent to, if not greater than, the emissions from Amazon deforestation (0.06 to 0.21 Pg C year-1). Amazon forest degradation can reduce dry-season evapotranspiration by up to 34% and cause as much biodiversity loss as deforestation in human-modified landscapes, generating uneven socioeconomic burdens, mainly to forest dwellers. Projections indicate that degradation will remain a dominant source of carbon emissions independent of deforestation rates. Policies to tackle degradation should be integrated with efforts to curb deforestation and complemented with innovative measures addressing the disturbances that degrade the Amazon forest.
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Affiliation(s)
- David M Lapola
- Laboratório de Ciência do Sistema Terrestre - LabTerra, Centro de Pesquisas Meteorológicas e Climáticas Aplicadas à Agricultura - CEPAGRI, Universidade Estadual de Campinas, Campinas, SP, Brazil
| | - Patricia Pinho
- Instituto de Pesquisas Ambientais da Amazônia, Brasília, DF, Brazil
| | - Jos Barlow
- Lancaster Environment Centre, Lancaster University, Lancaster, UK
| | - Luiz E O C Aragão
- Instituto Nacional de Pesquisas Espaciais, São José dos Campos, SP, Brazil.,Geography, University of Exeter, Exeter, UK
| | - Erika Berenguer
- Lancaster Environment Centre, Lancaster University, Lancaster, UK.,Environmental Change Institute, University of Oxford, Oxford, UK
| | | | - Hannah M Liddy
- Columbia Climate School, Columbia University, New York, NY, USA.,NASA Goddard Institute for Space Studies, New York, NY, USA
| | - Hugo Seixas
- Laboratório de Ciência do Sistema Terrestre - LabTerra, Centro de Pesquisas Meteorológicas e Climáticas Aplicadas à Agricultura - CEPAGRI, Universidade Estadual de Campinas, Campinas, SP, Brazil
| | - Camila V J Silva
- Instituto de Pesquisas Ambientais da Amazônia, Brasília, DF, Brazil.,Lancaster Environment Centre, Lancaster University, Lancaster, UK.,BeZero Carbon Ltd, London, UK
| | - Celso H L Silva-Junior
- Institute of Environment and Sustainability, University of California, Los Angeles, CA, USA.,Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA.,Programa de Pós-graduação em Biodiversidade e Conservação, Universidade Federal do Maranhão - UFMA, São Luís, MA, Brazil
| | - Ane A C Alencar
- Instituto de Pesquisas Ambientais da Amazônia, Brasília, DF, Brazil
| | - Liana O Anderson
- Centro Nacional de Monitoramento e Alertas de Desastres Naturais, São José dos Campos, SP, Brazil
| | | | | | - Kim Calders
- Computational & Applied Vegetation Ecology Laboratory, Department of Environment, Ghent University, Belgium.,School of Forest Sciences, University of Eastern Finland, Joensuu, Finland
| | | | | | | | - Bruno L Faria
- Instituto Federal de Educação, Ciência e Tecnologia do Norte de Minas Gerais, Diamantina, MG, Brazil
| | | | - Joice Ferreira
- Empresa Brasileira de Pesquisa Agropecuária, Belém, PA, Brazil
| | - Luciana Gatti
- Instituto Nacional de Pesquisas Espaciais, São José dos Campos, SP, Brazil
| | | | | | - Kathleen Hibbard
- National Aeronautics and Space Administration Headquarters, Washington, DC, USA
| | - Charles Koven
- Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Peter Lawrence
- National Center for Atmospheric Research, Boulder, CO, USA
| | - Julia Pongratz
- Max Planck Institute for Meteorology, Hamburg, Germany.,Ludwig-Maximilians University of Munich, Munich, Germany
| | | | - Mark Rounsevell
- Karlsruhe Institute of Technology, Karlsruhe, Germany.,University of Edinburgh, Edinburgh, UK
| | - Alex C Ruane
- NASA Goddard Institute for Space Studies, New York, NY, USA
| | | | | | - Celso von Randow
- Instituto Nacional de Pesquisas Espaciais, São José dos Campos, SP, Brazil
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3
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Ruane AC, Vautard R, Ranasinghe R, Sillmann J, Coppola E, Arnell N, Cruz FA, Dessai S, Iles CE, Islam AKMS, Jones RG, Rahimi M, Carrascal DR, Seneviratne SI, Servonnat J, Sörensson AA, Sylla MB, Tebaldi C, Wang W, Zaaboul R. The Climatic Impact-Driver Framework for Assessment of Risk-Relevant Climate Information. Earths Future 2022; 10:e2022EF002803. [PMID: 36582412 PMCID: PMC9787381 DOI: 10.1029/2022ef002803] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 10/05/2022] [Accepted: 10/11/2022] [Indexed: 06/17/2023]
Abstract
The climate science and applications communities need a broad and demand-driven concept to assess physical climate conditions that are relevant for impacts on human and natural systems. Here, we augment the description of the "climatic impact-driver" (CID) approach adopted in the Working Group I (WGI) contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report. CIDs are broadly defined as "physical climate system conditions (e.g., means, events, and extremes) that affect an element of society or ecosystems. Depending on system tolerance, CIDs and their changes can be detrimental, beneficial, neutral, or a mixture of each across interacting system elements and regions." We give background information on the IPCC Report process that led to the development of the 7 CID types (heat and cold, wet and dry, wind, snow and ice, coastal, open ocean, and other) and 33 distinct CID categories, each of which may be evaluated using a variety of CID indices. This inventory of CIDs was co-developed with WGII to provide a useful collaboration point between physical climate scientists and impacts/risk experts to assess the specific climatic phenomena driving sectoral responses and identify relevant CID indices within each sector. The CID Framework ensures that a comprehensive set of climatic conditions informs adaptation planning and risk management and may also help prioritize improvements in modeling sectoral dynamics that depend on climatic conditions. CIDs contribute to climate services by increasing coherence and neutrality when identifying and communicating relevant findings from physical climate research to risk assessment and planning activities.
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Affiliation(s)
- Alex C. Ruane
- NASA Goddard Institute for Space StudiesNew YorkNYUSA
| | - Robert Vautard
- Institut Pierre‐Simon LaplaceCNRSParisFrance
- Université Paris‐SaclayParisFrance
- Sorbonne UniversitéParisFrance
| | - Roshanka Ranasinghe
- Department of Coastal and Urban Risk & ResilienceIHE Delft Institute for Water EducationDelftThe Netherlands
- Department of Harbour, Coastal and Offshore EngineeringDeltaresDelftThe Netherlands
| | - Jana Sillmann
- Research Unit for Sustainability and Climate RisksUniversity of HamburgHamburgGermany
- Center for International Climate ResearchOsloNorway
| | - Erika Coppola
- The Abdus Salam International Centre for Theoretical PhysicsTriesteItaly
| | - Nigel Arnell
- Department of MeteorologyUniversity of ReadingReadingUK
| | | | - Suraje Dessai
- School of Earth and Environment and ESRC Centre for Climate Change Economics and PolicyUniversity of LeedsLeedsUK
| | - Carley E. Iles
- Institut Pierre‐Simon LaplaceCNRSParisFrance
- Center for International Climate ResearchOsloNorway
| | - A. K. M. Saiful Islam
- Institute of Water and Flood ManagementBangladesh University of Engineering and Technology (BUET)DhakaBangladesh
| | - Richard G. Jones
- Met Office Hadley CentreExeterUK
- School of Geography and the EnvironmentUniversity of OxfordOxfordUK
| | | | - Daniel Ruiz Carrascal
- Department of Ecology, Evolution and Environmental BiologyColumbia University in the City of New YorkNew YorkNYUSA
- Columbia Climate SchoolColumbia University in the City of New YorkNew YorkNYUSA
- International Research Institute for Climate and SocietyColumbia University in the City of New YorkNew YorkNYUSA
| | | | | | - Anna A. Sörensson
- Faculty of Exact and Natural SciencesUniversity of Buenos AiresBuenos AiresArgentina
- Centro de Investigaciones del Mar y la Atmosfera (CONICET – UBA)Buenos AiresArgentina
- CNRS, CNRS – IRD – CONICET – UBA, Instituto Franco‐Argentino para el Estudio del Clima y sus Impactos (IRL 3351 IFAECI)Buenos AiresArgentina
| | | | - Claudia Tebaldi
- Lawrence Berkeley National LaboratoryBerkeleyCAUSA
- Pacific Northwest National LaboratoryCollege ParkMDUSA
| | - Wen Wang
- State Key Laboratory of Hydrology‐Water Resources and Hydraulic EngineeringHohai UniversityNanjingChina
| | - Rashyd Zaaboul
- International Centre for Biosaline AgricultureDubaiUAE
- University of AlmeríaAlmeríaSpain
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4
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Cammarano D, Jamshidi S, Hoogenboom G, Ruane AC, Niyogi D, Ronga D. Processing tomato production is expected to decrease by 2050 due to the projected increase in temperature. Nat Food 2022; 3:437-444. [PMID: 37118037 DOI: 10.1038/s43016-022-00521-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 04/19/2022] [Indexed: 04/30/2023]
Abstract
The global production of processing tomatoes is concentrated in a small number of regions where climate change could have a notable impact on the future supply. Process-based tomato models project that the production in the main producing countries (the United States, Italy and China, representing 65% of global production) will decrease 6% by 2050 compared with the baseline period of 1980-2009. The predicted reduction in processing tomato production is due to a projected increase in air temperature. Under an ensemble of projected climate scenarios, California and Italy might not be able to sustain current levels of processing tomato production due to water resource constraints. Cooler producing regions, such as China and the northern parts of California, stand to improve their competitive advantage. The projected environmental changes indicate that the main growing regions of processing tomatoes might change in the coming decades.
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Affiliation(s)
- Davide Cammarano
- Department of Agroecology, iClimate, Centre for Circular Bioeconomy (CBIO), Aarhus University, Tjele, Denmark.
| | - Sajad Jamshidi
- Department of Agronomy, Purdue University, West Lafayette, IN, USA
| | - Gerrit Hoogenboom
- Department of Agricultural and Biological Engineering, University of Florida, Gainesville, FL, USA
| | - Alex C Ruane
- NASA Goddard Institute for Space Studies, New York, NY, USA
| | - Dev Niyogi
- Department of Agronomy, Purdue University, West Lafayette, IN, USA
- Department of Geological Sciences, Jackson School of Geosciences, and Department of Civil, Architectural, and Environmental Engineering, Cockrell School of Engineering, The University of Texas at Austin, Austin, TX, USA
| | - Domenico Ronga
- Department of Pharmacy, University of Salerno, Fisciano, Italy
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5
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Franke JA, Müller C, Minoli S, Elliott J, Folberth C, Gardner C, Hank T, Izaurralde RC, Jägermeyr J, Jones CD, Liu W, Olin S, Pugh TAM, Ruane AC, Stephens H, Zabel F, Moyer EJ. Agricultural breadbaskets shift poleward given adaptive farmer behavior under climate change. Glob Chang Biol 2022; 28:167-181. [PMID: 34478595 DOI: 10.1111/gcb.15868] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Accepted: 06/04/2021] [Indexed: 06/13/2023]
Abstract
Modern food production is spatially concentrated in global "breadbaskets." A major unresolved question is whether these peak production regions will shift poleward as the climate warms, allowing some recovery of potential climate-related losses. While agricultural impacts studies to date have focused on currently cultivated land, the Global Gridded Crop Model Intercomparison Project (GGCMI) Phase 2 experiment allows us to assess changes in both yields and the location of peak productivity regions under warming. We examine crop responses under projected end of century warming using seven process-based models simulating five major crops (maize, rice, soybeans, and spring and winter wheat) with a variety of adaptation strategies. We find that in no-adaptation cases, when planting date and cultivar choices are held fixed, regions of peak production remain stationary and yield losses can be severe, since growing seasons contract strongly with warming. When adaptations in management practices are allowed (cultivars that retain growing season length under warming and modified planting dates), peak productivity zones shift poleward and yield losses are largely recovered. While most growing-zone shifts are ultimately limited by geography, breadbaskets studied here move poleward over 600 km on average by end of the century under RCP 8.5. These results suggest that agricultural impacts assessments can be strongly biased if restricted in spatial area or in the scope of adaptive behavior considered. Accurate evaluation of food security under climate change requires global modeling and careful treatment of adaptation strategies.
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Affiliation(s)
- James A Franke
- Department of the Geophysical Sciences, University of Chicago, Chicago, Illinois, USA
- Center for Robust Decision-making on Climate and Energy Policy (RDCEP), University of Chicago, Chicago, Illinois, USA
| | - Christoph Müller
- Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, Potsdam, Germany
| | - Sara Minoli
- Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, Potsdam, Germany
| | - Joshua Elliott
- Center for Robust Decision-making on Climate and Energy Policy (RDCEP), University of Chicago, Chicago, Illinois, USA
| | - Christian Folberth
- Ecosystem Services and Management Program, International Institute for Applied Systems Analysis, Laxenburg, Austria
| | - Charles Gardner
- Program on Global Environment, University of Chicago, Chicago, Illinois, USA
| | - Tobias Hank
- Ludwig-Maximilians-Universitat Munchen (LMU), Munich, Germany
| | | | - Jonas Jägermeyr
- Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, Potsdam, Germany
- NASA Goddard Institute for Space Studies, New York City, New York, USA
- Center for Climate Systems Research, Columbia University, New York City, New York, USA
| | - Curtis D Jones
- Department of Geographical Sciences, University of Maryland, College Park, Maryland, USA
| | - Wenfeng Liu
- College of Water Resources and Civil Engineering, China Agricultural University, Beijing, China
| | - Stefan Olin
- Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden
| | - Thomas A M Pugh
- Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, UK
- Birmingham Institute of Forest Research, University of Birmingham, Birmingham, UK
| | - Alex C Ruane
- NASA Goddard Institute for Space Studies, New York City, New York, USA
| | - Haynes Stephens
- Department of the Geophysical Sciences, University of Chicago, Chicago, Illinois, USA
- Center for Robust Decision-making on Climate and Energy Policy (RDCEP), University of Chicago, Chicago, Illinois, USA
| | - Florian Zabel
- Ludwig-Maximilians-Universitat Munchen (LMU), Munich, Germany
| | - Elisabeth J Moyer
- Department of the Geophysical Sciences, University of Chicago, Chicago, Illinois, USA
- Center for Robust Decision-making on Climate and Energy Policy (RDCEP), University of Chicago, Chicago, Illinois, USA
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6
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Jägermeyr J, Müller C, Ruane AC, Elliott J, Balkovic J, Castillo O, Faye B, Foster I, Folberth C, Franke JA, Fuchs K, Guarin JR, Heinke J, Hoogenboom G, Iizumi T, Jain AK, Kelly D, Khabarov N, Lange S, Lin TS, Liu W, Mialyk O, Minoli S, Moyer EJ, Okada M, Phillips M, Porter C, Rabin SS, Scheer C, Schneider JM, Schyns JF, Skalsky R, Smerald A, Stella T, Stephens H, Webber H, Zabel F, Rosenzweig C. Climate impacts on global agriculture emerge earlier in new generation of climate and crop models. Nat Food 2021; 2:873-885. [PMID: 37117503 DOI: 10.1038/s43016-021-00400-y] [Citation(s) in RCA: 68] [Impact Index Per Article: 22.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Accepted: 09/29/2021] [Indexed: 04/30/2023]
Abstract
Potential climate-related impacts on future crop yield are a major societal concern. Previous projections of the Agricultural Model Intercomparison and Improvement Project's Global Gridded Crop Model Intercomparison based on the Coupled Model Intercomparison Project Phase 5 identified substantial climate impacts on all major crops, but associated uncertainties were substantial. Here we report new twenty-first-century projections using ensembles of latest-generation crop and climate models. Results suggest markedly more pessimistic yield responses for maize, soybean and rice compared to the original ensemble. Mean end-of-century maize productivity is shifted from +5% to -6% (SSP126) and from +1% to -24% (SSP585)-explained by warmer climate projections and improved crop model sensitivities. In contrast, wheat shows stronger gains (+9% shifted to +18%, SSP585), linked to higher CO2 concentrations and expanded high-latitude gains. The 'emergence' of climate impacts consistently occurs earlier in the new projections-before 2040 for several main producing regions. While future yield estimates remain uncertain, these results suggest that major breadbasket regions will face distinct anthropogenic climatic risks sooner than previously anticipated.
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Affiliation(s)
- Jonas Jägermeyr
- NASA Goddard Institute for Space Studies, New York, NY, USA.
- Columbia University, Center for Climate Systems Research, New York, NY, USA.
- Potsdam Institute for Climate Impacts Research (PIK), Member of the Leibniz Association, Potsdam, Germany.
| | - Christoph Müller
- Potsdam Institute for Climate Impacts Research (PIK), Member of the Leibniz Association, Potsdam, Germany
| | - Alex C Ruane
- NASA Goddard Institute for Space Studies, New York, NY, USA
| | - Joshua Elliott
- Center for Robust Decision-making on Climate and Energy Policy (RDCEP), University of Chicago, Chicago, IL, USA
| | - Juraj Balkovic
- International Institute for Applied Systems Analysis, Laxenburg, Austria
- Faculty of Natural Sciences, Comenius University in Bratislava, Bratislava, Slovak Republic
| | - Oscar Castillo
- Agricultural & Biological Engineering Department, University of Florida, Gainesville, FL, USA
| | - Babacar Faye
- Institut de recherche pour le développement (IRD) ESPACE-DEV, Montpellier, France
| | - Ian Foster
- Department of Computer Science, University of Chicago, Chicago, IL, USA
| | - Christian Folberth
- International Institute for Applied Systems Analysis, Laxenburg, Austria
| | - James A Franke
- Center for Robust Decision-making on Climate and Energy Policy (RDCEP), University of Chicago, Chicago, IL, USA
- Department of the Geophysical Sciences, University of Chicago, Chicago, IL, USA
| | - Kathrin Fuchs
- Institute of Meteorology and Climate Research, Atmospheric Environmental Research, Karlsruhe Institute of Technology, Garmisch-Partenkirchen, Germany
| | - Jose R Guarin
- NASA Goddard Institute for Space Studies, New York, NY, USA
- Columbia University, Center for Climate Systems Research, New York, NY, USA
| | - Jens Heinke
- Potsdam Institute for Climate Impacts Research (PIK), Member of the Leibniz Association, Potsdam, Germany
| | - Gerrit Hoogenboom
- Agricultural & Biological Engineering Department, University of Florida, Gainesville, FL, USA
- Institute for Sustainable Food Systems, University of Florida, Gainesville, FL, USA
| | - Toshichika Iizumi
- Institute for Agro-Environmental Sciences, National Agriculture and Food Research Organization, Tsukuba, Japan
| | - Atul K Jain
- Department of Atmospheric Sciences, University of Illinois, Urbana, IL, USA
| | - David Kelly
- Department of Computer Science, University of Chicago, Chicago, IL, USA
| | - Nikolay Khabarov
- International Institute for Applied Systems Analysis, Laxenburg, Austria
| | - Stefan Lange
- Potsdam Institute for Climate Impacts Research (PIK), Member of the Leibniz Association, Potsdam, Germany
| | - Tzu-Shun Lin
- Department of Atmospheric Sciences, University of Illinois, Urbana, IL, USA
| | - Wenfeng Liu
- Center for Agricultural Water Research in China, College of Water Resources and Civil Engineering, China Agricultural University, Beijing, China
| | - Oleksandr Mialyk
- Multidisciplinary Water Management group, University of Twente, Enschede, Netherlands
| | - Sara Minoli
- Potsdam Institute for Climate Impacts Research (PIK), Member of the Leibniz Association, Potsdam, Germany
| | - Elisabeth J Moyer
- Center for Robust Decision-making on Climate and Energy Policy (RDCEP), University of Chicago, Chicago, IL, USA
- Department of the Geophysical Sciences, University of Chicago, Chicago, IL, USA
| | - Masashi Okada
- Center for Climate Change Adaptation, National Institute for Environmental Studies, Tsukuba, Japan
| | - Meridel Phillips
- NASA Goddard Institute for Space Studies, New York, NY, USA
- Columbia University, Center for Climate Systems Research, New York, NY, USA
| | - Cheryl Porter
- Agricultural & Biological Engineering Department, University of Florida, Gainesville, FL, USA
| | - Sam S Rabin
- Institute of Meteorology and Climate Research, Atmospheric Environmental Research, Karlsruhe Institute of Technology, Garmisch-Partenkirchen, Germany
- Department of Environmental Sciences, Rutgers University, New Brunswick, NJ, USA
| | - Clemens Scheer
- Institute of Meteorology and Climate Research, Atmospheric Environmental Research, Karlsruhe Institute of Technology, Garmisch-Partenkirchen, Germany
| | | | - Joep F Schyns
- Multidisciplinary Water Management group, University of Twente, Enschede, Netherlands
| | - Rastislav Skalsky
- International Institute for Applied Systems Analysis, Laxenburg, Austria
- Soil Science and Conservation Research Institute, National Agricultural and Food Centre, Bratislava, Slovak Republic
| | - Andrew Smerald
- Institute of Meteorology and Climate Research, Atmospheric Environmental Research, Karlsruhe Institute of Technology, Garmisch-Partenkirchen, Germany
| | - Tommaso Stella
- Leibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg, Germany
| | - Haynes Stephens
- Center for Robust Decision-making on Climate and Energy Policy (RDCEP), University of Chicago, Chicago, IL, USA
- Department of the Geophysical Sciences, University of Chicago, Chicago, IL, USA
| | - Heidi Webber
- Leibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg, Germany
| | - Florian Zabel
- Ludwig-Maximilians-Universität München (LMU), Munich, Germany
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7
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Myers BJE, Weiskopf SR, Shiklomanov AN, Ferrier S, Weng E, Casey KA, Harfoot M, Jackson ST, Leidner AK, Lenton TM, Luikart G, Matsuda H, Pettorelli N, Rosa IMD, Ruane AC, Senay GB, Serbin SP, Tittensor DP, Beard TD. A New Approach to Evaluate and Reduce Uncertainty of Model-Based Biodiversity Projections for Conservation Policy Formulation. Bioscience 2021. [DOI: 10.1093/biosci/biab094] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Biodiversity projections with uncertainty estimates under different climate, land-use, and policy scenarios are essential to setting and achieving international targets to mitigate biodiversity loss. Evaluating and improving biodiversity predictions to better inform policy decisions remains a central conservation goal and challenge. A comprehensive strategy to evaluate and reduce uncertainty of model outputs against observed measurements and multiple models would help to produce more robust biodiversity predictions. We propose an approach that integrates biodiversity models and emerging remote sensing and in-situ data streams to evaluate and reduce uncertainty with the goal of improving policy-relevant biodiversity predictions. In this article, we describe a multivariate approach to directly and indirectly evaluate and constrain model uncertainty, demonstrate a proof of concept of this approach, embed the concept within the broader context of model evaluation and scenario analysis for conservation policy, and highlight lessons from other modeling communities.
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Affiliation(s)
- Bonnie J E Myers
- National Climate Adaptation Science Center, Reston, Virginia, United States
| | - Sarah R Weiskopf
- National Climate Adaptation Science Center, Reston, Virginia, United States
| | | | - Simon Ferrier
- Commonwealth Scientific and Industrial Research Organisation (CSIRO) Canberra, Australia
| | - Ensheng Weng
- NASA Goddard Institute for Space Studies and Columbia University, New York, New York, United States
| | - Kimberly A Casey
- US Geological Survey's National Land Imaging Program, Reston, Virginia, United States
| | - Mike Harfoot
- UN Environment Programme World Conservation Monitoring Centre, Cambridge, England, United Kingdom
| | | | - Allison K Leidner
- NASA Headquarters/Biological Diversity Program, Washington, DC, United States
| | - Timothy M Lenton
- Global Systems Institute, University of Exeter, Exeter, England, United Kingdom
| | - Gordon Luikart
- University of Montana Flathead Lake Biological Station, Polson, Montana, United States
| | | | - Nathalie Pettorelli
- Institute for Zoology, Zoological Society of London, Regent's Park, England, United Kingdom
| | - Isabel M D Rosa
- School of Natural Sciences, Bangor University, Bangor, Wales, United Kingdom
| | - Alex C Ruane
- NASA Goddard Institute for Space Studies, New York, New York, United States
| | - Gabriel B Senay
- US Geological Survey Earth Resources Observation Science Center, North Central Climate Adaptation Science Center, Fort Collins, Colorado, United States
| | - Shawn P Serbin
- Environmental and Climate Sciences Department, Brookhaven National Laboratory, Upton, New York, United States
| | - Derek P Tittensor
- UN Environment Programme World Conservation Monitoring Centre, Cambridge, England, United Kingdom
- Department of Biology, Dalhousie University, Halifax, Nova Scotia, Canada
| | - T Douglas Beard
- National Climate Adaptation Science Center, Reston, Virginia, United States
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8
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Zabel F, Müller C, Elliott J, Minoli S, Jägermeyr J, Schneider JM, Franke JA, Moyer E, Dury M, Francois L, Folberth C, Liu W, Pugh TAM, Olin S, Rabin SS, Mauser W, Hank T, Ruane AC, Asseng S. Large potential for crop production adaptation depends on available future varieties. Glob Chang Biol 2021; 27:3870-3882. [PMID: 33998112 DOI: 10.1111/gcb.15649] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Accepted: 04/08/2021] [Indexed: 06/12/2023]
Abstract
Climate change affects global agricultural production and threatens food security. Faster phenological development of crops due to climate warming is one of the main drivers for potential future yield reductions. To counter the effect of faster maturity, adapted varieties would require more heat units to regain the previous growing period length. In this study, we investigate the effects of variety adaptation on global caloric production under four different future climate change scenarios for maize, rice, soybean, and wheat. Thereby, we empirically identify areas that could require new varieties and areas where variety adaptation could be achieved by shifting existing varieties into new regions. The study uses an ensemble of seven global gridded crop models and five CMIP6 climate models. We found that 39% (SSP5-8.5) of global cropland could require new crop varieties to avoid yield loss from climate change by the end of the century. At low levels of warming (SSP1-2.6), 85% of currently cultivated land can draw from existing varieties to shift within an agro-ecological zone for adaptation. The assumptions on available varieties for adaptation have major impacts on the effectiveness of variety adaptation, which could more than half in SSP5-8.5. The results highlight that region-specific breeding efforts are required to allow for a successful adaptation to climate change.
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Affiliation(s)
- Florian Zabel
- Department of Geography, Ludwig-Maximilians-Universität München (LMU), Munich, Germany
| | - Christoph Müller
- Climate Resilience, Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, Potsdam, Germany
| | - Joshua Elliott
- Center for Climate Systems Research, Columbia University, New York, NY, USA
| | - Sara Minoli
- Climate Resilience, Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, Potsdam, Germany
| | - Jonas Jägermeyr
- Climate Resilience, Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, Potsdam, Germany
- Center for Climate Systems Research, Columbia University, New York, NY, USA
- NASA Goddard Institute for Space Studies, New York, NY, USA
| | - Julia M Schneider
- Department of Geography, Ludwig-Maximilians-Universität München (LMU), Munich, Germany
| | - James A Franke
- Department of the Geophysical Sciences, University of Chicago, Chicago, IL, USA
- Center for Robust Decision-making on Climate and Energy Policy (RDCEP), University of Chicago, Chicago, IL, USA
| | - Elisabeth Moyer
- Department of the Geophysical Sciences, University of Chicago, Chicago, IL, USA
- Center for Robust Decision-making on Climate and Energy Policy (RDCEP), University of Chicago, Chicago, IL, USA
| | | | | | - Christian Folberth
- International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria
| | - Wenfeng Liu
- Center for Agricultural Water Research in China, College of Water Resources and Civil Engineering, China Agricultural University, Beijing, China
| | - Thomas A M Pugh
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, UK
- Birmingham Institute of Forest Research, University of Birmingham, Birmingham, UK
| | | | - Sam S Rabin
- Institute of Meteorology and Climate Research - Atmospheric Environmental Research, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Wolfram Mauser
- Department of Geography, Ludwig-Maximilians-Universität München (LMU), Munich, Germany
| | - Tobias Hank
- Department of Geography, Ludwig-Maximilians-Universität München (LMU), Munich, Germany
| | - Alex C Ruane
- NASA Goddard Institute for Space Studies, New York, NY, USA
| | - Senthold Asseng
- School of Life Sciences, Technical University of Munich (TUM), München, Germany
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9
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Falconnier GN, Corbeels M, Boote KJ, Affholder F, Adam M, MacCarthy DS, Ruane AC, Nendel C, Whitbread AM, Justes É, Ahuja LR, Akinseye FM, Alou IN, Amouzou KA, Anapalli SS, Baron C, Basso B, Baudron F, Bertuzzi P, Challinor AJ, Chen Y, Deryng D, Elsayed ML, Faye B, Gaiser T, Galdos M, Gayler S, Gerardeaux E, Giner M, Grant B, Hoogenboom G, Ibrahim ES, Kamali B, Kersebaum KC, Kim SH, van der Laan M, Leroux L, Lizaso JI, Maestrini B, Meier EA, Mequanint F, Ndoli A, Porter CH, Priesack E, Ripoche D, Sida TS, Singh U, Smith WN, Srivastava A, Sinha S, Tao F, Thorburn PJ, Timlin D, Traore B, Twine T, Webber H. Modelling climate change impacts on maize yields under low nitrogen input conditions in sub-Saharan Africa. Glob Chang Biol 2020; 26:5942-5964. [PMID: 32628332 DOI: 10.1111/gcb.15261] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/21/2019] [Revised: 05/19/2020] [Accepted: 06/22/2020] [Indexed: 06/11/2023]
Abstract
Smallholder farmers in sub-Saharan Africa (SSA) currently grow rainfed maize with limited inputs including fertilizer. Climate change may exacerbate current production constraints. Crop models can help quantify the potential impact of climate change on maize yields, but a comprehensive multimodel assessment of simulation accuracy and uncertainty in these low-input systems is currently lacking. We evaluated the impact of varying [CO2 ], temperature and rainfall conditions on maize yield, for different nitrogen (N) inputs (0, 80, 160 kg N/ha) for five environments in SSA, including cool subhumid Ethiopia, cool semi-arid Rwanda, hot subhumid Ghana and hot semi-arid Mali and Benin using an ensemble of 25 maize models. Models were calibrated with measured grain yield, plant biomass, plant N, leaf area index, harvest index and in-season soil water content from 2-year experiments in each country to assess their ability to simulate observed yield. Simulated responses to climate change factors were explored and compared between models. Calibrated models reproduced measured grain yield variations well with average relative root mean square error of 26%, although uncertainty in model prediction was substantial (CV = 28%). Model ensembles gave greater accuracy than any model taken at random. Nitrogen fertilization controlled the response to variations in [CO2 ], temperature and rainfall. Without N fertilizer input, maize (a) benefited less from an increase in atmospheric [CO2 ]; (b) was less affected by higher temperature or decreasing rainfall; and (c) was more affected by increased rainfall because N leaching was more critical. The model intercomparison revealed that simulation of daily soil N supply and N leaching plays a crucial role in simulating climate change impacts for low-input systems. Climate change and N input interactions have strong implications for the design of robust adaptation approaches across SSA, because the impact of climate change in low input systems will be modified if farmers intensify maize production with balanced nutrient management.
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Affiliation(s)
| | - Marc Corbeels
- AIDA, Univ Montpellier, CIRAD, Montpellier, France
- CIMMYT, Nairobi, Kenya
| | | | | | - Myriam Adam
- CIRAD, UMR AGAP, Bobo-Dioulasso, Burkina Faso
- AGAP, Univ Montpellier, CIRAD, INRA, Montpellier SupAgro, Montpellier, France
| | - Dilys S MacCarthy
- Soil and Irrigation Research Centre, School of Agriculture, College of Basic and Applied Science, University of Ghana, Accra, Ghana
| | - Alex C Ruane
- Climate Impacts Group, National Aeronautics and Space Administration Goddard Institute for Space Studies, New York, NY, USA
| | - Claas Nendel
- Leibniz Centre for Agricultural Landscape Research, Müncheberg, Germany
| | - Anthony M Whitbread
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Dar es Salaam, Tanzania
| | - Éric Justes
- PERSYST, Univ Montpellier, CIRAD, Montpellier, France
| | | | - Folorunso M Akinseye
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Kano, Nigeria
| | - Isaac N Alou
- Department of Plant and Soil Sciences, University of Pretoria, Pretoria, South Africa
| | - Kokou A Amouzou
- West Africa Program, African Plant Nutrition Institute (APNI), Yamoussoukro, Cote d'Ivoire
| | | | - Christian Baron
- CIRAD, UMR TETIS, Montpellier, France
- TETIS, Univ Montpellier, AgroParisTech, CIRAD, CNRS, IRSTEA, Montpellier, France
| | - Bruno Basso
- Department of Earth and Environmental Sciences, Michigan State University, East Lansing, MI, USA
| | | | | | - Andrew J Challinor
- Institute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, Leeds, UK
| | - Yi Chen
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China
| | - Delphine Deryng
- Integrative Research Institute on Transformations of Human-Environment Systems (IRI THESys), Humboldt-Universität zu Berlin, Berlin, Germany
- NewClimate Institute, Berlin, Germany
| | - Maha L Elsayed
- MALR-ARC, Central Laboratory for Agricultural Climate (CLAC), Giza, Egypt
| | - Babacar Faye
- Crop Science Group, Institute of Crop Science and Resource Conservation (INRES), University of Bonn, Bonn, Germany
| | - Thomas Gaiser
- Crop Science Group, Institute of Crop Science and Resource Conservation (INRES), University of Bonn, Bonn, Germany
| | - Marcelo Galdos
- Institute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, Leeds, UK
| | - Sebastian Gayler
- Institute of Soil Science and Land Evaluation, Biogeophysics, University of Hohenheim, Stuttgart, Germany
| | | | - Michel Giner
- AIDA, Univ Montpellier, CIRAD, Montpellier, France
| | - Brian Grant
- Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON, Canada
| | | | - Esther S Ibrahim
- Leibniz Centre for Agricultural Landscape Research, Müncheberg, Germany
| | - Bahareh Kamali
- Leibniz Centre for Agricultural Landscape Research, Müncheberg, Germany
| | | | - Soo-Hyung Kim
- School of Environmental and Forest Sciences, University of Washington, Seattle, USA
| | - Michael van der Laan
- Department of Plant and Soil Sciences, University of Pretoria, Pretoria, South Africa
| | - Louise Leroux
- AIDA, Univ Montpellier, CIRAD, Montpellier, France
- CIRAD, UPR AIDA, Dakar, Senegal
| | - Jon I Lizaso
- CEIGRAM-Universidad Politécnica de Madrid, ETSIAAB, Madrid, Spain
| | - Bernardo Maestrini
- Department of Earth and Environmental Sciences, Michigan State University, East Lansing, MI, USA
| | - Elizabeth A Meier
- CSIRO Agriculture and Food, Queensland Bioscience Precinct, St Lucia, Qld, Australia
| | - Fasil Mequanint
- Institute of Soil Science and Land Evaluation, Biogeophysics, University of Hohenheim, Stuttgart, Germany
| | | | | | - Eckart Priesack
- Institute of Biochemical Plant Pathology, Helmholtz Center Munich, Neuherberg, Germany
| | | | | | - Upendra Singh
- International Center for Soil Fertility and Agricultural Development, Muscle Shoals, AL, USA
| | - Ward N Smith
- Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON, Canada
| | - Amit Srivastava
- Crop Science Group, Institute of Crop Science and Resource Conservation (INRES), University of Bonn, Bonn, Germany
| | - Sumit Sinha
- Institute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, Leeds, UK
| | - Fulu Tao
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China
- Natural Resources Institute Finland (Luke), Helsinki, Finland
| | - Peter J Thorburn
- CSIRO Agriculture and Food, Queensland Bioscience Precinct, St Lucia, Qld, Australia
| | - Dennis Timlin
- Crop Systems and Global Change Research Unit, USDA-ARS, Beltsville, MD, USA
| | | | - Tracy Twine
- Department of Soil, Water, and Climate, University of Minnesota, St. Paul, MN, USA
| | - Heidi Webber
- Leibniz Centre for Agricultural Landscape Research, Müncheberg, Germany
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10
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Cammarano D, Valdivia RO, Beletse YG, Durand W, Crespo O, Tesfuhuney WA, Jones MR, Walker S, Mpuisang TN, Nhemachena C, Ruane AC, Mutter C, Rosenzweig C, Antle J. Integrated assessment of climate change impacts on crop productivity and income of commercial maize farms in northeast South Africa. Food Secur 2020. [DOI: 10.1007/s12571-020-01023-0] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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11
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Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, Yang H. The Global Gridded Crop Model Intercomparison phase 1 simulation dataset. Sci Data 2019; 6:50. [PMID: 31068583 PMCID: PMC6506552 DOI: 10.1038/s41597-019-0023-8] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2018] [Accepted: 02/25/2019] [Indexed: 11/17/2022] Open
Abstract
The Global Gridded Crop Model Intercomparison (GGCMI) phase 1 dataset of the Agricultural Model Intercomparison and Improvement Project (AgMIP) provides an unprecedentedly large dataset of crop model simulations covering the global ice-free land surface. The dataset consists of annual data fields at a spatial resolution of 0.5 arc-degree longitude and latitude. Fourteen crop modeling groups provided output for up to 11 historical input datasets spanning 1901 to 2012, and for up to three different management harmonization levels. Each group submitted data for up to 15 different crops and for up to 14 output variables. All simulations were conducted for purely rainfed and near-perfectly irrigated conditions on all land areas irrespective of whether the crop or irrigation system is currently used there. With the publication of the GGCMI phase 1 dataset we aim to promote further analyses and understanding of crop model performance, potential relationships between productivity and environmental impacts, and insights on how to further improve global gridded crop model frameworks. We describe dataset characteristics and individual model setup narratives.
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Affiliation(s)
- Christoph Müller
- Potsdam Institute for Climate Impact Research, Member of the Leibniz Association, 14473, Potsdam, Germany.
| | - Joshua Elliott
- University of Chicago and ANL Computation Institute, Chicago, IL, 60637, USA
| | - David Kelly
- University of Chicago and ANL Computation Institute, Chicago, IL, 60637, USA
| | - Almut Arneth
- Karlsruhe Institute of Technology, IMK-IFU, 82467, Garmisch-Partenkirchen, Germany
| | - Juraj Balkovic
- Ecosystem Services and Management Program, International Institute for Applied Systems Analysis, 2361, Laxenburg, Austria
- Department of Soil Science, Comenius University in Bratislava, 842 15, Bratislava, Slovak Republic
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, CEA CNRS UVSQ Orme des Merisiers, F-91191, Gif-sur-Yvette, France
| | - Delphine Deryng
- University of Chicago and ANL Computation Institute, Chicago, IL, 60637, USA
- Center for Climate Systems Research, Columbia University, New York, NY, 10025, USA
| | - Christian Folberth
- Ecosystem Services and Management Program, International Institute for Applied Systems Analysis, 2361, Laxenburg, Austria
- Department of Soil Science, Comenius University in Bratislava, 842 15, Bratislava, Slovak Republic
| | - Steven Hoek
- Earth Observation and Environmental Informatics, Alterra Wageningen University and Research Centre, 6708PB, Wageningen, Netherlands
| | - Roberto C Izaurralde
- Department of Geographical Sciences, University of Maryland, College Park, MD, 20742, USA
- Texas AgriLife Research and Extension, Texas A&M University, Temple, TX, 76502, USA
| | - Curtis D Jones
- Department of Geographical Sciences, University of Maryland, College Park, MD, 20742, USA
| | - Nikolay Khabarov
- Ecosystem Services and Management Program, International Institute for Applied Systems Analysis, 2361, Laxenburg, Austria
| | - Peter Lawrence
- Earth System Laboratory, National Center for Atmospheric Research, Boulder, CO, 80307, USA
| | - Wenfeng Liu
- Laboratoire des Sciences du Climat et de l'Environnement, CEA CNRS UVSQ Orme des Merisiers, F-91191, Gif-sur-Yvette, France
- Eawag, Swiss Federal Institute of Aquatic Science and Technology, CH-8600, Duebendorf, Switzerland
| | - Stefan Olin
- Department of Physical Geography and Ecosystem Science, Lund University, 223 62, Lund, Sweden
| | - Thomas A M Pugh
- School of Geography, Earth & Environmental Science, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom
- Birmingham Institute of Forest Research, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom
| | - Ashwan Reddy
- Department of Geographical Sciences, University of Maryland, College Park, MD, 20742, USA
| | - Cynthia Rosenzweig
- Center for Climate Systems Research, Columbia University, New York, NY, 10025, USA
- National Aeronautics and Space Administration Goddard Institute for Space Studies, New York, NY, 10025, USA
| | - Alex C Ruane
- Center for Climate Systems Research, Columbia University, New York, NY, 10025, USA
- National Aeronautics and Space Administration Goddard Institute for Space Studies, New York, NY, 10025, USA
| | - Gen Sakurai
- Institute for Agro-Environmental Sciences, National Agriculture and Research Organization, Tsukuba, 305-8604, Japan
| | - Erwin Schmid
- Institute for Sustainable Economic Development, University of Natural Resources and Life Sciences, 1180, Vienna, Austria
| | - Rastislav Skalsky
- Ecosystem Services and Management Program, International Institute for Applied Systems Analysis, 2361, Laxenburg, Austria
- Soil Science and Conservation Research Institute, National Agricultural and Food Centre, 82109, Bratislava, Slovak Republic
| | - Xuhui Wang
- Laboratoire des Sciences du Climat et de l'Environnement, CEA CNRS UVSQ Orme des Merisiers, F-91191, Gif-sur-Yvette, France
- Sino-French Institute of Earth System Sciences, Peking University, 100871, Beijing, China
| | - Allard de Wit
- Earth Observation and Environmental Informatics, Alterra Wageningen University and Research Centre, 6708PB, Wageningen, Netherlands
| | - Hong Yang
- Eawag, Swiss Federal Institute of Aquatic Science and Technology, CH-8600, Duebendorf, Switzerland
- Department of Environmental Sciences, MGU, University of Basel, CH-4003, Basel, Switzerland
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12
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Liu B, Martre P, Ewert F, Porter JR, Challinor AJ, Müller C, Ruane AC, Waha K, Thorburn PJ, Aggarwal PK, Ahmed M, Balkovič J, Basso B, Biernath C, Bindi M, Cammarano D, De Sanctis G, Dumont B, Espadafor M, Eyshi Rezaei E, Ferrise R, Garcia-Vila M, Gayler S, Gao Y, Horan H, Hoogenboom G, Izaurralde RC, Jones CD, Kassie BT, Kersebaum KC, Klein C, Koehler AK, Maiorano A, Minoli S, Montesino San Martin M, Naresh Kumar S, Nendel C, O'Leary GJ, Palosuo T, Priesack E, Ripoche D, Rötter RP, Semenov MA, Stöckle C, Streck T, Supit I, Tao F, Van der Velde M, Wallach D, Wang E, Webber H, Wolf J, Xiao L, Zhang Z, Zhao Z, Zhu Y, Asseng S. Global wheat production with 1.5 and 2.0°C above pre-industrial warming. Glob Chang Biol 2019; 25:1428-1444. [PMID: 30536680 DOI: 10.1111/gcb.14542] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/10/2018] [Accepted: 11/24/2018] [Indexed: 05/21/2023]
Abstract
Efforts to limit global warming to below 2°C in relation to the pre-industrial level are under way, in accordance with the 2015 Paris Agreement. However, most impact research on agriculture to date has focused on impacts of warming >2°C on mean crop yields, and many previous studies did not focus sufficiently on extreme events and yield interannual variability. Here, with the latest climate scenarios from the Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) project, we evaluated the impacts of the 2015 Paris Agreement range of global warming (1.5 and 2.0°C warming above the pre-industrial period) on global wheat production and local yield variability. A multi-crop and multi-climate model ensemble over a global network of sites developed by the Agricultural Model Intercomparison and Improvement Project (AgMIP) for Wheat was used to represent major rainfed and irrigated wheat cropping systems. Results show that projected global wheat production will change by -2.3% to 7.0% under the 1.5°C scenario and -2.4% to 10.5% under the 2.0°C scenario, compared to a baseline of 1980-2010, when considering changes in local temperature, rainfall, and global atmospheric CO2 concentration, but no changes in management or wheat cultivars. The projected impact on wheat production varies spatially; a larger increase is projected for temperate high rainfall regions than for moderate hot low rainfall and irrigated regions. Grain yields in warmer regions are more likely to be reduced than in cooler regions. Despite mostly positive impacts on global average grain yields, the frequency of extremely low yields (bottom 5 percentile of baseline distribution) and yield inter-annual variability will increase under both warming scenarios for some of the hot growing locations, including locations from the second largest global wheat producer-India, which supplies more than 14% of global wheat. The projected global impact of warming <2°C on wheat production is therefore not evenly distributed and will affect regional food security across the globe as well as food prices and trade.
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Affiliation(s)
- Bing Liu
- 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 Agricultural University, Nanjing, China
| | - Pierre Martre
- LEPSE, Université Montpellier, INRA, Montpellier SupAgro, Montpellier, France
| | - Frank Ewert
- Institute of Crop Science and Resource Conservation INRES, University of Bonn, Bonn, Germany
- Leibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg, Germany
| | - John R Porter
- Plant & Environment Sciences, University Copenhagen, Taastrup, Denmark
- Lincoln University, Lincoln, New Zealand
- Montpellier SupAgro, INRA, CIHEAM-IAMM, CIRAD, University Montpellier, Montpellier, France
| | - Andy J Challinor
- Institute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, Leeds, UK
- CGIAR-ESSP Program on Climate Change, Agriculture and Food Security, International Centre for Tropical Agriculture (CIAT), Cali, Colombia
| | - Christoph Müller
- Potsdam Institute for Climate Impact Research, Member of the Leibniz Association, Potsdam, Germany
| | - Alex C Ruane
- NASA Goddard Institute for Space Studies, New York, New York
| | | | | | - Pramod K Aggarwal
- CGIAR Research Program on Climate Change, Agriculture and Food Security, BISA-CIMMYT, New Delhi, India
| | - Mukhtar Ahmed
- Biological Systems Engineering, Washington State University, Pullman, Washington
- Department of agronomy, Pir Mehr Ali Shah Arid Agriculture University, Rawalpindi, Pakistan
| | - Juraj Balkovič
- International Institute for Applied Systems Analysis, Ecosystem Services and Management Program, Laxenburg, Austria
- Department of Soil Science, Faculty of Natural Sciences, Comenius University in Bratislava, Bratislava, Slovakia
| | - Bruno Basso
- Department of Earth and Environmental Sciences, Michigan State University East Lansing, East Lansing, Michigan
- W.K. Kellogg Biological Station, Michigan State University, East Lansing, Michigan
| | - Christian Biernath
- Institute of Biochemical Plant Pathology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Marco Bindi
- Department of Agri-food Production and Environmental Sciences (DISPAA), University of Florence, Florence, Italy
| | | | | | - Benjamin Dumont
- Department AgroBioChem & TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liege, Gembloux, Belgium
| | - Mónica Espadafor
- IAS-CSIC, Department of Agronomy, University of Cordoba, Cordoba, Spain
| | - Ehsan Eyshi Rezaei
- Institute of Crop Science and Resource Conservation INRES, University of Bonn, Bonn, Germany
- Department of Crop Sciences, University of Göttingen, Göttingen, Germany
| | - Roberto Ferrise
- Department of Agri-food Production and Environmental Sciences (DISPAA), University of Florence, Florence, Italy
| | | | - Sebastian Gayler
- Institute of Soil Science and Land Evaluation, University of Hohenheim, Stuttgart, Germany
| | - Yujing Gao
- Agricultural & Biological Engineering Department, University of Florida, Gainesville, Florida
| | - Heidi Horan
- CSIRO Agriculture and Food, Brisbane, Qld, Australia
| | - Gerrit Hoogenboom
- Agricultural & Biological Engineering Department, University of Florida, Gainesville, Florida
- Institute for Sustainable Food Systems, University of Florida, Gainesville, Florida
| | - Roberto C Izaurralde
- Department of Geographical Sciences, University of Maryland, College Park, Maryland
- Texas A&M AgriLife Research and Extension Center, Texas A&M Univ., Temple, Texas
| | - Curtis D Jones
- Department of Geographical Sciences, University of Maryland, College Park, Maryland
| | - Belay T Kassie
- Agricultural & Biological Engineering Department, University of Florida, Gainesville, Florida
| | - Kurt C Kersebaum
- Leibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg, Germany
| | - Christian Klein
- Institute of Biochemical Plant Pathology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Ann-Kristin Koehler
- Institute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, Leeds, UK
| | - Andrea Maiorano
- LEPSE, Université Montpellier, INRA, Montpellier SupAgro, Montpellier, France
- European Food Safety Authority, Parma, Italy
| | - Sara Minoli
- Potsdam Institute for Climate Impact Research, Member of the Leibniz Association, Potsdam, Germany
| | | | - Soora Naresh Kumar
- Centre for Environment Science and Climate Resilient Agriculture, Indian Agricultural Research Institute, IARI PUSA, New Delhi, India
| | - Claas Nendel
- Leibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg, Germany
| | - Garry J O'Leary
- Department of Economic Development, Jobs, Transport and Resources, Grains Innovation Park, Agriculture Victoria Research, Horsham, Vic., Australia
| | - Taru Palosuo
- Natural Resources Institute Finland (Luke), Helsinki, Finland
| | - Eckart Priesack
- Institute of Biochemical Plant Pathology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | | | - Reimund P Rötter
- University of Göttingen, Tropical Plant Production and Agricultural Systems Modelling (TROPAGS), Göttingen, Germany
- Centre of Biodiversity and Sustainable Land Use (CBL), University of Göttingen, Göttingen, Germany
| | | | - Claudio Stöckle
- Biological Systems Engineering, Washington State University, Pullman, Washington
| | - Thilo Streck
- Institute of Soil Science and Land Evaluation, University of Hohenheim, Stuttgart, Germany
| | - Iwan Supit
- Water Systems & Global Change Group and WENR (Water & Food), Wageningen University, Wageningen, The Netherlands
| | - Fulu Tao
- Natural Resources Institute Finland (Luke), Helsinki, Finland
- Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Science, Beijing, China
| | | | | | - Enli Wang
- CSIRO Agriculture and Food, Black Mountain, ACT, Australia
| | - Heidi Webber
- Institute of Crop Science and Resource Conservation INRES, University of Bonn, Bonn, Germany
- Leibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg, Germany
| | - Joost Wolf
- Plant Production Systems, Wageningen University, Wageningen, The Netherlands
| | - Liujun Xiao
- 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 Agricultural University, Nanjing, China
- Agricultural & Biological Engineering Department, University of Florida, Gainesville, Florida
| | - Zhao Zhang
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing, China
| | - Zhigan Zhao
- CSIRO Agriculture and Food, Black Mountain, ACT, Australia
- Department of Agronomy and Biotechnology, China Agricultural University, Beijing, China
| | - Yan Zhu
- 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 Agricultural University, Nanjing, China
| | - Senthold Asseng
- Agricultural & Biological Engineering Department, University of Florida, Gainesville, Florida
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13
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Uz SS, Ruane AC, Duncan BN, Tucker CJ, Huffman GJ, Mladenova IE, Osmanoglu B, Holmes TR, McNally A, Peters-Lidard C, Bolten JD, Das N, Rodell M, McCartney S, Anderson MC, Doorn B. Earth observations and integrative models in support of food and water security. Remote Sens Earth Syst Sci 2019; 2:18-38. [PMID: 33005873 PMCID: PMC7526267 DOI: 10.1007/s41976-019-0008-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/19/2018] [Revised: 12/26/2018] [Accepted: 01/17/2019] [Indexed: 11/28/2022]
Abstract
Global food production depends upon many factors that Earth observing satellites routinely measure about water, energy, weather, and ecosystems. Increasingly sophisticated, publicly-available satellite data products can improve efficiencies in resource management and provide earlier indication of environmental disruption. Satellite remote sensing provides a consistent, long-term record that can be used effectively to detect large-scale features over time, such as a developing drought. Accuracy and capabilities have increased along with the range of Earth observations and derived products that can support food security decisions with actionable information. This paper highlights major capabilities facilitated by satellite observations and physical models that have been developed and validated using remotely-sensed observations. Although we primarily focus on variables relevant to agriculture, we also include a brief description of the growing use of Earth observations in support of aquaculture and fisheries.
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Affiliation(s)
| | - Alex C. Ruane
- NASA Goddard Institute for Space Studies, Climate Impacts Group, New York, NY, USA
| | | | | | | | - Iliana E. Mladenova
- NASA Goddard Space Flight Center, Greenbelt, MD, USA
- Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA
| | | | | | - Amy McNally
- NASA Goddard Space Flight Center, Greenbelt, MD, USA
- Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA
| | | | | | - Narendra Das
- NASA Jet Propulsion Laboratory, Pasadena, CA, USA
| | | | - Sean McCartney
- NASA Goddard Space Flight Center, Greenbelt, MD, USA
- Science Systems and Applications, Inc., Lanham, MD, USA
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14
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Asseng S, Martre P, Maiorano A, Rötter RP, O'Leary GJ, Fitzgerald GJ, Girousse C, Motzo R, Giunta F, Babar MA, Reynolds MP, Kheir AMS, Thorburn PJ, Waha K, Ruane AC, Aggarwal PK, Ahmed M, Balkovič J, Basso B, Biernath C, Bindi M, Cammarano D, Challinor AJ, De Sanctis G, Dumont B, Eyshi Rezaei E, Fereres E, Ferrise R, Garcia-Vila M, Gayler S, Gao Y, Horan H, Hoogenboom G, Izaurralde RC, Jabloun M, Jones CD, Kassie BT, Kersebaum KC, Klein C, Koehler AK, Liu B, Minoli S, Montesino San Martin M, Müller C, Naresh Kumar S, Nendel C, Olesen JE, Palosuo T, Porter JR, Priesack E, Ripoche D, Semenov MA, Stöckle C, Stratonovitch P, Streck T, Supit I, Tao F, Van der Velde M, Wallach D, Wang E, Webber H, Wolf J, Xiao L, Zhang Z, Zhao Z, Zhu Y, Ewert F. Climate change impact and adaptation for wheat protein. Glob Chang Biol 2019; 25:155-173. [PMID: 30549200 DOI: 10.1111/gcb.14481] [Citation(s) in RCA: 126] [Impact Index Per Article: 25.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/09/2018] [Accepted: 09/06/2018] [Indexed: 05/20/2023]
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.
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Affiliation(s)
- Senthold Asseng
- Agricultural & Biological Engineering Department, University of Florida, Gainesville, Florida
| | - Pierre Martre
- LEPSE, Université Montpellier INRA, Montpellier SupAgro, Montpellier, France
| | - Andrea Maiorano
- LEPSE, Université Montpellier INRA, Montpellier SupAgro, Montpellier, France
| | - Reimund P Rötter
- Tropical Plant Production and Agricultural Systems Modelling (TROPAGS), University of Göttingen, Göttingen, Germany
- Centre of Biodiversity and Sustainable Land Use (CBL), University of Göttingen, Göttingen, Germany
| | - Garry J O'Leary
- Department of Economic Development Jobs, Transport and Resources, Grains Innovation Park, Agriculture Victoria Research, Horsham, Victoria, Australia
| | - Glenn J Fitzgerald
- Department of Economic Development, Jobs, Transport and Resources, Agriculture Victoria Research, Horsham, Victoria, Australia
- Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Creswick, Victoria, Australia
| | | | - Rosella Motzo
- Department of Agricultural Sciences, University of Sassari, Sassari, Italy
| | - Francesco Giunta
- Department of Agricultural Sciences, University of Sassari, Sassari, Italy
| | - M Ali Babar
- World Food Crops Breeding, Department of Agronomy, IFAS, University of Florida, Gainesville, Florida
| | | | - Ahmed M S Kheir
- Soils, Water and Environment Research Institute, Agricultural Research Center, Giza, Egypt
| | | | - Katharina Waha
- CSIRO Agriculture and Food, Brisbane, Queensland, Australia
| | - Alex C Ruane
- NASA Goddard Institute for Space Studies, New York, New York
| | - Pramod K Aggarwal
- CGIAR Research Program on Climate Change, Agriculture and Food Security, BISA-CIMMYT, New Delhi, India
| | - Mukhtar Ahmed
- Biological Systems Engineering, Washington State University, Pullman, Washington
- Department of Agronomy, Pir Mehr Ali Shah Arid Agriculture University, Rawalpindi, Pakistan
| | - Juraj Balkovič
- International Institute for Applied Systems Analysis, Ecosystem Services and Management Program, Laxenburg, Austria
- Department of Soil Science, Faculty of Natural Sciences, Comenius University in Bratislava, Bratislava, Slovakia
| | - Bruno Basso
- Department of Earth and Environmental Sciences, Michigan State University, East Lansing, Michigan
- W.K. Kellogg Biological Station, Michigan State University, East Lansing, Michigan
| | - Christian Biernath
- Institute of Biochemical Plant Pathology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Marco Bindi
- Department of Agri-food Production and Environmental Sciences (DISPAA), University of Florence, Florence, Italy
| | | | - Andrew J Challinor
- Institute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, Leeds, UK
- Collaborative Research Program from CGIAR and Future Earth on Climate Change, Agriculture and Food Security (CCAFS), International Centre for Tropical Agriculture (CIAT), Cali, Colombia
| | | | - Benjamin Dumont
- Department Terra & AgroBioChem, Gembloux Agro-Bio Tech, University of Liege, Gembloux, Belgium
| | - Ehsan Eyshi Rezaei
- Institute of Crop Science and Resource Conservation INRES, University of Bonn, Bonn, Germany
- Department of Crop Sciences, University of Göttingen, Göttingen, Germany
| | | | - Roberto Ferrise
- Department of Agri-food Production and Environmental Sciences (DISPAA), University of Florence, Florence, Italy
| | | | - Sebastian Gayler
- Institute of Soil Science and Land Evaluation, University of Hohenheim, Stuttgart, Germany
| | - Yujing Gao
- Agricultural & Biological Engineering Department, University of Florida, Gainesville, Florida
| | - Heidi Horan
- CSIRO Agriculture and Food, Brisbane, Queensland, Australia
| | - Gerrit Hoogenboom
- Agricultural & Biological Engineering Department, University of Florida, Gainesville, Florida
- Institute for Sustainable Food Systems, University of Florida, Gainesville, Florida
| | - R César Izaurralde
- Department of Geographical Sciences, University of Maryland, College Park, Maryland
- Texas A&M AgriLife Research and Extension Center, Texas A&M University, Temple, Texas
| | - Mohamed Jabloun
- Department of Agroecology, Aarhus University, Tjele, Denmark
| | - Curtis D Jones
- Department of Geographical Sciences, University of Maryland, College Park, Maryland
| | - Belay T Kassie
- Agricultural & Biological Engineering Department, University of Florida, Gainesville, Florida
| | | | - Christian Klein
- Institute of Biochemical Plant Pathology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Ann-Kristin Koehler
- Institute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, Leeds, UK
| | - Bing Liu
- Agricultural & Biological Engineering Department, University of Florida, Gainesville, Florida
- 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 Agricultural University, Nanjing, China
| | - Sara Minoli
- Potsdam Institute for Climate Impact Research, Member of the Leibniz Association, Potsdam, Germany
| | | | - Christoph Müller
- Potsdam Institute for Climate Impact Research, Member of the Leibniz Association, Potsdam, Germany
| | - Soora Naresh Kumar
- Centre for Environment Science and Climate Resilient Agriculture, Indian Agricultural Research Institute, IARI PUSA, New Delhi, India
| | - Claas Nendel
- Leibniz Centre for Agricultural Landscape Research, Müncheberg, Germany
| | | | - Taru Palosuo
- Montpellier SupAgro, INRA, CIHEAM-IAMM, CIRAD, University Montpellier, Montpellier, France
| | - John R Porter
- Plant & Environment Sciences, University Copenhagen, Taastrup, Denmark
- Lincoln University, Lincoln, New Zealand
- Montpellier SupAgro, INRA, CIHEAM-IAMM, CIRAD, University Montpellier, Montpellier, France
| | - Eckart Priesack
- Institute of Biochemical Plant Pathology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | | | | | - Claudio Stöckle
- Biological Systems Engineering, Washington State University, Pullman, Washington
| | | | - Thilo Streck
- Institute of Soil Science and Land Evaluation, University of Hohenheim, Stuttgart, Germany
| | - Iwan Supit
- Water & Food and Water Systems & Global Change Group, Wageningen University, Wageningen, The Netherlands
| | - Fulu Tao
- Natural Resources Institute Finland (Luke), Helsinki, Finland
- Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Science, Beijing, China
| | | | | | - Enli Wang
- CSIRO Agriculture and Food, Canberra, Australian Capital Territory, Australia
| | - Heidi Webber
- Institute of Crop Science and Resource Conservation INRES, University of Bonn, Bonn, Germany
- Leibniz Centre for Agricultural Landscape Research, Müncheberg, Germany
| | - Joost Wolf
- Plant Production Systems, Wageningen University, Wageningen, The Netherlands
| | - Liujun Xiao
- 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 Agricultural University, Nanjing, China
| | - Zhao Zhang
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing, China
| | - Zhigan Zhao
- CSIRO Agriculture and Food, Canberra, Australian Capital Territory, Australia
- Department of Agronomy and Biotechnology, China Agricultural University, Beijing, China
| | - Yan Zhu
- 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 Agricultural University, Nanjing, China
| | - Frank Ewert
- Institute of Crop Science and Resource Conservation INRES, University of Bonn, Bonn, Germany
- Leibniz Centre for Agricultural Landscape Research, Müncheberg, Germany
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15
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Webber H, Ewert F, Olesen JE, Müller C, Fronzek S, Ruane AC, Bourgault M, Martre P, Ababaei B, Bindi M, Ferrise R, Finger R, Fodor N, Gabaldón-Leal C, Gaiser T, Jabloun M, Kersebaum KC, Lizaso JI, Lorite IJ, Manceau L, Moriondo M, Nendel C, Rodríguez A, Ruiz-Ramos M, Semenov MA, Siebert S, Stella T, Stratonovitch P, Trombi G, Wallach D. Diverging importance of drought stress for maize and winter wheat in Europe. Nat Commun 2018; 9:4249. [PMID: 30315168 PMCID: PMC6185965 DOI: 10.1038/s41467-018-06525-2] [Citation(s) in RCA: 147] [Impact Index Per Article: 24.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2018] [Accepted: 09/07/2018] [Indexed: 12/22/2022] Open
Abstract
Understanding the drivers of yield levels under climate change is required to support adaptation planning and respond to changing production risks. This study uses an ensemble of crop models applied on a spatial grid to quantify the contributions of various climatic drivers to past yield variability in grain maize and winter wheat of European cropping systems (1984–2009) and drivers of climate change impacts to 2050. Results reveal that for the current genotypes and mix of irrigated and rainfed production, climate change would lead to yield losses for grain maize and gains for winter wheat. Across Europe, on average heat stress does not increase for either crop in rainfed systems, while drought stress intensifies for maize only. In low-yielding years, drought stress persists as the main driver of losses for both crops, with elevated CO2 offering no yield benefit in these years. Drivers of crop yield variability require quantification, and historical records can help in improving understanding. Here, Webber et al. report that drought stress will remain a key driver of yield losses in wheat and maize across Europe, and benefits from CO2 will be limited in low-yielding years.
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Affiliation(s)
- Heidi Webber
- Leibniz-Centre for Agricultural Landscape Research (ZALF), 15374, Müncheberg, Germany. .,Institute of Crop Science and Resources Conservation, University of Bonn, Bonn, 53115, Germany.
| | - Frank Ewert
- Leibniz-Centre for Agricultural Landscape Research (ZALF), 15374, Müncheberg, Germany.,Institute of Crop Science and Resources Conservation, University of Bonn, Bonn, 53115, Germany
| | - Jørgen E Olesen
- Department of Agroecology, Aarhus University, Tjele, 8830, Denmark
| | - Christoph Müller
- Potsdam Institute for Climate Impact Research, Member of the Leibniz Association, Potsdam, 14473, Germany
| | | | - Alex C Ruane
- National Aeronautics and Space Administration Goddard Institute for Space Studies, New York, 10025, NY, USA
| | - Maryse Bourgault
- Northern Ag Research Center, Montana State University, 3710 Assinniboine Road, Havre, MT, USA
| | - Pierre Martre
- LEPSE, Université Montpellier, INRA, Montpellier SupAgro, 34060, Montpellier, France
| | - Behnam Ababaei
- LEPSE, Université Montpellier, INRA, Montpellier SupAgro, 34060, Montpellier, France.,Native Trait Research, Limagrain Europe, 63720, Chappes, France.,Centre for Crop Science, Queensland Alliance for Agriculture and Food Innovation, University of Queensland, 4069, Toowoomba, Australia
| | - Marco Bindi
- Department of Agri-food Production and Environmental Sciences, University of Florence, P.le delle Cascine 18, 50144, Firenze, Italy
| | - Roberto Ferrise
- Department of Agri-food Production and Environmental Sciences, University of Florence, P.le delle Cascine 18, 50144, Firenze, Italy
| | - Robert Finger
- ETH Zurich, Agricultural Economics and Policy Group, Zürich, 8092, Switzerland
| | - Nándor Fodor
- Agricultural Institute, Centre for Agricultural Research, Hungarian Academy of Sciences, Martonvásár, 2462, Hungary
| | | | - Thomas Gaiser
- Institute of Crop Science and Resources Conservation, University of Bonn, Bonn, 53115, Germany
| | - Mohamed Jabloun
- School of Biosciences, University of Nottingham, Loughborough, LE12 5RD, UK
| | | | - Jon I Lizaso
- Research Centre for the Management of Agricultural and Environmental Risks (CEIGRAM), Universidad Politécnica de Madrid, Madrid, 28040, Spain
| | - Ignacio J Lorite
- IFAPA-Centro Alameda del Obispo, P.O. Box 3092, 14080, Córdoba, Spain
| | - Loic Manceau
- LEPSE, Université Montpellier, INRA, Montpellier SupAgro, 34060, Montpellier, France
| | | | - Claas Nendel
- Leibniz-Centre for Agricultural Landscape Research (ZALF), 15374, Müncheberg, Germany
| | - Alfredo Rodríguez
- Research Centre for the Management of Agricultural and Environmental Risks (CEIGRAM), Universidad Politécnica de Madrid, Madrid, 28040, Spain.,Department of Economic Analysis and Finances, Universidad de Castilla-La Mancha, 45071, Toledo, Spain
| | - Margarita Ruiz-Ramos
- Research Centre for the Management of Agricultural and Environmental Risks (CEIGRAM), Universidad Politécnica de Madrid, Madrid, 28040, Spain
| | - Mikhail A Semenov
- Department of Plant Science, Rothamsted Research, Harpenden, AL5 2JQ, UK
| | - Stefan Siebert
- Department of Crop Sciences, University of Göttingen, Göttingen, 37075, Germany
| | - Tommaso Stella
- Leibniz-Centre for Agricultural Landscape Research (ZALF), 15374, Müncheberg, Germany
| | | | - Giacomo Trombi
- Centre for Crop Science, Queensland Alliance for Agriculture and Food Innovation, University of Queensland, 4069, Toowoomba, Australia
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16
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Ruane AC, Phillips MM, Rosenzweig C. Climate Shifts within Major Agricultural Seasons for +1.5 and +2.0 °C Worlds: HAPPI Projections and AgMIP Modeling Scenarios. Agric For Meteorol 2018; 259:329-344. [PMID: 30880854 PMCID: PMC6415298 DOI: 10.1016/j.agrformet.2018.05.013] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
This study compares climate changes in major agricultural regions and current agricultural seasons associated with global warming of +1.5 or +2.0 °C above pre-industrial conditions. It describes the generation of climate scenarios for agricultural modeling applications conducted as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Coordinated Global and Regional Assessments. Climate scenarios from the Half a degree Additional warming, Projections, Prognosis and Impacts project (HAPPI) are largely consistent with transient scenarios extracted from RCP4.5 simulations of the Coupled Model Intercomparison Project phase 5 (CMIP5). Focusing on food and agricultural systems and top-producing breadbaskets in particular, we distinguish maize, rice, wheat, and soy season changes from global annual mean climate changes. Many agricultural regions warm at a rate that is faster than the global mean surface temperature (including oceans) but slower than the mean land surface temperature, leading to regional warming that exceeds 0.5 °C between the +1.5 and +2.0 °C Worlds. Agricultural growing seasons warm at a pace slightly behind the annual temperature trends in most regions, while precipitation increases slightly ahead of the annual rate. Rice cultivation regions show reduced warming as they are concentrated where monsoon rainfall is projected to intensify, although projections are influenced by Asian aerosol loading in climate mitigation scenarios. Compared to CMIP5, HAPPI slightly underestimates the CO2 concentration that corresponds to the +1.5 °C World but overestimates the CO2 concentration for the +2.0 °C World, which means that HAPPI scenarios may also lead to an overestimate in the beneficial effects of CO2 on crops in the +2.0 °C World. HAPPI enables detailed analysis of the shifting distribution of extreme growing season temperatures and precipitation, highlighting widespread increases in extreme heat seasons and heightened skewness toward hot seasons in the tropics. Shifts in the probability of extreme drought seasons generally tracked median precipitation changes; however, some regions skewed toward drought conditions even where median precipitation changes were small. Together, these findings highlight unique seasonal and agricultural region changes in the +1.5°C and +2.0°C worlds for adaptation planning in these climate stabilization targets.
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Affiliation(s)
- Alex C Ruane
- NASA Goddard Institute for Space Studies, New York, NY, USA
| | - Meridel M Phillips
- Columbia University Center for Climate Systems Research, New York, NY, USA
- NASA Goddard Institute for Space Studies, New York, NY, USA
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17
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Müller C, Elliott J, Pugh TAM, Ruane AC, Ciais P, Balkovic J, Deryng D, Folberth C, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Reddy AD, Schmid E, Wang X. Global patterns of crop yield stability under additional nutrient and water inputs. PLoS One 2018; 13:e0198748. [PMID: 29949598 PMCID: PMC6021068 DOI: 10.1371/journal.pone.0198748] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2018] [Accepted: 05/24/2018] [Indexed: 11/18/2022] Open
Abstract
Agricultural production must increase to feed a growing and wealthier population, as well as to satisfy increasing demands for biomaterials and biomass-based energy. At the same time, deforestation and land-use change need to be minimized in order to preserve biodiversity and maintain carbon stores in vegetation and soils. Consequently, agricultural land use needs to be intensified in order to increase food production per unit area of land. Here we use simulations of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 to assess implications of input-driven intensification (water, nutrients) on crop yield and yield stability, which is an important aspect in food security. We find region- and crop-specific responses for the simulated period 1980-2009 with broadly increasing yield variability under additional nitrogen inputs and stabilizing yields under additional water inputs (irrigation), reflecting current patterns of water and nutrient limitation. The different models of the GGCMI ensemble show similar response patterns, but model differences warrant further research on management assumptions, such as variety selection and soil management, and inputs as well as on model implementation of different soil and plant processes, such as on heat stress, and parameters. Higher variability in crop productivity under higher fertilizer input will require adequate buffer mechanisms in trade and distribution/storage networks to avoid food price volatility.
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Affiliation(s)
| | - Joshua Elliott
- University of Chicago and ANL Computation Institute, Chicago, Illinois, United States of America
- Columbia University Center for Climate Systems Research, New York, New York, United States of America
| | - Thomas A. M. Pugh
- School of Geography, Earth & Environmental Science and Birmingham Institute of Forest Research, University of Birmingham, Birmingham, United Kingdom
- IMK-IFU, Karlsruhe Institute of Technology, Garmisch-Partenkirchen, Germany
| | - Alex C. Ruane
- Columbia University Center for Climate Systems Research, New York, New York, United States of America
- National Aeronautics and Space Administration Goddard Institute for Space Studies, New York, New York, United States of America
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l’Environnement, Gif-sur-Yvette, France
| | - Juraj Balkovic
- Ecosystem Services and Management Program, International Institute for Applied Systems Analysis, Laxenburg, Austria
- Department of Soil Science, Faculty of Natural Sciences, Comenius University in Bratislava, Bratislava, Slovak Republic
| | - Delphine Deryng
- Columbia University Center for Climate Systems Research, New York, New York, United States of America
- Climate Analytics, Berlin, Germany
| | - Christian Folberth
- Ecosystem Services and Management Program, International Institute for Applied Systems Analysis, Laxenburg, Austria
| | - R. Cesar Izaurralde
- University of Maryland, Department of Geographical Sciences, College Park, Maryland, United States of America
- Texas A&M University, Texas AgriLife Research and Extension, Temple, Texas, United States of America
| | - Curtis D. Jones
- University of Maryland, Department of Geographical Sciences, College Park, Maryland, United States of America
| | - Nikolay Khabarov
- Ecosystem Services and Management Program, International Institute for Applied Systems Analysis, Laxenburg, Austria
| | - Peter Lawrence
- National Center for Atmospheric Research, Earth System Laboratory, Boulder, Colorado, United States of America
| | - Wenfeng Liu
- Laboratoire des Sciences du Climat et de l’Environnement, Gif-sur-Yvette, France
- Eawag, Swiss Federal Institute of Aquatic Science and Technology, Duebendorf, Switzerland
| | - Ashwan D. Reddy
- University of Maryland, Department of Geographical Sciences, College Park, Maryland, United States of America
| | - Erwin Schmid
- Institute for Sustainable Economic Development, University of Natural Resources and Life Sciences, Vienna, Austria
| | - Xuhui Wang
- Laboratoire des Sciences du Climat et de l’Environnement, Gif-sur-Yvette, France
- Sino-French Institute of Earth System Sciences, Peking University, Beijing, China
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18
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Rosenzweig C, Ruane AC, Antle J, Elliott J, Ashfaq M, Chatta AA, Ewert F, Folberth C, Hathie I, Havlik P, Hoogenboom G, Lotze-Campen H, MacCarthy DS, Mason-D'Croz D, Contreras EM, Müller C, Perez-Dominguez I, Phillips M, Porter C, Raymundo RM, Sands RD, Schleussner CF, Valdivia RO, Valin H, Wiebe K. Coordinating AgMIP data and models across global and regional scales for 1.5°C and 2.0°C assessments. Philos Trans A Math Phys Eng Sci 2018; 376:20160455. [PMID: 29610385 PMCID: PMC5897826 DOI: 10.1098/rsta.2016.0455] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 11/29/2017] [Indexed: 05/19/2023]
Abstract
The Agricultural Model Intercomparison and Improvement Project (AgMIP) has developed novel methods for Coordinated Global and Regional Assessments (CGRA) of agriculture and food security in a changing world. The present study aims to perform a proof of concept of the CGRA to demonstrate advantages and challenges of the proposed framework. This effort responds to the request by the UN Framework Convention on Climate Change (UNFCCC) for the implications of limiting global temperature increases to 1.5°C and 2.0°C above pre-industrial conditions. The protocols for the 1.5°C/2.0°C assessment establish explicit and testable linkages across disciplines and scales, connecting outputs and inputs from the Shared Socio-economic Pathways (SSPs), Representative Agricultural Pathways (RAPs), Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) and Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble scenarios, global gridded crop models, global agricultural economics models, site-based crop models and within-country regional economics models. The CGRA consistently links disciplines, models and scales in order to track the complex chain of climate impacts and identify key vulnerabilities, feedbacks and uncertainties in managing future risk. CGRA proof-of-concept results show that, at the global scale, there are mixed areas of positive and negative simulated wheat and maize yield changes, with declines in some breadbasket regions, at both 1.5°C and 2.0°C. Declines are especially evident in simulations that do not take into account direct CO2 effects on crops. These projected global yield changes mostly resulted in increases in prices and areas of wheat and maize in two global economics models. Regional simulations for 1.5°C and 2.0°C using site-based crop models had mixed results depending on the region and the crop. In conjunction with price changes from the global economics models, productivity declines in the Punjab, Pakistan, resulted in an increase in vulnerable households and the poverty rate.This article is part of the theme issue 'The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels'.
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Affiliation(s)
- Cynthia Rosenzweig
- Goddard Institute for Space Studies, National Aeronautics and Space Administration, 2880 Broadway, New York, NY 10025, USA
- Center for Climate Systems Research, Columbia University, 2880 Broadway, New York, NY 10025, USA
| | - Alex C Ruane
- Goddard Institute for Space Studies, National Aeronautics and Space Administration, 2880 Broadway, New York, NY 10025, USA
- Center for Climate Systems Research, Columbia University, 2880 Broadway, New York, NY 10025, USA
| | - John Antle
- Department of Applied Economics, Oregon State University, 213 Ballard Hall, Corvallis, OR 97331, USA
| | - Joshua Elliott
- Computation Institute, University of Chicago, 5735 South Ellis Avenue, Chicago, IL 60637, USA
| | - Muhammad Ashfaq
- University of Agriculture Faisalabad, University Main Road, Faisalabad, Pakistan
| | - Ashfaq Ahmad Chatta
- University of Agriculture Faisalabad, University Main Road, Faisalabad, Pakistan
| | - Frank Ewert
- INRES-Crop Science, University of Bonn, Katzenburgweg 5, 53115 Bonn, Germany
- Leibniz Center for Agricultural Landscape Research (ZALF), Eberswalder Strasse 84, 15374 Müncheberg, Germany
| | - Christian Folberth
- Ecosystems Services and Management Program, International Institute for Applied Systems Analysis, Schlossplatz 1, 2361 Laxenburg, Austria
| | - Ibrahima Hathie
- Initiative Prospective Agricole et Rurale, 67 Rond-Point VDN--Ouest Foire, BP 16788, Dakar-Fann, Senegal
| | - Petr Havlik
- Ecosystems Services and Management Program, International Institute for Applied Systems Analysis, Schlossplatz 1, 2361 Laxenburg, Austria
| | - Gerrit Hoogenboom
- Department of Agricultural and Biological Engineering, University of Florida, Frazier Rogers Hall, Gainesville, FL 32611, USA
| | - Hermann Lotze-Campen
- Potsdam-Institut fur Klimafolgenforschung eV, PO Box 601203, 14412 Potsdam, Germany
- Humboldt-Universität zu Berlin, 10099 Berlin, Germany
| | - Dilys S MacCarthy
- Soil and Irrigation Research Centre, University of Ghana, PO Box LG 68, Kpong, Ghana
| | - Daniel Mason-D'Croz
- International Food Policy Research Institute, 1201 I Street NW, Washington, DC 20005, USA
- Commonwealth Science and Industrial Research Organisation, 306 Carmody Road, St Lucia, QLD 4067, Australia
| | - Erik Mencos Contreras
- Goddard Institute for Space Studies, National Aeronautics and Space Administration, 2880 Broadway, New York, NY 10025, USA
- Center for Climate Systems Research, Columbia University, 2880 Broadway, New York, NY 10025, USA
| | - Christoph Müller
- Potsdam-Institut fur Klimafolgenforschung eV, PO Box 601203, 14412 Potsdam, Germany
| | | | - Meridel Phillips
- Goddard Institute for Space Studies, National Aeronautics and Space Administration, 2880 Broadway, New York, NY 10025, USA
- Center for Climate Systems Research, Columbia University, 2880 Broadway, New York, NY 10025, USA
| | - Cheryl Porter
- Department of Agricultural and Biological Engineering, University of Florida, Frazier Rogers Hall, Gainesville, FL 32611, USA
| | - Rubi M Raymundo
- Department of Agricultural and Biological Engineering, University of Florida, Frazier Rogers Hall, Gainesville, FL 32611, USA
| | - Ronald D Sands
- Economic Research Service, United States Department of Agriculture, 355 E Street SW, Washington, DC 20024, USA
| | - Carl-Friedrich Schleussner
- Potsdam-Institut fur Klimafolgenforschung eV, PO Box 601203, 14412 Potsdam, Germany
- Climate Analytics, Ritterstrasse 3, 10969 Berlin, Germany
| | - Roberto O Valdivia
- Department of Applied Economics, Oregon State University, 213 Ballard Hall, Corvallis, OR 97331, USA
| | - Hugo Valin
- Ecosystems Services and Management Program, International Institute for Applied Systems Analysis, Schlossplatz 1, 2361 Laxenburg, Austria
| | - Keith Wiebe
- International Food Policy Research Institute, 1201 I Street NW, Washington, DC 20005, USA
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Ruane AC, Antle J, Elliott J, Folberth C, Hoogenboom G, Mason-D’Croz D, Müller C, Porter C, Phillips MM, Raymundo RM, Sands R, Valdivia RO, White JW, Wiebe K, Rosenzweig C. Biophysical and economic implications for agriculture of +1.5° and +2.0°C global warming using AgMIP Coordinated Global and Regional Assessments. Clim Res 2018; 76:17-39. [PMID: 33154611 PMCID: PMC7641099 DOI: 10.3354/cr01520] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
This study presents results of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Coordinated Global and Regional Assessments (CGRA) of +1.5° and +2.0°C global warming above pre-industrial conditions. This first CGRA application provides multi-discipline, multi-scale, and multi-model perspectives to elucidate major challenges for the agricultural sector caused by direct biophysical impacts of climate changes as well as ramifications of associated mitigation strategies. Agriculture in both target climate stabilizations is characterized by differential impacts across regions and farming systems, with tropical maize Zea mays experiencing the largest losses, while soy Glycine max mostly benefits. The result is upward pressure on prices and area expansion for maize and wheat Triticum aestivum, while soy prices and area decline (results for rice Oryza sativa are mixed). An example global mitigation strategy encouraging bioenergy expansion is more disruptive to land use and crop prices than the climate change impacts alone, even in the +2.0°C scenario which has a larger climate signal and lower mitigation requirement than the +1.5°C scenario. Coordinated assessments reveal that direct biophysical and economic impacts can be substantially larger for regional farming systems than global production changes. Regional farmers can buffer negative effects or take advantage of new opportunities via mitigation incentives and farm management technologies. Primary uncertainties in the CGRA framework include the extent of CO2 benefits for diverse agricultural systems in crop models, as simulations without CO2 benefits show widespread production losses that raise prices and expand agricultural area.
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Affiliation(s)
- Alex C. Ruane
- NASA Goddard Institute for Space Studies, New York, NY 10025, USA
- Corresponding author:
| | - John Antle
- Oregon State University, Corvallis, OR 97331, USA
| | | | - Christian Folberth
- International Institute for Applied Systems Analysis, 2361 Laxenburg, Austria
| | | | - Daniel Mason-D’Croz
- International Food Policy Research Institute, Washington, DC 20005, USA
- Commonwealth Science and Industrial Research Organisation, St Lucia, QLD 4067, Australia
| | - Christoph Müller
- Potsdam Institute for Climate Impacts Research, 14473 Potsdam, Germany
| | | | - Meridel M. Phillips
- NASA Goddard Institute for Space Studies, New York, NY 10025, USA
- Columbia University Center for Climate Systems Research, New York, NY 10025, USA
| | | | - Ronald Sands
- USDA Economic Research Service, Washington, DC 20036, USA
| | | | | | - Keith Wiebe
- International Food Policy Research Institute, Washington, DC 20005, USA
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Ruane AC, Rosenzweig C, Asseng S, Boote KJ, Elliott J, Ewert F, Jones JW, Martre P, McDermid SP, Müller C, Snyder A, Thorburn PJ. An AgMIP framework for improved agricultural representation in IAMs. Environ Res Lett 2017; 12:125003. [PMID: 30881482 PMCID: PMC6417889 DOI: 10.1088/1748-9326/aa8da6] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/23/2023]
Abstract
Integrated assessment models (IAMs) hold great potential to assess how future agricultural systems will be shaped by socioeconomic development, technological innovation, and changing climate conditions. By coupling with climate and crop model emulators, IAMs have the potential to resolve important agricultural feedback loops and identify unintended consequences of socioeconomic development for agricultural systems. Here we propose a framework to develop robust representation of agricultural system responses within IAMs, linking downstream applications with model development and the coordinated evaluation of key climate responses from local to global scales. We survey the strengths and weaknesses of protocol-based assessments linked to the Agricultural Model Intercomparison and Improvement Project (AgMIP), each utilizing multiple sites and models to evaluate crop response to core climate changes including shifts in carbon dioxide concentration, temperature, and water availability, with some studies further exploring how climate responses are affected by nitrogen levels and adaptation in farm systems. Site-based studies with carefully calibrated models encompass the largest number of activities; however they are limited in their ability to capture the full range of global agricultural system diversity. Representative site networks provide more targeted response information than broadly-sampled networks, with limitations stemming from difficulties in covering the diversity of farming systems. Global gridded crop models provide comprehensive coverage, although with large challenges for calibration and quality control of inputs. Diversity in climate responses underscores that crop model emulators must distinguish between regions and farming system while recognizing model uncertainty. Finally, to bridge the gap between bottom-up and top-down approaches we recommend the deployment of a hybrid climate response system employing a representative network of sites to bias-correct comprehensive gridded simulations, opening the door to accelerated development and a broad range of applications.
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Affiliation(s)
- Alex C Ruane
- NASA Goddard Institute for Space Studies, New York, NY, USA
| | | | - Senthold Asseng
- University of Florida, Agricultural and Biological Engineering, Gainesville, FL, USA
| | - Kenneth J Boote
- University of Florida, Agricultural and Biological Engineering, Gainesville, FL, USA
| | - Joshua Elliott
- University of Chicago, Computation Institute, Chicago, IL, USA
| | - Frank Ewert
- University of Bonn, Bonn, Germany
- Leibniz Center of Agricultural landscape Research (ZALF), Muencheberg, Germany
| | - James W Jones
- University of Florida, Agricultural and Biological Engineering, Gainesville, FL, USA
- National Science Foundation, Arlington, VA, USA
| | - Pierre Martre
- UMR LEPSE, INRA, Montpellier SupAgro, Montpellier, France
| | | | | | - Abigail Snyder
- Pacific Northwest National Laboratory, College Park, MD, USA
| | - Peter J Thorburn
- Commonwealth Scientific and Industrial Research Organization, Brisbane, Australia
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21
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Wang E, Martre P, Zhao Z, Ewert F, Maiorano A, Rötter RP, Kimball BA, Ottman MJ, Wall GW, White JW, Reynolds MP, Alderman PD, Aggarwal PK, Anothai J, Basso B, Biernath C, Cammarano D, Challinor AJ, De Sanctis G, Doltra J, Dumont B, Fereres E, Garcia-Vila M, Gayler S, Hoogenboom G, Hunt LA, Izaurralde RC, Jabloun M, Jones CD, Kersebaum KC, Koehler AK, Liu L, Müller C, Kumar SN, Nendel C, O'Leary G, Olesen JE, Palosuo T, Priesack E, Rezaei EE, Ripoche D, Ruane AC, Semenov MA, Shcherbak I, Stöckle C, Stratonovitch P, Streck T, Supit I, Tao F, Thorburn P, Waha K, Wallach D, Wang Z, Wolf J, Zhu Y, Asseng S. Author Correction: The uncertainty of crop yield projections is reduced by improved temperature response functions. Nat Plants 2017; 3:833. [PMID: 28955035 DOI: 10.1038/s41477-017-0032-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Nature Plants 3, 17102 (2017); published online 17 July 2017; corrected online 27 September 2017.
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Affiliation(s)
- Enli Wang
- CSIRO Agriculture and Food, Black Mountain, ACT, 2601, Australia.
| | - Pierre Martre
- UMR LEPSE, INRA, Montpellier SupAgro, 2 Place Viala, 34 060, Montpellier, France
| | - Zhigan Zhao
- CSIRO Agriculture and Food, Black Mountain, ACT, 2601, Australia
- College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Frank Ewert
- Institute of Crop Science and Resource Conservation (INRES), University of Bonn, 53115, Bonn, Germany
- Institute of Landscape Systems Analysis, Leibniz Centre for Agricultural Landscape Research, 15374, Müncheberg, Germany
| | - Andrea Maiorano
- UMR LEPSE, INRA, Montpellier SupAgro, 2 Place Viala, 34 060, Montpellier, France
| | - Reimund P Rötter
- Department of Crop Sciences, University of Goettingen, Tropical Plant Production and Agricultural Systems Modelling (TROPAGS), 37077, Göttingen, Germany
- Centre of Biodiversity and Sustainable Land Use (CBL), University of Goettingen, Büsgenweg 1, 37077, Göttingen, Germany
| | - Bruce A Kimball
- USDA, Agricultural Research Service, U.S. Arid-Land Agricultural Research Center, Maricopa, AZ, 85138, USA
| | - Michael J Ottman
- The School of Plant Sciences, University of Arizona, Tucson, AZ, 85721, USA
| | - Gerard W Wall
- USDA, Agricultural Research Service, U.S. Arid-Land Agricultural Research Center, Maricopa, AZ, 85138, USA
| | - Jeffrey W White
- USDA, Agricultural Research Service, U.S. Arid-Land Agricultural Research Center, Maricopa, AZ, 85138, USA
| | - Matthew P Reynolds
- Global Wheat Program, International Maize and Wheat Improvement Center (CIMMYT) Apdo, 06600, Mexico, D.F, Mexico
| | - Phillip D Alderman
- Global Wheat Program, International Maize and Wheat Improvement Center (CIMMYT) Apdo, 06600, Mexico, D.F, Mexico
| | - Pramod K Aggarwal
- CGIAR Research Program on Climate Change, Agriculture and Food Security, Borlaug Institute for South Asia, International Maize and Wheat Improvement Center (CIMMYT), New Delhi, 110012, India
| | - Jakarat Anothai
- AgWeatherNet Program, Washington State University, Prosser, WA, 99350-8694, USA
| | - Bruno Basso
- Department of Earth and Environmental Sciences and W.K. Kellogg Biological Station, Michigan State University, East Lansing, MI, 48823, USA
| | - Christian Biernath
- Helmholtz Zentrum München - German Research Center for Environmental Health, Institute of Biochemical Plant Pathology, Neuherberg, 85764, Germany
| | - Davide Cammarano
- Agricultural and Biological Engineering Department, University of Florida, Gainesville, FL, 32611, USA
| | - Andrew J Challinor
- Institute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, Leeds, LS29JT, UK
- CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), Km 17, Recta Cali-Palmira Apartado Aéreo, 6713, Cali, Colombia
| | - Giacomo De Sanctis
- GMO Unit, European Food Safety Authority (EFSA), Via Carlo Magno, 1A, 43126, Parma, Italy
| | - Jordi Doltra
- Cantabrian Agricultural Research and Training Centre (CIFA), 39600, Muriedas, Spain
| | - Benjamin Dumont
- Department of Earth and Environmental Sciences and W.K. Kellogg Biological Station, Michigan State University, East Lansing, MI, 48823, USA
| | - Elias Fereres
- Dep. Agronomia, University of Cordoba, Apartado 3048, 14080, Cordoba, Spain
- IAS-CSIC, Cordoba, 14080, Spain
| | - Margarita Garcia-Vila
- Dep. Agronomia, University of Cordoba, Apartado 3048, 14080, Cordoba, Spain
- IAS-CSIC, Cordoba, 14080, Spain
| | - Sebastian Gayler
- Institute of Soil Science and Land Evaluation, University of Hohenheim, 70599, Stuttgart, Germany
| | - Gerrit Hoogenboom
- AgWeatherNet Program, Washington State University, Prosser, WA, 99350-8694, USA
| | - Leslie A Hunt
- Department of Plant Agriculture, University of Guelph, Guelph, ON, N1G 2W1, Canada
| | - Roberto C Izaurralde
- Department of Geographical Sciences, University of Maryland, College Park, MD, 20742, USA
- Texas A&M AgriLife Research and Extension Center, Texas A&M University, Temple, TX, 76502, USA
| | - Mohamed Jabloun
- Department of Agroecology, Aarhus University, 8830, Tjele, Denmark
| | - Curtis D Jones
- Department of Geographical Sciences, University of Maryland, College Park, MD, 20742, USA
| | - Kurt C Kersebaum
- Institute of Landscape Systems Analysis, Leibniz Centre for Agricultural Landscape Research, 15374, Müncheberg, Germany
| | - Ann-Kristin Koehler
- Institute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, Leeds, LS29JT, UK
| | - Leilei Liu
- 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 Agricultural University, Nanjing, Jiangsu, 210095, China
| | - Christoph Müller
- Potsdam Institute for Climate Impact Research, 14473, Potsdam, Germany
| | - Soora Naresh Kumar
- Centre for Environment Science and Climate Resilient Agriculture, Indian Agricultural Research Institute, IARI PUSA, New Delhi, 110 012, India
| | - Claas Nendel
- Institute of Landscape Systems Analysis, Leibniz Centre for Agricultural Landscape Research, 15374, Müncheberg, Germany
| | - Garry O'Leary
- Department of Economic Development, Landscape & Water Sciences, Jobs, Transport and Resources, Horsham, 3400, Australia
| | - Jørgen E Olesen
- Department of Agroecology, Aarhus University, 8830, Tjele, Denmark
| | - Taru Palosuo
- Natural Resources Institute Finland (Luke), Latokartanonkaari 9, 00790, Helsinki, Finland
| | - Eckart Priesack
- Helmholtz Zentrum München - German Research Center for Environmental Health, Institute of Biochemical Plant Pathology, Neuherberg, 85764, Germany
| | - Ehsan Eyshi Rezaei
- Institute of Crop Science and Resource Conservation (INRES), University of Bonn, 53115, Bonn, Germany
| | | | - Alex C Ruane
- NASA Goddard Institute for Space Studies, New York, NY, 10025, USA
| | - Mikhail A Semenov
- Computational and Systems Biology Department, Rothamsted Research, Harpenden, Herts, AL5 2JQ, UK
| | - Iurii Shcherbak
- Department of Earth and Environmental Sciences and W.K. Kellogg Biological Station, Michigan State University, East Lansing, MI, 48823, USA
| | - Claudio Stöckle
- Biological Systems Engineering, Washington State University, Pullman, WA, 99164-6120, USA
| | - Pierre Stratonovitch
- Computational and Systems Biology Department, Rothamsted Research, Harpenden, Herts, AL5 2JQ, UK
| | - Thilo Streck
- Institute of Soil Science and Land Evaluation, University of Hohenheim, 70599, Stuttgart, Germany
| | - Iwan Supit
- PPS and WSG & CALM, Wageningen University, 6700AA, Wageningen, The Netherlands
| | - Fulu Tao
- Natural Resources Institute Finland (Luke), Latokartanonkaari 9, 00790, Helsinki, Finland
- Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Science, Beijing, 100101, China
| | - Peter Thorburn
- CSIRO Agriculture and Food, St Lucia, QLD, 4067, Australia
| | - Katharina Waha
- Potsdam Institute for Climate Impact Research, 14473, Potsdam, Germany
| | - Daniel Wallach
- INRA, UMR 1248 Agrosystèmes et développement territorial (AGIR), 31 326, Castanet-Tolosan, France
| | - Zhimin Wang
- College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Joost Wolf
- PPS and WSG & CALM, Wageningen University, 6700AA, Wageningen, The Netherlands
| | - Yan Zhu
- 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 Agricultural University, Nanjing, Jiangsu, 210095, China
| | - Senthold Asseng
- Agricultural and Biological Engineering Department, University of Florida, Gainesville, FL, 32611, USA
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McDermid SS, Mearns LO, Ruane AC. Representing agriculture in Earth System Models: approaches and priorities for development. J Adv Model Earth Syst 2017; 9:2230-2265. [PMID: 30574266 PMCID: PMC6298791 DOI: 10.1002/2016ms000749] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/07/2023]
Abstract
Earth System Model (ESM) advances now enable improved representations of spatially and temporally varying anthropogenic climate forcings. One critical forcing is global agriculture, which is now extensive in land-use and intensive in management, owing to 20th century development trends. Agriculture and food systems now contribute nearly 30% of global greenhouse gas emissions and require copious inputs and resources, such as fertilizer, water, and land. Much uncertainty remains in quantifying important agriculture-climate interactions, including surface moisture and energy balances and biogeochemical cycling. Despite these externalities and uncertainties, agriculture is increasingly being leveraged to function as a net sink of anthropogenic carbon, and there is much emphasis on future sustainable intensification. Given its significance as a major environmental and climate forcing, there now exist a variety of approaches to represent agriculture in ESMs. These approaches are reviewed herein, and range from idealized representations of agricultural extent to the development of coupled climate-crop models that capture dynamic feedbacks. We highlight the robust agriculture-climate interactions and responses identified by these modeling efforts, as well as existing uncertainties and model limitations. To this end, coordinated and benchmarking assessments of land-use-climate feedbacks can be leveraged for further improvements in ESM's agricultural representations. We suggest key areas for continued model development, including incorporating irrigation and biogeochemical cycling in particular. Lastly, we pose several critical research questions to guide future work. Our review focuses on ESM representations of climate-surface interactions over managed agricultural lands, rather than on ESMs as an estimation tool for crop yields and productivity.
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Affiliation(s)
- S S McDermid
- Dept. of Environmental Studies, New York University, New York, NY, USA
| | - L O Mearns
- National Center for Atmospheric Research, Boulder, CO, USA
| | - A C Ruane
- NASA Goddard Institute for Space Studies, New York, NY, USA
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23
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Zhao C, Liu B, Piao S, Wang X, Lobell DB, Huang Y, Huang M, Yao Y, Bassu S, Ciais P, Durand JL, Elliott J, Ewert F, Janssens IA, Li T, Lin E, Liu Q, Martre P, Müller C, Peng S, Peñuelas J, Ruane AC, Wallach D, Wang T, Wu D, Liu Z, Zhu Y, Zhu Z, Asseng S. Temperature increase reduces global yields of major crops in four independent estimates. Proc Natl Acad Sci U S A 2017; 114:9326-9331. [PMID: 28811375 PMCID: PMC5584412 DOI: 10.1073/pnas.1701762114] [Citation(s) in RCA: 712] [Impact Index Per Article: 101.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Wheat, rice, maize, and soybean provide two-thirds of human caloric intake. Assessing the impact of global temperature increase on production of these crops is therefore critical to maintaining global food supply, but different studies have yielded different results. Here, we investigated the impacts of temperature on yields of the four crops by compiling extensive published results from four analytical methods: global grid-based and local point-based models, statistical regressions, and field-warming experiments. Results from the different methods consistently showed negative temperature impacts on crop yield at the global scale, generally underpinned by similar impacts at country and site scales. Without CO2 fertilization, effective adaptation, and genetic improvement, each degree-Celsius increase in global mean temperature would, on average, reduce global yields of wheat by 6.0%, rice by 3.2%, maize by 7.4%, and soybean by 3.1%. Results are highly heterogeneous across crops and geographical areas, with some positive impact estimates. Multimethod analyses improved the confidence in assessments of future climate impacts on global major crops and suggest crop- and region-specific adaptation strategies to ensure food security for an increasing world population.
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Affiliation(s)
- Chuang Zhao
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Bing Liu
- National Engineering and Technology Center for Information Agriculture, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China
- Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture, Nanjing Agricultural University, Nanjing, Jiangsu 210095
- Jiangsu Key Laboratory for Information Agriculture, Nanjing Agricultural University, Nanjing, Jiangsu 210095
- Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, Jiangsu 210095
- Agricultural and Biological Engineering Department, University of Florida, Gainesville, FL 32611
| | - Shilong Piao
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China;
- Key Laboratory of Alpine Ecology and Biodiversity, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100085, China
- Center for Excellence in Tibetan Earth Science, Chinese Academy of Sciences, Beijing 100085, China
| | - Xuhui Wang
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - David B Lobell
- Department of Earth System Science Center on Food Security and the Environment, Stanford University, Stanford, CA 94305
| | - Yao Huang
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
| | - Mengtian Huang
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Yitong Yao
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Simona Bassu
- Desertification Research Centre, University of Sassari, 07100 Sassari, Italy
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, Le Commissariat à l'Énergie Atomique et aux Énergies Alternatives, CNRS, Université de Versailles Saint-Quentin, Gif-sur-Yvette 91191, France
| | - Jean-Louis Durand
- Unité de Recherche Pluridisciplinaire Prairies et Plantes Fourragères, Institut National de la Recherche Agronomique, CS 80006, 86600 Lusignan, France
| | - Joshua Elliott
- University of Chicago Computation Institute, University of Chicago, Chicago, IL 60637
- Columbia University Center for Climate Systems Research, Columbia University, New York, NY 10025
| | - Frank Ewert
- Institute of Crop Science and Resource Conservation, University of Bonn, Bonn 53115, Germany
- Leibniz Centre for Agricultural Landscape Research, 15374 Müncheberg, Germany
| | - Ivan A Janssens
- Department of Biology, University of Antwerp, 2610 Wilrijk, Belgium
| | - Tao Li
- International Rice Research Institute, Los Baños, 4031 Laguna, Philippines
| | - Erda Lin
- Agro-Environment and Sustainable Development Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Qiang Liu
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Pierre Martre
- UMR Laboratoire d'Ecophysiologie des Plantes sous Stress Environementaux, Institut National de la Recherche Agronomique, Montpellier SupAgro, 34060 Montpellier, France
| | - Christoph Müller
- Climate Impacts and Vulnerabilities, Potsdam Institute for Climate Impact Research, 14473 Potsdam, Germany
| | - Shushi Peng
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Josep Peñuelas
- Centre de Recerca Ecològica i Aplicacions Forestals, Cerdanyola del Valles, Barcelona 08193, Catalonia, Spain
- Global Ecology Unit CREAF-CSIC-UAB, Consejo Superior de Investigaciones Científicas, Bellaterra, Barcelona 08193, Catalonia, Spain
| | - Alex C Ruane
- National Aeronautics and Space Administration Goddard Institute for Space Studies, New York, NY 10025
- Columbia University Center for Climate Systems Research, Columbia University, New York, NY 10025
| | - Daniel Wallach
- UMR 1248 Agrosystèmes et Développement Territorial, Institut National de la Recherche Agronomique, 31326 Castanet-Tolosan Cedex, France
| | - Tao Wang
- Key Laboratory of Alpine Ecology and Biodiversity, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100085, China
- Center for Excellence in Tibetan Earth Science, Chinese Academy of Sciences, Beijing 100085, China
| | - Donghai Wu
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Zhuo Liu
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Yan Zhu
- National Engineering and Technology Center for Information Agriculture, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China
- Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture, Nanjing Agricultural University, Nanjing, Jiangsu 210095
- Jiangsu Key Laboratory for Information Agriculture, Nanjing Agricultural University, Nanjing, Jiangsu 210095
- Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, Jiangsu 210095
| | - Zaichun Zhu
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Senthold Asseng
- Agricultural and Biological Engineering Department, University of Florida, Gainesville, FL 32611;
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Wang E, Martre P, Zhao Z, Ewert F, Maiorano A, Rötter RP, Kimball BA, Ottman MJ, Wall GW, White JW, Reynolds MP, Alderman PD, Aggarwal PK, Anothai J, Basso B, Biernath C, Cammarano D, Challinor AJ, De Sanctis G, Doltra J, Fereres E, Garcia-Vila M, Gayler S, Hoogenboom G, Hunt LA, Izaurralde RC, Jabloun M, Jones CD, Kersebaum KC, Koehler AK, Liu L, Müller C, Kumar SN, Nendel C, O'Leary G, Olesen JE, Palosuo T, Priesack E, Rezaei EE, Ripoche D, Ruane AC, Semenov MA, Shcherbak I, Stöckle C, Stratonovitch P, Streck T, Supit I, Tao F, Thorburn P, Waha K, Wallach D, Wang Z, Wolf J, Zhu Y, Asseng S. Erratum: The uncertainty of crop yield projections is reduced by improved temperature response functions. Nat Plants 2017; 3:17125. [PMID: 28770816 DOI: 10.1038/nplants.2017.125] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
This corrects the article DOI: 10.1038/nplants.2017.102.
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25
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Wang E, Martre P, Zhao Z, Ewert F, Maiorano A, Rötter RP, Kimball BA, Ottman MJ, Wall GW, White JW, Reynolds MP, Alderman PD, Aggarwal PK, Anothai J, Basso B, Biernath C, Cammarano D, Challinor AJ, De Sanctis G, Doltra J, Dumont B, Fereres E, Garcia-Vila M, Gayler S, Hoogenboom G, Hunt LA, Izaurralde RC, Jabloun M, Jones CD, Kersebaum KC, Koehler AK, Liu L, Müller C, Naresh Kumar S, Nendel C, O'Leary G, Olesen JE, Palosuo T, Priesack E, Eyshi Rezaei E, Ripoche D, Ruane AC, Semenov MA, Shcherbak I, Stöckle C, Stratonovitch P, Streck T, Supit I, Tao F, Thorburn P, Waha K, Wallach D, Wang Z, Wolf J, Zhu Y, Asseng S. The uncertainty of crop yield projections is reduced by improved temperature response functions. Nat Plants 2017; 3:17102. [PMID: 28714956 DOI: 10.1038/nplants.2017.102] [Citation(s) in RCA: 52] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/06/2016] [Accepted: 06/05/2017] [Indexed: 05/22/2023]
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.
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Affiliation(s)
- Enli Wang
- CSIRO Agriculture and Food, Black Mountain, Australian Capital Territory 2601, Australia
| | - Pierre Martre
- UMR LEPSE, INRA, Montpellier SupAgro, 2 Place Viala, 34 060 Montpellier, France
| | - Zhigan Zhao
- College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
- CSIRO Agriculture and Food, Black Mountain, Australian Capital Territory 2601, Australia
| | - Frank Ewert
- Institute of Crop Science and Resource Conservation (INRES), University of Bonn, 53115 Bonn, Germany
- Institute of Landscape Systems Analysis, Leibniz Centre for Agricultural Landscape Research, 15374 Müncheberg, Germany
| | - Andrea Maiorano
- UMR LEPSE, INRA, Montpellier SupAgro, 2 Place Viala, 34 060 Montpellier, France
| | - Reimund P Rötter
- Department of Crop Sciences, University of Goettingen, Tropical Plant Production and Agricultural Systems Modelling (TROPAGS), 37077 Göttingen, Germany
- Centre of Biodiversity and Sustainable Land Use (CBL), University of Goettingen, Büsgenweg 1, 37077 Göttingen, Germany
| | - Bruce A Kimball
- USDA, Agricultural Research Service, U.S. Arid-Land Agricultural Research Center, Maricopa, Arizona 85138, USA
| | - Michael J Ottman
- The School of Plant Sciences, University of Arizona, Tucson, Arizona 85721, USA
| | - Gerard W Wall
- USDA, Agricultural Research Service, U.S. Arid-Land Agricultural Research Center, Maricopa, Arizona 85138, USA
| | - Jeffrey W White
- USDA, Agricultural Research Service, U.S. Arid-Land Agricultural Research Center, Maricopa, Arizona 85138, USA
| | - Matthew P Reynolds
- Global Wheat Program, International Maize and Wheat Improvement Center (CIMMYT) Apdo, 06600 Mexico, D.F, Mexico
| | - Phillip D Alderman
- Global Wheat Program, International Maize and Wheat Improvement Center (CIMMYT) Apdo, 06600 Mexico, D.F, Mexico
| | - Pramod K Aggarwal
- CGIAR Research Program on Climate Change, Agriculture and Food Security, Borlaug Institute for South Asia, International Maize and Wheat Improvement Center (CIMMYT), New Delhi 110012, India
| | - Jakarat Anothai
- AgWeatherNet Program, Washington State University, Prosser, Washington 99350-8694, USA
| | - Bruno Basso
- Department of Earth and Environmental Sciences and W.K. Kellogg Biological Station, Michigan State University East Lansing, Michigan 48823, USA
| | - Christian Biernath
- Helmholtz Zentrum München - German Research Center for Environmental Health, Institute of Biochemical Plant Pathology, Neuherberg, 85764, Germany
| | - Davide Cammarano
- Agricultural and Biological Engineering Department, University of Florida, Gainesville, Florida 32611, USA
| | - Andrew J Challinor
- Institute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, Leeds LS29JT, UK
- CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), Km 17, Recta Cali-Palmira Apartado Aéreo 6713, Cali, Colombia
| | - Giacomo De Sanctis
- GMO Unit, European Food Safety Authority (EFSA), Via Carlo Magno, 1A, 43126 Parma, Italy
| | - Jordi Doltra
- Cantabrian Agricultural Research and Training Centre (CIFA), 39600 Muriedas, Spain
| | | | - Elias Fereres
- Dep. Agronomia, University of Cordoba, Apartado 3048, 14080 Cordoba, Spain
- IAS-CSIC, Cordoba 14080, Spain
| | - Margarita Garcia-Vila
- Dep. Agronomia, University of Cordoba, Apartado 3048, 14080 Cordoba, Spain
- IAS-CSIC, Cordoba 14080, Spain
| | - Sebastian Gayler
- Institute of Soil Science and Land Evaluation, University of Hohenheim, 70599 Stuttgart, Germany
| | - Gerrit Hoogenboom
- AgWeatherNet Program, Washington State University, Prosser, Washington 99350-8694, USA
| | - Leslie A Hunt
- Department of Plant Agriculture, University of Guelph, Guelph, Ontario N1G 2W1, Canada
| | - Roberto C Izaurralde
- Department of Geographical Sciences, University of Maryland, College Park, Maryland 20742, USA
- Texas A&M AgriLife Research and Extension Center, Texas A&M University, Temple, Texas 76502, USA
| | - Mohamed Jabloun
- Department of Agroecology, Aarhus University, 8830 Tjele, Denmark
| | - Curtis D Jones
- Department of Geographical Sciences, University of Maryland, College Park, Maryland 20742, USA
| | - Kurt C Kersebaum
- Institute of Landscape Systems Analysis, Leibniz Centre for Agricultural Landscape Research, 15374 Müncheberg, Germany
| | - Ann-Kristin Koehler
- Institute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, Leeds LS29JT, UK
| | - Leilei Liu
- 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 Agricultural University, Nanjing, Jiangsu 210095, China
| | - Christoph Müller
- Potsdam Institute for Climate Impact Research, 14473 Potsdam, Germany
| | - Soora Naresh Kumar
- Centre for Environment Science and Climate Resilient Agriculture, Indian Agricultural Research Institute, IARI PUSA, New Delhi 110 012, India
| | - Claas Nendel
- Institute of Landscape Systems Analysis, Leibniz Centre for Agricultural Landscape Research, 15374 Müncheberg, Germany
| | - Garry O'Leary
- Department of Economic Development, Landscape &Water Sciences, Jobs, Transport and Resources, Horsham 3400, Australia
| | - Jørgen E Olesen
- Department of Agroecology, Aarhus University, 8830 Tjele, Denmark
| | - Taru Palosuo
- Natural Resources Institute Finland (Luke), Latokartanonkaari 9, 00790 Helsinki, Finland
| | - Eckart Priesack
- Helmholtz Zentrum München - German Research Center for Environmental Health, Institute of Biochemical Plant Pathology, Neuherberg, 85764, Germany
| | - Ehsan Eyshi Rezaei
- Institute of Crop Science and Resource Conservation (INRES), University of Bonn, 53115 Bonn, Germany
| | | | - Alex C Ruane
- NASA Goddard Institute for Space Studies, New York, New York 10025, USA
| | - Mikhail A Semenov
- Computational and Systems Biology Department, Rothamsted Research, Harpenden, Herts AL5 2JQ, UK
| | - Iurii Shcherbak
- Department of Earth and Environmental Sciences and W.K. Kellogg Biological Station, Michigan State University East Lansing, Michigan 48823, USA
| | - Claudio Stöckle
- Biological Systems Engineering, Washington State University, Pullman, Washington 99164-6120, USA
| | - Pierre Stratonovitch
- Computational and Systems Biology Department, Rothamsted Research, Harpenden, Herts AL5 2JQ, UK
| | - Thilo Streck
- Institute of Soil Science and Land Evaluation, University of Hohenheim, 70599 Stuttgart, Germany
| | - Iwan Supit
- PPS and WSG &CALM, Wageningen University, 6700AA Wageningen, The Netherlands
| | - Fulu Tao
- Natural Resources Institute Finland (Luke), Latokartanonkaari 9, 00790 Helsinki, Finland
- Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Science, Beijing 100101, China
| | - Peter Thorburn
- CSIRO Agriculture and Food, St Lucia, Queensland 4067, Australia
| | - Katharina Waha
- Potsdam Institute for Climate Impact Research, 14473 Potsdam, Germany
| | - Daniel Wallach
- INRA, UMR 1248 Agrosystèmes et développement territorial (AGIR), 31 326 Castanet-Tolosan, France
| | - Zhimin Wang
- College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
| | - Joost Wolf
- PPS and WSG &CALM, Wageningen University, 6700AA Wageningen, The Netherlands
| | - Yan Zhu
- 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 Agricultural University, Nanjing, Jiangsu 210095, China
| | - Senthold Asseng
- Agricultural and Biological Engineering Department, University of Florida, Gainesville, Florida 32611, USA
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26
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Ruane AC, McDermid SP. Selection of a representative subset of global climate models that captures the profile of regional changes for integrated climate impacts assessment. ACTA ACUST UNITED AC 2017. [DOI: 10.1186/s40322-017-0036-4] [Citation(s) in RCA: 62] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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27
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Fleisher DH, Condori B, Quiroz R, Alva A, Asseng S, Barreda C, Bindi M, Boote KJ, Ferrise R, Franke AC, Govindakrishnan PM, Harahagazwe D, Hoogenboom G, Naresh Kumar S, Merante P, Nendel C, Olesen JE, Parker PS, Raes D, Raymundo R, Ruane AC, Stockle C, Supit I, Vanuytrecht E, Wolf J, Woli P. A potato model intercomparison across varying climates and productivity levels. Glob Chang Biol 2017; 23:1258-1281. [PMID: 27387228 DOI: 10.1111/gcb.13411] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/03/2016] [Accepted: 06/19/2016] [Indexed: 05/22/2023]
Abstract
A potato crop multimodel assessment was conducted to quantify variation among models and evaluate responses to climate change. Nine modeling groups simulated agronomic and climatic responses at low-input (Chinoli, Bolivia and Gisozi, Burundi)- and high-input (Jyndevad, Denmark and Washington, United States) management sites. Two calibration stages were explored, partial (P1), where experimental dry matter data were not provided, and full (P2). The median model ensemble response outperformed any single model in terms of replicating observed yield across all locations. Uncertainty in simulated yield decreased from 38% to 20% between P1 and P2. Model uncertainty increased with interannual variability, and predictions for all agronomic variables were significantly different from one model to another (P < 0.001). Uncertainty averaged 15% higher for low- vs. high-input sites, with larger differences observed for evapotranspiration (ET), nitrogen uptake, and water use efficiency as compared to dry matter. A minimum of five partial, or three full, calibrated models was required for an ensemble approach to keep variability below that of common field variation. Model variation was not influenced by change in carbon dioxide (C), but increased as much as 41% and 23% for yield and ET, respectively, as temperature (T) or rainfall (W) moved away from historical levels. Increases in T accounted for the highest amount of uncertainty, suggesting that methods and parameters for T sensitivity represent a considerable unknown among models. Using median model ensemble values, yield increased on average 6% per 100-ppm C, declined 4.6% per °C, and declined 2% for every 10% decrease in rainfall (for nonirrigated sites). Differences in predictions due to model representation of light utilization were significant (P < 0.01). These are the first reported results quantifying uncertainty for tuber/root crops and suggest modeling assessments of climate change impact on potato may be improved using an ensemble approach.
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Affiliation(s)
- David H Fleisher
- Crop Systems and Global Change Laboratory, USDA-ARS, Beltsville, MD, USA
| | - Bruno Condori
- Crop Systems and Global Change Laboratory, USDA-ARS, Beltsville, MD, USA
| | - Roberto Quiroz
- Production Systems and the Environment, International Potato Center, Lima, Peru
| | - Ashok Alva
- Desert Agriculture and Ecosystem Program, Kuwait Institute for Scientific Research, Safat, Kuwait
| | - Senthold Asseng
- Agricultural & Biological Engineering Department, University of Florida, Gainesville, FL, USA
| | - Carolina Barreda
- Production Systems and the Environment, International Potato Center, Lima, Peru
| | - Marco Bindi
- Department of Agrifood Production and Environmental Sciences, University of Florence, Florence, Italy
| | - Kenneth J Boote
- Agricultural & Biological Engineering Department, University of Florida, Gainesville, FL, USA
| | - Roberto Ferrise
- Department of Agrifood Production and Environmental Sciences, University of Florence, Florence, Italy
| | - Angelinus C Franke
- Soil, Crop and Climate Sciences, University of the Free State, Bloemfontein, South Africa
| | | | - Dieudonne Harahagazwe
- Production Systems and the Environment, International Potato Center SSA, Nairobi, Kenya
| | - Gerrit Hoogenboom
- Agricultural & Biological Engineering Department, University of Florida, Gainesville, FL, USA
| | - Soora Naresh Kumar
- Centre for Environment Science and Climate Resilient Agriculture, Indian Agricultural Research Institute, New Delhi, India
| | - Paolo Merante
- Department of Agrifood Production and Environmental Sciences, University of Florence, Florence, Italy
| | - Claas Nendel
- Leibniz Centre for Agricultural Landscape Research, Institute of Landscape Systems Analysis, Müncheberg, Germany
| | - Jorgen E Olesen
- Department of Agroecology, Aarhus University, Tjele, Denmark
| | - Phillip S Parker
- Leibniz Centre for Agricultural Landscape Research, Institute of Landscape Systems Analysis, Müncheberg, Germany
| | - Dirk Raes
- Department of Earth and Environmental Sciences, KU Leuven University, Leuven, Belgium
| | - Rubi Raymundo
- Agricultural & Biological Engineering Department, University of Florida, Gainesville, FL, USA
| | - Alex C Ruane
- NASA Goddard Institute for Space Studies, New York, NY, USA
| | - Claudio Stockle
- Biological Systems Engineering, Washington State University, Pullman, WA, USA
| | - Iwan Supit
- Earth System Science and Climate Adaptive Land Management, Wageningen University and Research Center, Wageningen, The Netherlands
| | - Eline Vanuytrecht
- Department of Earth and Environmental Sciences, KU Leuven University, Leuven, Belgium
| | - Joost Wolf
- Plant Production Systems, Wageningen University and Research Center, Wageningen, The Netherlands
| | - Prem Woli
- AgWeatherNet Program, Washington State University, Pullman, WA, USA
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Glotter MJ, Moyer EJ, Ruane AC, Elliott JW. Evaluating the sensitivity of agricultural model performance to different climate inputs. J Appl Meteorol Climatol 2016; 55:579-594. [PMID: 29097985 PMCID: PMC5662947 DOI: 10.1175/jamc-d-15-0120.1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Projections of future food production necessarily rely on models, which must themselves be validated through historical assessments comparing modeled to observed yields. Reliable historical validation requires both accurate agricultural models and accurate climate inputs. Problems with either may compromise the validation exercise. Previous studies have compared the effects of different climate inputs on agricultural projections, but either incompletely or without a ground truth of observed yields that would allow distinguishing errors due to climate inputs from those intrinsic to the crop model. This study is a systematic evaluation of the reliability of a widely-used crop model for simulating U.S. maize yields when driven by multiple observational data products. The parallelized Decision Support System for Agrotechnology Transfer (pDSSAT) is driven with climate inputs from multiple sources - reanalysis, reanalysis bias-corrected with observed climate, and a control dataset - and compared to observed historical yields. The simulations show that model output is more accurate when driven by any observation-based precipitation product than when driven by un-bias-corrected reanalysis. The simulations also suggest, in contrast to previous studies, that biased precipitation distribution is significant for yields only in arid regions. However, some issues persist for all choices of climate inputs: crop yields appear oversensitive to precipitation fluctuations but undersensitive to floods and heat waves. These results suggest that the most important issue for agricultural projections may be not climate inputs but structural limitations in the crop models themselves.
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Affiliation(s)
- Michael J. Glotter
- Corresponding author address: Michael J. Glotter, Department of the Geophysical Sciences, University of Chicago, 5734 S Ellis Ave, Chicago, IL 60637.
| | - Elisabeth J. Moyer
- Department of the Geophysical Sciences, University of Chicago, Chicago, Illinois
| | - Alex C. Ruane
- NASA Goddard Institute for Space Studies, New York, New York
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Wallach D, Mearns LO, Ruane AC, Rötter RP, Asseng S. Lessons from climate modeling on the design and use of ensembles for crop modeling. Clim Change 2016; 139:551-564. [PMID: 32355375 PMCID: PMC7175712 DOI: 10.1007/s10584-016-1803-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2016] [Accepted: 08/31/2016] [Indexed: 05/02/2023]
Abstract
Working with ensembles of crop models is a recent but important development in crop modeling which promises to lead to better uncertainty estimates for model projections and predictions, better predictions using the ensemble mean or median, and closer collaboration within the modeling community. There are numerous open questions about the best way to create and analyze such ensembles. Much can be learned from the field of climate modeling, given its much longer experience with ensembles. We draw on that experience to identify questions and make propositions that should help make ensemble modeling with crop models more rigorous and informative. The propositions include defining criteria for acceptance of models in a crop MME, exploring criteria for evaluating the degree of relatedness of models in a MME, studying the effect of number of models in the ensemble, development of a statistical model of model sampling, creation of a repository for MME results, studies of possible differential weighting of models in an ensemble, creation of single model ensembles based on sampling from the uncertainty distribution of parameter values or inputs specifically oriented toward uncertainty estimation, the creation of super ensembles that sample more than one source of uncertainty, the analysis of super ensemble results to obtain information on total uncertainty and the separate contributions of different sources of uncertainty and finally further investigation of the use of the multi-model mean or median as a predictor.
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Affiliation(s)
| | | | - Alex C. Ruane
- National Aeronautics and Space Agency Goddard Institute for Space Studies, New York, NY USA
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30
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Li T, Hasegawa T, Yin X, Zhu Y, Boote K, Adam M, Bregaglio S, Buis S, Confalonieri R, Fumoto T, Gaydon D, Marcaida M, Nakagawa H, Oriol P, Ruane AC, Ruget F, Singh B, Singh U, Tang L, Tao F, Wilkens P, Yoshida H, Zhang Z, Bouman B. Uncertainties in predicting rice yield by current crop models under a wide range of climatic conditions. Glob Chang Biol 2015; 21:1328-41. [PMID: 25294087 DOI: 10.1111/gcb.12758] [Citation(s) in RCA: 109] [Impact Index Per Article: 12.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2014] [Revised: 09/11/2014] [Accepted: 09/12/2014] [Indexed: 05/18/2023]
Abstract
Predicting rice (Oryza sativa) productivity under future climates is important for global food security. Ecophysiological crop models in combination with climate model outputs are commonly used in yield prediction, but uncertainties associated with crop models remain largely unquantified. We evaluated 13 rice models against multi-year experimental yield data at four sites with diverse climatic conditions in Asia and examined whether different modeling approaches on major physiological processes attribute to the uncertainties of prediction to field measured yields and to the uncertainties of sensitivity to changes in temperature and CO2 concentration [CO2 ]. We also examined whether a use of an ensemble of crop models can reduce the uncertainties. Individual models did not consistently reproduce both experimental and regional yields well, and uncertainty was larger at the warmest and coolest sites. The variation in yield projections was larger among crop models than variation resulting from 16 global climate model-based scenarios. However, the mean of predictions of all crop models reproduced experimental data, with an uncertainty of less than 10% of measured yields. Using an ensemble of eight models calibrated only for phenology or five models calibrated in detail resulted in the uncertainty equivalent to that of the measured yield in well-controlled agronomic field experiments. Sensitivity analysis indicates the necessity to improve the accuracy in predicting both biomass and harvest index in response to increasing [CO2 ] and temperature.
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Affiliation(s)
- Tao Li
- International Rice Research Institute, Los Baños, Philippines
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31
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Martre P, Wallach D, Asseng S, Ewert F, Jones JW, Rötter RP, Boote KJ, Ruane AC, Thorburn PJ, Cammarano D, Hatfield JL, Rosenzweig C, Aggarwal PK, Angulo C, Basso B, Bertuzzi P, Biernath C, Brisson N, Challinor AJ, Doltra J, Gayler S, Goldberg R, Grant RF, Heng L, Hooker J, Hunt LA, Ingwersen J, Izaurralde RC, Kersebaum KC, Müller C, Kumar SN, Nendel C, O'leary G, Olesen JE, Osborne TM, Palosuo T, Priesack E, Ripoche D, Semenov MA, Shcherbak I, Steduto P, Stöckle CO, Stratonovitch P, Streck T, Supit I, Tao F, Travasso M, Waha K, White JW, Wolf J. Multimodel ensembles of wheat growth: many models are better than one. Glob Chang Biol 2015; 21:911-25. [PMID: 25330243 DOI: 10.1111/gcb.12768] [Citation(s) in RCA: 50] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/28/2014] [Revised: 08/07/2014] [Accepted: 09/25/2014] [Indexed: 05/18/2023]
Abstract
Crop models of crop growth are increasingly used to quantify the impact of global changes due to climate or crop management. Therefore, accuracy of simulation results is a major concern. Studies with ensembles of crop models can give valuable information about model accuracy and uncertainty, but such studies are difficult to organize and have only recently begun. We report on the largest ensemble study to date, of 27 wheat models tested in four contrasting locations for their accuracy in simulating multiple crop growth and yield variables. The relative error averaged over models was 24-38% for the different end-of-season variables including grain yield (GY) and grain protein concentration (GPC). There was little relation between error of a model for GY or GPC and error for in-season variables. Thus, most models did not arrive at accurate simulations of GY and GPC by accurately simulating preceding growth dynamics. Ensemble simulations, taking either the mean (e-mean) or median (e-median) of simulated values, gave better estimates than any individual model when all variables were considered. Compared to individual models, e-median ranked first in simulating measured GY and third in GPC. The error of e-mean and e-median declined with an increasing number of ensemble members, with little decrease beyond 10 models. We conclude that multimodel ensembles can be used to create new estimators with improved accuracy and consistency in simulating growth dynamics. We argue that these results are applicable to other crop species, and hypothesize that they apply more generally to ecological system models.
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Affiliation(s)
- Pierre Martre
- INRA, UMR1095 Genetics, Diversity and Ecophysiology of Cereals (GDEC), 5 chemin de Beaulieu, F-63 100, Clermont-Ferrand, France; Blaise Pascal University, UMR1095 GDEC, F-63 170, Aubière, France
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Bassu S, Brisson N, Durand JL, Boote K, Lizaso J, Jones JW, Rosenzweig C, Ruane AC, Adam M, Baron C, Basso B, Biernath C, Boogaard H, Conijn S, Corbeels M, Deryng D, De Sanctis G, Gayler S, Grassini P, Hatfield J, Hoek S, Izaurralde C, Jongschaap R, Kemanian AR, Kersebaum KC, Kim SH, Kumar NS, Makowski D, Müller C, Nendel C, Priesack E, Pravia MV, Sau F, Shcherbak I, Tao F, Teixeira E, Timlin D, Waha K. How do various maize crop models vary in their responses to climate change factors? Glob Chang Biol 2014; 20:2301-20. [PMID: 24395589 DOI: 10.1111/gcb.12520] [Citation(s) in RCA: 149] [Impact Index Per Article: 14.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/07/2013] [Accepted: 12/02/2013] [Indexed: 05/18/2023]
Abstract
Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2 ], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data for calibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly -0.5 Mg ha(-1) per °C. Doubling [CO2 ] from 360 to 720 μmol mol(-1) increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2 ] among models. Model responses to temperature and [CO2 ] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information.
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Affiliation(s)
- Simona Bassu
- Unité d'Agronomie, INRA-AgroParisTech, BP 01, Thiverval-Grignon, 78850, France
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33
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Ruane AC, McDermid S, Rosenzweig C, Baigorria GA, Jones JW, Romero CC, Dewayne Cecil L. Carbon-temperature-water change analysis for peanut production under climate change: a prototype for the AgMIP coordinated climate-crop modeling project (C3MP). Glob Chang Biol 2014; 20:394-407. [PMID: 24115520 DOI: 10.1111/gcb.12412] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/23/2013] [Revised: 08/16/2013] [Accepted: 09/09/2013] [Indexed: 06/02/2023]
Abstract
Climate change is projected to push the limits of cropping systems and has the potential to disrupt the agricultural sector from local to global scales. This article introduces the Coordinated Climate-Crop Modeling Project (C3MP), an initiative of the Agricultural Model Intercomparison and Improvement Project (AgMIP) to engage a global network of crop modelers to explore the impacts of climate change via an investigation of crop responses to changes in carbon dioxide concentration ([CO2 ]), temperature, and water. As a demonstration of the C3MP protocols and enabled analyses, we apply the Decision Support System for Agrotechnology Transfer (DSSAT) CROPGRO-Peanut crop model for Henry County, Alabama, to evaluate responses to the range of plausible [CO2 ], temperature changes, and precipitation changes projected by climate models out to the end of the 21st century. These sensitivity tests are used to derive crop model emulators that estimate changes in mean yield and the coefficient of variation for seasonal yields across a broad range of climate conditions, reproducing mean yields from sensitivity test simulations with deviations of ca. 2% for rain-fed conditions. We apply these statistical emulators to investigate how peanuts respond to projections from various global climate models, time periods, and emissions scenarios, finding a robust projection of modest (<10%) median yield losses in the middle of the 21st century accelerating to more severe (>20%) losses and larger uncertainty at the end of the century under the more severe representative concentration pathway (RCP8.5). This projection is not substantially altered by the selection of the AgMERRA global gridded climate dataset rather than the local historical observations, differences between the Third and Fifth Coupled Model Intercomparison Project (CMIP3 and CMIP5), or the use of the delta method of climate impacts analysis rather than the C3MP impacts response surface and emulator approach.
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Affiliation(s)
- Alex C Ruane
- Climate Impacts Group, NASA Goddard Institute for Space Studies, New York, NY, USA
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Estes LD, Beukes H, Bradley BA, Debats SR, Oppenheimer M, Ruane AC, Schulze R, Tadross M. Projected climate impacts to South African maize and wheat production in 2055: a comparison of empirical and mechanistic modeling approaches. Glob Chang Biol 2013; 19:3762-3774. [PMID: 23864352 DOI: 10.1111/gcb.12325] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/26/2012] [Revised: 06/28/2013] [Accepted: 06/28/2013] [Indexed: 06/02/2023]
Abstract
Crop model-specific biases are a key uncertainty affecting our understanding of climate change impacts to agriculture. There is increasing research focus on intermodel variation, but comparisons between mechanistic (MMs) and empirical models (EMs) are rare despite both being used widely in this field. We combined MMs and EMs to project future (2055) changes in the potential distribution (suitability) and productivity of maize and spring wheat in South Africa under 18 downscaled climate scenarios (9 models run under 2 emissions scenarios). EMs projected larger yield losses or smaller gains than MMs. The EMs' median-projected maize and wheat yield changes were -3.6% and 6.2%, respectively, compared to 6.5% and 15.2% for the MM. The EM projected a 10% reduction in the potential maize growing area, where the MM projected a 9% gain. Both models showed increases in the potential spring wheat production region (EM = 48%, MM = 20%), but these results were more equivocal because both models (particularly the EM) substantially overestimated the extent of current suitability. The substantial water-use efficiency gains simulated by the MMs under elevated CO2 accounted for much of the EM-MM difference, but EMs may have more accurately represented crop temperature sensitivities. Our results align with earlier studies showing that EMs may show larger climate change losses than MMs. Crop forecasting efforts should expand to include EM-MM comparisons to provide a fuller picture of crop-climate response uncertainties.
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Affiliation(s)
- Lyndon D Estes
- Program in Science, Technology, and Environmental Policy, Woodrow Wilson School, Princeton University, Princeton, NJ, 08544, USA; Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ, 08544, USA
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