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

Makowski David, Asseng Senthold, Ewert Franck, Bassu Simona, Durand Jean-Louis, Li Tao, Martre Pierre, Adam Myriam, Aggarwal P.K., Angulo C., Baron Christian, Basso Bruno, Bertuzzi Patrick, Biernath Christian, Boogaard Hendrik, Boote Kenneth J., Bouman Bas, Bregaglio Simone, Brisson Nadine, Buis Samuel, Cammarano Davide, Challinor Andrew J., Confalonieri Roberto, Conijn J.G., Corbeels Marc, Deryng Delphine, De Sanctis Giacomo, Doltra J., Fumoto Tamon, Gaydon Donald, Gayler Sebastian, Goldberg Richard, Grant R.F., Grassini Patricio, Hatfield Jerry L., Hasegawa Toshihiro, Heng L., Hoek Steven B., Hooker J., Hunt L.A., Ingwersen J., Izaurralde Cesar, Jongschaap R.E.E., Jones James W., Kemanian R.A., Kersebaum Kurt Christian, Kim S.H., Lizaso Jon, Marcaida Manuel, Müller C., Nakagawa Hitochi, Kumar Naresh S., Nendel Claas, O'Leary G.J., Olesen Jørgen E., Oriol Philippe, Osborne T.M., Palosuo Taru, Pravia Maria Virginia, Priesack Eckart, Ripoche Dominique, Rosenzweig Cynthia, Ruane Alex C., Ruget Françoise, Sau Federico, Semenov M.A., Shcherbak Iurii, Singh Balwinder, Singh Upendra, Soo H.K., Steduto P., Stöckle Claudio, Stratonovitch P., Streck T., Supit Iwan, Tang Liang, Tao F., Teixeira Edmar, Thorburn Peter J., Timlin Dennis, Travasso M., Rötter Reimund P., Waha Katharina, Wallach Daniel, White Jeffrey W., Wilkens Paul, Williams Jimmy R., Wolf Joost, Yin Xinyou, Yoshida Hiroe, Zhang Zhao, Zhu Yan. 2015. A statistical analysis of three ensembles of crop model responses to temperature and CO2 concentration. Agricultural and Forest Meteorology, 214-215 : pp. 483-493.

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Quartile : Outlier, Sujet : FORESTRY / Quartile : Outlier, Sujet : AGRONOMY / Quartile : Q1, Sujet : METEOROLOGY & ATMOSPHERIC SCIENCES

Abstract : Ensembles of process-based crop models are increasingly used to simulate crop growth for scenarios of temperature and/or precipitation changes corresponding to different projections of atmospheric CO2 concentrations. This approach generates large datasets with thousands of simulated crop yield data. Such datasets potentially provide new information but it is difficult to summarize them in a useful way due to their structural complexities. An associated issue is that it is not straightforward to compare crops and to interpolate the results to alternative climate scenarios not initially included in the simulation protocols. Here we demonstrate that statistical models based on random-coefficient regressions are able to emulate ensembles of process-based crop models. An important advantage of the proposed statistical models is that they can interpolate between temperature levels and between CO2 concentration levels, and can thus be used to calculate temperature and [CO2] thresholds leading to yield loss or yield gain, without re-running the original complex crop models. Our approach is illustrated with three yield datasets simulated by 19 maize models, 26 wheat models, and 13 rice models. Several statistical models are fitted to these datasets, and are then used to analyze the variability of the yield response to [CO2] and temperature. Based on our results, we show that, for wheat, a [CO2] increase is likely to outweigh the negative effect of a temperature increase of +2 °C in the considered sites. Compared to wheat, required levels of [CO2] increase are much higher for maize, and intermediate for rice. For all crops, uncertainties in simulating climate change impacts increase more with temperature than with elevated [CO2].

Mots-clés Agrovoc : Plante de culture, Modélisation des cultures, Modèle mathématique, Croissance, Température, Dioxyde de carbone, Air, Atmosphère, Changement climatique, Rendement des cultures, Zea mays, Oryza sativa, Triticum

Mots-clés géographiques Agrovoc : France, Brésil, République-Unie de Tanzanie, États-Unis, Pays-Bas, Argentine, Inde, Australie, Philippines, Chine, Japon

Classification Agris : F62 - Plant physiology - Growth and development
P40 - Meteorology and climatology

Champ stratégique Cirad : Axe 1 (2014-2018) - Agriculture écologiquement intensive

Auteurs et affiliations

  • Makowski David, INRA (FRA)
  • Asseng Senthold, University of Florida (USA)
  • Ewert Franck, Universität Bonn (DEU)
  • Bassu Simona, INRA (FRA)
  • Durand Jean-Louis, INRA (FRA)
  • Li Tao, IRRI (PHL)
  • Martre Pierre, INRA (FRA)
  • Adam Myriam, CIRAD-BIOS-UMR AGAP (BFA) ORCID: 0000-0002-8873-6762
  • Aggarwal P.K., IWMI (IND)
  • Angulo C., Universität Bonn (DEU)
  • Baron Christian, CIRAD-ES-UMR TETIS (FRA)
  • Basso Bruno, MSU (USA)
  • Bertuzzi Patrick, INRA (FRA)
  • Biernath Christian, Helmholtz Zentrum München (DEU)
  • Boogaard Hendrik, Alterra (NLD)
  • Boote Kenneth J., University of Florida (USA)
  • Bouman Bas, IRRI (PHL)
  • Bregaglio Simone, University of Milan (ITA)
  • Brisson Nadine, INRA (FRA)
  • Buis Samuel, INRA (FRA)
  • Cammarano Davide, James Hutton Institute (GBR)
  • Challinor Andrew J., University of Leeds (GBR)
  • Confalonieri Roberto, University of Milan (ITA)
  • Conijn J.G., Wageningen University and Research Centre (NLD)
  • Deryng Delphine, University of East Anglia (GBR)
  • De Sanctis Giacomo, European Commission Directorate General Joint Research Centre (ITA)
  • Doltra J., CIFA [Centro de Investigacion y Formacion Agraria] (ESP)
  • Fumoto Tamon, NIAES (JPN)
  • Gaydon Donald, CSIRO (AUS)
  • Gayler Sebastian, WESS (DEU)
  • Goldberg Richard, NASA (USA)
  • Grant R.F., University of Alberta (CAN)
  • Grassini Patricio, University of Nebraska (USA)
  • Hatfield Jerry L., USDA (USA)
  • Hasegawa Toshihiro, NIAES (JPN)
  • Heng L., IAEA (AUT)
  • Hoek Steven B., Alterra (NLD)
  • Hooker J., University of Reading (GBR)
  • Hunt L.A., University of Guelph (CAN)
  • Ingwersen J., Universitaet Hohenheim (DEU)
  • Izaurralde Cesar, University of Maryland (USA)
  • Jongschaap R.E.E., EMBRAPA (BRA)
  • Jones James W., University of Florida (USA)
  • Kemanian R.A., INIA (URY)
  • Kersebaum Kurt Christian, Leibniz Centre for Agricultural Landscape Research (DEU)
  • Kim S.H., University of Washington (USA)
  • Lizaso Jon, Universidad Politecnica de Madrid (ESP)
  • Marcaida Manuel, IRRI (PHL)
  • Müller C., Potsdam Institute for Climate Impact Research (DEU)
  • Nakagawa Hitochi, NARO (JPN)
  • Kumar Naresh S., IARI (IND)
  • Nendel Claas, Leibniz Centre for Agricultural Landscape Research (DEU)
  • O'Leary G.J., Grains Innovation Park (AUS)
  • Olesen Jørgen E., Aarhus University (DNK)
  • Oriol Philippe, CIRAD-BIOS-UMR AGAP (FRA)
  • Osborne T.M., University of Reading (GBR)
  • Palosuo Taru, Natural Resources Institute Finland (FIN)
  • Pravia Maria Virginia, University Park (USA)
  • Priesack Eckart, Institute of Soil Ecology (GBR)
  • Ripoche Dominique, INRA (FRA)
  • Rosenzweig Cynthia, NASA (USA)
  • Ruane Alex C., NASA (USA)
  • Ruget Françoise, INRA (FRA)
  • Sau Federico, Universidad Politecnica de Madrid (ESP)
  • Semenov M.A., Rothamsted Research (GBR)
  • Shcherbak Iurii, MSU (USA)
  • Singh Balwinder, CIMMYT (IND)
  • Singh Upendra, IFDC (USA)
  • Soo H.K., University of Washington (USA)
  • Steduto P., FAO (ITA)
  • Stöckle Claudio, Washington State University (USA)
  • Stratonovitch P., Rothamsted Research (GBR)
  • Streck T., Universitaet Hohenheim (DEU)
  • Supit Iwan, Wageningen University (NLD)
  • Tang Liang, National Engineering and Technology Center for Information Agriculture (CHN)
  • Tao F., Natural Resources Institute Finland (FIN)
  • Teixeira Edmar, New Zealand Institute for Plant and Food Research (NZL)
  • Thorburn Peter J., CSIRO (AUS)
  • Timlin Dennis, USDA (USA)
  • Travasso M., INTA (ARG)
  • Rötter Reimund P., NRI (FIN)
  • Waha Katharina, Potsdam Institute for Climate Impact Research (DEU)
  • Wallach Daniel, INRA (FRA)
  • White Jeffrey W., Arid-Land Agricultural Research Center (USA)
  • Wilkens Paul, IFDC (USA)
  • Williams Jimmy R., Texas A & M University (USA)
  • Wolf Joost, Wageningen Agricultural University (NLD)
  • Yin Xinyou, Centre for Crop Systems Analysis (NLD)
  • Yoshida Hiroe, NARO (JPN)
  • Zhang Zhao, Beijing Normal University (CHN)
  • Zhu Yan, National Engineering and Technology Center for Information Agriculture (CHN)

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