How do various maize crop models vary in their responses to climate change factors?

Bassu Simona, Brisson Nadine, Durand Jean-Louis, Boote Kenneth J., Lizaso Jon, Jones James W., Rosenzweig Cynthia, Ruane Alex C., Adam Myriam, Baron Christian, Basso Bruno, Biernath Christian, Boogaard Hendrik, Conjin Sjaak, Corbeels Marc, Deryng Delphine, De Sanctis Giacomo, Gayler Sebastian, Grassini Patricio, Hatfield Jerry L., Hoek Steven B., Izaurralde Cesar, Jongschaap Raymond, Kemanian Armen, Kersebaum Kurt Christian, Kim Soo-Hyung, Kumar Naresh S., Makowski David, Müller Christoph, Nendel Claas, Priesack Eckart, Pravia Maria Virginia, Sau Federico, Shcherbak Iurii, Tao Fulu, Teixeira Edmar, Timlin Dennis, Waha Katharina. 2014. How do various maize crop models vary in their responses to climate change factors?. Global Change Biology, 20 (7) : pp. 2301-2320.

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Quartile : Outlier, Sujet : ENVIRONMENTAL SCIENCES / Quartile : Outlier, Sujet : BIODIVERSITY CONSERVATION / Quartile : Outlier, Sujet : ECOLOGY

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 ?mol 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. (Résumé d'auteur)

Mots-clés Agrovoc : Zea mays, Rendement des cultures, Changement climatique, Modèle de simulation, Modélisation des cultures, Dioxyde de carbone, Température, Modèle mathématique

Mots-clés géographiques Agrovoc : France, Iowa, Brésil, République-Unie de Tanzanie

Classification Agris : P40 - Meteorology and climatology
U10 - Computer science, mathematics and statistics
F01 - Crops

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

Auteurs et affiliations

  • Bassu Simona, INRA (FRA)
  • Brisson Nadine, INRA (FRA)
  • Durand Jean-Louis, INRA (FRA)
  • Boote Kenneth J., University of Florida (USA)
  • Lizaso Jon, Universidad Politecnica de Madrid (ESP)
  • Jones James W., University of Florida (USA)
  • Rosenzweig Cynthia, NASA (USA)
  • Ruane Alex C., NASA (USA)
  • Adam Myriam, CIRAD-BIOS-UMR AGAP (BFA) ORCID: 0000-0002-8873-6762
  • Baron Christian, CIRAD-ES-UMR TETIS (FRA)
  • Basso Bruno, MSU (USA)
  • Biernath Christian, Institut für Bodenökologie (FRA)
  • Boogaard Hendrik, Alterra (NLD)
  • Conjin Sjaak, Wageningen University and Research Centre (NLD)
  • Deryng Delphine, University of East Anglia (GBR)
  • De Sanctis Giacomo, INRA (FRA)
  • Gayler Sebastian, WESS (DEU)
  • Grassini Patricio, University of Nebraska (USA)
  • Hatfield Jerry L., USDA (USA)
  • Hoek Steven B., Alterra (NLD)
  • Izaurralde Cesar, University of Maryland (USA)
  • Jongschaap Raymond, Wageningen University and Research Centre (NLD)
  • Kemanian Armen, University Park (USA)
  • Kersebaum Kurt Christian, Institute of Landscape Systems Analysis (DEU)
  • Kim Soo-Hyung, University of Washington (USA)
  • Kumar Naresh S., IARI (IND)
  • Makowski David, INRA (FRA)
  • Müller Christoph, Potsdam Institute for Climate Impact Research (DEU)
  • Nendel Claas, Institute of Landscape Systems Analysis (DEU)
  • Priesack Eckart, Institut für Bodenökologie (DEU)
  • Pravia Maria Virginia, University Park (USA)
  • Sau Federico, Universidad Politecnica de Madrid (ESP)
  • Shcherbak Iurii, MSU (USA)
  • Tao Fulu, Chinese Academy of Sciences (CHN)
  • Teixeira Edmar, New Zealand Institute for Plant and Food Research (NZL)
  • Timlin Dennis, USDA (USA)
  • Waha Katharina, IARI (IND)

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