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How accurately do maize crop models simulate the interactions of atmospheric CO2 concentration levels with limited water supply on water use and yield?

Durand Jean-Louis, Delusca Kenel, Boote Ken, Lizaso Jon, Manderscheid Remy, Weigel Hans Johachim, Ruane Alex C., Rosenzweig Cynthia, Jones Jim, Ahuja Lajpat R., Anapalli Saseendran S., Basso Bruno, Baron Christian, Bertuzzi Patrick, Biernath Christian, Deryng Delphine, Ewert Franck, Gaiser Thomas, Gayler Sebastian, Heinlein Florian, Kersebaum Kurt Christian, Kim Soo-Hyung, Müller Christoph, Nendel Claas, Olioso Albert, Priesack Eckart, Ramirez Villegas Julian, Ripoche Dominique, Rötter Reimund P., Seidel Sabine I., Srivastava Amit Kumar, Tao Fulu, Timlin Dennis, Twine Tracy E., Wang Enli, Webber Heidi, Zhao Zhigan. 2017. How accurately do maize crop models simulate the interactions of atmospheric CO2 concentration levels with limited water supply on water use and yield?. European Journal of Agronomy, 100 : 67-75.

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Quartile : Q1, Sujet : AGRONOMY

Résumé : This study assesses the ability of 21 crop models to capture the impact of elevated CO2 concentration ([CO2]) on maize yield and water use as measured in a 2-year Free Air Carbon dioxide Enrichment experiment conducted at the Thünen Institute in Braunschweig, Germany (Manderscheid et al., 2014). Data for ambient [CO2] and irrigated treatments were provided to the 21 models for calibrating plant traits, including weather, soil and management data as well as yield, grain number, above ground biomass, leaf area index, nitrogen concentration in biomass and grain, water use and soil water content. Models differed in their representation of carbon assimilation and evapotranspiration processes. The models reproduced the absence of yield response to elevated [CO2] under well-watered conditions, as well as the impact of water deficit at ambient [CO2], with 50% of models within a range of +/−1 Mg ha−1 around the mean. The bias of the median of the 21 models was less than 1 Mg ha−1. However under water deficit in one of the two years, the models captured only 30% of the exceptionally high [CO2] enhancement on yield observed. Furthermore the ensemble of models was unable to simulate the very low soil water content at anthesis and the increase of soil water and grain number brought about by the elevated [CO2] under dry conditions. Overall, we found models with explicit stomatal control on transpiration tended to perform better. Our results highlight the need for model improvement with respect to simulating transpirational water use and its impact on water status during the kernel-set phase.

Mots-clés Agrovoc : modèle de simulation, Zea mays, dioxyde de carbone, photosynthèse, évapotranspiration, rendement des cultures

Mots-clés géographiques Agrovoc : Allemagne

Mots-clés libres : Maize, CO2, Multi model, Crop model

Classification Agris : U10 - Informatique, mathématiques et statistiques
F61 - Physiologie végétale - Nutrition

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

Auteurs et affiliations

  • Durand Jean-Louis, INRA (FRA) - auteur correspondant
  • Delusca Kenel, INRA (FRA)
  • Boote Ken, University of Florida (USA)
  • Lizaso Jon, UPM (ESP)
  • Manderscheid Remy, Johann Heinrich von Thunen-Institut (DEU)
  • Weigel Hans Johachim, Johann Heinrich von Thunen-Institut (DEU)
  • Ruane Alex C., NASA (USA)
  • Rosenzweig Cynthia, NASA (USA)
  • Jones Jim, University of Florida (USA)
  • Ahuja Lajpat R., USDA (USA)
  • Anapalli Saseendran S., USDA (FRA)
  • Basso Bruno, MSU (USA)
  • Baron Christian, CIRAD-ES-UMR TETIS (FRA)
  • Bertuzzi Patrick, INRA (FRA)
  • Biernath Christian, Helmholtz Zentrum München (DEU)
  • Deryng Delphine, University of Chicago (USA)
  • Ewert Franck, Universität Bonn (DEU)
  • Gaiser Thomas, Universität Bonn (DEU)
  • Gayler Sebastian, Universität Hohenheim (DEU)
  • Heinlein Florian, Institute of Biochemical Plant Pathology (DEU)
  • Kersebaum Kurt Christian, Institute of Landscape Systems Analysis (DEU)
  • Kim Soo-Hyung, University of Washington (USA)
  • Müller Christoph, Potsdam Institute for Climate Impact Research (DEU)
  • Nendel Claas, Institute of Landscape Systems Analysis (DEU)
  • Olioso Albert, INRA (FRA)
  • Priesack Eckart, Institute of Biochemical Plant Pathology (DEU)
  • Ramirez Villegas Julian, University of Leeds (GBR)
  • Ripoche Dominique, INRA (FRA)
  • Rötter Reimund P., NRI (FIN)
  • Seidel Sabine I., Universität Bonn (DEU)
  • Srivastava Amit Kumar, Universität Bonn (DEU)
  • Tao Fulu, CAS (CHN)
  • Timlin Dennis, USDA (USA)
  • Twine Tracy E., University of Minnesota (USA)
  • Wang Enli, CSIRO (AUS)
  • Webber Heidi, Universität Bonn (DEU)
  • Zhao Zhigan, CAU [China Agricultural University] (CHN)

Source : Cirad-Agritrop (https://agritrop.cirad.fr/592868/)

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