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 Oñate, Jon Iñaqui; Jones, J.W.; Rosenzweig, Cynthia; Ruane, Alex C.; Adam, Myriam; Baron, Christian; Basso, Bruno; Biernath, Christian; Boogaard, Hendrik; Conijn, Sjaak; Corbeels, Marc; Deryng, Delphine; Sanctis, Giacomo de; Gayler, Sebastian; Grassini, Patricio; Hatfield, Jerry; Hoek, Steven; Izarurralde, César; Jongschaap, Raymond; Kemanian, Armen R.; Kersabaum, K. Christian; Kim, Soo-Hyung; Kumar, Naresh S.; Makowski, David; Müller, Christoph; Nendel, Claas; Priesack, Eckart; Pravia, Maria Virginia; Sau Sau, Federico; Shcherbak, Iurii; Tao, Fulu; Texeira, Edmar; Timlin, Dennis y Waha, Katharina (2013). How do various maize crop models vary in their responses to climate change factors?. "Global Change Biology", v. 20 (n. 7); pp. 2301-2320. ISSN 1354-1013.


Título: 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 Oñate, Jon Iñaqui
  • Jones, J.W.
  • Rosenzweig, Cynthia
  • Ruane, Alex C.
  • Adam, Myriam
  • Baron, Christian
  • Basso, Bruno
  • Biernath, Christian
  • Boogaard, Hendrik
  • Conijn, Sjaak
  • Corbeels, Marc
  • Deryng, Delphine
  • Sanctis, Giacomo de
  • Gayler, Sebastian
  • Grassini, Patricio
  • Hatfield, Jerry
  • Hoek, Steven
  • Izarurralde, César
  • Jongschaap, Raymond
  • Kemanian, Armen R.
  • Kersabaum, K. Christian
  • Kim, Soo-Hyung
  • Kumar, Naresh S.
  • Makowski, David
  • Müller, Christoph
  • Nendel, Claas
  • Priesack, Eckart
  • Pravia, Maria Virginia
  • Sau Sau, Federico
  • Shcherbak, Iurii
  • Tao, Fulu
  • Texeira, Edmar
  • Timlin, Dennis
  • Waha, Katharina
Tipo de Documento: Artículo
Título de Revista/Publicación: Global Change Biology
Fecha: Julio 2013
Volumen: 20
Escuela: E.T.S.I. Agrónomos (UPM) [antigua denominación]
Departamento: Otro
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Comments This article is a U.S. government work, and is not subject to copyright in the United States. 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 lmol 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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ID de Registro: 31081
Identificador DC:
Identificador OAI:
Identificador DOI: 10.1111/gcb.12520
URL Oficial:
Depositado por: Memoria Investigacion
Depositado el: 08 Oct 2014 16:46
Ultima Modificación: 21 Jun 2016 08:26
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