Literature DB >> 24395589

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

Simona Bassu1, Nadine Brisson, Jean-Louis Durand, Kenneth Boote, Jon Lizaso, James W Jones, Cynthia Rosenzweig, Alex C Ruane, Myriam Adam, Christian Baron, Bruno Basso, Christian Biernath, Hendrik Boogaard, Sjaak Conijn, Marc Corbeels, Delphine Deryng, Giacomo De Sanctis, Sebastian Gayler, Patricio Grassini, Jerry Hatfield, Steven Hoek, Cesar Izaurralde, Raymond Jongschaap, Armen R Kemanian, K Christian Kersebaum, Soo-Hyung Kim, Naresh S Kumar, David Makowski, Christoph Müller, Claas Nendel, Eckart Priesack, Maria Virginia Pravia, Federico Sau, Iurii Shcherbak, Fulu Tao, Edmar Teixeira, Dennis Timlin, Katharina Waha.   

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.
© 2014 John Wiley & Sons Ltd.

Entities:  

Keywords:  AgMIP; [CO2]; climate; maize; model intercomparison; simulation; temperature; uncertainty

Mesh:

Substances:

Year:  2014        PMID: 24395589     DOI: 10.1111/gcb.12520

Source DB:  PubMed          Journal:  Glob Chang Biol        ISSN: 1354-1013            Impact factor:   10.863


  44 in total

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6.  Climate Change as Migration Driver from Rural and Urban Mexico.

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Journal:  Earths Future       Date:  2017-05-17       Impact factor: 7.495

9.  Temperature increase reduces global yields of major crops in four independent estimates.

Authors:  Chuang Zhao; Bing Liu; Shilong Piao; Xuhui Wang; David B Lobell; Yao Huang; Mengtian Huang; Yitong Yao; Simona Bassu; Philippe Ciais; Jean-Louis Durand; Joshua Elliott; Frank Ewert; Ivan A Janssens; Tao Li; Erda Lin; Qiang Liu; Pierre Martre; Christoph Müller; Shushi Peng; Josep Peñuelas; Alex C Ruane; Daniel Wallach; Tao Wang; Donghai Wu; Zhuo Liu; Yan Zhu; Zaichun Zhu; Senthold Asseng
Journal:  Proc Natl Acad Sci U S A       Date:  2017-08-15       Impact factor: 11.205

10.  Evaluating the sensitivity of agricultural model performance to different climate inputs.

Authors:  Michael J Glotter; Elisabeth J Moyer; Alex C Ruane; Joshua W Elliott
Journal:  J Appl Meteorol Climatol       Date:  2016-02-29       Impact factor: 3.557

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