Publication Abstracts
Bassu et al. 2014
Bassu, S., N. Brisson, J.-L. Durand, K. Boote, J. Lizaso, J.W. Jones,
, , M. Adam, C. Baron, B. Basso, C. Biernath, H. Boogaard, S. Conijn, M. Corbeels, D. Deryng, G. De Sanctis, S. Gayler, P. Grassini, J. Hatfield, S. Hoek, C. Izaurralde, R. Jongschaap, A.R. Kemanian, K.C. Kersebaum, S.H. Kim, N.S. Kumar, D. Makowski, C. Müller, C. Nendel, E. Priesack, M.V. Pravia, F. Sau, I. Shcherbak, F. Tao, E. Teixeira, D. Timlin, and K. Waha, 2014: How do various maize crop models vary in their responses to climate change factors? Glob. Change Biol., 20, no. 7, 2301-2320, doi:10.1111/gcb.12520.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.
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BibTeX Citation
@article{ba05400t, author={Bassu, S. and Brisson, N. and Durand, J.-L. and Boote, K. and Lizaso, J. and Jones, J. W. and Rosenzweig, C. and Ruane, A. C. and Adam, M. and Baron, C. and Basso, B. and Biernath, C. and Boogaard, H. and Conijn, S. and Corbeels, M. and Deryng, D. and De Sanctis, G. and Gayler, S. and Grassini, P. and Hatfield, J. and Hoek, S. and Izaurralde, C. and Jongschaap, R. and Kemanian, A. R. and Kersebaum, K. C. and Kim, S. H. and Kumar, N. S. and Makowski, D. and Müller, C. and Nendel, C. and Priesack, E. and Pravia, M. V. and Sau, F. and Shcherbak, I. and Tao, F. and Teixeira, E. and Timlin, D. and Waha, K.}, title={How do various maize crop models vary in their responses to climate change factors?}, year={2014}, journal={Global Change Biology}, volume={20}, number={7}, pages={2301--2320}, doi={10.1111/gcb.12520}, }
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RIS Citation
TY - JOUR ID - ba05400t AU - Bassu, S. AU - Brisson, N. AU - Durand, J.-L. AU - Boote, K. AU - Lizaso, J. AU - Jones, J. W. AU - Rosenzweig, C. AU - Ruane, A. C. AU - Adam, M. AU - Baron, C. AU - Basso, B. AU - Biernath, C. AU - Boogaard, H. AU - Conijn, S. AU - Corbeels, M. AU - Deryng, D. AU - De Sanctis, G. AU - Gayler, S. AU - Grassini, P. AU - Hatfield, J. AU - Hoek, S. AU - Izaurralde, C. AU - Jongschaap, R. AU - Kemanian, A. R. AU - Kersebaum, K. C. AU - Kim, S. H. AU - Kumar, N. S. AU - Makowski, D. AU - Müller, C. AU - Nendel, C. AU - Priesack, E. AU - Pravia, M. V. AU - Sau, F. AU - Shcherbak, I. AU - Tao, F. AU - Teixeira, E. AU - Timlin, D. AU - Waha, K. PY - 2014 TI - How do various maize crop models vary in their responses to climate change factors? JA - Glob. Change Biol. JO - Global Change Biology VL - 20 IS - 7 SP - 2301 EP - 2320 DO - 10.1111/gcb.12520 ER -
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