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

Information about agricultural yields is an important input for a range of downstream system evaluations within the regional projects of the Sustainable Land Management Research Program. While historical yields can often be obtained from official statistics and field experiments, future yields need to be simulated. For the CARBIOCIAL project, potential consequences of climate and land use change on maize production is studied using the mechanistic agro-ecosystem simulation model MONICA. Beside MONICA, a broad variety of simulation models exist for maize at different levels of sophistication. However, ´the uncertainty of maize model predictions is yet unknown. Even more, it is not known whether the different models give similar 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], the largest maize crop model inter-comparison to date is presented, which included 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). It was found that temperature increase had a much larger influence on modeled yield response than did increased [CO2]. It caused an overall decrease of yield of roughly 0.5 Mg per °C. Doubling [CO2] from 360 to 720 μmol mol-1 increased simulated grain yield by 7.5% on average across models and sites. However, there was a large uncertainty in the response to [CO2] among models. Model responses to temperature and [CO2] factors did not differ whether models were simulated with low or high level of calibration information. While individual models differed considerably in absolute yield simulation at the four sites, the ensemble of models was able to simulate absolute yields quite accurate at each of the four sites, even if data for calibration was limited.

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Photo:  Carbiocial
Source: Bassu, S., N. Brisson, J.L. Durand, K.J. Boote, J. Lizaso, J.W. Jones, C. Rosenzweig, A.C. Ruane, M. Adam, C. Baron, B. Basso, C. Biernath, H. Boogard, S. Conijn, M. Corbeels, D. Deryng, G. De Sanctis, S. Gayler, P. Grassini, J.L. Hatfield, S.B. Hoek, C. Izaurralde, R. Jongschaap, A. Kemanian, K.C. Kersebaum, S. Naresh Kumar, D. Makowski, C. Müller, C. Nendel, E. Priesack, M.V. Pravia, K. Soo Hyung,  F. Sau, I. Shcherbak, F.L. 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., in press.

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