Published in

Elsevier, Agricultural and Forest Meteorology, (170), p. 89-102, 2013

DOI: 10.1016/j.agrformet.2011.12.003

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Projections of climate change impacts on potential C4 crop productivity over tropical regions

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This paper is available in a repository.

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Abstract

Climate change impacts on agriculture could arguably be most critical for developing countries in tropical regions: their populations rely importantly on agriculture and climate-dependant resources, poverty limits their capacity to anticipate and adapt to climate change, and population increase already poses a serious challenge to food security in those regions. Current projections of climate change impacts on tropical crop yields, even though on average negative, remain largely uncertain: there is need for more consistent, large-scale, quantitative assessments. In this study we use a newly developed agro-DGVM (Dynamical Global Vegetation Model including an explicit representation of croplands) driven by projections from several climate models and two SRES scenarios to evaluate climate change impacts on potential C4 crop productivity over Africa and India from 1960 to 2100. We specifically separate the effect of increasing atmospheric CO 2 levels. We perform transient simulations directly forced by climate model outputs: to preserve consistency in the analysis despite regional biases in climate models, we analyze yield change on a bioclimatic basis (using the Köppen classification) rather than on a geographical basis. We find that the potential productivity of one of the most important staple crops in those regions, millet, will overall decrease, on average over all models and scenarios, by −6% (individual model projections ranging from −29% to +11%). The bioclimatic analysis allows us to highlight the main climate drivers of these changes. The main impact is a moderate but robust temperature-driven yield decrease over Equatorial and Temperate Köppen zones; larger but much more inconsistent yield changes occur in Arid Köppen zones, reflecting the uncertainty in precipitation projections from climate models. The uncertainty in aggregated impacts reflects the uncertainty over these areas, underlining the need to narrow the uncertainty in precipitation projections over dry areas if more reliable agricultural impact assessments over tropical regions are to be provided. Our results are also consistent with the limited magnitude of the impact of increased atmospheric CO 2 levels on C4 crop yields described in the literature. While such climatic impacts further increase the challenge of achieving future food security in developing countries in the Tropics, most of these impacts can arguably be mitigated through adaptation measures and improved agricultural practices.