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Timescales of transformational climate change adaptation in sub-Saharan African agriculture

Abstract

Climate change is projected to constitute a significant threat to food security if no adaptation actions are taken1,2. Transformation of agricultural systems, for example switching crop types or moving out of agriculture, is projected to be necessary in some cases3,4,5. However, little attention has been paid to the timing of these transformations. Here, we develop a temporal uncertainty framework using the CMIP5 ensemble to assess when and where cultivation of key crops in sub-Saharan Africa becomes unviable. We report potential transformational changes for all major crops during the twenty-first century, as climates shift and areas become unsuitable. For most crops, however, transformation is limited to small pockets (<15% of area), and only for beans, maize and banana is transformation more widespread (30% area for maize and banana, 60% for beans). We envisage three overlapping adaptation phases to enable projected transformational changes: an incremental adaptation phase focused on improvements to crops and management, a preparatory phase that establishes appropriate policies and enabling environments, and a transformational adaptation phase in which farmers substitute crops, explore alternative livelihoods strategies, or relocate. To best align policies with production triggers for no-regret actions, monitoring capacities to track farming systems as well as climate are needed.

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Figure 1: Timing of transformational adaptation.
Figure 2: Extent of transformational adaptation.
Figure 3: Best substitute crops at mean time of crossing for maize for RCP8.5.

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Acknowledgements

This study was funded by the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) and by a Young Scientist Innovation Grant from the International Center for Tropical Agriculture (CIAT) awarded to J.R.-V. We thank the crop experts listed in Supplementary Table 3 who kindly provided their feedback on both parameter values and suitability simulations. We thank K. Sonder from the International Maize and Wheat Improvement Center (CIMMYT) for sharing an updated mega-environment data set with us and for providing critical feedback on maize parameterizations. U.R. thanks E. Jones from CIAT for help on scripting some of the analyses. Authors thank C. Navarro and J. Tarapues from CIAT for support with the CMIP5 data, L. P. Moreno (CIAT) for her work on improving the EcoCrop model, and A. K. Koehler, S. Jennings and S. Whitfield from the University of Leeds for insightful comments. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modeling, which is responsible for CMIP, and we thank the climate modelling groups for producing and making available their model output (models listed in Supplementary Table 5). For CMIP, the US Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. We thank numerous anonymous reviewers for their insightful feedback.

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J.R.-V. and A.J. conceived the study. U.R., J.R.-V. and A.J. designed the research. U.R. and J.R.-V. performed the analyses and analysed the results. F.M. and L.P. parameterized some of the crops used in the model. U.R., J.R.-V., A.J. and S.J.V. interpreted the results. U.R., J.R.-V., A.J. and S.J.V. wrote the manuscript. All authors discussed results and commented on the manuscript.

Corresponding author

Correspondence to Julian Ramirez-Villegas.

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The authors declare no competing financial interests.

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Rippke, U., Ramirez-Villegas, J., Jarvis, A. et al. Timescales of transformational climate change adaptation in sub-Saharan African agriculture. Nature Clim Change 6, 605–609 (2016). https://doi.org/10.1038/nclimate2947

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