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Uncertainty, ignorance and ambiguity in crop modelling for African agricultural adaptation

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  • Stephen Whitfield

Abstract

Drawing on social constructivist approaches to interpreting the generation of knowledge, particularly Stirling’s (Local Environ 4(2):111–135, 1999 ) schema of incomplete knowledge, this paper looks critically at climate-crop modelling, a research discipline of growing importance within African agricultural adaptation policy. A combination of interviews with climate and crop modellers, a meta-analysis survey of crop modelling conducted as part of the CGIAR’s Climate Change Agriculture and Food Security (CCAFS) programme in 2010, and peer-reviewed crop and climate modelling literature are analysed. Using case studies from across the crop model production chain as illustrations it is argued that, whilst increases in investment and growth of the modelling endeavour are undoubtedly improving observational data and reducing ignorance, the future of agriculture remains uncertain and ambiguous. The expansion of methodological options, assumptions about system dynamics, and divergence in model outcomes is increasing the space and need for more deliberative approaches to modelling and policy making. Participatory and deliberative approaches to science-policy are advanced in response. The discussion highlights the problem that, uncertainty and ambiguity become hidden within the growing complexity of conventional climate and crop modelling science, as such, achieving the transparency and accessibility required to democratise climate impact assessments represents a significant challenge. Suggestions are made about how these challenges might be responded to within the climate-crop modelling community. Copyright Springer Science+Business Media Dordrecht 2013

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  • Stephen Whitfield, 2013. "Uncertainty, ignorance and ambiguity in crop modelling for African agricultural adaptation," Climatic Change, Springer, vol. 120(1), pages 325-340, September.
    • Handle: RePEc:spr:climat:v:120:y:2013:i:1:p:325-340
    DOI: 10.1007/s10584-013-0795-3
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    1. Belay Kassie & Senthold Asseng & Reimund Rotter & Huib Hengsdijk & Alex Ruane & Martin Ittersum, 2015. "Exploring climate change impacts and adaptation options for maize production in the Central Rift Valley of Ethiopia using different climate change scenarios and crop models," Climatic Change, Springer, vol. 129(1), pages 145-158, March.
    2. Darren Nel & Araz Taeihagh, 2024. "The soft underbelly of complexity science adoption in policymaking: towards addressing frequently overlooked non-technical challenges," Policy Sciences, Springer;Society of Policy Sciences, vol. 57(2), pages 403-436, June.
    3. Louise Beveridge & Stephen Whitfield & Andy Challinor, 2018. "Crop modelling: towards locally relevant and climate-informed adaptation," Climatic Change, Springer, vol. 147(3), pages 475-489, April.
    4. Stephen Whitfield & Sarah Chapman & Marcelin Tonye Mahop & Chetan Deva & Kennedy Masamba & Andekelile Mwamahonje, 2021. "Exploring assumptions in crop breeding for climate resilience: opportunities and principles for integrating climate model projections," Climatic Change, Springer, vol. 164(3), pages 1-18, February.

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