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

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.