Addressing uncertainty in adaptation planning for agriculture

We present a framework for prioritizing adaptation approaches at a range of timeframes. The framework is illustrated by four case studies from developing countries, each with associated characterisation of uncertainty. Two cases, on near-term adaptation planning in Sri Lanka and on stakeholder scenario exercises in East Africa, show how the relative utility of â??capacityâ?? versus â??impactâ?? approaches to adaptation planning differ with level of uncertainty and associated lead time. A further two cases demonstrate that it is possible to identify uncertainties that are relevant to decision-making in specific timeframes and circumstances. The case on coffee in Latin America identifies altitudinal thresholds at which incremental versus transformative adaptation pathways are robust options. The final case uses three crop-climate simulation studies to demonstrate how uncertainty can be characterised at different time horizons to discriminate where robust adaptation options are possible. We find that â??impactâ?? approaches, which use predictive models, are increasingly useful over longer lead times and at higher levels of greenhouse gas emissions. We also find that extreme events are important in determining predictability across a broad range of timescales. The results demonstrate the potential for robust knowledge and actions in the face of uncertainty