Paper examining four case studies to demonstrate uncertainty management approaches in short- and long-term adaptation planning.
Achieving food security in the face of climate change is a huge and complex public policy issue. The magnitude of the possible impacts, and the costs of inaction or delayed action, means that humanity must begin adaptation now regardless of the inherent uncertainties that lay ahead. While policymakers are accustomed to dealing with uncertainty, science can nevertheless make a major contribution to highlighting and prioritising areas of uncertainty in ways helpful to decision-makers. The purpose of this Proceedings of the National Academy of Sciences of the United States of America article is to demonstrate how science can provide practical approaches to addressing uncertainty that can assist adaptation planning for agriculture in developing countries over multiple lead times.
The structure of the paper consists of four case studies split into pairs according to the time-spans involved. Two case studies deal with near-term adaptation planning scenarios, the first being the 5-year climate adaptation plan Sri Lanka recently developed. With high discrepancies between climate models leading to ambiguous projections, the government chose to conduct a multi-sector integrated vulnerability assessment, using historical impact data as a proxy for future risk priorities. This informed a series of ‘no-regrets’ approaches that illustrates how “good enough” knowledge can assist decision-making under climatic and socioeconomic uncertainty. Another technique to manage near-term uncertainty is portrayed in an East African multi-stakeholder workshop, where scenarios were built and uncertainties discussed so as to complement modelling data.
The final pair of case studies deal with variable time-frames stretching into the longer-term. The case on coffee in Latin America identifies altitudinal thresholds at which incremental versus transformative adaptation pathways are deemed as robust options. The final case uses three crop–climate simulation studies to demonstrate how uncertainty can be characterized at different time horizons to discriminate where robust adaptation options are possible. The report finds that generally, capacity analyses are most important for near-term adaptation planning, but that impact predictive tools, though useful even in the near term, generally become increasingly important over longer-term planning horizons, which contain increasingly novel climates. Additionally, the authors conclude that they find that uncertainty does not preclude robust decisions on adaptation actions, and that exploring uncertainty can assist with decision-making.