【2h】

Addressing uncertainty in adaptation planning for agriculture

机译:解决农业适应计划中的不确定性

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摘要

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 characterization 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 capacity vs. impact approaches to adaptation planning differ with level of uncertainty and associated lead time. An additional 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 vs. transformative adaptation pathways are 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. We find that impact 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.
机译:我们提出了一个框架,用于在一定范围内对适应方法进行优先排序。发展中国家的四个案例研究说明了该框架,每个案例研究都具有不确定性的特征。斯里兰卡的近期适应计划和东非利益相关者情景练习的两个案例表明,适应计划的能力与影响方法的相对效用随不确定性水平和相关交付时间的不同而不同。另外两个案例表明,可以确定与在特定时间范围和情况下进行决策相关的不确定性。拉丁美洲的咖啡案例确定了海拔阈值,在该阈值处,增量适应路径与转化适应路径是可靠的选择。最后的案例使用了三项作物-气候模拟研究来说明如何在不同的时间范围内表征不确定性,从而区分出可行的适应方案。我们发现,使用预测模型的影响方法在更长的交付周期和更高水平的温室气体排放中越来越有用。我们还发现,极端事件对于确定广泛时间范围内的可预测性很重要。结果证明了面对不确定性时强大的知识和行动的潜力。

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