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The impacts of climate change exacerbate the myriad challenges faced by smallholder farmers in the Tropics. In many of these same regions, there is a lack of current, consistent, and spatially-explicit data, which severely limits the ability to locate smallholder communities, map their adaptive capacity, and target adaptation measures to these communities. To explore the adaptive capacity of smallholder farmers in three data-poor countries in Central America, we leveraged expert input through in-depth mapping interviews to locate agricultural landscapes, identify smallholder farming systems within them, and characterize different components of farmer adaptive capacity. We also used this input to generate an index of adaptive capacity that allows for comparison across countries and farming systems. Here, we present an overview of the expert method used, followed by an examination of our results, including the intercountry variation in expert knowledge and the characterization of adaptive capacity for both subsistence and smallholder coffee farmers. While this approach does not replace the need to collect regular and consistent data on farming systems (e.g. agricultural census), our study demonstrates a rapid assessment approach for using expert input to fill key data gaps, enable trans-boundary comparisons, and to facilitate the identification of the most vulnerable smallholder communities for adaptation planning in data-poor environments that are typical of tropical regions. One potential benefit from incorporating this approach is that it facilitates the systematic consideration of field-based and regional experience into assessments of adaptive capacity, contributing to the relevance and utility of adaptation plans.
