Agricultural Community Adaptive Capacity in Kansas

Agriculture is one of the most significant contributors to Kansas economic success, yet it is highly susceptible to the impacts of climate change. Increasing heat and decreasing predictability of precipitation are expected to result in increased aridity in Kansas, placing additional strain on rain-fed agriculture and increasing pressure on limited groundwater reserves. The sustainability of Kansas agricultural communities ultimately depends upon their ability to adapt. Therefore, it is important to understand the current state of adaptive capacity across the state, the potential benefits of increasing adaptive capacity, and the factors that contribute most strongly to agricultural community adaptive capacity. In this study we develop a framework for assessing agricultural community adaptive capacity and construct an adaptive capacity index at the census tract scale in Kansas. To ensure that the adaptive capacity index is appropriate for adaptation planning and decision-making processes we examine the internal consistency of the index using Random Forest analysis and calculate the uncertainty associated with index values via an index construction sensitivity analysis. In addition, we examine the extent to which the constructed index reflects the desired quality of ability to change to reduce future impacts of adverse climate conditions using linear and non-linear regression. Preliminary results indicate that our Adaptive Capacity Index, which contains 31 variables associated with physical, social, and economic capital, is sensitive to assumptions about directionality of variable effects on adaptive capacity and index construction methods. Random forests analysis indicates that a subset of 4 variables can be used to explain most of the variation in the index, with an R-squared of 0.78 for predictions of the index on a held-out sample. In addition, we find that the Adaptive Capacity Index is strongly associated with improved farmer outcomes, and to a lesser extent community and economic outcomes after accounting for precipitation, heat, and soil conditions. Overall, these results suggest that while attempts to characterize adaptive capacity are challenged by sensitivity to construction methods, it is possible to develop an index that can be useful for identifying adaption planning priorities.