Using connectivity to identify climatic drivers of local adaptation

Understanding the climatic drivers of local adaptation is vital. Such knowledge is not only of theoretical interest but is critical to inform management actions under climate change, such as assisted translocation and targeted gene flow. Unfortunately, there are a vast number of potential trait–environment combinations, and simple relationships between trait and environment are ambiguous: representing either plastic or evolved variation. Here, we show that by incorporating connectivity as an index of gene flow, we can differentiate trait–environment relationships reflecting genetic variation vs. phenotypic plasticity. In this way, we rapidly shorten the list of trait–environment combinations that are of significance. Our analysis of an existing data set on geographic variation in a tropical lizard shows that we can effectively rank climatic variables by the strength of their role in local adaptation. The promise of our method is a rapid and general approach to identifying the environmental drivers of local adaptation.