1 Using connectivity to identify climatic drivers of local adaptation 2

33 Despite being able to conclusively demonstrate local adaptation, we are still often 34 unable to objectively determine the climatic drivers of local adaptation. Given the 35 rapid rate of global change, understanding the climatic drivers of local adaptation is 36 vital. Not only will this tell us which climate axes matter most to population fitness, 37 but such knowledge is critical to inform management strategies such as translocation 38 and targeted gene flow. While simple assessments of geographic trait variation are 39 useful, geographic variation (and its associations with environment) may represent 40 plastic, rather than evolved, differences. Additionally, the vast number of trait– 41 environment combinations makes it difficult to determine which aspects of the 42 environment populations adapt to. Here we argue that by incorporating a measure of 43 landscape connectivity as a proxy for gene flow, we can differentiate between trait– 44 environment relationships underpinned by genetic differences versus those that reflect 45 phenotypic plasticity. By doing so, we can rapidly shorten the list of trait– 46 environment combinations that may be of adaptive significance. We demonstrate how 47 this reasoning can be applied using data on geographic trait variation in a lizard 48 species from Australia’s Wet Tropics rainforest. Our analysis reveals an 49 overwhelming signal of local adaptation for the traits and environmental variables we 50 investigated. Our analysis also allows us to rank environmental variables by the 51 degree to which they appear to be driving local adaptation. Although encouraging, 52 methodological issues remain: we point to these issue in the hope that the community 53 can rapidly hone the methods we sketch here. The promise is a rapid and general 54 approach to identifying the environmental drivers of local adaptation. 55 56 . CC-BY-NC-ND 4.0 International license not peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was . http://dx.doi.org/10.1101/145169 doi: bioRxiv preprint first posted online Jun. 2, 2017;