The structure of the environment influences the patterns and genetics of local adaptation.

Abstract

Environmental heterogeneity can lead to spatially varying selection, which can, in turn, lead to local adaptation. Population genetic models have shown that the pattern of environmental variation in space can strongly influence the evolution of local adaptation. In particular, when environmental variation is highly autocorrelated in space local adaptation will more readily evolve. However, there have been few attempts to test this prediction empirically or characterize the consequences it would have for the genetic architecture underlying local adaptation. In this study, I analyze a large-scale provenance trial conducted on lodgepole pine and find suggestive evidence that spatial autocorrelation in environmental variation is related to the strength of local adaptation that has evolved in that species. Motivated by those results, I use simulations to model local adaptation to different spatial patterns of environmental variation. The simulations confirm that local adaptation is expected to increase with the degree of spatial autocorrelation in the selective environment, but also show that highly heterogeneous environments are more likely to exhibit high variation in local adaptation, a result not previously described. I find that the spatial pattern of environmental variation influences the genetic architectures underlying local adaptation. In highly autocorrelated environments, the genetic architecture of local adaptation tends to be composed of high-frequency alleles with small phenotypic effects. In weakly autocorrelated environments, locally adaptive alleles may have larger phenotypic effects but are present at lower frequencies across species' ranges and experience more evolutionary turnover. Overall, this work emphasizes the profound importance that the spatial pattern of selection can have on the evolution of local adaptation and how spatial autocorrelation should be considered when formulating hypotheses in ecological and genetic studies.