Identification of loci associated with climate variation
To identify loci subject to climate-induced selection, we searched for genomic markers that showed the strongest association between allele frequencies within populations and climatic condition in the respective population. We used the univariate approaches Bayenv2 (Coop et al., 2010) and LFMM (Frichot et al., 2013) together with multivariate redundancy analysis (RDA). RDA allows the analysis of multiple environmental variables and covarying selection signals across a set of multiple loci and facilitates the detection of signatures of polygenic selection (Forester et al., 2018) and was performed using the package ‘Vegan 2.5-4‘ in R (Dixon, 2003)⁠. As a conservative approach, we only considered candidate adaptive loci that were detected by at least two methods (Supplement M1, de Villemereuil et al., 2014).