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).