We used the CSS implemented by Jones et al. (11) as a measure of between-ecotype genetic distance, weighted by between-localities genetic distance (within each ecotype). However, we used the Euclidean distance between PCA scores as a proxy for genetic distance, as opposed to the multidimensional scaling (MDS) of DXY scores used by Jones et al. (11). Using a custom script, we first performed a PCA with all the SNPs contained within a map position. Then, we calculated the Euclidian distance between every pair of Crab versus Wave ecotype, and between every pair of localities within each of the ecotypes (the same procedure was followed for the Low-High axis of divergence). We used the first four axes of the PCA, as they contained most of the genetic variation (>60%). We calculated CSS from the PCA genetic distances following the formula in the Supplementary Materials and Jones et al. [(11), p. 5].

To identify map positions with significant CSS values, we compared the bootstrap values for each map position against bootstrap values across the whole genome. First, we estimated a genome-wide random expectation by calculating 10,000 CSS across the genome, each iteration consisting of choosing a random map position, randomly sampling the same number of SNPs contained in that map position, and performing the CSS calculation for that random sample. After 10,000 iterations, we obtained a genome-wide expected distribution of CSS values. Second, we calculated the observed CSS per map position and their CIs with 100 random subsamples with replacement of SNPs within a given map position. Last, to assign significance, we considered that the CSS of a given map position was significant (i.e., strong shared divergence between ecotypes across all localities) if its CSS 95% CI did not overlap with the CSS 95% CI of the genome-wide random expectation.

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