Contributions of climate to genetic divergence
Eight climate factors were included in the analysis of the contribution
of climate to genetic divergence (Fig. 3C). A total of 272 SNPs were
scanned by BayeScan and three GEA methods as significant outliers (Fig.
3D; Fig. S6). We observed a substantial intersection between the results
of RDA and BayEnv regardless of whether the former accounted for
population structure; 31 and 41 of the SNPs detected by BayEnv (i.e.,
24% of each set) were detected by RDA.raw and RDA.correct,
respectively. We also observed a sizable intersection (i.e., 33 SNPs;
20%) between the RDA.raw and RDA.correct sets. The 89 SNPs that were
detected by at least two methods were considered putative adaptive SNPs
(Fig. S3D). Forward selection also identified genetic structure
(PC1-PC2) and BIO18 as the only significant predictors explaining the
genetic allele frequencies of adaptive loci (Table S5). The 89 adaptive
SNPs belonged to 34 of the 51 genes enriched in this study. Many of
these are protein-coding genes that are known to be involved in the
adaptation of other species. A complete list of genes, potential
functions, and associated climate variables is given in Table S6.
Climate, demography, and geography together explained 71% of the
variance by pRDA (Table 2; Fig. S6). When two of the three factors were
controlled, demography was the only significant predictor, explaining
52.1% of the total variance, whereas pure climate and pure geography
explained 1% and 2% of the total variance, respectively. These results
suggest that the breaking of species boundaries by genetic groupings
(e.g., Fig. 2B) due to hybridization may play a stronger role in
enhancing the genetic diversity of these species within Taiwan Island
than differentiation caused by geographic or climate barriers. Notably,
16.3% of the variance was confounded among the predictors (Table 2),
suggesting some degree of collinearity among genetic structure, climate,
and geography.