Polygenic scores
We investigated the predictive value of each climate variable for the respective polygenic score based on 213 candidate loci, adjusting linear or quadratic models, selecting the model with the lowest Akaike information criterion (AIC) value. regressions were highly significant, and adjusted R2 values ranged between 0.35 and 0.86 (Figure 3). Analysis using all the 1,392 detected outliers resulted in similar positive regressions, independent of whether or not we corrected for the population structure (Table S8).
Figure 3. Correlations between individual additive polygenic scores (symbols) based on 213 candidate loci and each of the five explanatory climate variables determined per sampling site: Annual mean temperature (a), Annual precipitation (b), Temperature seasonality (c), Mean diurnal temperature range (d), and Precipitation seasonality (e). Polygenic scores were obtained by summing total numbers of favorable alleles. The line represents the regression line from the model, while the shaded area represents the 95% confidence interval. Variance explained and p-values for the linear (c) or quadratic regression (a, b, d, e) fits are given in the respective upper-left corner.