Broad-scale adaptive genetic variation in alpine plants is driven by temperature and precipitation

Abstract

Identifying adaptive genetic variation is a challenging task, in particular in non-model species for which genomic information is still limited or absent. Here, we studied distribution patterns of amplified fragment length polymorphisms (AFLPs) in response to environmental variation, in 13 alpine plant species consistently sampled across the entire European Alps. Multiple linear regressions were performed between AFLP allele frequencies per site as dependent variables and two categories of independent variables, namely Moran's eigenvector map MEM variables (to account for spatial and unaccounted environmental variation, and historical demographic processes) and environmental variables. These associations allowed the identification of 153 loci of ecological relevance. Univariate regressions between allele frequency and each environmental factor further showed that loci of ecological relevance were mainly correlated with MEM variables. We found that precipitation and temperature were the best environmental predictors, whereas topographic factors were rarely involved in environmental associations. Climatic factors, subject to rapid variation as a result of the current global warming, are known to strongly influence the fate of alpine plants. Our study shows, for the first time for a large number of species, that the same environmental variables are drivers of plant adaptation at the scale of a whole biome, here the European Alps.

Fig. 1. Approach used in this study to detect loci of ecological relevance in 13 alpine plant species.

(a) Map of the European Alps showing the study range and sampling intensity (circle area proportional to number of species genotyped per grid cell). (AUT, Austria; FRA, France; GER, Germany; ITA, Italy; SLO, Slovenia; SWI, Switzerland). The number of sampling sites per species is given in Table 1. (b) Type of genetic, environmental and spatial data (MEM variables: Moran’s eigenvector maps) used. (c) Schematic of the statistical analyses. The example given in (a) is Phyteuma hemisphaericum, one of the alpine plants studied.