Environmental Data Do Not Correlate With Plant Genetic Diversity in Alpine Ecosystems

Abstract

Genetic diversity is a fundamental asset for populations to adapt to changing environmental conditions, particularly under climate change. Although much attention has been paid to protecting taxonomic and ecological diversity, genetic diversity has often been overlooked in management and conservation plans due to the difficulty and costs of its evaluation. We expect an extraordinary impact of global warming on alpine habitats and species that urges us to prioritize the protection of genetic diversity. We analyzed the relationship between 48 environmental factors (climate, soil, and topography) and genetic diversity with AFLP data from 309 populations of 14 European alpine plant species. We used LASSO models and univariate linear regressions to investigate associations between genetic diversity and rarity values in populations as a function of environmental factors at sampling sites, and to identify the best environmental predictors. We found that among all factors, only a topographic descriptor associated with surface concavity and convexity (profile curvature, pcurv) had minimal but significant effects on heterozygosity and genetic rarity when combining all populations from all species (r2 = 0.022 and r2 = 0.017, respectively). When we analyzed the species independently, only Saponaria pumila (Caryophyllaceae) and Androsace vitaliana (Primulaceae) showed significant and marginally significant associations between heterozygosity and pcurv (p-value = 0.036, r2 = 0.126 and p-value = 0.086, r2 = 0.093, respectively). Further analyses pointed to a shared spatial autocorrelation between heterozygosity and pcurv in these species. No significant associations were observed between pcurv and the genetic diversity indexes of the remaining species analyzed. We found that, in general terms, the environment in European alpine areas does not drive the distribution of genetic diversity of plant species. We stress the need for species-specific data and detailed assessments of selectively neutral and adaptive genetic markers to inform conservation efforts to meet global biodiversity protection targets for 2030 in high mountain ecosystems.