Dispersal and habitat dynamics shape the genetic structure of the Northern chamois in the Alps

Abstract

AbstractAimUnderstanding the drivers of species distribution ranges and population genetic structure can help predict species' responses to global change, while mitigating threats to biodiversity through effective conservation measures. Here, we combined species habitat suitability through time with process‐based models and genomic data to investigate the role of landscape features and functional connectivity in shaping the population genetic structure of Northern chamois.LocationEuropean Alps.TaxonNorthern chamois (Rupicapra rupicapra).MethodsUsing a model that simulates dispersal and tracks the functional connectivity of populations over dynamic landscapes, we modelled the response of the chamois to climate change from the last glaciation (20,000 years ago) to the present. We reconstructed species habitat suitability and landscape connectivity over time and simulated cumulative divergence of populations as a proxy for genetic differentiation. We then compared simulated divergence with the actual population structure of 449 chamois (with >20 k SNPs) sampled across the Alps.ResultsWe found that Alpine populations of chamois are structured into two main clades, located in the south‐western and the eastern Alps. The contact zone between the two lineages is located near the Rhone valley in Switzerland. Simulations reproduced the geographic differentiation of populations observed in the genomic data, and limited dispersal ability and landscape connectivity co‐determined the fit of the simulations to data.Main conclusionsThe contemporary genetic structure of the chamois across the Alps is explained by limited functional connectivity in combination with large rivers or valleys acting as dispersal barriers. The results of our analysis combining simulations with population genomics highlight how biological characteristics, habitat preference and landscapes shape population genetic structure over time and in responses to climate change. We conclude that spatial simulations could be used to improve our understanding of how landscape dynamics, shaped by geological or climatic forces, impact intra‐ and interspecific diversity.