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

Abstract

Aim Understanding 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. Location European Alps. Taxon Northern chamois (Rupicapra rupicapra). Methods Using 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. Results We 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 conclusions The 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.

Unravelling the complex biogeographic and anthropogenic history of Alaska’s mountain goats

“…kyr BP, allowing for the expansion and divergence of both human and wildlife populations (Heintzman et al, 2016;Loog et al, 2020;Pedersen et al, 2016). Similar timeframes of expansion have been detected globally as was seen with the Northern chamois, a closely related species in the European Alps (Leugger et al, 2022). This timing corresponds with our findings of a northerly mountain goat expansion.…”

CHELSA-TraCE21k – high-resolution (1 km) downscaled transient temperature and precipitation data since the Last Glacial Maximum

“…Transient long-term climatic data have a wide range of possible applications, ranging from population genetics (Leugger et al, 2022;Yannic et al, 2020), community ecology (Staples et al, 2022), and biodiversity buildup (Garcés-Pastor et al, 2022;Alsos et al, 2022) to evolutionary biology (Cerezer et al, 2022), just to name a few. Here we use one application in paleoecology as a plausibility test to additionally check if the transient CHELSA-TraCE21k data can reliably detect known LGM refugia of plant species.…”