Inferring landscape factors driving microgeographic genetic structure of large-sized mountain ungulates: A case of Alashan red deer (Cervus elaphus alxaicus)

Abstract

Gene flow is crucial for maintaining population genetic diversity and increasing the adaptive potential of species. Therefore, identifying factors affecting gene flow is important for conservation planning, especially for threatened mammals in complex mountain system. In this study, we conducted a microgeographic-scale landscape genetic analysis for the endangered and ecologically isolated Alashan red deer (Cervus elaphus alxaicus) for the first time. Using data from 329 individuals for 11 microsatellite loci, we assessed how the environmental factors in the Chinese Helan Mountains affect the gene flow of this species. Three genetic clusters were identified by both Bayesian (STRUCTURE and GENELAND) and non-Bayesian (DAPC) methods, revealing clear spatial genetic structure within a limited geographic range. Landscape genetic analysis based on causal modelling and linear mixed-effect modelling revealed that gene flow was primarily restricted by topographic factors, including topographic complexity, aspect, altitude and slope, rather than geographical distance or anthropogenic barriers. Based on these results, we identified two important corridors that can potentially facilitate gene flow within the complex landscape of the Helan Mountains. Our results highlight the role of natural landscape features on Alashan red deer's population genetic structure and functional connectivity. This differs from findings regarding red deer populations in other regions, indicating that landscape genetic patterns are not homogenous across the range of a species, but rather differ among specific landscapes.

Keywords

• Cervus elaphus
• Circuit theory
• Landscape genetics
• Linear mixed model
• Reciprocal causal modelling