Biogeography and Climate Drive Population Divergence and Genomic Vulnerability in High Altitude Endemic Bird

High-elevation systems support species adapted to extreme conditions, and their rugged terrain and variable microclimates strongly shape evolution and persistence. Yet few studies have evaluated how geography and climate jointly shape genetic diversity, local adaptation and vulnerability to environmental change. Here, we investigate these processes in the Tibetan Partridge (Perdix hodgsoniae), a high-altitude endemic distributed across arid western and humid northeastern regions of the Sino-Himalayan landscape. This region's complex topography and contrasting climatic conditions provide a natural setting for examining population divergence, climate-associated adaptation and future resilience. We integrated whole-genome sequencing, ecological, climatic, landscape and morphological data to examine current patterns of local adaptation and forecast climate-induced risks. Our findings show that both biogeographic barriers and climatic gradients drive rapid population divergence in P. hodgsoniae, reflected in distinct morphological traits and population genetic structure. Populations in dry, fragmented western landscapes show adaptation to temperature, whereas those in humid northeastern regions exhibit adaptation primarily to precipitation. These contrasting adaptive trajectories lead to varying levels of vulnerability, with arid, isolated landscapes limiting gene flow and genetic diversity, thereby heightening sensitivity to future climate change. In contrast, humid regions maintain stronger connectivity and larger effective population sizes, supporting higher genetic diversity and facilitating precipitation-linked adaptation. Together, we demonstrate that mountain landscapes function as a 'double-edged sword' by simultaneously generating and limiting biodiversity through isolation, and by constraining persistence within microclimatic refugia. This study underscores the value of integrating genomic, ecological, climate and landscape data to uncover mechanisms of divergence and inform conservation planning under rapid environmental change.