Abstract: Context: The accurate estimation of landscape resistance to movement is important for ecological understanding and conservation applications. Rigorous estimation of resistance requires validation and optimization. One approach uses genetic data for the optimization or validation of resistance models. Objectives We used a genetic dataset of snow leopards from China to evaluate how landscape genetics resistance models varied across genetic distances and spatial scales of analysis. We evaluated whether landscape genetics models were superior to models of resistance derived from habitat suitability or isolation-by-distance.
Methods: We regressed genetically optimized, habitat-based, and isolation-by-distance hypotheses against genetic distances using mixed effect models. We explored all subset combinations of genetically optimized variables to find the most supported resistance scenario for each genetic distance.
Results: Genetically optimized models always out-performed habitat-based and isolation-by-distance hypotheses. The choice of genetic distances influenced the apparent influence of variables, their spatial scales and their functional response shapes, producing divergent resistance scenarios. Gene flow in snow leopards was largely facilitated by areas of intermediate ruggedness at intermediate elevations corresponding to small-to-large valleys within and between the mountain ranges.
Conclusions: This study highlights that landscape genetics models provide superior estimation of functional dispersal than habitat surrogates and suggests that optimization of genetic distance should be included as an optimization routine in landscape genetics, along with variables, scales, effect size and functional response shape. Furthermore, our study provides new insights on the ecological conditions that promote gene flow in snow leopards, which expands ecological knowledge, and we hope will improve conservation planning.

Abstract: The high-altitude region of Asia is prone to natural resource degradation caused by a variety of natural and anthropogenic factors that also threaten the habitat of critical top predator species, the snow leopard (Panthera uncia). The snow leopard’s landscape encompasses parts of the twelve Asian countries and is dominated by pastoral societies within arid mountainous terrain. However, no investigation has assessed the vulnerability and pathways towards long-term sustainability on the global snow leopard landscape scale. Thus, the current study reviewed 123 peer-reviewed scientific publications on the existing knowledge, identified gaps, and proposed sustainable mitigation options for the longer term and on larger landscape levels in the range countries. The natural resource degradation in this region is caused by various social, economic, and ecological threats that negatively affect its biodiversity. The factors that make the snow leopard landscapes vulnerable include habitat fragmentation through border fencing, trade corridor infrastructure, non-uniform conservation policies, human–snow leopard conflict, the increasing human population, climatic change, land use and cover changes, and unsustainable tourism. Thus, conservation of the integrated Socio-Ecological System (SES) prevailing in this region requires a multi-pronged approach. This paper proposes solutions and identifies the pathways through which to implement these solutions. The prerequisite to implementing such solutions is the adoption of cross-border collaboration (regional cooperation), the creation of peace parks, readiness to integrate transnational and cross-sectoral conservation policies, a focus on improving livestock management practices, a preparedness to control human population growth, a readiness to mitigate climate change, initiating transboundary landscape-level habitat conservation, adopting environment-friendly trade corridors, and promoting sustainable tourism. Sustainable development in this region encompasses the political, social, economic, and ecological landscapes across the borders.