Abstract: The snow leopard (Panthera uncia) inhabits a human-altered alpine landscape and is often tolerated by residents in regions where the dominant religion is Tibetan Buddhism, including in Qomolangma NNR on the northern side of the Chinese Himalayas. Despite these positive attitudes, many decades of rapid economic development and population growth can cause increasing disturbance to the snow leopards, altering their habitat use patterns and ultimately impacting their conservation. We adopted a dynamic landscape ecology perspective and used multi-scale technique and occupancy model to better understand snow leopard habitat use and coexistence with humans in an 825 km2 communal landscape. We ranked eight hypothetical models containing potential natural and anthropogenic drivers of habitat use and compared them between summer and winter seasons within a year. HABITAT was the optimal model in winter, whereas ANTHROPOGENIC INFLUENCE was the top ranking in summer (AICcw≤2). Overall, model performance was better in the winter than in the summer, suggesting that perhaps some latent summer covariates were not measured. Among the individual variables, terrain ruggedness strongly affected snow leopard habitat use in the winter, but not in the summer. Univariate modeling suggested snow leopards prefer to use rugged land in winter with a broad scale (4000 m focal radius) but with a lesser scale in summer (30 m); Snow leopards preferred habitat with a slope of 22° at a scale of 1000 m throughout both seasons, which is possibly correlated with prey occurrence. Furthermore, all covariates mentioned above showed inextricable ties with human activities (presence of settlements and grazing intensity). Our findings show that multiple sources of anthropogenic activity have complex connections with snow leopard habitat use, even under low human density when anthropogenic activities are sparsely distributed across a vast landscape. This study is also valuable for habitat use research in the future, especially regarding covariate selection for finite sample sizes in inaccessible terrain.

Abstract: Conservation geneticists apply genetic theory and techniques to preserve endangered species as dynamic entities, capable of coping with environmental change and thus minimizing their risk of extinction. Snow leopards are an umbrella species of High Asia, and a keystone for maintaining biodiversity within this fragile ecosystem. A clear understanding of patterns of snow leopard genetic diversity is critical for guiding conservation initiatives that will ensure their long-term persistence. Yet, a comprehensive analysis of snow leopard genetic variation is lacking. The number of published snow leopard genetic studies is far fewer than for other imperiled big cats. Here, I review the limited genetic work to date on snow leopards and the significant knowledge gaps to be filled. An emphasis must be placed on describing and understanding population genetic dynamics within and among meta-populations to provide information about the interactions between landscapes and the micro-evolutionary processes of gene flow and genetic drift. These results can be used to evaluate the levels and dynamics of genetic and demographic connectivity. A lack of connectivity, particularly in the low density, small populations that typify snow leopards, can lead to multiple demographic and genetic consequences, including inbreeding depression, loss of adaptive potential, and heightened susceptibility to demographic and environmental stochasticity. New efforts in conservation research on snow leopards should focus on this line of inquiry, and the opportunities and challenges for that are outlined and discussed to encourage the required, and considerable, transboundary partnerships and collaborations needed to be successful.

Abstract: This paper uses remote sensing data from the Sanjiangyuan National Park (SNP) to explore the divergence between the boundaries of national parks and the distribution of natural habitats. Results are used to argue that these discrepancies evolve along with the potential impact of global warming. Using the example of the habitat change of snow leopards and the conflicts between local people and snow leopards, we reflect on the consequences of this divergence. Results show that divergence between the political boundaries and natural habitats as well as the consequent influence on the living conditions of local people are strikingly visible, and the effects of global warming on such conflicts are apparent. The authors conclude that both notions of ‘political boundaries’ and ‘natural habitats’ are expected to come together as the SNP region is spatially configured, while ‘global warming’ seems to be relevant as an essential reference when delimiting the region in the future. Finally, the proposal for the establishment of cooperative conservation areas is presented,
emphasizing the role of cooperative governance in/around national parks.

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: Significant knowledge gaps persist on snow leopard demography
and reproductive behavior. From a GPS-collared population in Mongolia,
we estimated the timing of mating, parturition and independence. Based
on three mother–cub pairs, we describe the separation phase of the cub
from its mother as it gains independence. Snow leopards mated from
January–March and gave birth from April–June. Cubs remained with their
mother until their second winter (20–22 months of age) when cubs started
showing movements away from their mother for days at a time. This
initiation of independence appeared to coincide with their mother mating
with the territorial male. Two female cubs remained in their mothers’
territory for several months after initial separation, whereas the male
cub quickly dispersed. By comparing the relationship between body size
and age of independence across 11 solitary, medium-to-large felid
species, it was clear that snow leopards have a delayed timing of
separation compared to other species. We suggest this may be related to
their mating behavior and the difficulty of the habitat and prey capture
for juvenile snow leopards. Our results, while limited, provide
empirical estimates for understanding snow leopard ecology and for
parameterizing population models.