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Guoliang, P., Alexander, J. S., Riordan, P., Shi, K., Kederhan, Yang, H. (2016). Detection of a snow leopard population in northern Bortala, Xinjiang, China. Cat News, (63).
Abstract: We substantiate the presence of snow leopards Panthera uncia using camera
traps within the Dzungarian Alatau range in Bortala Mongolia Autonomous Prefecture, Xinjiang Province, China. A total of 13 camera trap stations were set up in 2012 and a total of 14 camera trap stations in 2013 within an area of 192 km2. A total of 11-15 individual adult snow leopards and two sub adults were identified from photo captures of sufficient quality. A range of human activities were noted within and surrounding the survey area, including livestock herding and mining. We recommend more large scale and intensive camera trap surveys to further assess the population status of the snow leopard within this area |
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Atzeni, L., Cushman, S. A., Wang, J., Riordan, P., Shi, K., Bauman, D. (2021). Evidence of spatial genetic structure in a snow leopard population from Gansu, China. Heredity, . Retrieved June 30, 2024, from http://dx.doi.org/https://doi.org/10.1038/s41437-021-00483-0
Abstract: Understanding the spatial structure of genetic diversity provides insights into a populations’ genetic status and enables assessment of its capacity to counteract the effects of genetic drift. Such knowledge is particularly scarce for the snow leopard, a conservation flagship species of Central Asia mountains. Focusing on a snow leopard population in the Qilian mountains of Gansu Province, China, we characterised the spatial genetic patterns by incorporating spatially explicit indices of diversity and multivariate analyses, based on different inertia levels of Principal Component Analysis (PCA). We compared two datasets differing in the number of loci and individuals. We found that genetic patterns were significantly spatially structured and were characterised by a broad geographical division coupled with a fine-scale cline of differentiation. Genetic admixture was detected in two adjoining core areas characterised by higher effective population size and allelic diversity, compared to peripheral localities. The power to detect significant spatial relationships depended primarily on the number of loci, and secondarily on the number of PCA axes. Spatial patterns and indices of diversity highlighted the cryptic structure of snow leopard genetic diversity, likely driven by its ability to disperse over large distances. In combination, the species’ low allelic richness and large dispersal ability result in weak genetic differentiation related to major geographical features and isolation by distance. This study illustrates how cryptic genetic patterns can be investigated and analysed at a fine spatial scale, providing insights into the spatially variable isolation effects of both geographic distance and landscape resistance.
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Xiao, C., Bai, D., Lambert, J. P., Li, Y., Cering, L., Gong, Z., Riordan, P., Shi, K. (2022). How Snow Leopards Share the Same Landscape with Tibetan Agro-pastoral Communities in the Chinese Himalayas. Journal of Resources and Ecology, 13(3), 483–500.
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.
Keywords: habitat use; landscape ecology; occupancy model; Qomolangma; Panthera uncia
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Changxi, X., Bai, D., Lambert, J. P., Li, Y., Cering, L., Gong, Z., Riordan, P., Shi, K. (2022). How Snow Leopards Share the Same Landscape with Tibetan Agro-pastoral Communities in the Chinese Himalayas. Journal of Resources and Ecology, 13(3), 483–500.
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.
Keywords: habitat use; landscape ecology; occupancy model; Qomolangma; Panthera uncia
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Atzeni, L., Wang, J., Riordan, P., Shi, K., Cushman, S. A. (2023). Landscape resistance to gene flow in a snow leopard population from Qilianshan National Park, Gansu, China. Landscape Ecology, .
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. |