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Suryawanshi, K. R., Khanyari, M., Sharma, K., Lkhagvajav, P., Mishra, C. (2019). Sampling bias in snow leopard population estimation studies. Population Eccology, , 1–9.
Abstract: Accurate assessments of the status of threatened species and their conservation
planning require reliable estimation of their global populations and robust monitoring of local population trends. We assessed the adequacy and suitability of studies in reliably estimating the global snow leopard (Panthera uncia) population. We compiled a dataset of all the peer-reviewed published literature on snow leopard population estimation. Metadata analysis showed estimates of snow leopard density to be a negative exponential function of area, suggesting that study areas have generally been too small for accurate density estimation, and sampling has often been biased towards the best habitats. Published studies are restricted to six of the 12 range countries, covering only 0.3�0.9% of the presumed global range of the species. Re-sampling of camera trap data from a relatively large study site (c.1684 km2) showed that small-sized study areas together with a bias towards good quality habitats in existing studies may have overestimated densities by up to five times. We conclude that current information is biased and inadequate for generating a reliable global population estimate of snow leopards. To develop a rigorous and useful baseline and to avoid pitfalls, there is an urgent need for (a) refinement of sampling and analytical protocols for population estimation of snow leopards (b) agreement and coordinated use of standardized sampling protocols amongst researchers and governments across the range, and (c) sampling larger and under-represented areas of the snow leopard's global range. |
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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Durbach, I., Borchers, D., Sutherland, C., Sharma, K. (2020). Fast, flexible alternatives to regular grid designs for spatial
capture–recapture..
Abstract: Spatial capture–recapture (SCR) methods use the location of
detectors (camera traps, hair snares and live-capture traps) and the locations at which animals were detected (their spatial capture histories) to estimate animal density. Despite the often large expense and effort involved in placing detectors in a landscape, there has been relatively little work on how detectors should be located. A natural criterion is to place traps so as to maximize the precision of density estimators, but the lack of a closed-form expression for precision has made optimizing this criterion computationally demanding. 2. Recent results by Efford and Boulanger (2019) show that precision can be well approximated by a function of the expected number of detected individuals and expected number of recapture events, both of which can be evaluated at low computational cost. We use these results to develop a method for obtaining survey designs that optimize this approximate precision for SCR studies using count or binary proximity detectors, or multi-catch traps. 3. We show how the basic design protocol can be extended to incorporate spatially varying distributions of activity centres and animal detectability. We illustrate our approach by simulating from a camera trap study of snow leopards in Mongolia and comparing estimates from our designs to those generated by regular or optimized grid designs. Optimizing detector placement increased the number of detected individuals and recaptures, but this did not always lead to more precise density estimators due to less precise estimation of the effective sampling area. In most cases, the precision of density estimators was comparable to that obtained with grid designs, with improvement in some scenarios where approximate CV(¬D) < 20% and density varied spatially. 4. Designs generated using our approach are transparent and statistically grounded. They can be produced for survey regions of any shape, adapt to known information about animal density and detectability, and are potentially easier and less costly to implement. We recommend their use as good, flexible candidate designs for SCR surveys when reasonable knowledge of model parameters exists. We provide software for researchers to construct their own designs, in the form of updates to design functions in the r package oSCR. |