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| Author | Changxi, X., Bai, D., Lambert, J. P., Li, Y., Cering, L., Gong, Z., Riordan, P., Shi, K. | ||||
| Title | How Snow Leopards Share the Same Landscape with Tibetan Agro-pastoral Communities in the Chinese Himalayas | Type | Journal Article | ||
| Year | 2022 | Publication | Journal of Resources and Ecology | Abbreviated Journal | |
| Volume | 13 | Issue | 3 | Pages | 483-500 |
| Keywords | habitat use; landscape ecology; occupancy model; Qomolangma; Panthera uncia | ||||
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. | ||||
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| Notes | Approved | no | |||
| Call Number | SLN @ rakhee @ | Serial | 1698 | ||
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| Author | Riordan, P. | ||||
| Title | Unsupervised recognition of individual tigers and snow leopards from their footprints | Type | Miscellaneous | ||
| Year | 1998 | Publication | Animal Conservation | Abbreviated Journal | |
| Volume | 1 | Issue | Pages | 253-262 | |
| Keywords | captive; panthera tigris; panthera uncia; snow leopard; techniques; tiger | ||||
| Abstract |
This study presents the testing of two unsupervised classification methods for their ability to accurately identify unknown individual tigers, Panthera tigris, and snow leopards, Panthera uncia, from their footprints. A neural-network based method, the Kohonen self-organizing map (SOM), and a Bayesian method, AutoClass, were assessed using hind footprints taken from captive animals under standardized conditions. AutoClass successfully discriminated individuals of both species from their footprints. Classification accuracy was greatest for tigers, with more misclassification of individuals occurring for snow leopards. Examination of variable influence on class formations failed to identify consistently influential measurements for either species. The self-organizing map did not provide accurate classification of individuals for either species. Results were not substantially improved by altering map dimensions nor by using principal components derived from the original data. The interpretation of resulting classifications and the importance of using such techniques in the study of wild animal populations are discussed. The need for further testing in the field is highlighted. | ||||
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| Notes | Approved | no | |||
| Call Number | SLN @ rana @ 896 | Serial | 823 | ||
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| Author | Atzeni, L., Cushman, S. A., Wang, J., Riordan, P., Shi, K., Bauman, D. | ||||
| Title | Evidence of spatial genetic structure in a snow leopard population from Gansu, China | Type | Journal Article | ||
| Year | 2021 | Publication | Heredity | Abbreviated Journal | |
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| 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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| Notes | Approved | no | |||
| Call Number | SLN @ rakhee @ | Serial | 1661 | ||
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| Author | Guoliang, P., Alexander, J. S., Riordan, P., Shi, K., Kederhan, Yang, H | ||||
| Title | Detection of a snow leopard population in northern Bortala, Xinjiang, China | Type | Journal Article | ||
| Year | 2016 | Publication | Cat News | Abbreviated Journal | |
| Volume | Issue | 63 | Pages | ||
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| 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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| Notes | Approved | no | |||
| Call Number | SLN @ rakhee @ | Serial | 1443 | ||
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| Author | Alexander, J. S., Gopalswamy, A. M., Shi, K., Riordan, P. | ||||
| Title | Face Value: Towards Robust Estimates of Snow Leopard Densities | Type | Journal Article | ||
| Year | 2015 | Publication | Plos One | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords | Densities, Snow Leopard, Camera traps, Spatial Capture Recapture models | ||||
| Abstract |
When densities of large carnivores fall below certain thresholds, dramatic ecological effects can follow, leading to oversimplified ecosystems. Understanding the population status of such species remains a major challenge as they occur in low densities and their ranges are wide. This paper describes the use of non-invasive data collection techniques combined with recent spatial capture-recapture methods to estimate the density of snow leopards Panthera uncia. It also investigates the influence of environmental and human activity indicators on their spatial distribution. A total of 60 camera traps were systematically set up during a three-month period over a 480 km2 study area in Qilianshan National Nature Reserve, Gansu Province, China. We recorded 76 separate snow leopard captures over 2,906 trapdays, representing an average capture success of 2.62 captures/100 trap-days. We identified a total number of 20 unique individuals from photographs and estimated snow leopard density at 3.31 (SE = 1.01) individuals per 100 km2. Results of our simulation exercise indicate that our estimates from the Spatial Capture Recapture models were not optimal to respect to bias and precision (RMSEs for density parameters less or equal to 0.87). Our results underline the critical challenge in achieving sufficient sample sizes of snow leopard captures and recaptures. Possible performance improvements are discussed, principally by optimising effective camera capture and photographic data quality. |
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| Notes | Approved | no | |||
| Call Number | SLN @ rakhee @ | Serial | 1431 | ||
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