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Holt, C. D. S., Nevin, O. T., Smith, D., Convery, I. (2018). Environmental niche overlap between snow leopard and four prey species in Kazakhstan. Elsevier, (48), 97–103.
Abstract: The snow leopard Panthera uncia has declined due to habitat loss, habitat fragmentation and human persecution. Predator distribution is heavily dependent on prey species availability and distribution. With increasing pressures from farming practices encroaching into native species range and persecution of snow leopards in response to livestock depredation, it is vital to assess current predator and prey species distribution to highlight sensitive areas of overlap for protection. This study uses MaxEnt, a presence-only Species Distribution Model (SDM) to assess snow leopard and four prey species habitat suitability along
the southern and eastern borders of Kazakhstan using environmental data. This area is considered an important corridor between snow leopard populations in the north and south of their range. Each of the five SDM's produced models of �good� discriminating abilities. We then compared the potential niche overlap between snow leopard and four prey species using ENMTools to highlight areas of important niche overlap within the corridor. The results indicated a very high degree of overlap between snow leopard and Siberian ibex and high degrees Capra sibirica with red deer Cervus elaphus, argali Ovis ammon and urial Ovis orientalis. The snow leopard population in this region is also found to be using forested areas below 2500 m, much lower than recorded in other areas of their range. The results highlight areas needed for protection but also pose additional conservation questions regarding the importance of prey species to transitory individuals. |
Karnaukhov, A. S., Malykh, S. V., Korablev, M. P., Kalashnikova, Y. M., Poyarkov, A. D., Rozhnov, V. V. (2018). Current Status of the Eastern Sayan Snow Leopard (Panthera uncia) Grouping and Its Nutritive Base. Biology Bulletin, 45(9), 1106–1115.
Abstract: A field survey of snow leopard (Panthera uncia) habitats was carried out in the southeastern part of
the Eastern Sayan Mountains (Okinskii and Tunkinskii districts of the Republic of Buryatia and the Kaa- Khemskii district of Tuva Republic). Seven or eight adult snow leopards were observed as constant inhabitants of the Tunkinskie Gol'tsy, Munku-Sardyk, and Bol'shoi Sayan mountain ridges. The presence of eight snow leopards was confirmed using DNA-based analyses of scats collected in 2014 – 2016. The main prey species of the snow leopard in Eastern Sayan is the Siberian ibex (Capra sibirica), but its abundance has steadily decreased over the past 20 years. The red deer (Cervus elaphus) and the wild boar (Sus scrofa), which were some of the most numerous ungulates in the survey area, are replacing the Siberian ibex in the snow leopard's diet. In addition, the mountain hare (Lepus timidus) is also of importance to the snow leopard's diet. |
Singh, R., Krausman, P. R., Pandey, P., Maheshwari, A., Rawal,
R. S., Sharma, S., Shekhar, S. (2020). Predicting Habitat Suitability of Snow Leopards in the Western
Himalayan Mountains, India. Biology bulletin, 47(6), 655–664.
Abstract: The population of snow leopard (Panthera uncia) is declining
across their range, due to poaching, habitat fragmentation, retaliatory killing, and a decrease of wild prey species. Obtaining information on rare and cryptic predators living in remote and rugged terrain is important for making conservation and management strategies. We used the Maximum Entropy (MaxEnt) ecological niche modeling framework to predict the potential habitat of snow leopards across the western Himalayan region, India. The model was developed using 34 spatial species occurrence points in the western Himalaya, and 26 parameters including, prey species distribution, temperature, precipitation, land use and land cover (LULC), slope, aspect, terrain ruggedness and altitude. Thirteen variables contributed 98.6% towards predicting the distribution of snow leopards. The area under the curve (AUC) score was high (0.994) for the training data from our model, which indicates pre- dictive ability of the model. The model predicted that there was 42432 km2 of potential habitat for snow leop- ards in the western Himalaya region. Protected status was available for 11247 km2 (26.5%), but the other 31185 km2 (73.5%) of potential habitat did not have any protected status. Thus, our approach is useful for predicting the distribution and suitable habitats and can focus field surveys in selected areas to save resources, increase survey success, and improve conservation efforts for snow leopards. |
Atzeni, L., Cushman, S. A., Bai, D., Wang, J., Chen, P., Shi,
K., Riordan, P. (2020). Meta-replication, sampling bias, and multi-scale model selection:
A case study on snow leopard (Panthera uncia) in western China. Ecology and Evolution, , 1–27.
Abstract: Replicated multiple scale species distribution models (SDMs)
have become increasingly important to identify the correct variables determining species distribution and their influences on ecological responses. This study explores multi-scale habitat relationships of the snow leopard (Panthera uncia) in two study areas on the Qinghai–Tibetan Plateau of western China. Our primary objectives were to evaluate the degree to which snow leopard habitat relationships, expressed by predictors, scales of response, and magnitude of effects, were consistent across study areas or locally landcape-specific. We coupled univariate scale optimization and the maximum entropy algorithm to produce multivariate SDMs, inferring the relative suitability for the species by ensembling top performing models. We optimized the SDMs based on average omission rate across the top models and ensembles’ overlap with a simulated reference model. Comparison of SDMs in the two study areas highlighted landscape-specific responses to limiting factors. These were dependent on the effects of the hydrological network, anthropogenic features, topographic complexity, and the heterogeneity of the landcover patch mosaic. Overall, even accounting for specific local differences, we found general landscape attributes associated with snow leopard ecological requirements, consisting of a positive association with uplands and ridges, aggregated low-contrast landscapes, and large extents of grassy and herbaceous vegetation. As a means to evaluate the performance of two bias correction methods, we explored their effects on three datasets showing a range of bias intensities. The performance of corrections depends on the bias intensity; however, density kernels offered a reliable correction strategy under all circumstances. This study reveals the multi-scale response of snow leopards to environmental attributes and confirms the role of meta-replicated study designs for the identification of spatially varying limiting factors. Furthermore, this study makes important contributions to the ongoing discussion about the best approaches for sampling bias correction. |