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Sharma, R. (2010). Of Men and Mountain Ghosts: Glimpses from the Rooftop of the World. GEO, 3(6), 56–67.
Abstract: Catching a glimpse of a snow leopard is a rare and exciting event for anyone. For researchers, hideen camera traps have become a vital tool in their work.
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Ming, M., Xu, F. (2006). Successful Camera Trapping on Snow Leopard in Muzat Valley, Tomur Feng Nature Reserve, Xinjiang, P. R. China. Arid Land Geography, , 307–308.
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Braden, K. (2015). Illegal recreational hunting in Russia: the role of social norms and elite violators. Eurasian Geography and Economics, .
Abstract: Poaching in Russia has been reported to be of catastrophic proportions and threatens
maintenance of biodiversity. Management of game species has stabilized some numbers,
but both endangered species listed in the Russian Red Book and animals traditionally
viewed as hunting prey are diminishing in some regions. Rank-and-file
hunters, increasingly shut off from access to hunting grounds, have expressed a negative
reaction to new hunting regulations adopted by the Russian government in 2012.
While high-profile poaching incidents by so-called “VIP hunters” do not apparently
make up a large portion of cases, the symbolism of the alleged crimes has a derogatory
impact on ordinary hunters because lawlessness is reinforced by perceptions of
impunity for elite poachers.
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Islam, M., Sahana, M., Areendran, G., Jamir, C., Raj, K., Sajjad, H. (2023). Prediction of potential habitat suitability of snow leopard (Panthera uncia) and blue sheep (Pseudois nayaur) and niche overlap in the parts of western Himalayan region. Geo: Geography and Environment, 10(e00121), 1–15.
Abstract: The snow leopard (Panthera uncia) and blue sheep (Pseudois nayaur) are the inhabitants of remote areas at higher altitudes with extreme geographic and climatic conditions. The habitats of these least-studied species are crucial for sustaining the Himalayan ecosystem. We employed the Maximum Entropy (MaxEnt) species distribution model to predict the potential habitat suitability of snow leopards and blue sheep and extracted common overlapped niches. For this, we utilised presence location, bio-climatic and environmental variables, and correlation analysis was applied to reduce the negative impact of multicollinearity. A total of 134 presence locations of snow leopards and 64 for blue sheep were selected from the Global Biodiversity Information Facility (GBIF). The annual mean temperature (Bio1) was found to be the most useful and highly influential factor to predict the potential habitat suitability of snow leopards. Annual mean temperature, annual precipitation and isothermality were the major influencing factors for blue sheep habitat suitability. Highly influential bio-climatic, topographic and environmental variables were integrated to construct the model for predicting habitat suitability. The area under the curve (AUC) values for snow leopard (0.87) and blue sheep (0.82) showed that the models are under good representation. Of the total area investigated, 47% was suitable for the blue sheep and 38% for the snow leopards. Spatial habitat assessment revealed that nearly 11% area from the predicted suitable habitat class of both species was spatially matched (overlapped), 48.6% area was unsuitable under niche overlap and 40.5% area was spatially mismatched niche. The presence of snow leopards and blue sheep in some highly suitable areas was not observed, yet such areas have the potential to sustain these elusive species. The other geographical regions interested in exploring habitat suitability may find the methodological framework adopted in this study useful for formulating an effective conservation policy and management strategy.
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