|
Anonymous. (1996). Preserving the snow leopard and its habitat. The Rolex Awards for Enterprise Journal, 3.
|
|
|
Kovshar A.F. (1982). Preservation of gene pool of rare and endangered animal species.
Abstract: The rare species are protected in six nature reserves in Kazakhstan, including 9 mammals, 29 birds, and one reptile species. More than 20 rare and endangered species inhabiting Kazakhstan cannot be met within the nature reserves. The point is to establish a network of state nature reserves, particularly in steppe and desert area of the country.
|
|
|
McCarthy, T., Murray, K., Sharma, K., & Johansson, O. (2010). Preliminary results of a long-term study of snow leopards in South Gobi, Mongolia. Cat News, Autumn(53), 15–19.
Abstract: Snow leopards Panthera uncia are under threat across their range and require urgent conservation actions based on sound science. However, their remote habitat and cryptic nature make them inherently difficult to study and past attempts have provided insufficient information upon which to base effective conservation. Further, there has been no statistically-reliable and cost-effective method available to monitor snow leopard populations, focus conservation effort on key populations, or assess conservation impacts. To address these multiple information needs, Panthera, Snow Leopard Trust, and Snow Leopard Conservation Fund, launched an ambitious long-term study in Mongolia’s South Gobi province in 2008. To date, 10 snow leo-pards have been fitted with GPS-satellite collars to provide information on basic snow leopard ecology. Using 2,443 locations we calculated MCP home ranges of 150 – 938 km2, with substantial overlap between individuals. Exploratory movements outside typical snow leopard habitat have been observed. Trials of camera trapping, fecal genetics, and occupancy modeling, have been completed. Each method ex-hibits promise, and limitations, as potential monitoring tools for this elusive species.
Keywords: snow leopard, Mongolia, monitor, population, Panthera, Snow Leopard Trust, Snow Leopard Conservation Fund, South Gobi, ecology, radio collar, GPS-satellite collar, home range, camera trapping, fecal genetics, occupancy modeling
|
|
|
Jackson, R., & Roe, J. (2002). Preliminary Observations On Non-Invasive Techniques for Identifying Individual Snow Leopards and Monitoring Populations.. Islt: Islt.
|
|
|
Koivisto, I. (1978). Preface. In L. Blomqvist (Ed.), International Pedigree Book of Snow Leopards, Vol. 3 (Vol. 1, pp. 1–2). Helsinki: Helsinki Zoo.
|
|
|
Bobrinskiy N.A. (1938). Preditors (Carnivora). The mountains of Central Asia. 1938.
Abstract: It describes fauna of the Tien Shan, Pamir and Hissar mountains of Central Asia. The mountains of Central Asia. Ibex (Capra sibirica) and snow leopard (Uncia uncia) are listed among other inhabitants of highlands in Tien Shan and Pamir Hissar.
|
|
|
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.
|
|
|
Kachel, S., Anderson, K., Shokirov, Q. (2022). Predicting carnivore habitat use and livestock depredation risk with false-positive multi-state occupancy models. Biological Conservation, 271(109588), 1–10.
Abstract: The cycle of livestock depredation and retaliatory killing constitutes a major threat to large carnivores worldwide and imposes considerable hardships on human communities. Mitigation efforts are often undertaken with little knowledge of ecological underpinnings and patterns of depredation, limiting conservationists' ability to develop, prioritize, and evaluate solutions. Carnivore detection and depredation data from interviews in affected communities may help address this gap, but such data are often prone to false-positive uncertainty. To address these challenges in the Pamir Mountains of Tajikistan we collected snow leopard, lynx, wolf, and bear detection and depredation reports from local communities via semi-structured interviews. We used a novel hierarchical multi-species multi-state occupancy model that accounted for potential false-positives to investigate carnivore site use and depredation concurrently with respondents' apparent vulnerability to that risk. Estimated false-positive probabilities were small, but failure to account for them overstated site use probabilities and depredation risk for all species. Although individual vulnerability was low, depredation was nonetheless commonplace. Carnivore site use was driven by clear habitat associations, but we did not identify any clearly important large-scale spatial correlates of depredation risk despite considerable spatial variation in that risk. Respondents who sheltered livestock in household corrals reinforced with wire mesh were less likely to report snow leopard depredations. Reducing depredation and retaliation at adequately large scales in the Pamirs will likely require a portfolio of species-specific strategies, including widespread proactive corral improvements. Our approach expanded inference on the often-cryptic processes surrounding human-carnivore conflict even though structured wildlife data were scarce.
|
|
|
Sokolov G.A. (2003). Predatory mammals of Central Siberia, status of populations, influence of anthropogenic factors.
Abstract: The species resources of Siberia's fauna decrease from south to north. The highest diversity of species is observed in the mountain systems, the lowest in sub-zones of south and central taiga and steppe zone, where the cat family species are absent. During the last 50 150 years number of species has decreased two- to tenfold. Imperfect hunting management, farming, and mining operations resulted in transformation of the animal habitats. Population of fox, polecat, and sable has reduced; snow leopard and dhole becoming endangered species. If current tendencies continue to develop some species will disappear in the region in decades to come.
|
|
|
Elkin K.F. (1979). Predatory mammals in the Eastern Kazakhstan.
Abstract: There are 20 predatory mammal species in eastern Kazakhstan, three of which disappeared (tiger, dhole, raccoon), five are endangered (snow leopard, wild cat, manul, marbled polecat, and stone marten). Snow leopard is not met in the South Altai and Tarbagatai each year.
|
|