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Yu, N. Z. C., Wang, X., He, G., Zhang, Z., Zhang, A., Lu, W., et al. (1996). A revision of genus Uncia Gray, 1854 based on mitochondrial DNA restriction site maps. Acta Theriologica Sinica, 16(2), 105–108.
Abstract: The Snow leopard (Panthera uncia) is one of the most threatened wild big cats within its range of distribution, however, the question of its systematic status is a matter of debate. Is it a member of genus Panthera, or is it in its own genus (Uncia)? The analysis of genetic difference at the DNA level may provide useful data to clarify the issue. In the present study, ten hexanucleotide-specific restriction endonucleases were used to evaluate the patterns of mitochondrial DNA variation between the Snow leopard and leopard (P. pardus). The molecular size of mtDNA from the two species was about 16.5 kb. Ten enzymes surveyed 32-34 restriction sites, which corresponded to 192 apprx 204 base pairs, or 1.16% apprx 1.24% of the total mtDNA molecule. A total of 45 restriction sites were mapped; of these sites, twenty-four, which correspond to 53.3% of the total sites, were variable. The sequence divergence between them was 0.075 33, which was undoubtedly in the species-level distinction but did not reach the genus level. Therefore, the Snow leopard should be placed in the genus Panthera rather than in its own ganus. It also seems reasonable to recognize Uncia as a valid subgenus. This conclusion not only support but also supplement the viewpoint of Simpson who treated Uncia as a subgenus within Panthera.
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Prasad, S. N., Chundawat, R. S., Hunter, D. O., Panwar, H. S., & Rawat, G. S. (1991). Remote sensing snow leopard habitat in the trans-Himalaya of India using spatial models and satellite imagery preliminary results. In G. J. Buhyoff (Ed.), (pp. 519–523).
Abstract: The snow leopard (Panthera uncia) is a flagship species for conservation in the high mountain regions of central Asia. Data on snow leopard predation, habitat conditions and range of main prey species were gathered along with thematic maps of the study area for elevation, snow cover, sighting data, kill data, blue sheep use areas, and vegetation data. These data were entered into a GIS and used to help delineate surface features from a satellite image. Preliminary results show that general physiographic features of snow leopard habitat can be detected using satellite imagery and that GIS cartographic modeling techniques can improve this delineation. -from Authors
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Karki, A., Panthi, S. (2021). Factors affecting livestock depredation by snow leopards (Panthera uncia) in the Himalayan region of Nepal. PeerJ, 9(e11575), 1–14.
Abstract: The snow leopard (Panthera uncia) found in central Asia is classified as vulnerable species by the International Union for Conservation of Nature (IUCN). Every year, large number of livestock are killed by snow leopards in Nepal, leading to economic loss to local communities and making human-snow leopard conflict a major threat to snow leopard conservation. We conducted formal and informal stakeholder’s interviews to gather information related to livestock depredation with the aim to map the attack sites by the snow leopard. These sites were further validated by district forest office staffs to assess sources of bias. Attack sites older than 3 years were removed from the survey. We found 109 attack sites and visited all the sites for geo location purpose (GPS points of all unique sites were taken). We maintained at least a 100 m distance between attack locations to ensure that each attack location was unique, which resulted in 86 unique locations. A total of 235 km2 was used to define livestock depredation risk zone during this study. Using Maximum Entropy (MaxEnt) modeling, we found that distance to livestock sheds, distance to paths, aspect, and distance to roads were major contributing factors to the snow leopard’s attacks. We identified 13.64 km2 as risk zone for livestock depredation from snow leopards in the study area. Furthermore, snow leopards preferred to attack livestock near livestock shelters, far from human paths and at moderate distance from motor roads. These identified attack zones should be managed both for snow leopard conservation and livestock protection in order to balance human livelihoods while protecting snow leopards and their habitats.
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Korablev, M. P., Poyarkov, A. D., Karnaukhov, A. S., Zvychaynaya, E. Y., Kuksin, A. N., Malykh, S. V., Istomov, S. V., Spitsyn, S. V., Aleksandrov, D. Y., Hernandez-Blanco, J. A., Munkhtsog, B., Munkhtogtokh, O., Putintsev, N. I., Vereshchagin, A. S., Becmurody, A., Afzunov, S., Rozhnov, V. V. (2021). Large-scale and fine-grain population structure and genetic diversity of snow leopards (Panthera uncia Schreber, 1776) from the northern and western parts of the range with an emphasis on the Russian population. Conservation Genetics, .
Abstract: The snow leopard (Panthera uncia Schreber, 1776) population in Russia and Mongolia is situated at the northern edge of the range, where instability of ecological conditions and of prey availability may serve as prerequisites for demographic instability and, consequently, for reducing the genetic diversity. Moreover, this northern area of the species distribution is connected with the western and central parts by only a few small fragments of potential habitats in the Tian-Shan spurs in China and Kazakhstan. Given this structure of the range, the restriction of gene flow between the northern and other regions of snow leopard distribution can be expected. Under these conditions, data on population genetics would be extremely important for assessment of genetic diversity, population structure and gene flow both at regional and large-scale level. To investigate large-scale and fine-grain population structure and levels of genetic diversity we analyzed 108 snow leopards identified from noninvasively collected scat samples from Russia and Mongolia (the northern part of the range) as well as from Kyrgyzstan and Tajikistan (the western part of the range) using panel of eight polymorphic microsatellites. We found low to moderate levels of genetic diversity in the studied populations. Among local habitats, the highest heterozygosity and allelic richness were recorded in Kyrgyzstan (He = 0.66 ± 0.03, Ho = 0.70 ± 0.04, Ar = 3.17) whereas the lowest diversity was found in a periphery subpopulation in Buryatia Republic of Russia (He = 0.41 ± 0.12, Ho = 0.29 ± 0.05, Ar = 2.33). In general, snow leopards from the western range exhibit greater genetic diversity (He = 0.68 ± 0.04, Ho = 0.66 ± 0.03, Ar = 4.95) compared to those from the northern range (He = 0.60 ± 0.06, Ho = 0.49 ± 0.02, Ar = 4.45). In addition, we have identified signs of fragmentation in the northern habitat, which have led to significant genetic divergence between subpopulations in Russia. Multiple analyses of genetic structure support considerable genetic differentiation between the northern and western range parts, which may testify to subspecies subdivision of snow leopards from these regions. The observed patterns of genetic structure are evidence for delineation of several management units within the studied populations, requiring individual approaches for conservation initiatives, particularly related to translocation events. The causes for the revealed patterns of genetic structure and levels of genetic diversity are discussed.
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McCarthy, K., Fuller, T., Ming, M., McCarthy, T., Waits, L., & Jumabaev, K. (2008). Assessing Estimators of Snow Leopard Abundance (Vol. 72).
Abstract: The secretive nature of snow leopards (Uncia uncia) makes them difficult to monitor, yet conservation efforts require accurate and precise methods to estimate abundance. We assessed accuracy of Snow Leopard Information Management System (SLIMS) sign surveys by comparing them with 4 methods for estimating snow leopard abundance: predator:prey biomass ratios, capture-recapture density estimation, photo-capture rate, and individual identification through genetic analysis. We recorded snow leopard sign during standardized surveys in the SaryChat Zapovednik, the Jangart hunting reserve, and the Tomur Strictly Protected Area, in the Tien Shan Mountains of Kyrgyzstan and China. During June-December 2005, adjusted sign averaged 46.3 (SaryChat), 94.6 (Jangart), and 150.8 (Tomur) occurrences/km. We used
counts of ibex (Capra ibex) and argali (Ovis ammon) to estimate available prey biomass and subsequent potential snow leopard densities of 8.7 (SaryChat), 1.0 (Jangart), and 1.1 (Tomur) snow leopards/100 km2. Photo capture-recapture density estimates were 0.15 (n = 1 identified individual/1 photo), 0.87 (n = 4/13), and 0.74 (n = 5/6) individuals/100 km2 in SaryChat, Jangart, and Tomur, respectively. Photo-capture rates
(photos/100 trap-nights) were 0.09 (SaryChat), 0.93 (Jangart), and 2.37 (Tomur). Genetic analysis of snow leopard fecal samples provided minimum population sizes of 3 (SaryChat), 5 (Jangart), and 9 (Tomur) snow leopards. These results suggest SLIMS sign surveys may be affected by observer bias and environmental variance. However, when such bias and variation are accounted for, sign surveys indicate relative abundances similar to photo rates and genetic individual identification results. Density or abundance estimates based on capture-recapture or ungulate biomass did not agree with other indices of abundance. Confidence in estimated densities, or even detection of significant changes in abundance of snow leopard, will require more effort and better documentation.
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Pavlinov I.Ya. (1987). Taxonomy of mammals in the USSR.
Abstract: The reference book on taxonomy of modern mammals in the USSR provides classification from order to species, list of synonyms for all taxons, and indicates types and typical habitats, and places of storage of typical exhibits. Fauna of the USSR has one species of genus Uncia Grey, 1854 Uncia uncia (Schreber, 1776).
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Yanushevich A.I. (1977). To be protected by the Red Data Book.
Abstract: The Red Data Book of the USSR includes 111 mammal species and 67 bird species. The following species inhabit or from time to time come into Kyrgyzstan: free-toiled bat, Menzbier's marmot, red dog, Tien Shan brown bear, marbled polecat, Central Asia otter, Turkistan lynx, manul, snow leopard, antelope, Tien-Shan wild sheep, and bison; Dalmatian pelican, rose pelican, black stork, flamingo, bar-headed goose, white-headed duck, osprey, short-toed eagle, tawny eagle, imperial eagle, golden eagle, white-tailed eagle, Pallas's sea eagle, bearded vulture, Himallayan griffon, Sociable plover, Saker falcon, Peregrine falcon, great bustard, houbara, little bustard, etc.
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Kovshar A.F. (1982). A problem of rare and endangered animal species in Kazakhstan.
Abstract: The Red Book of the Kazakh SSR includes 91 rare and endangered vertebrate animal species: 30 mammal, 48 bird, eight reptile, one amphibian, and four fish species. 26 species (Menzbier's marmot, marten species, lynx, snow leopard, and other species) became rare because of a direct anthropogenic pressure. The prohibition of hunting, conservation and rehabilitation of their habitats, reproduction in enclosures and preservation of some species' genomes is a way that would conserve rare species, the authors believe.
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Persianova L.A. (1980). About the Red Book listing rare and endangered animal and plant species.
Abstract: The Red Book includes data of rare and endangered fauna and flora species. The species are sub-divided into five categories by threat. Volume 1 of the Red Book of the Uzbek SSR includes 22 mammal species, 31 bird species, five reptile and five fish species. Among them there are endemic species and species included in the International Red list. Snow leopard is referred to a category of endangered species.
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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.
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