Subbotin, A. E., & Istomov, S. V. (2009). The population status of snow leopards Uncia uncia (Felidae, Carnivora) in the western Sayan Mountain Ridge. Doklady Biologicl Sciences, 425, 183–186.
Abstract: The snow leopard (Uncia uncial Schreber, 1776) is the most poorly studied species of the cat family in the world and, in particular, in Russia, where the northern periphery of the species area (no more than 3% of it) is located in the Altai-Hangai-Sayan range [1]. It is generally known that the existing data on the Russian part of the snow leopard population have never been a result of targeted studies; at best, they have been based on recording the traces of the snow leopard vital activity [2]. This is explained by the snow leopard's elusive behavior, inaccessibility of its habitats for humans, and its naturally small total numbers in the entire species area. All published data on the population status of the snow leopard in Russia, from the first descriptions of the species [3-6] to the latest studies [7, 8] are subjective, often speculative, and are not confirmed by
quantitative estimates. It is obvious, however, that every accurate observation of this animal is of particular interest [9]. The purpose of our study was to determine the structure and size of the population group presumably inhabiting the Western Sayan mountain ridge at the northern boundary of the species area
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Durbach, I., Borchers, D., Sutherland, C., Sharma, K. (2020). Fast, flexible alternatives to regular grid designs for spatial
capture–recapture..
Abstract: Spatial capture–recapture (SCR) methods use the location of
detectors (camera traps, hair snares and live-capture traps) and the
locations at which animals were detected (their spatial capture
histories) to estimate animal density. Despite the often large expense
and effort involved in placing detectors in a landscape, there has been
relatively little work on how detectors should be located. A natural
criterion is to place traps so as to maximize the precision of density
estimators, but the lack of a closed-form expression for precision has
made optimizing this criterion computationally demanding. 2. Recent
results by Efford and Boulanger (2019) show that precision can be well
approximated by a function of the expected number of detected
individuals and expected number of recapture events, both of which can
be evaluated at low computational cost. We use these results to develop
a method for obtaining survey designs that optimize this approximate
precision for SCR studies using count or binary proximity detectors, or
multi-catch traps. 3. We show how the basic design protocol can be
extended to incorporate spatially varying distributions of activity
centres and animal detectability. We illustrate our approach by
simulating from a camera trap study of snow leopards in Mongolia and
comparing estimates from our designs to those generated by regular or
optimized grid designs. Optimizing detector placement increased the
number of detected individuals and recaptures, but this did not always
lead to more precise density estimators due to less precise estimation
of the effective sampling area. In most cases, the precision of density
estimators was comparable to that obtained with grid designs, with
improvement in some scenarios where approximate CV(¬D) < 20% and density
varied spatially. 4. Designs generated using our approach are
transparent and statistically grounded. They can be produced for survey
regions of any shape, adapt to known information about animal density
and detectability, and are potentially easier and less costly to
implement. We recommend their use as good, flexible candidate designs
for SCR surveys when reasonable knowledge of model parameters exists. We
provide software for researchers to construct their own designs, in the
form of updates to design functions in the r package oSCR.
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Aryal, A. (2009). Final Report On Demography and Causes of Mortality of Blue Sheep (Pseudois nayaur) in Dhorpatan Hunting Reserve in Nepal.
Abstract: A total of 206 individual Blue sheep Pseudois nayaur were estimated in Barse and Phagune blocks of Dhorpatan Hunting Reserve (DHR) and population density was 1.8 Blue sheep/sq.km. There was not significant change in population density from last 4 decades. An average 7 animals/herd (SD-5.5) were classified from twenty nine herds, sheep per herds varying from 1 to 37. Blue sheep has classified into sex ratio on an average 75 male/100females was recorded in study area. The sex ratio was slightly lower but not significantly different from the previous study. Population of Blue sheep was seen stable or not decrease even there was high poaching pressure, the reason may be reducing the number of predators by poison and poaching which has
supported to increase blue sheep population. Because of reducing the predators Wolf Canis lupus, Wild boar population was increasing drastically in high rate and we can observed wild boar above the tree line of DHR. The frequency of occurrence of different prey species in scats of different predators shows that, excluding zero values, the frequencies of different prey species were no significantly different (ö2= 10.3, df = 49, p > 0.05). Most of the scats samples (74%) of Snow leopard, Wolf, Common Leopard, Red fox's cover one prey species while two and three species were present in 18% and 8%, respectively. Barking deer Muntiacus muntjak was the most frequent (18%) of total diet composition of common leopards. Pika Ochotona roylei was the most frequent (28%), and Blue sheep was in second position for diet of snow leopards which cover 21% of total diet composition. 13% of diet covered non-food item such as soil, stones, and vegetable. Pika was most frequent on Wolf and Red fox diet which covered 32% and 30% respectively. There was good positive relationship between the scat density and Blue sheep consumption rate, increasing the scat density, increasing the Blue sheep consumption rate. Blue sheep preference by different predators such as Snow leopard, Common leopard, Wolf and Red fox were 20%, 6%, 13% and 2% of total prey species respectively.
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Blomqvist, L. (1979). The 1978 register for the captive population of snow leopards, Panthera uncia. International Zoo News, 26(7-8), 17–23.
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Blomqvist, L. (1980). The 1979 world register for the captive population of snow leopards, Panthera uncia. In L. Blomqvist (Ed.), International Pedigree Book of Snow Leopards (pp. 62–75). Helsinki: Helsinki Zoo.
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Zhang, L., Lian, X., Yang, X. (2020). Population density of snow leopards (Panthera Uncia) in the Yage Valley Region of the Sanjiangyuan National Park: Conservation Implications and future directions. Artic, Antartic and Alpine Research, 52(1), 541–550.
Abstract: Population-based studies on snow leopard (Panthera uncia) are of theoretical and practical sig- nificance for the conservation of alpine ecosystems, though geographic remoteness and isolation hinder surveys in many promising regions. The Sanjiangyuan National Park on the Tibetan Plateau is acknowledged as a main snow leopard habitat, but most of the region remains unexplored and unknown. We adopted a combined approach of route survey and camera trapping survey to explore the population density of snow leopard in the Yage Valley region of the Sanjiangyuan National Park. Results indicated that (1) large populations of blue sheep contributed to the major food supply for snow leopards, along with diverse prey species as dietary supplementations, and (2) a population density of four to six snow leopards per 100 km2 on the north bank was estimated, and nine to fourteen individuals within the valley core areas were identified. We also argue that under the potential impacts of hydropower dams, this valley ecosystem should be symbolized as a conservation hotspot and therefore merits prioritized conservation. We recommend further surveys combined with novel methods/techniques and advocate a sustainable ecotourism model for the first V-shaped valley along the Yangtze mainstream.
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Sharma, R. K., Sharma, K., Borchers, D., Bhatnagar, Y. V., Suryawanshi, K. S., Mishra, C. (2020). Spatial variation in population-density, movement and detectability of snow leopards in
2 a multiple use landscape in Spiti Valley, Trans-Himalaya. bioRxiv, .
Abstract: The endangered snow leopard Panthera uncia occurs in human use landscapes in the mountains of South and Central Asia. Conservationists generally agree that snow leopards must be conserved through a land-sharing approach, rather than land-sparing in the form of strictly protected areas. Effective conservation through land-sharing requires a good understanding of how snow leopards respond to human use of the landscape. Snow leopard density is expected to show spatial variation within a landscape because of variation in the intensity of human use and the quality of habitat. However, snow leopards have been difficult to enumerate and monitor. Variation in the density of snow leopards remains undocumented, and the impact of human use on their populations is poorly understood. We examined spatial variation in snow leopard density in Spiti Valley, an important snow leopard landscape in India, via spatially explicit capture recapture analysis of camera trap data. We camera trapped an area encompassing a minimum convex polygon of 953 km . We estimated an overall density of 0.49 (95% CI: 0.39-0.73) adult snow leopards per 100 km . Using AIC, our best model showed the density of snow leopards to depend on wild prey density, movement about activity centres to depend on altitude, and the expected number of encounters at the activity centre to depend on topography. Models that also used livestock biomass as a density covariate ranked second, but the effect of livestock was weak. Our results highlight the importance of maintaining high density pockets of wild prey populations in multiple use landscapes to enhance snow leopard conservation.
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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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Blomqvist, L. (1995). Three decades of Snow Leopards Panthera uncia in Captivity. Int.Zoo Yearbook, 34, 178–185.
Abstract: The author reports the status of the captive population of snow leopards over the last three decades. Genetic and demographic information is also provided. The captive population as of 1992 was 541 leopards. klf. I
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Blomqvist, L. (2003). The global snow leopard population in captivity 2001 (Vol. 8).
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