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Mallon, D. (1984). The snow leopard in Ladakh. International Pedigree Book of Snow Leopards, 4, 23–37.
Abstract: Reports on 1 summer survey and four winter surveys covering some 3100 km in Ladakh, India. Reports on snow leopard sign commonly found, distribution, prey, attacks on livestock and peoples reaction, mortality factors and conservation status. Suggest recomendations for preventing unnecessary killing of snow leopards and estimates population of 100 to 200 snow leopards in Ladakh
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Kreuzberg, E., Esipov, A., Bykova, E., & Vashetko, E. (2000). Number, Distribution and Status of Habitats for Snow Leopard in Gissar Nature Reserve and Neighboring Areas (Vol. xvi). Seattle, Wa: Islt.
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Koshkarev, E. P. (1992). Range Structure, Numbers and Population Status of the Snow Leopard in the Tien Shan (Vol. x). Seattle: International Snow Leopard Trust.
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Koshkarev, E. (1998). Snow leopard along the border of Russia and Mongolia. Cat News, 28, 12–14.
Abstract: The author discusses the distribution of snow leopards along the border of Russia and Mongolia. The range extension of the leopard indicates their ability to cross desert areas that separate mountain habitats.habitat; range extension; scat analysis; techniques; tracks/tracking | snow leopard
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Khan, A. (1998). Snow Leopard: Integral to Chitral Gol National Park (Vol. xvi). Seattle: Islt.
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International Snow Leopard Trust. (1992). Assessing Presence, relative abundance and habitat of snow leopards and their prey: a handbook of field techniques.
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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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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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Kyes, R., & Chalise, M. K. (2005). Assessing the Status of the Snow Leopard Population in Langtang National Park, Nepal.
Abstract: This project is part of an ongoing snow leopard study established in 2003 with support from the ISLT. The study involves a multifaceted approach designed to provide important baseline data on the status of the snow leopard population in Langtang National Park (LNP), Nepal and to generate long-term support and commitment to the conservation of snow leopards in the park. The specific aims include: 1) conducting a population survey of the snow leopards in LNP, focusing on distribution and abundance; 2) assessing the status of prey species populations in the park; and 3) providing educational outreach programs on snow leopard conservation for local school children (K-8) living in the park. During the 2004 study period, snow leopard signs were observed (including pugmarks and scats) although somewhat fewer than in 2003. Similarly, the average herd size of the snow leopards' primary prey species in LNP (the Himalayan thar) was a bit lower than in 2003. There is speculation that the thar populations and the snow leopards may be moving to more remotes areas of the park perhaps in response to increasing pressure from domestic livestock grazing. This possibility is being addressed during the 2005 study period.
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Ming, M., Chundawat R.S., Jumabay, K., Wu, Y., Aizeizi, Q., & Zhu, M. H. (2006). Camera trapping of snow leopards for the photo capture rate and population size in the Muzat Valley of Tianshan Mountains. Acta Theriologica Sinica, 52(4), 788–793.
Abstract: The main purpose of this work was to study the use of infrared trapping cameras to estimate snow leopard Uncia uncia population size in a specific study area. This is the first time a study of this nature has taken place in China. During 71 days of field work, a total of 36 cameras were set up in five different small vales of the Muzat Valley adjacent to the Tomur Nature Reserve in Xinjiang Province, E80ø35' – 81ø00' and N42ø00' – 42ø10', elevation 2'300 – 3'000 m, from 18th October to 27th December 2005. We expended approximately 2094 trap days and nights total (c. 50'256 hours). At least 32 pictures of snow leopards, 22 pictures of other wild species (e.g. chukor, wild pig, ibex, red fox, cape hare) and 72 pictures of livestock were taken by the passive Cam Trakker (CT) train monitor in about 16 points of the Muzat Valley. The movement distance of snow leopard was 3-10 km/day. And the capture rate or photographic rate of snow leopard was 1.53%. Meanwhile, 20 transects were run and 31 feces sample were collected. According to 32 photos, photographic rate and sign survey after snowing on the spot, were about 5-8 individuals of snow leopards in the research area, and the minimum density of snow leopard in Muzat Valley was 2.0 – 3.2 individuals/100 km2. We observed the behavior of ibex for 77.3 hours, and found about 20 groups and a total of approximately 264 ibexes in the research area.
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