|
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.
|
|
Mallon, D. (1993). Snow Leopard in Kanji Wildlife Reserve, Ladakh (Vol. xi). Seattle: Islt.
|
|
McCarthy, T., & Munkhtsog, B. (1997). Preliminary Assessment of Snow Leopard Sign Surveys in Mongolia. In R.Jackson, & A.Ahmad (Eds.), (pp. 57–65). Lahore, Pakistan: Islt.
|
Ming, M., XuFeng, Turghan, M., & Shoujin, Y. (2004). Report on Snow Leopard (Uncia uncia) Surveys in Tomur, Xinjiang, China 2004. Xinjian, P.R. of China: Xinjiang Snow Leopard Group; Xinjiang Institute of Ecology and Geography; Chinese Academy of Science.
Abstract: The Snow Leopard (Uncia uncia) investigation in the Tomur area is the second step of the “Project of Snow Leopard Study in Xinjiang”. In this part of the project, we collected information on the distribution , abundance and population size of the snow leopard in this area. The investigation lasted for 3 weeks, between October 17 and November 7th, 2004. During the 22 days of field work, we surveyed 4 different places in Wensu County, Aksu District: e.g. Pochenzi and the Muzat River area, Bozdun and the Little Kuzbay River area, Yinyar and the Tomur River area, Taglak and the Qiong Tailan River area. The 4 main areas, along with a few other valleys, covered most of the Tomur National Conservation Zone. In total, we ran 42 transects. In 15 transects, we found signs left by snow leopards. We also collected 15 fecal samples for diet analysis. This time we interviewed nearly 90 local people from different nationalities: e.g. Han (Chinese), Uygur and Kyrgyz people, including herdsmen, geologists, mineworkers, drivers, veterinarians, businessmen, forest officials, soldiers and policemen. They provided us with an array of information on the historical and current distribution and abundance of the snow leopard in this area.
|
Mishra, C., Madhusudan, M. D., & Datta, A. (2006). Mammals of the high altitudes of western Arunachal Pradesh, eastern Himalaya: an assessment of threats and conservation needs (Vol. 40).
Abstract: The high altitudes of Arunachal Pradesh,India, located in the Eastern Himalaya biodiversity hotspot, remain zoologically unexplored and unprotected. We report results of recent mammal surveys in the high altitude habitats of western Arunachal Pradesh. A total of 35 mammal species (including 12 carnivores, 10 ungulates and 5 primates) were recorded, of which 13 are categorized as Endangered or Vulnerable on the IUCN Red List. One species of primate, the Arunachal macaque Macaca munzala, is new to science and the Chinese goral Nemorhaedus caudatus is a new addition to the ungulate fauna of the Indian subcontinent. We documented peoples' dependence on natural resources for grazing and extraction of timber and medicinal plants. The region's mammals are threatened by widespread hunting. The snow leopard Uncia uncia and dhole Cuon alpinus are also persecuted in retaliation for livestock depredation. The tiger Panthera tigris, earlier reported from the lower valleys, is now apparently extinct there, and range reductions over the last two decades are reported for bharal Pseudois nayaur and musk deer Moschus sp.. Based on mammal species richness, extent of high altitude habitat, and levels of anthropogenic disturbance, we identified a potential site for the creation of Arunachal's first high altitude wildlife reserve (815 km2). Community-based efforts that provide incentives for conservation-friendly practices could work in this area, and conservation awareness programmes are required, not just amongst the local communities and schools but for politicians, bureaucrats and the army.
|
|
Qiseng, Y. (1994). Further Study on the Geographical Distribution and Conservation of Snow Leopard in Qinghai, China. In J.L.Fox, & D.Jizeng (Eds.), (pp. 73–78). Usa: Islt.
|
|
Schaller, G. (1986). Surveys of Mountain Wildlife in China, Report # 4.
|
|
Schaller, G. (1987). Surveys of Mountain Wildlife in China, Report # 6.
|
Schaller, G. B. (1987). Status of large mammals in the Taxkorgan Reserve, Xinjiang, China. Biological-Conservation, 42(1), 53–71.
Abstract: A status survey of large mammals was conducted in the W half of 14 000 km“SUP 2” Taxkorgan Reserve. Only one viable population of fewer than 150 Marco Polo sheep Ovis ammon poli survives; it appears to be augmented by adult males from Russia and Afghanistan during the winter rut. Asiatic ibex Capra ibex occur primarily in the western part of the reserve and blue sheep Pseudois nayaur – the most abundant wild ungulate – in the E and SE parts. The 2 species overlap in the area of contact. Counts revealed an average wild ungulate density of 0.34 animals km“SUP -2”. Snow leopard Panthera uncia were rare, with possibly 50-75 in the reserve, as were wolves Canis lupus and brown bear Ursus arctos. The principal spring food of snow leopard was blue sheep (60%) and marmot (29%). Local people have greatly decimated wildlife. Overgrazing by livestock and overuse of shrubs for fuelwood is turning this arid steppe habitat into desert. -from Authors
|
|
Schaller, G. B., Tserendeleg, J., & Amarsana, G. (1994). Observations on snow leopards in Mongolia. In J.Fox, & D.Jizeng (Eds.), (pp. 33–42). Usa: Islt.
|
|
Schaller, G. B., Hong, L., Talipu, J., & Mingjiang, R. Q. (1989). The Snow Leopard in Xinjiang, China (Vol. winter). Seattle: Islt.
|
|
Schaller, G. (1988). Wildlife Survey in Tibet, Report #8.
|
|
Tserendeleg, J. (1994). On Protection and Survey of Snow Leopards in Mongolia. In J.L.Fox, & D.Jizeng (Eds.), (pp. 43–46). Usa: Islt.
|
|
Wikramanayake, E. Tracking snow leopard and blue sheep, WWF conservationist Eric Wikramanayake goes on a wildlife survey in Bhutan.
|
|
Yanfa, L., & Bangjie, T. (1988). A Preliminary Study on the Geographical Distribution of Snow Leopards in China. In H.Freeman (Ed.), (pp. 51–63). Interanational Snow Leopard Trust and The Wildlife Institute of India.
|
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.
|
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.
|
