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Namgay, K. (2007). Snow Leopard and Prey Population Conservation in Bhutan.
Abstract: Snow leopard conservation work in Bhutan dates back to 1999 and 2000 when the International Snow Leopard Trust-in collaboration with the Royal Government of Bhutan and World Wildlife Fund-initiated a training workshop. More than 30 government staff were trained in SLIMS survey techniques. As a part of the training exercise, a preliminary survey on snow leopard was also carried out using the SLIMS methods in Jigme Dorji Wangchuck National Park. Based on the survey results, we estimated there was a population of 100 snow leopards in the wild and 10,000 km2 of habitat. In 2005, World Wildlife Fund (WWF) organized the WWF/South Asia Regional Workshop on Snow leopard Conservation in Bhutan. Both regional (Bhutan, India, China, Nepal and Pakistan) and international experts revisited the snow leopard programs and developed a work plan for the overall conservation of the snow leopard in the region. This led to WWF's Regional Snow leopard Conservation Strategy. WWF is pleased to submit our final report to the International Snow Leopard Trust on the oneyear, $8,000 grant in support of Snow Leopard and Prey Population Conservation in Bhutan. With the support of the Snow Leopard Trust, we have made great strides towards achieving our goal for this project: To determine the current status of snow leopard and ungulate prey populations in prime snow leopard habitats. Major accomplishments and activities completed thanks to the generous support of the International Snow Leopard Trust include:
Signed of a Terms of Reference between Royal Government, International Snow Leopard Trust – India, World Wildlife Fund and International Snow Leopard Trust -US; Developed a joint revised project work plan; and Purchased basic field supplies and equipment needed for the surveys planned. Keywords: 2000; 30; activities; activity; asia; Bhutan; China; conservation; dates; Dorji; field; government; habitat; habitats; India; International; International-Snow-Leopard-Trust; international snow leopard trust; Jigme; Jigme-Dorji; leopard; leopards; methods; national; National-park; national park; Nepal; Pakistan; park; plan; population; populations; prey; program; programs; project; region; regional; Report; Slims; snow; snow-leopard; snow-leopards; snow leopard; snow leopards; staff; status; strategy; Support; survey; surveys; techniques; training; trust; ungulate; us; using; wild; wildlife; work; workshop; world-wildlife-fund; world wildlife fund; Wwf
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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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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.
Keywords: anthropogenic; area; Arunachal; assessment; awareness; bharal; biodiversity; carnivore; carnivores; community; community-based; conservation; deer; depredation; dhole; endangered; extinct; fauna; goral; grazing; habitat; habitats; High; Himalaya; hunting; incentives; India; indian; Iucn; leopard; livestock; livestock-depredation; livestock depredation; local; mammals; musk; musk-deer; nayaur; panthera; people; peoples; plant; plants; potential; Pseudois; Pseudois-nayaur; pseudois nayaur; range; recent; region; Report; reserve; resource; schools; snow; snow-leopard; snow leopard; species; survey; surveys; threat; threatened; threats; tiger; uncia; Uncia-uncia; Uncia uncia; ungulate; ungulates; valley; wildlife; work; Panthera-tigris; tigris
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Wikramanayake, E. Tracking snow leopard and blue sheep, WWF conservationist Eric Wikramanayake goes on a wildlife survey in Bhutan.
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Jackson, R. (1997). Bhutan Workshop: Thimpu, Land of the Thunder Dragon (Vol. xv). Seattle, Wa: Islt.
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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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Jackson, R., Roe, J., Wangchuk, R., & Hunter, D. (2005). Camera-Trapping of Snow Leopards. Cat News, 42(Spring), 19–21.
Abstract: Solitary felids like tigers and snow leopards are notoriously difficult to enumerate, and indirect techniques like pugmark surveys often produce ambiguous information that is difficult to interpret because many factors influence marking behavior and frequency (Ahlborn & Jackson 1988). Considering the snow leopard's rugged habitat, it is not surprising then that information on its current status and occupied range is very limited. We adapted the camera-trapping techniques pioneered by Ullas Karanth and his associates for counting Bengal tigers to the census taking of snow leopards in the Rumbak watershed of the India's Hemis High Altitude National Park (HNP), located in Ladakh near Leh (76ø 50' to 77ø 45' East; 33ø 15' to 34ø 20'North).
Keywords: camera trapping; snow; snow leopards; snow leopard; snow-leopards; snow-leopard; leopards; leopard; felids; tigers; tiger; techniques; surveys; survey; information; factor; marking; behavior; Ahlborn; Jackson; habitat; status; range; census; India; Hemis; High; national; national park; National-park; park; Ladakh; leh
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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.
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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.
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Jackson, R. (1994). Second SLIMS Workshop Held (Vol. xii). Seattle, WA: Islt.
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