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Villarrubia, C., & Jackson, R. (1994). Snow Leopard Conservation on a Regional Basis: Elements in Planning Protected Areas. In J.L.Fox, & D.Jizeng (Eds.), (pp. 253–263). Usa: Islt.
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Wikramanayake, E., Moktan, V., Aziz, T., Khaling, S., Khan, A., & Tshering, D. (2006). The WWF Snow Leopard Action Strategy for the Himalayan Region.
Abstract: As a 'flagship' and 'umbrella' species the snow leopard can be a unifying biological feature to
raise awareness of its plight and the need for conservation, which will benefit other facets of Himalayan
biodiversity as well. Some studies of snow leopards have been conducted in the Himalayan region. But,
because of its elusive nature and preference for remote and inaccessible habitat, knowledge of the
ecology and behaviour of this mystical montane predator is scant. The available information, however,
suggests that snow leopards occur at low densities and large areas of habitat are required to conserve
a viable population. Thus, many researchers and conservationists have advocated landscape-scale
approaches to conservation within a regional context, rather than focusing on individual protected areas.
While the issues are regional, the WWF's in the region have developed 5-year strategic actions and
activities, using the regional strategies as a touchstone, which will be implemented at national levels.
The WWF's will develop proposals based on these strategic actions, with estimated budgets, for use by
the network for funding and fund-raising. WWF also recognizes the need to collaborate and coordinate
within the network and with other organizations in the region to achieve conservation goals in an
efficient manner, and will form a working group to coordinate activities and monitor progress.
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McCarthy, T., Murray, K., Sharma, K., & Johansson, O. (2010). Preliminary results of a long-term study of snow leopards in South Gobi, Mongolia. Cat News, Autumn(53), 15–19.
Abstract: Snow leopards Panthera uncia are under threat across their range and require urgent conservation actions based on sound science. However, their remote habitat and cryptic nature make them inherently difficult to study and past attempts have provided insufficient information upon which to base effective conservation. Further, there has been no statistically-reliable and cost-effective method available to monitor snow leopard populations, focus conservation effort on key populations, or assess conservation impacts. To address these multiple information needs, Panthera, Snow Leopard Trust, and Snow Leopard Conservation Fund, launched an ambitious long-term study in Mongolia’s South Gobi province in 2008. To date, 10 snow leo-pards have been fitted with GPS-satellite collars to provide information on basic snow leopard ecology. Using 2,443 locations we calculated MCP home ranges of 150 – 938 km2, with substantial overlap between individuals. Exploratory movements outside typical snow leopard habitat have been observed. Trials of camera trapping, fecal genetics, and occupancy modeling, have been completed. Each method ex-hibits promise, and limitations, as potential monitoring tools for this elusive species.
Keywords: snow leopard, Mongolia, monitor, population, Panthera, Snow Leopard Trust, Snow Leopard Conservation Fund, South Gobi, ecology, radio collar, GPS-satellite collar, home range, camera trapping, fecal genetics, occupancy modeling
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Sharma, S., Thapa, K., Chalise, M., Dutta, T., Bhatnagar, Y.V., McCarthy, T. (2006). The snow leopard in Himalaya: A step towards their conservation by studying their distribution, marking habitat selection, coexistence with other predators, and wild prey-livestock-predator interaction. Conservation Biology in Asia, , 184–196.
Abstract: Snow leopard (Uncia uncial) is a flagship species of the Himalaya. Very few studies have been done on the ecology of this species in the Himalaya. This paper presents an overview of four studies conducted on snow leopards in Nepal and India, dealing with various aspects of snow leopard ecology including their status assessment, making behaviour, habitat selection, food habits, and impact on livestock. The information generated by these studies is useful in planning effective conservation and management strategies for this endangered top predator of high mountains.
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Suryawanshi, K. R., Khanyari, M., Sharma, K., Lkhagvajav, P., Mishra, C. (2019). Sampling bias in snow leopard population estimation studies. Population Eccology, , 1–9.
Abstract: Accurate assessments of the status of threatened species and their conservation
planning require reliable estimation of their global populations and robust monitoring
of local population trends. We assessed the adequacy and suitability of studies
in reliably estimating the global snow leopard (Panthera uncia) population. We
compiled a dataset of all the peer-reviewed published literature on snow leopard
population estimation. Metadata analysis showed estimates of snow leopard density
to be a negative exponential function of area, suggesting that study areas have generally
been too small for accurate density estimation, and sampling has often been
biased towards the best habitats. Published studies are restricted to six of the
12 range countries, covering only 0.3�0.9% of the presumed global range of the
species. Re-sampling of camera trap data from a relatively large study site
(c.1684 km2) showed that small-sized study areas together with a bias towards
good quality habitats in existing studies may have overestimated densities by up to
five times. We conclude that current information is biased and inadequate for generating
a reliable global population estimate of snow leopards. To develop a rigorous
and useful baseline and to avoid pitfalls, there is an urgent need for
(a) refinement of sampling and analytical protocols for population estimation of
snow leopards (b) agreement and coordinated use of standardized sampling protocols
amongst researchers and governments across the range, and (c) sampling
larger and under-represented areas of the snow leopard's global range.
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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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Mallon, D. P. (1988). A Further Report on The Snow Leopard in Ladakh. In H.Freeman (Ed.), (pp. 89–97). India: Snow Leopard Trust and Wildlife Institute of India.
Abstract: A detailed knowledge of the ecology of a species is fundemental to the drawing up of effective conservation measures. One aim of the current project was to identify good areas of snow leopard habitatand evaluate them for possible inclusion in the Protected Area Network. Several good areas were surveyed and an outstanding area identified, and included in a report to the Chief Wildlife Warden.
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Fox, J. L. (1991). Wildlife Ecology Workshop Held in Indias Himalaya Region (Vol. ix). Seattle: Islt.
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Jackson, P. (1997). The Snow Leopard: A Flagship for Biodiversity in the Mountains of Central Asia. In R.Jackson (Ed.), (pp. 3–7). Lahore, Pakistan: Allied Press.
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Jackson, R. (1992). Species Survival Commission Plan for Snow Leopard.
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