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Ale, S., Shrestha, B., and Jackson, R. (2014). On the status of Snow Leopard Panthera Uncia (Schreber 1775) in Annapurna, Nepal. Journal of Threatened Taxa, (6(3)), 5534–5543.
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Lama, R. P., Ghale, T. R., Suwal, M. K., Ranabhat, R., Regmi, G. R. (2018). First photographic evidence of Snow Leopard Panthera uncia (Mammalia: Carnivora: Felidae) outside current protected areas network in Nepal Himalaya. Journal of Threatened Taxa, , 12086–12090.
Abstract: The Snow Leopard Panthera uncia is a rare top predator of high-altitude ecosystems and insufficiently surveyed outside of protected areas in Nepal. We conducted a rapid camera-trapping survey to assess the presence of Snow Leopard in the Limi valley of Humla District. Three individuals were recorded in two camera locations offering the first photographic evidence of this elusive cat outside the protected area network of Nepal. In addition to Snow Leopard, the Blue Sheep Pseudois nayaur, Beech Marten Martes foina, Pika Ochotona spp. and different species of birds were also detected by camera-traps. More extensive surveys and monitoring are needed for reliably estimating the population size of Snow Leopard in the area. The most urgent needs are community-based conservation activities aimed at mitigating immediate threats of poaching, retaliatory killing, and rapid prey depletion to ensure the survival of this top predator in the Himalaya.
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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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Xu, A., Jiang, Z., Li, C., Guo, J., Da, S., Cui, Q., et al. (2008). Status and conservation of the snow leopard Panthera uncia in the Gouli Region, Kunlun Mountains, China (Vol. 42).
Abstract: The elusive snow leopard Panthera unica is a rare and little studied species in China. Over 1 March-15 May 2006 we conducted a survey for the snow leopard in the Gouli Region, East Burhanbuda Mountain, Kunlun Mountains, Qinghai Province, China, in an area of c. 300 km2 at altitudes of 4,000-4,700 m. We surveyed 29 linear transects with a total length of c. 440 km, and located a total of 72 traces (pug marks, scrapes and urine marks) of snow leopard along four of the transects. We obtained eight photographs of snow leopard from four of six camera traps. We also recorded 1,369 blue sheep, 156 Tibetan gazelles, 47 argali, 37 red deer and one male white-lipped deer. We evaluated human attitudes towards snow leopard by interviewing the heads of 27 of the 30 Tibetan households living in the study area. These local people did not consider that snow leopard is the main predator of their livestock, and thus there is little retaliatory killing. Prospects for the conservation of snow leopard in this area therefore appear to be good. We analysed the potential threats to the species and propose the establishment of a protected area for managing snow leopard and the fragile alpine ecosystem of this region. (c) 2008 Fauna & Flora International.
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Sanyal, O., Bashir, T., Rana, M., Chandan, P. (2023). First photographic record of the snow leopard Panthera uncia in Kishtwar High Altitude National Park, Jammu and Kashmir, India. Oryx, , 1–5.
Abstract: The snow leopard Panthera uncia is categorized as Vulnerable on the IUCN Red List. It is the least well-known of the large felids because of its shy and elusive nature and the inaccessible terrain it inhabits across the mountains of Central and South Asia. We report the first photographic record of the snow leopard in Kishtwar High Altitude National Park, India. During our camera-trapping surveys, conducted using a grid-based design, we obtained eight photographs of snow leopards, the first at 3,280 m altitude on 19 September 2022 and subsequent photographs over 3,004-3,878 m altitude. We identified at least four different individuals, establishing the species’ occurrence in Kiyar, Nanth and Renai catchments, with a capture rate of 0.123 ± SE 0.072 captures/100 trap-nights. ghts. We also recorded the presence of snow leopard prey species, including the Siberian ibex Capra sibirica, Himalayan musk deer Moschus leucogaster, long-tailed marmot Marmota caudata and pika Ochotona sp., identifying the area as potential snow leopard habitat. Given the location of Kishtwar High Altitude National Park, this record is significant for the overall snow leopard conservation landscape in India. We recommend a comprehensive study across the Kishtwar landscape to assess the occupancy, abundance, demography and movement patterns of the snow leopard and its prey. In addition, interactions between the snow leopard and pastoral communities should be assessed to understand the challenges facing the conservation and management of this important high-altitude region.
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Zhang, C., Ma, T., Ma, D. (2023). Status of the snow leopard Panthera uncia in the Qilian Mountains, Gansu Province, China. Oryx, , 1–6.
Abstract: Population density estimation is integral to the effective conservation and management of wildlife. The snow leopard Panthera uncia is categorized as Vulnerable on the IUCN Red List, and reliable information on its density is a prerequisite for its conservation and management. Little is known about the status of the snow leopard in the central and eastern Qilian Mountains, China. To address this, we estimated the population density of the snow leopard using a spatially explicit capture–recapture model based on camera trapping in Machang in the central and eastern Qilian Mountains during January–March 2019. We set up
40 camera traps and recorded 84 separate snow leopard captures over 3,024 trap-days. We identified 18 individual snow leopards and estimated their density to be 2.26/100 km. Our study provides baseline information on the snow leopard and the first population estimate for the species in the central and eastern Qilian Mountains.
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Alexander, J. S., Shi, K., Tallents, L. A., Riordan, P. (2015). On the high trail: examining determinants of site use by the Endangered snow leopard Panthera uncia in Qilianshan, China. Oryx, (Fauna & Flora International), 1–8.
Abstract: Abstract There is a need for simple and robust techniques for assessment and monitoring of populations of the Endangered snow leopard Panthera uncia to inform the de- velopment of action plans for snow leopard conservation. We explored the use of occupancy modelling to evaluate the influence of environmental and anthropogenic features on snow leopard site-use patterns. We conducted a camera trap survey across  km in Gansu Province, China, and used data from  camera traps to estimate probabilities of site use and detection using the single season occupancy model. We assessed the influence of three covariates on site use by snow leopards: elevation, the presence of blue sheep Pseudois nayaur and the presence of human disturb- ance (distance to roads). We recorded  captures of snow leopards over , trap-days, representing a mean capture success of . captures per  trap-days. Elevation had the strongest influence on site use, with the probability of site use increasing with altitude, whereas the influence of presence of prey and distance to roads was relatively weak. Our findings indicate the need for practical and robust tech- niques to appraise determinants of site use by snow leo- pards, especially in the context of the limited resources available for such work.
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Koju. N. P,, Bashyal, B., Pandey, B. P., Shah, S. N., Thami, S., Bleisch, W. V. (2020). First camera-trap record of the snow leopard Panthera uncia in Gaurishankar Conservation Area, Nepal. Oryx, , 1–4.
Abstract: The snow leopard Panthera uncia is the flagship species of the high mountains of the Himalayas. There is po- tentially continuous habitat for the snow leopard along the northern border of Nepal, but there is a gap in information about the snow leopard in Gaurishankar Conservation Area. Previous spatial analysis has suggested that the Lamabagar area in this Conservation Area could serve as a transbound- ary corridor for snow leopards, and that the area may con- nect local populations, creating a metapopulation. However, there has been no visual confirmation of the species in Lamabagar. We set !! infrared camera traps for " months in Lapchi Village of Gaurishankar Conservation Area, where blue sheep Pseudois nayaur, musk deer Moschus leucogaster and Himalayan tahr Hemitragus jemlahicus, all snow leopard prey species, had been observed. In November #$!% at &,!$$ m, ' km south-west of Lapchi Village, one camera recorded three images of a snow leopard, the first photographic evidence of the species in the Conservation Area. Sixteen other species of mammals were also recorded. Camera-trap records and sightings indicated a high abun- dance of Himalayan tahr, blue sheep and musk deer. Lapchi Village may be a potentially important corridor for snow leopard movement between the east and west of Nepal and northwards to Quomolongma National Park in China. However, plans for development in the region present in- creasing threats to this corridor. We recommend develop- ment of a transboundary conservation strategy for snow leopard conservation in this region, with participation of Nepal, China and international agencies.
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Rovero, F., Augugliaro, C., Havmoller, R. W., Groff, C., Zimmerman, F., Oberosler, V., Tenan, S. (2018). Co-occurrence of snow leopard Panthera uncia, Siberian ibex Capra sibirica and livestock: potential relationships and effects. Oryx, , 1–7.
Abstract: Understanding the impact of livestock on native
wildlife is of increasing conservation relevance. For the
Vulnerable snow leopard Panthera uncia, wild prey reduction,
intensifying human�wildlife conflicts and retaliatory
killings are severe threats potentially exacerbated by the
presence of livestock. Elucidating patterns of co-occurrence
of snow leopards, wild ungulate prey, and livestock, can be
used to assess the compatibility of pastoralism with conservation.
We used camera trapping to study the interactions of
livestock, Siberian ibex Capra sibirica and snow leopards in
a national park in the Altai mountains, Mongolia. We obtained
 detections of wild mammals and  of domestic
ungulates, dogs and humans. Snow leopards and Siberian
ibex were recorded  and  times, respectively. Co-occurrence
modelling showed that livestock had a higher estimated
occupancy (.) than ibex, whose occupancy was
lower in the presence of livestock (.) than in its absence
(.�. depending on scenarios modelled). Snow leopard
occupancy did not appear to be affected by the presence of
livestock or ibex but the robustness of such inference was
limited by uncertainty around the estimates. Although our
sampling at presumed snow leopard passing sites may have
led to fewer ibex detections, results indicate that livestock
may displace wild ungulates, but may not directly affect
the occurrence of snow leopards. Snow leopards could still
be threatened by livestock, as overstocking can trigger
human�carnivore conflicts and hamper the conservation
of large carnivores. Further research is needed to assess
the generality and strength of our results.
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Alexander, J. S., Gopalswamy, A. M., Shi, K., Riordan, P. (2015). Face Value: Towards Robust Estimates of Snow Leopard Densities. Plos One, .
Abstract: When densities of large carnivores fall below certain thresholds, dramatic ecological effects
can follow, leading to oversimplified ecosystems. Understanding the population status of
such species remains a major challenge as they occur in low densities and their ranges are
wide. This paper describes the use of non-invasive data collection techniques combined
with recent spatial capture-recapture methods to estimate the density of snow leopards
Panthera uncia. It also investigates the influence of environmental and human activity indicators
on their spatial distribution. A total of 60 camera traps were systematically set up during
a three-month period over a 480 km2 study area in Qilianshan National Nature Reserve,
Gansu Province, China. We recorded 76 separate snow leopard captures over 2,906 trapdays,
representing an average capture success of 2.62 captures/100 trap-days. We identified
a total number of 20 unique individuals from photographs and estimated snow leopard
density at 3.31 (SE = 1.01) individuals per 100 km2. Results of our simulation exercise indicate
that our estimates from the Spatial Capture Recapture models were not optimal to
respect to bias and precision (RMSEs for density parameters less or equal to 0.87). Our
results underline the critical challenge in achieving sufficient sample sizes of snow leopard
captures and recaptures. Possible performance improvements are discussed, principally by
optimising effective camera capture and photographic data quality.
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