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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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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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Alexander, S., A., Zhang, C., Shi, K., Riordan, P. (2016). A granular view of a snow leopard population using camera traps in Central China. Biological Conservation, (197), 27–31.
Abstract: Successful conservation of the endangered snow leopard (Panthera uncia) relies on the effectiveness of monitoring programmes. We present the results of a 19-month camera trap survey effort, conducted as part of a longterm study of the snow leopard population in Qilianshan National Nature Reserve of Gansu Province, China. Weassessed the minimumnumber of individual snowleopards and population density across different sampling periods using spatial capture–recapture methods. Between 2013–2014, we deployed 34 camera traps across an area of 375 km2, investing a total of 7133 trap-days effort. Weidentified a total number of 17–19 unique individuals
from photographs (10–12 adults, five sub-adults and two cubs). The total number of individuals identified and estimated density varied across sampling periods, between 10–15 individuals and 1.46–3.29 snow leopards per 100 km2 respectively. We demonstrate that snow leopard surveys of limited scale and conducted over short sampling periods only present partial views of a dynamic and transient system.We also underline the challenges in achieving a sufficient sample size of captures and recaptures to assess trends in snow leopard population size and/or density for policy and conservation decision-making
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Allen, M. L., Rovero, F., Oberosler, V., Augugliaro, C., Krofel, M. (2023). Effects of snow leopards (Panthera uncia) on olfactory communication of Pallas’s cats (Otocolobus manul) in the Altai Mountains, Mongolia. Behaviour, , 1–9.
Abstract: Olfactory communication is important for many solitary carnivores to delineate territories and communicate with potential mates and competitors. Pallas’s cats (Otocolobus manul) are small felids with little published research on their ecology and behaviour, including if they avoid or change behaviours due to dominant carnivores. We studied their olfactory communication and visitation at scent-marking sites using camera traps in two study areas in Mongolia. We documented four types of olfactory communication behaviours, and olfaction (sniffing) was the most frequent. Pallas’s cats used olfactory communication most frequently at sites that were not visited by snow leopards (Panthera uncia) and when they used communal scent-marking sites, they were more likely to use olfactory communication when a longer time had elapsed since the last visit by a snow leopard. This suggests that Pallas’s cats may reduce advertising their presence in response to occurrence of snow leopards, possibly to limit predation risk.
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Augugliaro, C., Paniccia, C., Janchivlamdan, C., Monti, I. E., Boldbaatar, T., Munkhtsog, B. (2019). Mammal inventory in the Mongolian Gobi, with the southeasternmost documented record of the Snow Leopard, Panthera uncia (Schreber, 1775), in the country. Check List, 15(4), 575–578.
Abstract: Studies on mammal diversity and distribution are an important source to develop conservation and management strategies.
The area located in southern Mongolia, encompassing the Alashan Plateau Semi-Desert and the Eastern Gobi Desert-Steppe ecoregions, is considered strategic for the conservation of threatened species. We surveyed the non-volant mammals in the Small Gobi-A Strictly Protected Area (SPA) and its surroundings, by using camera trapping, live trapping, and occasional sightings. We recorded 18 mammal species belonging to 9 families and 6 orders. Among them, 4 are globally threatened or near-threatened, 2 are included in the CITES Appendix I, and 2 are listed in the Appendix II. Moreover, we provide the southeasternmost record for the Snow Leopard (Panthera uncia) in Mongolia, supported by photographic evidence. Our study highlights the importance of this protected area to preserve rare, threatened, and elusive species.
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Bohnett, E., Faryabi, S. P., Lewison, R., An, L., Bian, X., Rajabi, A. M., Jahed, N., Rooyesh, H., Mills, E., Ramos, S., Mesnildrey, N., Perez, C. M. S., Taylor, J., Terentyev, V., Ostrowski, S. (2023). Human expertise combined with artificial intelligence improves performance of snow leopard camera trap studies. Global Ecology & Conservation, 41(e02350), 1–13.
Abstract: Camera trapping is the most widely used data collection method for estimating snow leopard (Panthera uncia) abundance; however, the accuracy of this method is limited by human observer errors from misclassifying individuals in camera trap images. We evaluated the extent Whiskerbook (www.whiskerbook.org), an artificial intelligence (AI) software, could reduce this error rate and enhance the accuracy of capture-recapture abundance estimates. Using 439 images of 34 captive snow leopard individuals, classification was performed by five observers with prior experience in individual snow leopard ID (“experts”) and five observers with no such experience (“novices”). The “expert” observers classified 35 out of 34 snow leopard individuals, on average erroneously splitting one individual into two, thus resulting in a higher number than true individuals. The success rate of experts was 90 %, with less than a 3 % error in estimating the population size in capture-recapture modeling. However, the “novice” observers successfully matched 71 % of encounters, recognizing 25 out of 34 individuals, underestimating the population by 25 %. It was found that expert observers significantly outperformed novice observers, making statistically fewer errors (Mann Whitney U test P = 0.01) and finding the true number of individuals (P = 0.01). These differences were contrasted with a previous study by Johansson et al. 2020, using the same subset of 16 individuals from European zoos. With the help of AI and the Whiskerbook platform, “experts” were able to match 87 % of encounters and identify 15 out of 16 individuals, with modeled estimates of 16 ± 1 individuals. In contrast, “novices” were 63 % accurate in matching encounters and identified 12 out of 16 individuals, modeling 12 ± 1 individuals that underestimated the population size by 12 %. When comparing the performance of observers using AI and the Whiskerbook platform to observers performing the tasks manually, we found that observers using Whiskerbook made significantly fewer errors in splitting one individual into two (P = 0.04). However, there were also a significantly higher number of combination errors, where two individuals were combined into one (P = 0.01). Specifically, combination errors were found to be made by “novices” (P = 0.04). Although AI benefited both expert and novice observers, expert observers outperformed novices. Our results suggest that AI effectively reduced the misclassification of individual snow leopards in camera trap studies, improving abundance estimates. However, even with AI support, expert observers were needed to obtain the most accurate estimates.
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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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Henschel, P., & Ray, J. (2003). Leopards in African Rainforests: Survey and Monitoring Techniques (Wildlife Conservation Society, Ed.).
Abstract: Monitoring Techniques Forest leopards have never been systematically surveyed in African forests, in spite of their potentially vital ecological role as the sole large mammalian predators in these systems. Because leopards are rarely seen in this habitat, and are difficult to survey using the most common techniques for assessing relative abundances of forest mammals, baseline knowledge of leopard ecology and responses to human disturbance in African forests remain largely unknown. This technical handbook sums up the experience gained during a two-year study of leopards by Philipp Henschel in the Lop‚ Reserve in Gabon, Central Africa, in 2001/2002, supplemented by additional experience from carnivore studies conducted by Justina Ray in southwestern Central African Republic and eastern Congo (Zaire) . The main focus of this effort has been to develop a protocol that can be used by fieldworkers across west and central Africa to estimate leopard densities in various forest types. In developing this manual, Henschel tested several indirect methods to assess leopard numbers in both logged and unlogged forests, with the main effort devoted to testing remote photography survey methods developed for tigers by Karanth (e.g., Karanth 1995, Karanth & Nichols 1998; 2000; 2002), and modifying them for the specific conditions characterizing African forest environments. This handbook summarizes the results of the field testing, and provides recommendations for techniques to assess leopard presence/absence, relative abundance, and densities in African forest sites. We briefly review the suitability of various methods for different study objectives and go into particular detail on remote photography survey methodology, adapting previously developed methods and sampling considerations specifically to the African forest environment. Finally, we briefly discuss how camera trapping may be used as a tool to survey other forest mammals. Developing a survey protocol for African leopards is a necessary first step towards a regional assessment and priority setting exercise targeted at forest leopards, similar to those carried out on large carnivores in Asian and South American forests.
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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).
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Jackson, R., Roe, J., Wangchuk, R., & Hunter, D. (2005). Surveying Snow Leopard Populations with Emphasis on Camera Trapping: A Handbook. Sonoma, California: The Snow Leopard Conservancy.
Abstract: This handbook provides an introduction to snow leopard population survey techniques, followed by a detailed account of camera trapping methods.During the 2002 through 2004 winter field seasons, the Snow Leopard Conservancy experimented with infrared camera trapping techniques to define a methodology suitable for the high altitude environment.
In 2001 and 2002, much of our time was spent familiarizing ourselves with various infrared camera traps, their operation and setup, and comparing the effectiveness of different models and sensor types. We placed infrared camera traps along frequently used travel corridors at or near scent-sprayed rocks (rock scents) and scrape sites within 16 km2 sampling cells between January and March in 2003 and 2004. A total of 66 and 49 captures of snow leopards were tallied during 2003 and 2004, resulting in an overall capture success of 8.91 and 5.63 individuals per 100 trap-nights, respectively. Capture probabilities ranged from 0.33 to 0.46. Density estimates ranged from 8.49 ± 0.22 individuals per 100 km2 in 2003 to 4.45 ± 0.16 in 2004, with the disparity between years largely attributed to different trapping densities. Snow leopard abundance estimates were calculated using the computer program CAPTURE.
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Jackson, R., Roe, J., Wangchuk, R., & Hunter, D. (2005). Surveying Snow Leopard Populations with Emphasis on Camera Trapping: A Handbook. Sonoma, California: The Snow Leopard Conservancy.
Abstract: This handbook provides an introduction to snow leopard population survey techniques, followed by a detailed account of camera trapping methods.During the 2002 through 2004 winter field seasons, the Snow Leopard Conservancy experimented with infrared camera trapping techniques to define a methodology suitable for the high altitude environment.
In 2001 and 2002, much of our time was spent familiarizing ourselves with various infrared camera traps, their operation and setup, and comparing the effectiveness of different models and sensor types. We placed infrared camera traps along frequently used travel corridors at or near scent-sprayed rocks (rock scents) and scrape sites within 16 km2 sampling cells between January and March in 2003 and 2004. A total of 66 and 49 captures of snow leopards were tallied during 2003 and 2004, resulting in an overall capture success of 8.91 and 5.63 individuals per 100 trap-nights, respectively. Capture probabilities ranged from 0.33 to 0.46. Density estimates ranged from 8.49 ± 0.22 individuals per 100 km2 in 2003 to 4.45 ± 0.16 in 2004, with the disparity between years largely attributed to different trapping densities. Snow leopard abundance estimates were calculated using the computer program CAPTURE.
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Jackson, R., Roe, J., Wangchuk, R., & Hunter, D. (2006). Estimating Snow Leopard Population Abundance Using Photography and Capture-Recapture Techniques (Vol. 34).
Abstract: Conservation and management of snow leopards (Uncia uncial) has largely relied on anecdotal evidence and presence-absence data due to their cryptic nature and the difficult terrain they inhabit. These methods generally lack the scientific rigor necessary to accurately estimate population size and monitor trends. We evaluated the use of photography in capture-mark-recapture (CMR) techniques for estimating snow leopard population abundance and density within Hemis National Park, Ladakh, India. We placed infrared camera traps along actively used travel paths, scent-sprayed rocks, and scrape sites within 16-30 kmý sampling grids in successive winters during January and March 2003-2004. We used head-on, oblique, and side-view camera configurations to obtain snow leopard photographs at varying body orientations. We calculated snow leopard abundance estimates using the program CAPTURE. We obtained a total of 66 and 49 snow leopard captures resulting in 8.91 and 5.63 individuals per 100 trap nights during 2003 and 2004, respectively. We identified snow leopards based on the distinct pelage patters located primarily on the forelimbs, flanks, and dorsal surface of the tail. Capture probabilities ranged from 0.33 to 0.67. Density estimates ranged from 8.49 (SE+0.22) individuals per 100 kmý in 2003 to 4.45 (SE+0.16) in 2004. We believe the density disparity between years is attributable to different trap density and placement rather than to an actual decline in population size. Our results suggest that photographic capture-mark-recapture sampling may be a useful tool for monitoring demographic patterns. However, we believe a larger sample size would be necessary for generating a statistically robust estimate of population density and abundance based on CMR models.
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Khanyari, M., Sanyal, O., Chandan, P., Bajaj, D., Sharma, C., Rana, M., Sharma, N., Bashir, T., Suryawanshi, K. (2024). A new dawn? Population baselines of snow leopards and other mammals of the Kishtwar High Altitude National Park, India. Integrative Conservation, , 1–10.
Abstract: Accurately assessing the status of threatened species requires reliable population estimates. Despite this necessity, only a small proportion of the global distribution range of the vulnerable snow leopard (Panthera uncia) has been systematically sampled. The Indian section of the Greater Himalayas, which includes Kishtwar High Altitude National Park (KHANP), harbours potential snow leopard habitat. Nevertheless, there has been limited ecological and conservation research focusing on species that are specific to KHANP, as well as limited research on the broader biodiversity of the Greater Himalayas. We used Spatially Explicit Capture‐Recapture (SECR) models to provide—to our knowledge—the first robust snow leopard population density and abundance estimates from KHANP. We also provide a Relative Abundance Index (RAI) for non‐volant mammals (excluding small rodents). Our study sampled three catchments within the Dachhan region of KHANP—Kibber, Nanth and Kiyar—using 44 cameras over a 45‐day period between May and June 2023. We identified four unique snow leopard individuals across 15 detections in nine camera locations. SECR analysis estimated a density of 0.50 snow leopards per 100 km2 (95% confidence interval: 0.13–1.86), corresponding to an abundance of four individual (4–9) adults. Camera trapping revealed a total of 16 mammal species, including the endangered Kashmir musk deer (Moschus cupreus). Marmots (Marmota caudata) had the highest RAI of 21.3 (±0.2). Although the estimated density and abundance of snow leopards in our study area had relatively wide 95% confidence intervals, our combined results of snow leopard densities and RAIs of prey species such as ibex and marmots indicate that KHANP is a potentially important area for snow leopards. Given the geopolitical history of Jammu and Kashmir in India, the region where KHANP is located, wildlife research remains a low priority. We hope our study encourages authorities to support further research. This study is an initial step towards evaluating the potential of KHANP as a conservation landscape under the Government of India's Project Snow Leopard.
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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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Li, X., Wei, C., Chen, X., Jia, D., Li, P., Liang, S., Jikmed, A., Gao, Y., Zhao, X., Chu, M., Sharma, K., Alexander, J. A., Lu, Z., Xiao, L. (2025). First large‑scale assessment of snow leopard population in China using existing data from multiple organizations. Biodiversity and Conservation, , 1–17.
Abstract: Abundance estimation of large carnivores is essential for their effective conservation planning, yet estimating population size is challenging due to their elusive and wide-ranging nature. China is estimated to encompass 60% of the snow leopard Panthera uncia habitat, making it a crucial pillar for global snow leopard conservation. However, no large-scale population assessment has been conducted despite scattered survey effort accumulating rapidly in recent years. This study combined and standardized existing camera trap sur-
vey data from 12 sites collected by four organizations during 2015 ~ 2021 to estimate snow leopard population in an area of 360,000 km2 on the Tibetan Plateau, China. The representativeness of existing survey was evaluated based on two habitat stratification approaches to achieve less biased population assessment. Spatially explicit capture-recapture (SECR) models were applied for snow leopard density estimation and the top-ranked model showed a significant positive correlation between conservation priority strata and density. An average snow leopard density of 0.90 /100 km2 (95% CI: 0.68 ~ 1.21 /100 km2) and a population size of 1,002 (95% CI: 755 ~ 1,341) individuals was estimated for the defined snow leopard habitat. Two more conservative estimates of 971 (95% CI: 732 ~ 1,287) and 978 (95% CI: 737 ~ 1,267) individuals were generated within two defined survey regions, in which our data had higher representativity. This study presents a practical approach to synthesize existing population survey data for large-scale population assessments of individually identifiable species. The estimated number represents 11 ~ 21% of the global snow leopard population, indicating high conservation value of this region.
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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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Ming, M. (2006). Camera trapping on snow leopards in the Muzat Valley, Reserve, Xinjiang, P.R. China (October-December 2005).
Abstract: The main purpose of this work was to study the use of infrared trapping cameras to estimate Snow Leopard 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 Muzat Valley adjacent to the Tomur Nature Reserve in Xinjiang Province. We expended approximately 2094 trap days total. At least 32 pictures of Snow Leopards, 22 pictures of other wild species and 72 pictures of livestock were taken in the Muzat Valley. Meanwhile, 20 transects were run and 31 feces sample were collected. We also observed the behavior of ibex for 77.3 hours and found a total of approximately 264 ibexes in the research area.
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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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Mueen, Q. H., Thuktan, T., Khanyari, M., Khaleel, M. (2024). Camera trapping survey for snow leopard provides first photographic record of Woolly Flying Squirrel from Kishtwar Himalayas, India. SL Reports, 3, 9–12.
Abstract: The Woolly Flying Squirrel (Eupetaurus cinereus), considered native to Northern Pakistan and North- Western Himalaya has remained an elusive species because of its presence in high mountain rocky cliffs near the tree line. These montane habitats have remained inaccessible for research thus making it difficult to study their distribution. Here, we present the first photographic evidence of the Woolly Flying Squirrel from the Kishtwar region of Jammu and Kashmir obtained from camera-traps placed to detect snow leopard presence and distribution. This record adds valuable presence information to the existing distribution range of the species from the North-Western Himalaya.
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Oberosler, V., Tenan, S., Groff, C., Krofel, M., Augugliaro, C., Munkhtsog, B., Rovero, F. (2021). First spatially‐explicit density estimate for a snow leopard population in the Altai Mountains. Biodiversity and Conservation, , 15.
Abstract: The snow leopard Panthera uncia is an elusive and globally-threatened apex predator occurring in the mountain ranges of central Asia. As with other large carnivores, gaps in data on its distribution and abundance still persist. Moreover, available density estimates are often based on inadequate sampling designs or analytical approaches. Here, we used camera trapping across a vast mountainous area (area of the sampling frame 850 km2; analysed habitat extent 2600 km2) and spatially-explicit capture-recapture (SECR) models to provide, to our knowledge, the first robust snow leopard population density estimate for the Altai Mountains. This region is considered one of the most important conservation areas for snow leopards, representing a vast portion of suitable habitat and a key ecological corridor. We also provide estimates of the scale parameter (σ) that reflects ranging behaviour (activity range) and baseline encounter probability, and investigated potential drivers of density and related parameters by assessing their associations with anthropogenic and environmental factors. Sampling yielded 9729 images of snow leopards corresponding to 224 independent detections that belonged to a minimum of 23 identified adult individuals. SECR analysis resulted in an overall density of 1.31 individuals/100 km2 (1.15%–1.50 95% CI), which was positively correlated with terrain slope. This estimate falls within the mid-values of the range of density estimates for the species globally. We estimated significantly different activity range size for females and males (79 and 329 km2, respectively). Base- line encounter probability was negatively associated with anthropogenic activity. Our study contributes to on-going efforts to produce robust global estimates of population abundance for this top carnivore.
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Rode, J., Lambert, C., Marescot, L., Chaix, B., Beesau, J., Bastian, S., Kyrbashev, J., Cabanat, A.L. (2021). Population monitoring of snow leopards using camera trapping in Naryn State Nature Reserve, Kyrgyzstan, between 2016 and 2019. Global Ecology and Conservation, 31(e01850), 1–6.
Abstract: Four field seasons of snow leopard (Panthera uncia) camera trapping inside Naryn State Nature Reserve, Kyrgyzstan, performed thanks to citizen science expeditions, allowed detecting a minimal population of five adults, caught every year with an equilibrated sex ratio (1.5:1) and reproduction: five cubs or subadults have been identified from three litters of two different females. Crossings were observed one to three times a year, in front of most camera traps, and several times a month in front of one of them. Overlap of adults’ minimal territories was observed in front of several camera traps, regardless of their sex. Significant snow leopard presence was detected in the buffer area and at Ulan area which is situated at the reserve border. To avoid poaching on this apex predator and its preys, extending the more stringent protection measures of the core zone to both the Southern buffer area and land adjacent to Ulan is recommended.
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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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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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Sharma, C., Thuktan, T., Tobge, R., Angrup, D., Chhering, D., Sherab, T., Chhering, T., Bajaj, D., Khanyari, M., Suryawanshi, K. (2024). First Photographic Evidence of Pallas’s Cat (Otocolobus manul) from Himachal Pradesh, India. SL Reports, 3, 79–87.
Abstract: While the study of carnivore ecology has made significant progress, our knowledge of small cats remains limited. For some species, their distribution remains largely unknown. We report the first photographic evidence of the Pallas’s cat in Himachal Pradesh, India. Of the 56 camera traps placed for snow leopard population estimation across Kinnaur region between March-May 2024, we recorded Pallas’s cat at three camera trap sites with 19 images from three instances during morning hours. These captures were at an elevation of 3900–4100 meters in rocky habitats largely dominated by boulders and cliffs. Sympatric carnivores captured were snow leopard (Panthera uncia), red fox (Vulpes vulpes), stone marten (Martes foina) and free-ranging dogs. This discovery not only extends the known distribution of Pallas’s cat but also underscores the urgent need for focused conservation research and action in this region, especially given the presence of free-ranging dogs. This can be achieved through coordinated, landscape level and trans-boundary efforts.
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Sharma, K., Fiechter, M., George, T., Young, J., Alexander, J.
S., Bijoor, Suryawanshi, K., Mishra, C. (2020). Conservation and people: Towards an ethical code of conduct for
the use of camera traps in wildlife research. Ecological Solutions and Evidence, , 1–6.
Abstract: 1. Camera trapping is a widely employed tool in wildlife
research, used to estimate animal abundances, understand animal
movement, assess species richness and under- stand animal behaviour. In
addition to images of wild animals, research cameras often record human
images, inadvertently capturing behaviours ranging from innocuous
actions to potentially serious crimes.
2. With the increasing use of camera traps, there is an urgent need to
reflect on how researchers should deal with human images caught on
cameras. On the one hand, it is important to respect the privacy of
individuals caught on cameras, while, on the other hand, there is a
larger public duty to report illegal activity. This creates ethical
dilemmas for researchers.
3. Here, based on our camera-trap research on snow leopards Panthera
uncia, we outline a general code of conduct to help improve the practice
of camera trap based research and help researchers better navigate the
ethical-legal tightrope of this important research tool.
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