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Author |
Jackson, R.; Roe, J.; Wangchuk, R.; Hunter, D. |
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Title |
Camera-Trapping of Snow Leopards |
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Journal Article |
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2005 |
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Cat News |
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42 |
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19-21 |
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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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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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SLN @ rana @ 1017 |
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475 |
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Thapa, K., Pradhan, N, M, B., Barker, J., Dhakal, M., Bhandari, A, R., Gurung, G, S., Rai, D, P., Thapa, G, J., Shrestha, S., Singh, G, R. |
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High elevation record of a leopard cat in the Kangchenjunga Conservation Area, Nepal |
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2013 |
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Cat News |
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No 58 |
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26-27 |
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leopard cat, camera trapping survey, Nepal |
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During a camera trapping survey in Khambachen valley of Kangchenjunga Conservation
Area KCA from 24 April to 26 May 2012 we camera trapped one leopard cat
Prionailurus bengalensis at an altitude of 4,474 meter. This is probably the highest
altitudinal record for the species in its range. Additionally, one melanistic leopard
Panthera pardus was captured at an altitude of 4,300 m, which is probably as well the
highest documented record in the country. Yet at this stage, no obvious reason can
explain these unusual high records for both species, thus more surveys are recommended
for this region. |
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SLN @ rakhee @ |
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1394 |
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Alexander, J. S., Shi, K., Tallents, L. A., Riordan, P. |
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Title |
On the high trail: examining determinants of site use by the Endangered snow leopard Panthera uncia in Qilianshan, China |
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2015 |
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Oryx |
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Fauna & Flora International |
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1-8 |
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Camera Trap, China, Detection Probability, Occupancy Modelling, Panthera Uncia, Site use, Snow Leopard |
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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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SLN @ rakhee @ |
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1433 |
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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. |
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Title |
Human expertise combined with artificial intelligence improves performance of snow leopard camera trap studies |
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Journal Article |
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2023 |
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Global Ecology & Conservation |
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41 |
Issue ![sorted by Issue field, descending order (down)](img/sort_desc.gif) |
e02350 |
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1-13 |
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Snow leopard, Artificial intelligence, Camera trap misclassification, individual ID, HotSpotter |
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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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1715 |
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Rode, J., Lambert, C., Marescot, L., Chaix, B., Beesau, J., Bastian, S., Kyrbashev, J., Cabanat, A.L. |
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Population monitoring of snow leopards using camera trapping in Naryn State Nature Reserve, Kyrgyzstan, between 2016 and 2019 |
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Journal Article |
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2021 |
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Global Ecology and Conservation |
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31 |
Issue ![sorted by Issue field, descending order (down)](img/sort_desc.gif) |
e01850 |
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1-6 |
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Snow leopard, camera trapping, Citizen science, Kyrgyzstan |
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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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1660 |
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Author |
Ale, S., Shrestha, B., and Jackson, R. |
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On the status of Snow Leopard Panthera Uncia (Schreber 1775) in Annapurna, Nepal |
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2014 |
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Journal of Threatened Taxa |
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6(3) |
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5534-5543 |
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Annapurna, Blue Sheep, Buddhism, camera-trapping, Himalayas, Mustang, sign-survey, Snow Leopard. |
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SLN @ rakhee @ |
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1407 |
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Author |
Sharma, R. |
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Of Men and Mountain Ghosts: Glimpses from the Rooftop of the World |
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2010 |
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GEO |
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3 |
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6 |
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56-67 |
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snow leopard, camera trap, Spiti, India, Sharma |
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Catching a glimpse of a snow leopard is a rare and exciting event for anyone. For researchers, hideen camera traps have become a vital tool in their work. |
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GEO International |
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India |
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SLN @ rana @ |
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1139 |
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McCarthy, T.; Murray, K.; Sharma, K.; Johansson, O. |
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Preliminary results of a long-term study of snow leopards in South Gobi, Mongolia |
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2010 |
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Cat News |
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Autumn |
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53 |
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15-19 |
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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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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. |
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1151 |
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Ming, M.; Chundawat R.S.; Jumabay, K.; Wu, Y.; Aizeizi, Q.; Zhu, M.H. |
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Camera trapping of snow leopards for the photo capture rate and population size in the Muzat Valley of Tianshan Mountains |
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2006 |
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Acta Theriologica Sinica |
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52 |
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4 |
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788-793 |
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behavior; camera trapping; capture; China; Chinese; density; feces; fox; ibex; infrared trapping cameras; livestock; photo; population; research; reserve; sign; snow leopard; survey; Tianshan Mountains; Tomur; transect; Uncia uncia; Xinjiang |
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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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SLN @ rana @ 971 |
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683 |
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Augugliaro, C., Paniccia, C., Janchivlamdan, C., Monti, I. E., Boldbaatar, T., Munkhtsog, B. |
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Mammal inventory in the Mongolian Gobi, with the southeasternmost documented record of the Snow Leopard, Panthera uncia (Schreber, 1775), in the country |
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2019 |
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Check List |
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15 |
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4 |
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575-578 |
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Camera trapping, desert, live trapping, mammal checklist, species richness, threatened species. |
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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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