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Spearing, A. (2002). A Note on the Prospects for Snow Leopard Census Using Photographic Capture.. Islt: Islt.
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Jiang, Z. (2005). Snow leopards in the Dulan International Hunting Ground, Qinghai, China.
Abstract: From March to May, 2006œªwe conducted extensive snow leopard surveys in the Burhanbuda Mountain Kunlun Mountains, Qinghai Province, China. 32 linear transect of 5~15 km each, which running through each vegetation type, were surveyed within the study area. A total of 72 traces of snow leopard were found along 4 transects (12.5% of total transects). The traces included pug marks or footprints, scrapes and urine marks. We estimated the average density of wild ungulates in the region was 2.88ñ0.35 individuals km-2(n=29). We emplaced 16 auto2 trigger cameras in different environments and eight photos of snow leopard were shot by four cameras and the capture rate of snow leopard was 71.4%. The minimum snow leopard population size in the Burhanbuda Mountain was two, because two snow leopards were phototrapped by different cameras at almost same time. Simultaneously, the cameras also shot 63 photos of other wild animals, including five photos are unidentified wild animals, and 20 photos of livestock. We evaluated the human attitudes towards snow leopard by interviewing with 27 Tibetan householders of 30 householders live in the study area. We propose to establish a nature reserve for protecting and managing snow leopards in the region. Snow leopard (Uncia uncia) is considered as a unique species because it lives above the snow line, it is endemic to alpines in Central Asia, inhabiting in 12 countries across Central Asia (Fox, 1992). Snow leopard ranges in alpine areas in Qinghai, Xinjiang, Inner Mongolia, Tibet, Gansu and Sichuan in western China (Liao, 1985, 1986; Zhou, 1987; Ma et al., 2002; Jiang & Xu, 2006). The total population and habitat of snow leopards in China are estimated to be 2,000~2,500 individuals and 1,824,316 km2, only 5% of which is under the protection of nature reserves. The cat's current range is fragmented (Zou & Zheng, 2003). Due to strong human persecutions, populations of snow leopards decreased significantly since the end of the 20th century. Thus, the
snow leopards are under the protection of international and domestic laws. From March to May, 2006, we conducted two field surveys in Zhiyu Village, Dulan County in Burhanbuda Mountain, Kunlun Mountains, China to determine the population, distribution and survival status of snow leopards in the area. The aim of the study was to provide ecologic data for snow leopard conservation.
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WWF Russia & Mongolia. (2010). WWF Altai-Sayan Newsletter. WWF.
Abstract: A Snow Leopard – A Treasure of Tuva. A beautiful animal as a winner of a wide-scale public vote
WWF will train a Scat Detection Dog for snow leopard monitoring project
WWF assessed the possibility to fight illegal helicopter hunting
WWF considers support of antipoaching activities an essential part of wildlife conservation in Altai – Sayan
Snow Leopard Camera Trapping in Argut River Valley
“Stars” of Tuva appeal to Snow Leopard Conservation
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Ming, M., Yun, G., & Bo, W. (2008). Chinese snow leopard team goes into action. Man & the Biosphere, 54(6), 18–25.
Abstract: China, the world's most populous country, also contains the largest number of Snow Leopards of any country in the world. But the survey and research of the snow leopard had been very little for the second half of the 20th century. Until recent years, the members of Xinjiang Snow Leopards Group (XSLG/SLT/XFC) , the Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences have been tracking down the solitary animal. The journal reporter does a face-to-face interview with professor Ma Ming who is a main responsible expert of the survey team. By the account of such conversation, we learn the achievements, advances and difficulty of research of snow leopards in the field, Tianshan and Kunlun, Xinjiang, the far west China, and we also know that why the team adopt the infrared camera to capture the animals. Last but not least professor talked about the survival menace faced by the Snow Leopards in Xinjiang.
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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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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. (2002). Preliminary Observations On Non-Invasive Techniques for Identifying Individual Snow Leopards and Monitoring Populations.. Islt: Islt.
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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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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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