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Alexander, S., A., Zhang, C., Shi, K., Riordan, P. |
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Title |
A granular view of a snow leopard population using camera traps in Central China |
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Journal Article |
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2016 |
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Biological Conservation |
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197 |
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27-31 |
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Snow leopard Camera trap China Density Monitoring |
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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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SLN @ rakhee @ |
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1436 |
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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 |
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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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SLN @ rakhee @ |
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1715 |
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Author |
Sharma, R. |
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Title |
Of Men and Mountain Ghosts: Glimpses from the Rooftop of the World |
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Magazine Article |
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2010 |
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GEO |
Abbreviated Journal |
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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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English |
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SLN @ rana @ |
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1139 |
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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 |
Abbreviated Journal |
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31 |
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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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SLN @ rakhee @ |
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1660 |
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Kashkarov, E. |
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Title |
THE SNOW LEOPARD OF KIRGIZIA: NATIONAL SHAME OR NATIONAL PRIDE |
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Journal Article |
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2017 |
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239-253 |
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snow leopard, irbis, ibex, mountain sheep, conservation, range, reserve, monitoring, cameratrap, Sarychat, Kirgizia, Central Asia. |
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Article examines the problems existing in conservation of the snow leopard in Kirgizia after break-up of the
USSR. Unfortunate situation is common to most of the 14 countries in the snow leopard range, but seems
especially sharp to Kirgizia. Yet half of the century ago Kirgizia has had about 1.5 thousand of the snow
leopards, and today there remains no more than 1/10. In Soviet time Kirgizia was a global supplier of the
snow leopards for the zoo-export � to create a reserve number of endangered cats in captivity. Today, at
least half of the snow leopards in the Zoos of the world are individuals, caught in Kirgizia or their
descendants.
Since independence, Kirgizia has set new records. In Sarychat-Irtash reserve � the best for the snow
leopard in Central Asia, and probably in the whole range � this species was completely destroyed after 3
years of reserve opening... and 17 years later � revived... Situation comes presently back to the worst-case
scenario, and not only for the snow leopard. Author shows how work in this direction social and economic
levers, and what kind future he would like to see in Kirgizia, where he lived for 12 years and was at the
forefront of pioneering research of the snow leopard and its conservation. |
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SLN @ rakhee @ |
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1454 |
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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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Simms, A., Moheb, Z., Salahudin, Ali, H., Ali, I. & Wood, T. |
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Title |
Saving threatened species in Afghanistan: snow leopards in the Wakhan Corridor |
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2011 |
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International Journal of Environmental Studies |
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68 |
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3 |
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299-312 |
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Snow leopard; Camera trap; Governance; Rangers; Corral; Insurance |
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The Wakhan Corridor in northeast Afghanistan is an area known for relatively abundant wildlife and it appears to represent Afghanistan’s most important snow leopard landscape. The Wildlife Conservation Society (WCS) has been working in Wakhan since 2006. Recent camera trap surveys have documented the presence of snow leopards at 16 different locations in the landscape. These are the first camera trap records of snow leopards in Afghanistan. Threats to snow leopards in the region include the fur trade, retaliatory killing by shepherds and the capture of live animals for pets. WCS is developing an integrated management approach for this species, involving local governance, protection by a cadre of rangers, education, construction of predator-proof livestock corrals, a livestock insurance program, tourism and research activities. This management approach is expected to contribute significantly to the conservation of snow leopards and other wildlife species in the Wakhan. |
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Wildlife Conservation Society, International Programs, 2300 Southern Blvd, New York 10460, USA |
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Wildlife Conservation Society |
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1347 |
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Zhang, L., Lian, X., Yang, X |
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Population density of snow leopards (Panthera Uncia) in the Yage Valley Region of the Sanjiangyuan National Park: Conservation Implications and future directions |
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2020 |
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Artic, Antartic and Alpine Research |
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52 |
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1 |
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541-550 |
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Keywords ![sorted by Keywords field, ascending order (up)](img/sort_asc.gif) |
Snow leopard; population density; camera trapping; Tibetan Plateau; alpine ecosystem |
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Population-based studies on snow leopard (Panthera uncia) are of theoretical and practical sig- nificance for the conservation of alpine ecosystems, though geographic remoteness and isolation hinder surveys in many promising regions. The Sanjiangyuan National Park on the Tibetan Plateau is acknowledged as a main snow leopard habitat, but most of the region remains unexplored and unknown. We adopted a combined approach of route survey and camera trapping survey to explore the population density of snow leopard in the Yage Valley region of the Sanjiangyuan National Park. Results indicated that (1) large populations of blue sheep contributed to the major food supply for snow leopards, along with diverse prey species as dietary supplementations, and (2) a population density of four to six snow leopards per 100 km2 on the north bank was estimated, and nine to fourteen individuals within the valley core areas were identified. We also argue that under the potential impacts of hydropower dams, this valley ecosystem should be symbolized as a conservation hotspot and therefore merits prioritized conservation. We recommend further surveys combined with novel methods/techniques and advocate a sustainable ecotourism model for the first V-shaped valley along the Yangtze mainstream. |
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Jackson, R.; Roe, J. |
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Preliminary Observations On Non-Invasive Techniques for Identifying Individual Snow Leopards and Monitoring Populations |
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2002 |
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snow; leopard; monitoring; population; uncia; non; invasive; photo; camera; trap; traps; 4970 |
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Islt |
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Islt |
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Abastract OnlyTitle, Monographic: Proceedings of the Snow Leopard Survival SummitPlace of Meeting: Seattle,WA |
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Spearing, A. |
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A Note on the Prospects for Snow Leopard Census Using Photographic Capture |
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2002 |
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snow; leopard; photo; trap; camera; image; capture; 35mm; film; 5080 |
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Title, Monographic: Proceedings of the Snow Leopard Survival SummitPlace of Meeting: Seattle,WA |
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SLN @ rana @ 494 |
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