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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 |
Type |
Journal Article |
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Year |
2023 |
Publication |
Global Ecology & Conservation |
Abbreviated Journal |
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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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1715 |
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Author |
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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Sivolobov, R. |
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Title |
ENDANGERED SPECIES OF KORYAKIA AND CHUKOTKA: IRBIS, TIGER AND THE IRKUYEM-BEAR |
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2017 |
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225-233 |
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endangered species, Beringian snow cat, Snow leopard, Irbis, Amur tiger, Irkuyem-bear, camera-trap, Koryakia, Chukotka |
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After 30 years of searching for the mysterious Beringian snow cat in vast space of Koryakia and Chukotka
one of the five cameras recorded finally this beast at night in September 2014. This is not so much a
sensation as a real scientific discovery, saying that the hearts of the snow leopard population resettlement are
not in 5000 km from the main range boundaries, but much closer. Where? � will show further studies.
In addition to the snow leopard in the North-Eastern Asia, it found two more endangered large
mammal species: the Amur tiger and the relict of the Ice Age � the Irkuyem-bear. Author has given these
animals his life and his article devoted to this topic. |
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SLN @ rakhee @ |
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1456 |
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Suryawanshi, K. R., Khanyari, M., Sharma, K., Lkhagvajav, P., Mishra, C. |
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Title |
Sampling bias in snow leopard population estimation studies |
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Journal Article |
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2019 |
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Population Eccology |
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1-9 |
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camera trap, Central Asia, Himalaya, meta-analysis, monitoring, Panthera uncia, population ecology |
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Abstract |
Accurate assessments of the status of threatened species and their conservation
planning require reliable estimation of their global populations and robust monitoring
of local population trends. We assessed the adequacy and suitability of studies
in reliably estimating the global snow leopard (Panthera uncia) population. We
compiled a dataset of all the peer-reviewed published literature on snow leopard
population estimation. Metadata analysis showed estimates of snow leopard density
to be a negative exponential function of area, suggesting that study areas have generally
been too small for accurate density estimation, and sampling has often been
biased towards the best habitats. Published studies are restricted to six of the
12 range countries, covering only 0.3�0.9% of the presumed global range of the
species. Re-sampling of camera trap data from a relatively large study site
(c.1684 km2) showed that small-sized study areas together with a bias towards
good quality habitats in existing studies may have overestimated densities by up to
five times. We conclude that current information is biased and inadequate for generating
a reliable global population estimate of snow leopards. To develop a rigorous
and useful baseline and to avoid pitfalls, there is an urgent need for
(a) refinement of sampling and analytical protocols for population estimation of
snow leopards (b) agreement and coordinated use of standardized sampling protocols
amongst researchers and governments across the range, and (c) sampling
larger and under-represented areas of the snow leopard's global range. |
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SLN @ rakhee @ |
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1477 |
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Alexander, J. S., Shi, K., Tallents, L. A., Riordan, P. |
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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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Author |
WWF Russia & Mongolia |
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Title |
WWF Altai-Sayan Newsletter |
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2010 |
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14 |
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Altai Sayan, WWF, camera trap, Argut River, poaching, conservation, Tuva |
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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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Communication Staff of Altai - Sayan Programme in Russia and Mongolia |
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WWF |
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October-December 2010. Email: tivanitskaya@wwf.ru |
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SLN @ rana @ |
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1297 |
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Sharma, K., Fiechter, M., George, T., Young, J., Alexander, J.
S., Bijoor, Suryawanshi, K., Mishra, C. |
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Conservation and people: Towards an ethical code of conduct for
the use of camera traps in wildlife research |
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2020 |
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Ecological Solutions and Evidence |
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1-6 |
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camera trap, code of conduct, ethics, human rights, law, PARTNERS principles for community- based conservation, privacy, snow leopard |
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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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1626 |
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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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Abastract OnlyTitle, Monographic: Proceedings of the Snow Leopard Survival SummitPlace of Meeting: Seattle,WA |
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SLN @ rana @ 483 |
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469 |
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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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1407 |
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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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918 |
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