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Jackson, R.; Roe, J.; Wangchuk, R.; Hunter, D. |
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Title |
Camera-Trapping of Snow Leopards |
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2005 |
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Cat News |
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42 |
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Spring |
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19-21 |
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Keywords |
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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Jackson, R.; Roe, J.; Wangchuk, R.; Hunter, D. |
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Title |
Estimating Snow Leopard Population Abundance Using Photography and Capture-Recapture Techniques |
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2006 |
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Wildlife Society Bulletin |
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34 |
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3 |
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772-781 |
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abundance; camera trapping; capture rates; dentistry; identification; India; photography; snow leopard; Uncia uncia |
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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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SLN @ rana @ 912 |
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476 |
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Ming, M. |
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Camera trapping on snow leopards in the Muzat Valley, Reserve, Xinjiang, P.R. China (October-December 2005) |
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2006 |
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behavior; camera trapping; China; feces; ibex; infrared trapping cameras; livestock; population size; snow leopard; Tomur; transect; Xinjiang |
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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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SLN @ rana @ 970 |
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682 |
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Author |
Sharma, K., Fiechter, M., George, T., Young, J., Alexander, J.
S., Bijoor, Suryawanshi, K., Mishra, C. |
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Title |
Conservation and people: Towards an ethical code of conduct for
the use of camera traps in wildlife research |
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2020 |
Publication |
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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Serial |
1626 |
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Author |
Durbach, I., Borchers, D., Sutherland, C., Sharma, K. |
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Title |
Fast, flexible alternatives to regular grid designs for spatial
capture–recapture. |
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Research Article |
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2020 |
Publication |
Methods in Ecology and Evolution |
Abbreviated Journal |
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1-13 |
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camera trap, population ecology,sampling, spatial capture-recapture, surveys |
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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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1618 |
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Author |
Xu, A.; Jiang, Z.; Li, C.; Guo, J.; Da, S.; Cui, Q.; Yu, S.; Wu, G. |
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Title |
Status and conservation of the snow leopard Panthera uncia in the Gouli Region, Kunlun Mountains, China |
Type |
Miscellaneous |
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2008 |
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Oryx |
Abbreviated Journal |
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460-463 |
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Camera trapping,China,human-wildlife conflict,Kunlun Mountains,Panthera uncia,snow leopard,trace. |
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The elusive snow leopard Panthera unica is a rare and little studied species in China. Over 1 March-15 May 2006 we conducted a survey for the snow leopard in the Gouli Region, East Burhanbuda Mountain, Kunlun Mountains, Qinghai Province, China, in an area of c. 300 km2 at altitudes of 4,000-4,700 m. We surveyed 29 linear transects with a total length of c. 440 km, and located a total of 72 traces (pug marks, scrapes and urine marks) of snow leopard along four of the transects. We obtained eight photographs of snow leopard from four of six camera traps. We also recorded 1,369 blue sheep, 156 Tibetan gazelles, 47 argali, 37 red deer and one male white-lipped deer. We evaluated human attitudes towards snow leopard by interviewing the heads of 27 of the 30 Tibetan households living in the study area. These local people did not consider that snow leopard is the main predator of their livestock, and thus there is little retaliatory killing. Prospects for the conservation of snow leopard in this area therefore appear to be good. We analysed the potential threats to the species and propose the establishment of a protected area for managing snow leopard and the fragile alpine ecosystem of this region. (c) 2008 Fauna & Flora International. |
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SLN @ rana @ 900 |
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1032 |
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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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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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1619 |
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Koju. N. P, , Bashyal, B., Pandey, B. P., Shah, S. N., Thami, S. ,Bleisch, W. V. |
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Title |
First camera-trap record of the snow leopard Panthera uncia in Gaurishankar Conservation Area, Nepal |
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2020 |
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Oryx |
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1-4 |
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Camera trap, corridor, Gaurishankar Conser- vation Area, Nepal, Panthera uncia, prey abundance, transboundary, snow leopard |
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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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1622 |
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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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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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Alexander, J. S., Gopalswamy, A. M., Shi, K., Riordan, P. |
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Title |
Face Value: Towards Robust Estimates of Snow Leopard Densities |
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2015 |
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Plos One |
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Densities, Snow Leopard, Camera traps, Spatial Capture Recapture models |
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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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