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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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Journal Article |
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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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1433 |
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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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Journal Article |
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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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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 |
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Methods in Ecology and Evolution |
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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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Salvatori, M., Tenan, S., Oberosler, V., Augugliaro, C., Christe, P., Groff, C., Krofel, M., Zimmermann, F., Rovero, F. |
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Title |
Co-occurrence of snow leopard, wolf and Siberian ibex under livestock encroachment into protected areas across the Mongolian Altai |
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Journal Article |
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Year |
2021 |
Publication |
Biological Conservatio |
Abbreviated Journal |
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261 |
Issue |
109294 |
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1-14 |
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Keywords |
Camera-trapping, Panthera uncia, Canis lupus, Capra sibirica, Occupancy, Human-wildlife conflicts, Activity pattern |
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In countries such as Mongolia, where globalization of the cashmere market has spurred herders to massively increase their livestock numbers, an important conservation concern is the effect of livestock encroachment on wildlife. This is especially important inside protected areas (PAs), which often represent the last refugia for threatened large mammals. We used camera-traps to sample four areas with different protection status across the Mongolian Altai Mountains, and targeted a predator-prey system composed of livestock, one large herbivore, the Siberian ibex, and two large carnivores, the snow leopard and the wolf. To determine the effect of livestock on habitat use by the wild species and their spatio-temporal co-occurrence we applied an occupancy framework explicitly developed for modelling interacting species. We recorded a widespread presence of domestic animals in the PAs, and observed avoidance of sites used by livestock by snow leopard and ibex, while wolves tended to co-occur with it. Snow leopard and ibex showed clear mutual co-occurrence, indicating a tight predator-prey relationship. Results provide evidence that, at the scale of sites sampled primarily to maximise snow leopard detections, grazing livestock interferes with wild species by inducing avoidance in snow leopards, and attraction in wolves. We suggest that (1) PAs management should enforce real grazing limitations on the ground, especially in the core areas of the parks; (2) new policies incorporating wildlife conservation into government subsidies to pastoralists should be envisaged, to prevent increasing displacement of snow leopards and ibex; (3) as wolves co- occurred with livestock, with the potential for human-wildlife conflicts, we encourage the use of a set of prevention techniques to mitigate livestock depredation. |
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SLN @ rakhee @ |
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1659 |
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Johansson, Torbjorn, A. Johansson, Orjan. McCarthy, Tom |
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Title |
An Automatic VHF Transmitter Monitoring System for Wildlife Research |
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Journal Article |
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2011 |
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Wildlife Society Bulletin |
Abbreviated Journal |
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9999 |
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1-5 |
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automatic system, monitoring, pulse detection, trap-site transmitter, VHF transmitter monitoring |
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Abstract |
We describe an automated system for monitoring multiple very high frequency (VHF) transmitters, which are commonly employed in wildlife studies. The system consists of a microprocessor-controlled radio-frequency monitor equipped with advanced signal-processing capabilities that communicates with, and relays information to, a user interface unit at a different location. the system was designed for a capture-and-release snow leopard (Panthera uncia) study in Mongolia, where checking trap-site transmitters manually entailed climbing a hill with telemetry equipment several times each day and night. Here, it monitors the trap-site transmitters and actively produces an alarm when any of the traps have been triggered, or if the system has lost contact with any trap-transmitter. The automated system allowed us to constantly monitor transmitters from a research camp, and alerted us each time a trap was triggered. The system has been field-tested for 83 days from mid-September 2010 to mid-december 2010 in the Tost mountain range on the edge of Mongolia's Gobi desert. During this time, the system performed reliably, responding correctly to 45 manually generated alarms and 9 animal captures. The system considerably shortens the time the captured animals spend in traps, and also mitigates the need for manual trap-site transmitter monitoring, greatly reducing risk to the animal and the human effort involved. |
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1379 |
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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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1660 |
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Johansson, O., Kachel, S., Weckworth, B. |
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Title |
Guidelines for Telemetry Studies on Snow Leopards |
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Journal Article |
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2022 |
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Animals |
Abbreviated Journal |
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12 |
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1663 |
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1-12 |
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animal welfare; capture; collar; felid; GPS; immobilization; Panthera uncia; trapping |
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Animal-borne tracking devices have generated a wealth of new knowledge, allowing us to better understand, manage and conserve species. Fitting such tracking devices requires that animals are captured and often chemically immobilized. Such procedures cause stress and involve the risk of injuries and loss of life even in healthy individuals. For telemetry studies to be justifiable, it is vital that capture operations are planned and executed in an efficient and ethical way. Project objectives must be clearly articulated to address well-defined knowledge gaps, and studies designed to maximize the probability of achieving those goals. We provide guidelines for how to plan, design, and implement telemetry studies with a special emphasis on snow leopards that are typically captured using foot snares. We also describe the necessary steps to ensure that captures are conducted safely, and with minimal stress to animals. |
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1712 |
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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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682 |
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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 |
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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Jackson, R.; Roe, J.; Wangchuk, R.; Hunter, D. |
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Title |
Surveying Snow Leopard Populations with Emphasis on Camera Trapping: A Handbook |
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Book Whole |
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2005 |
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1-73 |
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snow; snow leopard; snow-leopard; leopard; populations; population; camera; camera trapping; trapping |
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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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The Snow Leopard Conservancy |
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Sonoma, California |
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English version. |
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SLN @ rana @ 1016 |
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474 |
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