Johansson, T., A. Johansson, Orjan. McCarthy, Tom. (2011). An Automatic VHF Transmitter Monitoring System for Wildlife Research. Wildlife Society Bulletin, 9999, 1–5.
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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Johansson, T., A. Johansson, Orjan. McCarthy, Tom. (2011). An Automatic VHF Transmitter Monitoring System for Wildlife Research. Wildlife Society Bulletin, 35((4)), 489–493.
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 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 sys ten 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 sorters 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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Weiskopf, S. R., Kachel, S. M., McCarthy, K. P. (2016). What Are Snow Leopards Really Eating? Identifying Bias in Food-Habit Studies. Wildlife Society Bulletin, , 1–8.
Abstract: Declining prey populations are widely recognized as a primary threat to snow leopard (Panthera
uncia) populations throughout their range. Effective snow leopard conservation will depend upon reliable
knowledge of food habits. Unfortunately, past food-habit studies may be biased by inclusion of nontarget
species in fecal analysis, potentially misinforming managers about snow leopard prey requirements.
Differentiation between snow leopard and sympatric carnivore scat is now cost-effective and reliable using
genetics. We used fecal mitochondrial DNA sequencing to identify scat depositors and assessment bias in
snow leopard food-habit studies. We compared presumed, via field identification, and genetically confirmed
snow leopard scats collected during 2005 and 2012 from 4 sites in Central Asia, using standard forensic
microscopy to identify prey species. Field identification success varied across study sites, ranging from 21% to
64% genetically confirmed snow leopard scats. Our results confirm the importance of large ungulate prey for
snow leopards. Studies that fail to account for potentially commonplace misidentification of snow leopard
scat may mistakenly include a large percentage of scats originating from other carnivores and report
inaccurate dietary assessments. Relying on field identification of scats led to overestimation of percent
occurrence, biomass, and number of small mammals consumed, but underestimated values of these measures for large ungulates in snow leopard diet. This clarification suggests that the conservation value of secondary prey, such as marmots (Marmota spp.) and other small mammals, may be overstated in the literature; stable snow leopard populations are perhaps more reliant upon large ungulate prey than previously understood.
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Jackson, R., Roe, J., Wangchuk, R., & Hunter, D. (2006). Estimating Snow Leopard Population Abundance Using Photography and Capture-Recapture Techniques (Vol. 34).
Abstract: 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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Eisen, L. (1982). Symposium held on snow leopard. Woodland Park Zoological Gardens Newsletter, October/November, 2–3.
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Woodland Park Zoological Gardens. (1982). Symposium held on snow leopard. Woodland Park Zoological Gardens Newsletter, , 1–3.
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Anonymous. (1978). Look what's new at the zoo! Rare kittens make the nursery lively. WORLD, December(40), 20–24.
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Jackson, R. (1986). On the trail of the elusive snow leopard. World Wildlife Fund Monthly Report, May, 127–132.
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Karnaukhov А. S., K. М. P., Kuksin А. N., Malykh S. V., Poyarkov А. D., Spitsyn S. V., Chistopolova М. D., Hernandez-Blanco J. A. (2020). Snow Leopard Population Monitoring Guidebook (English).
Abstract: The “Snow Leopard Population Monitoring Guidebook” is the result of a multiyear effort to study and monitor the status of key snow leopard populations in the Russian Federation conducted by WWF Russia specialists alongside colleagues in protected areas and the Severtsov Institute for Ecology and Evolution (Russian Academy of Sciences). The book provides the most recent data regarding the distribution and population of the snow leopard in three administrative subjects of the Russian Federation – Republics of Altai, Tyva, and Buryatiya. Optimal survey routes and a grid network for camera-trapping stations are discussed and are based on a previously-developed program for standardized monitoring and surveying of the snow leopard population. The most important part of this publication is the analysis of methodologies for evaluating the status of population groups of this rare cat – from the traditional route census approach to innovative systems for automated collection of field data. In addition, the results of multi-year work analyze snow leopard nutrition and evaluate the genetic diversity of the snow leopard population in Russia.
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Karnaukhov А. S., K. М. P., Kuksin А. N., Malykh S. V., Poyarkov А. D., Spitsyn S. V., Chistopolova М. D., Hernandez-Blanco J. A. (2020). Snow Leopard Population Monitoring Guidebook (Russian).
Abstract: The “Snow Leopard Population Monitoring Guidebook” is the result of a multiyear effort to study and monitor the status of key snow leopard populations in the Russian Federation conducted by WWF Russia specialists alongside colleagues in protected areas and the Severtsov Institute for Ecology and Evolution (Russian Academy of Sciences). The book provides the most recent data regarding the distribution and population of the snow leopard in three administrative subjects of the Russian Federation – Republics of Altai, Tyva, and Buryatiya. Optimal survey routes and a grid network for camera-trapping stations are discussed and are based on a previously-developed program for standardized monitoring and surveying of the snow leopard population. The most important part of this publication is the analysis of methodologies for evaluating the status of population groups of this rare cat – from the traditional route census approach to innovative systems for automated collection of field data. In addition, the results of multi-year work analyze snow leopard nutrition and evaluate the genetic diversity of the snow leopard population in Russia.
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