Abstract: Since 1999, NABU, the German Society for Nature Conservation, has been organizing the conservation of snow leopards Uncia uncia in Kyrgyzstan in an international project in cooperation with the Kyrgyz Ministry of the Environment, Emergencies and Civil Defence and the Kyrgyz Ministry of the Interior. The animal, with its typical grey-beige patterned fur and bushy tail, is one of the most endangered big cats in the world. It is categorized as Endangered on the 2000 IUCN Red List and is on CITES Appendix I.

Abstract: Notes snow leopard as main predator in Pakistan study area. Describes content of some snow leopard droppings

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.

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.