Abstract: Kangchenjunga Conservation Area (KCA) is situated in the Taplejung district at the north-eastern region of Nepal. Livestock keeping is the main activity of people for making a living amidst a conflict with snow leopard (Uncia uncia). Each year snow leopard kills a number of livestock resulting significant economic losses for the poor people living in this remote area. Unless the people – snow leopard conflicts is well understood and appropriate conflict management activities are implemented, the long run co-existence between people and snow leopard –especially the existence of snow leopard in this part of the world–will be in question. This has now become an utmost important as the aspiration of the people for economic development has risen significantly and the area has been open to tourism. Study was done by counting snow leopard signs walking systematically in total 18 snow leopard sign transects covering 18.01 km in length in three sites, i.e. Lonak, Khambachen and Dudhpokhari of the Conservation Area. The average sign density was 12.63/km. The livestock depredation by snow leopard for one year (2005-06) was studied by interviewing the herders to understand the responsible and specific bio-physical and economic factors. The study revealed that sub-adult yaks were mostly hunted by snow leopard. Cattle's' winter (December-April) pastures are most vulnerable sites for predation. Presence of bushes, forest and boulders and rugged mountain crevices make good hides for snow leopard. The study also showed that a lax animal guarding system was significantly responsible for high livestock depredation by snow leopard. Blue sheep was observed by walking in selected trails and from vantage points. A total of 354 individual sheep of different age and sex of 14 different herds were recorded during the study period. The study showed that improvement in livestock guarding system should be adopted as the most important activity. However despite the importance of livestock in the KCA it is still not well understood why the herders neglect for proper livestock guarding. Proper guarding system required in winter pastures to reduce the depredation pressure.

Abstract: The enchanting state of Uttaranchal, carved out of Uttar Pradesh on 9th November 2000, has a total area of ca. 53,485 km2 with a population density of 160 persons/ km2, much lower than the national average of 324/km2. This young state can take pride in the fact that 13.42% of its area is under protected areas. The state has varied landscapes: snow-capped and conifer forest covered mountains in the north, forest covered foothills with numerous perennial rivers and streams, locally known as the bhabar tract which includes the Himalayan foothills and the Shivalik range. As a result, the land is home to a variety of fascinating wildlife such as the golden mahseer (Tor putitora), king cobra (Ophiophagus hanna), Himalayan monal (Lophophorus impejanus), great hornbill (Buceros bicornis), Himalayan tahr (Hemitragus jemlahicus), bharal (Pseudois nayaur), Himalayan musk deer (Moschus chrysogaster), goral (Nemorhaedus goral), elephant (Elephas maximus), snow leopard (Panthera uncia), leopard (P. pardus), black bear (Ursus thibetanus), and tiger (P. tigris). All across their range, most of these species are endangered. The potential of this state, with about 800 kilometers of riverine habitat, can only be surpassed by Arunachal Pradesh in terms of golden mahseer conservation. The mountains, bedecked with the scarlet flowers of rhododendron (Rhododendron arboreum) in the summer months, can be a veritable home to many forms of pheasants, mountain ungulates and carnivores, provided poaching for trade is eliminated and hunting for the pot is brought under control. The bhabar forests of this state, ca. 7,500 km2, extending between Yamuna and Sharda rivers (Fig. 1.), can easily support a population of about 1000 elephants and 200 tigers as long as this large habitat, now fragmented in three blocks, is managed and protected as one continuous habitat for wildlife. Six villages, gujjar settlements and encroachments need to be moved away from the main wildlife habitat which goes along the bhabar tract. Although the conservation of these habitats can eventually bring in immense benefits through well-planned ecotourism programmes that are rapidly catching up in the state, initial conservation efforts would need a substantial amount of funds.

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.