Abstract: Snow leopard conservation work in Bhutan dates back to 1999 and 2000 when the International Snow Leopard Trust-in collaboration with the Royal Government of Bhutan and World Wildlife Fund-initiated a training workshop. More than 30 government staff were trained in SLIMS survey techniques. As a part of the training exercise, a preliminary survey on snow leopard was also carried out using the SLIMS methods in Jigme Dorji Wangchuck National Park. Based on the survey results, we estimated there was a population of 100 snow leopards in the wild and 10,000 km2 of habitat. In 2005, World Wildlife Fund (WWF) organized the WWF/South Asia Regional Workshop on Snow leopard Conservation in Bhutan. Both regional (Bhutan, India, China, Nepal and Pakistan) and international experts revisited the snow leopard programs and developed a work plan for the overall conservation of the snow leopard in the region. This led to WWF's Regional Snow leopard Conservation Strategy. WWF is pleased to submit our final report to the International Snow Leopard Trust on the oneyear, $8,000 grant in support of Snow Leopard and Prey Population Conservation in Bhutan. With the support of the Snow Leopard Trust, we have made great strides towards achieving our goal for this project: To determine the current status of snow leopard and ungulate prey populations in prime snow leopard habitats. Major accomplishments and activities completed thanks to the generous support of the International Snow Leopard Trust include:
 Signed of a Terms of Reference between Royal Government, International Snow Leopard
Trust – India, World Wildlife Fund and International Snow Leopard Trust -US;
 Developed a joint revised project work plan; and
 Purchased basic field supplies and equipment needed for the surveys planned.

Abstract: This study presents the testing of two unsupervised classification methods for their ability to accurately identify unknown individual tigers, Panthera tigris, and snow leopards, Panthera uncia, from their footprints. A neural-network based method, the Kohonen self-organizing map (SOM), and a Bayesian method, AutoClass, were assessed using hind footprints taken from captive animals under standardized conditions. AutoClass successfully discriminated individuals of both species from their footprints. Classification accuracy was greatest for tigers, with more misclassification of individuals occurring for snow leopards. Examination of variable influence on class formations failed to identify consistently influential measurements for either species. The self-organizing map did not provide accurate classification of individuals for either species. Results were not substantially improved by altering map dimensions nor by using principal components derived from the original data. The interpretation of resulting classifications and the importance of using such techniques in the study of wild animal populations are discussed. The need for further testing in the field is highlighted.