Abstract: Over a time of four years the bazars of Afghanistan were surveyed for furs of spotted wild cats, in particular leopards and snow leopards. In 2004 in Kabul a total of 28 furs of leopards were purchased by shopkeepers and 21 sold at an average price of 825 $. In the same year 25 furs of snow leopards were purchased and 19 sold to clients at an average price of 583 $. In 2006 at a single inspection double as many furs of leopards were found to be offered for sale in comparison to the whole year of 2004. Also prices had increased over the two years by 20 % to an average of 1037 $. Similarly the number of furs of snow leopards at 21 pieces was higher than in 2004, and the prices had increased to an average of 652 $. In 2007 investigations rendered more difficult, because the authorities had started to control the fur trade, and the results are not unequivocal. Clients were without any exception foreigners.
Surveys in 2004 in Mazar-e-Sharif, Kunduz, Takhar and Faiz Abad, in 2006 additionally in Baharak and Iskashem in the province of Badakhshan, revealed a regular trade in furs of spotted cats, however not as extensive as in Kabul. The most interesting finding was a fur of a cheetah in Mazar-e-Sharif, the first record of this species after 35 years.
From the surveys can be concluded that leopards still exist in the whole range of its distribution area in Afghanistan. However they don't allow any conclusion on the population size and its threat by hunting. In contrast to the leopard there exists a recent estimation of the population size of the snow leopard, saying that there are still 100 to 200 snow leopards living in Afghanistan. On the basis of these figures as well as the numbers of furs traded annually a Population and Habitat Viability Analysis was conducted. The result of this analysis is alarming. It has to be assumed that the snow leopard will be extinct in Afghanistan within the next ten years. To improve the protection of spotted cats in Afghanistan it needs both, a better implementation of the existing legislation as well as an awareness campaign among potential clients, i. e. foreigners living in Afghanistan.
The second part of this thesis deals with the question of subspecies of leopards in Afghanistan. Out of the 27 subspecies described four are believed to exist in Afghanistan. However, according to a molecularbiological revision of the species there occurs only one subspecies in Afghanistan, Panthera pardus saxicolor. To clarify the subspecies question various measures of furs had been taken in the bazars. The results revealed that the leopards in Afghanistan are the biggest of its species. However a further differentiation according to the area of origin within the country was not possible. Also the traditional differentiation on the basis of colours and patterns on the furs was not possible.
In contrast to the molecularbiological investigations published not only samples of zoo animals were available in this study but also samples from the wild. The own results confim that almost all leopards from Afghanistan and Iran belong to one and the same subspecies, P. p. saxicolor. Only in the most eastern part of Afghanistan, the Indian leopard, Panthera pardus fusca, can be found. The International Studbook for the Persian Leopard was analysed. The whole population derives from a few founder animals, which were imported in the midth fifties from Iran and in the late sixties from Afghanistan. To avoid inbreeding later on the Iranian and the Afghan lines were mixed. A female imported in 1968 from Kabul to Cologne is represented in each of the more than 100 today living animals.Mixing the two lines subsequently is justified by the genetic results of this study. Recently acquired animals from the Caucasus, however, should be tested genetically before integrating them into the zoo population.

Abstract: The snow leopard is an endangered large felid inhabiting highlands of 12 Asian countries. It is distributed
across vast territories and adequate modern methods are required for mapping its potential habitats. The goal
of the present study is to create a model of snow leopard potential habitat within the northern part of its range
in Russia (and adjacent territories of Mongolia, China and Kazakhstan). More than 5 years of observations
(total number of presence points = 449), environmental variables and the maximum entropy distribution
method (Maxent) are used. The resulting map demonstrates that a suitable habitat (probability of the animal�s
presence between 0.5 and 1) of the northern population of snow leopard in Russia occupies 16500 km2
with a buffer of transient territories (probability between 0.25 and 0.49) covering 32800 km2. Most of a suitable
habitat within the study area is associated with the Altai Mountains, Western Sayan Mountains, Sangilen
Plateau, Tsagan-Shibetu and Shapshal. One third of the suitable habitat lies within areas of a varying protection
status. The results of modeling are of importance both for scientists and conservation managers, as they
allow for leopard occurrence to be predicted, supporting research on and the conservation of the species.

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.