Using species distribution modelling to guide survey efforts of the Snow Leopard (Panthera uncia) in the Central Kyrgyz Ala-Too region. -V. Tytar, T. Asykulov, M. Hammer. -Listed as Vulnerable (IUCN 2017), the snow leopard is declining across much of its present range. One of the major reasons for the snow leopard population decline in the last two decades is a reduction in large prey species that are the cornerstone of the conservation of the snow leopard; in the Central Kyrgyz Ala-Too region such species is primarily the Siberian ibex (Capra sibirica). Understanding factors affecting basic requirement of ibex and shaping its distribution is essential for protecting the prey species snow leopards rely on the most. Using a niche modelling approach we explored which environmental features are best associated with ibex occurrence, how well do models predict ibex occurrence, and does the potential distribution of highly suitable ibex habitat correlate with records of snow leopard. A PC analysis was used to capture aspects of ibex ecology and niche. Results of such analysis agree with the herbivore character of the species and bioclimatic habitat requirements of the vegetation it feeds upon, richer in flatter areas, and where plants may benefit from more sunlight. The niche model based on maximum entropy (Maxent) had "useful" discrimination abilities (AUC = 0.746), enabling to produce a map, where a contour line is drawn around areas of highly predicted probability (> 0.5) of ibex occurrence. In terms of nature conservation planning and setting snow leopard research priorities these areas represent the most interest. With one outlier, most of snow leopard records made in the study area (n = 15) fell within the 10 percentile presence threshold (0.368). Predicted probability of ibex occurrence in places where records were made of snow leopard presence (pugmarks, scrapes etc.) was 0.559 expectedly suggesting areas of high ibex habitat suitability attract the predator.

Distribution modeling of the long-tailed marmot (Marmota caudata) for objectives of directing field surveys and ground validation of the snow leopard (Panthera uncia) habitat quality. -V. Tytar, M. Hammer, T. Asykulov. -Marmots form a part of the diet of some endangered species such as the snow leopard (Panthera uncia), therefore the knowledge on their distribution and habitat preferences are crucial to the interest of the conservation and management of carnivores at high altitudes. Considering this, within a snow leopard project run by Biosphere Expeditions and NABU (Kyrgyzstan), surveys were carried out in summer field seasons of 2014-2019 to assess the distribution of the long-tailed marmots (Marmota caudata) in an area centered around the Karakol Mountain Pass (polygon centroid 74.83° E, 42.37° N) in the Kyrgyz Ala-Too Range. The presence of occupied marmot burrows was recorded using the location (cell) given by a grid, the code of which was displayed in a GPS. Using cells allows examination of data at a wider scale, so information is collected from different cells that are spread from each other, avoiding data autocorrelation. Environmental factors that may affect the spatial distribution of burrow systems were considered: land surface temperature (LST) in winter and summer, summer normalized difference vegetation index (NDVI), a Digital Elevation Model (DEM), and soil type data. The relationship between environmental factors and burrow records was analyzed using ecological niche models (Maxent) to predict the distributions of marmot burrows. The models performed well with average test AUC values of 0.939. The contribution orders of the variables in the models were summer NDVI and DEM, winter LST, summer LST, and soil type. The distribution of the suitable areas was largely (up to 38 % permutation importance) affected by summer NDVI. NDVI is an indicator of the feeding conditions of marmots and most of the records were distributed in areas with NDVI in summer ranging from 0.5 to 0.7. According to the prediction maps, suitable marmot habitat (> 0.5 predicted probabilities of occurrence) can occupy up to 40 % of study area. These maps are used to direct sampling efforts to areas on the landscape that tend to have greater predicted probabilities of occurrence and accomplish ground validation of snow leopard habitat quality.