Theriologia Ukrainica
(former Proceedings of the Theriological School)

ISSN 2616-7379 (print) ISSN 2617-1120 (online)

2019 Vol. 17 Contents of volume >>>

download pdfTytar, V., Asykulov, T., Hammer, M. Using species distribution modelling to guide survey efforts of the snow leopard (Panthera uncia) in the Central Kyrgyz Ala-Too region. Theriologia Ukrainica. 2019. Vol. 17: 112-118.



Using species distribution modelling to guide survey efforts of the snow leopard (Panthera uncia) in the Central Kyrgyz Ala-Too region


Tytar, V., Asykulov, T., Hammer, M.


Schmalhausen Institute of Zoology NAS of Ukraine (Kyiv, Ukraine)
Kyrgyz National University, Faculty of Geography and Ecology (Bishkek, Republic of Kyrgyzstan)
Der Naturschutzbund Deutschland e. V. NABU (Bishkek, Republic of Kyrgyzstan)
Biosphere Expeditions Deutschland (Hoechberg, Germany)


Theriologia Ukrainica. 2019. Vol. 17: 112-118.




English, with Ukrainian summary, titles of tables, captures to figs


Listed as Vulnerable (IUCN 2017), the snow leopard is declining across much of its present range. One of 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 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.


Capra sibirica, Panthera uncia, Kyrgyz Ala-Too, species distribution models, Maxent.



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