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Convery, Ian; Baibagysov, Azim; Baiturbayev, Kyat; Deecke, Volker B.; Harpley, D.; Holt, Claire; Janyspayev, A.D.; Nevin, Owen; Nurtazin, Sabir; Smith, Darrell J.; van der Velden, Naomi (2015)
Publisher: Centre for Wildlife Conservation, University of Cumbria
Languages: English
Types: Book
Subjects: Z740, Z600, Z688
The snow leopard population in Kazakhstan represents a small but important component of the species range, making up around 2.7% of the global range, of which 18,673 km2 lies within protected areas. The most recent population estimate, by Jackson et al. (2008), suggests that there are around 180-200 individuals. Prior to this study there were no reliable estimates of snow leopard numbers in Almaty State Nature Reserve, one of the only two stable populations of snow leopards in Kazakhstan. In total 40 camera traps were deployed for a total of 5152 traps nights and yielded 50 independent capture events of snow leopards (with between 1 and 10 images per event), 275 capture events of primary prey and 68 capture events of secondary prey. The study capture rate of 0.97 independent capture events per 100 trap nights is at the higher end of the range experienced by other studies (see McCarthy et al., 2008) and mark-recapture modelling estimated 11-18 individual snow leopards in the study area which suggests density between 4.4 and 7.2 individuals per 100km2. Our population estimate for the whole reserve is 39.6 individuals, with a standard error of 5.44536 individuals and a 95% confidence interval of 39 to 64. Analysis of movement patterns suggests that individuals frequently crossed valley bottoms and used densely forested habitat in winter, which may indicated prey switching from ibex to forest ungulates. The University of Cumbria has developed a fuzzy logic model which aggregates a wide range of socio-economic and ecological data and provides a tool that can be used to inform the sustainable natural resource and landscape management decision-making process. Our model predicts the consistent negative impact of climate change (warming) at elevations below the tree line; this is particularly significant as the potential positive impacts for snow leopards at high elevation are slower to kick in thereby increasing the habitat squeeze associated with climate change in mountain habitats.
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    • Baldwin, R. A. and L. C. Bender. 2012. Estimating population size and density of a low-density population of black bears in Rocky Mountain National Park, Colorado. European Journal of Wildlife Research 58:557-566.
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    • Bolger, D.T. et al. (2011) Wild--ID: Pattern Extraction and Matching Software for Computer--Assisted Photographic Mark-- Recapture Analysis. Dartmouth College, Hanover, NH.
    • Burton, A. C., E. Neilson, D. Moreira, A. Ladle, R. Steenweg, J. T. Fisher, E. Bayne, S. Boutin, and P. Stephens. 2015. REVIEW: Wildlife camera trapping: a review and recommendations for linking surveys to ecological processes. Journal of Applied Ecology 52:675-685.
    • Clapham, M., O. T. Nevin, A. D. Ramsey, and F. Rosell. 2014. Scent-marking investment and motor patterns are affected by the age and sex of wild brown bears. Animal Behaviour 94:107-116.
    • Janecka, J.E., Jackson, R., Yuquang, Z., Diqiang, L., Munkhtsog, B., Buckley-Beason, V. & Murphy, W.J. (2008) Population monitoring of snow leopards using noninvasive collection of scat samples: a pilot study. Animal Conservation, Vol.11, pp.401-411.
    • Shehzad, W., McCarthy, T. M., Pompanon, F., Purevjav, L., Coissac, E., Riaz, T., & Taberlet, P. (2012). Prey preference of snow leopard (Panthera uncia) in South Gobi, Mongolia. PloS One, 7(2), e32104.
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    The results below are discovered through our pilot algorithms. Let us know how we are doing!

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