Fuzzy logic modelling of snow leopard populations in response to threats from climate change

Convery, Ian ORCID logo ORCID: https://orcid.org/0000-0003-2527-5660 , Baibagysov, Azim, Baiturbayev, Kyat, Deecke, Volker B. ORCID logo ORCID: https://orcid.org/0000-0003-2781-5915 , Harpley, D., Holt, Claire ORCID logo ORCID: https://orcid.org/0000-0003-3635-5404 , Janyspayev, A.D., Nevin, Owen ORCID logo ORCID: https://orcid.org/0000-0003-3513-8053 , Nurtazin, Sabir, Smith, Darrell ORCID logo ORCID: https://orcid.org/0000-0002-6745-8804 and van der Velden, Naomi ORCID logo ORCID: https://orcid.org/0000-0001-8969-1191 (2015) Fuzzy logic modelling of snow leopard populations in response to threats from climate change. Centre for Wildlife Conservation, University of Cumbria, Ambleside, UK.

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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.

Item Type: Report
Publisher: Centre for Wildlife Conservation, University of Cumbria
Departments: Institute of Science and Environment > Forestry and Conservation
Centre for National Parks and Protected Areas (CNPPA)
Depositing User: Anna Lupton
Date Deposited: 10 May 2016 09:49
Last Modified: 12 Jan 2024 13:32
URI: https://insight.cumbria.ac.uk/id/eprint/2126


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