The density of leopards in a mixed-use landscape in the Western Cape, South Africa

dc.contributor.advisorO'riain, Mannus
dc.contributor.authorHinde, Kyle Cameron
dc.date.accessioned2023-07-04T10:53:58Z
dc.date.available2023-07-04T10:53:58Z
dc.date.issued2023
dc.date.updated2023-07-04T10:53:19Z
dc.description.abstractLarge carnivores face numerous threats, including habitat loss and fragmentation, direct killing, and prey depletion, leading to significant global range and population declines. Despite these threats, leopards (Panthera pardus) persist outside protected areas throughout most of their range, occupying a diverse range of habitat types and land uses, including peri-urban and rural areas. Our understanding of leopard population dynamics in mixed-use landscapes is limited, especially in South Africa, where most research has focused on protected areas. Here I use spatially explicit capture-recapture (SECR) models on camera trap data to estimate how leopard density varies across a mixed-use landscape of protected areas, farmland, and urban areas in the Overberg region of the Western Cape, South Africa. Data were derived from 86 paired camera stations, which collected data for 161 camera trap nights, providing 221 independent leopard captures at 50 camera trap stations. A total of 25 individual leopards were identified, and the best-performing SECR model included the covariate sex on the σ (spatial decay), and a combination of sex, vegetation type and the interaction on λ0 (capture probability), with a density estimate of 0.64 leopards per 100 km2 . Elevation, terrain ruggedness, protected area status and NDVI were all important drivers of leopard density in the region, with leopard density highest on elevated remnants of natural land outside of protected areas. These results are similar to previous research findings in the Western Cape, where high-lying natural vegetation was shown to serve as both a refuge and a corridor for leopard movement in otherwise transformed landscapes. Given the low level of risks to lives and livelihoods posed by leopards in this region, the continued persistence of leopards in this shared landscape is considered high. Education of landowners should still be prioritised to improve tolerance towards leopards in the event of occasional negative impacts (e.g., livestock depredation).
dc.identifier.apacitationHinde, K. C. (2023). <i>The density of leopards in a mixed-use landscape in the Western Cape, South Africa</i>. (). ,Faculty of Science ,Department of Biological Sciences. Retrieved from http://hdl.handle.net/11427/38015en_ZA
dc.identifier.chicagocitationHinde, Kyle Cameron. <i>"The density of leopards in a mixed-use landscape in the Western Cape, South Africa."</i> ., ,Faculty of Science ,Department of Biological Sciences, 2023. http://hdl.handle.net/11427/38015en_ZA
dc.identifier.citationHinde, K.C. 2023. The density of leopards in a mixed-use landscape in the Western Cape, South Africa. . ,Faculty of Science ,Department of Biological Sciences. http://hdl.handle.net/11427/38015en_ZA
dc.identifier.ris TY - Master Thesis AU - Hinde, Kyle Cameron AB - Large carnivores face numerous threats, including habitat loss and fragmentation, direct killing, and prey depletion, leading to significant global range and population declines. Despite these threats, leopards (Panthera pardus) persist outside protected areas throughout most of their range, occupying a diverse range of habitat types and land uses, including peri-urban and rural areas. Our understanding of leopard population dynamics in mixed-use landscapes is limited, especially in South Africa, where most research has focused on protected areas. Here I use spatially explicit capture-recapture (SECR) models on camera trap data to estimate how leopard density varies across a mixed-use landscape of protected areas, farmland, and urban areas in the Overberg region of the Western Cape, South Africa. Data were derived from 86 paired camera stations, which collected data for 161 camera trap nights, providing 221 independent leopard captures at 50 camera trap stations. A total of 25 individual leopards were identified, and the best-performing SECR model included the covariate sex on the σ (spatial decay), and a combination of sex, vegetation type and the interaction on λ0 (capture probability), with a density estimate of 0.64 leopards per 100 km2 . Elevation, terrain ruggedness, protected area status and NDVI were all important drivers of leopard density in the region, with leopard density highest on elevated remnants of natural land outside of protected areas. These results are similar to previous research findings in the Western Cape, where high-lying natural vegetation was shown to serve as both a refuge and a corridor for leopard movement in otherwise transformed landscapes. Given the low level of risks to lives and livelihoods posed by leopards in this region, the continued persistence of leopards in this shared landscape is considered high. Education of landowners should still be prioritised to improve tolerance towards leopards in the event of occasional negative impacts (e.g., livestock depredation). DA - 2023_ DB - OpenUCT DP - University of Cape Town KW - Conservation Biology LK - https://open.uct.ac.za PY - 2023 T1 - The density of leopards in a mixed-use landscape in the Western Cape, South Africa TI - The density of leopards in a mixed-use landscape in the Western Cape, South Africa UR - http://hdl.handle.net/11427/38015 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/38015
dc.identifier.vancouvercitationHinde KC. The density of leopards in a mixed-use landscape in the Western Cape, South Africa. []. ,Faculty of Science ,Department of Biological Sciences, 2023 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/38015en_ZA
dc.language.rfc3066eng
dc.publisher.departmentDepartment of Biological Sciences
dc.publisher.facultyFaculty of Science
dc.subjectConservation Biology
dc.titleThe density of leopards in a mixed-use landscape in the Western Cape, South Africa
dc.typeMaster Thesis
dc.type.qualificationlevelMasters
dc.type.qualificationlevelMSc
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