Advancing spatial analysis of invasive species movement data to improve monitoring, control programs and decision making: feral cat home range as a case study

Article


Wilson, Cameron, Gentle, Matthew and Fancourt, Bronwyn. 2024. "Advancing spatial analysis of invasive species movement data to improve monitoring, control programs and decision making: feral cat home range as a case study." Pacific Conservation Biology. 30 (5). https://doi.org/10.1071/PC24031
Article Title

Advancing spatial analysis of invasive species movement data to improve monitoring, control programs and decision making: feral cat home range as a case study

ERA Journal ID3301
Article CategoryArticle
AuthorsWilson, Cameron, Gentle, Matthew and Fancourt, Bronwyn
Journal TitlePacific Conservation Biology
Journal Citation30 (5)
Article NumberPC24031
Number of Pages11
Year2024
PublisherCSIRO Publishing
Place of PublicationAustralia
ISSN1038-2097
Digital Object Identifier (DOI)https://doi.org/10.1071/PC24031
Web Address (URL)https://www.publish.csiro.au/PC/PC24031
AbstractContext Many invasive animals are typically active across large areas, making monitoring and control programs expensive. To be efficacious, monitoring devices and control tools need to be strategically located to maximise the probability of encounter. This requires an understanding of how the target species uses the landscape, through identifying key habitat or landscape features that are preferred and used disproportionately more frequently by the species. Spatial analysis of animal movements can help identify high use areas. Aims The variability introduced by different range calculation methods can lead to uncertainty in subsequent habitat analyses. We aimed to determine which method is superior for accurate delineation of core areas for feral cats. Methods We analysed spatial data from 35 collared feral cats across four Australian study sites between 2016 and 2019, and compared the core areas generated using seven commonly used home range estimation methods. Key results We found that the alpha-hull method provided a higher precision of polygon placement, resulting in lower Type I and II errors and higher conformity to landscape features than other methods. The alpha-hull used a single default parameter and required no subjective input, making it a more objective, superior method. Conclusions We recommend that the alpha-hull method be used to define core activity areas for feral cats, enabling more robust habitat analysis, and identification of key habitat and landscape features to strategically target for monitoring and control programs. Implications This strategic approach could significantly improve cost efficiencies, particularly where existing management is widely dispersed, and core activity areas are clumped.
Keywordscore area; Felis catus; feral cat; GPS collar; home range; kernel; LoCoH; MCP; α-hull
Contains Sensitive ContentDoes not contain sensitive content
ANZSRC Field of Research 2020410407. Wildlife and habitat management
Byline AffiliationsUniversity of New England
Department of Agriculture and Fisheries, Queensland
School of Sciences
Department of Environment, Science and Innovation, Queensland
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