Rachael S. Leeman, Robert S. Davis, Antonio Uzal, Heinrich Neumeyer, Rebecca A. Garbett, Joshua P. Twining, Richard W. Yarnell
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引用次数: 0
Abstract
Spatial capture‐recapture (SCR) provides the gold standard for robust population estimates where animals are individually identifiable. Sampling for large carnivores is often conducted over short timeframes to meet assumptions of population closure. As large carnivores are often elusive and found at low densities, surveys often result in low numbers of unique individuals captured and limited spatial recaptures, which can lead to convergence and parameter identifiability issues. In areas of high tourism footfall, additional spatial capture information can be provided by tourists. We supplemented individual encounter history data from a camera trap‐based monitoring programme for leopards (Panthera pardus) with tourist sighting data within multi‐session SCR models; we evaluated the benefits of combining multiple data sources. Integrating tourist observations improved the precision of estimates (Half Relative Confidence Interval Width: Combined = 23.1%), resulting in an overall density estimate of 7.02 leopards per 100 km2 (95% CI: 5.59–8.84 per 100 km2). Tourist‐derived methods were 92.5% cheaper than camera trapping, highlighting the cost‐efficiency of supplementing camera trap surveys with this source of data in areas with high tourism activity. This study demonstrates that combining structured survey data from camera traps with unstructured tourist‐derived images improves resultant density estimates compared to using either method alone. Supplementing structured camera trapping data with tourist images in areas of high tourism activity can offer improvements in scalability by increasing spatial and temporal coverage of sampling, with limited additional costs and improved precision in density estimates. To further enhance the reliability of these methods, we provide recommendations for improving citizen science reporting for integration into SCR frameworks.
期刊介绍:
emote Sensing in Ecology and Conservation provides a forum for rapid, peer-reviewed publication of novel, multidisciplinary research at the interface between remote sensing science and ecology and conservation. The journal prioritizes findings that advance the scientific basis of ecology and conservation, promoting the development of remote-sensing based methods relevant to the management of land use and biological systems at all levels, from populations and species to ecosystems and biomes. The journal defines remote sensing in its broadest sense, including data acquisition by hand-held and fixed ground-based sensors, such as camera traps and acoustic recorders, and sensors on airplanes and satellites. The intended journal’s audience includes ecologists, conservation scientists, policy makers, managers of terrestrial and aquatic systems, remote sensing scientists, and students.
Remote Sensing in Ecology and Conservation is a fully open access journal from Wiley and the Zoological Society of London. Remote sensing has enormous potential as to provide information on the state of, and pressures on, biological diversity and ecosystem services, at multiple spatial and temporal scales. This new publication provides a forum for multidisciplinary research in remote sensing science, ecological research and conservation science.