• Medientyp: E-Artikel
  • Titel: Defining habitat covariates in camera-trap based occupancy studies
  • Beteiligte: Niedballa, Jürgen; Sollmann, Rahel; Mohamed, Azlan bin; Bender, Johannes; Wilting, Andreas
  • Erschienen: Springer Science and Business Media LLC, 2015
  • Erschienen in: Scientific Reports
  • Sprache: Englisch
  • DOI: 10.1038/srep17041
  • ISSN: 2045-2322
  • Entstehung:
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  • Beschreibung: <jats:title>Abstract</jats:title><jats:p>In species-habitat association studies, both the type and spatial scale of habitat covariates need to match the ecology of the focal species. We assessed the potential of high-resolution satellite imagery for generating habitat covariates using camera-trapping data from Sabah, Malaysian Borneo, within an occupancy framework. We tested the predictive power of covariates generated from satellite imagery at different resolutions and extents (focal patch sizes, 10–500 m around sample points) on estimates of occupancy patterns of six small to medium sized mammal species/species groups. High-resolution land cover information had considerably more model support for small, patchily distributed habitat features, whereas it had no advantage for large, homogeneous habitat features. A comparison of different focal patch sizes including remote sensing data and an <jats:italic>in-situ</jats:italic> measure showed that patches with a 50-m radius had most support for the target species. Thus, high-resolution satellite imagery proved to be particularly useful in heterogeneous landscapes and can be used as a surrogate for certain <jats:italic>in-situ</jats:italic> measures, reducing field effort in logistically challenging environments. Additionally, remote sensed data provide more flexibility in defining appropriate spatial scales, which we show to impact estimates of wildlife-habitat associations.</jats:p>
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