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Defining habitat covariates in camera-trap based occupancy studies
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, with...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4657010/ https://www.ncbi.nlm.nih.gov/pubmed/26596779 http://dx.doi.org/10.1038/srep17041 |
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author | Niedballa, Jürgen Sollmann, Rahel Mohamed, Azlan bin Bender, Johannes Wilting, Andreas |
author_facet | Niedballa, Jürgen Sollmann, Rahel Mohamed, Azlan bin Bender, Johannes Wilting, Andreas |
author_sort | Niedballa, Jürgen |
collection | PubMed |
description | 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 in-situ 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 in-situ 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. |
format | Online Article Text |
id | pubmed-4657010 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-46570102015-11-30 Defining habitat covariates in camera-trap based occupancy studies Niedballa, Jürgen Sollmann, Rahel Mohamed, Azlan bin Bender, Johannes Wilting, Andreas Sci Rep Article 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 in-situ 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 in-situ 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. Nature Publishing Group 2015-11-24 /pmc/articles/PMC4657010/ /pubmed/26596779 http://dx.doi.org/10.1038/srep17041 Text en Copyright © 2015, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Niedballa, Jürgen Sollmann, Rahel Mohamed, Azlan bin Bender, Johannes Wilting, Andreas Defining habitat covariates in camera-trap based occupancy studies |
title | Defining habitat covariates in camera-trap based occupancy studies |
title_full | Defining habitat covariates in camera-trap based occupancy studies |
title_fullStr | Defining habitat covariates in camera-trap based occupancy studies |
title_full_unstemmed | Defining habitat covariates in camera-trap based occupancy studies |
title_short | Defining habitat covariates in camera-trap based occupancy studies |
title_sort | defining habitat covariates in camera-trap based occupancy studies |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4657010/ https://www.ncbi.nlm.nih.gov/pubmed/26596779 http://dx.doi.org/10.1038/srep17041 |
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