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Resampling Method for Applying Density-Dependent Habitat Selection Theory to Wildlife Surveys

Isodar theory can be used to evaluate fitness consequences of density-dependent habitat selection by animals. A typical habitat isodar is a regression curve plotting competitor densities in two adjacent habitats when individual fitness is equal. Despite the increasing use of habitat isodars, their a...

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Autores principales: Tardy, Olivia, Massé, Ariane, Pelletier, Fanie, Fortin, Daniel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4456250/
https://www.ncbi.nlm.nih.gov/pubmed/26042998
http://dx.doi.org/10.1371/journal.pone.0128238
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author Tardy, Olivia
Massé, Ariane
Pelletier, Fanie
Fortin, Daniel
author_facet Tardy, Olivia
Massé, Ariane
Pelletier, Fanie
Fortin, Daniel
author_sort Tardy, Olivia
collection PubMed
description Isodar theory can be used to evaluate fitness consequences of density-dependent habitat selection by animals. A typical habitat isodar is a regression curve plotting competitor densities in two adjacent habitats when individual fitness is equal. Despite the increasing use of habitat isodars, their application remains largely limited to areas composed of pairs of adjacent habitats that are defined a priori. We developed a resampling method that uses data from wildlife surveys to build isodars in heterogeneous landscapes without having to predefine habitat types. The method consists in randomly placing blocks over the survey area and dividing those blocks in two adjacent sub-blocks of the same size. Animal abundance is then estimated within the two sub-blocks. This process is done 100 times. Different functional forms of isodars can be investigated by relating animal abundance and differences in habitat features between sub-blocks. We applied this method to abundance data of raccoons and striped skunks, two of the main hosts of rabies virus in North America. Habitat selection by raccoons and striped skunks depended on both conspecific abundance and the difference in landscape composition and structure between sub-blocks. When conspecific abundance was low, raccoons and striped skunks favored areas with relatively high proportions of forests and anthropogenic features, respectively. Under high conspecific abundance, however, both species preferred areas with rather large corn-forest edge densities and corn field proportions. Based on random sampling techniques, we provide a robust method that is applicable to a broad range of species, including medium- to large-sized mammals with high mobility. The method is sufficiently flexible to incorporate multiple environmental covariates that can reflect key requirements of the focal species. We thus illustrate how isodar theory can be used with wildlife surveys to assess density-dependent habitat selection over large geographic extents.
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spelling pubmed-44562502015-06-09 Resampling Method for Applying Density-Dependent Habitat Selection Theory to Wildlife Surveys Tardy, Olivia Massé, Ariane Pelletier, Fanie Fortin, Daniel PLoS One Research Article Isodar theory can be used to evaluate fitness consequences of density-dependent habitat selection by animals. A typical habitat isodar is a regression curve plotting competitor densities in two adjacent habitats when individual fitness is equal. Despite the increasing use of habitat isodars, their application remains largely limited to areas composed of pairs of adjacent habitats that are defined a priori. We developed a resampling method that uses data from wildlife surveys to build isodars in heterogeneous landscapes without having to predefine habitat types. The method consists in randomly placing blocks over the survey area and dividing those blocks in two adjacent sub-blocks of the same size. Animal abundance is then estimated within the two sub-blocks. This process is done 100 times. Different functional forms of isodars can be investigated by relating animal abundance and differences in habitat features between sub-blocks. We applied this method to abundance data of raccoons and striped skunks, two of the main hosts of rabies virus in North America. Habitat selection by raccoons and striped skunks depended on both conspecific abundance and the difference in landscape composition and structure between sub-blocks. When conspecific abundance was low, raccoons and striped skunks favored areas with relatively high proportions of forests and anthropogenic features, respectively. Under high conspecific abundance, however, both species preferred areas with rather large corn-forest edge densities and corn field proportions. Based on random sampling techniques, we provide a robust method that is applicable to a broad range of species, including medium- to large-sized mammals with high mobility. The method is sufficiently flexible to incorporate multiple environmental covariates that can reflect key requirements of the focal species. We thus illustrate how isodar theory can be used with wildlife surveys to assess density-dependent habitat selection over large geographic extents. Public Library of Science 2015-06-04 /pmc/articles/PMC4456250/ /pubmed/26042998 http://dx.doi.org/10.1371/journal.pone.0128238 Text en © 2015 Tardy et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Tardy, Olivia
Massé, Ariane
Pelletier, Fanie
Fortin, Daniel
Resampling Method for Applying Density-Dependent Habitat Selection Theory to Wildlife Surveys
title Resampling Method for Applying Density-Dependent Habitat Selection Theory to Wildlife Surveys
title_full Resampling Method for Applying Density-Dependent Habitat Selection Theory to Wildlife Surveys
title_fullStr Resampling Method for Applying Density-Dependent Habitat Selection Theory to Wildlife Surveys
title_full_unstemmed Resampling Method for Applying Density-Dependent Habitat Selection Theory to Wildlife Surveys
title_short Resampling Method for Applying Density-Dependent Habitat Selection Theory to Wildlife Surveys
title_sort resampling method for applying density-dependent habitat selection theory to wildlife surveys
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4456250/
https://www.ncbi.nlm.nih.gov/pubmed/26042998
http://dx.doi.org/10.1371/journal.pone.0128238
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