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Modeling Fence Location and Density at a Regional Scale for Use in Wildlife Management

Barbed and woven wire fences, common structures across western North America, act as impediments to wildlife movements. In particular, fencing influences pronghorn (Antilocapra americana) daily and seasonal movements, as well as modifying habitat selection. Because of fencing's impacts to prong...

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Autores principales: Poor, Erin E., Jakes, Andrew, Loucks, Colby, Suitor, Mike
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3885515/
https://www.ncbi.nlm.nih.gov/pubmed/24416180
http://dx.doi.org/10.1371/journal.pone.0083912
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author Poor, Erin E.
Jakes, Andrew
Loucks, Colby
Suitor, Mike
author_facet Poor, Erin E.
Jakes, Andrew
Loucks, Colby
Suitor, Mike
author_sort Poor, Erin E.
collection PubMed
description Barbed and woven wire fences, common structures across western North America, act as impediments to wildlife movements. In particular, fencing influences pronghorn (Antilocapra americana) daily and seasonal movements, as well as modifying habitat selection. Because of fencing's impacts to pronghorn and other wildlife, it is a potentially important factor in both wildlife movement and habitat selection models. At this time, no geospatial fencing data is available at regional scales. Consequently, we constructed a regional fence model using a series of land tenure assumptions for the Hi-Line region of northern Montana – an area consisting of 13 counties over 103,400 km(2). Randomized 3.2 km long transects (n = 738) on both paved and unpaved roads were driven to collect information on habitat, fence densities and fence type. Using GIS, we constructed a fence location and a density model incorporating ownership, size, neighboring parcels, township boundaries and roads. Local knowledge of land ownership and land use assisted in improving the final models. We predict there is greater than 263,300 km of fencing in the Hi-Line region, with a maximum density of 6.8 km of fencing per km(2) and mean density of 2.4 km of fencing per km(2). Using field data to assess model accuracy, Cohen's Kappa was measured at 0.40. On-the-ground fence modification or removal could be prioritized by identifying high fence densities in critical wildlife areas such as pronghorn migratory pathways or sage grouse lekking habitat. Such novel fence data can assist wildlife and land managers to assess effects of anthropogenic features to wildlife at various scales; which in turn may help conserve declining grassland species and overall ecological functionality.
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spelling pubmed-38855152014-01-10 Modeling Fence Location and Density at a Regional Scale for Use in Wildlife Management Poor, Erin E. Jakes, Andrew Loucks, Colby Suitor, Mike PLoS One Research Article Barbed and woven wire fences, common structures across western North America, act as impediments to wildlife movements. In particular, fencing influences pronghorn (Antilocapra americana) daily and seasonal movements, as well as modifying habitat selection. Because of fencing's impacts to pronghorn and other wildlife, it is a potentially important factor in both wildlife movement and habitat selection models. At this time, no geospatial fencing data is available at regional scales. Consequently, we constructed a regional fence model using a series of land tenure assumptions for the Hi-Line region of northern Montana – an area consisting of 13 counties over 103,400 km(2). Randomized 3.2 km long transects (n = 738) on both paved and unpaved roads were driven to collect information on habitat, fence densities and fence type. Using GIS, we constructed a fence location and a density model incorporating ownership, size, neighboring parcels, township boundaries and roads. Local knowledge of land ownership and land use assisted in improving the final models. We predict there is greater than 263,300 km of fencing in the Hi-Line region, with a maximum density of 6.8 km of fencing per km(2) and mean density of 2.4 km of fencing per km(2). Using field data to assess model accuracy, Cohen's Kappa was measured at 0.40. On-the-ground fence modification or removal could be prioritized by identifying high fence densities in critical wildlife areas such as pronghorn migratory pathways or sage grouse lekking habitat. Such novel fence data can assist wildlife and land managers to assess effects of anthropogenic features to wildlife at various scales; which in turn may help conserve declining grassland species and overall ecological functionality. Public Library of Science 2014-01-08 /pmc/articles/PMC3885515/ /pubmed/24416180 http://dx.doi.org/10.1371/journal.pone.0083912 Text en © 2014 Poor 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
Poor, Erin E.
Jakes, Andrew
Loucks, Colby
Suitor, Mike
Modeling Fence Location and Density at a Regional Scale for Use in Wildlife Management
title Modeling Fence Location and Density at a Regional Scale for Use in Wildlife Management
title_full Modeling Fence Location and Density at a Regional Scale for Use in Wildlife Management
title_fullStr Modeling Fence Location and Density at a Regional Scale for Use in Wildlife Management
title_full_unstemmed Modeling Fence Location and Density at a Regional Scale for Use in Wildlife Management
title_short Modeling Fence Location and Density at a Regional Scale for Use in Wildlife Management
title_sort modeling fence location and density at a regional scale for use in wildlife management
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3885515/
https://www.ncbi.nlm.nih.gov/pubmed/24416180
http://dx.doi.org/10.1371/journal.pone.0083912
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