A Regional Landscape Analysis and Prediction of Favorable Gray Wolf Habitat in the Northern Great Lakes Region

A Regional Landscape Analysis and Prediction of Favorable Gray Wolf Habitat in the Northern Great... Over the past 15 years the endangered eastern timber wolf (Canis lupus lycaon) has been slowly recolonizing northern Wisconsin and, more recently, upper Michigan, largely by dispersing from Minnesota (where it is listed as threatened). We have used geographic information systems (GISs) and spatial radiocollar data on recolonizing wolves in northern Wisconsin to assess the importance of factors in defining favorable wolf habitat. We built a multiple logistic regression model applied to the northern Great Lakes states to estimate the amount and spatial distribution of favorable wolf habitat at the regional landscape scale. Our results suggest that areas with high probability of favorable habitat are more extensive than previously estimated in the northern Great Lake States. Several variables were significant in comparing new pack areas in Wisconsin to nonpack areas, including land ownership class, land cover type, road density, human population, and spatial landscape indices such as fractal dimension (land cover patch boundary complexity), land cover type contagion, landscape diversity, and landscape dominance. Road density and fractal dimension were the most important predictor variables in the logistic regression models. The results indicate that public forest land and private industrial forest land are both important in managing for a broad‐ranging animal such as the wolf. Our data portray favorable habitat that is highly fragmented along development corridors in northern Wisconsin, which may be responsible for the slow growth of the wolf population. Upper Michigan, which is just beginning to be colonized by wolves, has very large, contiguous areas of likely habitat approaching the importance of those in northeastern Minnesota. If continuing development or wolf control restrict dispersing wolves from moving from Minnesota to Wisconsin, and Wisconsin habitat becomes more marginal through further fragmentation, Michigan has the potential to maintain a significant wolf population independent of Minnesota and serve as a source population for Wisconsin. However, a simple island/corridor model of wolf habitat in Wisconsin does not seem to apply. Wolves apparently move throughout the landscape, across many unfavorable areas, but establishment success is restricted to higher quality habitat. Source‐sink dynamics may be operating here, and they suggest that reduction of the Minnesota population in the near term may affect recovery in Wisconsin and Michigan. Our analysis is an example of use of long‐term monitoring data and large‐scale cross‐boundary regional analysis that must be done to solve complex spatial questions in resource management and conservation. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Conservation Biology Wiley

A Regional Landscape Analysis and Prediction of Favorable Gray Wolf Habitat in the Northern Great Lakes Region

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Publisher
Wiley
Copyright
Copyright © 1995 Wiley Subscription Services, Inc., A Wiley Company
ISSN
0888-8892
eISSN
1523-1739
DOI
10.1046/j.1523-1739.1995.9020279.x
Publisher site
See Article on Publisher Site

Abstract

Over the past 15 years the endangered eastern timber wolf (Canis lupus lycaon) has been slowly recolonizing northern Wisconsin and, more recently, upper Michigan, largely by dispersing from Minnesota (where it is listed as threatened). We have used geographic information systems (GISs) and spatial radiocollar data on recolonizing wolves in northern Wisconsin to assess the importance of factors in defining favorable wolf habitat. We built a multiple logistic regression model applied to the northern Great Lakes states to estimate the amount and spatial distribution of favorable wolf habitat at the regional landscape scale. Our results suggest that areas with high probability of favorable habitat are more extensive than previously estimated in the northern Great Lake States. Several variables were significant in comparing new pack areas in Wisconsin to nonpack areas, including land ownership class, land cover type, road density, human population, and spatial landscape indices such as fractal dimension (land cover patch boundary complexity), land cover type contagion, landscape diversity, and landscape dominance. Road density and fractal dimension were the most important predictor variables in the logistic regression models. The results indicate that public forest land and private industrial forest land are both important in managing for a broad‐ranging animal such as the wolf. Our data portray favorable habitat that is highly fragmented along development corridors in northern Wisconsin, which may be responsible for the slow growth of the wolf population. Upper Michigan, which is just beginning to be colonized by wolves, has very large, contiguous areas of likely habitat approaching the importance of those in northeastern Minnesota. If continuing development or wolf control restrict dispersing wolves from moving from Minnesota to Wisconsin, and Wisconsin habitat becomes more marginal through further fragmentation, Michigan has the potential to maintain a significant wolf population independent of Minnesota and serve as a source population for Wisconsin. However, a simple island/corridor model of wolf habitat in Wisconsin does not seem to apply. Wolves apparently move throughout the landscape, across many unfavorable areas, but establishment success is restricted to higher quality habitat. Source‐sink dynamics may be operating here, and they suggest that reduction of the Minnesota population in the near term may affect recovery in Wisconsin and Michigan. Our analysis is an example of use of long‐term monitoring data and large‐scale cross‐boundary regional analysis that must be done to solve complex spatial questions in resource management and conservation.

Journal

Conservation BiologyWiley

Published: Apr 1, 1995

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