A Review of Methods for Quantifying Wildlife Habitat in Large Landscapes

Michael A. Larson, Joshua J. Millspaugh, Frank R. Thompson

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

5 Scopus citations


The methods of modeling wildlife habitat are classified into five general approaches that correspond to common objectives in habitat studies. Habitat Suitability Index (HSI) models are the basis of the Habitat Evaluation Procedure (HEP) developed by the US Fish and Wildlife Service and constitute a basic mathematical technique for quantifying the quality of wildlife habitat. Weighted linear combination (WLC) procedures for multicriteria evaluations provide an alternative framework to HEP for habitat quality indexing (HQI). When WLC procedures are implemented in raster geographic information system, values in maps of habitat attributes are standardized to the same unitless scale. In some cases, models for predicting the presence or absence of a species in an area are less complex and require less data than an HQI model because one can simply define only two categories on the landscape: areas that provide habitat and areas that do not. Approaches to evaluating the viability of a population using habitat data fall into four categories: assessing availability of high-quality habitat, Bayesian belief networks, population simulation, and estimating population growth rates directly. Availability of high-quality habitat can be estimated with home range mapping procedures.

Original languageEnglish
Title of host publicationModels for Planning Wildlife Conservation in Large Landscapes
PublisherElsevier Inc.
Number of pages26
ISBN (Print)9780123736314
StatePublished - 2009


We thank J. A. Hepinstall, B. J. Kernohan, G. J. Roloff, and several anonymous referees for providing critical reviews that helped us improve earlier drafts of this manuscript. We also appreciate the support of our employers, the Minnesota Department of Natural Resources, the University of Missouri, and the U.S. Forest Service.

FundersFunder number
Minnesota Department of Natural Resources
U.S. Forest Service-Retired
Southeast Missouri State University


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