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Article
The development of a spatially explicit model to estimate
The Science of the Total Environment (2005)
  • Karen F. Gaines, Eastern Illinois University
  • C. Shane Boring, Rutgers University
  • Dwayne E. Porter, University of Georgia
Abstract

A spatially explicit model of raccoon (Procyon lotor) distribution for the U.S. Department of Energy’s (DOE) Savannah River Site (SRS) in west-central South Carolina was developed using data from a raccoon radio-telemetry study and visualized within a Geographic Information System (GIS). An inductive approach was employed to develop three sub-models using the ecological requirements of raccoons studied in the following habitats: (1) man-made reservoirs, (2) bottomland hardwood/ riverine systems, and (3) isolated wetland systems. Logistic regression was used to derive probabilistic resource selection functions using habitat compositional data and landscape metrics. The final distribution model provides a spatially explicit probability (likelihood of being in an area) surface for male raccoons. The model is a stand-alone tool consisting of algorithms independent of the specific GIS data layers to which they were derived. The model was then used to predict contaminant burdens in raccoons inhabiting a riverine system contaminated with radiocaesium (137Cs). The predicted 137Cs burdens were less than if one would assume homogeneous use of the contaminated areas. This modelling effort provides a template for DOE managed lands and other large government facilities to establish a framework for site-specific ecological assessments that use wildlife species as endpoints.

Keywords
  • GIS,
  • Raccoons (Procyon lotor),
  • Radiocaesium,
  • Resource selection functions,
  • Risk assessment,
  • Spatial modelling
Disciplines
Publication Date
2005
Citation Information
Karen F. Gaines, C. Shane Boring and Dwayne E. Porter. "The development of a spatially explicit model to estimate" The Science of the Total Environment Vol. 341 (2005)
Available at: http://works.bepress.com/karen_gaines/19/