A Spatially Explicit Model of the Wild Hog for Ecological Risk Assessment Activities at the Department of Energy's Savannah River Site

Karen F. Gaines, Dwayne E. Porter, Tracy Punshon, I. Lehr Brisbin

Research output: Contribution to journalArticlepeer-review

Abstract

In North America, wild hogs (Sus scrofa) are both sought after as prime game and despised due to their detrimental impacts to the environment from their digging and rooting behavior. They are also a potentially useful indicator species for environmental health for both ecological- and human-based risk assessments. An inductive approach was used to develop probabilistic resource selection models using logistic regression to quantify the likelihood of hogs being in any area of the Department of Energy’s 805 km2 Savannah River Site (SRS) in west-central South Carolina. These models were derived by using available SRS hog hunt data from 1993–2000 and a Geographic Information System database describing the habitat structure of the SRS. The model’s significant parameters indicated that wild hogs preferred hardwoods and avoided pine and shrubby areas. Further, landscape metric analyses revealed that hogs preferred areas with large complex patch areas and low size variation. These resource selection models were then utilized to better estimate exposure of wild hogs to radionuclides and metals in a disturbed riparian ecosystem on the SRS using two different possible diets based on food availability. Contaminant exposure can be better estimated using these resource selection models than has been previously possible, because past practices did not consider home range and habitat utilization probability in heterogeneously contaminated habitats. Had these models not been used, risk calculations would assume that contaminated areas were utilized 100% of the time, thus overestimating exposure by a factor of up to 25.

Original languageAmerican English
JournalHuman and Ecological Risk Assessment
Volume11
StatePublished - 2005
Externally publishedYes

Keywords

  • aluminum
  • ecological assessment
  • GIS
  • home range
  • landscape metrics

Disciplines

  • Biology

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