Habitat and exposure modelling for ecological risk assessment: A

T. Edwin Chow, Karen F. Gaines, Michael E. Hodgson, Machelle D. Wilson

Research output: Contribution to journalArticlepeer-review

Abstract

Contamination has a dramatic impact on the health of ecosystem and habitat suitability for the inhabited flora and fauna. The Environmental Protection Agency (EPA) mandates an ecological risk assessment (ERA) that evaluates the potential adverse impact of any anthropogenic activities on the ecosystem (US Environmental Protection Agency, 1997. Ecological Risk Assessment Guidance for Superfund: Process for Designing and Conducting Ecological Risk Assessment. EPA/630/R-021011, Washington, DC). This study provides a general framework and specific procedures to predict the contaminant exposure of midsized mammals using a geographical information system (GIS)-based Monte Carlo simulation model. The model was applied to the raccoons (Procyon lotor) on the Savannah River Site (SRS), a former nuclear production and current research facility. Habitat behavioral data of 13 radiocollared male raccoons were used to determine home range and core areas. Combined with other geographic data layers, such as distance to water, number of wetlands, and class landscape metrics, a logistic regression model was used to inductively derive the resource selection functions that define the occurrence of raccoon. The cross validation consistently revealed a high accuracy. A Monte Carlo simulation was then performed to estimate the likelihood of exposure and contaminant uptake of the species weighted by the resource selection probability. This model adopted conservative assumptions and spatial parameters. The proposed model served the purpose of assessing ecological risk and supporting decision-making. Implementation issues for a GIS-based ecological risk assessment model are discussed.

Original languageAmerican English
JournalEcological Modelling
Volume189
StatePublished - 2005
Externally publishedYes

Keywords

  • Ecologic risk assessment
  • Geographic information system
  • Habitat
  • Exposure
  • Raccoon
  • Monte Carlo simulation

Disciplines

  • Biology

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