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Spatial modeling of receptor species for ecological risk assessment activities on the Department of Energy's Savannah River Site

Posted on:2004-03-15Degree:Ph.DType:Dissertation
University:University of South CarolinaCandidate:Gaines, Karen FrancesFull Text:PDF
GTID:1461390011476655Subject:Health Sciences
Abstract/Summary:
To assist risk assessors on the Department of Energy's Savannah River Site (SRS), a Geographic Information System (GIS) was developed to provide relevant information about specific receptor species that can be used for ecological risk assessment (ERA). Although this GIS is a useful tool, it is limited in that it can only provide information about a species if it was studied in that particular area and does not describe the site-wide spatial distribution or life history of a receptor species, which may be crucial when developing an ecological impact assessment. The GIS was expanded by modeling wildlife species on the SRS to provide information regarding their over-all distribution (probability of being in an area) and habitat utilization. Each model is a stand-alone tool consisting of algorithms that are applied within a GIS and therefore dynamic enough to respond to stochastic events such as natural and anthropogenic habitat disturbances and/or long-term changes such as natural succession. Spatial analyses suggest toxicant exposure and accumulation risk in relation to the species probability of occurrence in the area. This modeling effort provides the tools that are crucial for the Department of Energy to conduct ERA activities for specific contaminants on the SRS. Further, it serves as a template for DOE managed lands and other large government facilities to establish a framework for site-specific ecological impact assessments that use wildlife species as endpoints. Predictive distribution models for the raccoon (Procyon lotor) and wild hog (Sus scrofa ) are used to demonstrate the construction and utilization of these models to: (1) estimate wildlife toxicant exposure, (2) identify possible contaminant vectors, and (3) construct human-based risk assessments from consuming wild game.
Keywords/Search Tags:Risk, Species, Department, Assessment, GIS, Ecological, SRS, Spatial
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