Document Detail


A geographic information systems-based, weights-of-evidence approach for diagnosing aquatic ecosystem impairment.
MedLine Citation:
PMID:  16916044     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
A Geographic Information Systems-based, watershed-level assessment using Bayesian weights of evidence (WOE) and weighted logistic regression (WLR) provides a method to determine and compare potential environmental stressors in lotic ecosystems and to create predictive models of general or species-specific biological impairment across numerous spatial scales based on limited existing sample data. The WOE/WLR technique used in the present study is a data-driven, probabilistic approach conceptualized in epidemiological research and both developed for and currently used in minerals exploration. Extrapolation of this methodology to a case-study watershed assessment of the Great and Little Miami watersheds (OH, USA) using archival data yielded baseline results consistent with previous assessments. The method additionally produced a quantitative determination of physical and chemical watershed stressor associations with biological impairment and a predicted comparative probability (i.e., favorability) of biological impairment at a spatial resolution of 0.5 km2 over the watershed study region. Habitat stressors showed the greatest spatial association with biological impairment in low-order streams (on average, 56% of total spatial association), whereas water chemistry, particularly that of wastewater effluent, was associated most strongly with biological impairment in high-order reaches (on average, 79% of total spatial association, 28% of which was attributed to effluent). Significant potential stressors varied by land-use and stream order as well as by species. This WOE/WLR method provides a highly useful "tier 1" watershed risk assessment product through the integration of various existing data sources, and it produces a clear visual communication of areas favorable for biological impairment and a quantitative ranking of candidate stressors and associated uncertainty.
Authors:
Katherine E Kapo; G Allen Burton
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Environmental toxicology and chemistry / SETAC     Volume:  25     ISSN:  0730-7268     ISO Abbreviation:  Environ. Toxicol. Chem.     Publication Date:  2006 Aug 
Date Detail:
Created Date:  2006-08-18     Completed Date:  2006-12-05     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  8308958     Medline TA:  Environ Toxicol Chem     Country:  United States    
Other Details:
Languages:  eng     Pagination:  2237-49     Citation Subset:  IM    
Affiliation:
Institute for Environmental Quality, Wright State University, 3640 Colonel Glenn Highway, Dayton, Ohio 45435, USA. kapo.2@wright.edu
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MeSH Terms
Descriptor/Qualifier:
Bayes Theorem
Ecosystem*
Geographic Information Systems*
Probability
Species Specificity

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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