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USING MODELS TO EXTRAPOLATE POPULATION-LEVEL EFFECTS FROM LABORATORY TOXICITY TESTS IN SUPPORT OF POPULATION RISK ASSESSMENTS
Citation:
Munns Jr., W R., A Kuhn, M. Mitro, AND T R. Gleason. USING MODELS TO EXTRAPOLATE POPULATION-LEVEL EFFECTS FROM LABORATORY TOXICITY TESTS IN SUPPORT OF POPULATION RISK ASSESSMENTS. Presented at Society of Environmental Toxicology and Chemistry Annual Meeting, Salt Lake City, UT, November 16-20, 2002.
Description:
Using models to extrapolate population-level effects from laboratory toxicity tests in support of population risk assessments. Munns, W.R., Jr.*, Anne Kuhn, Matt G. Mitro, and Timothy R. Gleason, U.S. EPA ORD NHEERL, Narragansett, RI, USA. Driven in large part by management goals, statutory requirements and stakeholder interests, populations of wildlife and aquatic organisms often are the assessment endpoint entities (assessment population) in ecological risk assessments. Yet, actual population risk assessments are seldom conducted, due primarily to the scientific and technical difficulties they entail. As with other activities in the risk assessment process, modeling offers a way to overcome some of these difficulties, albeit not without some concomitant degree of uncertainty. In this presentation, we describe a body of work to develop modeling approaches that can be used to characterize effects of chemical stressors on populations using data obtained from toxicity tests, and identify some of the assumptions, strengths and limitations of these approaches in population risk assessments. We suggest that models are best used to extrapolate population level effects when the tested species is the same as the assessment population, but that across-species extrapolations require special consideration because of differences in species' life histories. Certain population modeling approaches can be effective for extrapolating from laboratory to field situations, especially when they incorporate spatial and temporal heterogeneity in exposure, environmental conditions (e.g., habitat quality) and biological response explicitly. Models also can be used to establish threshold concentrations expected to elicit ecologically significant population response. We conclude that modeling is a useful tool to support population risk assessments when model limitations and uncertainties are considered and communicated openly.