WA5 Making Ecotoxicology Studies Relevant
Room 17A/B, Level 4
8:00 AM - 12:00 PM, Wednesday, 12 November 2003
Chair: Adams, Marshall ,
(361) Making ecotoxicology studies relevant: the so what question.
Adams, S1, 1 Oak Ridge National Lab., Oak Ridge, TN, USA
ABSTRACT- Ecotoxicology by definition implies that studies conducted to determine the effects of environmental stressors on ecological systems will include measurements of at least one ecologically- relevant endpoint. Many studies conducted under an ecotoxicological framework, however, typically measure biomarkers and other toxicological types of endpoints but these responses have rarely been linked or causally related to effects at the individual, population, and/or community levels (the Aso what@ question). While responses at lower levels of biological organization such as the sensitive and rapidly-responding biomarkers are important for determining the mechanistic basis of stress effects on organisms, measures at higher levels of organization are key for understanding the ecological consequences of stress. As an example for establishing relationships between contaminant exposure and biologically-significant effects, we determined the responses of fish to stress at five levels of biological organization (biochemical, histopathological, reproductive, population, and community) in a stream with a distinct downstream gradient in contaminant loading. Biomarkers at lower levels of organization provided direct evidence of contaminant exposure while intermediate level responses such as histopathological and bioenergetic parameters were related to effects at the individual, population, and community levels. Presentations in this session provide a variety of examples which relate contaminant exposure to effects at several levels of biological organization. Such integrative studies help improve the predictive capability of ERA and also serve as the basis for more informed environmental management and regulatory decisions.
Key words: ecologically-relevant, ecotoxicology, causal relationships