PARENT SESSION
Poster Session 37: Toxicology and Disease
Thursday, August 11, 5:00 PM - 6:30 PM, Exhibit Hall 220 A-E, Level 2, Palais des congrès de Montréal
Causal Analysis/Diagnosis Decision Information System for determining the causes of biological impairments in aquatic systems: Tools for evaluating metals as causal agents.
Shaw-Allen, Patricia1, Susan, Norton2, Susan, Cormier3, Suter, Glenn1, 1 US EPA Office of Research and Development, Cincinnati, OH, USA2 US EPA Office of Research and Development, Washington, DC, USA3 US EPA Office of Research and Development, Cincinnati, OH, USA
ABSTRACT- Over a thousand US waters are listed by states as biologically impaired. For many of these, the cause of the impairment is also reported as "unknown". Exceedence of metals criteria is the second most common reason for listing a water body as impaired, and therefore metals are likely to be a common cause of the biological impairments. Before an appropriate action can be taken to address a biological impairment, its primary cause must be determined. Defensible causal analyses require knowledge of the mechanisms, symptoms, and stressor-response relationships for various specific stressors as well as the ability to use that knowledge to draw appropriate conclusions. Components developed for the evaluation of metals as causes of biological impairments will be available through the Causal Analysis/Diagnosis Decision Information System (CADDIS). CADDIS is a web-based decision support system that will help investigators in the USEPA regions, states, and tribes find, access, organize, and share information useful for causal evaluations in aquatic systems. It is based on the USEPA's Stressor Identification process, which is a formal method for identifying causes of impairments in aquatic systems. Tools developed for the assessment of metals as causal agents include empirical stressor-response relationships such as species sensitivity distributions and exposure and tissue concentration response models. Species sensitivity distributions are interpreted in terms of consistency of taxa location among distributions as well as evenness of guild representation along these distributions. Syntheses of existing field data for metals effects under complex environmental conditions are also presented. Future versions will be developed incrementally and iteratively, and frequent user input and feedback will be essential to the system's success.
Key words: Metals, Causal Analysis, Stressor Identification, Biological Impairments