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Probability Surveys, Conditional Probabilities, and Ecological Risk Assessment

John F. Paul 1 and Wayne R. Munns, Jr. 2

1 U.S. Environmental Protection Agency (USEPA), NHEERL Mail Code B343-06, RTP, NC 27711
2 USEPA Atlantic Ecology Division, Narragansett, RI 20882

We show that probability-based environmental resource monitoring programs, such as U.S. Environmental Protection Agency’s ( U.S. EPA) Environmental Monitoring and Assessment Program (EMAP) and conditional probability analysis (CPA) can be used to conduct quantitative probabilistic ecological risk assessments over broad geographic areas. Under certain conditions (including appropriate stratification of the sampled population, sufficient density of samples, appropriate exposure and response variables, and sufficient range of exposure intensities to exert an observable effect ), this empirical approach provides estimates of risk from extant field-derived monitoring data. We illustrate this approach for risks to benthic communities from low dissolved oxygen (DO) in freshwater streams of the Mid-Atlantic region and in estuaries of the Virginian Biogeographical Province of the United States. In both cases, the resulting patterns of risk are consistent with the U.S. EPA’s ambient water quality criteria for DO. CPA of probability survey data can also support identification of environmental thresholds for use in establishing protective criteria. When considered with their original use to provide unbiased estimates of resource condition, probability-based monitoring programs can form the basis for cost-effective environmental management.

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