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Abstract-Realistic and reliable methods are needed for the accurate characterization of the potential ecological risks posed by pesticides. This study presents a sequence of risk assessment methods that are based on the comparison of exposure concentrations to laboratory-derived toxicity data for representative species of aquatic organisms exposed to pesticides. The sequence of methods progresses from single-value quotient calculations to comparison of cumulative distributions of exposure and toxicity data and culminates with the use of Monte Carlo methods to estimate distributions of quotients. To illustrate the sequence of increasingly quantitative methods, we used a case study of the ecological risks posed by diquat dibromide in U.S. regional lakes and farm ponds. Diquat dibromide is a well-studied aquatic herbicide and is one of only a few pesticides registered for direct use in aquatic systems. The exposure concentration for the farm pond scenario used in the U.S. Environmental Protection Agency reregistration eligibility decision for diquat dibromide was used. In addition, exposure concentrations were developed for several regional lake and farm pond scenarios using the Exposure Analysis Modeling System (EXAMSII) methodology with separate, region-specific parameter values and simulated diquat dibromide application rates. Except for the results obtained in the conservative quotient method, the calculations for diquat dibromide were consistent with its demonstrated high safety. This suggests that a minimal ecological impact to benthic invertebrates and fish exists. Aquatic plants in the vicinity of application to surface waters appear to be at risk, and this is expected, as diquat dibromide kills aquatic plants. Comparisons of cumulative distributions of exposure and toxicity data provided the most quantitative approach to characterizing risks. The probabilistic quotient approach does not specifically estimate ecological risk. However, the implicit correlation between increasing values of quotients and increased potential risk does suggest the utility of these methods for identifying pesticides as acceptable for registration and use (i.e., minimal risk compared to benefits) or unacceptable.

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