Abstract
Watersheds are subjected to diverse anthropogenic inputs, exposing aquatic biota to a wide range of chemicals. Detection of multiple, different chemicals can challenge natural resource managers who often have to determine where to allocate potentially limited resources. Here, we describe a weight-of-evidence framework for retrospectively prioritizing aquatic contaminants. To demonstrate framework utility, we used data from 96-h caged fish studies to prioritize chemicals detected in the Milwaukee Estuary (WI, USA; 2017-2018). Across study years, 77/178 targeted chemicals were detected. Chemicals were assigned prioritization scores based on spatial and temporal detection frequency, environmental distribution, environmental fate, ecotoxicological potential, and effect prediction. Chemicals were sorted into priority bins based on the intersection of prioritization score and data availability. Data-limited chemicals represented those that did not have sufficient data to adequately evaluate ecotoxicological potential or environmental fate. Seven compounds (fluoranthene, benzo[a]pyrene, pyrene, atrazine, metolachlor, phenanthrene, and DEET) were identified as high or medium priority and data sufficient and flagged as candidates for further effects-based monitoring studies. Twenty-one compounds were identified as high or medium priority and data limited and flagged as candidates for further ecotoxicological research. Fifteen chemicals were flagged as the lowest priority in the watershed. One of these chemicals (2-methylnaphthalene) displayed no data limitations and was flagged as a definitively low-priority chemical. The remaining chemicals displayed some data limitations and were considered lower-priority compounds (contingent on further ecotoxicological and environmental fate assessments). The remaining 34 compounds were flagged as low or medium priority. Altogether, this prioritization provided a screening-level (non-definitive) assessment that could be used to focus further resource management and risk assessment activities in the Milwaukee Estuary. Furthermore, by providing detailed methodology and a practical example with real experimental data, we demonstrated that the proposed framework represents a transparent and adaptable approach for prioritizing contaminants in freshwater environments. Integr Environ Assess Manag 2023;19:1276-1296. © 2022 SETAC.