Under the Endangered Species Act, the US Environmental Protection Agency (EPA) is required to assess potential risks to threatened and endangered (listed) species when registering pesticides. In cases, where the pesticide “may affect” one or more listed species, the EPA must consult with the Services (i.e., National Marine Fisheries Service [NMFS], Fish and Wildlife Service [FWS]). Recent endangered species assessments for chlorpyrifos, diazinon and malathion by EPA and NMFS included a weight-of-evidence (WOE) approach to make their “may affect/no effect” and “jeopardy/no jeopardy” conclusions. The Agencies’ WOE approach was troubling in several respects. First, the lines of evidence given by far the greatest weight in the assessments were slight variations on the same theme, i.e., comparison of modeled exposure estimates to highly correlated endpoints. These “lines of evidence” are really just one line of evidence with multiple measures of effect. As pointed out by Glenn Suter and Susan Cormier in a 2011 publication, if an assessor has ten toxicity tests and one field observational study, the assessor would combine the toxicity tests into one line of evidence, weight it, and combine it with the weighted field observational study line of evidence. Second, the Agencies only superficially considered other lines of evidence, e.g., water quality monitoring studies, mesocosm and field toxicity tests, <i>in situ</i> tests, field observation studies, incident reports, listed species population trends, etc. Finally, the scoring system used by the Agencies to arrive at their risk conclusions was simplistic, qualitative and relied heavily on professional judgment. In this presentation, a WOE approach and rubric for weighting and combining lines of evidence is proposed for endangered species risk assessments involving pesticides. The WOE approach and rubric are simply adaptations of what has been commonly used elsewhere since the early 1990s.

Weight-of-evidence pesticide assessments for threatened and endangered species to inform management decisions

256th National Meeting (2018)

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