North America’s rich and highly imperiled freshwater fauna can challenge the capacity of management agencies charged with preventing species extinctions. Most North American fishes, crayfishes, and mussels are knowledge- and data-deficient, which can limit analytical options for modeling imperilment risks under formal conservation assessments. A cross-agency research team consisting of USGS, U.S. Fish and Wildlife Service (USFWS), and university scientists are developing a tool to conduct imperilment risk assessments for freshwater fishes in the southeastern U.S. that have recently been petitioned for review under the Endangered Species Act (ESA). We introduce a Bayesian risk-assessment model, which leverages available fish distributional data, species traits, landscape stressor data, and expert judgment to support Species Status Assessments (SSAs). The model aligns with current USFWS mandates and terminology for SSAs, is robust to data-deficient situations, and can be quickly adapted for species with different life histories and emerging threats. In our presentation, we will discuss what we have learned from ground-truthing the model using datasets for three species with pre-existing SSAs (Carolina Madtom, Noturus furiosus; Candy Darter, Etheostoma osburni; Ozark Chub, Erimystax harryi). We will also discuss modifications to the model enabling its first use in support of actual SSA implementation for the Piebald Madtom (Noturus gladiator). The model could be used in support of status assessments for a backlog of ESA-petitioned fishes in the future, and its structure could potentially be modified to expand its scope to other commonly data-deficient freshwater taxonomic groups. 

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