Mississippi Project: Integrating Conservation Planning Tools to Develop a Transparent Conservation Blueprint for Southeastern Aquatic Species

Mississippi Project

Integrating Conservation Planning Tools to Develop a Transparent Conservation Blueprint for Southeastern Aquatic Species

October 2019 - August 2022

Personnel

Participating Agencies

USDOI Fish and Wildlife Service

Dozens of freshwater fishes will undergo formal Species Status Assessments under the Endangered Species Act over the next decade. However, most freshwater fishes are data-deficient, which creates uncertainty when evaluating species’ status. Therefore, we are developing an analytical framework and easy-to-use tools that integrate available data on species’ life history, distributions, and population trends for petitioned species. This work is a collaboration among Mississippi State University, USGS Mississippi Cooperative Fish and Wildlife Research Unit, and biologists with the US Fish and Wildlife Service. This decision-support tool will help the USFWS structure available information on petitioned fishes, thereby leading to more transparent, quantitative, and reproducible status assessments.

Research Publications

Research Publications	Publication Date
Dunn, C.G., D.A. Schumann, M.E. Colvin, L.J Sleezer, M. Wagner, D.T. Jones-Farrand, E. Rivenbark, S. McRae, and K. Evans. In 2024. Using resiliency, redundancy, and representation in a Bayesian belief network to assess imperilment of riverine fishes. Ecosphere. http://dx.doi.org/10.1002/ecs2.4738 \| Abstract \| Download \| Publisher Website	January 2024	Conservation-prioritization frameworks are used worldwide to identify species at greatest risk of extinction and to allocate limited resources across regions, species, and populations. Conservation prioritization can be impeded by ecological knowledge gaps and data deficiency, especially in freshwater species inhabiting highly complex aquatic ecosystems. Therefore, we developed a flexible approach that calculates a species’ imperilment risk based on the conservation principles of resiliency, redundancy, and representation (i.e., the “three R’s”). Our approach organizes data on species traits, distributions, population connectivity, and threats within a Bayesian belief network capable of predicting resiliency and redundancy within representative ecological settings. Empirical data and expert judgement inform the model to provide robust and repeatable risk assessments for rare and data-deficient species. The model calculates resiliency at hierarchical spatial scales from distributional trends and population strength. Redundancy is estimated from numbers and connectivity among extant populations. Resiliency, redundancy, and species’ inherent vulnerability based on species traits collectively estimate extirpation risk within each unique ecological setting. Extirpation risks across ecological settings characterize representation and are aggregated to estimate global imperilment risk. We demonstrate the model’s utility with Piebald Madtom (<i>Noturus gladiator</i>), a species petitioned for listing under the U.S. Endangered Species Act. Our results revealed that resiliency, redundancy, and extirpation risks can vary spatially across the species’ range while identifying populations where additional sampling could disproportionally reduce uncertainty in estimated global imperilment risk. Our approach could standardize and expedite conservation status assessments, identify opportunities for early management intervention of at-risk species and populations, and strategically reduce uncertainty by focusing monitoring and research on priority information gaps.

Presentations

Presentations	Presentation Date
Sleezer, L.J., C.G. Dunn, M.E. Colvin, D.A. Schumann, M Wagner, D.T. Jones-Farrand, E. Rivenbark, S. McRae, and J. Gilbert. 2024. Expanding Biologists’ Toolbox for Assessing the Status of Southeastern Freshwater Fishes. USGS Friday Findings Webinar.	January 2024
Dunn, C.G., Sleezer, L.J., M.E. Colvin, D.A. Schumann, M Wagner, D.T. Jones-Farrand, E. Rivenbark, S. McRae, and J. Gilbert. 2024. Believe it or not – A Bayesian network for estimating imperilment of data-deficient fishes. Southern Division of the American Fisheries Society. Chattanooga, TN	January 2024
Dunn, C.G., Sleezer, L.J., M.E. Colvin, D.A. Schumann, M Wagner, D.T. Jones-Farrand, E. Rivenbark, S. McRae, and J Gilbert. 2023. Believe it or not – A Bayesian network for estimating imperilment of data-deficient fishes. Annual meeting of the American Fisheries Society. Grand Rapids, Michigan	August 2023

Data or Software Releases

Type	Citation	Publication Date
Data Release	Dunn, C.G. and M.E. Colvin. 2023. “Piebald Madtom Bayesian belief network” (V1.2Pieblad_Madtom_BBN). Zenodo. https://doi.org/10.5281/zenodo.10034468	November 2023
Software Release	Dunn, C.G. and Colvin, M.E. 2023. R code for calculating imperilment of freshwater fish with a Bayesian belief network. Version 1.0.0: U.S. Geological Survey software release. Reston, Va. https://doi.org/10.5066/P9IBB2K5	October 2023

Cooperative Fish and Wildlife Research Units Program: Mississippi Education, Research and Technical Assistance for Managing Our Natural Resources