Leetown Project: Update to Tennessee Status Assessments and Recovery Plans for Listed Mussel Species

Leetown Project

Update to Tennessee Status Assessments and Recovery Plans for Listed Mussel Species

January 2018 - January 2025

Personnel

Participating Agencies

Tennessee Wildlife Resource Agency
USGS
Fish and Wildlife Service

Research is designed to assist the Fish and Wildlife Service with their backlog of Status Assessments, Recovery Plans, and baseline information for species listed or proposed for listing under the Endangered Species Act using the best available information, methodology, and scientific approaches.

Research Publications

Research Publications	Publication Date
Fitzgerald, D., A. Henderson, K. Maloney, M. Freeman, J. Young, A. Rosenberger, D. Kazyak, and D. Smith. 2021. A Bayesian framework for assessing extinction risk based on ordinal categories of population condition and projected landscape change. Biological Conservation 253: https://doi.org/10.1016/j.biocon.2020.108866 \| Abstract	December 2020	Many at-risk species lack standardized surveys across their range or quantitative data capable of detecting demographic trends. As a result, extinction risk assessments often rely on ordinal categories of risk based on explicit criteria or expert elicitation. This study demonstrates a Bayesian approach to assessing extinction risk based on this common data structure, using three freshwater mussel species being considered for listing under the US Endangered Species Act. The probability that a population is classified under each risk category was modeled as a function of projected landscape change using ordered probit regression, assuming observed categories reflect a latent, continuous probability of persistence. All three species were more likely than not (mean probability > 0.5) to be classified as extirpated or low condition throughout their range based on effects of urban development and hydrologic alteration. Spatial variation in estimates revealed strongholds and high-risk areas relevant to conservation decision making. Projected change in probabilities of each risk category based on multiple land-use and climate models was generally small relative to high baseline risk resulting from past landscape changes. Assessing extinction risk based on probabilities of ordinal condition as a function of landscape patterns may provide a flexible and robust approach for many at-risk taxa by adjusting species’ demographic criteria to match relative risk categories, following standardized criteria, or using expert elicitation for data-deficient species. This approach provides decision makers with a useful measure of uncertainty around ordinal classifications and provides a framework for estimating future risk based on projections of anthropogenic stressors.<br>
Fitzgerald, D., A. Henderson, K. Maloney, M. Freeman, J. Young, A. Rosenberger, D. Kazyak, and D. Smith. 2021. A Bayesian framework for assessing extinction risk based on ordinal categories of population condition and projected landscape change. Biological Conservation 253: https://doi.org/10.1016/j.biocon.2020.108866 \| Abstract	December 2020	Many at-risk species lack standardized surveys across their range or quantitative data capable of detecting demographic trends. As a result, extinction risk assessments often rely on ordinal categories of risk based on explicit criteria or expert elicitation. This study demonstrates a Bayesian approach to assessing extinction risk based on this common data structure, using three freshwater mussel species being considered for listing under the US Endangered Species Act. The probability that a population is classified under each risk category was modeled as a function of projected landscape change using ordered probit regression, assuming observed categories reflect a latent, continuous probability of persistence. All three species were more likely than not (mean probability > 0.5) to be classified as extirpated or low condition throughout their range based on effects of urban development and hydrologic alteration. Spatial variation in estimates revealed strongholds and high-risk areas relevant to conservation decision making. Projected change in probabilities of each risk category based on multiple land-use and climate models was generally small relative to high baseline risk resulting from past landscape changes. Assessing extinction risk based on probabilities of ordinal condition as a function of landscape patterns may provide a flexible and robust approach for many at-risk taxa by adjusting species’ demographic criteria to match relative risk categories, following standardized criteria, or using expert elicitation for data-deficient species. This approach provides decision makers with a useful measure of uncertainty around ordinal classifications and provides a framework for estimating future risk based on projections of anthropogenic stressors.<br>

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

Leetown Project

Update to Tennessee Status Assessments and Recovery Plans for Listed Mussel Species

January 2018 - January 2025

Personnel

Participating Agencies

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