Estimating Appalachian Elktoe Distribution And Abundance Using Occupancy And Detection Models
- ASU Author/Contributor (non-ASU co-authors, if there are any, appear on document)
- Chantelle Rondel (Creator)
- Institution
- Appalachian State University (ASU )
- Web Site: https://library.appstate.edu/
- Advisor
- Michael Gangloff
Abstract: Understanding the factors influencing the abundance, density, occupancy and detectability of endangered species is a critical component of managing at-risk species. The Appalachian elktoe (Alasmidonta raveneliana) is an endangered freshwater mussel endemic to the upper Tennessee River Drainage. I used a 3-pass mark-recapture study to model mussel detectability and occupancy at long-term monitoring sites in the South Toe River. I used models that accounted for imperfect detection and allowed me to model capture, recapture, occupancy and detection probability while incorporating habitat, mussel behavior, and sampling covariates. Mussel detection probability was most influenced by substrate composition whereas recapture probability was most influenced by substrate and mussel length. Probability of occupancy was influenced by substrate and current velocity whereas detectability was influenced by depth, searcher experience and substrate composition. This study serves as a model for future distribution and status surveys for this species and with a framework for collecting robust and precise population estimates for freshwater mussel populations. Future studies of Appalachian elktoe should include habitat modeling to identify occupied habitats and improve search effectiveness while obtaining data that may be useful to long-term monitoring in dynamic headwater streams.
Estimating Appalachian Elktoe Distribution And Abundance Using Occupancy And Detection Models
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Created on 9/12/2019
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Additional Information
- Publication
- Thesis
- Rondel, C. (2019). Estimating Appalachian Elktoe Distribution And Abundance Using Occupancy And Detection Models. Unpublished Master’s Thesis. Appalachian State University, Boone, NC.
- Language: English
- Date: 2019
- Keywords
- Freshwater Mussels, Headwater Stream,
Population Modeling, Capture-Mark-Recapture,
Species Monitoring