James Stoeckel
Auburn University, AL·Ecology & Evolution
Freshwater mussels filter water, recycle nutrients and shape river habitats. Yet about two-thirds of North American species are threatened, endangered or extinct.
- Fields
Ecology & Evolution
Physiology
Earth & Environmental Science
- Topics
freshwater mussels
unionid mussels
Lampsilis straminea
- Grants
- 1 known grant, through Dec 2030
What they work on
- Identify transcriptomic, lipidomic, metabolomic, mitochondrial and whole-animal metabolic signatures of how Lampsilis straminea and Fusconaia cerina adjust to water temperature and sediment at different life stages in lab acclimation.
- Measure growth, survival, feeding and reproduction of both mussel species under warmer and more sediment-laden conditions in experimental ponds and natural stream sites.
- Build mechanistic Dynamic Energy Budget (DEB) models for both species from experimental data to predict their responses to increasingly variable temperature and sediment.
More about the research
Warmer water and more suspended sediment, driven by changing conditions, farm runoff, dams and channel diversions, are major threats. Managers still lack data on how each species and life stage copes. This collaborative project studies how two mussel species with different life strategies, Lampsilis straminea and Fusconaia cerina, respond to changing water temperature and sediment levels.
Why it matters
Freshwater mussels are among the most endangered animals in North America. Data on how each species and life stage handles warmer, muddier water could guide risk assessment and monitoring by state, federal and international agencies. The Dynamic Energy Budget models could also improve predictions used in pollution assessment, aquaculture and agriculture.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
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Admin Husic
Virginia Polytechnic Institute and State University, VA·Earth & Environmental Science·Early-career
Quantify how strongly landscapes connect to rivers over time and space by training a deep learning model on high-frequency nitrate and turbidity sensor data from more than 150 U.S. rivers.
The school
Auburn University: 11 labs on PI Pages, $394M a year on research, 327 research doctorates a year.
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