Collaborative Research: An Integrative Approach To Examine Freshwater Mussel Physiological Responses to Multiple Stressors

This collaborative project examines responses of two freshwater mussel species to changes in water temperature (Tw) and sedimentation regimes (Tss), using a combination of subcellular biomarkers, physiological experiments, field studies, and Dynamic Energy Budget (DEB) modeling. Freshwater mussels are ecosystem engineers that recycle nutrients, filter water, and modify habitats, yet are among the most imperiled taxa, with ~66% of North American species threatened, endangered, or extinct. Alterations in water temperature and sedimentation in lakes and rivers due to changes in environmental conditions, agricultural runoff, and water-use projects (dam construction, channel diversions, etc.) are identified as major threats to freshwater mussels. However, stage-specific and species-specific physiological data that can inform mussel conservation and management are currently lacking. This project fills that gap by integrating traditional techniques with contemporary approaches using Artificial Technology-Machine Learning and data analytics, to understand mussel responses to stressors. This research will benefit society by translating new knowledge into solutions by providing information for risk assessment of mussel monitoring programs for various state, federal, and international agencies. The DEB modeling approach used in this project to link responses at the subcellular level to individual performance is currently used for ecotoxicological assessments and could benefit aquaculture and agriculture practices through more robust predictions of performance under changing conditions. The project will encourage careers in STEM fields for K-12 and college students and teachers across three EPSCoR states. By working with local science centers, zoos, and museums to create exhibits and video displays, the project will also increase general public engagement on freshwater mussel biology and ecosystem services that mussels provide, helping to improve scientific literacy. This project investigates the molecular, morphological, and physiological plasticity of two freshwater mussel species with contrasting life-history strategies, Lampsilis straminea and Fusconaia cerina, in response to Tw and Tss. Using a comparative and integrative framework, this project will pursue three objectives: [1] Identify molecular (transcriptomic, lipidomic, and metabolomic), mitochondrial, and whole-animal metabolic signatures of plasticity across ontogeny under laboratory acclimation, [2] Characterize organismal fitness metrics (growth, survival, feeding, and reproduction) and plasticity under (semi)natural acclimatization conditions in experimental ponds and natural stream sites, and [3] Leverage experimental physiological data to develop mechanistic Dynamic Energy Budget (DEB) models for L. straminea and F. cerina to predict their response to increasing variability in Tw and Tss. The integration of “bottom-up” experimental approaches (i.e., molecular, cellular, and organismal) into “top-down” (i.e., individual-centered) DEB models will enable the development of a framework that uses mussels as a model system to explore how sub-cellular and individual energetic fitness scales up to influence populations, while remaining broadly applicable to other taxa. This research will be the first study to integrate across levels of biological organization, from genes to populations, to probe the mechanisms underlying plastic responses in freshwater mussels. These comprehensive studies will provide an unprecedented view of the fitness consequences, costs, trade-offs, and mechanistic underpinnings of physiological responses to variability in Tw and Tss in one of the most imperiled taxonomic groups, and will contribute to management and conservation of vulnerable freshwater mussel species. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.