NSF AI Disclosure Required
NSF requires disclosure of AI tool usage in proposal preparation. Ensure you disclose the use of FindGrants' AI drafting in your application.
EPSCoR Research Fellows: NSF: Dynamic Energy Budget Theory to Predict Lifetime Fitness and Productivity Across Phenotypic and Energetic Landscapes
NSF
About This Grant
This Research Infrastructure Improvement EPSCoR Research Fellows project provides a fellowship to an Associate Professor and training for a graduate student at Montana State University (MSU). This work will be conducted with Dr. Romain Lavaud at Louisiana State University. The project will improve predictive computer models to study how Montana’s native fish and other animals that live in water deal with external stress, like catch-and-release fishing and changes in water temperature and river flow. This work will help manage declining animal populations and habitats important to Montana’s $900 million fishing industry and global fisheries, recreation, and aquaculture, while also advancing basic knowledge of animal ecology. The project will also help train the future STEM workforce by giving students from both institutions practical experience in biology, ecology, and data analysis. This project will improve predictive models of aquatic ectotherm life history by refining Dynamic Energy Budget (DEB) models. It will strengthen the principal investigator's and MSU’s research capacity in ecological physiology through a sustained collaboration with the host site. The project will advance understanding of energy allocation under environmental stress and its life history consequences. Novel DEB models refined to incorporate stress recovery costs and individual variation in energy fluxes will be applied to three key Montana aquatic species to test hypotheses on individual variation in energy use and fitness. Findings will inform mitigation strategies for declining populations of Montana’s ecologically and economically important wildlife and global wildlife, fisheries, and aquaculture, while advancing basic knowledge in evolutionary ecology. The project supports MSU’s goals in curriculum development, student training, and workforce development. Engagement with stakeholders and researchers will promote DEB modeling in conservation, aligning with NSF’s goals to accelerate research impact by developing robust, scalable decision-support tools. This project is supported by the EPSCoR Research Infrastructure Improvement Program: EPSCoR Research Fellows, which supports early- and mid-career investigators in eligible jurisdictions to develop collaborations at the nation’s private, government or academic research institutions. 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.
Focus Areas
Eligibility
How to Apply
Up to $239K
2027-12-31
One-time $749 fee · Includes AI drafting + templates + PDF export
AI Requirement Analysis
Detailed requirements not yet analyzed
Have the NOFO? Paste it below for AI-powered requirement analysis.