REU Site: Ecological Modeling of the Mississippi River Basin

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The objectives of this project are to train undergraduates in interdisciplinary mathematics via research projects in ecological modeling; to motivate undergraduate students, especially underrepresented and/or first-generation college students with limited access to research at their home institution, to attend graduate school; and to prepare undergraduate students to be successful in an interdisciplinary, collaborative setting. To achieve these objectives as part of this REU Site, students use ecological modeling techniques to address questions about wildlife diseases as well as the factors contributing to floodplain forest diversity and water quality. Projects utilize 20-year data sets from the Mississippi River Basin to better understand the biological patterns and processes underlying this unique region. The 24 student participants develop the motivation and wide-ranging skills necessary to transition into STEM-related careers, including those in mathematical biology. Since this REU research experience is in collaboration with federal scientists, results from students' projects can be rapidly applied to resource-management problems, which may help to inform future decisions made by state and federal agencies (such as the U.S. Fish and Wildlife Service).The research projects completed by participants in this REU Site will contribute to the overall body of knowledge in ecological modeling by tackling novel research questions in the areas of wildlife disease, water quality and forest diversity using ordinary and stochastic differential equations, optimal control theory, time-series analysis, multivariate analysis, and occupancy modeling. The mentors include faculty and federal scientists who are excited to continue leading undergraduate research projects in ecological modeling and disseminating project results in peer-reviewed journals and/or regional or national conferences.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.