REU Site: Mathematical Biology at the University of North Carolina at Greensboro

University Of North Carolina Greensboro, Greensboro NC

Investigators

Abstract

Many animals live in populations whose internal structure reflects multiple factors, for example, the interplay between territorial behavior between conspecifics and the spatial arrangement of the physical environment or other interactions demonstrated within the context of a social hierarchy established by dominance or kinship. This project will develop a unified mathematical framework for structured models of animal territoriality and social interactions. Using evolutionary graph theory, student researchers will study and classify the distribution of finite populations moving and interacting across a network of distinct sites under different models of interaction. Among several questions that will be explored, the participants will seek to understand the effect that the existing population structure has on the level of aggressiveness between conspecifics. This project will provide an understanding for the natural emergence of the ways in which animal populations and social groups organize and partition themselves into cooperative or antagonistic factions. The participants will endeavor to create a generalizable framework which could provide insight in multiple fields such as ecology, evolution, and the behavioral sciences. Many STEM fields are undergoing dynamic changes as a consequence of cross-disciplinary interactions, and this project will develop a diverse cadre of new scientists capable of working across traditional academic and scientific boundaries. This REU Site project trains undergraduate students to work at the interface of mathematics and the biological sciences. Each year, eight undergraduate students will participate in a ten week summer program and will be integrated into research teams lead by faculty members. The participants will be trained in pertinent mathematical techniques and biological concepts and they will engage in original research. This REU experience will improve participants' quantitative, analytical, and scientific communication skills and will prepare them for graduate school and scientific careers.