Year of Award
2010
Document Type
Dissertation
Degree Type
Doctor of Philosophy (PhD)
Degree Name
Interdisciplinary Studies
Department or School/College
Interdisciplinary Studies Program
Committee Co-chair
Emily Stone, Samual Cushman
Commitee Members
Jon Graham, John Bardsley, Leonid Kalachev
Publisher
University of Montana
Abstract
The Individualized Interdisciplinary Program (IIP) at the University of Montana allows students to work with faculty in the design of a graduate curriculum tailored to their unique academic, creative, and professional needs. The principal goal of the National Science Foundation's IGERT: Montana - Ecology of Infectious Diseases (MEID) program is to produce graduates with expertise to lead the collaborative, cross-, and inter-disciplinary efforts in education and research needed to address complex problems as exemplified by the ecology of endemic, epidemic, and emergent infectious diseases. Under the envelope of these two programs, I have developed a Ph.D. program in which I received an interdisciplinary education in applied mathematics and computational ecology.
I strongly feel that spatial modeling is one of the most promising approaches to advance the sciences of disease ecology and landscape ecology. Mathematical and computational modeling provide powerful tools for evaluating relationships between mechanisms and responses in a spatially complex environment. Past progress in these fields has been limited by the lack of computational power and flexible mathematical models to simulate the actions of ecosystem and population processes in complex environments.
My specific research focus is in the development of mathematical and computational models to synthesize environmental data for describing and predicting the characteristics of population and disease dynamics on the landscape. The results from this research are documented in the following chapters: 1) Mathematical Disease Ecology. This uses numerical and qualitative analysis to study a model for Tick Borne Relapsing Fever in an island ecosystem. 2) Computational Landscape Ecology. The development and applications of a spatially-explicit computer model to predict population connectivity and geneflow on complex landscapes are described.
Recommended Citation
Landguth, Erin, "Mathematical and Computational Applications in Disease and Landscape Ecology" (2010). Graduate Student Theses, Dissertations, & Professional Papers. 653.
https://scholarworks.umt.edu/etd/653
© Copyright 2010 Erin Landguth