Mathematical and Computational Applications in Disease and Landscape Ecology

Author

Erin Landguth, The University of MontanaFollow

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

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