| Summary: | <p> In this dissertation, we develop structured population models to examine how changes in the environmental affect population processes. In Chapter 2, we develop a general continuous time size structured model describing a susceptible-infected (SI) population coupled with the environment. This model applies to problems arising in ecology, epidemiology, and cell biology. The model consists of a system of quasilinear hyperbolic partial differential equations coupled with a system of nonlinear ordinary differential equations that represent the environment. We develop a second-order high resolution finite difference scheme to numerically solve the model. Convergence of this scheme to a weak solution with bounded total variation is proved. We numerically compare the second order high resolution scheme with a first order finite difference scheme. Higher order of convergence and high resolution property are observed in the second order finite difference scheme. In addition, we apply our model to a multi-host wildlife disease problem, questions regarding the impact of the initial population structure and transition rate within each host are numerically explored.</p><p> In Chapter 3, we use a stage structured matrix model for wildlife population to study the recovery process of the population given an environmental disturbance. We focus on the time it takes for the population to recover to its pre-event level and develop general formulas to calculate the sensitivity or elasticity of the recovery time to changes in the initial population distribution, vital rates and event severity. Our results suggest that the recovery time is independent of the initial population size, but is sensitive to the initial population structure. Moreover, it is more sensitive to the reduction proportion to the vital rates of the population caused by the catastrophe event relative to the duration of impact of the event. We present the potential application of our model to the amphibian population dynamic and the recovery of a certain plant population. In addition, we explore, in details, the application of the model to the sperm whale population in Gulf of Mexico after the Deepwater Horizon oil spill.</p><p> In Chapter 4, we summarize the results from Chapter 2 and Chapter 3 and explore some further avenues of our research.</p><p>
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