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EEB/Math 466 Mathematical Ecology:
Mathematical models are the backbone of ecological theory; they form the basis for modern approaches to understanding, managing, and predicting the dynamics of ecological systems. This course provides an overview of the major classes of ecological models, with an emphasis on ecological dynamics. We will focus on principles guiding the formulation of models and on the mathematical techniques that can be used to analyze them. We will examine deterministic and stochastic models, structured and unstructured models, single- and multiple-species models. Because ecological systems are typically nonlinear, we cannot often "solve" model equations: we employ techniques of nonlinear analysis, stochastic analysis, and numerical analysis to obtain results. This course will introduce many of these techniques in the context of ecological theory.
An additional goal of the course is to develop students' skills in the use of mathematical software. We will make extensive use of Matlab and R for numerical computations and Mathematica for symbolic computation.
Applied math and advanced ecology students interested in the use of mathematical models and theoretical, statistical, and computational ecology. The techniques introduced in the course will be useful to students from many disciplines, including chemical engineering, economics, natural resources, public health, and so on.
EEB 401 Advanced Topics in Biology:
Ecologists are frequently taught statistical recipes that can be used to analyze data, e.g., correlation, regression, analysis of variance. These classical methods have been designed with analytical tractability foremost in mind. The assumptions on which they depend are such that they typically afford only an oblique perspective on the specific ecological questions we wish to answer. This is a pity, since hard-won data are effectively squandered when we can ask only crude questions of them. |
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