Dynamic Optimization Modeling
in
Behavioral and Evolutionary Ecology

Dynamic optimization modeling (DOM) is a powerful and simple technique for formalizing behavioral and evolutionary hypotheses. This type of modeling is appropriate to address questions in the areas of life history evolution, ecology, behavioral ecology, and any other area in which the relative fitness of alternative choices, or strategies is compared. DOM requires only basic mathematical and programming skills, and the model structure easily allows field quantification of parameters and examination of predictions. Thus, this simulation modeling approach is useful and readily accessible to empiricists and theorists alike.

Format: This course will open with an introduction to dynamic optimization modeling, including the basics of the approach and the aspects of probability theory on which it depends. I will then highlight the application of DOM to questions in behavioral and evolutionary ecology, drawing from the literature. I will then introduce programming in Borland Delphi, one of various programming tools that can be used to implement these models. In the main portion of the course we will explore various complexities that can be built into the models and again draw on the literature to see these implemented. This exploration will involve programming some published models and constructing a model of our own devising. Students will then develop models on their own, based on their research interests, and present them to the class. Finally, the class will develop and analyze one of these models and write a manuscript for journal submission.