BIONB 4220 - [Modeling Behavioral Evolution]

(BIO-AS, PBS-AS, SMR-AS)

Fall. Not offered: 2022-2023. Next offered: 2024-2025. 4 credits. Student option grading.

Prerequisite: BIONB 2210, one year calculus, course in probability or statistics, or permission of instructor. Enrollment limited to: advanced undergraduates and graduate students. Offered in even-numbered years only.

H.K. Reeve.

Intensive lecture and computer lab course on modeling strategies and techniques in the study of behavioral evolution. Population-genetic (including quantitative-genetic), static optimization, dynamic programming, and game-theoretic methods are emphasized. These approaches are illustrated by application to problems in optimal foraging, sexual selection, sex ratio evolution, animal communication, and the evolution of cooperation and conflict within animal social groups. Students learn to critically assess recent evolutionary theories of animal behavior, as well as to develop their own testable models for biological systems of interest or to extend preexisting models in novel directions. The Mathematica software program is used as a modeling tool in the accompanying computer lab.

Outcome 1: To be able to understand and create single-locus population genetic models of selection.

Outcome 2: To be able to understand and manipulate the Price equation.

Outcome 3: To understand and use static and dynamic optimization methods, both constrained and unconstrained, as in models of patch residence time from optimal foraging theory.

Outcome 4: To understand and create discrete and continuous strategy game theory models and derive ESS’s from them with appropriate checks on stability.

Outcome 5: To understand and use kin selection theory, using both inclusive fitness and neighbor-modulated methods.