ABIO432

Course Objectives:

This course strongly emphasizes the functional significance of animal behavior; we can refer to the subject as the evolutionary ecology of animal behavior. Most lectures present a mathematical model treating behavior as adaptation under constraint, in order to understand principles addressing evolution of behavioral phenotypes. Consequently, students should gain familiarity with concepts evolutionary ecologists employ to predict (not simply describe) behavior, and to explain behavioral diversity in nature; familiarity with concepts implies solving mathematical problems. As the course progresses, students should be able to read, interpret and evaluate the original literature in behavioral ecology. Students will demonstrate attainment of objectives in tests, and by writing two papers.

Course Prerequisites:

No fewer than 12 credit hours in biology; completion of MAT 106 or higher-level calculus course, or completion of a Physics course with calculus. Students should have familiarity with derivatives and integrals. Students lacking the requisite course experience may be "deregistered."

Classroom Procedures:

Students should arrive on time when attending lecture, and avoid behavior that interferes with other students's learning. Cell phones should be turned off. Students should read the Undergraduate Bulletin's discussion of plagiarism, and understand the significance of violations of academic integrity (see applicable policies in the Undergraduate Bulletin).

Text:

No textbook is required. A series of reading lists will posted on this page.

For those students who wish to purchase a useful textbook, the recommended (i.e., not required) text is Principles of Animal Behavior, Second Edition (2009), by Dr. L.A. Dugatkin, W.W. Norton, New York, NY.

Five classic papers that evaluate/explain the use of optimization to investigate functional significance of behavior offer useful background reading. Listed below, they are all available in the Sience Library:

Krebs, J.R., and R.H. McCleery. 1984. Optimization in behavioural ecology. Pp. 91-121 in Behavioural Ecology: An Evolutionary Approach. Blackwell Scientific, Oxford, UK.

Grafen, Alan. 1984. Natural selection, kin selection and group selection. Pp. 62-89 in Behavioural Ecology: An Evolutionary Approach. Blackwell Scientific, Oxford, UK.

Maynard Smith, J. 1978. Optimization theory in evolution. Annual Review of Ecology and Systematics 9:31-56.

Maynard Smith, J. 1984. Game theory and the evolution of behavior. Behavioral and Brain Sciences 7:95-125.

Parker, G.A., and J. Maynard Smith. 1990. Optimality theory in evolutionary biology. Nature 348:27-33.

Grade Determination:

Course grades will depend on results of two hourly exams, and on the quality of two papers (each 10-12 pages, double spaced). Questions will emphasize mathematical methods needed to understand both theoretical models and tests of hypotheses in behavioral ecology. Final grades are based on the two tests and two papers; each contributes 25% of the course grade.

Each paper will address topics discussed in a different series of lectures. For each paper, a separate reading list, to help students develop their papers, will be available on this web page.

Some guidelines to be read before writing the first paper (pdf).
An old collective critique of the first papers submitted (pdf).

Tentative dates for the tests are: 2 March (Friday) and 16 April (Monday). The first paper is due 23 March (Friday). The second paper is due 7 May (Monday), the last scheduled class meeting.

For an outline of topics addressed during the first testing period see pdf. For an outline of topics addressed during the second testing period see pdf.

Accumulating 90 of the 100 total "points" assures a letter grade of A in this course. Final grades may be "curved" relative to expected total scores.

A reading list on Functional Efficiency and Survival of Soltaries: pdf.

Readings on Survival of Socially Interacting Individuals: pdf.

An older review of social group size; the file is large.

Some papers: linear programming models for diet choice: pdf.

A recent review of Foraging Theory.