(Biology 419/519 Spring semester)
This course will provide a general overview of the process involved in studying a variety of ecological and environmental problems. It will provide the students with a toolbox of techniques, and discuss how they can be used to address questions and generate testable predictions. It will examine connections between individuals and populations as well as between theory and data. The focus will be on theoretical and computer modeling approaches, while maintaining a strong link to data and real systems. Applied problems will be drawn from all areas of conservation, harvesting, pest control and epidemiology. Mathematical/calculus experience is preferred, as is some general ecology. No modeling experience is necessary as the course will start from basic principles. Graduate students will be expected to choose one of the models presented in class or a model of their own interest to explore in more detail and present at the end of the quarter.
Syllabus
Theory and modeling: Overview and a general approach
A Modeling Toolkit:
Individuals
- Simple optimality: Habitat selection and foraging
- Reproductive decisions: Tradeoffs and constraints
- Making decisions: stochastic dynamic programming
- Game theory: When your fitness depends on others
- Dynamic energy budgets
Populations in Space and Time
- Unstructured population models: Stability, cycles, chaos
- Population dynamic models: When age and size matter
- Structured population models: Effects of life history on populations
- Individual-based models: From individuals to populations
- Pseudo-spatial models: metapopulations
- Explicit spatial models: IBM’s, cellular automata, etc
Communities
- Interacting populations:
- Plant-herbivore
- Predator-prey
- Host-parasite/parasitoid
- Competitors
- Multi-species models
- Island biogeography
- Succession
Using the toolkit: Graduate student presentations of individual projects.
For further information, please email Katriona Shea or call 814-865-7910.
Katriona Shea's Lab 