The objective of this course is to expose students to the use of mathematical models to represent hypotheses about population dynamics processes and to evaluate the implications of alternative management policies. The focus will be on fisheries applications but the models and techniques are applicable broadly in quantitative conservation biology. 

• how to develop mathematical models based on population dynamic hypotheses;
• typical models used in fisheries stock assessment;
• fitting models to data; and
• evaluating the consequences of alternative management policies.

The models to investigated include: simple models that only  consider the total population size; age- and size-structured models; individual-based models, delay-difference models; spatial models; stock-recruitment models; meta-population models; and predation and ecosystem models;

Fitting models to data will cover: sums of squares fitting; maximum likelihood; selecting among different models;  and quantifying uncertainty using likelihood profile, boostrapping and Monte Carlo simulations. 

Policy evaluation will focus on: use of Monte Carlo methods to project population size into the future given different future management policies; comparing different harvest regimes in terms of the trade-off between resource conservation and utilitization; and estimating risk of extinction.

Models and model fitting techniques will be illustrated using examples from fisheries and terrestrial systems. The emphasis in this course is to develop the skill to represent alternative population dynamic hypotheses mathematically,  to implement them using Visual Basic, and to critique them based on their assumptions and implications.