The objective of this course is to expose students to how to use decision analysis to evaluate alternative management actions. The focus will be on fisheries applications, but the models and techniques are applicable broadly in quantitative conservation biology.The course is based on two major themes:
- what is decision analysis and what are the key
steps
when conducting a decision analysis; and
- using Bayesian methods to determine the probabilities that should be associated with alternative states of nature.
ht be evaluated,
and defining performance measures to summarize the
consequences
of each management action.
The second part of the course introduces Bayesian methods and how to sample parameter vectors from posterior distributions using numerical methods (the Sampling-Importance-Resample and Markov Chain Monte Carlo methods). The use of Bayesian meta-analysis will be introduced as an approach to syntheszing data from multiple studies.
Decision analysis and Bayesian methods will be
illustrated
in class and during homework assignments using examples
from fisheries and terrestrial systems.
These examples include applying fisheries stock
assessment methods based on fitting population dynamics
models (age-aggregated, age-structured) to data for
fish, invertebrate and marine mammal populations and
using the parameterized models to conduct projections
that evaluate risk-reward trade-offs for various
management strategies.
Students will conduct decision analyses for an actual
situation as part
of the course evaluation.