Course Overview

This course is a complete review of advanced quantitative methods in fisheries stock assessment.
Course covers introduction, decision analysis to evaluate alternative management actions, Bayesian state-space
modelling, Meta-analysis, Integrated analysis, and Spatial modelling in stock assessment Assessment models of
biomassdynamics model, age-structured production model, and integrated stock assessment model (e.g., Stock
Synthesis, SS) will be included. Student will be familiar with methods in fish population dynamics
and stock assessment (e.g.., Bayesian posterior distribution, Markov Chain Monte Carlo, state-space modelling, etc.)
and proficient in parameter estimation (e.g., unfished biomass, spawning biomass, MSY), as well as the uncertainty,
of an exploited fish population, and evaluation of harvest restrictions for fisheries management problems by using
various computer programs and tools (e.g., AD Model Builder [ADMB], WinBUGS/JAGS, SS).
The course draws examples from real fisheries in the world and provides student broad experiences of
various fishery data and fish biology. The course is primarily for students of fisheries and marine ecology,
but should also appeal to those interested in conservation ecology and advanced ecological modelling.

Learning Achievement

The main objective of the course was to become proficient with background and tools to conduct advanced stock assessment modelling for fisheries. Student will develop professional skills of data analysis, quantitative fish population modelling, and theory and implication of fish harvest management. Student will carry out fisheries data analysis, modelling, and interpretation on a regular basis throughout the course. The course expects student will develop their own model and application. Course will provide basic programming training by following the examples using Excel, R, ADMB, WinBUGS/JAGS.

Competence

Course prerequisites

Ocean 7176 Ecological Modeling for Conservation of Fisheries Resources is recommended (not required) prior to this course

Grading Philosophy

Course schedule

Course type

Online Course Requirement

Instructor

Yi-Jay Chang

Other information

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