Introductory fish population dynamics and stock assessment
Course name: Introductory fish population dynamics and stock assessment
Semester: 105-1
Department:
Instructor: Yi-Jay Chang
Course No.: FISH 808
Credit: 3
Year/Half year: Half year
Required/Selected: Selected
Class time: TBD
Notes: This course is lectured in English
Website: TBD
Description
This course is a complete review of basic population dynamics and stock assessment, methods to be applied at different level of data, and a review of relevant computer programs. Course covers introduction, data used in stock assessment (catch, abundance, and life history), population dynamics models, determination of stock status, biological reference points, and future forecast.
Assessment models of per-recruit model, biomass dynamics model, lagged recruitment, survival and growth model, and age-structured production model will be included. Student will be familiar with terms in fish population dynamics (e.g.., fishing mortality, catchability, selectivity, steepness, etc.) and proficient in parameter estimation (e.g., growth, mortality, unfished biomass, MSY), as well as the uncertainty, of an exploited fish population, and evaluation of harvest restrictions for fisheries management problems. 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 ecological modelling.
Objective
The main objective of the course was to become proficient with background and tools to conduct basic stock assessments 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 and R.
Prerequisites
Recommend having basic knowledge of Statistics (e.g., LS3022-Biostatistics) or the equivalent is recommended.
Grade
Participation/attendance (10%)
Homework (70%): Total five homeworks.
Final exam (20%): This will be 50-minute closed-book exams on DATE [TBD] that test knowledge of materials from the previous lectures, readings and homework exercise.
Textbook
Haddon, M. 2001. Modelling and Quantitative Methods in Fisheries. Chapman and Hall, London, 406 pp.
Hilborn, R., Walters, C.J., 1992. Quantitative Fisheries Stock Assessment: Choice, Dynamics and Uncertainty. Chapman and Hall, New York, 570 pp.
Office hours
TBD
Course outline
Lecture 1
Introduction and overview: what is stock assessment?
Lecture 2
Fish and “fished” population dynamics
Lab: demo
Lecture 3
Stock assessment-Key principle and components
Lecture 4
Data collection (sampling) and stock assessment
Lab: logbook and observer data analysis
Lecture 5
Modelling Growth -1
Lecture
Lab: modeling the growth curves, model selection, age-length key
Fitting model to data
Lecture 6
Modelling Growth -2
Length frequency method
Lab: maximum likelihood of length frequency method
Lecture 7
Modelling Growth -3
Modeling growth of crustacean, growth transition matrix, stepwise growth curve
Lab: estimation growth of crustacean
Lecture 8
Fisheries term: catchability, mortality, selectivity
Lab: estimation of mortality
Lecture 9
Reproduction, stock-recruitment, steepness
Lab: Fitting stock-recruitment curves
Lecture 10
Abundance indices, catch-per-unit-effort, and CPUE standardization
Lecture 11
Abundance indices, catch-per-unit-effort, and CPUE standardization
Lab: CPUE standardization, Generalized Linear Models
Lecture 12
Per recruit analysis, biological reference points
Lab: Equilibrium yield per recruit model
Lecture 13
Biomass dynamics models
Lecture 14
Biomass dynamics models
Lab: fitting biomass dynamics models
Lecture 15
Include S-R relationship into stock assessment model
Lab: Lagged recruitment, survival and growth models
Lecture 16
Age-Structured Production Models
Lab: Age-Structured Production Models
Lecture 17
Age-Structured Production Models-II