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Modelling and Quantitative Methods in Fisheries, Second Edition


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Table of Contents

Fisheries and Modelling
Fish Population Dynamics
The Objectives of Stock Assessment
Characteristics of Mathematical Models
Types of Model Structure

Simple Population Models
Assumptions-Explicit and Implicit
Density-Independent Growth
Density-Dependent Models
Responses to Fishing Pressure
The Logistic Model in Fisheries
Age-Structured Models
Simple Yield-per-Recruit

Model Parameter Estimation
Models and Data
Least Squared Residuals
Nonlinear Estimation
Bayes' Theorem
Concluding Remarks

Computer-Intensive Methods
Randomization Tests
Jackknife Methods
Bootstrapping Methods
Monte Carlo Methods
Bayesian Methods
Relationships between Methods
Computer Programming

Randomization Tests
Hypothesis Testing
Randomization of Structured Data

Statistical Bootstrap Methods
The Jackknife and Pseudo Values
The Bootstrap
Bootstrap Statistics
Bootstrap Confidence Intervals
Concluding Remarks

Monte Carlo Modelling
Monte Carlo Models
Practical Requirements
A Simple Population Model
A Non-Equilibrium Catch Curve
Concluding Remarks

Characterization of Uncertainty
Asymptotic Standard Errors
Percentile Confidence Intervals Using Likelihoods
Likelihood Profile Confidence Intervals
Percentile Likelihood Profiles for Model Outputs
Markov Chain Monte Carlo (MCMC)

Growth of Individuals
Growth in Size
von Bertalanffy Growth Model
Alternatives to von Bertalanffy
Comparing Growth Curves
Concluding Remarks

Stock Recruitment Relationships
Recruitment and Fisheries
Stock Recruitment Biology
Beverton-Holt Recruitment Model
Ricker Model
Deriso's Generalized Model
Residual Error Structure
The Impact of Measurement Errors
Environmental Influences
Recruitment in Age-Structured Models
Concluding Remarks

Surplus Production Models
Equilibrium Methods
Surplus Production Models
Observation Error Estimates
Beyond Simple Models
Uncertainty of Parameter Estimates
Risk Assessment Projections
Practical Considerations

Age-Structured Models
Types of Models
Cohort Analysis
Statistical Catch-at-Age
Concluding Remarks

Size-Based Models
The Model Structure

Appendix: The Use of Excel in Fisheries



About the Author

Malcolm Haddon is a senior fisheries modeller for CSIRO in Hobart, Tasmania, Australia. Prior to joining CSIRO, Dr. Haddon was an associate professor at the University of Tasmania, head of fisheries at Australian Maritime College, a senior research fellow at the University of Sydney, editor of the New Zealand Journal of Marine and Freshwater Research, and a lecturer at Victoria University of Wellington. He has conducted stock assessments on Tasmanian rock lobster, giant crab, and abalone. Now at CSIRO, he continues to produce stock assessments of abalone but also for an array of Australian Commonwealth fisheries.


Praise for the First Edition The book is a good introduction to modeling for students and practitioners. The emphasis is on population models, with chapters on parameter estimation, randomization tests, resampling methods, Monte Carlo methods, stock-recruitment, and age-structures models. One helpful feature is the use of spreadsheet examples to illustrate the methods. --Fisheries, 2002

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