Modelling and Quantitative Methods in Fisheries

Inhaltsverzeichnis

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



Simple Population Models Introduction 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 Likelihood Bayes' Theorem Concluding Remarks



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



Randomization Tests Introduction 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 Introduction Asymptotic Standard Errors Percentile Confidence Intervals Using Likelihoods Likelihood Profile Confidence Intervals Percentile Likelihood Profiles for Model Outputs Markov Chain Monte Carlo (MCMC) Conclusion



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

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

Size-Based Models Introduction The Model Structure Conclusion

Appendix: The Use of Excel in Fisheries

Bibliography

Index

Portrait

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.

Pressestimmen

The text remains true to the author's initial aim of providing an introduction to the analytical methods currently being used in quantitative biology and fisheries science. It is important to remember when reading this book that there are few texts that students can truly consult on fisheries science without a detailed understanding of stock assessment and fisheries management practices-this text continues to bridge that gap. The material has been revised and improvements made to a number of the examples. Two concerns and reservations that I commented on in my previous review have been addressed by the inclusion of two new chapters-one on characterizing uncertainty covering asymptotic errors and likelihood profiles, and the other on size-based models using abalone as an example. The book is lavishly illustrated throughout with the use of Microsoft Excel workbooks which adds to the flexibility, availability and ease of use of the text. I recommend the text both as a course companion and for private study. -Carl M. O'Brien, International Statistical Review, 2012 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