Modelling and Quantitative Methods in Fisheries
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Modelling and Quantitative Methods in Fisheries

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Description

With numerous real-world examples, Modelling and Quantitative Methods in Fisheries, Second Edition provides an introduction to the analytical methods used by fisheries' scientists and ecologists. By following the examples using Excel, readers see the nuts and bolts of how the methods work and better understand the underlying principles. Excel workbooks are available for download from CRC Press website. In this second edition, the author has revised all chapters and improved a number of the examples. This edition also includes two entirely new chapters: *Characterization of Uncertainty covers asymptotic errors and likelihood profiles and develops a generalized Gibbs sampler to run a Markov chain Monte Carlo analysis that can be used to generate Bayesian posteriors *Sized-Based Models implements a fully functional size-based stock assessment model using abalone as an example This book continues to cover a broad range of topics related to quantitative methods and modelling. It offers a solid foundation in the skills required for the quantitative study of marine populations. Explaining important and relatively complex ideas and methods in a clear manner, the author presents full, step-by-step derivations of equations as much as possible to enable a thorough understanding of the models and methods.show more

Product details

  • Hardback | 465 pages
  • 160.02 x 238.76 x 30.48mm | 793.78g
  • Taylor & Francis Ltd
  • Chapman & Hall/CRC
  • Boca Raton, FL, United States
  • English
  • Revised
  • 2nd Revised edition
  • 140 black & white illustrations, 22 black & white tables
  • 1584885610
  • 9781584885610
  • 445,575

Review quote

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, 2002show more

About Malcolm Haddon

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.show more

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 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 Indexshow more

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