1st Edition

Using R for Modelling and Quantitative Methods in Fisheries

ISBN 9780367469894
Published August 15, 2020 by Chapman and Hall/CRC
352 Pages 108 B/W Illustrations

USD $200.00

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Book Description

Using R for Modelling and Quantitative Methods in Fisheries has evolved and been adapted from an earlier book by the same author and provides a detailed introduction to analytical methods commonly used by fishery scientists, ecologists, and advanced students using the open-source software R as a programming tool. Some knowledge of R is assumed, as this is a book about using R, but an introduction to the development and working of functions, and how one can explore the contents of R functions and packages, is provided.

The example analyses proceed step-by-step using code listed in the book and from the book’s companion R package, MQMF, available from GitHub and the standard archive, CRAN. The examples are designed to be simple to modify so the reader can quickly adapt the methods described to use with their own data. A primary aim of the book is to be a useful resource to natural resource practitioners and students.

Featured Chapters:

  • Model Parameter Estimation provides a detailed explanation of the requirements and steps involved in fitting models to data, using R and, mainly, maximum likelihood methods.
  • On Uncertainty uses R to implement bootstrapping, likelihood profiles, asymptotic errors, and Bayesian posteriors to characterize any uncertainty in an analysis. The use of the Monte Carlo Markov Chain methodology is examined in some detail.
  • Surplus Production Models applies all the methods examined in the earlier parts of the book to conducting a stock assessment. This included fitting alternative models to the available data, characterizing the uncertainty in different ways, and projecting the optimum models forward in time as the basis for providing useful management advice.

Table of Contents

1. On Modelling
2. A Non-Introduction to R
3. Simple Population Models
4. Model parameter Estimation
5. Static Models
6. On Uncertainty
7. Surplus Production Models

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Dr. Malcolm Haddon has at least 35 years of experience in fisheries science, having worked in the Department of New Zealand Fisheries, the University of Sydney, the Australian Maritime College, the University of Tasmania, and, most recently, in Australia’s Commonwealth Scientific and Industrial Research Organization (CSIRO), from which he recently retired. He has worked with: Crustacea, including crabs, prawns, and rock lobster; Mollusca, including scallops and abalone; and scale-fish, many and various. Dr. Haddon’s interests are these days focussed on all aspects of resource assessment and simulation testing of resource management using management strategy evaluation. He considers himself fortunate to have become an adjunct professor in the Institute of Marine and Antarctic Sciences at the University of Tasmania and an Honorary Research Fellow at Oceans and Atmosphere, CSIRO, in Hobart, Tasmania. In both institutions he continues to collaborate with colleagues, most recently beginning to contribute to two research programs at the university on abalone population dynamics and management.


"This is an excellent update to the earlier versions of this book by Dr. Haddon and is a "go-to" resource for fisheries students and professionals alike. The development of a comprehensive R package to accompany the well-written text is a substantial update to the earlier text. One of the strengths of this book is the integration between the text and the examples provided which I have found really helps to reduce the time required to implement these methods into ones on research. Highly recommended text."
- Bill Pine, University of Florida