Using R for Modelling and Quantitative Methods in Fisheries

Using R for Modelling and Quantitative Methods in Fisheries is an introduction to analytical methods using the open-source software R, designed for fishery scientists, ecologists, and advanced students. It covers model parameter estimation, uncertainty analysis, and surplus production models and provides step-by-step examples with code and a companion R package. The book aims to be a valuable resource for natural resource practitioners and students.

Format: Paperback / softback
Length: 338 pages
Publication date: 25 September 2020
Publisher: Taylor & Francis Ltd

Using R for Modelling and Quantitative Methods in Fisheries is a comprehensive guide that has evolved and been adapted from an earlier book by the same author. It offers a detailed introduction to analytical methods commonly used by fishery scientists, ecologists, and advanced students utilizing the open-source software R as a programming tool. While some knowledge of R is assumed, as this book focuses on using R, an introduction to the development and working of functions, as well as how to 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, allowing the reader to quickly adapt the methods described to their own data. A primary aim of the book is to serve as a valuable resource for natural resource practitioners and students.

Featured Chapters:

Model Parameter Estimation: This chapter provides a detailed explanation of the requirements and steps involved in fitting models to data, using R and, primarily, maximum likelihood methods. It covers topics such as model selection, data fitting, and assessing model performance.

On Uncertainty: In this chapter, R is used 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: This chapter applies all the methods examined in the earlier parts of the book to conducting a stock assessment. It involves fitting alternative models to the available data, characterizing the uncertainty in different ways, and projecting the optimum.

The optimum models forward in time as the basis for providing useful management advice.

By leveraging the power and versatility of R, this book empowers fishery scientists, ecologists, and advanced students to apply advanced analytical methods and gain insights into complex fisheries-related issues. Whether you are a beginner or an experienced R user, this book will provide you with the tools and knowledge to unlock the full potential of R for your research and analysis.

Weight: 526g
Dimension: 156 x 234 x 23 (mm)
ISBN-13: 9780367469887