Introductory Fisheries Analyses with R  book cover
1st Edition

Introductory Fisheries Analyses with R

ISBN 9781482235203
Published November 24, 2015 by Chapman and Hall/CRC
338 Pages 76 B/W Illustrations

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Book Description

A How-To Guide for Conducting Common Fisheries-Related Analyses in R

Introductory Fisheries Analyses with R provides detailed instructions on performing basic fisheries stock assessment analyses in the R environment. Accessible to practicing fisheries scientists as well as advanced undergraduate and graduate students, the book demonstrates the flexibility and power of R, offers insight into the reproducibility of script-based analyses, and shows how the use of R leads to more efficient and productive work in fisheries science.

The first three chapters present a minimal introduction to the R environment that builds a foundation for the fisheries-specific analyses in the remainder of the book. These chapters help you become familiar with R for basic fisheries analyses and graphics.

Subsequent chapters focus on methods to analyze age comparisons, age-length keys, size structure, weight-length relationships, condition, abundance (from capture-recapture and depletion data), mortality rates, individual growth, and the stock-recruit relationship. The fundamental statistical methods of linear regression, analysis of variance (ANOVA), and nonlinear regression are demonstrated within the contexts of these common fisheries analyses. For each analysis, the author completely explains the R functions and provides sufficient background information so that you can confidently implement each method.

Web Resource The author’s website at includes the data files and R code for each chapter, enabling you to reproduce the results in the book as well as create your own scripts. The site also offers supplemental code for more advanced analyses and practice exercises for every chapter.

Table of Contents

(Very Brief) Introduction to R Basics
Why R for Fisheries Scientists?
Installing R and RStudio
Prompts, Expressions, and Comments
Data Storage
More with Functions
Saving Results
Getting Help

Loading Data and Basic Manipulations
Loading Data into R
Basic Data Manipulations
Joining Data.Frames
Re-Arranging Data.Frames
New Data.Frame from Aggregation
Exporting Data.Frames to External Data Files
Further Considerations

Plotting Fundamentals
Line Plots
Bar Plots
Fitted Model Plots
Some Finer Control of Plots
Saving or Exporting Plots

Age Comparisons
Data Requirements
Age-Bias Plot
Bias Metrics
Precision Metrics
Further Considerations

Age-Length Keys
Foundational Background
Constructing an Age-Length Key
Visualizing the Age-Length Key
Apply an Age-Length Key
Statistically Compare Age-Length Keys
Further Considerations

Size Structure
Data Requirements
Length Frequency
Proportional Size Distribution (PSD)
Among-Group Statistical Comparisons
Further Considerations

Weight-Length Relationships
Data Requirements
Weight-Length Model
Fitting Linear Regressions
Among-Group Statistical Comparisons
Further Considerations

Data Requirements
Condition Metrics
Among Group Statistical Comparisons
Further Considerations

Abundance from Capture-Recapture Data
Data Requirements
Closed Population, Single Recapture
Closed Population, Multiple Recaptures
Open Populations
Further Considerations

Abundance from Depletion Data
Leslie and DeLury Methods
K-Pass Removal Methods

Mortality Rates
Total Mortality Definitions
Total Mortality from Catch Curve Data
Total Mortality from Capture-Recapture Data
Mortality Components
Further Considerations

Individual Growth
Data Requirements
Growth Functions
Fitting Nonlinear Regressions
Among-Group Statistical Comparisons
Typical Model Fitting Problems
Further Considerations

Stock-Recruitment Relationships
Spawning Potential Ratio
Year-Class Strength
Further Considerations


Subject Index

R Functions (Demonstrated) Index

R Functions (Mentioned) Index

Scientific Names

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Derek H. Ogle is a professor of mathematical sciences and natural resources at Northland College, where he teaches statistics and fisheries science courses and has received awards for teaching, scholarly work, service, and assessment activities. Dr. Ogle maintains the fishR website, which is dedicated to sharing information on how to perform fisheries analyses in R. He earned a PhD in fisheries science from the University of Minnesota. His research interests include the population dynamics of invasive species and little-studied native species.