1st Edition

Introductory Fisheries Analyses with R

By Derek H. Ogle Copyright 2016
    338 Pages 76 B/W Illustrations
    by Chapman & Hall

    337 Pages 76 B/W Illustrations
    by Chapman & Hall

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    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 http://derekogle.com/IFAR/ 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.

    (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


    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.