Introductory Fisheries Analyses with R

• Main Author: Ogle, Derek H.
• Format: eBook Book
• Language: English
• Published: Boca Raton CRC Press 2016; CRC Press LLC; Chapman & Hall
• Edition: 1
• Series: Chapman & Hall/CRC The R Series
• Subjects: ANOVA; BIOSCIENCEnetBASE; Ecology - Environment Studies; ENVIROnetBASE; ENVIRONMENTALSCIENCEnetBASE; Fisheries > Computer programs; Fisheries > Statistics; fisheries data; fisheries science; fisheries stock assessment; fisheries stock assessment analyses; fisheries-specific analyses; Fishery management; Fishery sciences > Computer programs; Fishery sciences > Statistics; Handbooks, manuals, etc; LIFESCIENCEnetBASE; linear regression; Marine & Aquatic Science; metrics to assess fish populations; nonlinear regression; population dynamics; R (Computer program language); R for fisheries analyses and graphics; R functions; SCI-TECHnetBASE; script-based analyses; Statistics for the Biological Sciences; STATSnetBASE; STMnetBASE; stock-recruit relationship; Alk; Creek Chubs; Negative Log Likelihood Values; Quantile Regression; White Cells; Catch Curve; Bull Trout; Dummy Variable; Fulton’s Condition Factor; ANOVA Table; Von Bertalanffy Growth Func Tion; Weight Length Relationship; CSV File; Relative Condition Factor; NA NA NA NA NA; Cutthroat Trout; Black Crappie; Largemouth Bass; Beverton Holt Function; Descending Limb; Length Interval; Fork Length; NA NA NA NA; Homoscedasticity Assumption
• ISBN: 9781482235203; 148223520X
• DOI: 10.1201/9781315371986

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 Packages Prompts, Expressions, and Comments Objects Functions Data Storage More with Functions Looping 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 Scatterplots Line Plots Histograms 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 Condition 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 Recruitment Stock-Recruitment Relationships Spawning Potential Ratio Year-Class Strength Further Considerations References 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.