Introductory Fisheries Analyses with R

Introductory Fisheries Analyses with R
	Dedication
	Contents
	Preface
		Book Description and Intended Audience
		Companion Website
		Software Information and Conventions
		Acknowledgments
		Dedication
	Author
Chapter 1 - (Very Brief) Introduction to R Basics
	1.1 Why R for Fisheries Scientists?
	1.2 Installing R and RStudio
	1.3 Packages
	1.4 Prompts, Expressions, and Comments
	1.5 Objects
	1.6 Functions
	1.7 Data Storage
		1.7.1 Vectors or Variables
		1.7.2 Factors
		1.7.3 Matrices
		1.7.4 data.frames
	1.8 More with Functions
		1.8.1 Constructor and Extractor Functions
		1.8.2 User-Defined Functions
	1.9 Looping
		1.9.1 For Loops
		1.9.2 Apply "Loops"
	1.10 Saving Results
	1.11 Getting Help
	Notes
Chapter 2 - Loading Data and Basic Manipulations
	2.1 Loading Data into R
		2.1.1 Working Directory
		2.1.2 Database and Other Software Files
		2.1.3 Text or ASCII Files
		2.1.4 Internal Files
	2.2 Basic Data Manipulations
		2.2.1 Removing Individuals
		2.2.2 Filtering or Subsetting Individuals
		2.2.3 Selecting Variables
		2.2.4 Renaming Variables
		2.2.5 Creating New Variables
		2.2.6 Creating a Length Categorization Variable
		2.2.7 Recoding Variables
		2.2.8 Sorting
		2.2.9 Combined Manipulations with Piping
	2.3 Joining Data.Frames
		2.3.1 Combining Similar Data.Frames
		2.3.2 Combining Data.Frames by a Key Relation
	2.4 Rearranging Data.Frames
	2.5 New Data.frame from Aggregation
		2.5.1 Summarizing Catch per Unit Effort
	2.6 Exporting Data.Frames to External Data Files
	2.7 Further Considerations
	Notes
Chapter 3 - Plotting Fundamentals
	3.1 Scatterplots
		3.1.1 Simple Scatterplot
		3.1.2 Scatterplot with Different Symbols by Group
	3.2 Line Plots
		3.2.1 Basic Line Plots
		3.2.2 Superimposing a Line Plot on a Scatterplot
	3.3 Histograms
		3.3.1 Single Histograms
		3.3.2 Histograms for Multiple Groups
	3.4 Bar Plots
		3.4.1 Frequency of Individuals in Groups
		3.4.2 Other Values
	3.5 Fitted Model Plots
		3.5.1 Line or Curve
		3.5.2 Means Plot with Vertical Intervals
	3.6 Some Finer Control of Plots
		3.6.1 Plotting Parameter Options
		3.6.2 Adding Text to a Plot
		3.6.3 Simple Placement of Multiple Plots
	3.7 Saving or Exporting Plots
	Notes
Chapter 4 - Age Comparisons
	4.1 Data Requirements
	4.2 Age Bias Plot
	4.3 Bias Metrics
	4.4 Precision Metrics
	4.5 Further Considerations
	Notes
Chapter 5 - Age-Length Keys
	5.1 Foundational Background
	5.2 Constructing an Age-Length Key
		5.2.1 Preparing the Aged Sample
		5.2.2 Observed Age-Length Keys
		5.2.3 Smoothed or Modeled Age-Length Keys
	5.3 Visualizing an Age-Length Key
	5.4 Apply an Age-Length Key
		5.4.1 Classical Method for Age Distribution
		5.4.2 Age Distribution with Standard Errors
		5.4.3 Mean Length-at-Age
		5.4.4 Assign Individual Ages and Summarize
	5.5 Among Group Statistical Comparisons
	5.6 Further Considerations
	Notes
Chapter 6 - Size Structure
	6.1 Data Requirements
	6.2 Length Frequency
		6.2.1 Tables
		6.2.2 Histograms
		6.2.3 Cumulative Frequencies
	6.3 Proportional Size Distribution (PSD)
		6.3.1 Gabelhouse Length Categories
		6.3.2 Incremental PSD Indices
		6.3.3 Traditional PSD Indices
		6.3.4 Special PSD Indices
		6.3.5 Confidence Intervals
		6.3.6 Easy Calculations of Indices and Confidence Intervals
		6.3.7 Tic-Tac-Toe Plots
	6.4 Among Group Statistical Comparisons
		6.4.1 Kolmogorov-Smirnov Test
		6.4.2 Chi-Square Test
	6.5 Further Considerations
		Conveniently Summarizing PSD for ALL Species
	Notes
Chapter 7 - Weight-Length Relationships
	7.1 Data Requirements
	7.2 Weight-Length Model
	7.3 Fitting Linear Regressions
		7.3.1 Making Predictions
		7.3.2 Visualizing the Fit
		7.3.3 Assumption Checking
	7.4 Among Group Statistical Comparisons
		7.4.1 Factor and Dummy Variables
		7.4.2 Models and Submodels
		7.4.3 Model Fitting
		7.4.4 Testing Predictors
		7.4.5 Visualizing the Fit
	7.5 Further Considerations
	Notes
Chapter 8 - Condition
	8.1 Data Requirements
	8.2 Condition Metrics
		8.2.1 Fulton's Condition Factor
		8.2.2 Weight-Length Residuals
		8.2.3 Relative Condition Factor
		8.2.4 Relative Weight
	8.3 Among Group Statistical Comparisons
		8.3.1 Summary Statistics
		8.3.2 One-Way ANOVA
			8.3.2.1 Assumptions
		8.3.3 Kruskal-Wallis Test
	8.4 Further Considerations
	Notes
Chapter 9 - Abundance from Capture-Recapture Data
	9.1 Data Requirements
		9.1.1 Capture History Format
		9.1.2 Summarizing Capture History Data
	9.2 Closed Population, Single Recapture
		9.2.1 Single Group
		9.2.2 Separate Groups
		9.2.3 Assumptions
	9.3 Closed Population, Multiple Recaptures
		9.3.1 Schnabel and Schumacher-Eschmeyer Methods
		9.3.2 Log-Linear Model Methods
		9.3.3 Assumptions
	9.4 Open Populations
		9.4.1 Jolly-Seber Method
		9.4.2 Log-Linear Model or Cormack-Jolly-Seber Method
		9.4.3 Assumptions
	9.5 Further Considerations
	Notes
Chapter 10 - Abundance from Depletion Data
	10.1 Leslie and DeLury Methods
		10.1.1 Assumptions
	10.2 K-Pass Removal Methods
		10.2.1 Equal Catchability Among Passes
		10.2.2 Catchability Differs in First Pass
	Notes
Chapter 11 - Mortality Rates
	11.1 Total Mortality Definitions
	11.2 Total Mortality from Catch Curve Data
		11.2.1 Data Requirements
		11.2.2 Chapman-Robson Method
		11.2.3 Regression Methods
			11.2.3.1 Single Estimate
			11.2.3.2 Comparing Estimates
		11.2.4 Catch Curve Assumptions
	11.3 Total Mortality from Capture-Recapture Data
		11.3.1 Jolly-Seber Method
		11.3.2 Log-Linear Model or Cormack-Jolly-Seber Method
	11.4 Mortality Components
		11.4.1 Estimates of M or F from Field Data
		11.4.2 Meta-Analytic Estimates of M
	11.5 Further Considerations
	Notes
Chapter 12 - Individual Growth
	12.1 Data Requirements
	12.2 Growth Functions
	12.3 Fitting Nonlinear Regressions
		12.3.1 Starting Values
		12.3.2 Model Fitting
		12.3.3 Parameter Estimates
		12.3.4 Predictions
		12.3.5 Visualizing the Model Fit
		12.3.6 Assumptions
	12.4 Among Group Statistical Comparisons
		12.4.1 Family of Models
		12.4.2 Model Fitting
			Fit and Assess General Model
			Identify Any Differences
			Finding the Best Subset Model
			Model Selection with AIC or BIC
		12.4.3 Summarizing the Model Fit
	12.5 Typical Model Fitting Problems
	12.6 Further Considerations
	Notes
Chapter 13 - Recruitment
	13.1 Stock-Recruitment Relationships
		13.1.1 Data Requirements
		13.1.2 Common Models
		13.1.3 Fitting Models
			13.1.3.1 Starting Values
			13.1.3.2 Error Structure
			13.1.3.3 Parameter Estimates and Confidence Intervals
			13.1.3.4 Model Predictions
			13.1.3.5 Assessing Parameter Significance
			13.1.3.6 Visualizing the Model Fit
		13.1.4 Additional Explanatory Variables
	13.2 Spawning Potential Ratio
		13.2.1 Single Values
		13.2.2 Multiple Values
	13.3 Year-Class Strength
		13.3.1 Catch-Curve Residuals
		13.3.2 Two-Way ANOVA Models
	13.4 Further Considerations
	Notes
References
Subject Index
R Functions (Demonstrated) Index
R Functions (Mentioned) Index
Scientific Names