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TropFishR

Package description

TropFishR is a collection of fisheries models based on the FAO Manual "Introduction to tropical fish stock assessment" by Sparre and Venema (1998, 1999). Not only scientists working in the tropics will benefit from this new toolbox. The methods work with age-based or length-frequency data and assist in the assessment of data poor fish stocks. Overall, the package comes with 30 functions, 19 data sets and 10 s3 methods. All objects are documented and provide examples that allow reproducing the examples from the FAO manual.

News

You can find detailed descriptions of new features, bug fixes, other changes of specific package versions here.

Installation

Download the released version of TropFishR from CRAN:

install.packages(“TropFishR”)

Or the development version from GitHub:

# install.packages(devtools)
devtools::install_github(“tokami/TropFishR”)

Citation

Please use the R command citation("TropFishR") to receive information on how to cite this package.

Documentation

The tutorial demonstrates the use of the main functions of TropFishR for a single-species stock assessment with length-frequency data. The lfqDataTutorial gives a brief description of LFQ data and illustrates how files with raw length measurements (e.g. excel files) can be imported into R and trimmed for the use with TropFishR. The ELEFANTutorial demonstrates the ELEFAN functions available in TropFishR in detail and discusses best practices.

Questions / Issues

In case you have questions or find bugs, please write an email to Tobias Mildenberger or post on TropFishR/issues. If you want to be updated with the development of the package or want to discuss with TropFishR users and developers, follow the project on ResearchGate.

References

  1. Sparre, P., Venema, S.C., 1998. Introduction to tropical fish stock assessment. Part 1. Manual. FAO Fisheries Technical Paper, (306.1, Rev. 2). 407p. link
  2. Sparre, P., Venema, S.C., 1999. Introduction to tropical fish stock assessment. Part 2. Excercises. FAO Fisheries Technical Paper, (306.2, Rev. 2). 94p. link
  3. Mildenberger, T. K., Taylor, M. H. and Wolff, M., 2017. TropFishR: an R package for fisheries analysis with length-frequency data. Methods in Ecology and Evolution, 8: 1520-1527. doi:10.1111/2041-210X.12791 link
  4. Taylor, M. H., and Mildenberger, T. K., 2017. Extending electronic length frequency analysis in R. Fisheries Management and Ecology, 24:330-338. doi:10.1111/fme.12232 link

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Version

Install

install.packages('TropFishR')

Monthly Downloads

541

Version

1.6.2

License

GPL-3

Issues

Pull Requests

Stars

Forks

Maintainer

Tobias K Mildenberger

Last Published

January 28th, 2020

Functions in TropFishR (1.6.2)

ELEFAN_SA

ELEFAN_SA
alba

Length-frequency data of the clam Abra alba
ELEFAN_GA

ELEFAN_GA
Z_BevertonHolt

Beverton & Holt's Z-Equations
VBGF

Von Bertalanffy Growth function (VBGF)
ELEFAN

ELEFAN
Z_CPUE

Estimate Z from CPUE data
Bhattacharya

Bhattacharya's method
VPA

Virtual Population Analysis (VPA)
gillnet

Gillnet data
catchCurve

Catch curve
M_empirical

Empirical formulas for the estimation of natural mortality
growth_tagging

Growth from tagging data
bream

bream data
haddock

Haddock data
hake

Hake data
date2yeardec

Date - Year conversion
plot.lfq

Plotting of length frequency data (with VBGF curves)
lfqRestructure

Restructuring of length frequency data
plot.Bhattacharya

Bhattacharya plot
gillnetfit

Millar's original gillnet selectivity fitting function
lfqCreate

Create lfq data from length measurements
plot.predict_mod

Plotting prediction models yield per recruit and Thompson & Bell
plot.prod_mod

Plotting production models
emperor

Emperor data
goatfish

Yellowstriped goatfish data
plot.recruitment

Plot of recruitment patterns
plot.select_Millar

Millar's selectivity plot
startingPoint2tanchor

Convert FiSAT's starting point to t_anchor value
plot.prod_mod_ts

Plotting time series production models
stock_sim

Stock simulation
plot.select

Selectivity plot
growth_length_age

Estimation of growth parameter using length-at-age data
lfqFitCurves

Fitting VBGF growth curves through lfq data
synCAA1

Synthetic Catch-at-age data I
synCAA2

Synthetic Catch-at-age data II
synLFQ8

Synthetic length-frequency data VIII with variable harvest rate
lfqModify

Modify lfq data for further analysis
tilapia

Tilapia data
synLFQ2

Synthetic length frequency data II
rcurves_Millar

Predict gillnet selectivity (old Millar method)
select_ogive

Selectivity patterns
prod_mod_ts

Production models with time series fitting
synLFQ1

Synthetic length-frequency data I
shrimps

Shrimp data
synCPUE

Synthetical catch per unit of effort (CPUE) dataset
synLFQ3

Synthetic length frequency data III
recruitment

Recruitment patterns
rtypes_Millar

Millar's selectivity types
powell_wetherall

Powell-Wetherall method
synLFQ6

Synthetic length-frequency data VI (without seasonal oscillation)
synLFQ7

Synthetic length-frequency data VII with seasonal oscillation
whiting

Whiting data
yeardec2date

Year - Date conversion
ypr

Yield per recruit
ypr_sel

Yield per recruit with selection ogive
plot.catchCurve

Plotting catch curve
plot.VPA

VPA plot
prod_mod

Production models
predict_mod

Prediction models
select

Selectivity model
select_Millar

Millar's selectivity model
synLFQ4

Synthetic length-frequency data IV (with seasonal oscillation)
synLFQ5

Synthetic length-frequency data V (without seasonal oscillation)
trawl_fishery_Java

Data from the trawl fishery off the North coast of Java
trammelnet

Trammel net data