Tropical Fisheries Analysis with R
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Failed to load latest commit information.
R
data
inst
man
vignettes
.Rbuildignore
.gitattributes Update .gitattributes Feb 13, 2017
.gitignore
.travis.yml
DESCRIPTION
NAMESPACE
README.md
TropFishR.Rproj

README.md

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. In addition, the package includes the Length-based Bayesian biomass estimator method (LBB) by Froese et al. (2018), which allows to estimate reference levels (e.g. B/B0) based on yearly length-frequency data.

News

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

Installation

First, install the Gibbs sampler JAGS for your Operating System from this web site.

Then, 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. The LBBmanual introduces the Length-based Bayesian biomass estimator method (LBB) by Froese et al. (2018) and demonstrates its usage within TropFishR.

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
  5. Froese R, Winker H, Coro G, Demirel N, Tsikliras AC, Dimarchopoulou D, Scarcella G, Probst WN, Dureuil M, and Pauly D (2018). "A new approach for estimating stock status from length frequency data". ICES Journal of Marine Science. doi:10.1093/icesjms/fsy078 link