TropFishR v1.6.2


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Tropical Fisheries Analysis

A compilation of fish stock assessment methods for the analysis of length-frequency data in the context of data-poor fisheries. Includes methods and examples included in the FAO Manual by P. Sparre and S.C. Venema (1998), "Introduction to tropical fish stock assessment" (<>), as well as other more recent methods.



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.


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


Download the released version of TropFishR from CRAN:


Or the development version from GitHub:

# install.packages(devtools)


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


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.


  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

Functions in TropFishR

Name Description
alba Length-frequency data of the clam Abra alba
Z_BevertonHolt Beverton & Holt's Z-Equations
VBGF Von Bertalanffy Growth function (VBGF)
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 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
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Last month downloads


Type Package
Date 2020-01-27
LazyData TRUE
License GPL-3
NeedsCompilation no
RoxygenNote 7.0.2
VignetteBuilder knitr
Packaged 2020-01-28 13:19:18 UTC; tokami
Repository CRAN
Date/Publication 2020-01-28 14:30:06 UTC

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