FLR

The Fisheries Library in R, a collection of tools for quantitative fisheries science, developed in the R language, that facilitates the construction of bio-economic simulation models of fisheries systems.

INSTALL

Packages

The FLR toolset is composed of a series of packages offering different classes, methods and models.

FLCore

Core classes and methods for FLR.

FLa4a

The a4a population model for stock assessment and MSE.

ggplotFL

Apply ggplot2 to the FLR classes.

FLBRP

Reference Points and Fisheries Advice.

FLFleet

Modelling of fishing fleet dynamics.

FLBEIA

Bio-Economic Impact Assessment of Management strategies.

FLSAM

SAM stock assessment model in FLR.

FLXSA

Data sets and methods to simulate data.

FLAssess

Support for FLR Stock Assessment methods.

FLash

Package for fisheries forecasting.

kobe

Methods for summarising results from SAs and MSEs in the Kobe format.

FLasher

Next generation package for fisheries forecasting using Rcpp and cppAD.

FLife

Methods for incorporating life history traits and processes.

diags

Diagnostics for stock assessment methods.

mse

Tools for implementing and evaluating management procedures using MSE.

bbm

Two-stage biomass based model.

a4adiags

Perform diagnostics on a4a fit

FLSRTMB

Fit Stock-Recruitment Relationships in TMB

Installing FLR

To install the latest versions of any FLR package, and all the necessary dependencies, start R and enter


          install.packages(repos=c(FLR="https://flr.r-universe.dev", CRAN="https://cloud.r-project.org"))

A good starting point to explore FLR is A quick introduction to FLR

Tutorials

About FLR

The FLR project has been developing and providing fishery scientists with a powerful and flexible platform for quantitative fisheries science based on the R statistical language. The guiding principles of FLR are openness, through community involvement and the open source ethos, flexibility, through a design that does not constraint the user to a given paradigm, and extendibility, by the provision of tools that are ready to be personalized and adapted. The main aim is to generalize the use of good quality, open source, flexible software in all areas of quantitative fisheries research and management advice.

FLR development

Development code for FLR packages is available both on Github and on R-Universe. Bugs can be reported on Github as well as suggestions for further development.

Publications

Studies and publications citing or using FLR

Community

To stay updated

You can subscribe to the FLR mailing list.

To report bugs or propose changes

Please submit an issue for the relevant package, or at the tutorials repository.