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.

FLRDynState

2-Species Dynamic State Variable Model in FLR.

kobe

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

FLife

Methods for incorporating life history traits and processes.

diags

Diagnostics for stock assessment methods.

mpb

Biomass dynamics population and management procedures that can be simulation tested.

mse

Tools for implementing and evaluting management procedures using MSE.

FLasher

Next generation package for fisheries forecasting using Rcpp and cppAD.

Installing FLR

To install the released versions of the FLR packages, and all their dependencies, you can run in an R session our installation script

source("http://flr-project.org/R/instFLR.R")

or access directly the FLR repository by calling

install.packages(repos="http://flr-project.org/R")

About FLR

The FLR project attempts to develop and provide a 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.

Publications

Studies and publications citing or using FLR.

Contact Us

To stay updated

You can subscribe to the FLR help mailing list.

To report bugs or propose changes

Please submit an issue at the FLCore issue page, or at the issue page for the relevant package.

Or you can send an email to flr@flr-project.org.