fishstat-package: Global Fishery and Aquaculture Statistics

In fishstat: Global Fishery and Aquaculture Statistics

Global Fishery and Aquaculture Statistics

Description

The Food and Agriculture Organization of the United Nations (FAO) FishStat database is the leading source of global fishery and aquaculture statistics and provides unique information for sector analysis and monitoring.

This package provides the global production data from all fisheries and aquaculture in R format, ready for analysis.

Details

Production tables:

aquaculture	aquaculture production
capture	capture production
production	aquaculture and capture production

Lookup tables:

area	fishing areas
country	countries and territories
environment	aquaculture environments
measure	units of measurement
source	sources of production
species	taxonomic groups
status	status of data entries

Joining Tables

Production tables can be joined with lookup tables using the merge function, as demonstrated in the help page examples for aquaculture and capture production. The column names in this package have been designed to allow automatic inference of which columns to join, and the resulting table will have unique column names.

The merge function is generally useful for joining tables, but other join methods are available in R that can be faster but require either additional packages or more coding. The production example uses square brackets and the match function to add one lookup column at a time to the production table. Compared to the slower merge function, this saves time, both for users and CRAN servers running maintenance tests.

Rather than optimizing speed or memory footprint, one can optimize convenience by constructing a full table with all data records and all columns:

prod.all <- merge(merge(merge(merge(merge(merge(production,
                  area), country), measure), source), species), status)
cap.all <- merge(merge(merge(merge(merge(capture,
                 area), country), measure), species), status)
aqua.all <- merge(merge(merge(merge(merge(merge(aquaculture,
                  area), country), environment), measure), species), status)

Popular paradigms for joining tables include:

• Base R, where merge returns a data.frame.

• The dplyr package, where inner_join returns a tibble.

• The data.table package, where merge returns a data.table.

Note

The data in the package were downloaded from the FAO data server and imported into R. The R package version indicates the version of FishStat data it includes. Column names have been simplified to facilitate quick exploration and plotting in R.

An effort has been made to describe each table in the corresponding R help page. However, the official and authoritative documentation of the FishStat database is found on the FAO FishStat website.

The example below demonstrates how the FishStat data can be used to produce an overview of global fisheries and aquaculture. The combination of FishStat and the R environment can also be very efficient for analyses that focus on selected areas, countries, species, and/or taxonomic groups.

Author(s)

Arni Magnusson and Rishi Sharma created this R package.

All credit for the FishStat database goes to the Statistics Team of the FAO Fisheries and Aquaculture Division, as well as national data submitters. The database terms of use are based on the CC BY-NC-SA 3.0 IGO license. The R package is released under a similar CC BY-NC-SA 4.0 license.

To cite the use of FishStat data:

FAO. [Year]. FishStat data. Fisheries and Aquaculture Division. Rome. https://www.fao.org/fishery/en/fishstat.

To cite the use of this R package to access the data, cite FishStat (above) as well as:

Magnusson, A. and R. Sharma. [Year]. fishstat: Global Fishery and Aquaculture Statistics. R package version [Version]. https://cran.r-project.org/package=fishstat.

See Also

The package on CRAN provides the latest FishStat data, within a few weeks after the official FAO data release. For research and reference purposes, packages containing older data releases are available on GitHub with descriptive names such as fishstat21 and fishstat22, containing the FAO FishStat data releases from 2021 and 2022:

install_github("https://github.com/sofia-taf/fishstat21")
install_github("https://github.com/sofia-taf/fishstat22")

Examples

head(production)

# Analyze production measured in tonnes
prod <- production[production$measure == "Q_tlw" & production$value > 0,]

# Fast merge yearbook and inlandmarine columns
prod$yearbook <- species$yearbook[match(prod$species, species$species)]
prod$inlandmarine <- area$inlandmarine[match(prod$area, area$area)]

# Select SOFIA species, excluding mammals, reptiles, and plants
prod <- prod[grep("Fish, crustaceans and molluscs", prod$yearbook, fixed=TRUE),]

# Determine origin
prod$origin <- ifelse(prod$source == "CAPTURE", "Capture", "Aquaculture")
prod$w <- ifelse(prod$inlandmarine == "Marine areas", "marine", "inland")
prod$origin <- paste0(prod$origin, " (", prod$w, ")")
cbind(sort(unique(prod$origin)))

# World capture fisheries and aquaculture production
x <- xtabs(value~year+origin, aggregate(value~year+origin, prod, sum))
x <- x[,c(2,1,4,3)] / 1e6
library(areaplot)
areaplot(x, legend=TRUE, args.legend=list(x="topleft"), ylab="million tonnes")

fishstat documentation built on June 17, 2025, 9:08 a.m.