Employment in Fisheries and Aquaculture by Year — employment

This function summarises the FAO employment statistics (load_fao_employment()) of one or more countries, or of the world: the number of people in aquaculture, marine fishing, inland fishing and work areas not specified, by year, and how many are women and how many work full time, as FAO does in The State of World Fisheries and Aquaculture (FAO 2024, 2026).

Usage

employment_summary(
  country_name = NULL,
  employment = NULL,
  plot = TRUE,
  table = TRUE,
  lang = NULL,
  pptx = getOption("faofishingreport.pptx", FALSE),
  plot_show = fao_setting("plot_show"),
  label = NULL
)

Arguments

country_name: One or more countries, as named in the FAO data (e.g. "Norway"). Default is NULL, the world (all countries summed).
employment: Employment data from load_fao_employment(). Default is NULL, which loads it.
plot: A logical value. If TRUE (default), charts are saved in figures/png/summary/.
table: A logical value. If TRUE (default), tables are saved in tables/.
lang: The language of the chart text and names: "en" (English), "zh" (Chinese) or "both" (Chinese and English). Default is NULL, which uses the language set with fao_settings() ("en" unless changed).
pptx: A logical value. If TRUE, charts are also saved as editable PowerPoint files in figures/pptx/summary/. Default is FALSE, which can be changed for all functions with fao_settings(pptx = TRUE).
plot_show: A logical value. If TRUE, each chart is also drawn in the plot window (e.g. the Plots pane of RStudio) as it is saved, to look at it at once. Default is FALSE, which can be changed for all functions with fao_settings(plot_show = TRUE). The charts are saved as files (plot = TRUE) either way.
label: The name used in the output file names. Default is the country, "selected_countries" for several countries, or "World".

Value

Invisibly, a list of two data frames:

yearly: one row per country (or the world) and year: people in aquaculture, marine coastal, deep-sea and not specified fishing, all marine fishing, inland fishing, work area unspecified and in total; women, men and sex unknown; full time, part time, occasional and working time unknown; the share of women and of each working time among those known, the share with sex or working time unknown, and the share in estimated values; NA in the years without any record (not reported), between the first and last years reported;
notes: FAO's notes on the countries.

Charts are saved in figures/png/summary/: <label>_employment.png (people by work area, stacked) and <label>_employment_composition.png (shares of women and full-time workers, and of unknown sex and working time). The table <label>_employment.csv is saved in tables/.

Details

The shares of women and of full-time workers are calculated among the people whose sex or working time is known, and the share of people with unknown sex or working time is given next to them, as FAO does: they are unknown for a third to a half of the people (FAO 2024, 2026), and the detail available can change from year to year (FAO metadata), so a change in a share can come from a change in reporting. estimated_pct is the share of the people in estimated values (estimated by FAO or by the country). The FAO notes on each country are shown and returned (there are none for the world as a whole); read them before comparing years or countries.

References

FAO (2024). The State of World Fisheries and Aquaculture 2024. Blue Transformation in action. Rome: FAO. doi:10.4060/cd0683en

FAO (2026). The State of World Fisheries and Aquaculture 2026. Rome: FAO. doi:10.4060/cd8357en

FAO. Global employment in the primary sector of fisheries and aquaculture (FI_Employment), metadata and country notes of the release. https://www.fao.org/fishery/static/Data/

Coordinating Working Party on Fishery Statistics (CWP). Handbook of Fishery Statistics: fishers. https://www.fao.org/cwp-on-fishery-statistics/handbook/capture-fisheries-statistics/fishers/en/

Examples

if (FALSE) { # \dontrun{
employment <- load_fao_employment()
employment_summary(employment = employment, lang = "zh")              # the world
employment_summary(c("Norway", "Viet Nam", "Peru"), employment = employment)
} # }