🔍 Data quality, diversity and fleets

📦 Data: FAO Global Capture Production, release 2026.1.0 (published by FAO on 2026-03-30; catches 1950–2024), downloaded from Capture_2026.1.0.zip. Licence CC BY 4.0. fao_data_info() shows the release you use and how to cite it.

Like the analyses of 📈 Composition, stock status and trends, these functions take any catch data: a fishing area from fishing_area_data(), or any subset of load_fao_data(). Their charts are saved in figures/png/summary/ and their tables in tables/, with the name of the area at the start of the file names (or label), and they return their results invisibly.

FAO27 <- fishing_area_data("Atlantic, Northeast")

⚙️ Common arguments

All four functions have these arguments; the tables of each function list only its own.

Argument	Meaning	Default
area_data	FAO catch data: fishing_area_data()$area_data, or any subset of load_fao_data() (e.g. one country, or several fishing areas)	required
plot	Save the charts in figures/png/summary/	TRUE
table	Save the tables in tables/	TRUE
lang	Language of the chart text and names: "en", "zh" or "both"	NULL: the language of fao_settings() ("en" unless changed)
pptx	Also save the charts as editable PowerPoint files in figures/pptx/summary/	FALSE; fao_settings(pptx = TRUE) changes it for all functions
plot_show	Also draw each chart in the plot window (e.g. the Plots pane of RStudio) as it is saved	FALSE, or plot_show of fao_settings()
label	Name at the start of the output file names	NULL: the fishing area of the data (or its country; "selected_data" for several areas and countries)

🧪 Data quality

data_quality() shows two aspects of the statistics over time:

• the share of the catch reported officially (FAO status flag A), the share estimated by the country or imputed by FAO (flags E and I), and the share with other flags (e.g. provisional or negligible values);
• the share of the catch identified to species, genus, family, or only to an order or a higher group such as “Marine fishes nei”, from the FAO taxonomic codes.

quality <- data_quality(FAO27$area_data)

A large estimated share in the latest years usually means that FAO has not yet received the national reports; these values are often revised in the next release (Garibaldi 2012). The country table shows, for the countries with the largest catch in the last five years, how much of their catch in those years was estimated and how much identified to species:

show_table(quality$countries, digits = 1)

country	country_en	catch_last_5_years	estimated_pct	species_level_pct
Norway	Norway	11327375	0.0	95.5
Iceland	Iceland	6329277	0.0	99.4
Russian Federation	Russian Federation	4811200	0.0	99.6
United Kingdom	United Kingdom	3340084	0.0	96.9
Faroe Islands	Faroe Islands	3252896	0.0	98.1
Denmark	Denmark	2606338	0.0	79.8
France	France	1824629	0.2	91.0
Netherlands (Kingdom of the)	Netherlands (Kingdom of the)	1327367	0.0	100.0
Spain	Spain	1271825	0.0	94.4
Ireland	Ireland	1142570	16.4	85.8

Argument	Meaning	Default
top_n	Number of countries in the country table	10
area_data, plot, table, lang, pptx, label	See Common arguments

Output: <label>_data_quality_status_share.png and <label>_data_quality_taxon_share.png, and the tables <label>_data_quality_status.csv, ..._taxon.csv and ..._countries.csv; the function returns data_status, taxon_level (yearly catch by category) and countries.

The FAO statistics are the catches reported by countries (and estimated by FAO when no report arrives). Catch reconstructions that add estimates of unreported catches and discards found global marine catches higher than reported, and declining more strongly since their peak (Pauly and Zeller 2016). The data quality charts show how the reported statistics were made, not how complete they are.

🌈 Diversity and concentration

diversity_concentration() computes, for each year:

Indicator	Column	Calculation
Number of species reported	n_species	Items identified to species with catch
Number of countries	n_countries	Countries with catch
Shannon diversity (Shannon 1948)	shannon_species	$H = -\sum_i p_i \ln p_i$, with $p_i$ the share of species item $i$ (all items, including “nei” groups) in the year’s catch
HHI of species / countries (Rhoades 1993)	hhi_species, hhi_countries	$\text{HHI} = \sum_i (100\,p_i)^2$, from 0 to 10 000
Top-N share	top5_species_pct, top5_countries_pct	Share (%) of the top_n largest species items or countries (the column names follow top_n)

diversity <- diversity_concentration(FAO27$area_data, top_n = 5)

show_table(subset(diversity, Year %in% c(1970, 1990, 2010, max(Year))), digits = 2)

	Year	n_species	n_countries	shannon_species	hhi_species	hhi_countries	top5_species_pct	top5_countries_pct
1970	1970	107	22	3.02	897.68	1,348.67	60.29	71.05
1990	1990	161	24	3.32	631.00	1,199.47	48.53	68.73
2010	2010	280	26	3.21	862.25	1,405.73	53.74	69.11
2024	2024	514	32	2.96	1,100.44	1,226.80	64.95	67.81

Argument	Meaning	Default
top_n	Number of largest species items and countries in the top share	5
area_data, plot, table, lang, pptx, label	See Common arguments

Output: <label>_diversity.png (all indicators) and the table <label>_diversity.csv; the function returns a data frame with one row per year.

Reading the indicators. A higher Shannon index means more species items and a more even catch; its maximum is $\ln S$ for $S$ items. In the US merger guidelines (U.S. Department of Justice and Federal Trade Commission 2010), an HHI below 1 500 is unconcentrated, 1 500 to 2 500 moderately and above 2 500 highly concentrated. For example, three species with shares of 50%, 30% and 20% give $H = 1.03$ and $\text{HHI} = 50^2 + 30^2 + 20^2 = 3\,800$.

The indicators use FAO species items, including “nei” groups. When FAO splits a “nei” group into species, Shannon diversity rises and HHI falls even if nothing changed at sea. Country indicators change when countries split, e.g. the USSR in 1991.

🏳️ Country groups

country_group_summary() sums the catch by groups of countries from the FAO country list: World Bank income group, continent or region. It saves a chart of the catch of each group and one of its share, and a table by decade like that of species_group_composition().

income <- country_group_summary(FAO27$area_data, group = "income")

country_group_summary(FAO27$area_data, group = "region", top_n = 6, lang = "zh")

Argument	Meaning	Default
group	"income" (World Bank income groups), "continent" or "region"	"income"
top_n	Number of groups shown separately; the others are combined	8
area_data, plot, table, lang, pptx, label	See Common arguments

Output: <label>_country_income.png (or _continent, _region) and ..._share.png, and the table <label>_country_income.csv; the function returns yearly and table.

🚢 Coastal countries and distant-water fleets

coastal_distant() splits the catch between countries that border the fishing area and distant-water fleets from elsewhere, and shows the main distant-water countries.

A country is coastal to an area if its land (including overseas territories, from the Natural Earth map units) lies within 20 km of the FAO area boundary (the FAO major fishing areas of the CWP handbook). Former countries such as the USSR take the coastline of their successor states. In area 34 (Eastern Central Atlantic), for example, Spain and Portugal count as coastal because of the Canary Islands and Madeira. Catch reported as “Other nei” is shown as unknown.

fleets <- coastal_distant(FAO27$area_data)

show_table(fleets$table, digits = 0)

Fleet	1950s	1960s	1970s	1980s	1990s	2000s	2010s	2020s	2020	2021	2022	2023	2024	share_2024_pct
Coastal countries	6,956,166	8,930,049	11,522,278	10,722,687	10,713,646	10,080,097	8,899,457	8,445,147	8,598,826	8,343,100	8,719,874	8,738,529	7,825,406	100
Distant-water countries	0	1,000	20,186	14,021	16,346	3,569	7,511	12,742	10,649	15,624	9,353	11,298	16,787	0
Unknown	0	0	0	2	107	0	1,144	930	2,227	2	2,420	2	2	0

Argument	Meaning	Default
top_n	Number of distant-water countries shown separately	8
area_data, plot, table, lang, pptx, label	See Common arguments

The analysis works for marine areas; inland areas in the data are left out with a message. Output: <label>_coastal_distant.png and ..._share.png (coastal, distant-water and unknown catch), <label>_coastal_distant_countries.png (main distant-water countries), and the tables <label>_coastal_distant.csv and ..._countries.csv; the function returns yearly, distant and table. The profiles of the main distant-water countries are in 🔬 Shocks, collapses, synchrony and fleets.

📝 In the Word report

fao_report() writes data quality, diversity and concentration, and coastal and distant-water fleets into the Word report of a fishing area (see 📝 Assessment report: Word, LaTeX and PDF): they are the sections quality, diversity and fleets, all on by default. Their settings are given with the section name as prefix (quality_ for data_quality(), diversity_ for diversity_concentration(), fleets_ for coastal_distant()), and a section is left out with FALSE:

fao_report(27, diversity_top_n = 3, fleets = FALSE)

country_group_summary() is not part of the report.

📖 References

CWP (Coordinating Working Party on Fishery Statistics). CWP Handbook of Fishery Statistics: Main water areas (FAO major fishing areas). Rome: FAO. https://www.fao.org/cwp-on-fishery-statistics/handbook/general-concepts/main-water-areas/en/

FAO (2026). Global Capture Production 1950–2024, release 2026.1.0. In: Fisheries and Aquaculture. Rome: FAO. https://www.fao.org/fishery/collection/capture/en. Licence: CC BY 4.0. Release file: https://www.fao.org/fishery/static/Data/Capture_2026.1.0.zip

Garibaldi, L. (2012). The FAO global capture production database: a six-decade effort to catch the trend. Marine Policy 36: 760–768. doi:10.1016/j.marpol.2011.10.024

Natural Earth. Free vector and raster map data at 1:10m, 1:50m and 1:110m scales. https://www.naturalearthdata.com/

Pauly, D. and Zeller, D. (2016). Catch reconstructions reveal that global marine fisheries catches are higher than reported and declining. Nature Communications 7: 10244. doi:10.1038/ncomms10244

Rhoades, S.A. (1993). The Herfindahl-Hirschman index. Federal Reserve Bulletin 79(3): 188–189.

Shannon, C.E. (1948). A mathematical theory of communication. Bell System Technical Journal 27: 379–423. doi:10.1002/j.1538-7305.1948.tb01338.x

U.S. Department of Justice and Federal Trade Commission (2010). Horizontal Merger Guidelines, section 5.3 (market concentration). Washington, DC. https://www.justice.gov/atr/horizontal-merger-guidelines-08192010