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Data

Annual fish catch relative to mean catch by region

About this data

Source
RAM Legacy Stock Assessment Database (2021) – processed by Our World in Data
Last updated
September 10, 2021
Date range
1970–2018

Sources and processing

This data is based on the following sources

RAM Legacy Stock Assessment Database – Marine stocks by region and taxa

This dataset provides aggregated data on fish biomass, fishing pressure and catch by region and taxa, based on the results of the RAM Legacy Stock Assessment Database: https://www.ramlegacy.org/

This aggregated data was provided by Michael Melnychuk, researcher on the RAM Legacy Database.

These results were published in PNAS here: Hilborn, R., Amoroso, R. O., Anderson, C. M., Baum, J. K., Branch, T. A., Costello, C., ... & Ye, Y. (2020). Effective fisheries management instrumental in improving fish stock status. Proceedings of the National Academy of Sciences, 117(4), 2218-2224. Available at: https://www.pnas.org/content/117/4/2218

Definitions are as follows: – 'Biomass' is a measure of biomass of fish divided by the biomass of fish at the maximum sustainable yield (B / Bmsy) – 'Fishing pressure' is a measure of fishing pressure divided by the pressure at the maximum sustainable yield (U / Umsy) – 'Catch' is a measure of the annual catch divided by the mean catch across the stock's time series

Retrieved on
September 10, 2021
Retrieved from
https://www.ramlegacy.org/
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
RAM Legacy Stock Assessment Database. 2021. Version 4.495-assessment-only. Retrieved from DOI:10.5281/zenodo.4824192.

This dataset provides aggregated data on fish biomass, fishing pressure and catch by region and taxa, based on the results of the RAM Legacy Stock Assessment Database: https://www.ramlegacy.org/

This aggregated data was provided by Michael Melnychuk, researcher on the RAM Legacy Database.

These results were published in PNAS here: Hilborn, R., Amoroso, R. O., Anderson, C. M., Baum, J. K., Branch, T. A., Costello, C., ... & Ye, Y. (2020). Effective fisheries management instrumental in improving fish stock status. Proceedings of the National Academy of Sciences, 117(4), 2218-2224. Available at: https://www.pnas.org/content/117/4/2218

Definitions are as follows: – 'Biomass' is a measure of biomass of fish divided by the biomass of fish at the maximum sustainable yield (B / Bmsy) – 'Fishing pressure' is a measure of fishing pressure divided by the pressure at the maximum sustainable yield (U / Umsy) – 'Catch' is a measure of the annual catch divided by the mean catch across the stock's time series

Retrieved on
September 10, 2021
Retrieved from
https://www.ramlegacy.org/
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
RAM Legacy Stock Assessment Database. 2021. Version 4.495-assessment-only. Retrieved from DOI:10.5281/zenodo.4824192.

How we process data at Our World in Data

All data and visualizations on Our World in Data rely on data sourced from one or several original data providers. Preparing this original data involves several processing steps. Depending on the data, this can include standardizing country names and world region definitions, converting units, calculating derived indicators such as per capita measures, as well as adding or adapting metadata such as the name or the description given to an indicator.

At the link below you can find a detailed description of the structure of our data pipeline, including links to all the code used to prepare data across Our World in Data.

Read about our data pipeline

Reuse this work

  • All data produced by third-party providers and made available by Our World in Data are subject to the license terms from the original providers. Our work would not be possible without the data providers we rely on, so we ask you to always cite them appropriately (see below). This is crucial to allow data providers to continue doing their work, enhancing, maintaining and updating valuable data.
  • All data, visualizations, and code produced by Our World in Data are completely open access under the Creative Commons BY license. You have the permission to use, distribute, and reproduce these in any medium, provided the source and authors are credited.

Citations

How to cite this page

To cite this page overall, including any descriptions, FAQs or explanations of the data authored by Our World in Data, please use the following citation:

“Data Page: Annual fish catch relative to mean catch by region”. Our World in Data (2026). Data adapted from RAM Legacy Stock Assessment Database. Retrieved from https://archive.ourworldindata.org/20260511-092124/grapher/fish-catch-region.html [online resource] (archived on May 11, 2026).

How to cite this data

In-line citationIf you have limited space (e.g. in data visualizations), you can use this abbreviated in-line citation:

RAM Legacy Stock Assessment Database (2021) – processed by Our World in Data

Full citation

RAM Legacy Stock Assessment Database (2021) – processed by Our World in Data. “Annual fish catch relative to mean catch by region” [dataset]. RAM Legacy Stock Assessment Database, “Marine stocks by region and taxa 4.495-assessment-only” [original data]. Retrieved May 14, 2026 from https://archive.ourworldindata.org/20260511-092124/grapher/fish-catch-region.html (archived on May 11, 2026).

Download

Quick download

Download the data shown in this chart as a ZIP file containing a CSV file, metadata in JSON format, and a README. The CSV file can be opened in Excel, Google Sheets, and other data analysis tools.

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Includes all entities and time points

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Data API

Use these URLs to programmatically access this chart's data and configure your requests with the options below. Our documentation provides more information on how to use the API, and you can find a few code examples below.

Data URL (CSV format)
https://ourworldindata.org/grapher/fish-catch-region.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://ourworldindata.org/grapher/fish-catch-region.metadata.json?v=1&csvType=full&useColumnShortNames=false

Code examples

Examples of how to load this data into different data analysis tools.

Excel / Google Sheets
=IMPORTDATA("https://ourworldindata.org/grapher/fish-catch-region.csv?v=1&csvType=full&useColumnShortNames=false")
Python with Pandas
import pandas as pd
import requests

# Fetch the data.
df = pd.read_csv("https://ourworldindata.org/grapher/fish-catch-region.csv?v=1&csvType=full&useColumnShortNames=false", storage_options = {'User-Agent': 'Our World In Data data fetch/1.0'})

# Fetch the metadata
metadata = requests.get("https://ourworldindata.org/grapher/fish-catch-region.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/fish-catch-region.csv?v=1&csvType=full&useColumnShortNames=false")

# Fetch the metadata
metadata <- fromJSON("https://ourworldindata.org/grapher/fish-catch-region.metadata.json?v=1&csvType=full&useColumnShortNames=false")
Stata
import delimited "https://ourworldindata.org/grapher/fish-catch-region.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear