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Fish Stocks

Metric
Total or Relative
Fish Stocks

Interactive visualization requires JavaScript.

About this data

Source
RAM Legacy Stock Assessment Database (2018) – processed by Our World in Data
Last updated
October 30, 2024
Date range
1800–2017

Sources and processing

This data is based on the following sources

RAM Legacy Stock Assessment Database – Fish stocks (RAM Legacy Stock Assessment Database)

The RAM Legacy Stock Assessment Database is a compilation of stock assessment results for commercially exploited marine populations from around the world. It provides data on fish biomass, catch, fishing intensity and other indicators of stock status, used to evaluate the abundance and exploitation of fish populations.

Retrieved on
October 30, 2024
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.
Ricard, D., Minto, C., Jensen, O.P. and Baum, J.K. (2012) Evaluating the knowledge base and status of commercially exploited marine species with the RAM Legacy Stock Assessment Database. Fish and Fisheries 13 (4) 380-398. DOI: 10.1111/j.1467-2979.2011.00435.x
RAM Legacy Stock Assessment Database. 2018. Version 4.44-assessment-only. Released 2018-12-22. Retrieved from DOI:10.5281/zenodo.2542919.

The RAM Legacy Stock Assessment Database is a compilation of stock assessment results for commercially exploited marine populations from around the world. It provides data on fish biomass, catch, fishing intensity and other indicators of stock status, used to evaluate the abundance and exploitation of fish populations.

Retrieved on
October 30, 2024
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.
Ricard, D., Minto, C., Jensen, O.P. and Baum, J.K. (2012) Evaluating the knowledge base and status of commercially exploited marine species with the RAM Legacy Stock Assessment Database. Fish and Fisheries 13 (4) 380-398. DOI: 10.1111/j.1467-2979.2011.00435.x
RAM Legacy Stock Assessment Database. 2018. Version 4.44-assessment-only. Released 2018-12-22. Retrieved from DOI:10.5281/zenodo.2542919.

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
Notes on our processing step for this indicator

We use the data as published by the RAM Legacy Stock Assessment Database, with no further transformations beyond renaming the entity column to "country" so it fits Our World in Data's standard schema. Each entity is an individual fish stock, not a country.

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: Fish stocks relative to the maximum sustainable yield”, part of the following publication: Hannah Ritchie and Max Roser (2021) - “Fish and Overfishing”. Data adapted from RAM Legacy Stock Assessment Database. Retrieved from https://archive.ourworldindata.org/20261111-180934/grapher/fish-stocks.html [online resource] (archived on November 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 (2018) – processed by Our World in Data

Full citation

RAM Legacy Stock Assessment Database (2018) – processed by Our World in Data. “Fish stocks relative to the maximum sustainable yield” [dataset]. RAM Legacy Stock Assessment Database, “Fish stocks (RAM Legacy Stock Assessment Database)” [original data]. Retrieved November 11, 2026 from https://archive.ourworldindata.org/20261111-180934/grapher/fish-stocks.html (archived on November 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.

Download full data

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-stocks.csv?v=1&csvType=full&useColumnShortNames=false&metric=fish_stocks_biomass&total_or_relative=relative_to_max_sustainable_yield
Metadata URL (JSON format)
https://ourworldindata.org/grapher/fish-stocks.metadata.json?v=1&csvType=full&useColumnShortNames=false&metric=fish_stocks_biomass&total_or_relative=relative_to_max_sustainable_yield

Code examples

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

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

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

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

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

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