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Data

Countries with more than 25 species at risk of losing more than 25% of their habitat by 2050

About this data

Source
Williams et al. (2021) – processed by Our World in Data
Last updated
January 1, 2021
Date range
2050–2050
Unit
species

Sources and processing

This data is based on the following sources

Williams et al. – Proactive conservation to prevent habitat losses to agricultural expansion

Projected species' habitat loss is projected to 2050 under a business-as-usual, plus five intervention scenarios with changes to diets or agricultural production.

Business-as-usual: This assumes population growth from UN medium projections; crop yield increases in line with historical rates of improvement; and dietary changes in line with projected rises in income.

Closing yield gaps: Yields increase linearly from current yields to 80% of the estimated maximum potential by 2050. Increasing yields above 80% is rarely achieved over large areas.

Halve food waste: consumer food waste and food losses in supply chains are reduced by 25% by 2030 and 50% by 2050.

Healthier diets: Diets transition to the EAT-Lancet diet which is in line with healthy calorie and nutritional requirements. For richer countries this would mean a reduction (but not elimination) of meat consumption. For poorer countries, this would mean an increase.

Optimize trade: agricultural production and trade is optimized to produce food in the locations with the least risk of habitat loss. Agricultural production shifts from the 25 countries projected to have the greatest mean losses of suitable habitat across all species to countries where less than 10% of species are threatened with extinction.

Combined: all four interventions are combined.

Retrieved on
April 10, 2025
Retrieved from
https://www.nature.com/articles/s41893-020-00656-5
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.
Williams, D. R., Clark, M., Buchanan, G. M., Ficetola, G. F., Rondinini, C., & Tilman, D. (2021). Proactive conservation to prevent habitat losses to agricultural expansion. Nature Sustainability, 4(4), 314-322.

Projected species' habitat loss is projected to 2050 under a business-as-usual, plus five intervention scenarios with changes to diets or agricultural production.

Business-as-usual: This assumes population growth from UN medium projections; crop yield increases in line with historical rates of improvement; and dietary changes in line with projected rises in income.

Closing yield gaps: Yields increase linearly from current yields to 80% of the estimated maximum potential by 2050. Increasing yields above 80% is rarely achieved over large areas.

Halve food waste: consumer food waste and food losses in supply chains are reduced by 25% by 2030 and 50% by 2050.

Healthier diets: Diets transition to the EAT-Lancet diet which is in line with healthy calorie and nutritional requirements. For richer countries this would mean a reduction (but not elimination) of meat consumption. For poorer countries, this would mean an increase.

Optimize trade: agricultural production and trade is optimized to produce food in the locations with the least risk of habitat loss. Agricultural production shifts from the 25 countries projected to have the greatest mean losses of suitable habitat across all species to countries where less than 10% of species are threatened with extinction.

Combined: all four interventions are combined.

Retrieved on
April 10, 2025
Retrieved from
https://www.nature.com/articles/s41893-020-00656-5
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.
Williams, D. R., Clark, M., Buchanan, G. M., Ficetola, G. F., Rondinini, C., & Tilman, D. (2021). Proactive conservation to prevent habitat losses to agricultural expansion. Nature Sustainability, 4(4), 314-322.

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.

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  • 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: Countries with more than 25 species at risk of losing more than 25% of their habitat by 2050”. Our World in Data (2026). Data adapted from Williams et al.. Retrieved from https://archive.ourworldindata.org/20260512-085513/grapher/habitat-loss-25-species.html [online resource] (archived on May 12, 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:

Williams et al. (2021) – processed by Our World in Data

Full citation

Williams et al. (2021) – processed by Our World in Data. “Countries with more than 25 species at risk of losing more than 25% of their habitat by 2050” [dataset]. Williams et al., “Proactive conservation to prevent habitat losses to agricultural expansion” [original data]. Retrieved May 17, 2026 from https://archive.ourworldindata.org/20260512-085513/grapher/habitat-loss-25-species.html (archived on May 12, 2026).

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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/habitat-loss-25-species.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://ourworldindata.org/grapher/habitat-loss-25-species.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/habitat-loss-25-species.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/habitat-loss-25-species.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/habitat-loss-25-species.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/habitat-loss-25-species.csv?v=1&csvType=full&useColumnShortNames=false")

# Fetch the metadata
metadata <- fromJSON("https://ourworldindata.org/grapher/habitat-loss-25-species.metadata.json?v=1&csvType=full&useColumnShortNames=false")
Stata
import delimited "https://ourworldindata.org/grapher/habitat-loss-25-species.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear