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A global dataset for the projected impacts of climate change on four major crops

Reliable estimates of the impacts of climate change on crop production are critical for assessing the sustainability of food systems. Global, regional, and site-specific crop simulation studies have been conducted for nearly four decades, representing valuable sources of information for climate chan...

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Autores principales: Hasegawa, Toshihiro, Wakatsuki, Hitomi, Ju, Hui, Vyas, Shalika, Nelson, Gerald C., Farrell, Aidan, Deryng, Delphine, Meza, Francisco, Makowski, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8850443/
https://www.ncbi.nlm.nih.gov/pubmed/35173186
http://dx.doi.org/10.1038/s41597-022-01150-7
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author Hasegawa, Toshihiro
Wakatsuki, Hitomi
Ju, Hui
Vyas, Shalika
Nelson, Gerald C.
Farrell, Aidan
Deryng, Delphine
Meza, Francisco
Makowski, David
author_facet Hasegawa, Toshihiro
Wakatsuki, Hitomi
Ju, Hui
Vyas, Shalika
Nelson, Gerald C.
Farrell, Aidan
Deryng, Delphine
Meza, Francisco
Makowski, David
author_sort Hasegawa, Toshihiro
collection PubMed
description Reliable estimates of the impacts of climate change on crop production are critical for assessing the sustainability of food systems. Global, regional, and site-specific crop simulation studies have been conducted for nearly four decades, representing valuable sources of information for climate change impact assessments. However, the wealth of data produced by these studies has not been made publicly available. Here, we develop a global dataset by consolidating previously published meta-analyses and data collected through a new literature search covering recent crop simulations. The new global dataset builds on 8703 simulations from 202 studies published between 1984 and 2020. It contains projected yields of four major crops (maize, rice, soybean, and wheat) in 91 countries under major emission scenarios for the 21st century, with and without adaptation measures, along with geographical coordinates, current temperature and precipitation levels, projected temperature and precipitation changes. This dataset provides a solid basis for a quantitative assessment of the impacts of climate change on crop production and will facilitate the rapidly developing data-driven machine learning applications.
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spelling pubmed-88504432022-03-04 A global dataset for the projected impacts of climate change on four major crops Hasegawa, Toshihiro Wakatsuki, Hitomi Ju, Hui Vyas, Shalika Nelson, Gerald C. Farrell, Aidan Deryng, Delphine Meza, Francisco Makowski, David Sci Data Data Descriptor Reliable estimates of the impacts of climate change on crop production are critical for assessing the sustainability of food systems. Global, regional, and site-specific crop simulation studies have been conducted for nearly four decades, representing valuable sources of information for climate change impact assessments. However, the wealth of data produced by these studies has not been made publicly available. Here, we develop a global dataset by consolidating previously published meta-analyses and data collected through a new literature search covering recent crop simulations. The new global dataset builds on 8703 simulations from 202 studies published between 1984 and 2020. It contains projected yields of four major crops (maize, rice, soybean, and wheat) in 91 countries under major emission scenarios for the 21st century, with and without adaptation measures, along with geographical coordinates, current temperature and precipitation levels, projected temperature and precipitation changes. This dataset provides a solid basis for a quantitative assessment of the impacts of climate change on crop production and will facilitate the rapidly developing data-driven machine learning applications. Nature Publishing Group UK 2022-02-16 /pmc/articles/PMC8850443/ /pubmed/35173186 http://dx.doi.org/10.1038/s41597-022-01150-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) applies to the metadata files associated with this article.
spellingShingle Data Descriptor
Hasegawa, Toshihiro
Wakatsuki, Hitomi
Ju, Hui
Vyas, Shalika
Nelson, Gerald C.
Farrell, Aidan
Deryng, Delphine
Meza, Francisco
Makowski, David
A global dataset for the projected impacts of climate change on four major crops
title A global dataset for the projected impacts of climate change on four major crops
title_full A global dataset for the projected impacts of climate change on four major crops
title_fullStr A global dataset for the projected impacts of climate change on four major crops
title_full_unstemmed A global dataset for the projected impacts of climate change on four major crops
title_short A global dataset for the projected impacts of climate change on four major crops
title_sort global dataset for the projected impacts of climate change on four major crops
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8850443/
https://www.ncbi.nlm.nih.gov/pubmed/35173186
http://dx.doi.org/10.1038/s41597-022-01150-7
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