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Risk analysis of maize yield losses in mainland China at the county level
Food security in China is under additional stress due to climate change. The risk analysis of maize yield losses is crucial for sustainable agricultural production and climate change impact assessment. It is difficult to quantify this risk because of the constraints on the high-resolution data avail...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7326987/ https://www.ncbi.nlm.nih.gov/pubmed/32606437 http://dx.doi.org/10.1038/s41598-020-67763-3 |
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author | Li, Xuan Fang, Shibo Wu, Dong Zhu, Yongchao Wu, Yingjie |
author_facet | Li, Xuan Fang, Shibo Wu, Dong Zhu, Yongchao Wu, Yingjie |
author_sort | Li, Xuan |
collection | PubMed |
description | Food security in China is under additional stress due to climate change. The risk analysis of maize yield losses is crucial for sustainable agricultural production and climate change impact assessment. It is difficult to quantify this risk because of the constraints on the high-resolution data available. Moreover, the current results lack spatial comparability due to the area effect. These challenges were addressed by using long-term county-level maize yield and planting area data from 1981 to 2010. We analyzed the spatial distribution of maize yield loss risks in mainland China. A new comprehensive yield loss risk index was established by combining the reduction rate, coefficient of variation, and probability of yield reduction after removing the area effect. A total of 823 counties were divided into areas of lowest, low, moderate, high, and highest risk. High risk in maize production occurred in Heilongjiang and Jilin Provinces, the eastern part of Inner Mongolia, the eastern part of Gansu-Xinjiang, west of the Loess Plateau, and the western part of the Xinjiang Uygur Autonomous Region. Most counties in Northeast China were at high risk, while the Loess Plateau, middle and lower reaches of the Yangtze River and Gansu-Xinjiang were at low risk. |
format | Online Article Text |
id | pubmed-7326987 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-73269872020-07-01 Risk analysis of maize yield losses in mainland China at the county level Li, Xuan Fang, Shibo Wu, Dong Zhu, Yongchao Wu, Yingjie Sci Rep Article Food security in China is under additional stress due to climate change. The risk analysis of maize yield losses is crucial for sustainable agricultural production and climate change impact assessment. It is difficult to quantify this risk because of the constraints on the high-resolution data available. Moreover, the current results lack spatial comparability due to the area effect. These challenges were addressed by using long-term county-level maize yield and planting area data from 1981 to 2010. We analyzed the spatial distribution of maize yield loss risks in mainland China. A new comprehensive yield loss risk index was established by combining the reduction rate, coefficient of variation, and probability of yield reduction after removing the area effect. A total of 823 counties were divided into areas of lowest, low, moderate, high, and highest risk. High risk in maize production occurred in Heilongjiang and Jilin Provinces, the eastern part of Inner Mongolia, the eastern part of Gansu-Xinjiang, west of the Loess Plateau, and the western part of the Xinjiang Uygur Autonomous Region. Most counties in Northeast China were at high risk, while the Loess Plateau, middle and lower reaches of the Yangtze River and Gansu-Xinjiang were at low risk. Nature Publishing Group UK 2020-06-30 /pmc/articles/PMC7326987/ /pubmed/32606437 http://dx.doi.org/10.1038/s41598-020-67763-3 Text en © The Author(s) 2020 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/. |
spellingShingle | Article Li, Xuan Fang, Shibo Wu, Dong Zhu, Yongchao Wu, Yingjie Risk analysis of maize yield losses in mainland China at the county level |
title | Risk analysis of maize yield losses in mainland China at the county level |
title_full | Risk analysis of maize yield losses in mainland China at the county level |
title_fullStr | Risk analysis of maize yield losses in mainland China at the county level |
title_full_unstemmed | Risk analysis of maize yield losses in mainland China at the county level |
title_short | Risk analysis of maize yield losses in mainland China at the county level |
title_sort | risk analysis of maize yield losses in mainland china at the county level |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7326987/ https://www.ncbi.nlm.nih.gov/pubmed/32606437 http://dx.doi.org/10.1038/s41598-020-67763-3 |
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