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Response of Wheat, Maize, and Rice to Changes in Temperature, Precipitation, CO(2) Concentration, and Uncertainty Based on Crop Simulation Approaches
The influence of global climate change on agricultural productivity is an essential issue of ongoing concern. The growth and development of wheat, maize, and rice are influenced by elevated atmospheric CO(2) concentrations, increased temperatures, and seasonal rainfall patterns. However, due to diff...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10385928/ https://www.ncbi.nlm.nih.gov/pubmed/37514323 http://dx.doi.org/10.3390/plants12142709 |
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author | Qin, Mengting Zheng, Ennan Hou, Dingmu Meng, Xuanchen Meng, Fanxiang Gao, Yu Chen, Peng Qi, Zhijuan Xu, Tianyu |
author_facet | Qin, Mengting Zheng, Ennan Hou, Dingmu Meng, Xuanchen Meng, Fanxiang Gao, Yu Chen, Peng Qi, Zhijuan Xu, Tianyu |
author_sort | Qin, Mengting |
collection | PubMed |
description | The influence of global climate change on agricultural productivity is an essential issue of ongoing concern. The growth and development of wheat, maize, and rice are influenced by elevated atmospheric CO(2) concentrations, increased temperatures, and seasonal rainfall patterns. However, due to differences in research methodologies (e.g., crop models, climate models, and climate scenarios), there is uncertainty in the existing studies regarding the magnitude and direction of future climate change impacts on crop yields. In order to completely assess the possible consequences of climate change and adaptation measures on crop production and to analyze the associated uncertainties, a database of future crop yield changes was developed using 68 published studies (including 1842 samples). A local polynomial approach was used with the full dataset to investigate the response of crop yield changes to variations in maximum and minimum temperatures, mean temperature, precipitation, and CO(2) concentrations. Then, a linear mixed-effects regression model was utilized with the limited dataset to explore the quantitative relationships between them. It was found that maximum temperature, precipitation, adaptation measure, study area, and climate model had significant effects on changes in crop yield. Crop yield will decline by 4.21% for each 1 °C rise in maximum temperature and increase by 0.43% for each 1% rise in precipitation. While higher CO(2) concentrations and suitable management strategies could mitigate the negative effects of warming temperatures, crop yield with adaptation measures increased by 64.09% compared to crop yield without adaptation measures. Moreover, the uncertainty of simulations can be decreased by using numerous climate models. The results may be utilized to guide policy regarding the influence of climate change and to promote the creation of adaptation plans that will increase crop systems’ resilience in the future. |
format | Online Article Text |
id | pubmed-10385928 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-103859282023-07-30 Response of Wheat, Maize, and Rice to Changes in Temperature, Precipitation, CO(2) Concentration, and Uncertainty Based on Crop Simulation Approaches Qin, Mengting Zheng, Ennan Hou, Dingmu Meng, Xuanchen Meng, Fanxiang Gao, Yu Chen, Peng Qi, Zhijuan Xu, Tianyu Plants (Basel) Review The influence of global climate change on agricultural productivity is an essential issue of ongoing concern. The growth and development of wheat, maize, and rice are influenced by elevated atmospheric CO(2) concentrations, increased temperatures, and seasonal rainfall patterns. However, due to differences in research methodologies (e.g., crop models, climate models, and climate scenarios), there is uncertainty in the existing studies regarding the magnitude and direction of future climate change impacts on crop yields. In order to completely assess the possible consequences of climate change and adaptation measures on crop production and to analyze the associated uncertainties, a database of future crop yield changes was developed using 68 published studies (including 1842 samples). A local polynomial approach was used with the full dataset to investigate the response of crop yield changes to variations in maximum and minimum temperatures, mean temperature, precipitation, and CO(2) concentrations. Then, a linear mixed-effects regression model was utilized with the limited dataset to explore the quantitative relationships between them. It was found that maximum temperature, precipitation, adaptation measure, study area, and climate model had significant effects on changes in crop yield. Crop yield will decline by 4.21% for each 1 °C rise in maximum temperature and increase by 0.43% for each 1% rise in precipitation. While higher CO(2) concentrations and suitable management strategies could mitigate the negative effects of warming temperatures, crop yield with adaptation measures increased by 64.09% compared to crop yield without adaptation measures. Moreover, the uncertainty of simulations can be decreased by using numerous climate models. The results may be utilized to guide policy regarding the influence of climate change and to promote the creation of adaptation plans that will increase crop systems’ resilience in the future. MDPI 2023-07-20 /pmc/articles/PMC10385928/ /pubmed/37514323 http://dx.doi.org/10.3390/plants12142709 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Qin, Mengting Zheng, Ennan Hou, Dingmu Meng, Xuanchen Meng, Fanxiang Gao, Yu Chen, Peng Qi, Zhijuan Xu, Tianyu Response of Wheat, Maize, and Rice to Changes in Temperature, Precipitation, CO(2) Concentration, and Uncertainty Based on Crop Simulation Approaches |
title | Response of Wheat, Maize, and Rice to Changes in Temperature, Precipitation, CO(2) Concentration, and Uncertainty Based on Crop Simulation Approaches |
title_full | Response of Wheat, Maize, and Rice to Changes in Temperature, Precipitation, CO(2) Concentration, and Uncertainty Based on Crop Simulation Approaches |
title_fullStr | Response of Wheat, Maize, and Rice to Changes in Temperature, Precipitation, CO(2) Concentration, and Uncertainty Based on Crop Simulation Approaches |
title_full_unstemmed | Response of Wheat, Maize, and Rice to Changes in Temperature, Precipitation, CO(2) Concentration, and Uncertainty Based on Crop Simulation Approaches |
title_short | Response of Wheat, Maize, and Rice to Changes in Temperature, Precipitation, CO(2) Concentration, and Uncertainty Based on Crop Simulation Approaches |
title_sort | response of wheat, maize, and rice to changes in temperature, precipitation, co(2) concentration, and uncertainty based on crop simulation approaches |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10385928/ https://www.ncbi.nlm.nih.gov/pubmed/37514323 http://dx.doi.org/10.3390/plants12142709 |
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