Coupling coordination between agricultural carbon emission efficiency and food security in China: The spatial-temporal evolution and prediction.
Addressing climate change and food insecurity is crucial for achieving the Sustainable Development Goals (SDGs), with the enhancement of Agricultural Carbon Emission Efficiency (ACEE) and the assurance of Food Security (FS) playing pivotal roles. This study conducts a comprehensive evaluation of the...
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Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0325026 |
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| author | Xixian Zheng Wenmei Liao |
| author_facet | Xixian Zheng Wenmei Liao |
| author_sort | Xixian Zheng |
| collection | DOAJ |
| description | Addressing climate change and food insecurity is crucial for achieving the Sustainable Development Goals (SDGs), with the enhancement of Agricultural Carbon Emission Efficiency (ACEE) and the assurance of Food Security (FS) playing pivotal roles. This study conducts a comprehensive evaluation of the coordination between ACEE and FS across 31 Chinese provinces from 2007 to 2021. The methodology employs the Super Slack-Based Model (SBM) and the Entropy- Weighted Technique for Order Preference by Similarity to Ideal Solution (EW-TOPSIS) for ACEE and FS assessments, respectively, while utilizing the Coupling Coordination Degree Model (CCDM) to gauge their coordination. This research applies Global spatial autocorrelation (GA), Local Indicators of Spatial Association (LISA) clustering, and Markov chain analysis to investigate the spatial correlation characteristics and dynamic evolutionary probability of Coupling Coordination Degree (CCD). Additionally, a Combination Forecasting Model predicts CCD trends through 2030. The findings indicate positive trends in both ACEE and FS, albeit with significant regional disparities and a notable lag of FS behind ACEE improvement. The evolution of China's CCD from "barely coordinated" towards "primary coordination" is evident, with the northeastern and central regions outperforming their western and eastern counterparts. Spatial analysis reveals pronounced clustering of CCD, indicating the impact of spatial spillover effects. Markov chain analysis shows that provinces have at least a 71.4% probability of maintaining their current CCD status, revealing substantial system inertia. Projections point to increasing CCD levels across various regions, with the northeastern region expected to reach 0.827 by 2030 (a 5.72% increase from 2021), followed by the central (0.742), western (0.659), and eastern regions (0.638); however, regional imbalances persist, highlighting the need for concentrated efforts in areas experiencing CCD stagnation or decline. The study concludes with a call for region-specific development strategies, enhanced resource allocation and technological support, and a comprehensive policy framework that accounts for the long-term and spatial dimensions, aiming to facilitate equitable advancements in reducing agricultural carbon emissions and enhancing food security. |
| format | Article |
| id | doaj-art-023de2ed2a774455a7e40271d4e0d668 |
| institution | OA Journals |
| issn | 1932-6203 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Public Library of Science (PLoS) |
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| series | PLoS ONE |
| spelling | doaj-art-023de2ed2a774455a7e40271d4e0d6682025-08-20T02:36:04ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01207e032502610.1371/journal.pone.0325026Coupling coordination between agricultural carbon emission efficiency and food security in China: The spatial-temporal evolution and prediction.Xixian ZhengWenmei LiaoAddressing climate change and food insecurity is crucial for achieving the Sustainable Development Goals (SDGs), with the enhancement of Agricultural Carbon Emission Efficiency (ACEE) and the assurance of Food Security (FS) playing pivotal roles. This study conducts a comprehensive evaluation of the coordination between ACEE and FS across 31 Chinese provinces from 2007 to 2021. The methodology employs the Super Slack-Based Model (SBM) and the Entropy- Weighted Technique for Order Preference by Similarity to Ideal Solution (EW-TOPSIS) for ACEE and FS assessments, respectively, while utilizing the Coupling Coordination Degree Model (CCDM) to gauge their coordination. This research applies Global spatial autocorrelation (GA), Local Indicators of Spatial Association (LISA) clustering, and Markov chain analysis to investigate the spatial correlation characteristics and dynamic evolutionary probability of Coupling Coordination Degree (CCD). Additionally, a Combination Forecasting Model predicts CCD trends through 2030. The findings indicate positive trends in both ACEE and FS, albeit with significant regional disparities and a notable lag of FS behind ACEE improvement. The evolution of China's CCD from "barely coordinated" towards "primary coordination" is evident, with the northeastern and central regions outperforming their western and eastern counterparts. Spatial analysis reveals pronounced clustering of CCD, indicating the impact of spatial spillover effects. Markov chain analysis shows that provinces have at least a 71.4% probability of maintaining their current CCD status, revealing substantial system inertia. Projections point to increasing CCD levels across various regions, with the northeastern region expected to reach 0.827 by 2030 (a 5.72% increase from 2021), followed by the central (0.742), western (0.659), and eastern regions (0.638); however, regional imbalances persist, highlighting the need for concentrated efforts in areas experiencing CCD stagnation or decline. The study concludes with a call for region-specific development strategies, enhanced resource allocation and technological support, and a comprehensive policy framework that accounts for the long-term and spatial dimensions, aiming to facilitate equitable advancements in reducing agricultural carbon emissions and enhancing food security.https://doi.org/10.1371/journal.pone.0325026 |
| spellingShingle | Xixian Zheng Wenmei Liao Coupling coordination between agricultural carbon emission efficiency and food security in China: The spatial-temporal evolution and prediction. PLoS ONE |
| title | Coupling coordination between agricultural carbon emission efficiency and food security in China: The spatial-temporal evolution and prediction. |
| title_full | Coupling coordination between agricultural carbon emission efficiency and food security in China: The spatial-temporal evolution and prediction. |
| title_fullStr | Coupling coordination between agricultural carbon emission efficiency and food security in China: The spatial-temporal evolution and prediction. |
| title_full_unstemmed | Coupling coordination between agricultural carbon emission efficiency and food security in China: The spatial-temporal evolution and prediction. |
| title_short | Coupling coordination between agricultural carbon emission efficiency and food security in China: The spatial-temporal evolution and prediction. |
| title_sort | coupling coordination between agricultural carbon emission efficiency and food security in china the spatial temporal evolution and prediction |
| url | https://doi.org/10.1371/journal.pone.0325026 |
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