Temporal and Spatial Changes and Trend Predictions of Forest Carbon Sequestration Efficiency in China Based on the Carbon Neutrality Goal
Forestry’s high-quality development is crucial for China’s sustainable ecological, economic, and social progress. To elevate the efficiency of carbon sequestration in forestry, continuously improve the increment of carbon sinks, and contribute to achieving carbon neutrality, it is crucial to accurat...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-12-01
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| Series: | Forests |
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| Online Access: | https://www.mdpi.com/1999-4907/14/12/2387 |
| _version_ | 1797381082683801600 |
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| author | Sixue Zhao Wei Shi Fuwei Qiao Chengyuan Wang Yi An Luyao Zhang |
| author_facet | Sixue Zhao Wei Shi Fuwei Qiao Chengyuan Wang Yi An Luyao Zhang |
| author_sort | Sixue Zhao |
| collection | DOAJ |
| description | Forestry’s high-quality development is crucial for China’s sustainable ecological, economic, and social progress. To elevate the efficiency of carbon sequestration in forestry, continuously improve the increment of carbon sinks, and contribute to achieving carbon neutrality, it is crucial to accurately assess the level of carbon sequestration efficiency in China’s forestry and explore its long-term evolution trend. In this paper, a super-efficiency SBM model, which combines the SBM model with the super-efficiency method and considers the relaxation variables, was selected to evaluate the forestry carbon sequestration efficiency of 31 provinces in China; likewise, the temporal development features of the efficacy of Chinese forests in sequestering carbon were examined using the nuclear density estimation method. Secondly, the study constructed traditional and spatial Markov probability transfer matrices to further explore the spatiotemporal evolution of carbon sequestration efficiency within Chinese forestry. Finally, combined with the Markov chain infinite distribution matrix, the future trajectory of carbon sequestration efficiency in China’s forestry was scientifically forecasted. The findings indicate that: (1) The average carbon sequestration efficiency of forestry in China showed a stable increase with fluctuations and reached the optimal state in 2018. The carbon sequestration efficiency level of various forest regions was always portrayed as southwest forest region > southern forest region > northeast forest region > northern forest region. From 2003 to 2018, there were significant differences in forestry carbon sequestration efficiency among provinces. The distribution of forestry carbon sequestration efficiency exhibited a “three-pillar” distribution pattern with Xizang, Zhejiang, and Heilongjiang as the core, and the marginal regions continuously promoted the carbon sequestration efficiency to the inland. (2) The type of transfer of forestry carbon sequestration efficiency in China is stable, and it is difficult to achieve cross-stage transfer in the short term. Moreover, the forestry carbon sequestration efficiency of each province tended to converge to a high (low) level over time, showing a “bimodal distribution” of low efficiency and high efficiency, indicating the existence of the obvious “club convergence phenomenon”. (3) Forecasting from a long-term evolution trend perspective, the outlook for the future evolution of forestry carbon sequestration efficiency in China is optimistic, and the overall trend was concentrated in the high-value area. Therefore, future forestry development in China should contemplate both internal structure optimization and coordinated regional development. Attention should be placed on forestry carbon sequestration’s role while considering the distinctive endowments of each region and developing reasonable, differentiated, and collaborative forestry management strategies. |
| first_indexed | 2024-03-08T20:46:10Z |
| format | Article |
| id | doaj.art-dccd02807d414e24be1745b8dcfd7978 |
| institution | Directory Open Access Journal |
| issn | 1999-4907 |
| language | English |
| last_indexed | 2024-03-08T20:46:10Z |
| publishDate | 2023-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Forests |
| spelling | doaj.art-dccd02807d414e24be1745b8dcfd79782023-12-22T14:09:36ZengMDPI AGForests1999-49072023-12-011412238710.3390/f14122387Temporal and Spatial Changes and Trend Predictions of Forest Carbon Sequestration Efficiency in China Based on the Carbon Neutrality GoalSixue Zhao0Wei Shi1Fuwei Qiao2Chengyuan Wang3Yi An4Luyao Zhang5College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730030, ChinaCollege of Geography and Environmental Science, Northwest Normal University, Lanzhou 730030, ChinaSchool of Economics, Northwest Normal University, Lanzhou 730070, ChinaGansu Ecological Environment Science Design and Research Institute, Lanzhou 730022, ChinaCollege of Geography and Environmental Science, Northwest Normal University, Lanzhou 730030, ChinaCollege of Geography and Environmental Science, Northwest Normal University, Lanzhou 730030, ChinaForestry’s high-quality development is crucial for China’s sustainable ecological, economic, and social progress. To elevate the efficiency of carbon sequestration in forestry, continuously improve the increment of carbon sinks, and contribute to achieving carbon neutrality, it is crucial to accurately assess the level of carbon sequestration efficiency in China’s forestry and explore its long-term evolution trend. In this paper, a super-efficiency SBM model, which combines the SBM model with the super-efficiency method and considers the relaxation variables, was selected to evaluate the forestry carbon sequestration efficiency of 31 provinces in China; likewise, the temporal development features of the efficacy of Chinese forests in sequestering carbon were examined using the nuclear density estimation method. Secondly, the study constructed traditional and spatial Markov probability transfer matrices to further explore the spatiotemporal evolution of carbon sequestration efficiency within Chinese forestry. Finally, combined with the Markov chain infinite distribution matrix, the future trajectory of carbon sequestration efficiency in China’s forestry was scientifically forecasted. The findings indicate that: (1) The average carbon sequestration efficiency of forestry in China showed a stable increase with fluctuations and reached the optimal state in 2018. The carbon sequestration efficiency level of various forest regions was always portrayed as southwest forest region > southern forest region > northeast forest region > northern forest region. From 2003 to 2018, there were significant differences in forestry carbon sequestration efficiency among provinces. The distribution of forestry carbon sequestration efficiency exhibited a “three-pillar” distribution pattern with Xizang, Zhejiang, and Heilongjiang as the core, and the marginal regions continuously promoted the carbon sequestration efficiency to the inland. (2) The type of transfer of forestry carbon sequestration efficiency in China is stable, and it is difficult to achieve cross-stage transfer in the short term. Moreover, the forestry carbon sequestration efficiency of each province tended to converge to a high (low) level over time, showing a “bimodal distribution” of low efficiency and high efficiency, indicating the existence of the obvious “club convergence phenomenon”. (3) Forecasting from a long-term evolution trend perspective, the outlook for the future evolution of forestry carbon sequestration efficiency in China is optimistic, and the overall trend was concentrated in the high-value area. Therefore, future forestry development in China should contemplate both internal structure optimization and coordinated regional development. Attention should be placed on forestry carbon sequestration’s role while considering the distinctive endowments of each region and developing reasonable, differentiated, and collaborative forestry management strategies.https://www.mdpi.com/1999-4907/14/12/2387forestrycarbon sequestration efficiencysuper efficiency SBMspatial Markov chain modeltrend forecasting |
| spellingShingle | Sixue Zhao Wei Shi Fuwei Qiao Chengyuan Wang Yi An Luyao Zhang Temporal and Spatial Changes and Trend Predictions of Forest Carbon Sequestration Efficiency in China Based on the Carbon Neutrality Goal Forests forestry carbon sequestration efficiency super efficiency SBM spatial Markov chain model trend forecasting |
| title | Temporal and Spatial Changes and Trend Predictions of Forest Carbon Sequestration Efficiency in China Based on the Carbon Neutrality Goal |
| title_full | Temporal and Spatial Changes and Trend Predictions of Forest Carbon Sequestration Efficiency in China Based on the Carbon Neutrality Goal |
| title_fullStr | Temporal and Spatial Changes and Trend Predictions of Forest Carbon Sequestration Efficiency in China Based on the Carbon Neutrality Goal |
| title_full_unstemmed | Temporal and Spatial Changes and Trend Predictions of Forest Carbon Sequestration Efficiency in China Based on the Carbon Neutrality Goal |
| title_short | Temporal and Spatial Changes and Trend Predictions of Forest Carbon Sequestration Efficiency in China Based on the Carbon Neutrality Goal |
| title_sort | temporal and spatial changes and trend predictions of forest carbon sequestration efficiency in china based on the carbon neutrality goal |
| topic | forestry carbon sequestration efficiency super efficiency SBM spatial Markov chain model trend forecasting |
| url | https://www.mdpi.com/1999-4907/14/12/2387 |
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