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中国遵义碳储量对土地利用变化的响应及多情景预测

Response of carbon storage to land use change and multi-scenario predictions in Zunyi, China.

作者信息

Liu Yi, Mei Xuemeng, Yue Li, Zhang Mingming

机构信息

College of Forestry, Guizhou University, Guiyang, 550025, Guizhou, China.

Research Center for Biodiversity and Nature Conservation, Guizhou University, Guiyang, China.

出版信息

Sci Rep. 2025 Jan 2;15(1):236. doi: 10.1038/s41598-024-81444-5.

DOI:10.1038/s41598-024-81444-5
PMID:39747253
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11696291/
Abstract

Evaluating and predicting how carbon storage (CS) is impacted by land use change can enable optimizing of future spatial layouts and coordinate land use and ecosystem services. This paper explores the changes in and driving factors of Zunyi CS from 2000 to 2020, predicts the changes in CS under different development scenarios, and determines the optimal development scenario. Woodland and farmland are the main land use types in Zunyi. Land use change was reflected mainly in the mutual conversion among woodland, farmland, and grassland and by their conversion to construction land and water. In 2000, 2010, and 2020, the CS in Zunyi was 658.77 × 10^6 t, 661.44 × 10^6 t, and 658.35 × 10^6 t, respectively. Woodland, farmland and grassland conversions to construction land and water were primarily responsible for CS loss. The normalized difference vegetation index (NDVI) is the main factor influencing the pattern of CS (q > 10%). Furthermore, the impacts of the human footprint index and population density are increasing. In 2030, the CS of Zunyi is trending downward. Under the ecological-farmland conservation scenario (ECS), the CS is estimated to be 656.67 × 10^6 t, with the smallest decrease (- 0.26%) among timepoints. The effective control of woodland and farmland weakens the trend of CS reduction.

摘要

评估和预测碳储量(CS)如何受到土地利用变化的影响,有助于优化未来的空间布局,并协调土地利用与生态系统服务。本文探讨了2000年至2020年遵义市碳储量的变化及驱动因素,预测了不同发展情景下碳储量的变化,并确定了最优发展情景。林地和农田是遵义市主要的土地利用类型。土地利用变化主要体现在林地、农田和草地之间的相互转换以及它们向建设用地和水域的转换。2000年、2010年和2020年,遵义市的碳储量分别为658.77×10^6吨、661.44×10^6吨和658.35×10^6吨。林地、农田和草地向建设用地和水域的转换是碳储量损失的主要原因。归一化植被指数(NDVI)是影响碳储量格局的主要因素(q>10%)。此外,人类足迹指数和人口密度的影响正在增加。到2030年,遵义市的碳储量呈下降趋势。在生态农田保护情景(ECS)下,碳储量预计为656.67×10^6吨,是各时间点中下降幅度最小的(-0.26%)。对林地和农田的有效控制减弱了碳储量减少的趋势。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d474/11696291/3dfd8317f651/41598_2024_81444_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d474/11696291/56280bf8e443/41598_2024_81444_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d474/11696291/c424fdb3ba43/41598_2024_81444_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d474/11696291/f55adc4718be/41598_2024_81444_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d474/11696291/cc6ca3b9e4aa/41598_2024_81444_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d474/11696291/3dfd8317f651/41598_2024_81444_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d474/11696291/56280bf8e443/41598_2024_81444_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d474/11696291/9cdb5fadf24a/41598_2024_81444_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d474/11696291/51c6bd902567/41598_2024_81444_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d474/11696291/a073b39c462e/41598_2024_81444_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d474/11696291/8ebb34700054/41598_2024_81444_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d474/11696291/c424fdb3ba43/41598_2024_81444_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d474/11696291/f55adc4718be/41598_2024_81444_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d474/11696291/cc6ca3b9e4aa/41598_2024_81444_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d474/11696291/3dfd8317f651/41598_2024_81444_Fig9_HTML.jpg

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