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基于PLUS-InVEST模型的长江上游流域退耕还林工程对碳储量的影响

The impact of the Grain-for-Green Programme on carbon storage in the Upper Yangtze River Basin based on the PLUS-InVEST model.

作者信息

Peng Minghong, Yang Ye, Deng Yuanjie, Jize Dingdi, Chen Hang, Hai Yifeng, Liu Guojie, Wang Haijun, Xie Tianhui, Li Hu, Luo Ji

机构信息

School of Economics, Sichuan University of Science & Engineering, Zigong, 643000, PR China.

State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, (Chengdu University of Technology), Chengdu, Sichuan, 610059, China.

出版信息

Carbon Balance Manag. 2025 Jul 30;20(1):24. doi: 10.1186/s13021-025-00315-2.

DOI:10.1186/s13021-025-00315-2
PMID:40739445
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12312590/
Abstract

Alterations in land use and land cover (LUCC) play a fundamental role in influencing the variability of ecosystem carbon storage. Evaluating how land use dynamics affect carbon sequestration and projecting future carbon storage scenarios are essential steps toward meeting China's dual carbon objectives. In this study, we integrated the Patch-generating Land Use Simulation (PLUS) model with the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) framework to investigate LUCC dynamics and their implications for carbon storage across the Upper Yangtze River Basin (UYRB) between 2000 and 2020. Furthermore, projections of regional carbon storage were made under multiple Grain-for-Green Programme (GFGP) scenarios extending to the year 2040. Our findings indicated that cultivated land (CL), forest land (FL), and grassland (GL) consistently dominated land use composition within the UYRB, collectively occupying approximately 96.45% of the total area throughout 2000-2020. During this period, construction land (CSL) steadily expanded, primarily at the expense of CL. Both CL and GL experienced substantial reductions. Spatially, carbon storage exhibited a decreasing gradient from east to west, with the Jinsha River Basin exhibiting the greatest levels. Carbon storage values over the two decades were recorded at 6.387 × 10¹⁰ t in 2000, 6.382 × 10¹⁰ t in 2005, 6.379 × 10¹⁰ t in 2010, 6.369 × 10¹⁰ t in 2015, and 6.373 × 10¹⁰ t in 2020. Despite a slight recovery between 2015 and 2020, total carbon storage fell by 0.23% (1.438 × 10 t) overall. This decline was primarily driven by the conversion of high-carbon-density CL and FL into low-carbon-density CSL and GL. Future projections show distinct disparities across four policy scenarios by 2040. Under the Natural Development Scenario (NDS), rapid economic growth and land conversion are projected to result in a carbon storage loss of 1.324 × 10 t. Conversely, the mild, moderate, and strong GFGPS anticipate carbon storage increases of 1.385 × 10⁸ t, 3.157 × 10⁸ t, and 5.136 × 10⁸ t, respectively. The Jialing River Basin shows the highest gains under all GFGPS. Our findings underscore the significance of the GFGP in enhancing regional carbon sequestration, primarily through encouraging afforestation of previously CL and GL and curbing the expansion of CSL. Such insights can guide land-use planning and ecological conservation strategies in the UYRB moving forward.

摘要

土地利用和土地覆盖变化(LUCC)在影响生态系统碳储量变化方面起着根本性作用。评估土地利用动态如何影响碳固存并预测未来碳储存情景是实现中国双碳目标的关键步骤。在本研究中,我们将斑块生成土地利用模拟(PLUS)模型与生态系统服务和权衡综合评估(InVEST)框架相结合,以研究2000年至2020年长江上游流域(UYRB)的LUCC动态及其对碳储存的影响。此外,还对延伸至2040年的多个退耕还林还草计划(GFGP)情景下的区域碳储存进行了预测。我们的研究结果表明,耕地(CL)、林地(FL)和草地(GL)在UYRB的土地利用构成中一直占据主导地位,在2000 - 2020年期间共占总面积的约96.45%。在此期间,建设用地(CSL)稳步扩张,主要以牺牲CL为代价。CL和GL都经历了大幅减少。在空间上,碳储量呈现出从东到西的递减梯度,金沙江流域的碳储量水平最高。二十年间的碳储量值分别为2000年6.387×10¹⁰吨、2005年6.382×10¹⁰吨、2010年6.379×10¹⁰吨、2015年6.369×10¹⁰吨和2020年6.373×10¹⁰吨。尽管在2015年至2020年之间略有恢复,但总体碳储量仍下降了0.23%(1.438×10吨)。这种下降主要是由于高碳密度的CL和FL转变为低碳密度的CSL和GL。未来预测显示,到2040年,四种政策情景存在明显差异。在自然发展情景(NDS)下,预计经济快速增长和土地转换将导致碳储存损失1.324×10吨。相反,轻度、中度和重度GFGP情景预计碳储存分别增加1.385×10⁸吨、3.157×10⁸吨和5.136×10⁸吨。嘉陵江流域在所有GFGP情景下的碳储存增加量最高。我们的研究结果强调了GFGP在增强区域碳固存方面的重要性,主要是通过鼓励对以前的CL和GL进行造林以及抑制CSL的扩张。这些见解可为未来UYRB的土地利用规划和生态保护策略提供指导。

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