Spatiotemporal Evolution and Prediction of Ecosystem Carbon Storage in the Yiluo River Basin Based on the PLUS-InVEST Model

IF 2.4 2区 农林科学 Q1 FORESTRY Forests Pub Date : 2023-12-14 DOI:10.3390/f14122442
Lei Li, Guangxing Ji, Qingsong Li, Jincai Zhang, Huishan Gao, Mengya Jia, Meng Li, Genming Li
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Abstract

Land-use change has a great impact on regional ecosystem balance and carbon storage, so it is of great significance to study future land-use types and carbon storage in a region to optimize the regional land-use structure. Based on the existing land-use data and the different scenarios of the shared socioeconomic pathway and the representative concentration pathway (SSP-RCP) provided by CMIP6, this study used the PLUS model to predict future land use and the InVEST model to predict the carbon storage in the study area in the historical period and under different scenarios in the future. The results show the following: (1) The change in land use will lead to a change in carbon storage. From 2000 to 2020, the conversion of cultivated land to construction land was the main transfer type, which was also an important reason for the decrease in regional carbon storage. (2) Under the three scenarios, the SSP126 scenario has the smallest share of arable land area, while this scenario has the largest share of woodland and grassland land area, and none of the three scenarios shows a significant decrease in woodland area. (3) From 2020 to 2050, the carbon stocks in the study area under the three scenarios, SSP126, SSP245, and SSP585, all show different degrees of decline, decreasing to 36,405.0204 × 104 t, 36,251.4402 × 104 t, and 36,190.4066 × 104 t, respectively. Restricting the conversion of land with a high carbon storage capacity to land with a low carbon storage capacity is conducive to the benign development of regional carbon storage. This study can provide a reference for the adjustment and management of future land-use structures in the region.
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基于 PLUS-InVEST 模型的伊洛河流域生态系统碳储量时空演变与预测
土地利用变化对区域生态系统平衡和碳储存具有重要影响,因此研究区域未来土地利用类型和碳储存对优化区域土地利用结构具有重要意义。本研究基于现有土地利用数据和 CMIP6 提供的共享社会经济路径和代表性浓度路径(SSP-RCP)的不同情景,利用 PLUS 模型预测了研究区未来土地利用情况,并利用 InVEST 模型预测了研究区历史时期和未来不同情景下的碳储量。结果表明(1)土地利用的变化将导致碳储存的变化。从 2000 年到 2020 年,耕地转为建设用地是主要的转移类型,也是区域碳储量减少的重要原因。(2)三种情景下,SSP126 情景下耕地面积所占比例最小,而该情景下林地和草地面积所占比例最大,三种情景下林地面积均未出现明显减少。(3)2020-2050 年,SSP126、SSP245 和 SSP585 三种情景下研究区的碳储量均有不同程度的下降,分别降至 36 405.0204×104 t、36 251.4402×104 t 和 36 190.4066×104 t。限制高碳储量土地向低碳储量土地转化,有利于区域碳储量的良性发展。本研究可为该地区未来土地利用结构的调整和管理提供参考。
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来源期刊
Forests
Forests FORESTRY-
CiteScore
4.40
自引率
17.20%
发文量
1823
审稿时长
19.02 days
期刊介绍: Forests (ISSN 1999-4907) is an international and cross-disciplinary scholarly journal of forestry and forest ecology. It publishes research papers, short communications and review papers. There is no restriction on the length of the papers. Our aim is to encourage scientists to publish their experimental and theoretical research in as much detail as possible. Full experimental and/or methodical details must be provided for research articles.
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