Ren Yuexiao, Zhang Leyi, Li Xia, Zhang Guozhuang, Li Yile, Lian Zhiyang
School of Land Engineering, Chang'an University, Xi'an, 710064, China.
School of Water and Environment, Chang'an University, Xi'an, 710064, China; Key Laboratory of Subsurface Hydrology and Ecological Effect in Arid Region of Ministry of Education, Chang'an University, Xi'an, 710064, China; Key Laboratory of Ecohydrology and Water-Security in Arid and Semi-arid Regions of Ministry of Water Resources, Chang'an University, Xi'an, 710064, China.
J Environ Manage. 2025 Aug;389:126123. doi: 10.1016/j.jenvman.2025.126123. Epub 2025 Jun 13.
Against the backdrop of global climate change and rapid socioeconomic advancement, significant land use/cover changes(LUCC) in Central Asia have profoundly impacted terrestrial ecosystem carbon storage(CS). However, the assessment and spatiotemporal dynamics of CS in Central Asia remain inadequately understood. This study systematically examined the spatiotemporal dynamics of LUCC and CS in Central Asia from 1990 to 2020, and anticipated CS in 2030 under 3 SSP-RCP scenarios using an combined structure consisting of the land use harmonization 2(LUH2) dataset, the patch-generating land use simulation(PLUS) model, and the integrated valuation of ecosystem services and tradeoffs(InVEST) model. Additionally, the extreme gradient boosting(XGBoost) model-Shapley(SHAP) values was employed to identify the elements impacting geographical distinction of CS. The findings show the following: (1)there was a net rise of 0.02 Pg in total CS in Central Asia between 1990 and 2020. From 1990 to 2010, extensive deforestation and urban sprawl led to a 0.1 Pg reduction in CS. However, post-2010, forest regeneration and large-scale conversion of unused land to grassland contributed to a 0.13 Pg increase in CS. (2)Between 2020 and 2030, forest expansion under the SSP126 and SSP245 scenarios is projected to enhance total CS by 0.03 %(0.01 Pg) and 0.17 %(0.08 Pg), respectively. Conversely, under the SSP585 scenario, substantial declines in both forestland and grassland are expected to result in a pronounced 1.67 % loss in CS. Moreover, while grassland undergoes a notable reduction under SSP126(-1.82 %), it experiences a expansion under SSP245(0.06 %). Consequently, the total CS exhibits a more substantial increase under SSP245 than under SSP126, SSP245 scenario is more favorable for enhancing CS in Central Asia. (3)Soil temperature(ST) is the most critical factor impacting the spatial heterogeneity of CS in Central Asia, followed by the normalized difference vegetation index(NDVI). This study explores a suitable path for Central Asian countries to optimize land use planning, increase ecosystem CS and achieve sustainable development, and also provides a reference for arid and semi-arid regions to enhance their carbon sequestration capacity.
在全球气候变化和社会经济快速发展的背景下，中亚地区显著的土地利用/覆盖变化（LUCC）对陆地生态系统碳储量（CS）产生了深远影响。然而，中亚地区碳储量的评估及其时空动态仍未得到充分了解。本研究系统地考察了1990年至2020年中亚地区LUCC和CS的时空动态，并使用由土地利用协调2（LUH2）数据集、斑块生成土地利用模拟（PLUS）模型和生态系统服务与权衡综合评估（InVEST）模型组成的组合结构，预测了2030年在3种共享社会经济路径-代表性浓度路径（SSP-RCP）情景下的碳储量。此外，采用极端梯度提升（XGBoost）模型-夏普利（SHAP）值来识别影响碳储量地理差异的因素。研究结果表明：（1）1990年至2020年期间，中亚地区的总碳储量净增加了0.02Pg。1990年至2010年，大规模森林砍伐和城市扩张导致碳储量减少了0.1Pg。然而，2010年后，森林再生以及未利用土地大规模转变为草地使碳储量增加了0.13Pg。（2）2020年至2030年期间，预计在SSP1-2.6和SSP2-4.5情景下森林扩张将分别使总碳储量增加0.03%（0.01Pg）和0.17%（0.08Pg）。相反，在SSP5-8.5情景下，林地和草地的大幅减少预计将导致碳储量显著损失1.67%。此外，虽然草地在SSP1-2.6情景下显著减少（-1.82%），但在SSP2-4.5情景下却有所扩张（0.06%）。因此，SSP2-4.5情景下的总碳储量增加幅度比SSP1-2.6情景下更大，SSP2-4.5情景更有利于提高中亚地区的碳储量。（3）土壤温度（ST）是影响中亚地区碳储量空间异质性的最关键因素，其次是归一化植被指数（NDVI）。本研究探索了中亚国家优化土地利用规划、增加生态系统碳储量并实现可持续发展的合适路径，也为干旱和半干旱地区提高其碳固存能力提供了参考。
