川滇生态屏障区碳储量时空演变及驱动因素研究

Spatiotemporal evolution and driving factors of carbon storage in the Sichuan-Yunnan ecological barrier region

  • 摘要: 土壤理化性质是碳储量的重要驱动因素。作为中国西南边境地区的关键生态屏障区, 土壤理化性质对川滇生态屏障区碳储量的影响研究仍显不足。本研究耦合InVEST模型与最优参数地理探测器(OPGD)及多尺度地理加权回归(MGWR)模型, 基于多源数据集分析川滇生态屏障区2000—2020年碳储量的时空演变格局及其空间异质性驱动因素。研究结果表明: (1)研究期内碳储量整体呈降低趋势, 主要由低地河谷地区的城市扩张和农业开发导致, 但局部区域因森林扩张和退耕还林等生态工程实现增长; (2)归一化植被指数(NDVI)、有机质含量(OC)和高程(DEM)为主导因子, 解释力均超过50%; 多因子交互均为增强型, 最强交互对为NDVI ∩ OC, 揭示了生态-地形-土壤养分耦合机制在碳储量空间分布中的主导作用; (3)MGWR模型有效捕捉了驱动因子的空间异质性, 表明土壤理化性质显著影响碳储量的分布与转移格局。研究结果对川滇生态屏障区未来土地利用优化、生态治理和碳汇管理具有指导价值, 可为生态屏障区的碳储量可持续管理提供科学依据和新型分析框架, 对于缓解气候变化和促进区域生态保护具有重要意义。

     

    Abstract: Soil physicochemical properties serve as crucial driving factors for carbon storage. As a vital ecological barrier zone in China's southwestern border region, the Sichuan-Yunnan ecological barrier area has received limited research attention regarding the specific influence of soil physicochemical properties on carbon storage dynamics. This study integrates the InVEST model with the Optimal Parameters Geographical Detector (OPGD) and Multiscale Geographically Weighted Regression (MGWR) model, drawing on multi-source datasets—including land use/land cover data at 30 m resolution, soil properties at 1 km resolution, and climate variables—to systematically examine the spatiotemporal evolution patterns of carbon storage and the spatially heterogeneous driving factors in the Sichuan-Yunnan ecological barrier area from 2000 to 2020.The results reveal that: (1) Over the study period, total carbon storage exhibited an overall declining trend, primarily attributable to rapid urban expansion and intensive agricultural development in lowland river valley regions. These anthropogenic activities drove widespread conversion of woodland and grassland into construction land and cropland, resulting in substantial losses in aboveground and belowground biomass carbon pools, as well as accelerated soil organic carbon release due to tillage disturbance and erosion. In contrast, localized increases in carbon storage were observed in certain areas, largely benefiting from woodland expansion and large-scale ecological restoration projects such as the Grain for Green Program (returning farmland to forest), which enhanced vegetation cover, litter input, and soil organic matter accumulation. (2) Normalized Difference Vegetation Index (NDVI), soil organic matter content (OC), and elevation (DEM) emerged as the dominant driving factors, each accounting for explanatory power exceeding 50%. All multi-factor interactions were of the enhancement type, with the strongest synergistic effect observed between NDVI and OC (NDVI ∩ OC). This finding underscores the dominant role of the coupled ecology–terrain–soil nutrient mechanism in shaping the spatial distribution of carbon storage across the region. (3) The MGWR model successfully captured significant spatial heterogeneity in the effects of driving factors, confirming that soil physicochemical properties play a pivotal role in influencing both the distribution patterns and transfer processes of carbon storage, particularly in areas with strong topographic gradients. These findings provide practical guidance for future land-use optimization, ecological governance, and carbon sink management in the Sichuan-Yunnan ecological barrier area. By highlighting the central importance of soil properties, vegetation–soil interactions, and spatial heterogeneity, the study offers a scientific foundation and innovative multi-model analytical framework for sustainable carbon storage management in similar ecological barrier regions. Ultimately, the results contribute to climate change mitigation efforts, support enhanced regional ecological conservation, and promote ecosystem resilience under ongoing human and climatic pressures.

     

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