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[不同景观复合体中土壤有机碳的空间分异特征及驱动因素]

[Spatial Differentiation Characteristics and Driving Factors of Soil Organic Carbon in Various Landscape Complexes].

作者信息

Kong Chen-Chen, Yan Fang, Wang Wei-Rui, Zhang Shi-Wen, Guo Dan-Dan, Wang Shan

机构信息

School of Earth and Environment, Anhui University of Science & Technology, Huainan 232001, China.

Beijing Cultivated Land Construction and Protection Center, Beijing 100020, China.

出版信息

Huan Jing Ke Xue. 2025 Mar 8;46(3):1679-1689. doi: 10.13227/j.hjkx.202403253.

DOI:10.13227/j.hjkx.202403253
PMID:40113307
Abstract

Investigating the spatial differentiation characteristics of soil organic carbon (SOC) in regional agricultural land and analyzing its driving factors are important for screening auxiliary variables for SOC prediction in agricultural land and the accurate prediction of soil carbon stock. This study considered SOC in different types of agricultural land landscape complexes in Beijing as the research object. The differences in SOC content and its stock in different landscape complexes were explored based on the long-term positional monitoring data on the quality of cultivated land in Beijing and the field sampling and testing data. Utilizing multi-source and open-source data as environmental variables that affected SOC spatial differentiation, we explored the quantitative and spatial relationships between SOC and climate, topography, soil parent material, land use, and biomass factors in different landscape complexes through GeoDetector and geographically weighted regression modeling. Additionally, we constructed a structural equation model to reveal the pathways that influence each driving factor on SOC in terms of direct and indirect effects. Ultimately, the major controlling factors of SOC were identified in the study area. The results showed that: ① The mean values of (SOC) for various types of landscape complexes in the study area ranged from 6.23 to 28.26 g·kg, with a variation coefficient of 3.80% to 33.92%, showing spatial heterogeneity. ② Climate, topography, soil parent material, land type, and biomass factors contributed to SOC at highly significant levels ( < 0.01), and all factors were synergistic on SOC after their interaction. All factors could explain the spatial variation of SOC from 0.691 to 0.704, with stable explanatory validity. ③ Temperature, topography, and land type showed a highly significant direct effect ( < 0.01) on SOC in the study area. Among them, temperature was negatively correlated with SOC content. In different land types, SOC content was higher in landscape complexes located in forested land and lower in cultivated land. Topographic factors had the most excellent direct effect on SOC (effect value = 0.698, < 0.001), with higher SOC content in the mountains and lower in the plains, and topographic factors could also exert an indirect effect on SOC through differences in temperature and land type ( < 0.01). Soil parent material and normalized difference vegetation index correlated significantly with topographic factors but had non-significant ( ≥ 0.05) direct effects on SOC content. Overall, topographic factors are essential factors influencing SOC spatial heterogeneity in the study area. It can be used as a critical cofactor to provide a reference for accurately assessing soil carbon stock on agricultural land in the study area.

摘要

研究区域农用地土壤有机碳(SOC)的空间分异特征并分析其驱动因素,对于筛选农用地SOC预测的辅助变量以及准确预测土壤碳储量具有重要意义。本研究以北京不同类型农用地景观复合体中的SOC为研究对象。基于北京耕地质量长期定位监测数据以及野外采样测试数据,探究不同景观复合体中SOC含量及其储量的差异。利用多源和开源数据作为影响SOC空间分异的环境变量,通过地理探测器和地理加权回归建模,探究不同景观复合体中SOC与气候、地形、土壤母质、土地利用和生物量因素之间的定量和空间关系。此外,构建结构方程模型以揭示各驱动因素对SOC的直接和间接影响路径。最终,确定研究区域SOC的主要控制因素。结果表明:①研究区域各类景观复合体的(SOC)平均值在6.23至28.26 g·kg之间,变异系数在3.80%至33.92%之间,呈现出空间异质性。②气候、地形、土壤母质、土地类型和生物量因素对SOC的贡献达到极显著水平(<0.01),各因素相互作用后对SOC均具有协同作用。所有因素对SOC空间变异的解释度在0.691至0.704之间,解释效度稳定。③温度、地形和土地类型对研究区域SOC具有极显著的直接影响(<0.01)。其中,温度与SOC含量呈负相关。在不同土地类型中,位于林地的景观复合体SOC含量较高,耕地较低。地形因素对SOC的直接影响最为显著(效应值=0.698,<0.001),山区SOC含量高于平原,地形因素还可通过温度和土地类型的差异对SOC产生间接影响(<0.01)。土壤母质和归一化植被指数与地形因素显著相关,但对SOC含量的直接影响不显著(≥0.05)。总体而言,地形因素是影响研究区域SOC空间异质性的关键因素。它可作为关键辅助因子,为准确评估研究区域农用地土壤碳储量提供参考。

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