| 不同景观综合体土壤有机碳空间分异特征及驱动因素分析 |
| 摘要点击 1111 全文点击 125 投稿时间：2024-03-27 修订日期：2024-05-22 |
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| 中文关键词 农用地 土壤有机碳（SOC） 景观综合体 空间分异 驱动因子 影响路径 |
| 英文关键词 agricultural land soil organic carbon （SOC） landscape complex spatial variation driving factors influence pathway |
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| 中文摘要 |
| 为探究区域农用地土壤有机碳（SOC）空间分异特征,解析其驱动因素,以北京市农用地不同类型景观综合体的SOC为研究对象,利用多源和开源数据为环境变量,通过地理探测器、地理加权回归和结构方程模型,分析不同景观综合体SOC空间分异特征及其与气候、地形、土壤母质、土地利用和生物量之间的关系,揭示各因素对SOC的影响路径. 结果表明：①研究区不同类型景观综合体ω（SOC）均值为6.23~28.26 g·kg-1,变异系数为3.80%~33.92%,存在空间异质性；②气候、地形、土壤母质、地类和生物量因素对SOC的贡献均达到极显著水平（P < 0.01）,交互后对SOC呈协同影响作用；各因素共解释了SOC空间变异的0.691~0.704；③气温、地形和地类对研究区SOC呈极显著直接影响效应（P < 0.01）；气温与SOC含量为负相关；不同地类中,位于林地的景观综合体SOC含量较高,耕地较低；地形因素对SOC的直接影响效应最大（效应值为0.698,P < 0.001）,其中山地SOC含量较高,平原较低,且地形因素还可通过气温和地类的差异对SOC产生间接影响效应（P < 0.01）；土壤母质和归一化植被指数与地形因素呈显著关联,但对SOC的直接影响效应不显著（P ≥ 0.05）. 整体上,地形因素是影响研究区SOC空间分异的重要因素,将其作为关键辅助因子,可为精确评估研究区土壤碳储量提供参考. |
| 英文摘要 |
| 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 ω（SOC） for various types of landscape complexes in the study area ranged from 6.23 to 28.26 g·kg-1, 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 （P < 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 （P < 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, P < 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 （P < 0.01）. Soil parent material and normalized difference vegetation index correlated significantly with topographic factors but had non-significant （P ≥ 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. |
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