| 许世奇,寇威,时若萱,邢睿,李泽宇,张育林,王旭东.陕北红柳林煤矿区不同植被类型土壤有机碳含量及组成特征[J].干旱地区农业研究,2025,(3):220~232 |
| 陕北红柳林煤矿区不同植被类型土壤有机碳含量及组成特征 |
| Soil organic carbon content and composition characteristics of different vegetation types in the northern Shaanxi Hongliulin coal mining area |
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| DOI：10.7606/j.issn.1000-7601.2025.03.23 |
| 中文关键词: 植被类型 土壤有机碳 有机碳组分 通径分析 红柳林煤矿区 |
| 英文关键词:vegetation type soil organic carbon organic carbon fraction path analysis Hongliulin coal mine area |
| 基金项目:陕煤集团神木红柳林矿业公司集团级科研项目(2020SMHKJ-A-J-03-02/02) |
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| 中文摘要: |
| 为探究不同植被类型对红柳林煤矿区土壤有机碳（SOC）库的影响，以红柳林煤矿区3种植被类型（草本、灌木、草灌）土壤为研究对象，分析0~200 cm土层土壤有机碳含量及密度，有机碳组分如微生物量碳（MBC）、可溶性有机碳（DOC）、轻组有机碳（LFOC）、颗粒有机碳（POC）及矿质结合态有机碳（MAOC）的含量变化及占比差异，并采用通径分析法明确影响土壤有机碳及组分的关键因子。结果表明：在0~200 cm土层中，3种植被类型SOC含量范围为2.04~18.35 g·kg-1，其平均含量以草本最高，依次为灌木和草灌。3种植被的土壤有机碳密度表现为草本（16.51 kg·m-2）>灌木（12.28 kg·m-2）>草灌（7.91 kg·m-2）。在0~200 cm土层中，均以灌木植被土壤MBC、POC、LFOC平均含量最高，其次为草灌和草本；DOC平均含量则以草灌最高，其次为草本和灌木。不同植被类型间DOC/SOC、MBC/SOC、POC/SOC和LFOC/SOC值均以草灌最大；而MAOC/SOC值则以草本最高，草灌相对最小。Pearson相关性分析显示，在土壤理化因子中，SOC与铵态氮、有效磷及砂粒间呈极显著正相关关系，与速效钾、pH及粉粒间呈极显著负相关关系；通径分析表明，SOC含量主要受到土壤有效磷与矿质结合态有机碳的影响，其中SOC组分则主要受到土壤有效磷、铵态氮和pH的影响。综上，在陕北红柳林煤矿区的复垦和生态重构中，应优先加强草本植被的种植，其次为灌木植被。研究成果可望为优化矿区植被结构及生态修复提供理论支撑。 |
| 英文摘要: |
| To examine the impact of different vegetation types on the soil organic carbon (SOC) pool in the Hongliulin coal mine of northern Shaanxi, this study analyzed soil from three vegetation types—grassland, shrubland, and grass\|shrub ecosystems—within the mining area. The content and density of SOC, as well as content changes and percentage differences in SOC fractions such as microbial biomass carbon (MBC), dissolved organic carbon (DOC), light organic carbon (LFOC), particulate organic carbon (POC), and mineral\|associated organic carbon (MAOC) were analyzed along soil profiles (0~200 cm) under different vegetation. In addition, pathway analysis was used to identify the key factors influencing SOC and its fractions. The results of research showed that in the 0~200 cm soil layer, the SOC contents of the three vegetation types ranged from 2.04~18.35 g·kg-1, with the highest average content in grassland, followed by shrubland and grass\|shrub. The SOC densities of the three vegetation types followed the order of grassland (16.51 kg·m-2) > shrubland (12.28 kg·m-2) > grass\|shrub (7.91 kg·m-2). In the 0~200 cm soil layer, the average contents of MBC, POC, and LFOC were the highest in shrubland, followed by grass\|shrub, and the lowest in grassland. The average contents of DOC were the highest in grass\|shrub, followed by grassland and shrubland. Among different vegetation types, DOC/SOC, MBC/SOC, POC/SOC, and LFOC/SOC value were the highest in grass\|shrub. MAOC/SOC value was the highest in grassland and the smallest in grass\|shrub. Pearson correlation analysis showed that among the soil physicochemical factors, SOC was significantly positively correlated with ammonium nitrogen, available phosphorus, and sand, and significantly negatively correlated with available potassium, pH, and silt. Path analysis revealed that SOC content was mainly affected by soil\|available phosphorus and MAOC, while SOC fractions were mainly affected by the content of soil\|available phosphorus, ammonium nitrogen, and pH. In conclusion, in the reclamation and ecological restoration of the Hongliulin coal mine in northern Shaanxi, priority should be given to enhancing grassland vegetation, followed by shrubland vegetation. These findings are expected to provide theoretical support for optimizing vegetation structure and advancing ecological restoration in mining areas. |
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