高级检索
    赵晗, 王海燕, 罗鹏, 杜雪, 邹佳何, 符利勇, 雷相东. 微地形对云冷杉阔叶混交林土壤有机碳和全氮的影响[J]. 北京林业大学学报, 2022, 44(8): 88-97. DOI: 10.12171/j.1000-1522.20210237
    引用本文: 赵晗, 王海燕, 罗鹏, 杜雪, 邹佳何, 符利勇, 雷相东. 微地形对云冷杉阔叶混交林土壤有机碳和全氮的影响[J]. 北京林业大学学报, 2022, 44(8): 88-97. DOI: 10.12171/j.1000-1522.20210237
    Zhao Han, Wang Haiyan, Luo Peng, Du Xue, Zou Jiahe, Fu Liyong, Lei Xiangdong. Effects of micro-topography on soil organic carbon and total nitrogen in mixed spruce-fir-broadleaf forest[J]. Journal of Beijing Forestry University, 2022, 44(8): 88-97. DOI: 10.12171/j.1000-1522.20210237
    Citation: Zhao Han, Wang Haiyan, Luo Peng, Du Xue, Zou Jiahe, Fu Liyong, Lei Xiangdong. Effects of micro-topography on soil organic carbon and total nitrogen in mixed spruce-fir-broadleaf forest[J]. Journal of Beijing Forestry University, 2022, 44(8): 88-97. DOI: 10.12171/j.1000-1522.20210237

    微地形对云冷杉阔叶混交林土壤有机碳和全氮的影响

    Effects of micro-topography on soil organic carbon and total nitrogen in mixed spruce-fir-broadleaf forest

    • 摘要:
        目的  土壤有机碳与全氮是土壤质量评价的重要指标,同时与全球碳氮循环和气候变化密切相关。地形,尤其微地形是驱动土壤特征空间异质性的重要因素。本文旨在探究微地形对土壤有机碳和全氮的影响,为无人机数据应用与东北天然林土壤养分管理提供依据。
        方法  以云冷杉阔叶混交林为对象,通过无人机激光雷达数据提取4块1 hm2样地中400个10 m × 10 m样方的微地形因子,采用相关性分析和冗余分析研究微地形对土壤有机碳和全氮的影响。
        结果  研究区20 ~ 40 cm土层土壤有机碳和全氮均与高程呈极显著正相关(r = 0.26,0.25,P < 0.01),0 ~ 20 cm土壤全氮含量与坡度呈极显著正相关(r = 0.18,P < 0.01),其余相关性皆不显著。各样地的相关性分析结果存在差异。样地Ⅰ土壤有机碳与高程呈负相关(0 ~ 20 cm:r = −0.37,P < 0.01;20 ~ 40 cm:r = −0.21,P < 0.05),样地Ⅲ与样地Ⅳ 20 ~ 40 cm土壤有机碳与高程呈负相关(r = −0.20,−0.21,P < 0.05),样地Ⅲ 0 ~ 20 cm土壤有机碳与坡向呈正相关(r = 0.26,P < 0.05);样地Ⅰ20 ~ 40 cm土层土壤全氮与高程呈负相关(r = −0.34,P < 0.01),与复合地形因子平面曲率呈负相关(r = −0.24,P < 0.05)。在冗余分析中,RDA1约束轴的解释率达到88.05%,其中高程与20 ~ 40 cm土壤有机碳向量夹角较小,呈正相关关系,且高程与坡向对土壤有机碳和全氮有较大影响。
        结论  对比样地中心法和缓冲区法两种方法提取的无人机激光雷达数据,发现样方中心法选取的地形因子更多,且回归模型R2较大。微地形中的高程、坡度、坡向均对云冷杉阔叶混交林表层土壤有机碳和全氮有一定影响。以研究区4块样地整体和样地个体为尺度,分析微地形因子与土壤有机碳和全氮的相关性时发现,两者存在较大差异,表明云冷杉阔叶混交林土壤有机碳和全氮具有很强的空间异质性,且与简单地形因子的相关性强于复合地形因子。

       

      Abstract:
        Objective  Soil organic carbon (SOC) and total nitrogen (TN) are important indicators for soil quality assessment, which are closely related to global carbon and nitrogen cycle and climate change. Topography, especially micro-topography, is a key factor driving the spatial heterogeneity of soil characteristics. This paper aims to explore the effects of micro-topography on SOC and TN, and provide a basis for unmanned aerial vehicle (UAV) data application and soil nutrient management of natural forests in Northeast China.
        Method  Micro-topography factors of 400 10 m × 10 m sample plots were extracted from UAV Lidar data in 4 1-ha stands of mixed spruce-fir-broadleaf forest using sample center method and buffer zone method. Correlation analysis and redundancy analysis were carried out to study the effects of micro-topography on SOC and TN.
        Result  In the whole study area, SOC and TN at depth of 20−40 cm were significantly positively correlated with the elevation (r = 0.26, 0.25, P < 0.01), soil TN was significantly positively correlated with the slope at depth of 0−20 cm (r = 0.18, P < 0.01), and the other correlations were not significant. The results of correlation analysis were different among varied sample plots. There was a negative correlation between SOC and the elevation in sample plot Ⅰ (0−20 cm: r = −0.37, P < 0.01; 20−40 cm: r = −0.21, P < 0.05), a negative correlation between SOC at depth of 20−40 cm and the elevation in sample plot Ⅲ and Ⅳ (r = −0.20, −0.21, P < 0.05), and a positive correlation between SOC at depth of 0−20 cm and the aspect in sample plot Ⅲ (r = 0.26, P < 0.05). Soil TN at 20−40 cm of sample plot Ⅰ was negatively correlated with elevation (r = −0.34, P < 0.01), and negatively correlated with the plane curvature of secondary terrain factor (r = −0.24, P < 0.05). In the redundancy analysis, the interpretation rate of RDA1 constraint axis reached 88.05%, and the angle between elevation and SOC at depth of 20−40 cm was small indicative of a positive correlation. The elevation and aspect had significant effects on SOC and TN.
        Conclusion  The sample center method is superior to buffer zone method due to the selection of more terrain factors and higher R2 of the regression model. In the mixed spruce-fir-broadleaf forest, the elevation, slope and aspect of micro-topography have certain effects on SOC and TN in the surface horizon. Correlation analysis results vary as for the whole study area and individual sample plots, indicating a strong soil spatial heterogeneity. The correlations of SOC and TN with primary terrain factors are generally stronger than the secondary terrain factor.

       

    /

    返回文章
    返回