微地形对云冷杉阔叶混交林土壤有机碳和全氮的影响

赵晗; 王海燕; 罗鹏; 杜雪; 邹佳何; 符利勇; 雷相东

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

doi: 10.12171/j.1000-1522.20210237

赵晗^1,,
王海燕^1, ,,
罗鹏²,
杜雪¹,
邹佳何¹,
符利勇²,
雷相东²

1.
北京林业大学林学院，森林培育与保护教育部重点实验室北京 100083
2.
中国林业科学研究院资源信息所北京 100091

基金项目: 国家重点研发计划重点专项（2017YFC0504002）

详细信息

作者简介:
赵晗。主要研究方向：土壤学。Email：1171187930@qq.com　地址：100083北京市海淀区清华东路35号北京林业大学林学院

责任作者:
王海燕，教授。主要研究方向：土壤学、植物营养学。Email：haiyanwang72@aliyun.com　地址：同上

中图分类号: S714.2
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出版历程
- 收稿日期: 2021-06-22
- 修回日期: 2021-08-14
- 网络出版日期: 2022-07-27

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

1.
School of Forestry, Key Laboratory for Silviculture and Conservation of Ministry of Education, Beijing Forestry University, Beijing 100083, China
2.
Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China

摘要

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。
- 微地形 /
- 土壤有机碳 /
- 土壤全氮 /
- 无人机
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.
- micro-topography /
- soil organic carbon /
- soil total nitrogen /
- UAV

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图 1 样地位置图

图中数据为高程（m）。Ⅰ ~ Ⅳ为样地号 The data in the figure are elevation (m). Ⅰ−Ⅳ mean sample plot No.

Figure 1. Diagram of sample plot location

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图 2 样方设置图

Figure 2. Sample plot setting diagram

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图 3 无人机获取DEM三维图

Figure 3. 3D diagram of DEM extracted by UAV

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图 4 土壤有机碳及全氮与地形因子的 RDA排序

SOC1. 0 ~ 20 cm土壤有机碳；SOC2. 20 ~ 40 cm土壤有机碳；TN1. 0 ~ 20 cm土壤全氮；TN2. 20 ~ 40 cm土壤全氮。SOC1 and SOC2 denote soil organic carbon at soil depths of 0−20 cm and 20−40 cm; TN1 and TN2 denote soil total nitrogen at soil depths of 0−20 cm and 20−40 cm.

Figure 4. Redundancy analysis （RDA） between soil organic carbon, total nitrogen and terrain factors

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表 1 样地概况表

Table 1. Characteristics of experimental sample plots

样地 Sample plot	海拔 Elevation/m	坡度 Slope/(°)	坡向 Aspect/(°)	坡位 Slope position	郁闭度 Canopy density/%
Ⅰ	742	3	东北 Northeast	下坡 Downslope	59
Ⅱ	732	5	东北 Northeast	下坡 Downslope	75
Ⅲ	769	5	东北 Northeast	上坡 Upslope	65
Ⅳ	773	3	东北 Northeast	上坡 Upslope	73

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表 2 研究区土壤有机碳及全氮的统计数据

Table 2. Statistics of soil organic carbon and total nitrogen in the study area

土壤指标 Soil index	土壤深度 Soil depth/cm	平均值 Average	最小值 Min. value	最大值 Max. value	标准差 Standard deviation	变异系数 Coefficient of variance/%
土壤有机碳 Soil organic carbon/(g·kg⁻¹)	0 ~ 20	79.66	29.50	247.90	28.27	35.49
土壤有机碳 Soil organic carbon/(g·kg⁻¹)	20 ~ 40	41.10	12.60	107.30	14.99	36.47
土壤全氮 Soil total nitrogen/(g·kg⁻¹)	0 ~ 20	4.68	1.18	14.95	1.98	42.31
土壤全氮 Soil total nitrogen/(g·kg⁻¹)	20 ~ 40	2.19	0.41	5.18	0.92	42.01
注：n = 382。下同。Notes: n = 382. The same below.

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表 3 研究区地形因子的统计数据

Table 3. Statistics of terrain factors in the study area

地形因子 Terrain factor		平均值 Average	最小值 Min. value	最大值 Max. value	标准差 Standard deviation	变异系数 Coefficient of variance/%
简单地形因子 Primary terrain factor	高程 Elevation/m	786.79	755.23	822.09	22.88	2.91
	坡度 Slope/(°)	8.53	6.58	11.93	1.03	12.08
	坡向 Aspect/(°)	302.41	282.43	332.95	7.82	2.59
复合地形因子 Composite terrain factor	平面曲率 Plane curvature/((100 m)⁻¹)	0.01	−0.79	1.26	0.26	32.50
复合地形因子 Composite terrain factor	剖面曲率 Profile curvature/((100 m)⁻¹)	−0.02	−1.20	0.93	0.29	23.77

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表 4 研究区土壤有机碳及全氮与地形因子的相关性

Table 4. Correlation of soil organic carbon and total nitrogen with terrain factors in the study area

土壤指标 Soil index	土壤深度 Soil depth/cm	简单地形因子 Primary terrain factor			复合地形因子 Composite terrain factor
土壤指标 Soil index	土壤深度 Soil depth/cm	高程 Elevation	坡度 Slope	坡向 Aspect	平面曲率 Plane curvature	剖面曲率 Profile curvature
土壤有机碳 Soil organic carbon	0 ~ 20	0.09	0.00	0.06	−0.04	0.06
土壤有机碳 Soil organic carbon	20 ~ 40	0.26^**	0.02	0.00	−0.06	0.05
土壤全氮 Soil total nitrogen	0 ~ 20	−0.06	0.18^**	0.10	−0.01	0.07
土壤全氮 Soil total nitrogen	20 ~ 40	0.25^**	0.05	0.06	−0.10	0.07
注：*表示在0.01水平上显著相关，表示在0.05水平上显著相关。下同。Notes: ** means significant correlation at 0.01 level, * means significant correlation at 0.05 level. The same below.

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表 5 各样地土壤有机碳与地形因子的相关性

Table 5. Correlations between soil organic carbon and terrain factors in each sample plot

样地 Sample plot	土壤深度 Soil depth/cm	简单地形因子 Primary terrain factor			复合地形因子 Composite terrain factor
样地 Sample plot	土壤深度 Soil depth/cm	高程 Elevation	坡度 Slope	坡向 Aspect	平面曲率 Plane curvature	剖面曲率 Profile curvature
Ⅰ	0 ~ 20	−0.37**	−0.17	0.02	−0.12	0.10
Ⅰ	20 ~ 40	−0.21*	−0.04	0.02	−0.19	0.19
Ⅱ	0 ~ 20	0.06	0.00	0.11	0.13	−0.01
Ⅱ	20 ~ 40	−0.05	0.06	0.19	0.11	−0.02
Ⅲ	0 ~ 20	−0.16	−0.00	0.26*	0.00	0.05
Ⅲ	20 ~ 40	−0.20*	0.12	0.15	0.06	0.00
Ⅳ	0 ~ 20	−0.11	−0.07	0.13	−0.02	0.15
Ⅳ	20 ~ 40	−0.21*	−0.11	0.12	−0.01	0.06

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表 6 各样地土壤全氮与地形因子的相关性

Table 6. Correlations between soil total nitrogen and terrain factors in each sample plot

样地 Sample plot	土壤深度 Soil depth/cm	简单地形因子 Primary terrain factor			复合地形因子 Composite terrain factor
样地 Sample plot	土壤深度 Soil depth/cm	高程 Elevation	坡度 Slope	坡向 Aspect	平面曲率 Plane curvature	剖面曲率 Profile curvature
Ⅰ	0 ~ 20	0.16	−0.04	0.11	0.00	0.03
Ⅰ	20 ~ 40	−0.34**	−0.05	−0.06	−0.24*	0.15
Ⅱ	0 ~ 20	0.17	−0.03	−0.00	0.01	0.12
Ⅱ	20 ~ 40	−0.04	−0.02	0.17	0.01	0.09
Ⅲ	0 ~ 20	−0.17	0.08	0.23*	−0.02	0.10
Ⅲ	20 ~ 40	−0.10	0.12	0.06	−0.06	0.12
Ⅳ	0 ~ 20	−0.15	0.16	0.11	0.01	0.15
Ⅳ	20 ~ 40	−0.11	0.08	0.08	0.08	−0.01

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表 7 不同提取方法相关系数与回归模型R²

Table 7. Correlation coefficients between different extraction methods and determination coefficients of regression models

方法 Method	20 ~ 40 cm 土壤有机碳−高程 20−40 cm soil organic carbon-elevation	20 ~ 40 cm 土壤全氮−高程 20−40 cm soil total nitrogen-elevation	0 ~ 20 cm 土壤全氮−坡度 0−20 cm soil total nitrogen-slope	回归模型R² Regression model R²
方法 Method	20 ~ 40 cm 土壤有机碳−高程 20−40 cm soil organic carbon-elevation	20 ~ 40 cm 土壤全氮−高程 20−40 cm soil total nitrogen-elevation	0 ~ 20 cm 土壤全氮−坡度 0−20 cm soil total nitrogen-slope	0 ~ 20 cm 土壤有机碳 0−20 cm soil organic carbon	20 ~ 40 cm 土壤有机碳 20−40 cm soil organic carbon	0 ~ 20 cm 土壤全氮 0−20 cm soil total nitrogen	20 ~ 40 cm 土壤全氮 20−40 cm soil total nitrogen
样方中心法 Quadrat center method	0.262**	0.245**	0.176**	0.025	0.098	0.046	0.090
内切缓冲区 Inscribed circle buffer	0.261**	0.245**	0.184**	0.022	0.084	0.035	0.072
100 m²缓冲区 100 m² circle buffer	0.261**	0.245**	0.191**	0.021	0.084	0.038	0.072
外接缓冲区 Circumscribed circle buffer	0.261**	0.244**	0.190**	0.023	0.092	0.038	0.076
注：表格只选取了具有显著性的相关关系。Note: only significant correlations are selected in the table.

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