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微地形对云冷杉阔叶混交林土壤有机碳和全氮的影响     被引量:5

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

文献类型:期刊文献

中文题名:微地形对云冷杉阔叶混交林土壤有机碳和全氮的影响

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

作者: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]

第一作者:赵晗

机构:[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

年份:2022

卷号:44

期号:8

起止页码:88-97

中文期刊名:北京林业大学学报

外文期刊名:Journal of Beijing Forestry University

收录:CSTPCD;;北大核心:【北大核心2020】;CSCD:【CSCD2021_2022】;

基金:国家重点研发计划重点专项(2017YFC0504002)。

语种:中文

中文关键词:微地形;土壤有机碳;土壤全氮;无人机

外文关键词:micro-topography;soil organic carbon;soil total nitrogen;UAV

分类号:S714.2

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 hm^(2)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Ⅳ20~40 cm土壤有机碳与高程呈负相关(r=-0.20,-0.21,P<0.05),样地Ⅲ0~20 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R~2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。
[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 40010 m×10 m sample plots were extracted from UAV Lidar data in 41-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 microtopography 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 plotⅠ(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 plotⅢandⅣ(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 plotⅢ(r=0.26,P<0.05).Soil TN at 20-40 cm of sample plotⅠwas 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 RDA1constraint 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 R^(2) 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.

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