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祁连山中段土壤有机碳剖面垂直分布特征及其影响因素
引用本文:杨 敏,杨 飞,杨仁敏,杨 帆,张甘霖.祁连山中段土壤有机碳剖面垂直分布特征及其影响因素[J].土壤,2017,49(2):386-392.
作者姓名:杨 敏  杨 飞  杨仁敏  杨 帆  张甘霖
作者单位:1. 土壤与农业可持续发展国家重点实验室(中国科学院南京土壤研究所),南京 210008;中国科学院大学,北京 100049;2. 土壤与农业可持续发展国家重点实验室(中国科学院南京土壤研究所),南京,210008
基金项目:国家自然科学(41130530)资助。* 通讯作者(glzhang@issas.ac.cn)
摘    要:以2012—2013年调查的我国西北祁连山中段97个代表性土壤剖面为对象,分析了土壤有机碳(SOC)含量的剖面垂直分布模式,计算了1 m土体内各层次SOC相对含量及其与环境因素(年均降水、年均温度、海拔、坡度、坡向、NDVI)和土壤因素(颗粒组成、体积质量)之间的关系。结果表明:(1)SOC含量剖面垂直分布模式可分为均一分布型、表层聚集型、普通递减型、不规则分布型4个类型,SOC含量剖面垂直分布模式与选取的环境因素和土壤颗粒组成之间没有明显的关系;(2)SOC含量的变异较大,随着深度的增加从中度变异过渡到强度变异;(3)NDVI和年均降水是影响表层土体SOC含量的主要因子,而黏粒和砂粒是影响下层土体SOC含量的主要因子。

关 键 词:土壤有机碳  剖面垂直分布  有机碳密度  影响因子  祁连山
收稿时间:2016/4/29 0:00:00
修稿时间:2016/11/23 0:00:00

Profile Vertical Distribution Modes of SOC and Influential Factors in Qilian Mountains
YANG Min,YANG Fei,YANG Renmin,YANG Fan and ZHANG Ganlin.Profile Vertical Distribution Modes of SOC and Influential Factors in Qilian Mountains[J].Soils,2017,49(2):386-392.
Authors:YANG Min  YANG Fei  YANG Renmin  YANG Fan and ZHANG Ganlin
Institution:Institute of Soil Science, Chinese Academy of Sciences,State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences,State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences,State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences,State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences
Abstract:Ninety-seven soil profiles were sampled across the Qilian Mountain using a purposively sampling strategy. Vertical variations of soil organic carbon (SOC) as well as their drivers within different soils depths were analyzed. Results showed that both SOC content and SOC density had moderate to strong variability, and the coefficient of variation increased with depth. Random forest method was adopted to predict the content and density of SOC with multiple influencing factors and each factor was ranked according to their relative importance in the model. It turned out that the surface soil layer (0-20 cm) had the best model performance with R2 reaching 0.68 and 0.52 for SOC content and SOC density respectively and R2 decreased with increasing soil depth. Moreover, the environmental factors (esp. NDVI and MAP) were the main drivers for variations in surface SOC content and density, while edaphic factors added their weights with increasing soil depth.
Keywords:Soil organic carbon  Vertical Variability  Random forest  Impact factors
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