土壤碳
环境科学
土壤科学
流域
空间分布
空间变异性
生物地球化学循环
土壤水分
水文学(农业)
土壤有机质
植被(病理学)
归一化差异植被指数
自然地理学
地质学
生态学
叶面积指数
地理
遥感
统计
地图学
数学
岩土工程
生物
医学
病理
作者
Tianwei Wang,Fengfeng Kang,Xiaoqin Cheng,Hairong Han,Yingchen Bai,Junyong Ma
出处
期刊:Catena
[Elsevier]
日期:2017-03-09
卷期号:155: 41-52
被引量:57
标识
DOI:10.1016/j.catena.2017.03.004
摘要
Soil organic carbon (SOC) and total nitrogen (TN) are critical indicators of soil quality and play a pivotal role in key biogeochemical process (i.e. soil carbon and nutrient cycling). Many studies have assessed soil organic matter and nutrients individually in different ecosystems. However, appropriate sampling density for accurate estimation of the spatial distribution of SOC in subalpine forests and quantification of the relative importance of influencing factors remains uncertain. In this study, a combination of conventional analytical and geostatistical methods was used to analyze the spatial variability and patterns of SOC and TN along a soil profile. A total of 444 soil samples, taken from three layers down to 60 cm, were collected from the Jieshigou catchment area (5.64 km2) of Mount Taiyue in northern China. Results show that a large spatial variability of SOC and TN appears in upper 40 cm along an elevation and vegetation gradient, while strong spatial autocorrelation is present below 40 cm (40-60 cm). Range and degree of spatial autocorrelation for SOC were slightly larger than those of TN; All the same, both showed clustered spatial distribution. A distribution map of Kriging revealed that both SOC and TN concentrations in the Jieshigou catchment area decreased from west to east along the direction of the valley, which coincides with the overlay of topographic features. More than 40% of the variance in SOC and TN contents could be explained by topographical indices and normalized difference vegetation index (NDVI). SOC and TN significantly increased (from 23.6 to 56.8 g kg− 1) with age of larch plantations in the surface layer. Our results suggest that a stratified random sampling was proved a sufficiently reliable way for estimating the spatial distribution of SOC and TN.
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