Spatial analysis of soil organic carbon in Zhifanggou catchment of the Loess Plateau.

Soil organic carbon (SOC) reflects soil quality and plays a critical role in soil protection, food safety, and global climate changes. This study involved grid sampling at different depths (6 layers) between 0 and 100 cm in a catchment. A total of 1282 soil samples were collected from 215 plots over...

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Main Authors: Mingming Li, Xingchang Zhang, Qing Zhen, Fengpeng Han
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2013-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC3873912?pdf=render
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author Mingming Li
Xingchang Zhang
Qing Zhen
Fengpeng Han
author_facet Mingming Li
Xingchang Zhang
Qing Zhen
Fengpeng Han
author_sort Mingming Li
collection DOAJ
description Soil organic carbon (SOC) reflects soil quality and plays a critical role in soil protection, food safety, and global climate changes. This study involved grid sampling at different depths (6 layers) between 0 and 100 cm in a catchment. A total of 1282 soil samples were collected from 215 plots over 8.27 km(2). A combination of conventional analytical methods and geostatistical methods were used to analyze the data for spatial variability and soil carbon content patterns. The mean SOC content in the 1282 samples from the study field was 3.08 g · kg(-1). The SOC content of each layer decreased with increasing soil depth by a power function relationship. The SOC content of each layer was moderately variable and followed a lognormal distribution. The semi-variograms of the SOC contents of the six different layers were fit with the following models: exponential, spherical, exponential, Gaussian, exponential, and exponential, respectively. A moderate spatial dependence was observed in the 0-10 and 10-20 cm layers, which resulted from stochastic and structural factors. The spatial distribution of SOC content in the four layers between 20 and 100 cm exhibit were mainly restricted by structural factors. Correlations within each layer were observed between 234 and 562 m. A classical Kriging interpolation was used to directly visualize the spatial distribution of SOC in the catchment. The variability in spatial distribution was related to topography, land use type, and human activity. Finally, the vertical distribution of SOC decreased. Our results suggest that the ordinary Kriging interpolation can directly reveal the spatial distribution of SOC and the sample distance about this study is sufficient for interpolation or plotting. More research is needed, however, to clarify the spatial variability on the bigger scale and better understand the factors controlling spatial variability of soil carbon in the Loess Plateau region.
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spelling doaj.art-3d775fbb3e6042b982977ba4ad92130a2022-12-21T23:59:22ZengPublic Library of Science (PLoS)PLoS ONE1932-62032013-01-01812e8306110.1371/journal.pone.0083061Spatial analysis of soil organic carbon in Zhifanggou catchment of the Loess Plateau.Mingming LiXingchang ZhangQing ZhenFengpeng HanSoil organic carbon (SOC) reflects soil quality and plays a critical role in soil protection, food safety, and global climate changes. This study involved grid sampling at different depths (6 layers) between 0 and 100 cm in a catchment. A total of 1282 soil samples were collected from 215 plots over 8.27 km(2). A combination of conventional analytical methods and geostatistical methods were used to analyze the data for spatial variability and soil carbon content patterns. The mean SOC content in the 1282 samples from the study field was 3.08 g · kg(-1). The SOC content of each layer decreased with increasing soil depth by a power function relationship. The SOC content of each layer was moderately variable and followed a lognormal distribution. The semi-variograms of the SOC contents of the six different layers were fit with the following models: exponential, spherical, exponential, Gaussian, exponential, and exponential, respectively. A moderate spatial dependence was observed in the 0-10 and 10-20 cm layers, which resulted from stochastic and structural factors. The spatial distribution of SOC content in the four layers between 20 and 100 cm exhibit were mainly restricted by structural factors. Correlations within each layer were observed between 234 and 562 m. A classical Kriging interpolation was used to directly visualize the spatial distribution of SOC in the catchment. The variability in spatial distribution was related to topography, land use type, and human activity. Finally, the vertical distribution of SOC decreased. Our results suggest that the ordinary Kriging interpolation can directly reveal the spatial distribution of SOC and the sample distance about this study is sufficient for interpolation or plotting. More research is needed, however, to clarify the spatial variability on the bigger scale and better understand the factors controlling spatial variability of soil carbon in the Loess Plateau region.http://europepmc.org/articles/PMC3873912?pdf=render
spellingShingle Mingming Li
Xingchang Zhang
Qing Zhen
Fengpeng Han
Spatial analysis of soil organic carbon in Zhifanggou catchment of the Loess Plateau.
PLoS ONE
title Spatial analysis of soil organic carbon in Zhifanggou catchment of the Loess Plateau.
title_full Spatial analysis of soil organic carbon in Zhifanggou catchment of the Loess Plateau.
title_fullStr Spatial analysis of soil organic carbon in Zhifanggou catchment of the Loess Plateau.
title_full_unstemmed Spatial analysis of soil organic carbon in Zhifanggou catchment of the Loess Plateau.
title_short Spatial analysis of soil organic carbon in Zhifanggou catchment of the Loess Plateau.
title_sort spatial analysis of soil organic carbon in zhifanggou catchment of the loess plateau
url http://europepmc.org/articles/PMC3873912?pdf=render
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