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Frontiers of Earth Science

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Front. Earth Sci.    2022, Vol. 16 Issue (4) : 835-845    https://doi.org/10.1007/s11707-021-0940-7
RESEARCH ARTICLE
The response of soil organic carbon to climate and soil texture in China
Yi ZHANG1,2, Peng LI1,2(), Xiaojun LIU3, Lie XIAO1,2, Tanbao LI4, Dejun WANG4
1. State Key Laboratory Base of Eco-hydraulic Engineering in Arid Area, Xi’an University of Technology, Xi’an 710048, China
2. State Key Laboratory of National Forestry and Grassland Administration on Ecological Hydrology and Disaster Prevention in Arid Regions, Xi’an 710048, China
3. Forestry College, Jiangxi Agricultural University, Nanchang 330045, China
4. Northwest Surveying, Planning and Designing Institute of National Forestry and Grassland Administration, Xi’an 710048, China
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Abstract

Soil organic carbon (SOC) plays an essential role in the carbon cycle and global warming mitigation, and it varies spatially in relation to other soil and environmental properties. But the national distributions and the impact mechanisms of SOC remain debated in China. Therefore, how soil texture and climate factors affect the SOC content and the regional differences in SOC content were explored by analyzing 7857 surface soil samples with different land-use. The results showed that the SOC content in China, with a mean value of 11.20 g·kg−1, increased gradually from north to south. The SOC content of arable land in each geographical area was lower than in grassland and forest-land. Although temperature also played a specific role in the SOC content, precipitation was the most critical climate factor. The SOC content was positively correlated with the silt and clay content. The lower the temperature, the greater the effect of environmental factors on SOC. In contrast, the higher the temperature, the more significant impact of soil texture on SOC. The regional difference in SOC highlights the importance of soil responses to climate change. Temperature and soil texture should be explicitly considered when predicting potential future carbon cycle and sequestration.
Keywords soil organic carbon      climate      soil texture      land use     
Corresponding Author(s): Peng LI   
Online First Date: 26 January 2022    Issue Date: 11 January 2023
 Cite this article:   
Yi ZHANG,Peng LI,Xiaojun LIU, et al. The response of soil organic carbon to climate and soil texture in China[J]. Front. Earth Sci., 2022, 16(4): 835-845.
 URL:  
https://academic.hep.com.cn/fesci/EN/10.1007/s11707-021-0940-7
https://academic.hep.com.cn/fesci/EN/Y2022/V16/I4/835
Fig.1  Overview of the research area.
Type Northwest Northern Southern Qinghai-Tibet
Arable land 314 2210 2547 328
Grassland 248 333 118 175
Forest land 129 387 884 184
Tab.1  The number of arable land, forest land and grassland sample points in each region
Fig.2  Semivariogram function theory model. C0: nugget variance; C1: structural variance; GD: degree of spatial dependence; RSS: residual sum of squares.
Theoretical Model Nugget (C0) Sill Value (C0 + C1) C0/(C0 + C1) RSS Range R2
Spherical Model 0.150 0.031 0.476 2.718 × 10−3 269000 0.501
Gaussian Model 0.020 0.040 0.498 9.076 × 10−3 197000 0.654
Exponential Model 0.006 0.014 0.405 1.496 × 10−3 160000 0.822
Tab.2  Semivariogram theoretical models of SOC content and the parameters
Fig.3  Soil organic carbon (SOC) content and geographical divisions.
Fig.4  Soil organic carbon (SOC) content in each geographical zone. Note: uppercase letters represent the differences among the different land use types in the same area, and the lowercase letters indicate the differences in different areas of the same land use type.
Area Climate Correlation coefficient Efficacy analysis
Arable land Grass land Forest land Arable land Grass land Forest land Ensemble
Northwest MAT −0.295** −0.471** −0.694** 0.779 0.966 0.999 0.999
MAP 0.197* 0.351** 0.469** 0.113 0.254 0.946 0.885
MAT × MAP - - - 0.059 0.131 0.954 0.088
Northern MAT −0.381** −0.263* −0.153* 0.999 0.846 0.727 0.104
MAP 0.230 −0.030 0.220* 0.916 0.063 0.938 0.897
MAT × MAP - - - 0.823 0.050 0.076 0.784
Southern MAT −0.070 −0.363* −0.058 0.539 0.881 0.420 0.05
MAP 0.107** 0.142 0.088 0.995 0.467 0.590 0.997
MAT × MAP - - - 0.944 0.116 0.055 0.602
Qinghai-Tibet MAT −0.193* −0.163 −0.093 0.934 0.385 0.058 0.545
MAP 0.107** 0.200 0.154 0.923 0.490 0.177 0.879
MAT × MAP - - - 0.470 0.114 0.053 0.379
Tab.3  Partial correlation and interpretation between soil organic carbon (SOC), mean annual temperature (MAT), and mean annual precipitation (MAP)
Area Soil texture Correlation coefficient
Arable land Grass land Forest land
Northwest Sand −0.248** −0.184** −0.510**
Silt 0.140** 0.103** 0.613**
Clay 0.317** 0.254** 0.089**
Northern Sand −0.273** −0.500** −0.344**
Silt 0.186** 0.394** 0.309**
Clay 0.266** 0.423** 0.304**
Southern Sand −0.271** −0.103** −0.190**
Silt 0.243** 0.229** 0.152**
Clay 0.184** −0.209** 0.144**
Qinghai-Tibet Sand −0.148** −0.325** −0.371**
Silt −0.135** 0.331** 0.354**
Clay −0.109** 0.208** 0.306**
Tab.4  Correlation analysis between soil organic carbon (SOC) content and soil texture factors in China
Area Land use Regression analysis a)
R2 b)adj Equation
Northwest Arable land 0.317** SOC= 6.567+ 0.201 × Clay
Grass land 0.254** SOC= 6.113+ 0176 × Clay
Forest land 0.614** SOC= 3.927+ 0.266 × Silt
Northern Arable land 0.289** SOC= 9.006+ 0.750 × Clay–0.470 × Sand c
Grass land 0.500** SOC= 19.854–0.171 × Sand
Forest land 0.344** SOC= 19.609–0.137 × Sand
Southern Arable land 0.271** SOC= 16.335–0.075 × Sand
Grass land 0.120** SOC= 3.719–0.910 × Clay
Forest land 0.190** SOC= 16.367–0.057 × Sand
Qinghai-Tibet Arable land 0.313** SOC= 6.567+ 0.810 × Clay
Grass land 0.331** SOC= 5.886+ 0.131 × Silt
Forest land 0.371** SOC= 3.307+ 0.108 × Sand
Tab.5  Stepwise regression analysis of soil organic carbon (SOC) and soil texture factors in different land use patterns in different geographical areas
Area Land use Stepwise regression model a R2 c)adj ΔR2 d)1 ΔR2 e)2 ΔR2 f)3 ΔR2 g)4
Predictors b
North-west Arable land Constant, Clay, MAT, Silt 0.491 0.094 0.187 0.21
Grass land Constant, MAT, Clay 0.486 0.215 0.271
Forest land Constant, MAT, Silt 0.992 0.471 0.521
Ensemble Constant, MAT, Sand, MAP 0.719 0.171 0.264 0.284
Northern Arable land Constant, MAT, Sand, Clay, MAP 0.886 0.145 0.242 0.248 0.251
Grass land Constant, Sand, MAT 0.519 0.244 0.275
Forest land Constant, Sand, MAP 0.266 0.118 0.148
Ensemble Constant, Sand, MAT 0.497 0.238 0.259
Southern Arable land Constant, Sand, MAP 0.171 0.073 0.098
Grass land Constant, MAT, Silt, MAP 0.505 0.117 0.164 0.224
Forest land Constant, Sand, MAP 0.077 0.034 0.043
Ensemble Constant, Sand, MAP, Silt 0.798 0.235 0.279 0.284
Qinghai-Tibet Arable land Constant, MAP, MAT, Clay 0.419 0.076 0.156 0.187
Grass land Constant, Silt 0.099 0.099
Forest land Constant, Sand 0.126 0.126
Ensemble Constant, MAP, Sand, MAT 0.494 0.195 0.232 0.262
Tab.6  Results of a stepwise regression analysis of soil organic carbon (SOC) and climatic texture in different geographical regions of China
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