Scientia Agricultura Sinica ›› 2025, Vol. 58 ›› Issue (6): 1145-1158.doi: 10.3864/j.issn.0578-1752.2025.06.008

• SOIL & FERTILIZER·WATER-SAVING IRRIGATION·AGROECOLOGY & ENVIRONMENT • Previous Articles     Next Articles

Temporal and Spatial Variation Characteristics of Soil Organic Carbon in Hulunbuir and Its Influencing Factors

WU XinJia1(), XUE Wei2, YAN YiDan1, NIE YingYing1, YE LiMing3, XU LiJun1()   

  1. 1 State Key Laboratory of Efficient Utilization of Arid and Semi-arid Arable Land in Northern China/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences/National Observation and Research Station of Hulunbuir Grassland Ecosystem, Beijing 100081, China
    2 Xishuangbanna Dai Autonomous Prefecture Meteorological Office of Yunnan Province, Xishuangbanna 666100, Yunnan, China
    3 Department of Geology, Ghent University, Ghent 9000, Belgium
  • Received:2024-05-14 Accepted:2024-11-11 Online:2025-03-25 Published:2025-03-25
  • Contact: XU LiJun

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Abstract:

【Objective】 This study aimed to analyze the spatiotemporal distribution characteristics and driving factors of soil organic carbon (SOC) content in Hulunbuir, China, in order to provide the scientific basis for soil carbon storage management and ecosystem services.【Method】 The point-to-point sampling survey method was used to collect measured SOC data from 1980 (historical data) and 2022, involving four land use types: farmland, grassland, forest, and wetland. Using regression kriging method, combined with environmental variables such as temperature, precipitation, slope, altitude, and NDVI, the spatial prediction of SOC content and its changes was carried out. 【Result】 (1) The SOC content in 1980 was significantly affected by these five factors (P<0.05), while the SOC data in 2022 was mainly affected by altitude, slope, precipitation, and NDVI, with no significant effect from temperature (P=0.07). The fitting accuracies of the models for the two periods of 1980 and 2022 were R²=0.60 and R²=0.63, respectively, indicating that the predictive model had a certain level of reliability. (2) According to spatial prediction data, the average SOC content in Hulunbuir was 40.29 g·kg-1 in 1980, and decreased to 31.75 g·kg-1 in 2022. The spatial variation trend of soil SOC content in the two periods was similar, with higher content in the central region and lower content in the western and eastern regions. (3) There were differences in the changes of SOC content under different land use patterns. Over the past 40 years, the SOC content of farmland, grassland, forest, and wetland soils has decreased by 4.59 g·kg-1 (13.3%), 6.08 g·kg-1(18.7%), 11.16 g·kg-1(23.0%), and 7.20 g·kg-1(24.4%), respectively. 【Conclusion】 The spatial distribution trend of SOC content in Hulunbuir area remained consistent between 1980 and 2022, and SOC content showed a decreasing trend under different land use patterns. The transformation of land use patterns was a key factor affecting the spatial distribution changes of SOC. In addition, there was uncertainty in the prediction of SOC changes by environmental variables, and future research needs to consider their dynamic characteristics. In the Hulunbuir region, the forest grassland transition zone and the forest farmland transition zone had carbon sink potential, while grasslands, central high-altitude forest areas, and farmland areas might be carbon source areas.

Key words: soil organic carbon, spatiotemporal variation, land use pattern, regression kriging interpolation, Generalized Additive Model, GAM, Hulunbuir

Fig. 1

Land types and distribution of sampling points in Hulunbuir area"

Table 1

Selection of GAM model factors influencing SOC content in 1980 and 2022"

年份
Year		 影响因素
Influence factor		 标准化系数
Standardized coefficient		 显著性
Significance		 拟合度
R2
1980 海拔Elevation 14.134 <0.001 0.72
坡度Slope 1.601 <0.001
温度Temperature -13.709 <0.001
降水量Precipitation 0.240 <0.05
归一化植被指数Normalized difference vegetation index 8.280 <0.05
2022 海拔Elevation 0.024 <0.001 0.71
坡度Slope 1.102 <0.01
降水量Precipitation 5.758 <0.001
归一化植被指数Normalized difference vegetation index 2.785 <0.05

Table 2

Fitting effects of different models for SOC content"

年份
Year		 编号
Number		 模型函数
Model function		 块金值
Nugget value		 偏基台值
Partial abutment value		 平均值误差
ME
(g·kg-1)		 均方根误差
RMSE
(g·kg-1)		 平均绝对误差MAE
(g·kg-1)		 拟合度
R2
1980 1 指数函数Exponential function 1.02 0.00 -0.04 5.28 5.04 0.48
2 指数函数Exponential function 1.51 0.00 -0.04 5.28 6.12 0.48
3 高斯函数Gauss function 1.02 0.00 -0.06 5.37 4.99 0.47
4 指数函数Exponential function 0.10 0.00 -0.04 5.28 1.58 0.48
5 指数函数Exponential function 1.02 0.00 -0.06 5.48 4.97 0.46
6 指数函数Exponential function 1.02 0.00 -0.19 5.60 4.67 0.45
7 高斯函数Gauss function 1.68 0.16 -0.06 5.37 6.70 0.47
8 高斯函数Gauss function 1.02 0.00 -0.01 5.20 5.07 0.48
9 高斯函数Gauss function 1.02 0.00 -0.06 5.37 5.61 0.47
10 指数函数Exponential function 43.33 0.00 0.08 5.24 6.72 0.48
11 J-Bessel 0.02 1.68 -0.01 0.81 0.22 0.65
2022 1 指数函数Exponential function 0.88 0.12 0.00 1.04 4.57 0.48
2 指数函数Exponential function 1.00 0.10 0.02 4.92 4.49 0.47
3 指数函数Exponential function 1.29 0.12 0.01 4.80 5.22 0.48
4 高斯函数Gauss function 1.24 0.34 0.01 4.92 5.68 0.47
5 指数函数Exponential function 1.02 0.00 0.00 4.81 4.58 0.48
6 高斯函数Gauss function 1.34 0.00 0.04 4.95 5.17 0.46
7 稳定Stable 1.01 0.00 -0.01 4.72 4.64 0.49
8 稳定Stable 1.01 0.00 0.00 4.68 4.64 0.49
9 多项式5 Polynomial 5 0.27 0.33 0.02 0.99 0.78 0.62
10 指数函数Exponential function 27.33 0.00 0.10 4.80 5.32 0.48
11 孔洞效应Hole effect 22.25 5.29 0.22 5.25 5.59 0.43
12 J-Bessel 20.49 6.66 0.11 4.63 5.25 0.50
13 稳定Stable 24.29 3.18 0.11 4.81 5.33 0.48

Fig. 2

Predicted and measured SOC content in Hulunbuir in 1980 and 2022"

Table 3

Comparison results of cross validation of SOC content in Hulunbuir in different years under the Kriging Regression Model"

年份
Year		 MAE
(g·kg-1)		 RMSE
(g·kg-1)		 R²
1980 9.16 11.83 0.60
2022 7.13 10.92 0.63

Fig. 3

SOC content under different land use patterns in Hulunbuir in 1980 and 2022 Different lowercase letters indicate significant differences between different treatments (P<0.05). The same as below"

Fig. 4

Spatial distribution of predicted soil surface SOC content in Hulunbuir in 1980 and 2022"

Fig. 5

Spatial distribution of surface SOC content changes in Hulunbuir from 1980 to 2022"

Table 4

SOC content changes by land use type in Hulunbuir from 1980 to 2022"

土地利用方式
Land use patterns		 1980 SOC
(g·kg-1)		 2022 SOC
(g·kg-1)		 SOC变化
SOC change (g·kg-1)		 变化率
Rate of change (%)		 面积
Area (km2)
农田Farmland 34.64 30.05 -4.59 -13.3% 19815.80
草原Grassland 32.46 26.38 -6.08 -18.7% 122530.40
森林Forest 48.48 37.32 -11.16 -23.0% 95727.30
湿地Wetland 29.53 22.33 -7.20 -24.4% 11461.50

Fig. 6

The relative importance of environmental factors on SOC content in Hulunbuir in 1980 and 2022 TEM: Temperature; PRE: Precipitation; NDVI: Normalized Vegetation Index; Dem: Elevation; Slope: The slope"

Fig. 7

Land use patterns and changes in Hulunbuir in the late 1980s and 2022"

Fig. 8

Spatial distribution of SOC content changes in Hulunbuir"

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