呼伦贝尔土壤有机碳时空变异特征及其影响因素

doi:10.3864/j.issn.0578-1752.2025.06.008

中国农业科学 ›› 2025, Vol. 58 ›› Issue (6): 1145-1158.doi: 10.3864/j.issn.0578-1752.2025.06.008

• 土壤肥料·节水灌溉·农业生态环境 • 上一篇下一篇

呼伦贝尔土壤有机碳时空变异特征及其影响因素

吴欣珈¹(), 薛玮², 严翊丹¹, 聂莹莹¹, 叶立明³, 徐丽君¹()

¹ 北方干旱半干旱耕地高效利用全国重点实验室/中国农业科学院农业资源与农业区划研究所/内蒙古呼伦贝尔草原生态系统国家野外科学观测研究站，中国北京 100081
² 云南省西双版纳傣族自治州气象局，中国云南西双版纳 666100
³ 根特大学地质系，比利时根特 9000

收稿日期:2024-05-14 接受日期:2024-11-11 出版日期:2025-03-25 发布日期:2025-03-25
通信作者:
徐丽君，E-mail：xulijun@caas.cn
联系方式: 吴欣珈，E-mail：15975592102@163.com。
基金资助:
国家自然科学基金面上项目(22378422)

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 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 Published:2025-03-25 Online:2025-03-25

摘要/Abstract

摘要：

【目的】分析中国呼伦贝尔土壤有机碳（SOC）含量的时空分布特征及其驱动因素，以期为土壤碳储量管理和生态系统服务提供科学依据。【方法】采用点对点采样调查方法，收集1980年（历史数据）和2022年的土壤有机碳实测数据，涉及农田、草原、森林和湿地4种土地利用类型。利用回归克里金方法，结合温度、降水、坡度、海拔和归一化植被指数（NDVI）等环境变量，对SOC含量及其变化进行空间预测。【结果】（1）1980年SOC含量受这5个因子显著影响（P<0.05），而2022年SOC含量主要受海拔、坡度、降水量和NDVI的显著影响，温度影响不显著（P=0.07）。两个时期的模型拟合精度分别为R²=0.60和R²=0.63，表明预测模型具有一定的可靠性。（2）空间预测数据显示，1980年呼伦贝尔SOC平均含量为40.29 g·kg^-1，而2022年降为31.75 g·kg^-1。两个时期土壤SOC含量在空间上的变化趋势相似，表现为中部地区含量较高，西部和东部地区含量较低。（3）不同土地利用方式下SOC含量的变化存在差异。近40年间，农田、草原、森林和湿地土壤的SOC含量分别下降了4.59 g·kg^-1（13.3%）、6.08 g·kg^-1（18.7%）、11.16 g·kg^-1（23.0%）和7.20 g·kg^-1（24.4%）。【结论】呼伦贝尔地区SOC含量的空间分布，1980年与2022年保持一致，且不同土地利用方式下的SOC含量均呈现下降趋势。土地利用方式的转变是影响SOC空间分布变化的关键因素。此外，环境变量对SOC变化的预测存在不确定性，未来的研究需考虑其动态变化特性。在呼伦贝尔地区，森林-草原过渡带和森林-农田过渡带具有碳汇潜力，而草原、中部高海拔森林区域和农田区域则可能是碳源区域。

关键词: 土壤有机碳, 时空变异, 土地利用方式, 回归克里金插值, 广义加性模型, 呼伦贝尔

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

吴欣珈, 薛玮, 严翊丹, 聂莹莹, 叶立明, 徐丽君. 呼伦贝尔土壤有机碳时空变异特征及其影响因素[J]. 中国农业科学, 2025, 58(6): 1145-1158.

WU XinJia, XUE Wei, YAN YiDan, NIE YingYing, YE LiMing, XU LiJun. Temporal and Spatial Variation Characteristics of Soil Organic Carbon in Hulunbuir and Its Influencing Factors[J]. Scientia Agricultura Sinica, 2025, 58(6): 1145-1158.

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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

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

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

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

呼伦贝尔土壤有机碳时空变异特征及其影响因素

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

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