湟水河流域耕地土壤团聚体有机碳空间变异特征及其驱动因素分析

doi:10.16258/j.cnki.1674-5906.2025.11.005

生态环境学报 ›› 2025, Vol. 34 ›› Issue (11): 1715-1727.DOI: 10.16258/j.cnki.1674-5906.2025.11.005

湟水河流域耕地土壤团聚体有机碳空间变异特征及其驱动因素分析

孔小云¹^,²(), 张永坤¹^,^*(), 李润杰¹, 李颖¹, 林成清¹^,², 马占明¹^,², 辛继林¹^,², 杨晓璇¹^,², 党怡乐¹^,², 赵家艺¹, 冯玲正³, 周燕³

1.青海大学/三江源生态与高原农牧业国家重点实验室，青海西宁 810016
2.青海大学农牧学院，青海西宁 810016
3.青海省国土整治与生态修复中心，青海西宁 810016

收稿日期:2024-11-14 出版日期:2025-11-18 发布日期:2025-11-05
通讯作者: *E-mail: zhangyongkun321@163.com
作者简介:孔小云（2000年生），女（彝族），硕士研究生，主要从事土壤生态学等研究。E-mail: kongxiaoyun001@163.com
基金资助:
国家自然科学基金项目(42207375);国家自然科学基金项目(2024-SF-148)

Characteristics of Spatial Variation of Organic Carbon in Cultivated Soil Aggregates in Huangshui River Basin and Analysis of Its Driving Factors

KONG Xiaoyun¹^,²(), ZHANG Yongkun¹^,^*(), LI Runjie¹, LI Ying¹, LIN Chengqing¹^,², MA Zhanming¹^,², XIN Jilin¹^,², YANG Xiaoxuan¹^,², DANG Yile¹^,², ZHAO Jiayi¹, FENG Lingzheng³, ZHOU Yan³

1. State Key Laboratory of Sanjiangyuan Ecology and Plateau Agriculture and Animal Husbandry/Qinghai University, Xining 810016, P. R. China
2. College of Agriculture and Animal Husbandry, Qinghai University, Xining 810016, P. R. China
3. Qinghai Provincial Land Rectification and Ecological Restoration Centre, Xining 810016, P. R. China

Received:2024-11-14 Online:2025-11-18 Published:2025-11-05

摘要/Abstract

摘要：

土壤团聚体作为土壤的基本单元，其形成和稳定与土壤有机碳密切相关。以青藏高原东北部的湟水河流域为研究区域，布设84个耕地样点，采集0－20 cm和20－40 cm土层的土样进行耕地土壤有机碳、土壤团聚体组分及其内相关有机碳的测定，综合土壤理化因素及地理环境因子的半方差函数、克里金插值和偏最小二乘结构方程模型分析其空间变化特征，识别影响其空间分布特征的主控因子并进行评价。结果表明：1）该流域内土壤团聚体表现出中等程度的变异性，土壤有机碳表现出较高的变异性；2）地统计学分析表明，随团聚体粒径变小（由大团聚体、微团聚体变为粉黏粒），土壤团聚体组分及其内有机碳的基台值相应变小，空间自相关性相应变弱；3）克里金插值结果表明，土壤团聚体组分及其内有机碳的空间分布格局大致相似，总体从西北往东南部递减；4）结合Spearman’s相关性分析和偏最小二乘结构方程模型，发现土壤和地形因素是湟水流域耕地土壤团聚体组分及其有机碳空间变异最重要的直接和间接驱动因素。其中，土壤质地是影响土壤团聚体及其有机碳空间变异的最重要控制因素，地形因子通过土壤因子对团聚体有机碳具有最主要的间接效应，这种影响随着土壤深度的增加而减弱。在研究湟水河流域耕地土壤团聚体及其有机碳相互作用机制的基础上，分析它们的空间异质性及其驱动因素，可为高寒农牧区防止土壤退化、维持耕地生产力以及对区域生态环境效应评估与管理提供一定的理论依据。

关键词: 湟水河, 土壤团聚体, 有机碳, 空间变异, 影响因素

Abstract:

As the basic unit of soil, the formation and stability of soil aggregates are closely related to soil organic carbon (SOC) content. Previous studies have mainly focused on the spatial variation characteristics and driving factors of a single soil aggregate or organic carbon. Few studies have investigated the spatial variation characteristics of all soil aggregate components and their associated organic carbon and analyzed the main driving factors. Therefore, in this study, the Huangshui River Basin in the northeastern part of the Tibetan Plateau was selected as the study area, and 84 arable land sample sites were established. Soil samples were collected from the 0‒20 cm and 20‒40 cm soil horizons to determine arable land soil organic carbon, soil aggregate fractions, and their related organic carbon. The half-variance function, kriging interpolation, and bias-variance function were used to integrate the soil physicochemical and geographic environmental factors. The spatial variation characteristics were analyzed using the half-variance function, Kriging interpolation, and partial least squares structural equation model, and the main controlling factors affecting the spatial distribution characteristics were identified and evaluated. The results of the study showed that 1) soil aggregates in the watershed showed moderate variability, whereas soil organic carbon showed high variability. 2) Geostatistical analyses showed that as the particle size of aggregates decreased (from macro-aggregates and micro-aggregates to powdery and sticky grains), the abutment values of soil aggregate fractions and the organic carbon within them decreased, and spatial autocorrelation weakened. 3) The kriging interpolation results indicated that the spatial distribution patterns of soil aggregate fractions and organic carbon were similar, generally decreasing from the northwest to the southeast region. 4) Combined with Spearman’s correlation analysis and partial least squares structural equation model, we found that soil and topographic factors are the most important direct and indirect driving factors for the spatial variability of soil aggregate fractions and organic carbon in cultivated land in the Huangshui Basin. Among them, soil texture was the most important control factor affecting the spatial variability of soil aggregates and their organic carbon, and topographic factors had the most important indirect effect on the organic carbon of aggregates through soil factors, which weakened with the increasing soil depth. Therefore, the study of Huangshui River Basin cultivated land in the soil agglomerates and their organic carbon interaction mechanism on the basis of the analysis of their spatial heterogeneity and its driving factors, alpine agriculture, and animal husbandry areas to prevent soil degradation, optimize the land management and maintenance of arable land productivity, regional ecological and environmental effects of the assessment and management to provide a certain theoretical basis.

Key words: Huangshui River, soil aggregates, organic carbon, spatial variability, influencing factor

中图分类号:

孔小云, 张永坤, 李润杰, 李颖, 林成清, 马占明, 辛继林, 杨晓璇, 党怡乐, 赵家艺, 冯玲正, 周燕. 湟水河流域耕地土壤团聚体有机碳空间变异特征及其驱动因素分析[J]. 生态环境学报, 2025, 34(11): 1715-1727.

KONG Xiaoyun, ZHANG Yongkun, LI Runjie, LI Ying, LIN Chengqing, MA Zhanming, XIN Jilin, YANG Xiaoxuan, DANG Yile, ZHAO Jiayi, FENG Lingzheng, ZHOU Yan. Characteristics of Spatial Variation of Organic Carbon in Cultivated Soil Aggregates in Huangshui River Basin and Analysis of Its Driving Factors[J]. Ecology and Environmental Sciences, 2025, 34(11): 1715-1727.

图/表 9

参考文献 40

[4]	DENG L, KIM D G, PENG C H, et al., 2018. Controls of soil and aggregate-associated organic carbon variations following natural vegetation restoration on the Loess Plateau in China[J]. Land Degradation & Development, 29(11): 3974-3984. DOI URL
[5]	HU J, HARTEMINK A E, DESAI A R, et al., 2023. A continental-scale estimate of soil organic carbon change at neon sites and their environmental and edaphic controls[J]. Journal of Geophysical Research: Biogeosciences, 128(5): e2022JG006981.
[6]	JOZEDAEMI E, GOLCHIN A, 2024. Changes in aggregate-associated carbon and microbial respiration affected by aggregate size, soil depth, and altitude in a forest soil[J]. Catena, 234: 107567. DOI URL
[7]	LI J Y, CHEN P, LI Z G, 2023. Soil aggregate-associated organic carbon mineralization and its drivingfactors in rhizosphere soil[J]. Soil Biology and Biochemistry, 186: e109182.
[8]	LINSLER D, GEISSELER D, LOGES R, et al., 2013. Temporal dynamics of soil organic matter composition and aggregate distribution in permanent grassland after a single tillage event in a temperate climate[J]. Soil and Tillage Research, 126(1): 90-99. DOI URL
[9]	MARTENS D A, REEDY T E, LEWISD T, 2004. Soilorganic carbon content and composition of 130-yearcrop, pasture and forest land-use managements[J]. Global Change Biology, 10(1): 65-78. DOI URL
[10]	NIELSEN D R, Th. VAN G M, BIGGAR J W, 1986. Water flow and solute transport processes in the unsaturated zone[J]. Water Resources Research, 22(9S): 89S-108S.
[11]	PENG X Y, HUANG Y, DUAN X W, et al., 2023. Particulate and mineral-associated organic carbon fractions reveal the roles of soil aggregates under different land-use types in a karst faulted basin of China[J]. Catena, 220(PartB): 106721.
[12]	QIAO L L, ZHOU H K, WANG Z H, et al., 2023. Variations in soil aggregate stability and organic carbon stability of alpine meadow and shrubland under long-term warming[J]. Catena, 222: 106848. DOI URL
[13]	ROWTHER T W, TODD-BROWN K E O, ROWE C W, et al., 2016. Quantifying global soil carbon losses in response to warming[J]. Nature, 540(7631): 104-108. DOI
[14]	SIX J, CONANT R T, PAUL E A, et al., 2002. Stabilization mechanisms of soil organic matter: Implications for C-saturation of soils[J]. Plant and Soil, 241: 155-176. DOI
[15]	SIX J, ELLIOT E T, PAUSTAIN K, et al., 2016. Aggregation and soil organic matter accumulation in cultivated and native grassland soils[J]. Soil Science Society of America Journal, 62(5): 1367-1377. DOI URL
[16]	SUN S B, SONG Z L, CHEN B Z, et al., 2023. Current and future potential soil organic carbon stocks of vegetated coastal ecosystems and their controls in the Bohai Rim Region, China[J]. Catena, 225: 107023. DOI URL
[17]	WANG B, GONG Z Q, MENG M, et al., 2022. The soil aggregates and associated organic carbon across the Greater Khingan Mountains: Spatial patterns and impacting factors[J]. Forests, 13(8): 1267.
[18]	WRIGHT S F, UPADHYAYA A, 1998. A survey of soils for aggregate stability and glomalin, a glycoprotein produced by hyphae of arbuscular mycorrhizal fungi[J]. Plant and Soil, 198(1): 97-107. DOI
[19]	WEN L, LI D J, XIAO K C, et al., 2023. Dynamics of aggregate-associated organic carbon after long-term cropland conversion in a karst region, southwest China[J]. Scientific Reports, 13(1): 1773.
[20]	XIN Z B, QIN Y B, YU X X, 2016. Spatial variability in soil organic carbon and its influencing factors in a hilly watershed of the Loess Plateau, China[J]. Catena, 137: 660-669. DOI URL
[21]	ZHANG J, TANG X L, HE X H, et al., 2015. Glomalin-related soil protein responses to elevated CO₂ and nitrogen addition in a subtropical forest: Potential consequences for soil carbon accumulation[J]. Soil Biology and Biochemistry, 83: 142-149. DOI URL
[1]	CAMBARDELLA C A, ELLIOTT E T, 1992. Particulate soil organic-matter changes across a grassland cultivation sequence[J]. Soil Science Society of America Journal, 56(3): 777-783. DOI URL
[2]	CAMBARDELLA C A, MOORMAN T B, NOVAK J M, et al., 1994. Field-scale variability of soil properties in Central Iowa soils[J]. Soil Science Society of America Journal, 58(5): 1501-1511. DOI URL
[3]	CHAOLOT V, BOUAHOM B, VALENTIN C, 2010. Soil organic carbon stocks in Laos: spatial variations and controlling factors[J]. Global Change Biology, 16(4): 1380-1393. DOI URL
[22]	ZHANG P P, WANG Y Q, XU L, et al., 2021. Factors controlling spatial variation in soil aggregate stability in a semi-humid watershed[J]. Soil and Tillage Research, 214: 105187. DOI URL
[23]	代子俊, 2018. 近30年湟水流域土壤养分时空变异及影响因素[D]. 西宁: 青海师范大学.
	DAI Z J, 2018. Spatial and temporal variability of soil nutrients and influencing factors in Huangshui watershed in the last 30 years[D]. Xining: Qinghai Normal University.
[24]	刘尊方, 雷浩川, 雷蕾, 等, 2022. 湟水流域土壤有机质和速效磷空间布局分析[J]. 科学技术与工程, 22(34): 15095-15102.
	LIU Z F, LEI H C, LEI L, et al., 2022. Spatial layout analysis of soil organic matter and quick-acting phosphorus in Huangshui Basin[J]. Science and Technology and Engineering, 22(34): 15095-15102.
[25]	刘亚龙, 王萍, 汪景宽, 等, 2023. 土壤团聚体的形成和稳定机制: 研究进展与展望[J]. 土壤学报, 60(3): 627-643.
	LIU Y L, WANG P, WANG J K, et al., 2023. Formation and stabilization mechanisms of soil aggregates: Research advances and prospects[J]. Acta Pedologica Sinica, 60(3): 627-643.
[26]	鲁如坤, 2000. 土壤农业化学分析方法[M]. 北京: 中国农业科技出版社: 106-107.
	LU R K, 2000. Methods of agrochemical analysis of soils[M]. Beijing: China Agricultural Science and Technology Press: 106-107.
[27]	林成清, 李润杰, 盛海彦, 等, 2025. 湟水流域耕地表层土壤有机碳空间分布及其驱动因素分析[J]. 西南农业学报, 38(1): 135-144.
	LIN C Q, LI R J, SHENG H Y, et al., 2025. Spatial distribution of soil organic carbon in the surface layer of arable land in Huangshui Basin and analysis of its driving factors[J]. Southwest Journal of Agriculture, 38(1): 135-144.
[28]	马东方, 袁再健, 吴新亮, 等, 2020. 华南花岗岩侵蚀区不同植被类型坡面土壤有机碳分布和团聚体稳定性[J]. 水土保持学报, 34(5): 137-144.
	MA D F, YUAN Z J, WU X L, et al., 2020. Distribution of soil organic carbon and stability of clusters on slopes with different vegetation types in a granitic erosion zone in south China[J]. Journal of Soil and Water Conservation, 34(5): 137-144.
[29]	宋文婕, 梁誉正, 陶贞, 等, 2023. 微生物介导的土壤有机碳动态研究进展[J]. 地球科学进展, 38(12): 1213-1223. DOI
	SONG W J, LIANG Y C, TAO Z, et al., 2023. Progress in microbially mediated soil organic carbon dynamics[J]. Advances in Earth Sciences, 38(12): 1213-1223.
[30]	吴林甲, 祁琛, 闫秋艳, 等, 2023. 耕作方式对旱地麦田土壤团聚体及其碳氮组分分布的影响[J]. 干旱地区农业研究, 41(2): 193-200, 220.
	WU L J, QI C, YAN Q Y, et al., 2023. Effects of tillage practices on soil aggregates and their carbon and nitrogen fractions distribution in dryland wheat fields[J]. Agricultural Research in Arid Regions, 41(2): 193-200, 220.
[31]	王兴, 钟泽坤, 张欣怡, 等, 2020. 长期撂荒恢复土壤团聚体组成与有机碳分布关系[J]. 环境科学, 41(5): 2416-2424.
	WANG X, ZHONG Z K, ZHANG X Y, et al., 2020. Relationship between soil aggregate composition and organic carbon distribution in long-term abandonment and restoration[J]. Environmental Science, 41(5): 2416-2424.
[32]	徐佩, 王玉宽, 邓玉林, 等, 2007. 岷江流域不同土地利用方式下紫色土有机碳储量特征[J]. 应用与环境生物学报, 13(2): 205-208.
	XU P, WANG Y K, DENG Y L, et al., 2007. Characteristics of organic carbon storage in purple soils under different land use modes in Minjiang River Basin[J]. Journal of Applied and Environmental Biology, 13(2): 205-208.
[33]	杨璐, 刘小芳, 巨佳敏, 等, 2024. 黄土坡面种植柠条对土壤团聚体稳定性和可蚀性的影响[J]. 水土保持通报, 44(3): 46-55.
	YANG L, LIU X F, JU J M, et al., 2024. Effects of planting lemons on soil aggregate stability and erodibility on loess slopes[J]. Soil and Water Conservation Bulletin, 44(3): 46-55.
[34]	叶露萍, 2020. 黄土高原土壤团聚体-水-植被的时空变异分析[D]. 杨凌: 中国科学院教育部水土保持与生态环境研究中心.
	YE L P, 2020. Analysis of spatial and temporal variability of soil aggregates-water-vegetation in the Loess Plateau[D]. Yangling: Soil and Water Conservation and Ecological Environment Research Centre, Ministry of Education, Chinese Academy of Sciences.
[35]	于雯霏, 王佩佩, 刘俊娥, 等, 2023. 黄土高原典型植被根系对土壤团聚体及其有机碳组分的影响[J]. 水土保持学报, 37(6): 246-254.
	YU W F, WANG P P, LIU J E, et al., 2023. Effects of typical vegetation root systems on soil aggregates and their organic carbon fractions in the Loess Plateau[J]. Journal of Soil and Water Conservation, 37(6): 246-254.
[36]	张旭冉, 张卫青, 等, 2020. 土壤团聚体研究进展[J]. 北方园艺, 44(21): 131-137.
	ZHANG X R, ZHANG W Q, et al., 2020. Progress of soil agglomerate research[J]. Northern Horticulture, 44(21): 131-137.
[37]	赵金花, 张丛志, 张佳宝, 等, 2015. 农田生态系统中土壤有机碳与团聚体相互作用机制的研究进展[J]. 中国农学通报, 31(35): 152-157. DOI
	ZHAO J H, ZHANG C Z, ZHANG J B, et al., 2015. Research progress on the interaction mechanism between soil organic carbon and clusters in agroecosystems[J]. Chinese Agronomy Bulletin, 31(35): 152-157.
[38]	朱锟恒, 段良霞, 李元辰, 等, 2021. 土壤团聚体有机碳研究进展[J]. 中国农学通报, 37(21): 86-90. DOI
	ZHU K H, DUAN L X, LI Y C, et al., 2021. Progress of organic carbon research in soil aggregates[J]. Chinese Agronomy Bulletin, 37(21): 86-90.
[39]	邹萌萌, 周卫红, 张静静, 等, 2019. 我国东部地区农田土壤重金属污染概况[J]. 中国农业科技导报, 21(1): 117-124.
	ZOU M M, ZHOU W H, ZHANG J J, et al., 2019. Overview of heavy metal contamination in farmland soils in the eastern region of China[J]. China Agricultural Science and Technology Guide, 21(1): 117-124.
[40]	周家昊, 褚军杰, 孙万春, 等, 2023. 有机碳对土壤团聚体形成的影响研究进展[J]. 河南农业科学, 52(11): 10-20.
	ZHOU J H, CHU J J, SUN W C, et al., 2023. Progress of research on the effect of organic carbon on soil aggregate formation[J]. Henan Agricultural Science, 52(11): 10-20.

土壤深度/cm	变量	最小值	最大值	平均值	标准差	变异系数	偏度	峰度	DT
0‒20	P_MA/%	22.87	80.17	49.08b	11.74	23.92	0.24	0.20	N
	P_MI/%	9.00	65.01	36.50a	9.90	27.12	0.07	0.98	N
	P_SC/%	4.93	25.63	14.42c	3.98	27.60	0.72	1.61	NN
	SOC_MA/（g∙kg⁻¹）	3.49	67.01	22.06a	12.10	54.85	2.58	7.71	NN
	SOC_MI/（g∙kg⁻¹）	4.42	62.46	14.21c	9.44	66.43	2.90	11.73	NN
	SOC_SC/（g∙kg⁻¹）	0.35	43.62	16.35b	8.11	49.60	0.59	1.55	NN
	SOC_Bulk/（g∙kg⁻¹）	4.97	40.14	17.80b	6.41	36.01	1.19	3.31	NN
20‒40	P_MA/%	29.08	74.78	46.94b	10.47	22.30	0.16	-0.27	N
	P_MI/%	11.07	54.69	37.56a	9.11	24.25	-0.06	0.53	N
	P_SC/%	8.37	38.12	15.49c	4.66	30.08	2.46	11.28	NN
	SOC_MA/（g∙kg⁻¹）	4.44	50.20	17.42a	8.12	46.61	1.69	5.33	NN
	SOC_MI/（g∙kg⁻¹）	4.78	37.01	13.55c	6.28	46.35	1.70	3.57	NN
	SOC_SC/（g∙kg⁻¹）	2.47	33.24	16.21b	6.57	40.53	0.55	0.29	N
	SOC_Bulk/（g∙kg⁻¹）	3.06	67.01	16.45b	9.64	58.60	3.30	16.21	NN

土壤深度/cm	变量	最小值	最大值	平均值	标准差	变异系数	偏度	峰度	DT
0‒20	P_MA/%	22.87	80.17	49.08b	11.74	23.92	0.24	0.20	N
	P_MI/%	9.00	65.01	36.50a	9.90	27.12	0.07	0.98	N
	P_SC/%	4.93	25.63	14.42c	3.98	27.60	0.72	1.61	NN
	SOC_MA/（g∙kg⁻¹）	3.49	67.01	22.06a	12.10	54.85	2.58	7.71	NN
	SOC_MI/（g∙kg⁻¹）	4.42	62.46	14.21c	9.44	66.43	2.90	11.73	NN
	SOC_SC/（g∙kg⁻¹）	0.35	43.62	16.35b	8.11	49.60	0.59	1.55	NN
	SOC_Bulk/（g∙kg⁻¹）	4.97	40.14	17.80b	6.41	36.01	1.19	3.31	NN
20‒40	P_MA/%	29.08	74.78	46.94b	10.47	22.30	0.16	-0.27	N
	P_MI/%	11.07	54.69	37.56a	9.11	24.25	-0.06	0.53	N
	P_SC/%	8.37	38.12	15.49c	4.66	30.08	2.46	11.28	NN
	SOC_MA/（g∙kg⁻¹）	4.44	50.20	17.42a	8.12	46.61	1.69	5.33	NN
	SOC_MI/（g∙kg⁻¹）	4.78	37.01	13.55c	6.28	46.35	1.70	3.57	NN
	SOC_SC/（g∙kg⁻¹）	2.47	33.24	16.21b	6.57	40.53	0.55	0.29	N
	SOC_Bulk/（g∙kg⁻¹）	3.06	67.01	16.45b	9.64	58.60	3.30	16.21	NN

土壤深度/cm	变量	半方差	块金值C₀	基台值C₀+C	变程/m	块金系数/%	决定系数R²	残差RSS	Moran’s I
土壤深度/cm	变量	半方差	块金值C₀	基台值C₀+C	变程/m	块金系数/%	决定系数R²	残差RSS	Value	p
0‒20	P_MA	Gaussian	0.0001	0.0597	2780	1.67	0.954	0.0001	0.03	0.469
	P_MI	Gaussian	0.0010	0.5410	2610	0.18	0.844	0.0446	0.01	0.735
	P_SC	Gaussian	0.0001	0.0408	1960	0.24	0.915	0.00002	0.18	0.009
	SOC_MA	Gaussian	0.0314	0.3238	5480	9.70	0.708	0.028	−0.005	0.918
	SOC_MI	Spherical	0.0066	0.3052	12500	2.16	0.730	0.0009	0.10	0.125
	SOC_SC	Exponential	0.0021	0.0316	7700	6.64	0.772	0.00003	0.20	0.003
	SOC_Bulk	Spherical	0.0010	0.7200	11900	0.14	0.515	0.0135	0.16	0.021
20‒40	P_MA	Gaussian	0.3500	0.7440	5940	47.04	0.600	0.0797	0.14	0.004
	P_MI	Gaussian	0.0117	0.1020	22490	11.47	0.842	0.00003	0.02	0.646
	P_SC	Gaussian	0.0107	0.0266	5600	40.22	0.517	0.0001	0.24	0.001
	SOC_MA	Spherical	0.0310	0.9630	12500	3.22	0.453	0.0431	0.002	0.850
	SOC_MI	Exponential	0.0850	0.7540	7100	11.27	0.553	0.056	0.10	0.144
	SOC_SC	Spherical	0.0170	0.0465	30000	36.56	0.783	0.0001	0.25	0.007
	SOC_Bulk	Gaussian	0.0358	0.3126	7600	11.45	0.831	0.0021	0.25	0.001

土壤深度/cm	变量	半方差	块金值C₀	基台值C₀+C	变程/m	块金系数/%	决定系数R²	残差RSS	Moran’s I
土壤深度/cm	变量	半方差	块金值C₀	基台值C₀+C	变程/m	块金系数/%	决定系数R²	残差RSS	Value	p
0‒20	P_MA	Gaussian	0.0001	0.0597	2780	1.67	0.954	0.0001	0.03	0.469
	P_MI	Gaussian	0.0010	0.5410	2610	0.18	0.844	0.0446	0.01	0.735
	P_SC	Gaussian	0.0001	0.0408	1960	0.24	0.915	0.00002	0.18	0.009
	SOC_MA	Gaussian	0.0314	0.3238	5480	9.70	0.708	0.028	−0.005	0.918
	SOC_MI	Spherical	0.0066	0.3052	12500	2.16	0.730	0.0009	0.10	0.125
	SOC_SC	Exponential	0.0021	0.0316	7700	6.64	0.772	0.00003	0.20	0.003
	SOC_Bulk	Spherical	0.0010	0.7200	11900	0.14	0.515	0.0135	0.16	0.021
20‒40	P_MA	Gaussian	0.3500	0.7440	5940	47.04	0.600	0.0797	0.14	0.004
	P_MI	Gaussian	0.0117	0.1020	22490	11.47	0.842	0.00003	0.02	0.646
	P_SC	Gaussian	0.0107	0.0266	5600	40.22	0.517	0.0001	0.24	0.001
	SOC_MA	Spherical	0.0310	0.9630	12500	3.22	0.453	0.0431	0.002	0.850
	SOC_MI	Exponential	0.0850	0.7540	7100	11.27	0.553	0.056	0.10	0.144
	SOC_SC	Spherical	0.0170	0.0465	30000	36.56	0.783	0.0001	0.25	0.007
	SOC_Bulk	Gaussian	0.0358	0.3126	7600	11.45	0.831	0.0021	0.25	0.001

土壤深度/cm	变量	地形因素
土壤深度/cm	变量	直接	间接	总	直接	间接	总	直接	间接	总
0−20	P_MA	0.107	0.400	0.507	0.030	−0.064	−0.034	0.320	−0.074	0.246
	P_MI	0.205	−0.531	−0.326	−0.084	−0.096	−0.180	−0.281	0.041	−0.240
	P_SC	−0.280	−0.307	−0.587	−0.151	0.052	−0.099	−0.294	0.080	−0.214
	SOC_MA	−0.036	−0.150	−0.186	−0.076	−0.013	−0.063	0.035	−0.011	0.024
	SOC_MI	−0.018	0.617	0.599	−0.232	−0.031	−0.263	0.034	−0.024	0.010
	SOC_SC	0.049	0.521	0.570	0.321	0.037	0.358	−0.090	0.037	−0.053
	SOC_Bulk	0.023	0.694	0.717	0.308	−0.067	0.241	−0.070	−0.037	−0.107
20−40	P_MA	0.025	0.363	0.388	0.027	0.046	0.073	0.008	−0.117	−0.109
	P_MI	0.202	−0.475	−0.273	−0.050	−0.060	−0.110	−0.009	0.155	0.146
	P_SC	−0.454	−0.032	−0.486	0.024	−0.004	0.020	0.005	0.008	0.013
	SOC_MA	0.156	0.081	0.237	0.207	−0.011	0.196	−0.210	−0.008	−0.218
	SOC_MI	0.055	0.562	0.617	0.091	0.069	0.160	0.064	−0.027	0.037
	SOC_SC	0.061	0.513	0.574	0.318	0.037	0.355	−0.102	0.051	−0.051
	SOC_Bulk	−0.032	0.749	0.717	0.305	−0.063	0.242	−0.030	−0.078	−0.108

湟水河流域耕地土壤团聚体有机碳空间变异特征及其驱动因素分析

Characteristics of Spatial Variation of Organic Carbon in Cultivated Soil Aggregates in Huangshui River Basin and Analysis of Its Driving Factors

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