青海高寒草地水热因子对土壤微生物生物量碳、氮空间变异的贡献——基于增强回归树模型

doi:10.16258/j.cnki.1674-5906.2023.07.004

生态环境学报 ›› 2023, Vol. 32 ›› Issue (7): 1207-1217.DOI: 10.16258/j.cnki.1674-5906.2023.07.004

青海高寒草地水热因子对土壤微生物生物量碳、氮空间变异的贡献——基于增强回归树模型

陈懂懂¹(), 霍莉莉², 赵亮¹, 陈昕³, 舒敏¹^,⁴, 贺福全¹, 张煜坤¹, 张莉¹, 李奇¹^,^*()

1.青海三江源草地生态系统国家野外科学观测研究站/中国科学院三江源国家公园研究院/高原生物适应与进化重点实验室/中国科学院西北高原生物研究所，青海西宁 810008
2.青海省青海湖景区保护利用管理局，青海西宁 810000
3.中央民族大学，北京 100081
4.中国科学院大学，北京 100049

收稿日期:2023-03-28 出版日期:2023-07-18 发布日期:2023-09-27
通讯作者: * 李奇。E-mail: liqi@nwipb.cas.cn
作者简介:陈懂懂（1982年生），女，高级工程师，博士，研究方向为草地生态学，土壤生态学。E-mail:chendd@nwipb.cas.cn
基金资助:
青海省基础研究项目(2021-ZJ-761);第二次青藏高原综合科学考察研究项目(2019QZKK0302);科技基础资源调查专项(2021FY100705)

Contribution of Water and Heat Factors to Spatial Variability of Soil Microbial Biomass Carbon and Nitrogen in Qinghai Alpine Grassland: Based on Enhanced Regression Tree Model

CHEN Dongdong¹(), HUO Lili², ZHAO Liang¹, CHEN Xin³, SHU Min¹^,⁴, HE Fuquan¹, ZHANG Yukun¹, ZHANG Li¹, LI Qi¹^,^*()

1. Sanjiangyuan Grassland Ecosystem National Observation and Research Station/Institute of Sanjiangyuan National Park/Key Laboratory of Adaptation and Evolution of Plateau Biota/Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810008, P. R. China
2. Qinghai Lake Protection and Utilization Administration Bureau of Qinghai Province, Xining 810000, P. R. China
3. Minzu University of China, Beijing 100081, P. R. China
4. Graduate University of Chinese Academy of Sciences, Beijing 100049, P. R. China

Received:2023-03-28 Online:2023-07-18 Published:2023-09-27

摘要/Abstract

摘要：

由于环境因子之间的互相干扰，土壤微生物生物量碳、氮及其影响因子之间的关系研究存在着不同的结论，亟需在不同的生态系统中加强研究。为探究青海高寒草地生长季土壤微生物生物量动态，以及水热因子对其空间变化的相对贡献，在青海三江源草地生态系统国家野外科学观测研究站设置的监测样地进行了相关研究。结果显示：（1）位于青海省中西部的高寒草原，尤其是可可西里地区土壤微生物生物量最低，而高寒草甸、高寒草甸草原和温性草原则相对较高；（2）不同区域土壤微生物生物量碳、氮存在不同的季节动态，青海省中西部与东部区域表现出明显不同的变化趋势；（3）利用增强回归树模型定量评估水（土壤含水量、空气相对湿度、降雨量、实际蒸散发）、热（土壤温度、气温、净辐射）因子对微生物生物量变化的相对贡献，发现：与其他水热因子相比，对微生物生物量碳、氮影响最大的为土壤含水量（P=0.000）和土壤温度（P=0.000），且均为正相关。在土壤垂直梯度上，水分因子（63.58%-76.62%）对微生物生物量变化的影响均大于热量因子（23.38%-36.42%），且其贡献随土层加深呈下降趋势。从不同研究区看，东中部区域对土壤微生物生物量变异贡献较大的是热量因子（52.11%-81.84%），而到西部区域，则为水分因子（66.33%-95.19%）控制着微生物生物量的变化。结论：青海高寒草甸、高寒草甸草原和温性草原的土壤微生物生物量明显高于高寒草原；土壤含水量和土壤温度是控制土壤微生物生物量变异的主要因子；对土壤微生物生物量变异的影响，在区域上从东到西呈现从热量因子向水分因子的过度。该研究为探究在气候变化大背景下青海高寒草地土壤碳氮循环规律及其影响因素提供参考。

关键词: 青藏高原, 三江源, 高寒草地, 土壤微生物生物量, 土壤含水量, 土壤温度

Abstract:

Owing to the interactions between environmental factors, different conclusions can be drawn about the relationships among soil microbial biomass carbon, nitrogen, and their influencing factors. Thus, it is important to increase research in different ecosystems. To explore the dynamics of soil microbial biomass during the growing season in the Qinghai alpine grassland and the relative contribution of water and heat factors to spatial changes in soil microbial biomass, we conducted studies on the plots set up by the Sanjiangyuan Grassland Ecosystem National Observation and Research Station. The results showed that: (1) The alpine steppes located in the central and western regions of Qinghai Province, especially the Hoh Xil region, had the lowest microbial biomass, while there was relatively high microbial biomass in alpine meadow, alpine meadow steppe, and warm steppe. (2) The seasonal dynamics of soil microbial biomass carbon and nitrogen varied in different regions, and the central western and eastern regions of Qinghai Province exhibited significantly different trends. (3) Using an enhanced regression tree model to quantitatively evaluate the relative contributions of water (soil water content, relative humidity of air, precipitation, and evapotranspiration) and heat (soil temperature, air temperature, and net radiation) factors to microbial biomass changes, it was found that, compared with other water and heat factors, the soil water content (P=0.000) and soil temperature (P=0.000) had the greatest impact on microbial biomass carbon and nitrogen, and both were positively correlated. On the vertical gradient of the soil, the influence of the water factor (63.58%-76.62%) on the change of microbial biomass was greater than that of the heat factor (23.38%-36.42%), but its contribution decreased with depth in the soil layer. Over the whole region, the heat factor (52.11%-81.84%) contributed most to the variation in microbial biomass in the eastern and central regions, while the water factor (66.33%-95.19%) controlled the variation in microbial biomass in the western regions. We conclude that the soil microbial biomass of alpine meadow, alpine meadow steppe, and temperate steppe was significantly higher than that of alpine steppe in Qinghai. The soil water content and soil temperature were the main factors controlling variations in soil microbial biomass. The impact of the factors on the variation of soil microbial biomass across the region showed a transition from the heat factor in the east to the water factor in the west. This study provides a reference for exploring the soil carbon nitrogen cycle and its influencing factors in Qinghai alpine grassland in the context of climate change.

Key words: Qinghai-Tibetan Plateau, Sanjiangyuan, alpine grassland, soil microbial biomass, soil water content, soil temperature

中图分类号:

陈懂懂, 霍莉莉, 赵亮, 陈昕, 舒敏, 贺福全, 张煜坤, 张莉, 李奇. 青海高寒草地水热因子对土壤微生物生物量碳、氮空间变异的贡献——基于增强回归树模型[J]. 生态环境学报, 2023, 32(7): 1207-1217.

CHEN Dongdong, HUO Lili, ZHAO Liang, CHEN Xin, SHU Min, HE Fuquan, ZHANG Yukun, ZHANG Li, LI Qi. Contribution of Water and Heat Factors to Spatial Variability of Soil Microbial Biomass Carbon and Nitrogen in Qinghai Alpine Grassland: Based on Enhanced Regression Tree Model[J]. Ecology and Environment, 2023, 32(7): 1207-1217.

图/表 9

参考文献 40

[1]	ALVAREZ R, SANTANATOGLIA O J, GARCÎA R, 1995. Effect of temperature on soil microbial biomass and its metabolic quotient in situ under different tillage systems[J]. Biology and Fertility of Soils, 19: 227-230. DOI URL
[2]	BARDGETT R D, LOVELL R D, HOBBS P J, et al., 1999. Seasonal changes in soil microbial communities along a fertility gradient of temperature grasslands[J]. Soil Biology and Biochemistry, 31: 1021-1030. DOI URL
[3]	BROOKES P C, LANDAM A, PRUDEN G, et al., 1985. Chloroform fumigation and the release of soil nitrogen: A rapid direct extraction method to measure microbial biomass nitrogen in soil[J]. Soil Biology and Biochemistry, 17(6): 837-842. DOI URL
[4]	CHEN D D, LI Q, LI C L, et al., 2022. Density and stoichiometric characteristics of carbon, nitrogen, and phosphorus in surface soil of alpine grassland in Sanjiangyuan[J]. Polish Journal of Environmental Studies, 31(4): 3531-3539. DOI URL
[5]	ELITH J, LEATHWICK J R, HASTIE T, 2008. A working guide to boosted regression trees[J]. Journal of Animal Ecology, 77(4): 802-813. DOI PMID
[6]	FAN J, LIU T, LIAO Y, et al., 2021. Distinguishing Stoichiometric Homeostasis of Soil Microbial Biomass in Alpine Grassland Ecosystems: Evidence From 5,000 km Belt Transect Across Qinghai-Tibet Plateau[J]. Frontiers in Plant Science, 12: 781695. DOI URL
[7]	GARCÎA F O, CHARLES W R, 1994. Microbial biomass dynamics in tallgrass prairie[J]. Soil Science Society of America Journal, 58(3): 816-823. DOI URL
[8]	HU J X, DU M L, CHEN J, et al., 2023. Microbial necromass under global change and implications for soil organic matter[J]. Global Change Biology, 29(12): 3503-3515. DOI PMID
[9]	JILLING A, KEILUWEIT M, CONTOSTA A R, et al., 2018. Minerals in the rhizosphere: overlooked mediators of soil nitrogen availability to plants and microbes[J]. Biogeochemistry, 139(2): 103-122. DOI
[10]	JOERGENSEN R G, MEYER B, MUELLER T, 1994. Time-course of the soil microbial biomass under wheat: A one year field study[J]. Soil Biology and Biochemistry, 26: 987-994. DOI URL
[11]	WANG H, LU Z X, RAGHAVAN A, 2018. Weak dynamical threshold for the “strict homeostasis” assumption in ecological stoichiometry[J]. Ecological Modelling, 384: 233-240. DOI URL
[12]	XU Z Z, HOU Y H, ZHANG L H, et al., 2016. Ecosystem responses to warming and watering in typical and desert steppes[J]. Scientific Reports, 6: 34801. DOI PMID
[13]	van GESTEL N C, DHUGANA N, TISSUE D T, et al., 2016. Seasonal microbial and nutrient responses during a 5-year reduction in the daily temperature range of soil in a Chihuahuan Desert ecosystem[J]. Oecologia, 180(1): 265-277. DOI PMID
[14]	VANCE E D, BROOKES P C, JENKINSON D C, 1987. An extraction method for measuring soil microbial C[J]. Soil Biology and Biochemistry, 19(6): 703-707. DOI URL
[15]	鲍士旦, 2000. 土壤农化分析[M]. 第3版. 北京: 中国农业出版社: 22-24.
	BAO S D, 2000. Soil agricultural chemistry analysis[M]. Third Edition. Beijing: China Agricultural Press: 22-24.
[16]	蔡家艳, 2017. 鄱阳湖湿地土壤微生物碳氮特征及对温度水分变化的响应[D]. 南昌: 江西师范大学:30-31.
	CAI J Y, 2017. Characteristics of soil microbial carbon and nitrogen in Poyang lake wetland and their responses to soil temperature and water change[D]. Nanchang: Jiangxi Normal University:30-31.
[17]	管海英, 赵鑫, 靳佳, 等, 2014. 荒漠生态系统土壤表层微生物量碳空间分布及其影响因子[J]. 干旱区研究, 31(6): 1125-1131.
	GUAN H Y, ZHAO X, JIN J, et al., 2014. Spatial Patterns of soil microbial biomass carbon and factors influencing the distribution in a typical desert ecosystem[J]. Arid Zone Research, 31(6): 1125-1131.
[18]	管海英, 王权, 赵鑫, 等, 2015. 两种典型荒漠植被区土壤微生物量碳的季节变化及影响因素分析[J]. 干旱区地理, 38(1): 67-75.
	GUAN H Y, WANG Q, ZHAO X, et al., 2015. Seasonal patterns of soil microbial biomass C and impacting factors in two typical arid desert vegetation regions[J]. Arid Land Geography, 38(1): 67-75.
[19]	何容, 王国兵, 汪家社, 等, 2009. 武夷山不同海拔植被土壤微生物量的季节动态及主要影响因子[J]. 生态学杂志, 28(3): 394-399.
	HE R, WANG G B, WANG J S, et al., 2009. Seasonal variation and its main affecting factors of soil microbial biomass under different vegetations along an elevation gradient in Wuyi Mountains of China[J]. Chinese Journal of Ecology, 28(3): 394-399.
[20]	何亚婷, 董云社, 齐玉春, 等, 2010. 草地生态系统土壤微生物量及其影响因子研究进展[J]. 地理科学进展, 29(11): 1350-1359. DOI
	HE Y T, DONG Y S, QI Y C, et al., 2010. Advances in researches on soil microbial biomass of grassland ecosystems and its influencing factors[J]. Progress in Geography, 29(11): 1350-1359. DOI
[21]	霍莉莉, 陈懂懂, 李奇, 等, 2022. 三江源地区草地植物功能性状与蒸散发关系研究[J]. 草地学报, 30(8): 2182-2190. DOI
	HUO L L, CHEN D D, LI Q, et al., 2022. Relationship between functional traits of grassland plants and evapotranspiration in the Sanjiangyuan[J]. Acta Agrestia Sinica, 30(8): 2182-2190.
[22]	李红英, 张存桂, 汪生珍, 等, 2022. 近40年青藏高原植被动态变化对水热条件的响应[J]. 生态学报, 42(12): 4770-4783.
	LI H Y, ZHANG C G, WANG S Z, et al., 2022. Response of vegetation dynamics to hydrothermal conditions on the Qinghai-Tibet Plateau in the last 40 years[J]. Acta Ecologica Sinica, 42(12): 4770-4783.
[23]	李世清, 任书杰, 李生秀, 2004. 土壤微生物体氮的季节性变化及其与土壤水分和温度的关系[J]. 植物营养与肥料学报, 10(1): 18-23.
	LI S Q, REN S J, LI S X, 2004. Seasonal change of soil microbial biomass and the relationship between soil microbial biomass and soil moisture and temperature[J]. Plant Nutrition and Fertilizer Science, 10(1): 18-23.
[24]	李雪萍, 李建宏, 刘永刚, 等, 2020. 甘南草原不同退化草地植被和土壤微生物特性[J]. 草地学报, 28(5): 1252-1259. DOI
	LI X P, LI J H, LIU Y G, et al., 2020. The vegetation and soil microorganism characteristics of different degraded grassland in Gannan steppe[J]. Acta Agrestia Sinica, 28(5): 1252-1259.
[25]	刘放, 吴明辉, 魏培洁, 等, 2020. 疏勒河源高寒草甸土壤微生物生物量碳氮变化特征[J]. 生态学报, 40(18): 6416-6426.
	LIU F, WU M H, WEI P J, et al., 2020. Variations of soil microbial biomass carbon and nitrogen in alpine meadow of the Shule river headwater region[J]. Acta Ecologica Sinica, 40(18): 6416-6426.
[26]	马昊翔, 陈长成, 宋英强, 等, 2018. 青海省近10年草地植被覆盖动态变化及其驱动因素分析[J]. 水土保持研究, 25(6):137-145.
	MA H X, CHEN C C, SONG Y Q, et al., 2018. Analysis of vegetation cover change and its driving factors over the past ten years in Qinghai Province[J]. Research of Soil and Water Conservation, 25(6): 137-145.
[27]	覃乾, 朱世硕, 夏彬, 等, 2019. 黄土丘陵区侵蚀坡面土壤微生物量碳时空动态及影响因素[J]. 环境科学, 40(4): 1973-1980.
	QIN Q, ZHU S S, XIA B, et al., 2019. Temporal and spatial dynamics of soil microbial biomass carbon and its influencing factors on an eroded slope in the Hilly Loess Plateau region[J]. Environmental Science, 40(4): 1973-1980.
[28]	王亚晖, 唐文家, 李森, 等, 2022. 青海省草地生产力变化及其驱动因素[J]. 草业学报, 31(2): 1-13. DOI
	WANG Y H, TANG W J, LI S, et al., 2022. Change in grassland productivity in Qinghai Province and its driving factors[J]. Acta Prataculturae Sinica, 31(2): 1-13.
[29]	王国兵, 王丰, 金裕华, 等, 2011. 武夷山不同海拔植被土壤微生物量N时空变异[J]. 生态学杂志, 30(4): 784-789.
	WANG G B, WANG F, JIN Y H, et al., 2011. Spatiotemporal variation of soil microbial biomass N under different vegetations along an altitude gradient in Wuyi Mountains of southeast China[J]. Chinese Journal of Ecology, 30(4): 784-789.
[30]	邬嘉华, 王立新, 张景惠, 等, 2018. 温带典型草原土壤理化性质及微生物量对放牧强度的响应[J]. 草地学报, 26(4): 832-840. DOI
	WU J H, WANG L X, ZHANG J H, et al., 2018. Response of soil properties and microbial biomass to different grazing intensities in temperate typical steppe[J]. Acta Agrestia Sinica, 26(4): 832-840.
[31]	谢梅珍, 赵林, 吴晓东, 等, 2022. 青藏高原多年冻土区两种高寒草地生态系统土壤氮季节变化及其与环境因子的关系[J]. 冰川冻土, 44(5): 1631-1639. DOI
	XIE M Z, ZHAO L, WU X D, et al., 2022. Seasonal variation of soil nitrogen and its relationship to environmental factors under two alpine grassland ecosystems in permafrost regions on the Qinghai-Tibet Plateau[J]. Journal of Glaciology and Geocryology, 44(5): 1631-1639. DOI
[32]	严登华, 王刚, 金鑫, 等, 2010. 滦河流域不同土地利用类型土壤微生物量C、TN、TP垂直分异规律及其影响因子研究[J]. 生态环境学报, 19(8): 1844-1849. DOI
	YAN D H, WANG G, JIN X, et al., 2020. Study on vertical distribution regularity of soil microbial biomass C, TN, TP from different landuse patterns and their influencing factors in Luan River basin[J]. Ecology and Environmental Sciences, 19(8): 1844-1849.
[33]	杨晓娟, 李春俭, 2008. 机械压实对土壤质量、作物生长、土壤生物及环境的影响[J]. 中国农业科学, 41(7): 2008-2015.
	YANG X J, LI C J, 2008. Impacts of mechanical compaction on soil properties, growth of crops, soil-borne organisms and environment[J]. Scientia Agricultura Sinica, 41(7): 2008-2015.
[34]	尹才, 刘淼, 孙凤云, 等, 2016. 基于增强回归树的流域非点源污染影响因子分析[J]. 应用生态学报, 27(3): 911-919.
	YIN C, LIU M, SUN F Y, et al., 2016. Influencing factors of non-point source pollution of watershed based on boosted regression tree algorithm[J]. Chinese Journal of Applied Ecology, 27(3): 911-919.
[35]	喻岚晖, 王杰, 廖李容, 等, 2020. 青藏高原退化草甸土壤微生物量、酶化学计量学特征及其影响因素[J]. 草地学报, 28(6): 1702-1710. DOI
	YU L H, WANG J, LIAO L R, et al., 2020. Soil microbial biomass, enzyme activities and ecological stoichiometric characteristics and influencing factors along degraded meadows on the Qinghai-Tibet plateau[J]. Acta Agrestia Sinica, 28(6): 1702-1710.
[36]	许华, 何明珠, 唐亮, 等, 2020. 荒漠土壤微生物量碳、氮变化对降水的响应[J]. 生态学报, 40(4): 1295-1304.
	XU H, HE M Z, TANG L, et al., 2020. Response of changes of microbial biomass and nitrogen to precipitation in desert soil[J]. Acta Ecologica Sinica, 40(4): 1295-1304.
[37]	张稳, 2015. 泥炭沼泽微生物量碳和可溶性有机碳时空分布及影响因子探究[D]. 长春: 东北师范大学:27-43.
	ZHANG W, 2015. Dynamic and factors of microbial biomass carbon and dissolved organic carbon in Peatland [D]. Changchun: Northeast Normal University: 27-43.
[38]	张崇邦, 刘士山, 1996. 东北羊草草原环境因素对微生物生物量影响的灰色分析[J]. 中国草地 (1): 10-14.
	ZHANG C B, LIU S S, 1996. Grey analysis about the effect of environment factors on microbial biomass on the Leymus chinesis grassland in northern China[J]. Grassland of China (1): 10-14.
[39]	张法伟, 李红琴, 李文清, 等, 2022. 三江源国家公园表层土壤有机碳和全氮密度的特征评估和等级区划[J]. 生态学报, 42(14): 5593-5602.
	ZHANG F W, LI H Q, LI W Q, et al., 2022. The Spatial pattern and regional classifications of topsoil organic carbon and total nitrogen density based on boosted regression trees in the Sanjiangyuan National Park[J]. Acta Ecologica Sinica, 42(14): 5593-5602.
[40]	仲波, 孙庚, 陈冬明, 等, 2017. 不同恢复措施对若尔盖沙化退化草地恢复过程中土壤微生物生物量碳氮及土壤酶的影响[J]. 生态环境学报, 26(3): 392-399.
	ZHONG B, SUN G, CHEN D M, et al., 2017. Effects of different restoration measures on soil microbial biomass carbon and nitrogen and soil enzymes in the process of restoration of the desertified grassland in Zoige[J]. Ecology and Environmental Sciences, 26(3): 392-399.

地点	纬度(N)/(°)	经度(E)/(°)	海拔/ m	草地类型	优势物种	土壤pH	土壤有机质质量分数/ (g·kg^-1)	土壤全氮质量分数/ (g·kg^-1)	土壤全磷质量分数/ (g·kg^-1)	土壤质地
海晏 HY	36.92	100.94	3150	高寒草甸草原	疏花针茅 (Stipa penicillata), 矮生嵩草 (Kobresia humilis), 星毛委陵菜 (Potentilla acaulis)	7.74	45.49	3.17	0.58	粉壤土
同德 TD	35.23	100.72	3544	温性草原	疏花针茅, 无穗柄薹草 (Carex ivanoviae), 火绒草 (Leontopodium leontopodioides)	7.77	37.77	2.51	0.62	粉壤土
玛多 MD	35.02	97.32	4300	高寒草原	紫花针茅 (Stipa purpurea Griseb), 冷地早熟禾 (Poa crymophila Keng), 多裂委陵菜 (Potentilla multifida)	7.77	26.70	1.88	0.52	粉壤土
曲麻莱 QML	34.99	94.49	4400	高寒草甸	矮生嵩草, 高山嵩草 (Kobresia pygmaea), 蒙古穗三毛 (Trisetum spicatum)	7.50	61.35	2.82	0.47	粉壤土
可可西里 KKXL	35.46	93.48	4474	高寒草原	紫花针茅, 青藏薹草 (Carex moorcroftii), 扇穗茅 (Littledalea racemosa)	8.04	7.35	0.59	0.29	砂壤土

地点	纬度(N)/(°)	经度(E)/(°)	海拔/ m	草地类型	优势物种	土壤pH	土壤有机质质量分数/ (g·kg^-1)	土壤全氮质量分数/ (g·kg^-1)	土壤全磷质量分数/ (g·kg^-1)	土壤质地
海晏 HY	36.92	100.94	3150	高寒草甸草原	疏花针茅 (Stipa penicillata), 矮生嵩草 (Kobresia humilis), 星毛委陵菜 (Potentilla acaulis)	7.74	45.49	3.17	0.58	粉壤土
同德 TD	35.23	100.72	3544	温性草原	疏花针茅, 无穗柄薹草 (Carex ivanoviae), 火绒草 (Leontopodium leontopodioides)	7.77	37.77	2.51	0.62	粉壤土
玛多 MD	35.02	97.32	4300	高寒草原	紫花针茅 (Stipa purpurea Griseb), 冷地早熟禾 (Poa crymophila Keng), 多裂委陵菜 (Potentilla multifida)	7.77	26.70	1.88	0.52	粉壤土
曲麻莱 QML	34.99	94.49	4400	高寒草甸	矮生嵩草, 高山嵩草 (Kobresia pygmaea), 蒙古穗三毛 (Trisetum spicatum)	7.50	61.35	2.82	0.47	粉壤土
可可西里 KKXL	35.46	93.48	4474	高寒草原	紫花针茅, 青藏薹草 (Carex moorcroftii), 扇穗茅 (Littledalea racemosa)	8.04	7.35	0.59	0.29	砂壤土

土壤深度/ cm	研究区	土壤水分含量/%	土壤微生物生物量碳质量分数/ (g·kg^-1)	土壤微生物生物量氮质量分数/ (g·kg^-1)
0-10	HY	18.84±1.03bc	1.092±0.043a	0.194±0.009a
	TD	22.19±1.24b	0.826±0.022b	0.159±0.007b
	QML	42.07±4.18a	0.785±0.058c	0.160±0.011b
	MD	12.81±0.87cd	0.528±0.031c	0.105±0.005c
	KKXL	10.22±0.97d	0.153±0.014d	0.034±0.002d
	Total	21.23±5.63	0.677±0.158	0.131±0.028
10-20	HY	20.14±1.01b	0.694±0.040a	0.124±0.007a
	TD	18.99±0.63bc	0.390±0.024c	0.071±.004c
	QML	41.53±5.28a	0.564±0.054b	0.095±0.009b
	MD	12.00±0.63c	0.390±0.021c	0.071±0.005c
	KKXL	13.31±0.77bc	0.087±0.010d	0.022±0.002d
	Total	21.19±5.32	0.425±0.102	0.077±0.017
20-30	HY	19.81±0.75b	0.346±0.028a	0.057±0.005a
	TD	17.18±0.52bc	0.233±0.018b	0.037±0.002c
	QML	30.43±3.54a	0.270±0.031b	0.046±0.004bc
	MD	13.52±0.51c	0.270±0.020b	0.050±0.005ab
	KKXL	13.82±0.86c	0.062±0.008c	0.018±0.003d
	Total	18.95±3.09	0.236±0.047	0.042±0.007
30-40	HY	18.84±0.67ab	0.178±0.015ab	0.033±0.003b
	TD	17.30±0.38bc	0.148±0.016bc	0.028±0.002b
	QML	21.68±1.81a	0.131±0.015c	0.025±0.003b
	MD	13.02±0.65c	0.242±0.046a	0.047±0.009a
	KKXL	-	-	-
	Total	17.71±1.81	0.175±0.025	0.033±0.005

土壤深度/ cm	研究区	土壤水分含量/%	土壤微生物生物量碳质量分数/ (g·kg^-1)	土壤微生物生物量氮质量分数/ (g·kg^-1)
0-10	HY	18.84±1.03bc	1.092±0.043a	0.194±0.009a
	TD	22.19±1.24b	0.826±0.022b	0.159±0.007b
	QML	42.07±4.18a	0.785±0.058c	0.160±0.011b
	MD	12.81±0.87cd	0.528±0.031c	0.105±0.005c
	KKXL	10.22±0.97d	0.153±0.014d	0.034±0.002d
	Total	21.23±5.63	0.677±0.158	0.131±0.028
10-20	HY	20.14±1.01b	0.694±0.040a	0.124±0.007a
	TD	18.99±0.63bc	0.390±0.024c	0.071±.004c
	QML	41.53±5.28a	0.564±0.054b	0.095±0.009b
	MD	12.00±0.63c	0.390±0.021c	0.071±0.005c
	KKXL	13.31±0.77bc	0.087±0.010d	0.022±0.002d
	Total	21.19±5.32	0.425±0.102	0.077±0.017
20-30	HY	19.81±0.75b	0.346±0.028a	0.057±0.005a
	TD	17.18±0.52bc	0.233±0.018b	0.037±0.002c
	QML	30.43±3.54a	0.270±0.031b	0.046±0.004bc
	MD	13.52±0.51c	0.270±0.020b	0.050±0.005ab
	KKXL	13.82±0.86c	0.062±0.008c	0.018±0.003d
	Total	18.95±3.09	0.236±0.047	0.042±0.007
30-40	HY	18.84±0.67ab	0.178±0.015ab	0.033±0.003b
	TD	17.30±0.38bc	0.148±0.016bc	0.028±0.002b
	QML	21.68±1.81a	0.131±0.015c	0.025±0.003b
	MD	13.02±0.65c	0.242±0.046a	0.047±0.009a
	KKXL	-	-	-
	Total	17.71±1.81	0.175±0.025	0.033±0.005

参数	线性模型	r²	P	F
C_mic	C_mic=0.650+0.055t_S+0.897SWC-0.032t- 0.011RH-0.011R_n	0.305	<0.05	34.471
N_mic	N_mic=0.094+0.011t_S-0.009t+0.156SWC- 0.002RH	0.252	<0.001	33.117

青海高寒草地水热因子对土壤微生物生物量碳、氮空间变异的贡献——基于增强回归树模型

Contribution of Water and Heat Factors to Spatial Variability of Soil Microbial Biomass Carbon and Nitrogen in Qinghai Alpine Grassland: Based on Enhanced Regression Tree Model

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