Characteristics and Network of Soil Bacterial Communities in Different Land Use Types in Rare Earth Mining Areas

doi:10.16258/j.cnki.1674-5906.2022.04.018

Ecology and Environment ›› 2022, Vol. 31 ›› Issue (4): 793-801.DOI: 10.16258/j.cnki.1674-5906.2022.04.018

• Research Articles • Previous Articles Next Articles

Characteristics and Network of Soil Bacterial Communities in Different Land Use Types in Rare Earth Mining Areas

YANG Xianfang¹^,⁴(), CHEN Zhao²^,³, ZHENG Lin¹^,^*(), WAN Zhiwei⁴, CHEN Yonglin⁴, WANG Yuandong⁴

1. School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, P. R. China
2. Guangdong Key Laboratory of Integrated Agro-environmental Pollution Control and Management, Institute of Eco-environmental and Soil Sciences, Guangdong Academy of Sciences, Guangzhou 510650, P. R. China
3. National-Regional Joint Engineering Research Center for Soil Pollution Control and Remediation in South China, Guangzhou 510650, P. R. China
4. School of Geography and Environmental Engineering, Gannan Normal University, Ganzhou 341000, P. R. China.

Received:2021-12-06 Online:2022-04-18 Published:2022-06-22
Contact: ZHENG Lin

稀土矿区不同土地利用类型土壤细菌群落特征及网络分析

杨贤房¹^,⁴(), 陈朝²^,³, 郑林¹^,^*(), 万智巍⁴, 陈永林⁴, 王远东⁴

1.江西师范大学地理与环境学院,江西南昌 330022
2.广东省科学院生态环境与土壤研究所/广东省农业环境综合治理重点实验室,广东广州 510650
3.华南土壤污染控制与修复国家地方联合工程研究中心,广东广州 510650
4.赣南师范大学地理与环境工程学院,江西赣州 341000

通讯作者: 郑林
作者简介:杨贤房（1983年生）,男,讲师,博士研究生,主要研究方向生态修复与土地利用。E-mail: 573492915@qq.com
基金资助:
国家自然科学基金项目(42161019);江西省教育厅科技项目(190763);江西省教育厅科技项目(190761);江西省教育厅科技项目(202015);江西省高校人文社会科学研究项目(JC21117)

Abstract

Abstract:

In order to explore the diversity and community structure of soil bacteria in different land use types in ionic rare earth mining areas, this study selected seven different land use types, including paddy field, vegetable field, orchard, corn field, grassland, forest, and bare land (control group) around zudong mining area in Longnan. Soil physico-chemical properties and heavy metal content were measured. Bacterial community compositions and species interactions in different habitats were analyzed through 16SrRNA Illumina high-throughput sequencing and molecular ecological network methods. The results showed that the available phosphorus content of grassland, forest, and bare land was very low. The contents of Cd, Pb, As, Mn, Zn in soil of different habitats exceeded the background values. The comprehensive pollution index of Nemero was ranked as grassland>forest field>orchard>paddy field>bare land> vegetable field>corn field. Chao1 index was ranked as corn field>vegetable field>paddy field>orchard>grassland>forest field>bare land. The abundance of Proteobacteria in the paddy field and the vegetation soil decreased significantly. The abundance of Acidobacteria and Nitrospirae increased. The abundance of Ralstonia decreased significantly, while the abundance of Rhodanobacter, Bradyrhizobium and Kaistobacter increased significantly. The abundance of Thiobacillus, Desulfobulbus and Gallionella in farmland soil was higher than that in vegetation soil. The abundance of Rhodanobacter in grassland and vegetable field was 1.4% and 2.0%, respecctively. The abundance of Thiobacillus and Desulfobulbus in farmland soil was 1.6% and 0.9%, respectively. The results of the co-occurrence network analysis showed that vegetation and farmland soil planting increased the scale of bacterial network size and reduced the network path length. Correlation analyses showed that ammonium nitrogen, total nitrogen, organic matter, pH, Cu, and Ni were the main factors affecting the bacterial community structure. Compared with bare land, vegetation and farmland restoration can improve the diversity of dominant bacteria with growth promotion and denitrification function in mining areas. The diversity of sulfur cycling dominant bacteria in farmland was higher than that in vegetative soil. Identification of functional bacteria in different land use types provides a scientific guidance for ecological restoration in mining areas.

Key words: Bacterial community, land use types, Ecological network, High throughput sequencing, Rare earth mining area, Heavy metal

摘要：

为了探明离子型稀土矿区不同土地利用类型土壤细菌多样性及群落结构差异,该研究选择了龙南足洞矿区周边水稻田、蔬菜地、果园、玉米地、草地、林地、裸地（对照组）7种土地利用类型,测量土壤理化性质和重金属含量,利用16S rRNA Illumina高通量测序技术和分子生态网络方法,分析不同生境细菌群落组成和物种互作关系。结果表明,草地、林地、裸地有效磷含量低,土壤Cd、Pb、As、Mn、Zn等重金属含量超过背景值,内梅罗综合污染指数排序为草地>林地>果园>水稻田>裸地>蔬菜地>玉米地。Chao1指数排序为玉米地>蔬菜地>水稻田>果园>草地>林地>裸地;相较裸地,耕地、植被类土壤变形菌门（Proteobacteria）丰度大幅下降,而酸酐菌门（Acidobacteria）、硝化螺旋菌门（Nitrospirae）丰度升高;劳尔氏菌属（Ralstonia）丰度显著下降,产黄杆菌属（Rhodanobacter）、慢生根瘤菌属（Bradyrhizobium）和Kaistobacter等细菌丰度显著上升。耕地土壤中硫杆菌属（Thiobacillus）、脱硫球茎菌属（Desulfobulbus）、披毛菌属（Gallionella）相较植被土壤丰度更高,其中草地和蔬菜地Rhodanobacter丰度分别为1.4%、2.0%,水稻田土壤菌属Thiobacillus、Desulfobulbus丰度分别为1.6%、0.9%。共现网络分析结果显示,植被、耕地种植措施增加了细菌网络规模,减少了网络路径长度。铵态氮、全氮、有机质、pH、Cu、Ni与细菌群落结构变化关联性最大。研究显示,相较裸地对照组,植被和耕地恢复措施均能提升矿区土壤促生和反硝化功能优势细菌多样性,耕地土壤中硫循环优势细菌较植被土壤多样性更高。不同土地利用类型土壤功能细菌的识别对稀土矿区生态修复提供了科学指引。

关键词: 细菌群落, 土地利用类型, 生态网络, 高通量测序, 稀土矿区, 重金属

CLC Number:

X171.5

YANG Xianfang, CHEN Zhao, ZHENG Lin, WAN Zhiwei, CHEN Yonglin, WANG Yuandong. Characteristics and Network of Soil Bacterial Communities in Different Land Use Types in Rare Earth Mining Areas[J]. Ecology and Environment, 2022, 31(4): 793-801.

杨贤房, 陈朝, 郑林, 万智巍, 陈永林, 王远东. 稀土矿区不同土地利用类型土壤细菌群落特征及网络分析[J]. 生态环境学报, 2022, 31(4): 793-801.

Figures/Tables 9

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土壤理化性质 Physicochemical properties of soil	土地利用类型 Land use types
土壤理化性质 Physicochemical properties of soil	裸地 Bare land	玉米地 Corn field	果园 Orchard	蔬菜 Vegetables field	稻田 Paddy field	草地 Grassland	林地 Forest field
pH	4.35±0.21	6.26±0.29	4.40±0.35	5.18±0.41	5.42±0.22	4.59±0.14	4.57±0.25
w_(TN)/(g∙kg^-1)	0.42±0.01	3.99±0.68	1.03±0.17	2.69±0.36	1.32±0.62	0.84±0.10	1.03±0.19
w_(OM)/(g∙kg^-1)	1.29±0.12	31.34±0.27	14.04±1.79	33.2±0.84	13.26±2.65	2.76±0.30	6.75±0.75
w_(TP)/(g∙kg^-1)	0.002±0	0.44±0.04	0.21±0.03	2.36±0.18	0.23±0.05	0.004±0	0.003±0
w_(AP)/(g∙kg^-1)	0.001±0	0.01±0.01	0.01±0	0.32±0.02	0.01±0	0.001±0	0.001±0
w_(NH3-N)/(mg∙kg^-1)	6.42±0.56	10.81±2.34	1.34±1.26	31.91±2.31	30.53±1.21	11.32±7.14	5.20±2.01
w_(NO2-N)/(mg∙kg^-1)	19.7±0.34	1.97±0.26	2.51±0.13	44.1±7.79	2.01±0.17	15.5±4.76	2.56±1.12
w_(As)/(mg∙kg^-1)	15.95±0.02	7.92±1.63	6.55±1.45	9.4±0.69	5.98±1.09	52.38±2.80	15.50±6.67
w_(Cd)/(mg∙kg^-1)	0.21±0.02	0	0	0.14±0.02	0	0.63±0.06	0.26±0.01
w_(Cu)/(mg∙kg^-1)	4.25±0.12	15.86±3.58	10.58±2.57	14.89±4.52	11.91±3.6	4.72±0.38	6.67±1.04
w_(Mn)/(mg∙kg^-1)	152.98±4.60	368.93±75.31	329.81±175	440.61±150	266.5±126.4	329.48±15.60	213.13±39.5
w₍^Ni)/(mg∙kg^-1)	1.90±0.12	14.19±4.65	5.97±1.14	5.40±2.02	10.99±7.27	4.82±0.89	2.70±1.86
w_(Pb)/(mg∙kg^-1)	59.09±1.60	64.47±20.30	89.46±9.42	64.07±9.65	72.45±10.01	120.01±7.90	191.11±84.4
w_(Zn)/(mg∙kg^-1)	40.19±5.40	71.85±24.50	68.56±15.30	72.24±18.5	85.81±27.2	84.04±3.90	75.06±8.70
w_(Cr)/(mg∙kg^-1)	4.25±0.06	48.56±12.3	28.94±11.30	21.76±8.08	36.34±17.86	23.68±1.23	5.86±4.47
综合污染指数 (P_N) Composite pollution index (P_N)	1.61	1.57	2.08	1.60	1.71	4.75	4.35

土壤理化性质 Physicochemical properties of soil	土地利用类型 Land use types
土壤理化性质 Physicochemical properties of soil	裸地 Bare land	玉米地 Corn field	果园 Orchard	蔬菜 Vegetables field	稻田 Paddy field	草地 Grassland	林地 Forest field
pH	4.35±0.21	6.26±0.29	4.40±0.35	5.18±0.41	5.42±0.22	4.59±0.14	4.57±0.25
w_(TN)/(g∙kg^-1)	0.42±0.01	3.99±0.68	1.03±0.17	2.69±0.36	1.32±0.62	0.84±0.10	1.03±0.19
w_(OM)/(g∙kg^-1)	1.29±0.12	31.34±0.27	14.04±1.79	33.2±0.84	13.26±2.65	2.76±0.30	6.75±0.75
w_(TP)/(g∙kg^-1)	0.002±0	0.44±0.04	0.21±0.03	2.36±0.18	0.23±0.05	0.004±0	0.003±0
w_(AP)/(g∙kg^-1)	0.001±0	0.01±0.01	0.01±0	0.32±0.02	0.01±0	0.001±0	0.001±0
w_(NH3-N)/(mg∙kg^-1)	6.42±0.56	10.81±2.34	1.34±1.26	31.91±2.31	30.53±1.21	11.32±7.14	5.20±2.01
w_(NO2-N)/(mg∙kg^-1)	19.7±0.34	1.97±0.26	2.51±0.13	44.1±7.79	2.01±0.17	15.5±4.76	2.56±1.12
w_(As)/(mg∙kg^-1)	15.95±0.02	7.92±1.63	6.55±1.45	9.4±0.69	5.98±1.09	52.38±2.80	15.50±6.67
w_(Cd)/(mg∙kg^-1)	0.21±0.02	0	0	0.14±0.02	0	0.63±0.06	0.26±0.01
w_(Cu)/(mg∙kg^-1)	4.25±0.12	15.86±3.58	10.58±2.57	14.89±4.52	11.91±3.6	4.72±0.38	6.67±1.04
w_(Mn)/(mg∙kg^-1)	152.98±4.60	368.93±75.31	329.81±175	440.61±150	266.5±126.4	329.48±15.60	213.13±39.5
w₍^Ni)/(mg∙kg^-1)	1.90±0.12	14.19±4.65	5.97±1.14	5.40±2.02	10.99±7.27	4.82±0.89	2.70±1.86
w_(Pb)/(mg∙kg^-1)	59.09±1.60	64.47±20.30	89.46±9.42	64.07±9.65	72.45±10.01	120.01±7.90	191.11±84.4
w_(Zn)/(mg∙kg^-1)	40.19±5.40	71.85±24.50	68.56±15.30	72.24±18.5	85.81±27.2	84.04±3.90	75.06±8.70
w_(Cr)/(mg∙kg^-1)	4.25±0.06	48.56±12.3	28.94±11.30	21.76±8.08	36.34±17.86	23.68±1.23	5.86±4.47
综合污染指数 (P_N) Composite pollution index (P_N)	1.61	1.57	2.08	1.60	1.71	4.75	4.35

参数 Indices	α 多样性指数 Alpha diversity index
参数 Indices	Ace指数 Ace index	Chao1指数 Chao1 index	Shannon指数 Shannon index	Simpson指数 Simpson index
裸地 Bare land	1074.70	1065.93	3.09	0.61
玉米地 Corn field	3227.02	3212.19	10.79	0.99
果园 Orchard	1574.79	1568.44	8.81	0.99
蔬菜地Vegetables field	2266.58	2258.78	9.77	0.99
水稻田 Paddy field	2414.05	2405.44	10.11	0.99
草地 Grassland	1483.53	1478.72	8.42	0.99
林地 Forest field	1452.32	1449.05	8.91	0.99

参数 Indices	α 多样性指数 Alpha diversity index
参数 Indices	Ace指数 Ace index	Chao1指数 Chao1 index	Shannon指数 Shannon index	Simpson指数 Simpson index
裸地 Bare land	1074.70	1065.93	3.09	0.61
玉米地 Corn field	3227.02	3212.19	10.79	0.99
果园 Orchard	1574.79	1568.44	8.81	0.99
蔬菜地Vegetables field	2266.58	2258.78	9.77	0.99
水稻田 Paddy field	2414.05	2405.44	10.11	0.99
草地 Grassland	1483.53	1478.72	8.42	0.99
林地 Forest field	1452.32	1449.05	8.91	0.99

参数 Parameters	节点数Nodes	连接数Links	平均连通度 Average degree	平均路径长度 Average Path distance	平均聚类系数 Average clustering coefficient	负相关比例 Negative correlation ratio	模块数 Modules	图密度 Graph density
裸地 Bare land	29	104	3.54	3.58	0.44	8.80%	5	0.12
植被 Vegetation	29	106	3.66	3.37	0.46	15.1%	5	0.13
耕地 Arable land	32	219	6.84	2.35	0.58	37.5%	3	0.22

Characteristics and Network of Soil Bacterial Communities in Different Land Use Types in Rare Earth Mining Areas

稀土矿区不同土地利用类型土壤细菌群落特征及网络分析

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References 33

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Indices 指数	OTUs指数 OTUs index	Ace指数 Ace index	Chao1指数 Chao1 index	Shannon指数 Shannon index	Simpson指数 Simpson index
pH	0.86**	0.87**	0.87**	0.59**	0.24
TN	0.78**	0.78**	0.78**	0.55**	0.28
TC	0.71**	0.72**	0.72**	0.57**	0.28
TP	0.35	0.35	0.35	0.30	0.16
AP	0.21	0.21	0.21	0.21	0.12
NH₃-N	0.32	0.33	0.38	0.21	0.19
NO₂-N	0.25	0.27	0.31	0.29	0.11
As	-0.26	-0.26	-0.26	-0.13	0.04
Cd	-0.30	-0.30	-0.30	-0.15	0.01
Cr	0.37*	0.37*	0.37*	0.31	0.23
Cu	0.63**	0.63**	0.63**	0.46*	0.19
Mn	0.23	0.23	0.23	0.25	0.25
Ni	0.58**	0.58**	0.58**	0.43*	0.24
Pb	-0.30	-0.31	-0.31	0.05	0.23
Zn	0.08	0.08	0.08	0.33	0.43*

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