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In this study, Six treatments were established: a control (CK), warming (W), increased precipitation (+P30), decreased precipitation(-P30), increased warming and precipitation (W+P30), and increased warming and decreased precipitation (W-P30). Field experiments were conducted to investigate the effects of warming and precipitation changes on the structure and function of soil bacterial communities in dry-crop farmland. Macro-genome sequencing was exployed to examine the composition, diversity, network structure and metabolic function characteristics of soil bacterial communities under varying treatments. The results demonstrated that the W and W+P30 treatments significantly elevated the relative abundance of Alphaproteobacteria, while the W+P30 treatment notably increased the relative abundance of unclassified Chloroflexi. Conversely, the W, +P30, W+P30, and W-P30 treatments significantly reduced the relative abundance of unclassified Actinomycetia. The +P30 treatment resulted in a significant increase in the Shannon, Simpson and Pielou indices, whereas the W-P30 treatment led to a significant reduction in the alpha diversity index of bacteria. Significant differences were observed in the effects of warming, precipitation changes and their interactions on the β-diversity of the bacterial community. The W, +P30, W+P30 and W-P30 treatments exhibited higher complexity and connectivity than the CK treatment. However, the -P30 treatment exhibited lower relevant parameters than CK. The W, -P30 and W+P30 treatments demonstrated an increase in the number of connectivity nodes, whereas the +P30 and W-P30 treatments did not exhibit this increase. The W treatment led to a notable increase in the relative abundance of the circulatory system, while the +P30 treatment resulted in a significantly decreased the relative abundance of xenobiotics biodegradation and metabolism. The -P30 treatment led to a considerable decrease in the relative abundance of the excretory system, and the W+P30 treatment caused a notable decrease in the relative abundance of nucleotide metabolism. It was observed that warming, precipitation changes (either an increase or decrease in precipitation) and their interaction had significant impact on the structure and metabolic functions of soil bacterial in wheat fields.

, correspAuthors=He-ling WANG, Xiao-dong LYU, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Rui TIAN, Jin KOU, Xiao HU, Peng ZHANG, Jun LEI, He-ling WANG, Xiao-dong LYU), CN=ArticleExt(id=1241049981403066840, articleId=1241049975656870094, tenantId=1146029695717560320, journalId=1234093305789726721, language=CN, title=增温和降水变化对旱作农田土壤细菌群落结构和功能的影响, columnId=1240689596959346705, journalTitle=中国环境科学, columnName=环境微生物, runingTitle=null, highlight=null, articleAbstract=

设置对照(CK),增温(W),降水量增加(+P30),降水量减少(-P30),增温和降水量增加(W+P30)和增温和降水量减少(W-P30)6个处理,开展了增温和降水变化对旱作农田土壤细菌群落结构和功能影响的田间试验.采用宏基因组测序研究不同处理下土壤细菌群落的组成、多样性、网络结构和代谢功能特征.结果表明,W和W+P30处理显著增加了α变形菌纲的相对丰度,W+P30处理显著增加了绿弯菌门未定名属的相对丰度,W、+P30、W+P30和W-P30处理显著降低了放线菌门未定名属的相对丰度.+P30处理显著提高了Shannon指数、Simpson指数和Pielou指数,但W-P30处理显著降低了细菌的α多样性指数.增温、降水变化及其交互对细菌群落β多样性的影响存在显著差异.W、+P30、W+P30和W-P30处理的复杂性和连接性高于CK,但-P30处理的相关参数低于CK.W、-P30和W+P30处理增加了连接节点的数量,但+P30和W-P30处理没有增加连接节点的数量.W处理显著增加了循环系统的相对丰度,+P30处理显著降低了外源物质降解和代谢的相对丰度,-P30处理显著降低了排泄系统的相对丰度,W+P30处理显著降低了核苷酸代谢的相对丰度.增温、降水变化(降水量增加或减少)及其交互作用对小麦田土壤细菌群落结构和代谢功能有显著影响.

, correspAuthors=王鹤龄, 吕晓东, authorNote=null, correspAuthorsNote=
*责任作者,副教授,
**研究员,
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田瑞(1999-),女,甘肃镇原人,兰州交通大学环境与市政工程学院硕士研究生,研究方向为全球气候变化微生物生态学..

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田瑞(1999-),女,甘肃镇原人,兰州交通大学环境与市政工程学院硕士研究生,研究方向为全球气候变化微生物生态学..

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田瑞(1999-),女,甘肃镇原人,兰州交通大学环境与市政工程学院硕士研究生,研究方向为全球气候变化微生物生态学..

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journalId=1234093305789726721, articleId=1241049975656870094, language=EN, label=Fig.3, caption=PCoA analysis of soil bacterial communities under warming and precipitation changes, figureFileSmall=XPnUTmbo3Wrj38vd5lxFdA==, figureFileBig=2kYt1siXEb2DNm6FW6i2Gg==, tableContent=null), ArticleFig(id=1241049994850005035, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241049975656870094, language=CN, label=图3, caption=增温和降水变化下土壤细菌群落PCoA分析图, figureFileSmall=XPnUTmbo3Wrj38vd5lxFdA==, figureFileBig=2kYt1siXEb2DNm6FW6i2Gg==, tableContent=null), ArticleFig(id=1241049996561281085, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241049975656870094, language=EN, label=Fig.4, caption=Network diagram of soil bacterial community structure in wheat fields under warming and precipitation changes不同灰度代表微生物群属于不同的模块类型,节点大小与细菌相对丰度成正比, figureFileSmall=zQLXK7WpaFGkuCffIK6Gag==, figureFileBig=UxjQhKlgNjnUX+FMEMBsyA==, tableContent=null), 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横坐标为模块间连通度;纵坐标为模块内连通度.不同灰度的点代表不同属性的节点.依据节点的拓扑特征可将节点属性分为4种类型,包括:Module hubs(模块中心点,在模块内部具有高连通度的节点,Zi > 2.5且Pi < 0.62),Connectors(连接节点,在两个模块之间具有高连通度的节点,Zi < 2.5且Pi >

, figureFileSmall=fXOGNb4uy5eljEVeFeeSzA==, figureFileBig=xwi+xw3hhRz63oNL89tq6w==, tableContent=null), ArticleFig(id=1241049997668577380, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241049975656870094, language=EN, label=Fig.6, caption=Histogram of test of variance of metabolic function abundance of soil microbial community under different treatments, figureFileSmall=cTL2zFpULWS56mdjbQ5Kvg==, figureFileBig=gTxfIVYdMqKQZYugx2R7XQ==, tableContent=null), ArticleFig(id=1241049997773434994, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241049975656870094, language=CN, label=图6, caption=不同处理下土壤微生物群落代谢功能丰度的差异检验, figureFileSmall=cTL2zFpULWS56mdjbQ5Kvg==, figureFileBig=gTxfIVYdMqKQZYugx2R7XQ==, tableContent=null), ArticleFig(id=1241049997895069819, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241049975656870094, language=EN, label=Table 1, caption=

Precipitation, precipitation date and irrigation water amount in the plots during wheat growing season in 2023

, figureFileSmall=null, figureFileBig=null, tableContent=
日期降雨量(mm)自然降水量处理(L)减水处理(L)增水处理(L)
04-120.933.722.604.84
04-192.359.406.5812.22
04-216.1824.7217.3032.14
04-2218.3773.4851.4495.52
05-031.445.764.037.49
05-053.7815.1210.5819.66
05-089.5038.0026.6049.40
05-142.9511.808.2615.34
05-182.9811.928.3415.50
05-235.5322.1215.4828.76
05-2716.1464.5645.1983.93
05-309.8339.3227.5251.12
06-039.8339.3227.5251.12
06-114.1816.7211.7021.74
06-225.321.2014.8427.56
06-241.054.202.945.46
06-3010.1340.5228.3652.68
07-0211.8547.4033.1861.62
07-098.7234.8824.4245.34
07-1115.3561.4042.9879.82
), ArticleFig(id=1241049998108979335, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241049975656870094, language=CN, label=表1, caption=

2023年小麦生长季降水量、降水时间和小区灌水量

, figureFileSmall=null, figureFileBig=null, tableContent=
日期降雨量(mm)自然降水量处理(L)减水处理(L)增水处理(L)
04-120.933.722.604.84
04-192.359.406.5812.22
04-216.1824.7217.3032.14
04-2218.3773.4851.4495.52
05-031.445.764.037.49
05-053.7815.1210.5819.66
05-089.5038.0026.6049.40
05-142.9511.808.2615.34
05-182.9811.928.3415.50
05-235.5322.1215.4828.76
05-2716.1464.5645.1983.93
05-309.8339.3227.5251.12
06-039.8339.3227.5251.12
06-114.1816.7211.7021.74
06-225.321.2014.8427.56
06-241.054.202.945.46
06-3010.1340.5228.3652.68
07-0211.8547.4033.1861.62
07-098.7234.8824.4245.34
07-1115.3561.4042.9879.82
), ArticleFig(id=1241049998360637588, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241049975656870094, language=EN, label=Table 2, caption=

Differences in relative abundance of bacterial taxa at the level of soil phyla and genera in wheat fields (>1%)

, figureFileSmall=null, figureFileBig=null, tableContent=
分类类群CKW+P30-P30W+P30W-P30
Alphaproteobacteria9.6911.97*11.119.9712.00*10.29
Thermoleophilia5.583.74**3.81**4.983.69**4.01*
Gammaproteobacteria4.217.25*6.524.736.85*6.36
Actinobacteria;unclassified3.062.12**2.20*2.901.97**2.24*
Deltaproteobacteria3.133.86*3.98**3.413.493.87*
Cytophagia1.833.002.972.833.20*2.31
Rubrobacteria1.691.14**1.17**1.601.04**1.22*
Gemmatimonadetes1.331.651.78*1.421.721.74*
Chloroflexi;unclassified8.287.067.438.166.48*7.12
Actinobacteria;unclassified3.382.36**2.45*3.212.19**2.49*
Solirubrobacter2.982.09**2.08**2.632.06**2.14*
Gaiella1.501.07*1.04*1.430.97**1.09*
Steroidobacter1.151.85**1.411.101.64*1.41
Conexibacter1.200.81**0.82**1.100.79**0.87*
Mesorhizobium1.101.63*1.201.081.55*1.08
), ArticleFig(id=1241049998599712927, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241049975656870094, language=CN, label=表2, caption=

小麦田土壤纲、属水平上细菌类群相对丰度的差异(>1%)

, figureFileSmall=null, figureFileBig=null, tableContent=
分类类群CKW+P30-P30W+P30W-P30
Alphaproteobacteria9.6911.97*11.119.9712.00*10.29
Thermoleophilia5.583.74**3.81**4.983.69**4.01*
Gammaproteobacteria4.217.25*6.524.736.85*6.36
Actinobacteria;unclassified3.062.12**2.20*2.901.97**2.24*
Deltaproteobacteria3.133.86*3.98**3.413.493.87*
Cytophagia1.833.002.972.833.20*2.31
Rubrobacteria1.691.14**1.17**1.601.04**1.22*
Gemmatimonadetes1.331.651.78*1.421.721.74*
Chloroflexi;unclassified8.287.067.438.166.48*7.12
Actinobacteria;unclassified3.382.36**2.45*3.212.19**2.49*
Solirubrobacter2.982.09**2.08**2.632.06**2.14*
Gaiella1.501.07*1.04*1.430.97**1.09*
Steroidobacter1.151.85**1.411.101.64*1.41
Conexibacter1.200.81**0.82**1.100.79**0.87*
Mesorhizobium1.101.63*1.201.081.55*1.08
), ArticleFig(id=1241049998742319275, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241049975656870094, language=EN, label=Table 3, caption=

Topological parameters of soil bacterial co-occurrence networks under warming and precipitation changes

, figureFileSmall=null, figureFileBig=null, tableContent=
拓扑参数CKW+P30-P30W+P30W-P30
节点数147147150147152150
边数83399610375721762898
边数/节点数5.6676.7766.9133.89111.5925.987
平均度11.33313.55113.8277.78223.18411.973
连接性0.0780.0930.0930.0530.1540.080
图密度0.0390.0460.0460.0270.0770.040
模块化0.6280.6250.6290.6870.4760.730
平均聚类系数0.2180.2160.2490.1990.2030.239
平均路径长度2.0711.9912.0182.6302.2872.357
), ArticleFig(id=1241049998918480062, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241049975656870094, language=CN, label=表3, caption=

增温和降水变化下土壤细菌共现网络拓扑参数

, figureFileSmall=null, figureFileBig=null, tableContent=
拓扑参数CKW+P30-P30W+P30W-P30
节点数147147150147152150
边数83399610375721762898
边数/节点数5.6676.7766.9133.89111.5925.987
平均度11.33313.55113.8277.78223.18411.973
连接性0.0780.0930.0930.0530.1540.080
图密度0.0390.0460.0460.0270.0770.040
模块化0.6280.6250.6290.6870.4760.730
平均聚类系数0.2180.2160.2490.1990.2030.239
平均路径长度2.0711.9912.0182.6302.2872.357
), ArticleFig(id=1241049999073669323, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241049975656870094, language=EN, label=Table 4, caption=

Parameters and classification related to key species in the bacterial co-occurrence network

, figureFileSmall=null, figureFileBig=null, tableContent=
处理ZiPi节点属性
CK2.8020.430模块中心点GammaproteobacteriaNANA
W0.7560.655连接节点///
1.1280.643连接节点///
+P30外围节点
-P300.6570.711连接节点Actinomycetia
1.3490.707连接节点NANANA
1.2340.689连接节点///
1.4000.640连接节点ThermoleophiliaSolirubrobacteralesNA
-1.1290.634连接节点NitrospiraNitrospiralesNitrospira
0.4970.626连接节点AlphaproteobacteriaSphingomonadalesSphingosinicella
0.1950.626连接节点GemmatimonadetesGemmatimonadalesGemmatirosa
W+P30-1.7610.647连接节点///
W-P30外围节点
), ArticleFig(id=1241049999304356052, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241049975656870094, language=CN, label=表4, caption=

细菌共现网络中关键物种相关参数及分类

, figureFileSmall=null, figureFileBig=null, tableContent=
处理ZiPi节点属性
CK2.8020.430模块中心点GammaproteobacteriaNANA
W0.7560.655连接节点///
1.1280.643连接节点///
+P30外围节点
-P300.6570.711连接节点Actinomycetia
1.3490.707连接节点NANANA
1.2340.689连接节点///
1.4000.640连接节点ThermoleophiliaSolirubrobacteralesNA
-1.1290.634连接节点NitrospiraNitrospiralesNitrospira
0.4970.626连接节点AlphaproteobacteriaSphingomonadalesSphingosinicella
0.1950.626连接节点GemmatimonadetesGemmatimonadalesGemmatirosa
W+P30-1.7610.647连接节点///
W-P30外围节点
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增温和降水变化对旱作农田土壤细菌群落结构和功能的影响
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田瑞 1 , 寇谨 1 , 胡啸 1 , 张鹏 1 , 雷俊 2 , 王鹤龄 2, ** , 吕晓东 1, 3, *
中国环境科学 | 环境微生物 2025,45(1): 508-518
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中国环境科学 | 环境微生物 2025, 45(1): 508-518
增温和降水变化对旱作农田土壤细菌群落结构和功能的影响
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田瑞1 , 寇谨1, 胡啸1, 张鹏1, 雷俊2, 王鹤龄2, ** , 吕晓东1, 3, *
作者信息
  • 1.兰州交通大学环境与市政工程学院,甘肃 兰州 730070
  • 2.中国气象局兰州干旱气象研究所中国气象局干旱气候变化与减灾重点开放实验室,甘肃 兰州 730020
  • 3.祁连山中部亚高山生态系统野外科学观测研究站,甘肃 张掖 734000
  • 田瑞(1999-),女,甘肃镇原人,兰州交通大学环境与市政工程学院硕士研究生,研究方向为全球气候变化微生物生态学..

通讯作者:

*责任作者,副教授,
Effects of warming and precipitation changes on the structure and function of soil bacterial communities in dry-crop farmland
Rui TIAN1 , Jin KOU1, Xiao HU1, Peng ZHANG1, Jun LEI2, He-ling WANG2, ** , Xiao-dong LYU1, 3, *
Affiliations
  • 1.School of Environmental and Municipal Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
  • 2.Key Laboratory of Arid Climate Change and Disaster Reduction in Gansu Province, Lanzhou Institute of Arid Meteorology, China Meteorological Administration, Lanzhou 730020, China
  • 3.Observation Station of Subalpine Ecology Systems in the Middle Qilian Mountains, Zhangye 73400, China
出版时间: 2025-01-20
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设置对照(CK),增温(W),降水量增加(+P30),降水量减少(-P30),增温和降水量增加(W+P30)和增温和降水量减少(W-P30)6个处理,开展了增温和降水变化对旱作农田土壤细菌群落结构和功能影响的田间试验.采用宏基因组测序研究不同处理下土壤细菌群落的组成、多样性、网络结构和代谢功能特征.结果表明,W和W+P30处理显著增加了α变形菌纲的相对丰度,W+P30处理显著增加了绿弯菌门未定名属的相对丰度,W、+P30、W+P30和W-P30处理显著降低了放线菌门未定名属的相对丰度.+P30处理显著提高了Shannon指数、Simpson指数和Pielou指数,但W-P30处理显著降低了细菌的α多样性指数.增温、降水变化及其交互对细菌群落β多样性的影响存在显著差异.W、+P30、W+P30和W-P30处理的复杂性和连接性高于CK,但-P30处理的相关参数低于CK.W、-P30和W+P30处理增加了连接节点的数量,但+P30和W-P30处理没有增加连接节点的数量.W处理显著增加了循环系统的相对丰度,+P30处理显著降低了外源物质降解和代谢的相对丰度,-P30处理显著降低了排泄系统的相对丰度,W+P30处理显著降低了核苷酸代谢的相对丰度.增温、降水变化(降水量增加或减少)及其交互作用对小麦田土壤细菌群落结构和代谢功能有显著影响.

增温效应  /  降水量变化  /  旱作农田  /  微生物群落

In this study, Six treatments were established: a control (CK), warming (W), increased precipitation (+P30), decreased precipitation(-P30), increased warming and precipitation (W+P30), and increased warming and decreased precipitation (W-P30). Field experiments were conducted to investigate the effects of warming and precipitation changes on the structure and function of soil bacterial communities in dry-crop farmland. Macro-genome sequencing was exployed to examine the composition, diversity, network structure and metabolic function characteristics of soil bacterial communities under varying treatments. The results demonstrated that the W and W+P30 treatments significantly elevated the relative abundance of Alphaproteobacteria, while the W+P30 treatment notably increased the relative abundance of unclassified Chloroflexi. Conversely, the W, +P30, W+P30, and W-P30 treatments significantly reduced the relative abundance of unclassified Actinomycetia. The +P30 treatment resulted in a significant increase in the Shannon, Simpson and Pielou indices, whereas the W-P30 treatment led to a significant reduction in the alpha diversity index of bacteria. Significant differences were observed in the effects of warming, precipitation changes and their interactions on the β-diversity of the bacterial community. The W, +P30, W+P30 and W-P30 treatments exhibited higher complexity and connectivity than the CK treatment. However, the -P30 treatment exhibited lower relevant parameters than CK. The W, -P30 and W+P30 treatments demonstrated an increase in the number of connectivity nodes, whereas the +P30 and W-P30 treatments did not exhibit this increase. The W treatment led to a notable increase in the relative abundance of the circulatory system, while the +P30 treatment resulted in a significantly decreased the relative abundance of xenobiotics biodegradation and metabolism. The -P30 treatment led to a considerable decrease in the relative abundance of the excretory system, and the W+P30 treatment caused a notable decrease in the relative abundance of nucleotide metabolism. It was observed that warming, precipitation changes (either an increase or decrease in precipitation) and their interaction had significant impact on the structure and metabolic functions of soil bacterial in wheat fields.

warming effect  /  precipitation changes  /  dry farmland  /  microbial community
田瑞, 寇谨, 胡啸, 张鹏, 雷俊, 王鹤龄, 吕晓东. 增温和降水变化对旱作农田土壤细菌群落结构和功能的影响. 中国环境科学, 2025 , 45 (1) : 508 -518 .
Rui TIAN, Jin KOU, Xiao HU, Peng ZHANG, Jun LEI, He-ling WANG, Xiao-dong LYU. Effects of warming and precipitation changes on the structure and function of soil bacterial communities in dry-crop farmland[J]. China Environmental Science, 2025 , 45 (1) : 508 -518 .
土壤微生物由细菌、真菌、古菌和病毒等组成,其中细菌分布最广、数量最多,是陆地生态系统关键功能和过程的重要驱动者[1-2].土壤微生物对未来全球气候变化的响应和适应一直是全球变化生态学的研究热点[3-4].全球温升和降水增加/减少等气候变化因子将改变微生物环境适应力、微生物群落结构以及微生物种群间相互作用,从而影响到微生物群落的稳定性和恢复力[5]. IPCC第六次评估报告指出,未来几十年,全球气温将升高1.5℃(与工业化前水平相比)[6].与此同时,全球降水模式也随之发生显著变化,将导致更多的极端高温、降水或干旱事件频发[7].在此背景下,土壤微生物群落的结构和功能如何响应仍需探索.
来自森林和草地生态系统的试验证据表明,全球变化将直接或间接改变土壤微生物群落多样性、结构和功能[8].增温能够重塑微生物多样性和改变物种相互作用,提高微生物网络复杂性和稳定性[9].一般认为,降水变化影响土壤微生物群落的多样性和丰度,降低土壤微生物和酶活性[10].目前研究大多集中于单个全球变化因子对土壤微生物群落多样性的影响,而增温和降水变化的组合往往会调控微生物多样性[11].例如,增温降低了土壤微生物丰富度、均匀度和多样性,但这种减少可以被降水量减少所抵消,最终提高了土壤微生物多样性[12].由于土壤微生物在农田生态系统生物地球化学循环、碳固存和植物健康生长等方面具有关键作用[13],因此深入理解农田土壤微生物应对气候变化的规律和机理过程具有重要意义.增温对农田土壤微生物的研究已有报道,但降水改变以及增温和降水改变交互对微生物群落结构和功能影响的研究报道鲜见.黄河中游黄土高原是我国主要的旱地农业区,区内降水时空分布不均,年际变异大且潜在蒸发强烈,同时生态环境脆弱且稳定性较低[14],是气候变化和人类活动最敏感的陆地生态系统之一.近年来,黄土高原西部气候变暖趋势和降水发生明显变化,温度增速为0.34℃/10a,降水增加率为7.7mm/10a[15],导致生态系统中水、热、碳和微生物群落等发生非同步性演变[16],这将直接影响土壤微生物的生长和活性,进而影响土壤微生物群落的周转和功能[17].有关增温、降水变化及其交互对旱作农田土壤细菌群落结构和功能的影响研究尚未见报道.
本研究以黄土高原西部旱地小麦田为研究对象,基于增温和降水改变田间控制试验,采用宏基因组学技术,探究增温、降水改变及其交互对旱地小麦田土壤细菌组成、多样性、结构及其代谢功能的影响,以期为深入理解旱作农田土壤微生物响应全球升温和降水改变机理提供理论认知.
试验在中国气象局兰州干旱气象研究所定西半干旱气象与生态环境试验基地进行(104°37′E,35°35′N,海拔1920m).该基地位于甘肃省陇中黄土高原半干旱区,属温带大陆性气候.年平均气温7.2℃,年平均降水量为375.1mm,且分布不均匀,多集中于7~9月,潜在蒸发量高达1400mm以上.年日照时数为2500h,无霜期年平均为140d.土壤类型为黄绵土,0~10cm土壤pH值为8.01,有机质18.57g/kg,全氮1.24g/kg.该区域为黄土高原旱作农业区,属于典型雨养农业,主栽作物为一年一熟春小麦和马铃薯.
试验采用裂区设计,以温度为主区,设定自然环境温度和增温(1.5±0.5)℃2个水平.以降水变化为副区,设定自然降水、自然降水增加30%和自然降水减少30%3个水平,副区内降水处理随机排列.试验共6个处理,分别为自然环境温度+自然降水,增温+自然降水,自然环境温度+降水增加30%,自然环境温度+降水减少30%,增温+降水增加30%,增温+降水减少30%,处理编号分别为CK、W、+P30、-P30、W+P30、W-P30.每个小区面积为4.0m2,重复3次,共18个小区.
野外实验采用开顶式气室(OTC)进行增温,该装置始建于2011年.开顶式气室结构为八面柱状开顶结构,周围镶透光玻璃,边长2.15m,底面积22.3m2,高2.4m.室内又被划分为5个等面积的小区,小区间采用宽0.15m,深2m的水泥墙分割.同时,装有温湿度传感器,可实时采集开顶气室内作物冠层温湿度.
降水控制装置:采用固定框架卷轴式遮雨棚实现.降水时间和频次根据当地自然降雨时间和频次进行(表1).试验过程中当降雨发生时,采用遮雨棚进行遮雨.利用雨量筒,准确记录降雨量.当降雨结束时,根据当次降雨量、灌溉面积和实验设定增减降水比例计算出各小区灌水量,尽可能快地完成人工喷洒补灌.
试验春小麦在2023年4月1日播种,于2023年7月20日收获.试验春小麦品种选择当地主栽品种“酒春10号”.播种行距0.15m,播种量为225kg/hm2,一次性施肥:磷酸二铵228kg/hm2和尿素138kg/hm2.春小麦生产管理按照当地高产栽培技术规程进行,试验过程中各小区管理措施保持一致.
2023年7月16日小麦成熟期采集田间土壤.采样前先清除试验小区土壤表面新鲜和半分解的凋落物残体.在3个重复的不同区域内,用土钻按梅花状采集3个点(0~10cm土层).将采集的土样混合均匀,并过2mm筛.取大约10g土样装入冻存管,暂放于液氮罐中,用于DNA提取.
利用磁珠法强力土壤基因组DNA提取试剂盒(白垩纪纳磁美籍;CNA03190)进行样品DNA提取.完成DNA提取后,利用Qubit Fluorometer检测DNA浓度,利用1.5%琼脂糖凝胶电泳检测DNA完整性,利用Q-sep400检测片段大小.由武汉爱基百客生物科技有限公司利用Illumina NovaSeq 6000PE150测序平台进行宏基因测序.
在进行数据分析之前,对测序数据进行质量控制.去除含有接头的Reads和低质量的Reads后,得到高质量的Clean Data.利用拼接软件MEGAHIT(或IDBA_UD)对其进行拼接组装,筛选500bp以上的Contigs进行统计.使用Prodigal软件对拼接的Contigs序列进行ORF预测,并将其翻译为氨基酸序列,获得样本基因预测结果.使用bowtie2软件,分别将每个样本的clean reads与非冗余基因集进行比对(95% identity),统计基因在对应样本中的丰度信息.
利用DIAMOND软件将Unigenes与从NCBI的NR(Version:2021.11)数据库中抽提出的细菌序列进行比对(blastp,evalue≤1×10-5).对于每一条序列的比对结果,选取evalue≤最小evalue*10的比对结果.采取LCA算法(应用于MEGAN软件的系统分类),将出现第一个分支前的分类级别,作为该序列的物种注释信息.使用DIAMOND软件将非冗余基因与各功能数据库进行比对,取e<1×10-5的注释,筛选具有最高序列相似性的蛋白,从而得到功能注释信息.对于每一条序列的比对结果,选取score最高的比对结果(one HSP>60bits).从比对结果出发,统计不同功能层级的相对丰度.其中,KEGG数据库划分为5个层级.
采用Excel 2021软件进行数据整理,IBM SPSS Statistics 27软件进行增温、降水改变及其交互作用下处理间单因素ANOVA检验和多变量线性模型分析,采用Origin 2024软件绘图.利用R语言进行细菌α多样性、β多样性和共现网络分析和绘图.不同处理下土壤微生物群落代谢功能之间的差异检验柱状图(Stamp分析)于在线平台绘制(http://cloudtutu.com.cn/).
在纲水平上,小麦田土壤细菌类群共有243个.相对丰度排在前10的类群分别为放线菌纲(Actinomycetia)、酸杆菌门未定名纲(Acidobacteria;unclassified)、α变形菌纲(Alphaproteobacteria)、绿弯菌门未定名纲(Chloroflexi;unclassified)、嗜热油菌纲(Thermoleophilia)、芽单胞菌门未定名纲(Gemmatimonadetes;unclassified)、β变形菌纲(Betaproteobacteria)、γ变形菌纲(Gammaproteobacteria)、放线菌门未定名纲(Actinobacteria;unclassified)和δ变形菌纲(Deltaproteobacteria).其中,放线菌纲、酸杆菌门未定名纲和α变形菌纲为主要优势类群,相对丰度分别为16.11%~20.46%、10.55%~16.95%和9.32%~12.58%(图1).-P30处理对纲水平的细菌类群无显著影响.与CK相比,W和W+P30处理显著增加了α变形菌纲和γ变形菌纲的相对丰度,但+P30和W-P30处理对该类群无显著影响;W、+P30、W+P30和W-P30处理显著降低了嗜热油菌纲、放线菌门未定名纲和红螺菌纲(Rubrobacteria)的相对丰度;W、+P30和W-P30处理显著增加了δ变形菌纲的相对丰度,但W+P30处理对该类群无显著影响;W+P30处理显著提高了噬纤维菌纲(Cytophagia)的相对丰度,但W、+P30和W-P30处理对该类群无显著影响;+P30和W-P30处理显著提高了芽单胞菌纲(Gemmatimonadetes)的相对丰度,但W和W+P30处理对该类群无显著影响(表2).
在属水平上,小麦田土壤细菌类群共有2938个.相对丰度排在前10的类群分别为酸杆菌门未定名属(Acidobacteria;unclassified)、绿弯菌门未定名属(Chloroflexi;unclassified)、芽单胞菌门未定名属(Gemmatimonadetes;unclassified)、类诺卡氏菌属(Nocardioides)、放线菌门未定名属(Actinobacteria;unclassified)、土壤红杆菌属(Solirubrobacter)、念珠菌门未定名属(Candidatus_Rokubacteria;unclassified)、放线菌纲未定名属(Actinomycetia;unclassified)、β变形菌纲未定名属(Betaproteobacteria;unclassified)和鞘氨醇单胞菌属(Sphingomonas).其中,酸杆菌门未定名属、绿弯菌门未定名属和芽单胞菌门未定名属为主要优势类群,相对丰度分别为11.87%~18.68%、6.52%~8.79%和5.98%~6.82%(图1).-P30处理对属水平的细菌类群无显著影响.与CK相比,W+P30处理显著增加了绿弯菌门未定名属的相对丰度,但W、+P30和W-P30处理对该类群无显著影响;W、+P30、W+P30和W-P30处理显著降低了放线菌门未定名属、土壤红杆菌属、Gaiella属和伍氏束缚菌属(Conexibacter)的相对丰度;W和W+P30处理显著增加了黄色类固醇杆菌属(Steroidobacter)和慢生根瘤菌属(Mesorhizobium)的相对丰度,但+P30和W-P30处理对该类群无显著影响(表2).
根据Kruskal-Wallis秩和检验可知,+P30处理的Shannon指数、Simpson指数和Pielou指数显著高于CK,但W-P30处理的Shannon指数、Simpson指数和Pielou指数显著低于CK.而-P30、W、W+P30处理的α多样性指数与CK之间无显著差异(图2).根据PERMANOVA分析可知,增温对细菌群落α多样性无显著影响,但降水变化、增温和降水变化交互对细菌群落α多样性的影响存在显著差异(R2=0.120,P=0.051;R2=0.388,P=0.010;R2=0.213,P=0.026).
基于Bray-Curtis距离的主坐标分析(PCoA),分析不同处理下细菌群落β多样性的差异(图3).图中横纵坐标为前两个主成分(PCoA1和PCoA2),解释率分别为44.97%和30.56%. ANOSIM检验显示,组间差异大于组内差异,且组间差异具有显著性(R=0.6535,P=0.001). W、+P30和W+P30处理与CK之间的分离距离较远,而-P30和W-P30处理和与CK之间的分离距离比较近.此外,根据PERMANOVA分析可知,增温、降水变化及其交互作用对细菌群落β多样性的影响存在显著差异(R2=0.146,P=0.001;R2=0.332,P=0.001;R2=0.251,P=0.001).
增温和降水变化下小麦田土壤细菌群落共现网络有较为明显的差异(表3图4). W处理的复杂性、平均度、连接性和完整性高于CK,-P30处理的复杂性、平均度、连接性和完整性均低于CK,而W-P30处理的复杂性、平均度、连接性和完整性略高于CK.+P30和W+P30处理的复杂性、平均度、连接性和完整性高于CK,其中W+P30处理与CK的差异最为明显.此外,W、+P30处理的模块性与CK差异不太明显,-P30和W-P30处理的模块性高于CK,其中W-P30处理差异最为明显,但W+P30处理的模块性明显低于CK.
在网络模块的基础上衍生出了两个重要的节点特征,即模块内连通度(Zi)和模块间连通度(Pi).通过计算Zi和Pi获得关键类群(表4).其中,+P30和W-P30处理并没有关键类群,CK有1个关键类群,属于变形菌门(Proteobacteria);W处理有2个关键类群,分别属于变形菌门和绿弯菌门;-P30处理有7个关键类群,分别属于放线菌门放线菌纲(Actinobacteria;Actinomycetia)、放线菌门嗜热油菌纲(Actinobacteria;Thermoleophilia)、芽单胞菌门(Gemmatimonadetes)、芽单胞菌门未定名纲(Gemmatimonadetes;NA)、芽单胞菌门芽单胞菌纲(Gemmatimonadetes;Gemmatimonadetes)、变形菌门和硝化螺旋菌门(Nitrospirae);W+P30处理1个关键类群,属于硝化螺旋菌门(表4图5).此外,根据Zi和Pi大小,将节点属性分为4种类型(图5).其中,W、-P30和W+P30处理增加了连接节点的数量,但+P30和W-P30处理没有增加连接节点的数量.
本研究小麦田土壤微生物群落的KEGG代谢通路第一层级共有6大代谢通路,分别为细胞过程(Cellular Processes)、环境信息处理(Environmental Information Processing)、遗传信息处理(Genetic Information Processing)、人类疾病(Human Diseases)、新陈代谢(Metabolism)和有机体系统(Organismal Systems).第二层子功能共有45种,其中一些细菌的代谢功能丰度在不同处理下存在显著差异(如图6).与CK相比,W处理显著增加了循环系统(Circulatory system)、耐药性(抗肿瘤)(Drug resistance:antineoplastic)、环境适应(Environmental adaptation)的相对丰度;+P30处理显著降低了外源物质降解和代谢(Xenobiotics biodegradation and metabolism)与神经系统(Nervous system)的相对丰度,但显著降低了环境适应的相对丰度;-P30处理显著增加了排泄系统(Excretory system)的相对丰度;W+P30处理显著降低了核苷酸代谢(Nucleotide metabolism)、但显著增加了寄生虫传染病(Infectious disease:parasitic)、特定类型癌症(Cancer:specific types)、环境适应、细胞运动(Cell motility)和信号转导(Signal transduction)的相对丰度;W-P30处理显著增加了循环系统的相对丰度.
增温和增水显著改变了旱作农田土壤细菌群落组成.本研究发现,增温、增水显著增加了δ变形菌纲的相对丰度,但降低了嗜热油菌纲相对丰度,而对噬纤维菌纲相对丰度无显著影响.该研究结论与李怡佳等[18]一致,即增温、增水对农田土壤细菌群落组成的影响存在增加、降低和无影响3种效应.但是Habtewold等[19]研究表明升温显著降低了农田土壤中δ变形菌纲的相对丰度,提高了嗜热油菌纲相对丰度,这可能是由于试验增温幅度、添加尿素含量以及气候条件等不同导致的差异.相比于增温、增水,减水并未改变土壤细菌群落组成,说明旱作农田土壤细菌群落组成对降水量减少有很强的耐受性.这可能是由于旱作农田土壤细菌群落长期处于半干旱地区,导致其对干旱有一定的适应力,而长期频繁的干湿循环胁迫可能是细菌群落具有巨大耐旱潜力的原因之一[20].
增温和降水变化交互显著改变了旱作农田土壤微生物群落组成.本研究发现,增温、增水显著增加了δ变形菌纲的相对丰度,而两者交互对该类群的相对丰度无显著影响,这说明增温、增水相互抵消了对δ变形菌纲相对丰度的影响;增温、增水对噬纤维菌纲的相对丰度无显著影响,而两者交互显著增加了该类群的相对丰度,这说明了增温、增水相互促进了对噬纤维菌纲相对丰度的影响;增温、增水及其交互都显著降低了土壤红杆菌属的相对丰度.此外,增温、减水对芽单胞菌纲的相对丰度无显著影响,而两者交互显著提高了该类群的相对丰度,这说明增温、减水相互促进了对芽单胞菌纲相对丰度的影响;增温、减水及其交互显著降低了土壤红杆菌属的相对丰度.该研究结论与马星宇[21]一致,即农田土壤细菌群落组成增温和降水变化的交互效应存在叠加、拮抗和协同作用.
增温和增水对旱作农田土壤细菌群落多样性有显著影响.本研究中,增温对土壤细菌群落α多样性无显著影响,而对β多样性有显著影响;增水显著提高了土壤细菌群落α多样性且对β多样性有显著影响.Shen等[22]研究表明稻田土壤细菌的α多样性在变暖与对照土壤之间没有差异,而增温引起细菌群落结构变化差异显著(P=0.001).但也有研究表明增温对小麦成熟期土壤细菌多样性无显著影响[23],其原因可能是:(1)气候类型不同.半干旱区旱地小麦成熟期在7月中旬,雨热同季,强烈的雨热条件差异可能使得土壤细菌在适应和生存策略上不同,从而影响土壤细菌的多样性;(2)种植方式不同.不同的种植方式会影响土壤中的微生物群落结构.轮作有助于调节土壤中的养分平衡,可能影响土壤细菌的生存环境和多样性.而单作模式下,土壤养分的变化相对较为单一,可能对细菌多样性的影响也不同.此外,Hu等[24]研究表明降水量增加对细菌群落多样性无显著影响,与本研究结果相反.这可能是因为该研究地区超过80%降水量主要集中在4~9月的生长季节,导致该研究土壤微生物群落对降水量增加有很强的耐受性.与增温、增水相比,减水对土壤细菌群落多样性无显著影响.Zhang等[25]研究结果也表明细菌丰富度、辛普森指数和β多样性不受降水量减少的影响.因此,农田土壤细菌群落多样性对温度升高和降水量增加很敏感,但对降水量减少有很强的耐受性.
增温和降水变化交互对旱作农田土壤细菌群落多样性有显著影响.本研究中,增温和增水对土壤细菌α多样性无显著影响,但对β多样性有显著影响;增温和减水显著降低了土壤细菌α多样性,但对β多样性无显著影响.Hu等[26]研究发现增温和降水量增加对细菌多样性无显著影响,但使得细菌群落结构发生显著变化.但也有研究发现增温和增水显著降低了土壤细菌α多样性,且对β多样性有显著影响[27],这可能是由于气候条件和生态系统不同所导致的.此外,有研究也表明增温和减水导致土壤细菌α多样性减少且对细菌群落结构无显著影响[28].因此,农田土壤细菌群落多样性对增温和降水变化比较敏感,且受到气温升高和降水量减少的不利影响.
通过构建细菌共发生网络,以探究增温和降水变化对土壤微生物相互作用的潜在影响.增温、降水变化使得旱作农田土壤细菌网络结构发生变化.本研究中增温、增水增强了旱作农田土壤细菌类群之间的相互作用,使得细菌的网络结构更为复杂,且温度升高增加了细菌关键物种数量;但降水量减少降低了细菌共现网络的复杂性,且增加土壤细菌关键物种数量.Xing等[29]研究也发现稻田土壤细菌网络的复杂性在增温时显著增加,Tian等[30]研究还发现气候变暖会增加细菌关键物种数量.此外,有研究结果也表示降水量增加使得细菌共现网络更加稳定,但降水量减少使得细菌共现网络稳定性降低,且增加了细菌关键物种数量[31].这说明土壤细菌网络结构对增温、降水变化的响应受其他因素(作物类型和生态系统等)的影响较小.
增温和降水变化交互引起旱作农田土壤细菌网络结构发生改变.本研究中增温和降水变化均增强了土壤细菌共现网络的复杂性,但增温和减水并未增加细菌关键物种数量.而有研究表明增温和减水增加了细菌关键物种数量[32].这可能是因为海拔高度会影响细菌关键物种数量,高海拔地区(3215m)的细菌关键物种数量会增加[32].此外,降水量变化的幅度不同也可能会影响细菌关键类群的增温效应.
增温、降水变化对土壤细菌群落代谢功能丰度有显著影响.本研究表明增温显著增加了细菌的有机体系统和人类疾病功能丰度,说明增温对土壤细菌群落代谢功能有促进作用,有利于微生物进行分解代谢.这可能是由于土壤细菌群落结构对增温响应迅速,进而对细菌代谢造成影响[33].有研究表明增温会促进土壤有机质的分解[34],但也有研究结论预示在短期变暖条件下微生物C合成代谢潜力的加速,而不是分解代谢[35].因此,在气候变暖条件下微生物代谢功能的变化还需进一步研究.增水显著降低了细菌的新陈代谢功能丰度,这说明降水量增加对土壤细菌群落代谢功能有抑制作用,有助于微生物维持土壤碳储存量,该研究结论与Li等[36]一致.减水显著降低了有机体系统的相对丰度,这说明降水量减少对土壤细菌群落代谢功能有抑制作用,有利于微生物进行土壤碳储存.
增温和降水变化交互对土壤细菌群落代谢功能丰度有显著影响.本研究表明增温和增水显著降低了新陈代谢的功能丰度,但显著增加了人类疾病、有机体系统、细胞过程以及环境信息处理的功能丰度.这说明相比于增温、降水量增加对土壤细菌群落代谢功能的影响,增温和降水量增加交互对其影响更为复杂,值得深入探究.而增温和减水显著增加了有机体系统的相对丰度,这说明增温和降水量减少对土壤细菌群落代谢功能有促进作用,有利于微生物进行分解代谢.
4.1 增温(1.5±0.5)℃、降水量增加30%与增温和降水变化交互(增温+降水量增加30%、增温+降水量减少30%)改变细菌群落的组成.其中,纲水平的优势细菌主要是放线菌、酸杆菌与α变形菌;属水平的优势细菌主要是酸杆菌、绿弯菌和芽单胞菌.
4.2 增温对细菌群落α多样性无显著影响,降水量增加显著增加了细菌群落α多样性,增温和降水量减少交互显著降低了土壤细菌α多样性.
4.3 增温、降水量增加与增温和降水增加/减少交互促进了土壤细菌类群之间的相互作用,使得细菌共现网络更为复杂,但降水量减少30%降低了细菌共现网络的复杂性.
4.4 增温、增温和降水量减少交互对土壤细菌群落代谢功能丰度有促进作用,而降水变化(降水量增加30%和减少30%)对土壤细菌群落代谢功能丰度有抑制作用.
  • 中国气象局干旱气候变化与减灾重点开放实验室基金项目(IAM202102)
  • 国家自然科学基金项目(41775107)
  • 中国气象局创新发展专项(CXFZ2024J056)
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  • 接收时间:2024-05-13
  • 首发时间:2026-03-18
  • 出版时间:2025-01-20
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  • 收稿日期:2024-05-13
基金
中国气象局干旱气候变化与减灾重点开放实验室基金项目(IAM202102)
国家自然科学基金项目(41775107)
中国气象局创新发展专项(CXFZ2024J056)
作者信息
    1.兰州交通大学环境与市政工程学院,甘肃 兰州 730070
    2.中国气象局兰州干旱气象研究所中国气象局干旱气候变化与减灾重点开放实验室,甘肃 兰州 730020
    3.祁连山中部亚高山生态系统野外科学观测研究站,甘肃 张掖 734000

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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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