Bacterial diversity in soils around a lead and zinc mine

Rhizosphere 、Rhizoplane 到底谁才是根际，根际土该如何取？师弟（男）：师兄师兄，根际土该怎么取？本葱：查文献！师妹（女）：师兄，根际土该怎么取？本葱：你这个问题问得好，来来来，师兄跟你讲……根际（Rhizosphere ）是指受植物根系活动的影响，在物理、化学和生物性质上不同于土体的那部分微域土区。

根际的范围很小，一般指离根轴表面数毫米之内。

说到根际（Rhizosphere ）不得不提Bulk 、Rhizoplane 、Endosphere ，尤其是Rhizosphere 与Bulk 、Rhizosphere 与Rhizoplane 经常傻傻分不清。

在文章“Structure,variation, and assembly of the root-associated microbiomes of rice ”中给出的解释是比较经典的，如下图：Bulk （编号B ）：大田土（微生物）、非根际（微生物）。

Rhizosphere （编号S ）：根际（微生物），来自根际土。

Rhizoplane （编号P ）：根表（微生物），紧密附着根表面、部分来自根皮。

Endosphere （编号E ）：内生（微生物）。

转藏到我的图书馆2018-09-06 Seabiscui... 阅 1400 转 12文中给出的方法：Rhizosphere（编号S）：文中将根表约1mm土壤视为根际土，根放入PBS中充分搅动，洗下、收集浊液，不离心，同一天内取部分浊液用作提DNA。

本文为手工搅动，（也有放入摇床中搅动的）。

本文是在同一天完成DNA提取所以没有离心，若要保存，可高速离心后收集土壤进行保存。

Rhizoplane（编号P）：将上述根再次放入PBS中+超声震荡1次（30s 50-60Hz）。

由于此部分微生物较少，提取后作者对DNA进行了浓缩。

Endosphere（编号E）：额外两次超声震荡，玻珠击打均质后，用于提取DNA。

西岛表业学板2018年31卷2期372S o u t h w e s t C h i n a J o u r n a l of Agricultural S c i e n c e s Vol. 31N o. 2文章编号：l〇〇l -4829(2018)2 -0372-07D O I：10. 16213/j. c n k i. s cj a s. 2018. 2. 026不同作物根际土壤生物学性状及细菌多样性特征比较姚华开1，刘岳飞1，张传进1，吴人敏1，杨尚东1’2*(1.广西大学农学院，广西南宁530004;2.广西壮族自治区农业科学院甘蔗研究所/广西甘蔗遗传改良重点实验室，广西南宁530007)摘要：【目的】比较并探究根际土壤生物学性状及细菌多样性能否作为筛选具有促生效果作物组合的生物学指标，为筛选促生的 间套种作物组合及对土壤连作障碍的生态防控提供理论依据和技术支撑。

【方法】选取葫芦科、豆科及旋花科作物根际土壤作为 研究对象，比较不同作物根际土壤生物学性状及细菌群落结构的差异。

【结果】同为葫芦科的根际土壤中涉及土壤碳、氮和磷循环 相关的酶活性之间无显著差异水平，缺乏互补性；而葫芦科作物与豆科的ST豆和旋花科的红薯根际土壤相应的酶活性之间均呈现 显著的差异水平，表现出良好的互补效果；细菌多样性分析结果表明葫芦科作物根际土壤中富集的优势细菌种属趋向一致，而ST 豆和红薯根际土壤中均拥有各自特异的优势细菌种属，同样表现出具有与葫芦科作物互补及提高葫芦科作物根际土壤细菌多样 性的潜力。

【结论】作物根际土壤中涉及碳、氮和磷循环的相关酶活性和细菌多样性指数，以及作物根际土壤中富集的优势细菌种 属均适宜作为鉴定不同作物根际微环境之间是否具有互补效果的生物学指标；ST豆和红薯根际土壤生物学特性表明ST豆和红薯 均具有改良葫芦科作物黄瓜、瓠瓜和南瓜根际土壤微环境的潜力。

关键词：作物；根际；生物学性状；细菌多样性;P C R-D G G E中图分类号:S151.9+4文献标识码:AAnalysis of Soil Biological Properties and BacterialDiversity in Rhizospheres of Different CropsYAO Hua-kai1 , LIU Yue-fei1, ZHANG Chuan-jin1, WU Ren-min1 ,YANG Shang-dong1'2 *(1. Agricultural College of Guangxi University, Guangxi Nanning 530004, China；2. Guangxi Key Laboratory of Sugarcane Genetic Im­provement ,Guangxi Academy of Agricultural Sciences, Guangxi Nanning 530007, China)Abstract:【Objective】 In order to select the growth-promoting crops for bio-controlling the soil-bome diseases, soil biological properties and bacterial diversity in rhizospheres among different crops were analyzed and explored whether they could be used as the biological indicators for the selection of the growth-promoting crops.【Method】 The present study assessed the Cucurbits, Leguminosae and Convolvulaceae crops as the research subjects, and compared the soil biological characteristics and bacterial community structure in rhizospheres of different crops.【Result】 The soil enzyme activities in rhizosphere of Cucurbit involved in soil carbon, nitrogen and phosphorus cycling had no significant difference between each other, without any complementarity. However, soil enzyme activities in rhizosphere between cucurbit crops and sweet potato or legume cowpea showed a significant difference between each other, which indicated that a good complementary effect could be found out in soils between cucurbit crops and sweet potato or legume cowpea. In addition, the results of bacterial diversity showed that the dominant bacterial species in rhizosphere of cucurbit crops tended to be similar. By contrast, specific bacterial species could be found out in rhizospheres of cowpea and sweet potato, respectively. It also indicated that a good complementary effect for bacterial diversity in rhizosphere of cucurbit crops could be implemented by using cowpea or sweet potato for inter-cropping.【Conclusion 】Soil enzyme activities, related to carbon, nitrogen and phosphorus cycling, and the indexes of bacterial diversity in rhizosphere, could be used as bio-indicators to identify thecomplementarity effect in rhizosphere among different crops.Meanwhile, it also showed that cowpea and sweet potato, both收稿日期=2017-10-27基金项目：国家自然科学基金项目（31360506);广西壮族自治 区农业科学院甘蔗研究所/广西甘蔗遗传改良重点实验室开放 课题(16-K-04-01);亚热带农业生物资源保护与利用国家重点 实验室开放课题（O S K L201506);广西研究生教育创新计划项 目（Y C S W2017044,J G Y2017003)作者简介:姚华开（1993-)，侗族，男，贵州铜仁人，硕士研究 生，研究方向为园艺植物营养与生理，E-m a i l:y h k0820 @ 163. c o m,*为通讯作者:杨尚东，E-m a i l:y s d706@g x u. e du. c n。

Soil microbial community structure and function relationships:A heatstress experimentWassila Riah-Anglet a ,*,Isabelle Trinsoutrot-Gattin a ,Fabrice Martin-Laurent b ,Emilie Laroche-Ajzenberg a ,Marie-Paule Norini a ,Xavier Latour c ,Karine Laval aaUnitéAgri'Terr,Esitpa,3rue du Tronquet 76134,Mont Saint Aignan,FrancebINRA,UMR Agroécologie,Écologie des Communautés et DurabilitéSystèmes Agricoles,Centre de Dijon,17rue Sully BP 86510,21065Dijon cedex,France cLaboratoire de Microbiologie Signaux et Microenvironnement (LMSM EA 4312)Normandie Université-Universitéde Rouen -IUT Evreux,Evreux,FranceA R T I C L E I N F OArticle history:Received 5May 2014Received in revised form 25September 2014Accepted 1October 2014Available online xxxKeywords:Microbial diversity Bacterial taxaEnzymatic activities Heat stress Soil land use(>25years).The soil functions were evaluated by measuring the enzyme activities,including cellulase,N -acetyl-glucosaminidase,b -glucosidase,xylanase and dehydrogenase.The total microbial biomass was assayed by the quanti fication of the total DNA extracted from the microcosm soils.The abundance of total bacterial and fungal communities and different bacterial taxa were measured by qPCR rRNA genes.For both soil types,heat stress induced changes in the microbial community structure and soil functions.In most cases,the results yielded effects following heat treatment.All of the enzymes were inhibited except xylanase.Heat stress signi ficantly reduced the total microbial biomass and fungal abundance in the soils.The abundance of the total bacterial community was not affected by heat stress.In the two soils,the dominant taxa were Actinobacteria (13–40%)and Bacteroidetes (14–32%),while Planctomycetes and Gammaproteobacteria exhibited lower abundance (0–3%).Changes in the microbial community structure and changes in the functions were correlated;the correlation was positive in the PG soil and negative in the CC soil.The changes in the CC soil structural and functional state were greater than of those observed in PG soil.Our initial hypothesis was con firmed,indeed,grassland soil is more resistant to drastic stress due to its highly abundant and highly diversi fied microbial community.These results represent a contribution to the understanding of soil microbial community structure and functions relationships.ã2014Elsevier B.V.All rights reserved.1.IntroductionSoils are considered the primary reservoirs of biodiversity (Jangid et al.,2010).Among this biodiversity,micro flora represents a considerable fraction,which is highly diversi fied (Torsvik et al.,1990;Allison and Martiny,2008).A large number of studies have documented how the microbial community struc-ture,or the different types of microorganisms and their abundances (Fuhrman,2009),constitute an essential elementfor understanding the impacts of environmental and anthropo-genic perturbations on soil functioning (Nannipieri et al.,2003).However,the close relationship between the structure of microbial communities and soil functions remain poorly understood because of functional redundancy of microbial communities.Yin et al.(2000)de fined the functional redundancy as the potential for multiple species to be able to perform the same function and thus,changes in the microbial community structure do not necessarily lead to a change in soil functioning (Chapin et al.,1997).Microbial species that appear after an environmental stress or disruption but harbor the same ability to perform a function might (i)not have the same growth rate or competitive ability compared with the original community*Corresponding author.Tel.:+33232829198.E-mail address:wriah@esitpa.fr (W.Riah-Anglet)./10.1016/j.apsoil.2014.10.0010929-1393/ã2014Elsevier B.V.All rights reserved.Applied Soil Ecology 86(2014)121–130Contents lists available at ScienceDirectApplied Soil Ecologyj o u r n a l h o m e p a g e :w w w.e l s e v i e r.c o m /l o c a t e /a p s o i lmembers(Petterson and Bååth,2003),or(ii)not perform functions with the same efficiency and/or generate the same metabolic by-products,or(iii)directly or indirectly influence the activity of other populations in the community.The small numbers of studies addressing the link between microbial community structure and function have shown that the manipulation of species diversity is a key to establishing empirical relationships(Griffiths et al.,2000).Two types of experimental approaches could be identified from the literature for microbial community manipulations:(i)the destructive approach and(ii)the constructive approach.The destructive approach reduces the microbial diversity by creating realistic rates of diversity but has the disadvantage of selecting the most abundant microorganisms(Dimitriu et al.,2010).Other authors have used more destructive methods,such as repeated fumiga-tions to progressively decrease microbial diversity(Dickens and Anderson,1999;Griffiths et al.,2000)or applications of different stress(including biocides)to kill specific microorganisms.The second approach involves the reconstitution of microbial communities through the establishment of a combination of culturable microorganisms(Liebich et al.,2007;Griffiths et al., 2008).The two approaches cited here were biased in the selection of diversity and composition,but are helpful methods for understanding functions of microbial community structural changes or alteration(Griffiths and Philippot,2013;Bell et al., 2005).These studies have demonstrated that a decrease in the diversity is not necessarily followed by loss of function.Indeed some authors argued that community structure is positively correlated with functions(Chesson,2000),and other authors argued that redundancy is similar to an“insurance policy”against functional loss and that species loss is unlikely to impact the function(Yachi and Loreau,1999).This research aimed to examine the relationship between the microbial community structure and soil functions.As defined by Fuhrman,(2009),here we consider microbial structure simply to include the number of different fungal and bacterial species,and their relative abundance in soil microflora.We opted to apply a destructive approach by subjecting soil to heat stress to simplify the microbial community structure and observe consequences on the resultant functions.We studied two soils with the same edaphic characteristics and great difference in microbial commu-nity structure:(i)a permanent grassland(PG)and(ii)a conventional crop(CC).Several authors have already demonstrat-ed that the initial microbial community structure was different between PG soil and CC soil(Jackson et al.,2003;Bissett et al., 2011).Moreover,PG has been described as resilient soil because of the very abundant and highly diversified microbial communities (Jangid et al.,2008).Thus,we hypothesized that the soil function responses to the heat stress would be different in PG soil and in CC soil.Soil functions were studied by evaluating soil enzymatic activities that are considered indicative of specific biochemical reactions of the entire soil microbial community(Nannipieri et al., 2002).Soil microbial community structures were examined by the quantification(qPCR)of the total bacterial and fungal biomasses and ten bacterial taxa.2.Materials and methods2.1.Soil samplingThe soil samples were collected in the experimental site of Yvetôt(northwestern France).The climate was temperate oceanic (+10 C mean annual temperature and850mm annual precipita-tion).The soils characteristics,determined by the Soil Analysis Laboratory(LAS,INRA,Arras,France),are presented in Table1.The soil is defined as a silty soil and classified as a luvisol.The soils were sampled according to two land uses,including a long-term arable conventional cropping plot(>10year,wheat,maize,flax or beet crop rotation)(CC)and a permanent grassland(PG)(>25years, dominant ray-grass species).The soil samples were collected by using an auger at a depth of0–20cm by poolingfive subsamples. Prior to use,the samples were sieved to2mm.The water content was determined after drying10g of soil at105 C in an oven for 24h.2.2.Microcosm preparation and heat stress treatmentsMicrocosms were prepared in20cm3glass jars.Each micro-cosm contained200g of freshly sieved soil.Several temperatures were tested to choose the appropriate heat stress that most impacted the soil’s microorganisms(results not shown).Heat stress at50 C and60 C similarly impacted the microbial communities and the enzymatic activities.A temperature of 50 C was selected for this study.For controls without heat stress, the soils were incubated at17 C,which corresponded to the soil temperature at the time of sampling.The heat stress treatments included PG and CC soil microcosms incubated at17 C and50 C in a ventilated oven for28days.The soils were used directly after sieving without stabilization period.A daily weight of the microcosms allowed for controlling the moisture of the soils. The water losses were replaced using sterile distilled water.Three replicates were performed for each soil at each sampling time (5,14,21and28days)and at each temperature treatment,for a total of48samples(24destructive microcosms for the PG plot and 24destructive microcosms for the CC plot).T=0corresponded to 5days after the start of the incubation to avoid including the disturbances of soil microbial community caused by the establish-ment of the experiment.2.3.Total DNA extraction and real-time PCR quantification(qPCR)For the48replicates,the total DNA of the soil was extracted from0.5g fresh soil using the BIO101Fast DNA Spin Kit for soil (MP-Biomedicals,France).The total DNA extracts were re-suspended in sterile deionised water in afinal volume of 50m L and were quantified using the Fluorescent DNA Quantifica-tion Kit(picoGreen,invitrogen)(Gangneux et al.,2011).The DNA extracts were stored atÀ20 C.The total bacterial communities and some bacterial taxa (Actinobacteria,Acidobacteria,Firmicutes,Alphaproteobacteria, Bacteroidetes,Gemmatimonadetes,Verrucomicrobiales,Table1Physicochemical properties of soils.Site Plot Soil propertiesClay(g kgÀ1)Silt(g kgÀ1)Sand(g kgÀ1)Total C(g kgÀ1)Total N(g kgÀ1)pH water CEC(cmolÆkgÀ1)P2O5(g kgÀ1)Yvetot PG163Æ(5.38)633Æ(4.64)204Æ(4.99)26Æ(0.96) 2.50Æ(0.07) 5.46Æ(0.05)8.08Æ(0.26)0.13Æ(0.13) CC133Æ(3.95)671Æ(3.92)196Æ(6.45)11Æ(0.34) 1.10Æ(0.04) 6.43Æ(0.04)7.04Æ(0.30)0.20Æ(0.02)MeanÆ(SD).122W.Riah-Anglet et al./Applied Soil Ecology86(2014)121–130Betaproteobacteria,Planctomycetes and Gammaproteobacteria) were quantified using the taxon-specific16S rRNA qPCR assays developed by Philippot et al.(2011)using an Applied Bioystem 7300.The qPCR assay was carried out in a total volume of15m L with1ÂSYBR green PCR Master Mix(Absolute QPCR SYBR Green Rox ABgene),1m M of each primer,16.66ng m LÀ1of T4bacteriophage gene32(QBiogene,France),and2ng of total DNA.Standard curves were obtained using serial dilutions of linearized plasmids containing the cloned16S rRNA genes from the different taxa.The qPCR was performed as described by Philippot et al.(2011)in an Applied Bioystem7300.The qPCR efficiency for the assays ranged between86%and99%.The no template controls showed null or negligible values.The presence of PCR inhibitors in the DNA extracted from the soil was estimated by(1)diluting the soil DNA extract and(2)mixing a known amount of standard DNA with the soil DNA extract prior to the qPCR analysis.No inhibition was detected in either case.Two independent qPCR assays were performed for each taxon.The results are expressed as the16S rRNA gene copy number per gram of soil dry weight(gÀ1DW).The results of the bacterial taxa quantification are expressed as a percentage of the changes from control in the relative abundance of bacterial groups,and the soils incubated at17 C were used as a reference point in the PG and CC soils.The changes in the relative abundance of the bacterial taxa were calculated for each bacterial group and for each incubation time.A negative percentage indicates a decrease in the relative abundance,and a positive percentage indicates an increase in the relative abundance of the bacterial taxa by heat treatments.For the total fungal communities,18S rRNA qPCR amplifications were performed in a total volume of25m L with1ÂqPCR Master Mix(SYBR Green I,Applied Bioystem),0.5m M of FU18S1and Nu-SSU-1536primers(Borneman and Hartin,2000),0.5mg mLÀ1 BSA(NEB)and10ng of total DNA.Standard curves were obtained using serial dilutions of linearized plasmids containing the cloned 18S rRNA gene of Fusarium graminearum.After an initial denaturation and enzyme activation step of10min at95 C, 40cycles of PCR were performed in an Applied Bioystem7300as follows:20s at95 C,30s at62 C and30s at72 C.The qPCR efficiency ranged from95%to98%.The results are expressed as the 18S rRNA gene copy number per gram of soil DW.2.4.Enzyme assaysThe activities of four enzymes were measured using the methods described in Table2.Cellulase,N-acetyl-glucosaminidase, b-glucosidase,xylanase and dehydrogenase activities wereexamined in three replicates for each soil sample.A unit of enzyme activity was defined as the nanomoles of substrate hydrolyzed or oxidized per minute and per gram of soil DW.As in previous approaches(Sannino and Gianfreda,2001;Floch et al., 2011),the enzyme activity values of the soils incubated at17 C were used as a reference point,which allows for the conversion of the enzyme activity values of soils incubated at50 C as a percentage of changes.The enzymatic activities were calculated for each enzyme and for each incubation time.A negative percentage indicates enzymatic activities inhibition,and a positive percentage indicates stimulation by heat treatments.2.5.Statistical analysesStatistical tests were performed to highlight the effects of heat stress on the soil total microbial biomass,the total bacterial and fungal communities,the abundance of different bacterial taxa and enzymatic activities.The data measured for soils incubated at50 C and the control soils incubated at17 C at each incubation time were compared by Student’s t-test with significant differences at 5%(P<0.05).For each soil land use type,two Principal Component Analysis(PCA)were performed(see Supplementary data).Thefirst PCA was performed with twelve structural variables,and the second PCA was performed withfive functional variables.The projection of all the sample coordinates according to thefirst and second axis of the factorial plan of each PCA allowed us to extract these coordinates and calculate the Euclidean distances.Nine combinations of Euclidean distances were obtained because three replicates were performed for each soil land use type at each temperature and at each incubation time(see Section2.2).The nine obtained Euclidean distances were used to calculate the means and standard deviations.The values of Euclidean distances provide information on the degree of the difference between the soil land use types for structural and functional profiles.For example,in the CC soil,the large distance measured at5days obtained with the structural variables indicates that heat stress had a large impact on the structure of the microbial communities in this soil.For each land use type,the correlation between the amplitude changes in structure and function(Euclidean distances) under heat stress was tested by Spearman’s correlations.All the statistical tests were computed with the R freeware(R Develop-ment Core Team,2009).3.Results3.1.Abundance of microbial communities in PG and CC soilThe total microbial biomass was measured by the total DNA quantification expressed as micrograms per gram of soil DW (Table3).The heat stress significantly reduced the total microbial biomass(from26.7Æ1.05to9.78Æ1.50in PG and from16.5Æ7.60to 6.33Æ3.87in CC).The microbial community was dominated by bacteria in both soil types.Fungi(expressed as the18S rRNA gene copy number per gram of soil DW)were less abundant than bacteria in these soil types and were more sensitive to warming.Indeed,in PG soil the changes ranged from2.28Â108Æ0.74Â108to0.28Â108Æ0.15Â108and from6.75Â107Æ3.0Â107to1.72Â107Æ2.67Â107in CC soil.Bacteria(expressed as the16S rRNA gene copy number per gram of soil DW)were not significantly affected by the heat stress. The bacterial biomass ranged(from6.05Â108Æ2Â108to3.56Â108Æ3.15Â108in PG and from0.86Â107Æ0.28Â107to0.70Â107Æ0.47Â107in CC soil).Table2Protocols used for enzyme assays.Enzymes E.C.number Substrates(pH buffer and concentration)ReferencesDehydrogenase 1.1.1.12-(p-Iodophenyl)-3-(p-nitrophenyl)-5-phenyltetrazolium chloride Schaefer,1963Cellulase 3.2.1.4p-NP-b-D-Cellobioside(pH6;10mM)Trap et al.,2012N-Acetyl-glucosaminidase 3.2.1.30p-NP-N-Acetyl-glucosaminide(pH6;10mM)Trap et al.,2012b-Glucosidase 3.2.1.21p-NP-b-D-Glucopyranoside(pH6;10mM)Eivazi and Tabatabai,1988 Xylanase 3.2.1.8Xylan(pH5.5,12g LÀ1)Schinner and Von Mersi,1990 NP:nitrophynyl.W.Riah-Anglet et al./Applied Soil Ecology86(2014)121–1301233.2.Changes in bacterial population under heat stressTo estimate the relative abundance of the different studied taxa within the total bacterial community in PG and CC soils,we calculated the ratio of the taxon-specific16S rRNA gene copies per gram of soil DW to the total bacterial16S rRNA gene copies per gram of soil DW.In the control PG and CC soils incubated at17 C, the sum of the relative abundance of all the studied taxa reached a maximum of68%in the PG soil and92%in the CC soil.In both soils types,the dominant taxa were Actinobacteria(13–40%)and Bacteroidetes(14–32%).The Planctomycetes and Gammaproteo-bacteria taxa had lower abundances(0–3%).The abundance of other groups(Acidobacteria,Firmicutes,Alphaproteobacteria, Gemmatimonadetes,Verrucomicrobiales,and Betaproteobacteria) ranged between the abundance of dominant and less represented taxa.The results of the changes from the control in the relative abundance of bacterial taxa in the PG and CC soil types are presented in Fig.1.In the PG soil,a significant decrease was observed from the start of the incubation for the Acidobacteria,Planctomycetes,Alphap-roteobacteria,and Gammaproteobacteria taxa,this decrease on average reached80%in comparison to PG control soils.For the Actinobacteria,Bacteroidetes and Gemmatinomonadetes taxa,the decrease appeared only at the end of the incubation.The Firmicutes,Verrucomicrobiales and Betaproteobacteria taxa seemed to be insensitive to warming even if transient effects were observed.In the CC soil,among the10analyzed bacterial taxa, Gammaproteobacteria,and Acidobacteria decreased about95% and Actinobacteria and Planctomycetes decreased about20%, respectively,under heat stress in comparison to CC control soils. While Bacteroidetes,Gemmatinomonadetes,Verrucomicrobiales, Betaproteobacteria,and Alphaproteobacteria were less sensitive, as shown by the transitory increased or decreased effects.The Firmicutes taxa increased at the end of incubation period.3.3.Heat stress effects on PG and CC soil enzymatic activitiesHeat stress treatment did not have the same impact on all the enzymes tested in the PG and CC soils(Fig.2).In most cases,heat stress inhibited the enzymatic activities for the two soils over time. The cellulase,b-glucosidase dehydrogenase and N-acetyl-glucosaminidase activities decreased significantly following heat treatment during the incubation time(5–28days).For the N-acetyl-glucosaminidase activity at5days of incubation,a transient stimulating effect was observed(153%)in the CC soil.A different effect of heat stress was observed for xylanase activity,depending on the soils.In the PG soil,this activity increased significantly at21days of incubation(104%).In the CC soil,after an initial decrease,this activity tended to return to its initial soil background level at14days of incubation.3.4.Relationships between structure and functions of soil microbial communitiesTo explore the relationships between the soil microbial community structure and functions,Euclidean distances were calculated,and the correlations were used as described in Section2.Thefirst step consisted of a comparison of PG and CC reference soils based on the calculated distances to evaluate the impact of the two land use types on microbial community structure and functions.The results highlighted a constant difference between the two soils over time(average distances of 2).Thisfinding confirmed the impact of management on the soil microbial community structural and functional states(Fig.3).The second step relied on a comparison of the microbial community structure and functions in each soil type(PG and CC)under heat stress based on the calculated distances.In the PG and CC soils, heat stress had an effect on the microbial community structure and functions(see PCAs in Supplementary data).Significant changes from the control in structure and functions were observed(Fig.4). According to our measurement changes approach,the structure and function of microbial communities of the CC soil were more severely impacted by heat stress compared with PG soil.The CC soil showed impacts that were3times and1.5times greater on the structure and functions,respectively(Fig.4).In the PG soil,there was a significant change from the control in the microbial community structure at the beginning of incubation (distance=1.32).This progressive change achieved its maximum at 21days of incubation(distance=6.32).Changes in the functions occurred at the beginning of the incubation and then remained constant.Spearman’s correlation showed a relationship between the changes in microbial community structures and the changes in functions in the PG soil(r=0.34,P<0.05).In the CC soil,significantTable3The total nucleic acid and quantification of the ribosomal gene copies by qPCR from PG and CC soils at different incubation times.Land use Days Treatment Total nucleic acid,m g g soilDWÀ1Bacterial16S rRNA genes copy number,g soil DWÀ1(Â1010)Fungal18S rRNA genes copy number,g soil DWÀ1(Â108)PG5Con25.6Æ(2.4)a 4.30Æ(3.90) 1.20Æ(0.14)aWarm7.70Æ(2.6)b0.82Æ(0.31)0.43Æ(0.03)b14Con28.0Æ(1.1)a 6.20Æ(0.62) 2.80Æ(0.11)aWarm9.80Æ(1.5)b 4.50Æ(3.10)0.38Æ(0.18)b21Con27.1Æ(0.4)a8.80Æ(3.60)a 2.70Æ(0.29)aWarm11.2Æ(5.6)b 1.30Æ(0.40)b0.20Æ(0.09)b28Con26.2Æ(0.9)a 4.90Æ(2.70) 2.40Æ(0.18)aWarm10.4Æ(4.2)b7.60Æ(5.70)0.11Æ(0.07)b–CC5Con 5.20Æ(2.2)a0.62Æ(0.15) 2.40Æ(2.00)aWarm12.1Æ(3.1)b 1.30Æ(0.13) 5.70Æ(0.23)b14Con19.7Æ(1.8)a0.62Æ(0.20)8.10Æ(5.20)aWarm 4.00Æ(0.7)b0.44Æ(0.39)0.76Æ(0.70)b21Con21.5Æ(0.9)a 1.10Æ(0.21)a7.30Æ(6.30)aWarm 4.90Æ(3.3)b0.23Æ(0.12)b0.17Æ(0.10)b28Con19.7Æ(1.3)a 1.10Æ(1.00)9.20Æ(6.40)aWarm 4.30Æ(0.9)b0.81Æ(0.51)0.24Æ(0.22)bMeanÆ(SD).Letters(a and b)indicate significant difference between control(Con)and heated soil(Warm)in PG and CC soil at each incubation time(Student’s test P<0.05, n=3).124W.Riah-Anglet et al./Applied Soil Ecology86(2014)121–130changes from the control in the microbial community structure and enzymatic activities were observed at the beginning of the incubation.Changes in the microbial community structure then remained constant.Changes in the enzymatic activities declinedsigni ficantly and progressively after 21days of incubation (distance decreased from 4.28to 2.33).The changes in the microbial community structure were negatively correlated with the changes in the functions in the CC soil (r =À0.69,P <0.05).-20 0-1000100200300400% o f c h a n g e s f r o m c o n t r o l-50050100150200250% o f c h a n g e s f r o mc o n t r o l-20 0200400600800% o f c h a n g e s f r o m c o n t r o l-12 0-80-4004080% o f c h a n g e s f r o mc o n t r o l-10 00100200300400% o f c h a n g e s f r o mc o n t r o l-20 0-10 00100200300400% o f c h a n g e s f r o m c o n t r o l-40 0040080012001600% o f c h a n g e s f r o mc o n t r o l-20 0-10 00100200300400% o f c h a n g e s f r o m c o n t r o l-10 00100200300% o f c h a n g e s f r o mc o n t r o l-20 02004006008001000% o f c h a n g e s f r o mc o n t r o l5 14 2128days5142128days5 14 21 28 days5142128days5142128days5142128days5 14 21 28days5142128daysFig.1.The effect of heat stress on the relative abundance of bacterial phyla from the PG and CC soils at each incubation time.The error bars represent the standard deviation ofthe mean of three replicates (n =3).The signs (*)and (z )above the histogram indicate signi ficant differences between the control and the heated soil at 50 C in the PG and CC soil,respectively (Student ’s test P <0.05).W.Riah-Anglet et al./Applied Soil Ecology 86(2014)121–1301254.Discussion4.1.Changes of microbial community structure under heat stressIn this study,total microbial biomass was assessed according to the DNA analysis,however,our findings agreed with reductions reported in microbial biomass C due to heat stress in other studies.Joergensen and Brookes (1991),for example,observed a decreased in the soil microbial carbon biomass of 1.72%per day at 35 C during a 50day incubation experiment.In the majority of heating studies,heat stress causes no effect or a drastic reduction in the soil-200-1000100200300% o f c h a n g e s i n e n z y m e a c t i v i t y-80-60-40-200% o f c h a n g e s i n e n z y m e a c t i v i t yβ-glucosidase-120-100-80-60-40-200% o f c h a n g e s i n e n z y m e a c t i v i t yCellulase-120-100-80-60-40-200% o f c h a n g e i n e n z y m e a c t i v i t yDehydrogense-100-50050100150% o f c h a n g e s i n e n z y m e a c t i v i t y571428days571428days571428days571428days571428daysFig.2.The effect of heat stress on N -acetylglucosaminidase,b -glucosidase,cellulase,xylanase and dehydrogenase activities of the PG soil and CC soil at each incubation time.The error bars represent the standard deviation of the mean of three replicates (n =3).The signs (*)and (z )above the histogram indicate signi ficant differences between the control and the heated soil at 50 C in the PG and CC soil,respectively (Student ’s test P <0.05).12345142128E u c l i d e a n d i s t a n c e (C h a n g e s b e t w e e n P G a n d C C )DaysstructureFig. 3.Changes in the microbial community structure and enzymatic activity functions at each incubation time expressed by Euclidean distances between the PG and CC control soils.The error bars represent the standard deviation of the mean of nine replicates.No signi ficant differences were observed between the changes in the structure and function at 5days and 14days or between 21days and 28days (Student ’s test P <0.05).E 5con-5warm x5con-5warm x betwee ns ns ns 02468105142128u c l i d e a n d i s t a n c e (c h a n g e s f r o m c o n t r o l )nctionstructurePGfu nctionPGstructureANOVA14con-14warm 21con-21 warm 5con-5warm x28con-28warmCorrelation n S and FPGStructure (S)* * *r = 0,34 *Fun ction (F)nsns nsCCStructure (S)r = - 0,69*Functi on (F)***Fig.4.The changes in the microbial community structure and enzymatic activity functions in the PG soil and CC soil at each incubation time expressed by Euclidean distances.The error bars represent the standard deviation of the mean of nine replicates.(*)indicates a signi ficant difference between the changes at 5days and 14days and between 21days and 28days (Student ’s test P <0.05).ns:no signi ficant differences.r:Spearman coef ficient correlation between structure and function.126W.Riah-Anglet et al./Applied Soil Ecology 86(2014)121–130。

Soil Microbial Diversity Soil microbial diversity is a critical aspect of the overall health and functionality of soil ecosystems. The diversity of microorganisms in soil,including bacteria, fungi, and other microbes, plays a crucial role in nutrient cycling, soil structure, and overall ecosystem resilience. However, this diversity is increasingly threatened by human activities such as industrial agriculture, deforestation, and urbanization. In this response, we will explore the importance of soil microbial diversity, the threats it faces, and potential solutions to preserve and enhance it. One of the key reasons why soil microbial diversity isso important is its role in nutrient cycling. Microbes in the soil play a vitalrole in breaking down organic matter and releasing nutrients that are essentialfor plant growth. This process is crucial for maintaining the fertility of thesoil and supporting healthy plant communities. Additionally, soil microbial diversity also contributes to soil structure, as certain microbes produce substances that help bind soil particles together, improving its stability and ability to retain water. Furthermore, soil microbial diversity is also essential for the overall resilience of ecosystems. A diverse microbial community is better able to withstand environmental stresses and disturbances. For example, in theface of a drought or extreme temperatures, a diverse microbial community is more likely to contain species that are able to survive and continue providingessential ecosystem services. This resilience is crucial for maintaining the productivity and stability of agricultural systems, as well as natural ecosystems. Despite its importance, soil microbial diversity is increasingly threatened by human activities. The expansion of industrial agriculture has led to the widespread use of chemical fertilizers, pesticides, and herbicides, which can have detrimental effects on soil microbial communities. Additionally, deforestation and urbanization can lead to the loss of important microbial habitats and further reduce diversity. Climate change is also a significant threat, as it can disrupt the delicate balance of microbial communities in the soil. To address thesethreats and preserve soil microbial diversity, a multi-faceted approach is necessary. First and foremost, sustainable agricultural practices that prioritize soil health are essential. This includes reducing the use of chemical inputs,implementing crop rotation and cover cropping, and minimizing soil disturbance. These practices not only support soil microbial diversity but also contribute to overall ecosystem health and resilience. Furthermore, protecting natural habitats and reducing deforestation and urbanization are also crucial steps in preserving soil microbial diversity. By maintaining diverse and undisturbed ecosystems, we can help ensure that soil microbial communities are able to thrive and continue to provide essential ecosystem services. Additionally, more research is needed to better understand soil microbial communities and their responses to environmental changes. This knowledge can then be used to develop targeted conservation and restoration strategies. In conclusion, soil microbial diversity is a critical component of healthy and functional ecosystems. Its role in nutrient cycling, soil structure, and overall resilience cannot be overstated. However, it isincreasingly threatened by human activities and environmental changes. By prioritizing sustainable agricultural practices, protecting natural habitats, and investing in research, we can work towards preserving and enhancing soil microbial diversity for the benefit of current and future generations.。

Soil Bacterial Community Soil bacterial community plays a crucial role in maintaining soil health and ecosystem functioning. However, various factors such as land use change, climate change, and pollution can significantly impact the diversity and composition ofsoil bacterial communities. This essay will discuss the problems associated with soil bacterial community and potential solutions to address these issues. Firstly, land use change, particularly the conversion of natural ecosystems to agricultural land, can lead to a decline in soil bacterial diversity. Intensive agricultural practices, such as the use of chemical fertilizers and pesticides, can alsodisturb the natural balance of soil bacterial communities. As a result, the soil may become less resilient to environmental stress and more susceptible to diseases. This problem is further exacerbated by the loss of habitat for beneficial soil bacteria, which are essential for nutrient cycling and soil fertility. Inaddition to land use change, climate change poses a significant threat to soil bacterial communities. Changes in temperature and precipitation patterns can directly impact the abundance and activity of soil bacteria. For example, extreme weather events such as droughts or heavy rainfall can disrupt the soil structure and alter the availability of oxygen, which in turn affects the distribution ofsoil bacteria. Moreover, rising temperatures can accelerate the decomposition of organic matter, leading to changes in nutrient cycling processes mediated by soil bacteria. Furthermore, soil pollution from industrial activities and improper waste disposal can have detrimental effects on soil bacterial communities. Contamination with heavy metals, pesticides, and other toxic substances caninhibit the growth of certain bacterial groups and disrupt the overall balance of the soil microbiome. As a result, the capacity of the soil to support plant growth and provide ecosystem services may be compromised. To address these problems, itis essential to implement sustainable land management practices that promote soil health and biodiversity. This includes reducing the use of chemical inputs in agriculture, adopting agroecological approaches, and restoring degraded soils. By promoting the conservation of natural habitats and minimizing soil disturbance, it is possible to enhance the resilience of soil bacterial communities and theirability to support ecosystem functioning. Additionally, efforts to mitigateclimate change and adapt to its impacts are crucial for maintaining soil bacterial diversity. This involves reducing greenhouse gas emissions, promoting carbon sequestration in soils, and implementing measures to enhance soil water retention and reduce erosion. By addressing the root causes of climate change, it is possible to minimize its negative effects on soil bacterial communities. Finally, effective soil pollution control measures, such as remediation techniques and pollution prevention strategies, are essential for safeguarding soil bacterial communities. This includes the use of bioremediation methods that harness the metabolic capabilities of soil bacteria to degrade contaminants. Furthermore, promoting the use of organic farming practices and phytoremediation can help to reduce soil pollution and protect the diversity of soil bacteria. In conclusion, the problems associated with soil bacterial communities are multifaceted and interconnected with broader environmental issues. By addressing the underlying causes of these problems and implementing sustainable land management practices, it is possible to mitigate the negative impacts on soil bacterial diversity and promote soil health. This, in turn, will contribute to the resilience and sustainability of ecosystems and agricultural systems.。

中国环境科学 2017,37(11)：4230~4240 China Environmental Science 煤矸石充填不同复垦年限土壤细菌群落结构及其酶活性侯湖平,王琛,李金融,丁忠义,张绍良*,黄磊,董健,马静,杨永均(中国矿业大学环境与测绘学院,江苏徐州 221116)摘要：基于徐州市3块煤矸石充填复垦地(复垦时间分别为2015、2010和2001年)的土壤样本,采用llumina PE250测序方法测定微生物群落组分,以未受采煤塌陷影响区的土壤样本为对照地,对比分析充填复垦区细菌群落的垂直结构及其时间变化.结果表明:(1)与对照地相比,复垦土壤在各个分类水平的细菌种类数量减少,群落多样性降低.随着复垦年限的增加,复垦地与对照地的贴近度越高.(2)厚壁菌门、变形菌门是复垦土壤中门水平的优势菌,厚壁菌门在复垦土壤中优势地位上升,有从20~40cm土层向0~20cm土层转移的趋势.(3)芽孢杆菌纲在纲水平占绝对优势,在复垦土壤0~20cm土层中的数量多于对照土壤,在复垦土壤20~40cm土层的数量随年限增加而减少.(4)乳杆菌目、芽孢杆菌目在目水平是优势菌,除硫单胞菌目对重金属污染修复有重要作用,然而在复垦土壤的0~20cm土层中的数量比正常农田土壤少74.81%~99.59%.(5)芽孢杆菌科、肠球菌科、链球菌科是科水平的优势菌,芽孢杆菌属、肠球菌属、乳球菌属是属水平的优势菌,芽孢杆菌属-JH7、屎肠球菌、乳球菌属-piscium是种水平的优势菌,3大类在复垦土壤中的数量比例大于正常农田,且在0~20cm土层中的差别更明显,在复垦土壤的20~40cm土层的数量随年限增加而减少.(6)脱氢酶活性与厚壁菌门下的多种细菌的数量呈显著负相关,与放线菌门的数量呈显著正相关,与γ-变形菌纲的数量呈极显著正相关.随着复垦年限的增加,土壤优势菌群的类型没有变化,但是数量结构在变化.厚壁菌门在缺水和极端环境下适合生长,变形菌门有助于土壤氮素以及能量的循环.采用微生物修复技术,调整土壤细菌群落结构,可以改善土壤质量,缩短土壤恢复年限.关键词：煤矸石充填复垦；微生物群落；细菌群落；复垦年限；徐州矿区中图分类号：X171 文献标识码：A 文章编号：1000-6923(2017)11-4230-11Variation of bacterial community structure and enzyme activities in reclaimed soil filled with coal gangues along a relamation chronosequence. HOU Hu-ping, WANG Chen, LI Jin-rong, DING Zhong-yi, ZHANG Shao-liang*, HUANG Lei, DONG Jian, MA Jing, YANG Yong-jun (School of Environment Science & Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China). China Environmental Science, 2017,37(11)：4230~4240Abstract：In this study, soil samples from the reclaimed land filled with coal gangue (SS) with different reclamation years (2015, 2010, and 2001 years) in Xuzhou mining area and from normal farmlands which were not affected by coal mining subsidence (SSC) were collected. The sequence numbers of bacterial community were determined by the Illumina PE250sequencing method, and the vertical structure and time structure were analyzed. The results showed that: (1) Reclamation decreased the number of bacteria species and the community diversity, but the goodness between SS and SSC increased with the age of reclamation. (2) Firmicutes and Proteobacteria dominated in SS at the phylum level, the number of Firmicutes increased after reclamation and Firmicutes also likely transferred from 20~40cm to 0~20cm soil layer. (3) Bacilli predominantly existed in soils at the class level, the number of Bacilli in 0~20cm soil layer was higher in SS than in SSC samples, and the number in 20~40cm soil layers of SS samples decreased with the increase of the reclamation years. (4) Lactobacillales and Bacillales dominated in SS at the order level. Desulfuromonadales played an important role in the remediation of heavy metal pollution and its number in 0~20cm soil layer of SS was 74.81~99.59% less than that in SSC samples. (5) In SS samples, Bacillus, Enterococcus and Streptococcaceae were the dominant family, while Bacillus, Enterococcus and Lactococcus were the dominant genus, and Bacillus sp. JH7, Enterococcus faecium and Lactococcus piscium were the dominant species. All of these in SS samples were less in number than SSC samples收稿日期：2017-04-14基金项目：国家自然基金资助项目(51474217);中国矿业大学大学生创新训练项目(201610290044)* 责任作者, 教授, slzhang@11期侯湖平等：煤矸石充填不同复垦年限土壤细菌群落结构及其酶活性 4231especially in 0~20cm soil layer, while the number in 20~40cm soil layer of SS decreased with the increase of the reclamationyears. (6) Dehydrogenase activity was negatively correlated with the number of Firmicutes.spp, but was positively correlatedwith the number of Actinobacteria and the number of Gammaproteobacteria. Also, the type of dominant soil bacteria did notchange, but their quantitative structure varied over time. Owing to Firmicutes are suitable for growth in the absence of waterand extreme environments, but Proteobacteria is conducive to soil nitrogen and energy cycling. Therefore, the soil qualitywas improved by adjusting soil bacterial community structure and shorten the recovery period.Key words：land reclamation filled with coal gangue；soil microbial community；bacterial community structure；reclamation term；Xuzhou coal-mining areas煤炭资源开发在促进经济发展的同时,对生态环境也产生巨大的负效应,煤矸石堆积与土地沉陷是其中的问题之一.煤矸石充填复垦是处理煤矸石问题之一,它是以煤矸石为充填物并在上面填充土壤,使其土地达到可供利用状态的复垦模式.该模式一方面解决煤矸石压占土地的问题,另一方面,降低煤矸石对大气、土壤和水等造成的一定程度污染,在我国被广泛应用[1].但是,复垦后的农田与未受采煤塌陷的正常农田相比,土壤理化性质和土壤微生物群落的结构特征发生变化[2-4],进而影响着复垦后耕地的质量.土壤细菌群落结构特征和变化规律能够反映矿区复垦土壤微生物群落多样性和生态功能,反应土壤复垦水平和质量[5-8].国内外学者对矿区复垦土壤中的微生物进行研究,主要有以下几个方面:一是针对复垦土壤微生物的生物量及其数量进行研究,分析复垦前后不同复垦年限、不同植被模式下土壤细菌、真菌、放线菌的生物量及其数量变化[10-13].二是对复垦土壤中细菌群落多样性的研究,包括不同复垦年限煤矸石填埋场的土壤微生物特性[3],对不同复垦植被类型和复垦年限对土壤细菌群落多样性的影响[14],土壤pH值变化对复垦土壤细菌群落多样性以及细菌门结构特征的影响[15].三是对细菌群落结构中优势菌群的研究,诸如中国东部矿区不同复垦植被类型和不同复垦时间土壤细菌的优势菌及其多样性[16],我国准格尔地区煤矿不同复垦时间土壤细菌组成及其多样性的变化[17].四是对复垦土壤中微生物量和土壤养分的相关性研究,诸如昆阳磷矿不同年限和不同植被的矿山恢复土壤的理化性状和微生物的相关性[18],研究采石场不同开采模式和土壤恢复模式对土壤微生物群落的活性、生物量和遗传结构的影响[5].这些研究多针对复垦土壤中的微生物活动情况,但是对于煤矸石充填复垦土壤中细菌群落的研究不够深入.本研究以徐州不同复垦年限的煤矸石复垦地为研究对象,研究复垦区土壤0~20cm和20~40cm深度的土壤样本,采用I llumina PE250测序方法,测定土样中细菌门、纲、目、科、属、种6个水平的序列数,研究煤矸石充填复垦土壤细菌群落的结构、多样性及其酶活性,目的在于分析煤矸石充填复垦地不同复垦年限土壤细菌群落的变化特征,为采用微生物修复措施提高复垦地质量提供理论依据.1材料与方法1.1研究区概况研究区位于江苏省徐州市西北部的煤矿开采区,属于华东高潜水位平原区,属暖温带半湿润季风气候区,四季分明.年气温13.8℃,年日照时数为2284~2495h,日照率为52%~57%,年均无霜期200~220d,年均降水量800~930mm,年均湿度72%.气候资源丰富,适宜农作物生长,为我国华东地区重要粮食产区.该区域正常水旱轮作地的地下水位在(0.80±0.20)m,正常旱地地下水位在1.0m以下.受采煤影响,研究区复垦前最大沉陷量1~1.5m,最小沉陷量0.6m,平均沉陷量1.1m,大部分塌陷地出现积水,农田绝产.煤矸石充填前,首先将积水清理,然后表土层剥离,采用统一矸石分层振压回填复垦,充填煤矸石4.6m,压实度为85%,覆土厚度为50cm.经检测,煤矸石有毒元素的平均含量分别为:Hg为0.104mg/kg(标准值为0.15mg/kg),Cd为0.086mg/ kg(标准值为0.2mg/kg),Pb为29.73mg/kg(标准值为35mg/kg),As为9.25mg/kg(标准值为15mg/kg),4232 中国环境科学 37卷该含量均符合我国土壤的可接受水平[19].在研究区内选取3块不同复垦年限的煤矸石充填复垦地,并在每块复垦地附近1km以内选取未受采煤塌陷影响的正常农田作为对照地,对照地与复垦地具有相同的种植作物种类和施肥管理方式.第1块复垦地S(116°48′44″E, 34°48′47″N),复垦年限为1年,对照地SC (116°48′36″E,34°48'25″N);第2块复垦地M (117°23′48″E,34°21'25″N),复垦年限为6年,对照地MC(117°23′36″E,34°21′05″N);第3块复垦地L(117°08′22″E,34°25' 24″N),复垦年限为15年,对照地LC(117°08′33″E,34°25'25″N).复垦地和对照地的地面作物以种植玉米和大豆为主,一年两熟制,作物长势良好.土壤以黄河冲积物为其母质发育而成,土壤类型为普通褐土,土壤pH6~7呈弱酸性,土壤电导率为652.1~664.3μS/cm,属于正常的盐分浓度范围.1.2土壤样本采集采样时间为2016年6月.每块样地以S型采样,利用无菌取土器取0~20cm和20~40cm深度的土壤样品各约1kg,共采样12个点,每个点取样取5次重复,然后混合作为样本.将一部分新鲜土样研磨过2mm筛后,置于-20℃冰箱中保存待用,3d内进行土壤微生物指标分析;另一部分土样进行自然风干,研磨处理,过0.149mm筛后,用于土壤理化性质和酶活性指标分析.1.3土壤细菌的16S rRNA 基因测序1.3.1 DNA提取和PCR扩增利用E.Z.N.A.Soil DNA试剂盒(Omega Bio-tek, Norcross, GA, U.S.)提取12个土壤样本DNA.针对细菌的16S rRNA的V4-V5区进行PCR扩增.使用的兼并引物为:515F 5’-barcode-GTGCCAGCMGC-CGCGG)-3’和907R 5’-CCGTCAATTCMTTT-RAGTTT-3’.PCR,扩增程序如下:95℃预变性2min,随后95℃变性30s,55℃退火30s,72℃延伸30s,共25个循环;最后72℃最终延伸5min结束. PCR反应在一式3份的20μL含有4μL 5×FastPfu 缓冲液,2μL 2.5m dNTP,0.8μL每种引物(5μmol/ L),0.4μL FastPfu聚合酶和10ng模板DNA的混合物中进行.从2%琼脂糖凝胶中提取扩增子,并利用AxyPrep DNA凝胶提取试剂盒(Axygen Biosciences,Union City,CA,U.S.)进行纯化,并使用QuantiFluor TM-ST(Promega,U.S.)进行定量.实验过程中,每个样本进行3个重复.1.3.2文库的构建及测序纯化的PCR产物通过Qubit®3.0(Life Invitrogen)定量,并且序列不同的每12个扩增子混合均匀.在Illumina的基因组DNA文库制备程序之后,将汇集的DNA产物用于构建I llumina Pair-End文库.然后根据标准方案在Illumina MiSeq平台(上海BIOZERON有限公司)上对扩增子文库进行配对终点测序(2×250).原始读取存储在NCBI序列读取存档(SRA)数据库中.1.4数据处理1.4.1原始数据处理与样本序列数目统计使用QIIME(1.17版本)对原始fastq文件进行质量过滤:在任何平均质量评分小于20的位点,在10bp滑动窗口上截断250bp读数,丢弃短于50bp 的截断读数.精确条码匹配,引物匹配中的2个核苷酸不匹配,去除包含模糊字符的读数.根据重叠序列仅组装长度大于10bp的序列,无法组装的读数被丢弃.使用UPARSE(版本7.1)将操作单位(OTU)聚类为具有97%的相似性截断,并使用UCHIME鉴定和去除嵌合序列.通过使用70%的置信阈值的RDP分类器[20],对silva(SSU123)16S rRNA数据库分析每个16S rRNA基因序列的系统发生亲缘关系.1.4.2生物信息学分析基于Mothur v.1.21.的分析[21],计算Shannon和Chao多样性指数[22].使用UniFrac进行β多样性分析[23],比较使用群落生态包R-forge的主成分分析(PCA)的结果,使用SPSS(ver.22.0)软件通过平均连结的聚类技术对从RDP分类器获得的门进行聚类,利用基于Spearman的方法计算相关性系数,用OriginPro (ver.9.0)进行绘图.2结果与分析2.1 复垦地与对照地土壤细菌群落结构的对比分析2.1.1细菌群落多样性分析由表1可知,复垦11期 侯湖平等：煤矸石充填不同复垦年限土壤细菌群落结构及其酶活性 4233土壤中细菌群落在各个分类水平的细菌种类数量都少于对照地,但是在不同复垦年限中,细菌种类数量的变化规律性不强.细菌群落多样性和物种丰富度降低,Shannon 、Chao 指数(图1)在0~20cm 土层中复垦地比对照地降低33.39%~ 66.94%和34.75%~85.32%,在20~40cm 土层中复垦地比对照地降低13.41%~65.62%和12.43%~ 84.80%.可见,经过煤炭资源开采、土地塌陷、煤矸石充填复垦工程等严重扰动后,土壤细菌群落在1年内立即产生响应,煤矸石充填复垦后的土壤细菌群落的数量减少,直到复垦15年后细菌群落多样性仍未完全恢复,并且在0~20cm 深度比在20~40cm 深度的变化更剧烈.随着复垦年限增加,20~40cm 土层的群落多样性指数增加,因为随着时间的推移,微生物生存环境不断改善,细菌群落多样性呈现变好的趋势.表1 样本中的细菌种类数Table 1 Number of bacterial categories in different soil samplesS -1 SC -1 S -2 SC -2 M -1 MC -1M -2 MC -2L -1 LC -1 L -2 LC -2参数0~20cm 20~40cm 0~20cm 20~40cm 0~20cm 20~40cm门 27 33 27 30 26 32 22 31 28 31 29 29 纲 60 68 56 65 58 65 45 70 38 69 63 66 目 123 139 117 134 116 138 86 140 72 139 127 135 科 213 244 204 232 203 244 138 243 117 239 223 233 属 469 589 416 551 442 618 216 603 178 548 488 518 种 688 919 575 838 628 943 276 925 234 813 715 751S SC MMCLLC500 1000 1500 2000 2500 30003500 4000 样地C h a oS SC MMC L LC 012345678样地S h a n n o n图1 97%相似度水平下不同土层的细菌群落Chao 、Shannon 指数Fig.1 Shannon and Chao index of bacterial community in different soil layer under 97% similarity level0~20cm 土层20~40cm 土层采用行聚类分析法对12个样本的土壤细菌群落在门水平的序列数进行聚类,结果如图2所示.当聚类分为2类时,分别为复垦地样本S 、M 、L 聚为一类,SC 、MC 、LC 样本聚为一类,说明了复垦土壤细菌群落结构和对照土壤细菌结构之间的差异明显.2.1.2 土壤优势菌分析 在复垦土壤中,各样本中占主要数量比例的细菌序列数统计见表2.从物种组成来看,复垦地与对照地比较,复垦细菌群落构成相对简单,呈现物种数量少,丰富度低.本结论和Poncelet 等[2]、马守臣等[3]、李媛媛等[24]、钱奎梅等[25]的结果类似.可见,矿区经过煤矸石充填复垦工程扰动后,土壤生态环境受到严重影响,土壤微生物多样性有降低的趋势.但是,随着复垦年限的增加,植物生长导致土壤有机质含量上升,为微生物的生长和繁殖提供有利条件,复垦4234 中 国 环 境 科 学 37卷土壤的多样性指数、丰富度指数会有提高的趋势,这一结论与樊文华等[13]、钱奎梅等[25]对不同复垦年限对土壤微生物多样性的影响研究一致.随着复垦年限的增加,复垦土壤中的细菌优势菌种不变,都是以厚壁菌门和变形菌门为主,但是数量比例略有变化.0 510152025MC-1 MC-2 SC-1 LC-1 SC-2 M-2 L-1 L-2 LC-2 S-2 S-1M-1 7 8 3 11 4 6 9 10 12 2 15图2 不同样本细菌群落聚类Fig.2 Cluster diagram of bacterial community in different soil samples表2 土壤中主要细菌的序列数Table 2 Number of sequence of the main bacteria in soil samples参数 S -1 S -2 SC -1SC -2M -1M -2MC -1MC -2L -1 L -2 LC -1 LC -2 厚壁菌门 251293286494969617 20961260918189152013448724295 4830 23348 变形菌门 6571249911384116417203361311428784821567111 14903 9258放线菌门 123835 28993085 678 335 3246276419 1770 4692 3190 门绿弯菌门 168074 20672481 584 404 2855211913 474 1585 1350 芽孢杆菌纲239673137882358438 19883247467224141403288122838 3806 21916 γ-变形菌纲 2836222032602668 282518863721263719331957 2930 2497β-变形菌纲 136760 26122382 1255540 1742114953 1941 4771 2004 δ-变形菌纲 143067 36524540 967 473 3486232126 2481 4752 3565 纲放线菌纲 129847 10211228 395711851562113311 265 947 775 乳杆菌目125751626142303441 1041012949340072841734411929 1872 11449 芽孢杆菌目 113931511740054997 947411798382468561553710909 1934 10467 肠杆菌目14131841538 351 962 1081341 678 1680950 196 1018 目除硫单胞菌目 412 23 16341985 348 189 169611388 921 1947 1403芽孢杆菌科 101321320733564107 82491012831745941135479525 1592 9128 链球菌科6160759020941533 492660521654351781785955 864 5590 肠球菌科 5894787019511739 499162731534339183195412 912 5301 类芽孢杆菌科 12301887576 529 11771622440 800 19701363 310 1303 科肠杆菌科14131841538 351 962 1081341 678 1680950 196 1018 芽孢杆菌属 100581311933063866 81841005829975798134509462 1574 9071 肠球菌属 5894787019511739 499162731534339183195412 912 5301 属乳球菌属5830712819731426 466356921554331777115641 816 5255 芽孢杆菌属-JH7 92231204729082489 7490923025185192123718726 1430 8342 屎肠球菌5894787019511739 499162731534339183195412 912 5301 种乳球菌属- piscium 5520671918551348 439453711464311772785361 770 4965在门水平,复垦土壤和对照土壤中的优势菌均为厚壁菌门和变形菌门,二者在复垦土壤中共11期侯湖平等：煤矸石充填不同复垦年限土壤细菌群落结构及其酶活性 4235占87.56%~93.96%,在对照土壤中共占64.22%~ 69.37%.在纲的水平上,芽孢杆菌纲占绝对优势,在复垦土壤中相对丰度为64.55%~76.24%,然而在对照地土壤中为25.01%~35.25%.在目水平上,乳杆菌目、芽孢杆菌目共占64.55%~75.84%.在科水平上,复垦土壤中的芽孢杆菌科、肠球菌科、链球菌科共占58.75%~69.70%.在属水平上,复垦土壤的芽孢杆菌属、肠球菌属、乳球菌属共占57.65%~68.37%.在种水平上,芽孢杆菌属-JH7、屎肠球菌、乳球菌属-piscium是优势菌种,在数量上共占54.79%~65.12%.复垦土壤中几乎所有细菌门的数量比对照地少,但是厚壁菌门在复垦土壤中的数量比例大于对照地土壤,在复垦土壤0~20cm和20~40cm 土层中的数量分别比对照地土壤多155.96%~ 614.01%和 4.06%~241.73%.厚壁菌门有从20~ 40cm土层向0~20cm土层转移的趋势.芽孢杆菌纲属于厚壁菌门,在复垦地中的数量大于对照地,在0~20cm土层中的数量比对照地多191.04%~ 764.03%,差别更明显,其在复垦土壤的20~40cm 土层的数量随年限增加而减少.乳杆菌目、芽孢杆菌目、芽孢杆菌科、肠球菌科、链球菌科、类芽孢杆菌科属于芽孢杆菌纲,在复垦地中的数量大于对照地,在0~20cm土层中的差别更明显,复垦土壤中的数量分别比对照地多197.27%~ 826.72%、147.74%~703.36%、159.92%~751.21%、202.10%~812.17%、194.24%~846.47%、113.73%~536.51%.属和种水平,厚壁菌门下的芽孢杆菌属、肠球菌属、乳球菌属、芽孢杆菌属-JH7、屎肠球菌、乳球菌属-piscium均有同样的分布特征,在复垦地的数量大于对照地,在0~ 20cm土层中的差别更明显,复垦土壤中的数量分别比对照地多173.06%~754.78%、202.10%~ 812.17%、194.24%~846.47%、197.46%~765.10%、202.10%~812.17%、197.63%~45.74%.上述细菌目、科、属、种在复垦土壤的20~40cm土层的数量均随年限增加而减少.变形菌门下的γ-变形菌纲、δ-变形菌纲、β-变形菌纲在复垦土壤中数量均小于对照地,分别少13.02%~34.04%、3.42%~98.54%、3.14%~ 97.52%.γ-变形菌纲下的肠杆菌目、肠杆菌科在复垦地中的数量大于对照地,在0~20cm土层中的差别更明显,复垦土壤中的数量分别比对照地多162.79%~756.89%和162.79%~181.96%.δ-变形菌纲下的除硫单胞菌目在复垦地中的数量比对照地少34.39%~98.84%,在研究区复垦土壤中的含量低于正常水平.放线菌门作为高G+C革兰氏阳性菌,能促使土壤中的动物和植物遗骸腐烂.而在研究区的复垦地土壤中,20~40cm土层的数量比对照地少19.18%~97.04%.2.2 不同复垦年限土壤细菌群落结构的对比通过分析不同样本OTU(97%相似性)组成,对3组样地的土壤细菌群落数据进行主成分分析(PCA),不同环境间的样本表现出分散或聚集的分布情况(图3).PC1轴的可信度为97.12%, PC2轴的可信度为 1.01%,累计贡献率达98.13%.在PC1轴上,复垦地土壤样本与对照地土壤样本从PC1的0值位置显著分离,表明煤矸石充填复垦后土壤细菌群落结构发生较大变化,此结果与不同样品间的聚类分析结果一致.同时,不同复垦年限对土壤微生物的影响差异在PC1轴和PC2轴上均有较好的体现,复垦地样本L和LC距离最远,M和MC样本次之,S和SC样本距离最近,表明随着时间的推移,复垦土壤的微生物群落结构组成会逐渐发生变化,与对照地土壤中的微生物群落结构将偏离正常土壤的水平.-9000-6000-30003000 6000 9000 -100010001500PC1:97.12%PC2:1.1%图3 土壤样本主成分分析Fig.3 PCA of soil samples4236 中国环境科学 37卷2.3细菌群落优势菌和脱氢酶的相关性分析土壤酶在土壤生态系统的物质循环和能量转化过程中有重要作用[26].土壤酶活性能表征土壤的综合肥力特征及土壤养分转化进程[27-29].已有研究表明,土壤酶和土壤微生物之间存在相互促进和制约的复杂关系[30].由于作物和微生物的分泌物及对其残体的分解物是土壤酶的主要来源,增加土壤中微生物的含量,有利于提高土壤的酶活性,土壤酶与土壤细菌的相互作用能够推动土壤有机质的矿化分解和养分循环转化.因此,土壤酶活性能够敏感地反映土壤微生物的活性状况,在复垦土壤中起到重要的生态指示作用.本研究中测得土壤中脱氢酶活性(图4),在复垦土壤和对照土壤中,脱氢酶活性均表现出0~20cm土层的含量大于20~40cm土层,在复垦土壤中多出1.62%~9.43%,在对照土壤中多出4.35%~17.49%,土壤脱氢酶含量在不同土层的分布上总体呈现出随土壤深度的增加而递减的规律.用复垦样本数据除以对照样本,得到的百分数可以表示复垦地土壤相比对照土壤的贴近度.经过计算,0~ 20cm土层的S、M、L样本的贴近度分别为83.76%、86.05%、89.57%,呈现L>M>S的规律.此数据表明,采煤塌陷与复垦工程改变了土壤脱氢酶活性及其分布,随着复垦年限增加,土壤脱氢酶活性正逐步恢复到正常土壤.20~40cm土层的S、M、L样本的贴近度分别为89.93%、88.31%、91.98%,说明复垦年限的变化对20~40cm的土层酶活性没有明显的影响.S SC M MC L LC0.340.360.380.400.420.440.460.48样地脱氢酶活性[mg/(L⋅h)]图4 土壤样品中脱氢酶含量Fig.4 Dehydrogenase content in soil samples土壤脱氢酶的活性能表征土壤微生物的氧化能力,可以作为微生物氧化还原系统的指标[31].细菌群落优势菌和脱氢酶的相关性见表3,土壤中脱氢酶活性与厚壁菌门、芽孢杆菌纲、乳杆菌目、芽孢杆菌目,芽孢杆菌科、链球菌科、肠球菌科、芽孢杆菌属、肠球菌属、乳球菌属、芽孢杆菌属-JH7、屎肠球菌和乳球菌属-piscium成显著负相关,与放线菌门成显著正相关,和γ-变形菌纲成极显著正相关,说明土壤中脱氢酶活性与土壤中细菌数量有密切的关系,脱氢酶活性可作为判断细菌群落结构是否发生变化的指标之一.其原因在于部分土壤微生物体内的脱氢酶通过催化生物氧化还原反应,而后经过氧化磷酸化作用生成腺苷三磷酸(ATP),以作为异养生物能量的主要来源,该类土壤细菌得以生存.表3细菌群落优势菌和脱氢酶的相关性系数Table 3Correlations between dominant bacterial species and dehydrogenase优势菌相关系数优势菌相关系数优势菌相关系数厚壁菌门-0.742* 乳杆菌目-0.728* 芽孢杆菌属-0.753* 变形菌门 0.673 芽孢杆菌目-0.757* 肠球菌属-0.732* 绿弯菌门 0.58 梭菌目-0.665 乳球菌属-0.719* 放线菌门 0.745* 除硫单胞菌目 0.639 芽孢杆菌属-JH7 -0.739* 芽孢杆菌纲-0.743* 肠杆菌目-0.642 屎肠球菌-0.732* δ-变形菌纲 0.604 芽孢杆菌科-0.755* 乳球菌属-piscium -0.72* γ-变形菌纲 0.889** 链球菌科-0.719*β-变形菌纲 0.056 肠球菌科-0.732*注:*、**分别代表差异达到极显著(P<0.01)、显著(P<0.05)水平.11期侯湖平等：煤矸石充填不同复垦年限土壤细菌群落结构及其酶活性 42373讨论根据Shannon指数和Chao指数,将复垦样本数据除以对照样本计算贴近度,表征复垦地土壤相比正常农田土壤的生物多样性的贴近程度.在0~20cm土层,S、M、L样本的Shannon指数贴近度分别为66.61%、65.04%、33.06%,Chao指数的贴近度分别为54.88%、65.25%、14.69%,说明在0~20cm深度的土层,随着复垦年限增加,煤矸石充填复垦土壤的细菌群落多样性和物种丰富度会偏离正常农田的水平.在20~40cm土层,S、M、L样本的Shannon指数贴近度分别为60.74%、34.38%、86.59%,Chao指数的贴近度分别为44.87%、15.20%、87.57%,数值虽有波动,但是值得注意的是,复垦15年的20~40cm深度的样本中,细菌群落多样性和物种丰富度已经与正常农田的水平十分接近.从不同分类水平上对土壤微生物优势菌进行分析,厚壁菌门、变形菌门、芽孢杆菌纲、乳杆菌目、芽孢杆菌目、芽孢杆菌科、肠球菌科、链球菌科、芽孢杆菌属、肠球菌属、乳球菌属、芽孢杆菌属-JH7、屎肠球菌、乳球菌属-piscium 是研究区煤矸石充填复垦土壤中的优势菌(表2).这与陈来红等[16]对露天煤矿区复垦多样性的研究结果类似.而李媛媛等[24].对采煤塌陷区泥浆泵复垦的研究发现,土壤细菌主要由变形菌、放线菌、浮霉菌、酸杆菌、绿弯菌、拟杆菌、芽单胞菌、厚壁菌和硝化螺旋菌组成,且复垦的效果优于本研究区,这可能由于复垦方式和农田耕作方式的不同引起的差异,说明复垦方式对土壤细菌群落结构的影响显著,也说明土壤微生物对生态环境变化十分敏感.计算优势菌的贴近度,结果见表4:厚壁菌门以及厚壁菌门下属的芽孢杆菌纲、乳杆菌目、芽孢杆菌目、芽孢杆菌科、链球菌科、肠球菌科、芽孢杆菌属、肠球菌属、乳球菌属、芽孢杆菌属-JH7、屎肠球菌、乳球菌属- piscium等的贴近度基本呈现样本S<M<L的规律,因此进一步验证厚壁菌门的多数细菌可以适应煤矸石充填复垦土壤的特点,并能在此环境中长期生存下来.变形菌门以及其下属的γ-变形菌纲、δ-变形菌纲、β-变形菌纲的贴近度表现出样本S>M>L的规律,说明在煤矸石充填复垦土壤的演替过程中,变形菌门在减少.而在20~40cm土层中,优势菌的相对丰富度随着复垦年限的增加有波动规律,因此0~20cm土层中的细菌群落结构比20~40cm土层中的细菌群落更容易受人为扰动或时间推演而发生变化.不同复垦年限土壤细菌的演替是有差异的,在不同复垦年限,土壤生态系统优势菌群的比例在不断发生变化.在0~20cm土层的复垦土壤中,厚壁菌门的相对丰度随着复垦年限增加而增加,在复垦15年的样本中厚壁菌门占绝对优势,相对丰度高达93.83%.厚壁菌门中主要的细菌目、细菌科、细菌属在复垦土壤中的数量比例会大于正常农田土壤,说明厚壁菌门有特殊的生理结构,多数菌种能通过形成孢子适应矿区缺水和极端环境,因此对于采煤塌陷地的生态修复、土壤生态系统的重建有重要意义.芽孢杆菌属具有耐高热、低温、辐射等抵抗极端环境的能力,并去除土壤中的重金属污染,是一种环境友好型生物农药[32].类芽孢杆菌的菌株具有抗性强、固氮、抑菌等优良特性,可以作为促生菌剂促进植物生长[33].芽孢杆菌属-JH7具有耐碱耐热性[34],屎肠球菌长速快,有较好的黏附能力,能产生乳酸及一些抗菌物质[35],可用作益生菌制剂.因此上述几种菌能与经过复垦工程后发生改变的生态系统相适应,能改良土壤环境,改善养分相对贫瘠的复垦土壤,表现出复垦后土壤质量提升的目的.贺龙等[14]也有同样的研究结果,其研究认为,露天煤矿复垦土壤的优势菌群多为化能自养或化能异养型细菌或参与氮循环、或降解多环芳烃类有机物等有利于污染土壤的生态修复和土壤肥力恢复的功能细菌属,能在营养贫瘠的环境下生长繁殖,这对于复垦土壤肥力恢复具有重要作用,尤其是对露天煤矿的土壤修复、生态系统改善具有重要的利用价值.变形菌门以及变形菌门下的δ-变形菌纲、β-变形菌纲、γ-变形菌纲、除硫单胞菌目的数量变化和厚壁菌门相反,在0~20cm土层中随着年限增加而减少,在20~。

山东林业科技 2021 年第 1 期 总 252 期 SHANDONG FORESTRY SCIENCE AND TECHNOLOGY 2021.No.l文章编号：1002-2724(2021)01-0027-04黄河三角洲盐地碱蓬-芦苇群落土壤粒径组成与细菌多样性梁楠，刘嘉元，丰'，田 静，李德生!(天津理工大学环境科学与安全工程学院，天津300384)摘要：土壤细菌在维持生态平衡中具有重要作用0本文以黄河三角洲湿地保护区盐地碱蓬、芦苇混生群落不同植物根际和非根际土壤为研究对象，分析微生物种类及其多样性的变化、土壤粒径组成及两者之间的关系，结果表明：(1)不同植物根际和 非根际的土壤以粉粒(Silt &和砂粒(Sand )为主，占90%以上；(2) 土壤细菌门水平15门类中变 菌 (Proteobacteria &是主要优势菌群，在不同植物根际和非根际土壤中占40%以上；(3)芦苇的土壤细菌根际 ， 其非根际土壤细菌的Chad 指数、ACE 指数和Shannon 指数均显著小于盐地碱蓬；(4)土壤微生物多样性Shannon 指数与粉粒(Silt &之间呈显著正相关，粉粒占 越高土壤细菌群落越丰富，均°关键词：黄河三角洲;混生群落；土壤细菌；土壤粒径中图分类号：X172文献标识码：4Soil Particle Size Distribution and Bacterial Diversity of Suaeda Salsa-Phragmites Australis Community ofthe Yellow River DeltaLIANG Nan ,LIU Jiayuan ,FENG Yue ,TIAN Jing ,LI Desheng **： 2020-12-18作者简介：梁楠(1994-)，硕士研究生，从事湿地生态学研究,E-mail :liangnan0516@ *通讯作者：李德生(1964-),男，博士，教授，从事环境生态学研究,E-mail :***************.cn(School of Environmental Science and Safety Engineering ,Tianjin University of Technology ,Tianjin 300384)Abstract ： Soil bacteria play an important role in maintaining ecological balance. In this paper, we analyze the changes in bacterial diversity, the composition of soil particle size and the relationship between them in rhizophere and non rhizophere soils in a mixed community of Suaeda salsa and Phragmites australis of the Yellow River Delta. The result shows that: (1) Rhizophere and non rhizophere soils of different plants are dominated by silt and sand, which account for more than 90% of the soil. (2) Among the top 15 categories of soil bacteria phylum, Proteobacteria is the main dominant bacterial group, accounting for more than 40% of the rhizosphere and non-rhizosphere soils of different plants. (3) The rhizosphere effect of soil bacteria in Phragmites aus trails is more significant, but the Chaol index, ACE index and Shannon index of soil samples from different plant communities in the non - rhizosphere are significantly lower than those of Suaeda salsa. (4) There is a significant positive correlation between the Shannon index of soil bacterial diversity and silt. The higher the relative volume percentages of silt was, the richer the bacterial community and the higher the degree of uniformity.Keywords ： Yellow River delta ；mixed community ； soil bacteria ； soil particle size土壤微生物是土壤结构活跃成分之一，微生 物代谢活动分泌的有机酸、团粒等利于土壤颗粒 形成,改善土壤质量,从而使颗粒演变成能够生长植物的土壤叭土壤微生物结构特征是土壤质地状 态和生态系统稳定性主要的评价因子巴土壤微生 物多样性对环境的作用主要通过不同生物群落代谢功能的差异性实现叫作为分解者,微生物以重要的物质循环和能量动作用在生态系统中，在 维持生态系统的完整性和稳定性上具有 重要 的作用叫湿地生态系统超50%的土壤不同 程度盐渍化[5],植被类型单一,以盐地碱蓬、芦苇 等盐生植物为 物。

温室中生物肥料对抑制香蕉镰刀菌枯萎病的作用以及优化土壤微生物和化学特征的作用Effect of biofertilizer for suppressing Fusarium wilt disease of banana as well as enhancing microbial and chemical properties of soil under greenhouse trial 样本：土壤杂志：2015年4月《Applied Soil Ecology》IF：2.644合作单位：南京农业大学有机肥料国家工程研究中心研究背景生物肥料是治疗香蕉镰刀菌枯萎病的一种策略。

但是关于长期应用生物肥料对土壤健康的影响尚未有研究报导，因此本研究通过四季盆栽实验探究某种生物肥料对抑制香蕉枯萎病的长期作用以及对土壤化学特性以及微生物结构的影响；使用16S扩增子测序技术研究了生物肥料对土壤微生物群落的影响。

研究方法：取样点：万众农业公司(18°38’N, 108°47’E)样本处理•各样本均在10cm深处取100g•使用2mm筛子过滤去除大颗粒，-70℃保存理化性质•pH值、土壤总有机碳含量、总有机氮含量、碳氮比、NH4-N、NO3N、K、P浓度检测DNA提取•PowerSoil DNA Isolation Kit (MoBio Laboratories Inc., USA)提取DNA16S测序•16S V4区，引物515F／806R，诺禾致源MiSeq上机测序•OTU聚类和分析，α和β多样性分析ITS测序•ITS1，引物ITS1F/ITS2，诺禾致源MiSeq上机测序•OTU聚类和分析，α和β多样性分析研究成果1.16S测序以及ITS测序表明，高浓度生物肥料（HBIO）处理条件的土壤细菌和真菌群落显著区分与低浓度处理组（LBIO）以及化学（CF）肥料对照组；2.与化学肥料对照组相比高浓度生物肥料处理组中Firmicutes和Bacillus丰度显著升高，而Acidobacteria, Bacteroidetes和Ascomycota丰度显著降低。

Soil Microbial Diversity Soil microbial diversity is a critical aspect of the environment that often goes unnoticed. The intricate web of microscopic organisms that live within thesoil plays a crucial role in maintaining the health and fertility of the soil. These organisms, including bacteria, fungi, protozoa, and other microorganisms,are responsible for various essential functions such as nutrient cycling, decomposition of organic matter, and disease suppression. The diversity of these soil microbes is a key indicator of soil health and can greatly impact the overall productivity of the ecosystem. One of the primary reasons why soil microbial diversity is so important is its role in nutrient cycling. Microbes in the soilare responsible for breaking down organic matter and releasing nutrients such as nitrogen, phosphorus, and potassium, which are essential for plant growth. Without a diverse microbial community, the nutrient cycling process would be significantly impaired, leading to nutrient deficiencies in the soil and ultimately affectingthe health of plants and the entire ecosystem. Therefore, maintaining a diverse microbial community is crucial for the sustainability of agricultural systems and natural ecosystems alike. In addition to nutrient cycling, soil microbialdiversity also plays a significant role in disease suppression. Certain microorganisms in the soil have the ability to suppress the growth of plant pathogens, thereby reducing the incidence of diseases in crops. This natural form of disease control is an important aspect of sustainable agriculture, as it reduces the reliance on synthetic pesticides and promotes a healthier and more balanced ecosystem. However, a loss of microbial diversity in the soil can weaken this natural defense mechanism, making plants more susceptible to diseases and requiring increased use of chemical interventions. Furthermore, soil microbial diversity is closely linked to soil structure and stability. Microbial activity, particularly that of fungi and bacteria, helps to bind soil particles together, creating stable soil aggregates. These aggregates improve soil structure, porosity, and water infiltration, which in turn enhances the soil's ability to hold waterand resist erosion. A decline in microbial diversity can lead to a breakdown ofsoil structure, resulting in increased soil erosion, reduced water holding capacity, and overall degradation of soil quality. The impact of human activitieson soil microbial diversity cannot be overlooked. Practices such as intensive agriculture, excessive use of chemical fertilizers and pesticides, and land degradation can significantly reduce the diversity and abundance of soil microbes. Deforestation, urbanization, and industrialization also contribute to the loss of microbial diversity in the soil. These human-induced changes to the soil microbial community have far-reaching consequences, not only for the health of the soil and the environment but also for global food security and human well-being. In conclusion, soil microbial diversity is a fundamental component of healthy and productive ecosystems. The intricate relationships between soil microorganisms and the environment are vital for nutrient cycling, disease suppression, soil structure, and overall ecosystem sustainability. It is imperative that we recognize the importance of preserving and promoting soil microbial diversity through sustainable land management practices, conservation efforts, and a deeper understanding of the complex interactions within the soil ecosystem. By doing so, we can ensure the long-term health and productivity of our soils and the ecosystems they support.。