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Microbial Community Sructure Characteristics And Its Adaptation Mechanisms To Soil Salinity In Tianjin

Posted on:2019-03-08Degree:MasterType:Thesis
Country:ChinaCandidate:W ZhengFull Text:PDF
GTID:2370330548983310Subject:Environmental Science
Abstract/Summary:PDF Full Text Request
Soil microbes are often used as important parameters for the change of soil quality.Salinity,the main factor affecting soil microbes,has been studied,and Sardinha described that the effect of salt on soil microbes is stronger than that of heavy metals.Currently,most studies focused on the effect of salinity on soil physical and chemical properties and microbial community structure,while the influence of salinity on soil microbial community interaction is relatively scarce.The soil salinization in Tianjin is very serious.It is an ideal study site to explore the characteristics of soil microbial community structure and its adaptation mechanism in different soil levels.This paper combine field sampling investigation and laboratory experiments,analyze the differences of diversity,composition and structure of soil microbial community under different salinity conditions by 16S rRNA gene sequencing technology,and investigate microbial interactions to salinity changes using molecular ecology network method(pMENs)in Tianjin farmland soils,to explore the adaptation mechanisms of microbial community to salt stress.The main results are as follows:(1)The soil salinity of the sampling points in the study area is increasing from north to south.The concentration of Cl-in soil also decreased from south to north.Tianjin is located in the coast of Bohai,there have been many times of marine transgression and regression in history,so the soil in southern area may be salty.Furthermore,the cluster analysis based on soil salinity showed that the salt content of two sampling sites in northern Jixian was similar,and the salt content of two sampling sites in central Wuqing was similar,and the salt content in Jinghai and Dagang in the South was similar.Therefore,the spatial distribution of soil salinity in Tianjin shows a trend of increasing from north to south,causing different soil salinity levels.(2)Soil salinity significantly affected the diversity of soil microbial community,and microbial diversity decreased with the increase of salinity.The relative abundances of Proteobacteria,Bacteroidetes and Firmicutes were higher,and those of Acidobacteria and Thaumarchaeota were lower under high salinity than in medium and low salinity soils.Furthermore,the results of similarity analysis(ANOSIM)showed that the composition of microbial communities were significantly different in H,M and L group(R=0.490>0,P=0.001;R=0.329>0,P=0.001).The results of the principal coordinate analysis(PCoA)based on the relative abundance of the sequence showed that the salinity changed the microbial community structure.The results of Mantel test showed that soil microbial community composition was significantly correlated with salinity.(3)The topology attribute analysis results showed that compared with M-and L-MENs,the H-MENs demonstrated less total nodes,less modules,but more links,higher average degree and average clustering coefficients.This indicated that salinity may enhance the interaction between microorganisms,and the network became denser with high salinity.Strong positive correlations were observed in all six pMENs,while negative correlations were rare.It showed that microorganisms may be more likely to cooperate with each other to adapt to the high salt environment or have similar niche.Further,we constructed the sub-networks of Flavobacterium and Acidobacteria_Gp4.The results showed that compared with M and L groups,Flavobacterium in H group had more complex interactions,while Acidobacteria_Gp4 had much less complex interactions in H group.It indicated that salinity shifted the interactions among different microbial taxa,and such changes vary among different microbial populations.
Keywords/Search Tags:Soil salinity, Microbial community structure, Molecular ecological network, Microbial interactions
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