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Microbial Ecology

, Volume 75, Issue 2, pp 434–446 | Cite as

The Aboveground Vegetation Type and Underground Soil Property Mediate the Divergence of Soil Microbiomes and the Biological Interactions

  • Shu-Hong Wu
  • Bing-Hong Huang
  • Chia-Lung Huang
  • Gang Li
  • Pei-Chun Liao
Soil Microbiology

Abstract

The composition of the soil microbiome is influenced by environmental (abiotic) variables and biological interactions (biotic factors). To determine whether the aboveground vegetation and soil physicochemical properties were the main determinant of beta-diversity and biological interaction of soil microbial community, we sampled soils from the temperate coniferous forest and grassland. Clustering of operational taxonomic units was conducted using 16S rRNA gene. We found that the microbial composition of the rhizospheres, in which root exudates influence the microbial environment, show lower alpha-diversity than that of nonroot soils. The nonsignificant rhizosphere effect suggested other undetermined factors or stochastic processes accounted for microbial diversity in the rhizosphere. More significant microbe-microbe interactions were observed in forest and rhizosphere soils relative to the grassland soils. The elevated number of positive correlations for relative abundances in forest soil implied beneficial associations being common among bacteria, in particular within the rhizosphere environment. The particular soil properties generated by root exudates also alter the physicochemical properties of soil such as K and pH value, and might in turn favor the adoption of teamwork-cooperation strategies for microbe-microbe interactions, represented as large clusters of positive associations among bacterial taxa. Specific biological interactions differentiated the microbiomes within forest soils. Thus, the environmental selection pressure of aboveground vegetation accounts for differences between soil microbiomes while biotic factors are responsible for fine-scale differences of the microbial community in forest soils.

Keywords

Biological interactions Environmental factors Forest Grassland Rhizosphere Soil microbiome 

Notes

Acknowledgements

This research was financially supported by the Fundamental Research Funds for the Central Universities to SHW and supported by the Ministry of Science and Technology, Taiwan (MOST 105-2628-B-003-001-MY3 and MOST 105-2628-B-003-002-MY3) to PCL. This article was also subsidized by the National Taiwan Normal University (NTNU).

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no conflict of interest.

Supplementary material

248_2017_1050_MOESM1_ESM.docx (65 kb)
ESM 1 (DOCX 64 kb)
248_2017_1050_MOESM2_ESM.xlsx (1.9 mb)
ESM 2 (XLSX 1922 kb)
248_2017_1050_Fig5_ESM.gif (519 kb)
Figure S1

Sampling map with satellite images generated using ggmap packages implemented in R [62]. The grassland soil is presented in red point, the rhizosphere soil is presented in blue point, and the forest soil is presented in green point. (GIF 518 kb)

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High resolution image (TIFF 1870 kb)
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Figure S2

Loading plots for DAPC of the relative abundance of microbiomes in sampled soils of the three sampling groups (grassland, under forest and rhizosphere) at the phylum level, for Archaea OTUs and for Bacteria OTUs. Gray lines indicate the threshold 0.1 to identify the main contributors. OTU435804 belongs to Euryarchaeota; OTU191208 belongs to Acidobacteria_Gp4. (GIF 274 kb)

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High resolution image (TIFF 2277 kb)
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Figure S3

Correlation matrices for microbial phyla of total samples and samples of each sample group. The upper four panels are presented in alphabetical order for comparing the correlation patterns of each microbial phylum; the lower four panels are presented in order of hierarchical clustering so as to reveal clustering patterns (number of clusters and cluster size). The codes for microbial phyla are: P1, Acetothermia; P2, Acidobacteria; P3, Actinobacteria; P4, Aminicenantes; P5, Aquificae; P6, Armatimonadetes; P7, Atribacteria; P8, Bacteroidetes; P9, BRC1; P10, Caldiserica; P11, candidate division WPS-1; P12, candidate division WPS-2; P13, candidate division ZB3; P14, Candidatus Saccharibacteria; P15, Chlamydiae; P16, Chlorobi; P17, Chloroflexi; P18, Cloacimonetes; P19, Crenarchaeota; P20, Cyanobacteria/Chloroplast; P21, Deferribacteres; P22, Deinococcus-Thermus; P23, Elusimicrobia; P24, Euryarchaeota; P25, Fibrobacteres; P26, Firmicutes; P27, Fusobacteria; P28, Gemmatimonadetes; P29, Hydrogenedentes; P30, Ignavibacteriae; P31, Latescibacteria; P32, Lentisphaerae; P33, Microgenomates; P34, Nitrospirae; P35, Omnitrophica; P36, Parcubacteria; P37, Planctomycetes; P38, Proteobacteria; P39, Spirochaetes; P40, SR1; P41, Synergistetes; P42, Tenericutes; P43, Thaumarchaeota; P44, Thermodesulfobacteria; P45, Thermotogae; P46, unclassified; P47, Verrucomicrobia. (GIF 1381 kb)

248_2017_1050_MOESM5_ESM.tif (16.2 mb)
High resolution image (TIFF 16580 kb)

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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.School of Nature ConservationBeijing Forestry UniversityBeijingChina
  2. 2.Department of Life ScienceNational Taiwan Normal UniversityTaipeiTaiwan

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