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Ecology Letters
Article
License: publisher-specific, author manuscript
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Ecology Letters
Article . 2016 . Peer-reviewed
License: Wiley Online Library User Agreement
Data sources: Crossref
Ecology Letters
Article . 2017
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The interconnected rhizosphere: High network complexity dominates rhizosphere assemblages

Authors: Shengjing Shi; Erin E. Nuccio; Zhou J. Shi; Zhili He; Jizhong Zhou; Mary K. Firestone;

The interconnected rhizosphere: High network complexity dominates rhizosphere assemblages

Abstract

AbstractWhile interactions between roots and microorganisms have been intensively studied, we know little about interactions among root‐associated microbes. We used random matrix theory‐based network analysis of 16S rRNA genes to identify bacterial networks associated with wild oat (Avena fatua) over two seasons in greenhouse microcosms. Rhizosphere networks were substantially more complex than those in surrounding soils, indicating the rhizosphere has a greater potential for interactions and niche‐sharing. Network complexity increased as plants grew, even as diversity decreased, highlighting that community organisation is not captured by univariate diversity. Covariations were predominantly positive (> 80%), suggesting that extensive mutualistic interactions may occur among rhizosphere bacteria; we identified quorum‐based signalling as one potential strategy. Putative keystone taxa often had low relative abundances, suggesting low‐abundance taxa may significantly contribute to rhizosphere function. Network complexity, a previously undescribed property of the rhizosphere microbiome, appears to be a defining characteristic of this habitat.

Country
United States
Keywords

16S, Environmental management, Avena, random matrix theory, microbial ecology, microbial interactions, Microbiology, Models, Biological, Plant Roots, Ecological applications, Models, RNA, Ribosomal, 16S, Community ecology, Soil Microbiology, Ribosomal, Evolutionary Biology, Ecology, Bacteria, Bacterial, quorum sensing, Biodiversity, Biological Sciences, Biological, RNA, Bacterial, microbial networks, Ecological Applications, RNA, rhizosphere, keystone species

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
999
Top 0.01%
Top 1%
Top 0.1%
Green
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