Literature DB >> 24077652

Spatial variation in the bacterial and denitrifying bacterial community in a biofilter treating subsurface agricultural drainage.

J Malia Andrus1, Matthew D Porter, Luis F Rodríguez, Timothy Kuehlhorn, Richard A C Cooke, Yuanhui Zhang, Angela D Kent, Julie L Zilles.   

Abstract

Denitrifying biofilters can remove agricultural nitrates from subsurface drainage, reducing nitrate pollution that contributes to coastal hypoxic zones. The performance and reliability of natural and engineered systems dependent upon microbially mediated processes, such as the denitrifying biofilters, can be affected by the spatial structure of their microbial communities. Furthermore, our understanding of the relationship between microbial community composition and function is influenced by the spatial distribution of samples.In this study we characterized the spatial structure of bacterial communities in a denitrifying biofilter in central Illinois. Bacterial communities were assessed using automated ribosomal intergenic spacer analysis for bacteria and terminal restriction fragment length polymorphism of nosZ for denitrifying bacteria.Non-metric multidimensional scaling and analysis of similarity (ANOSIM) analyses indicated that bacteria showed statistically significant spatial structure by depth and transect,while denitrifying bacteria did not exhibit significant spatial structure. For determination of spatial patterns, we developed a package of automated functions for the R statistical environment that allows directional analysis of microbial community composition data using either ANOSIM or Mantel statistics.Applying this package to the biofilter data, the flow path correlation range for the bacterial community was 6.4 m at the shallower, periodically in undated depth and 10.7 m at the deeper, continually submerged depth. These spatial structures suggest a strong influence of hydrology on the microbial community composition in these denitrifying biofilters. Understanding such spatial structure can also guide optimal sample collection strategies for microbial community analyses.

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Year:  2014        PMID: 24077652     DOI: 10.1007/s00248-013-0286-0

Source DB:  PubMed          Journal:  Microb Ecol        ISSN: 0095-3628            Impact factor:   4.552


  28 in total

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2.  Soil resources influence spatial patterns of denitrifying communities at scales compatible with land management.

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Journal:  Appl Environ Microbiol       Date:  2010-01-29       Impact factor: 4.792

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Authors:  Jessica L Green; Andrew J Holmes; Mark Westoby; Ian Oliver; David Briscoe; Mark Dangerfield; Michael Gillings; Andrew J Beattie
Journal:  Nature       Date:  2004-12-09       Impact factor: 49.962

4.  The contribution of species richness and composition to bacterial services.

Authors:  Thomas Bell; Jonathan A Newman; Bernard W Silverman; Sarah L Turner; Andrew K Lilley
Journal:  Nature       Date:  2005-08-25       Impact factor: 49.962

5.  Multiscale responses of microbial life to spatial distance and environmental heterogeneity in a patchy ecosystem.

Authors:  Alban Ramette; James M Tiedje
Journal:  Proc Natl Acad Sci U S A       Date:  2007-02-12       Impact factor: 11.205

6.  Synchrony in aquatic microbial community dynamics.

Authors:  Angela D Kent; Anthony C Yannarell; James A Rusak; Eric W Triplett; Katherine D McMahon
Journal:  ISME J       Date:  2007-05       Impact factor: 10.302

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Authors:  C M Jones; J E Thies
Journal:  J Microbiol Methods       Date:  2007-01-18       Impact factor: 2.363

8.  The detection of disease clustering and a generalized regression approach.

Authors:  N Mantel
Journal:  Cancer Res       Date:  1967-02       Impact factor: 12.701

9.  Microbial community and physicochemical analysis of an industrial waste gas biofilter and design of 16S rRNA-targeting oligonucleotide probes.

Authors:  Udo Friedrich; Herman Van Langenhove; Karlheinz Altendorf; André Lipski
Journal:  Environ Microbiol       Date:  2003-03       Impact factor: 5.491

10.  In situ bioreactors and deep drain-pipe installation to reduce nitrate losses in artificially drained fields.

Authors:  Dan B Jaynes; Tom C Kaspar; Tom B Moorman; Tim B Parkin
Journal:  J Environ Qual       Date:  2008-02-11       Impact factor: 2.751

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  1 in total

1.  Seasonal Patterns in Microbial Community Composition in Denitrifying Bioreactors Treating Subsurface Agricultural Drainage.

Authors:  Matthew D Porter; J Malia Andrus; Nicholas A Bartolerio; Luis F Rodriguez; Yuanhui Zhang; Julie L Zilles; Angela D Kent
Journal:  Microb Ecol       Date:  2015-04-26       Impact factor: 4.552

  1 in total

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