NDLI: Spatial Variation in the Bacterial and Denitrifying Bacterial Community in a Biofilter Treating Subsurface Agricultural Drainage

Content Provider	Springer Nature Link
Author	Andrus, J. Malia Porter, Matthew D. Rodríguez, Luis F. Kuehlhorn, Timothy Cooke, Richard A. C. Zhang, Yuanhui Kent, Angela D. Zilles, Julie L.
Copyright Year	2013
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 inundated 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.
Starting Page	265
Ending Page	272
Page Count	8
File Format	PDF
ISSN	00953628
Journal	Microbial Ecology
Volume Number	67
Issue Number	2
e-ISSN	1432184X
Language	English
Publisher	Springer US
Publisher Date	2013-09-29
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Microbiology Ecology Microbial Ecology Geoecology/Natural Processes Nature Conservation Water Quality/Water Pollution
Content Type	Text
Resource Type	Article
Subject	Soil Science Ecology Ecology, Evolution, Behavior and Systematics

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