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

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

Research output: Contribution to journalArticle

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.

Original languageEnglish (US)
Pages (from-to)265-272
Number of pages8
JournalMicrobial Ecology
Volume67
Issue number2
DOIs
StatePublished - Feb 25 2014

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Ecology
  • Soil Science

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