Spatial and temporal heterogeneity of the bacterial communities in stream epilithic biofilms

Authors: Lear, Gavin1; Anderson, Marti J.2; Smith, Joanna P.1; Boxen, Kristine1; Lewis, Gillian D.1

Source: FEMS Microbiology Ecology, Volume 65, Number 3, September 2008 , pp. 463-473(11)

Publisher: Blackwell Publishing

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Abstract:

The spatial and temporal variability in bacterial communities within freshwater systems is poorly understood. The bacterial composition of stream epilithic biofilms across a range of different spatial and temporal scales both within and between streams and across the profile of individual stream rocks was characterised using a community DNA-fingerprinting technique (Automated Ribosomal Intergenic Spacer Analysis, ARISA). The differences in bacterial community structure between two different streams were found to be greater than the spatial variability within each stream site, and were larger than the weekly temporal variation measured over a 10-week study period. Greater variations in bacterial community profiles were detected on different faces of individual stream rocks than between whole rocks sampled within a 9-m stream section. Stream temperature was found to be the most important determinant of bacterial community variability using distance-based redundancy analysis (dbRDA) of ARISA data, which may have broad implications for riparian zone management and ecological change as a consequence of global warming. The combination of ARISA with multivariate statistical methods and ordination, such as multidimensional scaling (MDS), permutationalmanovaand RDA, provided rapid and effective methods for quantifying and visualising variation in bacterial community structure, and to identify potential drivers of ecological change.

Keywords: stream biofilm; microbial communities; ARISA; multivariate analysis; multidimensional scaling

Document Type: Research article

DOI: 10.1111/j.1574-6941.2008.00548.x

Affiliations: 1: School of Biological Sciences, The University of Auckland, Auckland, New Zealand; and 2: Department of Statistics, Tamaki Campus, The University of Auckland, Auckland, New Zealand

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