Engineering difference: Matrix design determines community composition in wastewater treatment systems

Date

2012-03-01T00:00:00Z

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Elsevier Science B.V., Amsterdam.

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Article

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0925-8574

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Free to read from

Citation

J.A. Harris, J.D.C. Baptista, T.P. Curtis, A.K. Nelson, M. Pawlett, K. Ritz, S.F. Tyrrel, Engineering difference: Matrix design determines community composition in wastewater treatment systems, Ecological Engineering, Volume 40, March 2012, Pages 183–188.

Abstract

There is a growing view that the application of ecological theory has the potential to facilitate a transition from a descriptive to a predictive framework in wastewater engineering. In this study we tested the hypotheses that: (i) it is possible to engineer consistent differences between microbial communities in wastewater treatment modules; (ii) there is a positive relationship between structural complexity and genetic diversity; (iii) such interactions are modulated by the availability of energy. We developed four treatment modules of increasingly complex support material (matrix) design, and pumped a synthetic wastewater through them for 16 weeks. We then disassembled the modules and assessed the phylogenetic (general eubacteria and ammonium diversity of the communities present on the support materials. We found that different genotypic and phenotypic community structures were reliably generated by the engineering of their physical environment in terms of structural complexity (as determined by particle size distribution and therefore pore size distribution). Furthermore, there was a notably consistent response of the phenotypic structure to such circumstances, and also to the presence of organic matter. However, we found no significant relationships between genetic diversity and structural complexity either for eubacterial or ammonia-oxidiser microbial groups. This work demonstrates that is it possible to engineer modules of differing microbial community composition by varying their physical complexity. This is an essential first step in testing relationships between system diversity and treatment resilience at a process level.oxidisers, by DGGE profiling) and phenotypic (by PLFA profiling)

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NOTICE: this is the author’s version of a work that was accepted for publication in Ecological Engineering. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Ecological Engineering, VOL 40, (2012) DOI:10.1016/j.ecoleng.2011.12.016

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