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Please use this identifier to cite or link to this item: http://hdl.handle.net/10373/97

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Title: Visualization, modelling and prediction in soil microbiology
Authors: O'Donnell, Anthony G.
Young, Iain M.
Rushton, Steven P.
Shirley, Mark D.
Crawford, John W.
Affiliation: University of Abertay Dundee. School of Contemporary Sciences
University of Abertay Dundee. SIMBIOS
Keywords: Soil microbiology
Microbial communities
Issue Date: Sep-2007
Publisher: Nature Publishing Group
Type: Article
Refereed: peer-reviewed
Rights: Published version available from Nature Publishing Group at http://www.nature.com/nrmicro/journal/v5/n9/abs/nrmicro1714.html
Citation: O'Donnell, A.G. et al. 2007. Visualization, modelling and prediction in soil microbiology. Nature Reviews Microbiology 5: 689-699. [online] Available from: http://dx.doi.org/10.1038/nrmicro1714 [Accessed 15 December 2008]
Abstract: The introduction of new approaches for characterizing microbial communities and imaging soil environments has benefited soil microbiology by providing new ways of detecting and locating microorganisms. Consequently, soil microbiology is poised to progress from simply cataloguing microbial complexity to becoming a systems science. A systems approach will enable the structures of microbial communities to be characterized and will inform how microbial communities affect soil function. Systems approaches require accurate analyses of the spatio–temporal properties of the different microenvironments present in soil. In this Review we advocate the need for the convergence of the experimental and theoretical approaches that are used to characterize and model the development of microbial communities in soils.
URI: http://hdl.handle.net/10373/97
Appears in Collections:Science Engineering & Technology Collection

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