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Please use this identifier to cite or link to this item: http://hdl.handle.net/10373/110

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Title: Modelling interactions in fungi
Authors: Falconer, Ruth E.
Bown, James L.
White, Nia A.
Crawford, John W.
Affiliation: University of Abertay Dundee. Scottish Informatics, Mathematics, Biology and Statistics Centre
Keywords: Fungal colony
Fungal interaction
Individual-based modelling
Issue Date: Jun-2008
Publisher: The Royal Society
Type: Journal Article
Refereed: peer-reviewed
Rights: Published version (c)The Royal Society, available from http://rsif.royalsocietypublishing.org/content/5/23/603
Citation: Falconer, R. E., et al. 2008. Modelling interactions in fungi. Journal of the Royal Society Interface. 5(23): pp.603-615. [Online] Available from: DOI: 10.1098/rsif.2007.1210
Abstract: Indeterminate organisms have received comparatively little attention in theoretical ecology and still there is much to be understood about the origins and consequences of community structure. The fungi comprise an entire kingdom of life and epitomize the indeterminate growth form. While interactions play a significant role in shaping the community structure of indeterminate organisms, to date most of our knowledge relating to fungi comes from observing interaction outcomes between two species in two-dimensional arena experiments. Interactions in the natural environment are more complex and further insight will benefit from a closer integration of theory and experiment. This requires a modelling framework capable of linking genotype and environment to community structure and function. Towards this, we present a theoretical model that replicates observed interaction outcomes between fungal colonies. The hypotheses underlying the model propose that interaction outcome is an emergent consequence of simple and highly localized processes governing rates of uptake and remobilization of resources, the metabolic cost of production of antagonistic compounds and non-localized transport of internal resources. The model may be used to study systems of many interacting colonies and so provides a platform upon which the links between individual-scale behaviour and community-scale function in complex environments can be built.
URI: http://hdl.handle.net/10373/110
ISSN: 1742-5662
Appears in Collections:SIMBIOS Collection
Science Engineering & Technology Collection

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