Modelling interactions between hydrodynamics and dispersal that help shape biofilm community composition across a range of scales
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| Description: |
Sloan, W (University of Glasgow)
Tuesday 12 August 2014, 14:00-15:00 |
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| Created: | 2014-08-15 14:58 |
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| Collection: | Understanding Microbial Communities; Function, Structure and Dynamics |
| Publisher: | Isaac Newton Institute |
| Copyright: | Sloan, W |
| Language: | eng (English) |
| Distribution: |
World
(downloadable)
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| Explicit content: | No |
| Aspect Ratio: | 16:9 |
| Screencast: | No |
| Bumper: | UCS Default |
| Trailer: | UCS Default |
| Abstract: | (Joint with A. J. Pinto and E. Vignaga)
In any open biological community there are a few basic biological processes that shape the community composition: births, deaths, immigration and emigration. Of course there are myriad factors that influence the rate at which each of these occur in different species within a community. For bacterial biofilms, our understanding and growing ability to quantify these factors has been furnished by laboratory experimentation often at very-small scale in comparison to the system that is ultimately of interest. Here we present circumstantial evidence that in drinking water distribution networks, where biofilm control is of paramount importance, and in river networks, where biofilms mediate biogeochemical cycling, limitations in the hydrodynamic dispersal of bacterial between locations has a strong influence on the community composition. Thus, where biofilms reside in a hydraulically connected network, immigration and emigration at the local scale can have a strong effect on the biodiversity patterns across the network. In most biofilm models, conceived on the basis of laboratory biofilms, these mechanisms assume less importance than the environmental and biological factors affecting births and deaths and are often modelled as flow-dependent biomass loss/gain terms. We present evidence and models for more complex dynamic interactions between dispersal and flow regimes. Developing a better understanding of bacterial dispersal mechanisms in networks should allow for a more robust quantification of risk in, for example, pathogen occurrence in drinking water or disturbance of river ecosystems, which should inform network management strategies. |
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