2018
DOI: 10.3390/pr6010002
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Individual-Based Modelling of Invasion in Bioaugmented Sand Filter Communities

Abstract: Using experimental data obtained from in vitro bioaugmentation studies of a sand filter community of 13 bacterial species, we develop an individual-based model representing the in silico counterpart of this synthetic microbial community. We assess the inter-species interactions, first by identifying strain identity effects in the data then by synthesizing these effects into a competition structure for our model. Pairwise competition outcomes are determined based on interaction effects in terms of functionality… Show more

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Cited by 6 publications
(5 citation statements)
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“…A system-based approach that addresses key eco-evolutionary mechanisms (pathogen ability versus habitat properties versus disturbance-induced niche availability) and identifies their relative contributions, combined with appropriate modelling tools, can significantly advance the discipline. For example, the use of random forest and structural equation models can identify the relative contribution of different factors, whereas the use of spatial individual-based models that incorporate an adaptive process, diversification and emergent behaviour can significantly improve our ability to predict the rate and success of pathogen invasion under different climate and environmental settings [149][150][151] .…”
Section: Science-policy Interface and Social Innovationsmentioning
confidence: 99%
“…A system-based approach that addresses key eco-evolutionary mechanisms (pathogen ability versus habitat properties versus disturbance-induced niche availability) and identifies their relative contributions, combined with appropriate modelling tools, can significantly advance the discipline. For example, the use of random forest and structural equation models can identify the relative contribution of different factors, whereas the use of spatial individual-based models that incorporate an adaptive process, diversification and emergent behaviour can significantly improve our ability to predict the rate and success of pathogen invasion under different climate and environmental settings [149][150][151] .…”
Section: Science-policy Interface and Social Innovationsmentioning
confidence: 99%
“…Functionality was related to MSH1 cell density and to the individual fitness of the SFIs, and for selected combinations, the cell densities of the SFIs were examined to understand the interactions from the perspective of the SFIs. Some results of this work were used and reported previously for developing mathematical models of the invasion process, where the focus was on analysis and discussion of the predictive modeling methodologies and performances rather than an ecologically focused interpretation and discussion as in this paper. , …”
Section: Introductionmentioning
confidence: 99%
“…Some results of this work were used and reported previously for developing mathematical models of the invasion process, where the focus was on analysis and discussion of the predictive modeling methodologies and performances rather than an ecologically focused interpretation and discussion as in this paper. 40,41 ■ MATERIALS AND METHODS Bacterial Strains. A variant of Aminobacter sp.…”
Section: ■ Introductionmentioning
confidence: 99%
“…For example, a famous early study by Gause () demonstrated competitive exclusion, whereby two different Paramecium species competing for the same resources led to the domination and survival of only one. Synthetic co‐cultures are well known to also mutually benefit from the cross‐feeding of organic acids and nutrients (e.g., McCully et al ., ) and various individual‐based modelling approaches are developed to predict the individuals' competition for process control (Friedman et al, ; Daly et al, ). Additionally, predator–prey relationships contribute to microbial assembly dynamics, such as the bacterial predator Bdellovibrio spp ., which feeds on gram‐negative bacterial species (Johnke et al ., ), or host–parasite relationships in which genotype‐specific phages change community structures (Laanto et al ., ).…”
Section: Introductionmentioning
confidence: 99%