EconPapers    
Economics at your fingertips  
 

Spatial heterogeneity promotes antagonistic evolutionary scenarios in microbial community explained by ecological stratification: a simulation study

Alexandra I. Klimenko, Yury G. Matushkin, Nikolay A. Kolchanov and Sergey A. Lashin

Ecological Modelling, 2019, vol. 399, issue C, 66-76

Abstract: There are two evolutionary trends in genome organization among microbes: towards either amplification or reduction. Which evolutionary scenario overcomes depends on environmental conditions and the complexity of gene networks determining phenotypic traits such as metabolic features of cells. In this simulation study, we have shown that the habitats characterized by nutrient gradients allow spatial subdivision of evolutionary trends depending on the distance to the nutrient source. We have considered interrelations between cell motility, metabolic complexity of dominant populations and ecological features of developing communities and have shown that the distribution of local dominant ecogroups follows clear patterns in chemotaxis-on and -off cases. Chemotaxis was shown to be a factor impeding introduction of new forms and decreasing total biomass of the community. Our simulations have shown that ecological patterns of self-organization of microbial communities cause sustainable different strategies underlying antagonistic evolutionary scenarios.

Keywords: Microbial communities; Individual-based modelling; Ecological modelling; Evolutionary modelling; Spatial heterogeneity; Stratification (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304380019300687
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:399:y:2019:i:c:p:66-76

DOI: 10.1016/j.ecolmodel.2019.02.007

Access Statistics for this article

Ecological Modelling is currently edited by Brian D. Fath

More articles in Ecological Modelling from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:ecomod:v:399:y:2019:i:c:p:66-76