Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Quantifying Drift-Fitness Balance Using an Agent-Based Biofilm Model of Identical Heterotrophs Under Low Nutrient Conditions

View ORCID ProfileJoseph Earl Weaver
doi: https://doi.org/10.1101/2022.12.08.519628
Joseph Earl Weaver
1School of Civil Engineering &Geosciences, Newcastle University, Cassie Building, Newcastle upon Tyne, NE1 7RU, United Kingdom
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Joseph Earl Weaver
  • For correspondence: Joe.Weaver@newcastle.ac.uk
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Data/Code
  • Preview PDF
Loading

Abstract

Both deterministic and stochastic forces shape biofilm communities, but the balance between those forces is variable. Quantifying the balance is both desirable and challenging. For example, negative drift selection, a stochastic force, can be thought of as an organism experiencing ‘bad luck’ and manipulating ‘luck’ as a factor in real world systems is difficult. We used an agent-based model to manipulate luck by controlling seed values governing random number generation. We determined which organism among identical competitors experienced the greatest negative drift selection, gave it a deterministic growth advantage, and re-ran the simulation with the same seed. This enabled quantifying the growth advantage required to overcome drift, e.g., a 50% chance to thrive may require a 10-20% improved growth rate. Further, we found that crowding intensity affected that balance. At moderate spacings, there were wide ranges where neither drift nor growth dominated. Those ranges shrank at extreme spacings; close and loose crowding respectively favoured drift and growth. We explain how these results may partially illuminate two conundrums: the difference between taxa and functional stability in wastewater treatment plans and the difference between equivalent and total community size in neutral community assembly models.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://osf.io/fch3z/

  • https://github.com/joeweaver/agent_based_biofilm_drift/

  • https://github.com/nufeb/NUFEB-dev/tree/compute_vol_group

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
Back to top
PreviousNext
Posted December 08, 2022.
Download PDF

Supplementary Material

Data/Code
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Quantifying Drift-Fitness Balance Using an Agent-Based Biofilm Model of Identical Heterotrophs Under Low Nutrient Conditions
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Quantifying Drift-Fitness Balance Using an Agent-Based Biofilm Model of Identical Heterotrophs Under Low Nutrient Conditions
Joseph Earl Weaver
bioRxiv 2022.12.08.519628; doi: https://doi.org/10.1101/2022.12.08.519628
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
Quantifying Drift-Fitness Balance Using an Agent-Based Biofilm Model of Identical Heterotrophs Under Low Nutrient Conditions
Joseph Earl Weaver
bioRxiv 2022.12.08.519628; doi: https://doi.org/10.1101/2022.12.08.519628

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Microbiology
Subject Areas
All Articles
  • Animal Behavior and Cognition (4237)
  • Biochemistry (9148)
  • Bioengineering (6788)
  • Bioinformatics (24029)
  • Biophysics (12141)
  • Cancer Biology (9548)
  • Cell Biology (13796)
  • Clinical Trials (138)
  • Developmental Biology (7642)
  • Ecology (11718)
  • Epidemiology (2066)
  • Evolutionary Biology (15519)
  • Genetics (10650)
  • Genomics (14333)
  • Immunology (9493)
  • Microbiology (22858)
  • Molecular Biology (9103)
  • Neuroscience (49034)
  • Paleontology (355)
  • Pathology (1485)
  • Pharmacology and Toxicology (2572)
  • Physiology (3850)
  • Plant Biology (8339)
  • Scientific Communication and Education (1472)
  • Synthetic Biology (2296)
  • Systems Biology (6197)
  • Zoology (1302)