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

Dynamical patterns of coexisting strategies in a hybrid discrete-continuum spatial evolutionary game model

A.E.F. Burgess, P.G. Schofield, S.F. Hubbard, View ORCID ProfileM.A.J. Chaplain, T. Lorenzi
doi: https://doi.org/10.1101/079434
A.E.F. Burgess
Division of Mathematics, University of Dundee, Dundee DD1 4HN, Scotland
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
P.G. Schofield
College of Life Sciences, University of Dundee, Dundee DD1 4HN, Scotland
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
S.F. Hubbard
College of Life Sciences, University of Dundee, Dundee DD1 4HN, Scotland
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
M.A.J. Chaplain
School of Mathematics and Statistics, University of St Andrews, St Andrews KY16 9SS, Scotland
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for M.A.J. Chaplain
T. Lorenzi
School of Mathematics and Statistics, University of St Andrews, St Andrews KY16 9SS, Scotland
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: tl47@st-andrews.ac.uk
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Preview PDF
Loading

Abstract

We present a novel hybrid modelling framework that takes into account two aspects which have been largely neglected in previous models of spatial evolutionary games: random motion and chemotaxis. A stochastic individual-based model is used to describe the player dynamics, whereas the evolution of the chemoattractant is governed by a reaction-diffusion equation. The two models are coupled by deriving individual movement rules via the discretisation of a taxis-diffusion equation which describes the evolution of the local number of players. In this framework, individuals occupying the same position can engage in a two-player game, and are awarded a payoff, in terms of reproductive fitness, according to their strategy. As an example, we let individuals play the Hawk-Dove game. Numerical simulations illustrate how random motion and chemotactic response can bring about self-generated dynamical patterns that create favourable conditions for the coexistence of hawks and doves in situations in which the two strategies cannot coexist otherwise. In this sense, our work offers a new perspective of research on spatial evolutionary games, and provides a general formalism to study the dynamics of spatially-structured populations in biological and social contexts where individual motion is likely to affect natural selection of behavioural traits.

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-NC-ND 4.0 International license.
Back to top
PreviousNext
Posted October 05, 2016.
Download PDF
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.
Dynamical patterns of coexisting strategies in a hybrid discrete-continuum spatial evolutionary game model
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
Share
Dynamical patterns of coexisting strategies in a hybrid discrete-continuum spatial evolutionary game model
A.E.F. Burgess, P.G. Schofield, S.F. Hubbard, M.A.J. Chaplain, T. Lorenzi
bioRxiv 079434; doi: https://doi.org/10.1101/079434
Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
Citation Tools
Dynamical patterns of coexisting strategies in a hybrid discrete-continuum spatial evolutionary game model
A.E.F. Burgess, P.G. Schofield, S.F. Hubbard, M.A.J. Chaplain, T. Lorenzi
bioRxiv 079434; doi: https://doi.org/10.1101/079434

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

  • Evolutionary Biology
Subject Areas
All Articles
  • Animal Behavior and Cognition (1537)
  • Biochemistry (2494)
  • Bioengineering (1751)
  • Bioinformatics (9712)
  • Biophysics (3923)
  • Cancer Biology (2983)
  • Cell Biology (4225)
  • Clinical Trials (135)
  • Developmental Biology (2645)
  • Ecology (4116)
  • Epidemiology (2033)
  • Evolutionary Biology (6919)
  • Genetics (5229)
  • Genomics (6528)
  • Immunology (2201)
  • Microbiology (6988)
  • Molecular Biology (2774)
  • Neuroscience (17378)
  • Paleontology (126)
  • Pathology (432)
  • Pharmacology and Toxicology (709)
  • Physiology (1064)
  • Plant Biology (2508)
  • Scientific Communication and Education (646)
  • Synthetic Biology (835)
  • Systems Biology (2695)
  • Zoology (437)