Literature DB >> 26040593

The organization and control of an evolving interdependent population.

Dervis C Vural1, Alexander Isakov2, L Mahadevan3.   

Abstract

Starting with Darwin, biologists have asked how populations evolve from a low fitness state that is evolutionarily stable to a high fitness state that is not. Specifically of interest is the emergence of cooperation and multicellularity where the fitness of individuals often appears in conflict with that of the population. Theories of social evolution and evolutionary game theory have produced a number of fruitful results employing two-state two-body frameworks. In this study, we depart from this tradition and instead consider a multi-player, multi-state evolutionary game, in which the fitness of an agent is determined by its relationship to an arbitrary number of other agents. We show that populations organize themselves in one of four distinct phases of interdependence depending on one parameter, selection strength. Some of these phases involve the formation of specialized large-scale structures. We then describe how the evolution of independence can be manipulated through various external perturbations.
© 2015 The Author(s) Published by the Royal Society. All rights reserved.

Entities:  

Keywords:  cooperation; evolution; game theory; interdependence; networks; symbiogenesis

Mesh:

Year:  2015        PMID: 26040593      PMCID: PMC4528575          DOI: 10.1098/rsif.2015.0044

Source DB:  PubMed          Journal:  J R Soc Interface        ISSN: 1742-5662            Impact factor:   4.118


  25 in total

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Authors:  A Stoltzfus
Journal:  J Mol Evol       Date:  1999-08       Impact factor: 2.395

Review 2.  Cooperation beyond the dyad: on simple models and a complex society.

Authors:  Richard C Connor
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2010-09-12       Impact factor: 6.237

3.  Evolutionary game theory: Temporal and spatial effects beyond replicator dynamics.

Authors:  Carlos P Roca; José A Cuesta; Angel Sánchez
Journal:  Phys Life Rev       Date:  2009-08-07       Impact factor: 11.025

4.  Cell biology. Irremediable complexity?

Authors:  Michael W Gray; Julius Lukes; John M Archibald; Patrick J Keeling; W Ford Doolittle
Journal:  Science       Date:  2010-11-12       Impact factor: 47.728

Review 5.  Five rules for the evolution of cooperation.

Authors:  Martin A Nowak
Journal:  Science       Date:  2006-12-08       Impact factor: 47.728

6.  Fitness correlates with the extent of cheating in a bacterium.

Authors:  N Jiricny; S P Diggle; S A West; B A Evans; G Ballantyne; A Ross-Gillespie; A S Griffin
Journal:  J Evol Biol       Date:  2010-03-01       Impact factor: 2.411

Review 7.  Evolution of cooperation among tumor cells.

Authors:  Robert Axelrod; David E Axelrod; Kenneth J Pienta
Journal:  Proc Natl Acad Sci U S A       Date:  2006-08-28       Impact factor: 11.205

8.  Dynamic social networks promote cooperation in experiments with humans.

Authors:  David G Rand; Samuel Arbesman; Nicholas A Christakis
Journal:  Proc Natl Acad Sci U S A       Date:  2011-11-14       Impact factor: 11.205

Review 9.  Exploiting social evolution in biofilms.

Authors:  Kerry E Boyle; Silja Heilmann; Dave van Ditmarsch; Joao B Xavier
Journal:  Curr Opin Microbiol       Date:  2013-01-26       Impact factor: 7.934

10.  A model for the emergence of cooperation, interdependence, and structure in evolving networks.

Authors:  S Jain; S Krishna
Journal:  Proc Natl Acad Sci U S A       Date:  2001-01-09       Impact factor: 11.205

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  2 in total

1.  Symbiotic Cell Differentiation and Cooperative Growth in Multicellular Aggregates.

Authors:  Jumpei F Yamagishi; Nen Saito; Kunihiko Kaneko
Journal:  PLoS Comput Biol       Date:  2016-10-17       Impact factor: 4.475

2.  Shearing in flow environment promotes evolution of social behavior in microbial populations.

Authors:  Gurdip Uppal; Dervis Can Vural
Journal:  Elife       Date:  2018-05-22       Impact factor: 8.140

  2 in total

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