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dc.contributor.authorAlcalde Cuesta, Fernando
dc.contributor.authorGonzález Sequeiros, Pablo
dc.contributor.authorLozano Rojo, Álvaro
dc.date.accessioned2020-05-08T11:15:27Z
dc.date.available2020-05-08T11:15:27Z
dc.date.issued2018
dc.identifier.citationAlcalde Cuesta F, González Sequeiros P, Lozano Rojo Á (2018) Evolutionary regime transitions in structured populations. PLoS ONE 13(11): e0200670
dc.identifier.urihttp://hdl.handle.net/10347/22139
dc.description.abstractThe evolutionary dynamics of a finite population where resident individuals are replaced by mutant ones depends on its spatial structure. Usually, the population adopts the form of an undirected graph where the place occupied by each individual is represented by a vertex and it is bidirectionally linked to the places that can be occupied by its offspring. There are undirected graph structures that act as amplifiers of selection increasing the probability that the offspring of an advantageous mutant spreads through the graph reaching any vertex. But there also are undirected graph structures acting as suppressors of selection where this probability is less than that of the same individual placed in a homogeneous population. Here, firstly, we present the distribution of these evolutionary regimes for all undirected graphs with N ≤ 10 vertices. Some of them exhibit transitions between different regimes when the mutant fitness increases. In particular, as it has been already observed for small-order random graphs, we show that most graphs of order N ≤ 10 are amplifiers of selection. Secondly, we describe examples of amplifiers of order 7 that become suppressors from some critical value. In fact, for graphs of order N ≤ 7, we apply computer-aided techniques to symbolically compute their fixation probability and then their evolutionary regime, as well as the critical values for which they change their regime. Thirdly, the same technique is applied to some families of highly symmetrical graphs as a mean to explore methods of suppressing selection. The existence of suppression mechanisms that reverse an amplification regime when fitness increases could have a great interest in biology and network science. Finally, the analysis of all graphs from order 8 to order 10 reveals a complex and rich evolutionary dynamics, with multiple transitions between different regimes, which have not been examined in detail until now
dc.description.sponsorshipThis work was supported by the Agencia Estatal de Investigacion (Grant MTM2016-77642-C2-2-P) and the European Regional Development Fund grant MTM2016-77642-C2-2-P to FAC, PGS and ALR. ALR was also supported by the Ministerio de Educacion, Cultura y Deporte (Jose Castillejos Grant CAS17/00258), the Gobierno de Aragon and the European Regional Development Fund (Grant E15 Geometra)
dc.language.isoeng
dc.publisherPLOS
dc.rights© 2018 Alcalde Cuesta et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleEvolutionary regime transitions in structured populations
dc.typejournal article
dc.identifier.doi10.1371/journal.pone.0200670
dc.relation.publisherversionhttps://doi.org/10.1371/journal.pone.0200670
dc.type.hasVersionVoR
dc.identifier.essn1932-6203
dc.rights.accessRightsopen access
dc.contributor.affiliationUniversidade de Santiago de Compostela. Departamento de Didácticas Aplicadas
dc.contributor.affiliationUniversidade de Santiago de Compostela. Departamento de Matemáticas
dc.description.peerreviewedSI
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/MTM2016-77642-C2-2-P/ES


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© 2018 Alcalde Cuesta et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
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 © 2018 Alcalde Cuesta et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited





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