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How complex, probable, and predictable is genetically driven red queen chaos?

2015-12Journal article Restricted access
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dc.contributor.authorDuarte, Jorge
dc.contributor.authorRodrigues, Carla
dc.contributor.authorJanuário, Cristina
dc.contributor.authorMartins, Nuno
dc.contributor.authorSardanyés, Josep
dc.date.accessioned2016-04-15T10:12:01Z
dc.date.available2016-04-15T10:12:01Z
dc.date.issued2015-12
dc.description.abstractCoevolution between two antagonistic species has been widely studied theoretically for both ecologically- and genetically-driven Red Queen dynamics. A typical outcome of these systems is an oscillatory behavior causing an endless series of one species adaptation and others counter-adaptation. More recently, a mathematical model combining a three-species food chain system with an adaptive dynamics approach revealed genetically driven chaotic Red Queen coevolution. In the present article, we analyze this mathematical model mainly focusing on the impact of species rates of evolution (mutation rates) in the dynamics. Firstly, we analytically proof the boundedness of the trajectories of the chaotic attractor. The complexity of the coupling between the dynamical variables is quantified using observability indices. By using symbolic dynamics theory, we quantify the complexity of genetically driven Red Queen chaos computing the topological entropy of existing one-dimensional iterated maps using Markov partitions. Co-dimensional two bifurcation diagrams are also built from the period ordering of the orbits of the maps. Then, we study the predictability of the Red Queen chaos, found in narrow regions of mutation rates. To extend the previous analyses, we also computed the likeliness of finding chaos in a given region of the parameter space varying other model parameters simultaneously. Such analyses allowed us to compute a mean predictability measure for the system in the explored region of the parameter space. We found that genetically driven Red Queen chaos, although being restricted to small regions of the analyzed parameter space, might be highly unpredictable.pt_PT
dc.identifier.citationDUARTE, JORGE; [et al.] - How complex, probable, and predictable is genetically driven red queen chaos? Acta Biotheoretica. ISSN. 0001-5342. Vol. 63, N.º 4 (2015), pp. 341-361.pt_PT
dc.identifier.doi10.1007/s10441-015-9254-zpt_PT
dc.identifier.issn0001-5342
dc.identifier.issn1572-8358
dc.identifier.urihttp://hdl.handle.net/10400.21/5989
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherSPRINGERpt_PT
dc.relation.publisherversionhttp://link.springer.com/article/10.1007/s10441-015-9254-zpt_PT
dc.subjectAdaptive dynamicspt_PT
dc.subjectChaospt_PT
dc.subjectCoevolutionpt_PT
dc.subjectEcologypt_PT
dc.subjectPredator-preypt_PT
dc.subjectPredictabilitypt_PT
dc.subjectRed Queenpt_PT
dc.titleHow complex, probable, and predictable is genetically driven red queen chaos?pt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage361pt_PT
oaire.citation.issue4pt_PT
oaire.citation.startPage341pt_PT
oaire.citation.volume63pt_PT
person.familyNameDuarte
person.familyNameJanuário
person.givenNameJorge
person.givenNameCristina
person.identifier.ciencia-idBC1D-1E83-E2B2
person.identifier.orcid0000-0003-2641-3199
person.identifier.orcid0000-0002-6978-876X
person.identifier.ridG-7261-2011
person.identifier.scopus-author-id35310049800
person.identifier.scopus-author-id56526791400
rcaap.rightsclosedAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication4dbec82a-caa4-4662-b156-af73687e867f
relation.isAuthorOfPublication42a4023b-b4c4-4456-aaba-d97bf8c14d6a
relation.isAuthorOfPublication.latestForDiscovery4dbec82a-caa4-4662-b156-af73687e867f

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