How complex, probable, and predictable is genetically driven red queen chaos?
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.21/5989 |
Resumo: | Coevolution 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. |
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How complex, probable, and predictable is genetically driven red queen chaos?Adaptive dynamicsChaosCoevolutionEcologyPredator-preyPredictabilityRed QueenCoevolution 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.SPRINGERRCIPLDuarte, JorgeRodrigues, CarlaJanuário, CristinaMartins, NunoSardanyés, Josep2016-04-15T10:12:01Z2015-122015-12-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.21/5989engDUARTE, 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. 341-361.0001-534210.1007/s10441-015-9254-zmetadata only accessinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-08-03T09:50:13Zoai:repositorio.ipl.pt:10400.21/5989Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:15:12.226519Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
How complex, probable, and predictable is genetically driven red queen chaos? |
title |
How complex, probable, and predictable is genetically driven red queen chaos? |
spellingShingle |
How complex, probable, and predictable is genetically driven red queen chaos? Duarte, Jorge Adaptive dynamics Chaos Coevolution Ecology Predator-prey Predictability Red Queen |
title_short |
How complex, probable, and predictable is genetically driven red queen chaos? |
title_full |
How complex, probable, and predictable is genetically driven red queen chaos? |
title_fullStr |
How complex, probable, and predictable is genetically driven red queen chaos? |
title_full_unstemmed |
How complex, probable, and predictable is genetically driven red queen chaos? |
title_sort |
How complex, probable, and predictable is genetically driven red queen chaos? |
author |
Duarte, Jorge |
author_facet |
Duarte, Jorge Rodrigues, Carla Januário, Cristina Martins, Nuno Sardanyés, Josep |
author_role |
author |
author2 |
Rodrigues, Carla Januário, Cristina Martins, Nuno Sardanyés, Josep |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
RCIPL |
dc.contributor.author.fl_str_mv |
Duarte, Jorge Rodrigues, Carla Januário, Cristina Martins, Nuno Sardanyés, Josep |
dc.subject.por.fl_str_mv |
Adaptive dynamics Chaos Coevolution Ecology Predator-prey Predictability Red Queen |
topic |
Adaptive dynamics Chaos Coevolution Ecology Predator-prey Predictability Red Queen |
description |
Coevolution 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. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-12 2015-12-01T00:00:00Z 2016-04-15T10:12:01Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.21/5989 |
url |
http://hdl.handle.net/10400.21/5989 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
DUARTE, 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. 0001-5342 10.1007/s10441-015-9254-z |
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metadata only access info:eu-repo/semantics/openAccess |
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metadata only access |
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openAccess |
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application/pdf |
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SPRINGER |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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