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Recurrence analysis of ant activity patterns

In this study, we used recurrence quantification analysis (RQA) and recurrence plots (RPs) to compare the movement activity of individual workers of three ant species, as well as a gregarious beetle species. RQA and RPs quantify the number and duration of recurrences of a dynamical system, including...

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Detalles Bibliográficos
Autores principales: Neves, Felipe Marcel, Viana, Ricardo Luiz, Pie, Marcio Roberto
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5633173/
https://www.ncbi.nlm.nih.gov/pubmed/29016648
http://dx.doi.org/10.1371/journal.pone.0185968
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author Neves, Felipe Marcel
Viana, Ricardo Luiz
Pie, Marcio Roberto
author_facet Neves, Felipe Marcel
Viana, Ricardo Luiz
Pie, Marcio Roberto
author_sort Neves, Felipe Marcel
collection PubMed
description In this study, we used recurrence quantification analysis (RQA) and recurrence plots (RPs) to compare the movement activity of individual workers of three ant species, as well as a gregarious beetle species. RQA and RPs quantify the number and duration of recurrences of a dynamical system, including a detailed quantification of signals that could be stochastic, deterministic, or both. First, we found substantial differences between the activity dynamics of beetles and ants, with the results suggesting that the beetles have quasi-periodic dynamics and the ants do not. Second, workers from different ant species varied with respect to their dynamics, presenting degrees of predictability as well as stochastic signals. Finally, differences were found among minor and major caste of the same (dimorphic) ant species. Our results underscore the potential of RQA and RPs in the analysis of complex behavioral patterns, as well as in general inferences on animal behavior and other biological phenomena.
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spelling pubmed-56331732017-10-30 Recurrence analysis of ant activity patterns Neves, Felipe Marcel Viana, Ricardo Luiz Pie, Marcio Roberto PLoS One Research Article In this study, we used recurrence quantification analysis (RQA) and recurrence plots (RPs) to compare the movement activity of individual workers of three ant species, as well as a gregarious beetle species. RQA and RPs quantify the number and duration of recurrences of a dynamical system, including a detailed quantification of signals that could be stochastic, deterministic, or both. First, we found substantial differences between the activity dynamics of beetles and ants, with the results suggesting that the beetles have quasi-periodic dynamics and the ants do not. Second, workers from different ant species varied with respect to their dynamics, presenting degrees of predictability as well as stochastic signals. Finally, differences were found among minor and major caste of the same (dimorphic) ant species. Our results underscore the potential of RQA and RPs in the analysis of complex behavioral patterns, as well as in general inferences on animal behavior and other biological phenomena. Public Library of Science 2017-10-09 /pmc/articles/PMC5633173/ /pubmed/29016648 http://dx.doi.org/10.1371/journal.pone.0185968 Text en © 2017 Neves et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Neves, Felipe Marcel
Viana, Ricardo Luiz
Pie, Marcio Roberto
Recurrence analysis of ant activity patterns
title Recurrence analysis of ant activity patterns
title_full Recurrence analysis of ant activity patterns
title_fullStr Recurrence analysis of ant activity patterns
title_full_unstemmed Recurrence analysis of ant activity patterns
title_short Recurrence analysis of ant activity patterns
title_sort recurrence analysis of ant activity patterns
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5633173/
https://www.ncbi.nlm.nih.gov/pubmed/29016648
http://dx.doi.org/10.1371/journal.pone.0185968
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