Jaguar movement behavior: using trajectories and association rule mining algorithms to unveil behavioral states and social interactions
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1371/journal.pone.0246233 http://hdl.handle.net/11449/205916 |
Resumo: | Animal movement data are widely collected with devices such as sensors and collars, increasing the ability of researchers to monitor animal movement and providing information about animal behavioral patterns. Animal behavior is used as a basis for understanding the relationship between animals and the environment and for guiding decision-making by researchers and public agencies about environmental preservation and conservation actions. Animal movement and behavior are widely studied with a focus on identifying behavioral patterns, such as, animal group formation, the distance between animals and their home range. However, we observed a lack of research proposing a unified solution that aggregates resources for analyses of individual animal behavior and of social interactions between animals. The primary scientific contribution of this work is to present a framework that uses trajectory analysis and association rule mining [Jaiswal and Agarwal, 2012] to provide statistical measures of correlation and dependence to determine the relationship level between animals, their social interactions, and their interactions with other environmental factors based on their individual behavior and movement data. We demonstrate the usefulness of the framework by applying it to movement data from jaguars in the Pantanal, Brazil. This allowed us to describe jaguar behavior, social interactions among jaguars and their behavior in different landscapes, thus providing a highly detailed investigation of jaguar movement decisions at the fine scale. |
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Jaguar movement behavior: using trajectories and association rule mining algorithms to unveil behavioral states and social interactionsAnimal movement data are widely collected with devices such as sensors and collars, increasing the ability of researchers to monitor animal movement and providing information about animal behavioral patterns. Animal behavior is used as a basis for understanding the relationship between animals and the environment and for guiding decision-making by researchers and public agencies about environmental preservation and conservation actions. Animal movement and behavior are widely studied with a focus on identifying behavioral patterns, such as, animal group formation, the distance between animals and their home range. However, we observed a lack of research proposing a unified solution that aggregates resources for analyses of individual animal behavior and of social interactions between animals. The primary scientific contribution of this work is to present a framework that uses trajectory analysis and association rule mining [Jaiswal and Agarwal, 2012] to provide statistical measures of correlation and dependence to determine the relationship level between animals, their social interactions, and their interactions with other environmental factors based on their individual behavior and movement data. We demonstrate the usefulness of the framework by applying it to movement data from jaguars in the Pantanal, Brazil. This allowed us to describe jaguar behavior, social interactions among jaguars and their behavior in different landscapes, thus providing a highly detailed investigation of jaguar movement decisions at the fine scale.Computer Engineering and Digital Systems Department-Escola Politécnica da Universidade de São Paulo (USP)Centro Nacional de Pesquisa e Conservação de Mamíferos Carnívoros (CENAP) ICMBIOCentro de Computação Científica Universidade Estadual Paulista Júlio de Mesquita Filho (UNESP)Centro de Computação Científica Universidade Estadual Paulista Júlio de Mesquita Filho (UNESP)Universidade de São Paulo (USP)ICMBIOUniversidade Estadual Paulista (Unesp)Garcia Fontes, SuelaneGonçalves Morato, RonaldoStanzani, Silvio Luiz [UNESP]Pizzigatti Corrêa, Pedro Luiz2021-06-25T10:23:30Z2021-06-25T10:23:30Z2021-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlee0246233http://dx.doi.org/10.1371/journal.pone.0246233PloS one, v. 16, n. 2, p. e0246233-, 2021.1932-6203http://hdl.handle.net/11449/20591610.1371/journal.pone.02462332-s2.0-85101208053Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengPloS oneinfo:eu-repo/semantics/openAccess2021-10-22T18:56:57Zoai:repositorio.unesp.br:11449/205916Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462021-10-22T18:56:57Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Jaguar movement behavior: using trajectories and association rule mining algorithms to unveil behavioral states and social interactions |
title |
Jaguar movement behavior: using trajectories and association rule mining algorithms to unveil behavioral states and social interactions |
spellingShingle |
Jaguar movement behavior: using trajectories and association rule mining algorithms to unveil behavioral states and social interactions Garcia Fontes, Suelane |
title_short |
Jaguar movement behavior: using trajectories and association rule mining algorithms to unveil behavioral states and social interactions |
title_full |
Jaguar movement behavior: using trajectories and association rule mining algorithms to unveil behavioral states and social interactions |
title_fullStr |
Jaguar movement behavior: using trajectories and association rule mining algorithms to unveil behavioral states and social interactions |
title_full_unstemmed |
Jaguar movement behavior: using trajectories and association rule mining algorithms to unveil behavioral states and social interactions |
title_sort |
Jaguar movement behavior: using trajectories and association rule mining algorithms to unveil behavioral states and social interactions |
author |
Garcia Fontes, Suelane |
author_facet |
Garcia Fontes, Suelane Gonçalves Morato, Ronaldo Stanzani, Silvio Luiz [UNESP] Pizzigatti Corrêa, Pedro Luiz |
author_role |
author |
author2 |
Gonçalves Morato, Ronaldo Stanzani, Silvio Luiz [UNESP] Pizzigatti Corrêa, Pedro Luiz |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Universidade de São Paulo (USP) ICMBIO Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Garcia Fontes, Suelane Gonçalves Morato, Ronaldo Stanzani, Silvio Luiz [UNESP] Pizzigatti Corrêa, Pedro Luiz |
description |
Animal movement data are widely collected with devices such as sensors and collars, increasing the ability of researchers to monitor animal movement and providing information about animal behavioral patterns. Animal behavior is used as a basis for understanding the relationship between animals and the environment and for guiding decision-making by researchers and public agencies about environmental preservation and conservation actions. Animal movement and behavior are widely studied with a focus on identifying behavioral patterns, such as, animal group formation, the distance between animals and their home range. However, we observed a lack of research proposing a unified solution that aggregates resources for analyses of individual animal behavior and of social interactions between animals. The primary scientific contribution of this work is to present a framework that uses trajectory analysis and association rule mining [Jaiswal and Agarwal, 2012] to provide statistical measures of correlation and dependence to determine the relationship level between animals, their social interactions, and their interactions with other environmental factors based on their individual behavior and movement data. We demonstrate the usefulness of the framework by applying it to movement data from jaguars in the Pantanal, Brazil. This allowed us to describe jaguar behavior, social interactions among jaguars and their behavior in different landscapes, thus providing a highly detailed investigation of jaguar movement decisions at the fine scale. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-06-25T10:23:30Z 2021-06-25T10:23:30Z 2021-01-01 |
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://dx.doi.org/10.1371/journal.pone.0246233 PloS one, v. 16, n. 2, p. e0246233-, 2021. 1932-6203 http://hdl.handle.net/11449/205916 10.1371/journal.pone.0246233 2-s2.0-85101208053 |
url |
http://dx.doi.org/10.1371/journal.pone.0246233 http://hdl.handle.net/11449/205916 |
identifier_str_mv |
PloS one, v. 16, n. 2, p. e0246233-, 2021. 1932-6203 10.1371/journal.pone.0246233 2-s2.0-85101208053 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
PloS one |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
e0246233 |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1803649932534480896 |