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Jaguar movement behavior: Using trajectories and association rule mining algorithms to unveil behavioral states and social interactions

dc.contributor.authorFontes, Suelane Garcia
dc.contributor.authorMorato, Ronaldo Goncalves
dc.contributor.authorStanzani, Silvio Luiz [UNESP]
dc.contributor.authorCorrea, Pedro Luiz Pizzigatti
dc.contributor.institutionUniversidade de São Paulo (USP)
dc.contributor.institutionICMBIO
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2021-06-25T10:19:38Z
dc.date.available2021-06-25T10:19:38Z
dc.date.issued2021-02-01
dc.description.abstractAnimal 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.en
dc.description.affiliationComputer Engineering and Digital Systems Department Escola Politecnica da Universidade de Sao Paulo(USP)
dc.description.affiliationCentro Nacional de Pesquisa e Conservacao de Mamíferos Carnívoros (CENAP) ICMBIO
dc.description.affiliationCentro de Computacao Científica Universidade Estadual PaulistaJulio de Mesquita Filho (UNESP)
dc.description.affiliationUnespCentro de Computacao Científica Universidade Estadual PaulistaJulio de Mesquita Filho (UNESP)
dc.identifierhttp://dx.doi.org/10.1371/journal.pone.0246233
dc.identifier.citationPLoS ONE, v. 16, n. 2 February 2021, 2021.
dc.identifier.doi10.1371/journal.pone.0246233
dc.identifier.issn1932-6203
dc.identifier.scopus2-s2.0-85098951874
dc.identifier.urihttp://hdl.handle.net/11449/205688
dc.language.isoeng
dc.relation.ispartofPLoS ONE
dc.sourceScopus
dc.titleJaguar movement behavior: Using trajectories and association rule mining algorithms to unveil behavioral states and social interactionsen
dc.typeArtigo
dspace.entity.typePublication

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