Evaluation of caridean ecological distribution in the Ubatuba region, southeastern Brazilian coast using unsupervised machine learning technique

Detalhes bibliográficos
Autor(a) principal: Marques, Alexandre Oliveira [UNESP]
Data de Publicação: 2021
Outros Autores: de Sousa, Aline Nonato [UNESP], Bernardes, Veronica Pereira [UNESP], Bernardo, Camila Hipolito [UNESP], Reis, Danielle Monique [UNESP], Godoy, Amanda Thaís [UNESP], Fransozo, Adilson [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1111/maec.12673
http://hdl.handle.net/11449/233346
Resumo: We used the unsupervised machine learning technique to evaluate the environmental factors responsible for modulating the spatial and seasonal distribution of caridean shrimps from a southeastern region of the Brazilian coast. Samplings were collected from seven transects with an artisanal shrimp fishery boat with two double-rig nets. Samplings occurred every month from October 2008 to September 2009. The most frequently captured species were Exhippolysmata oplophoroides, Leander paulensis, and Nematopalaemon schmitti. The highest abundance of shrimps occurred in autumn at the II, III, and V transects, which present a higher amount of coarse sediment and biodetritic fragments on the bottom. During autumn, the temperatures were the highest and salinity values were the lowest. Data evaluation indicated efficiency in the visualization of interactions of different shrimp species and environmental data. This kind of sediment may be allowing shrimps to burrow in shelters that prevent predation. The seasons with high temperatures and low salinities can offer better conditions for the establishment of the studied species, despite the fact that there is no hypothesis to prove it. Additionally, the higher abundance of such shrimps coincides with vegetal debris deposition, which could serve as food and provide protection for these shrimps. In this region, the vegetation matter deposited at the bottom of the bay comes from the Atlantic Forest. Overall, the preservation of the coastal forest strongly influences the abundance of this taxon, as it provides protection and food for these shrimps.
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spelling Evaluation of caridean ecological distribution in the Ubatuba region, southeastern Brazilian coast using unsupervised machine learning techniquebiodetritusbycatchclusteringcompositionenvironmental protection areashelterWe used the unsupervised machine learning technique to evaluate the environmental factors responsible for modulating the spatial and seasonal distribution of caridean shrimps from a southeastern region of the Brazilian coast. Samplings were collected from seven transects with an artisanal shrimp fishery boat with two double-rig nets. Samplings occurred every month from October 2008 to September 2009. The most frequently captured species were Exhippolysmata oplophoroides, Leander paulensis, and Nematopalaemon schmitti. The highest abundance of shrimps occurred in autumn at the II, III, and V transects, which present a higher amount of coarse sediment and biodetritic fragments on the bottom. During autumn, the temperatures were the highest and salinity values were the lowest. Data evaluation indicated efficiency in the visualization of interactions of different shrimp species and environmental data. This kind of sediment may be allowing shrimps to burrow in shelters that prevent predation. The seasons with high temperatures and low salinities can offer better conditions for the establishment of the studied species, despite the fact that there is no hypothesis to prove it. Additionally, the higher abundance of such shrimps coincides with vegetal debris deposition, which could serve as food and provide protection for these shrimps. In this region, the vegetation matter deposited at the bottom of the bay comes from the Atlantic Forest. Overall, the preservation of the coastal forest strongly influences the abundance of this taxon, as it provides protection and food for these shrimps.Group of Studies on Crustacean Biology Ecology and Culture (NEBECC) Institute of Biosciences Doctoral Program of Zoology University of the State of São Paulo (UNESP)Laboratory of Ecology and Evolution of Crustaceans (LABEEC) Federal University of Rio Grande do Norte (UFRN)Group of Studies on Crustacean Biology Ecology and Culture (NEBECC) Institute of Biosciences Doctoral Program of Zoology University of the State of São Paulo (UNESP)Universidade Estadual Paulista (UNESP)Federal University of Rio Grande do Norte (UFRN)Marques, Alexandre Oliveira [UNESP]de Sousa, Aline Nonato [UNESP]Bernardes, Veronica Pereira [UNESP]Bernardo, Camila Hipolito [UNESP]Reis, Danielle Monique [UNESP]Godoy, Amanda Thaís [UNESP]Fransozo, Adilson [UNESP]2022-05-01T07:58:49Z2022-05-01T07:58:49Z2021-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1111/maec.12673Marine Ecology.1439-04850173-9565http://hdl.handle.net/11449/23334610.1111/maec.126732-s2.0-85111745362Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengMarine Ecologyinfo:eu-repo/semantics/openAccess2022-05-01T07:58:49Zoai:repositorio.unesp.br:11449/233346Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T14:16:14.841108Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Evaluation of caridean ecological distribution in the Ubatuba region, southeastern Brazilian coast using unsupervised machine learning technique
title Evaluation of caridean ecological distribution in the Ubatuba region, southeastern Brazilian coast using unsupervised machine learning technique
spellingShingle Evaluation of caridean ecological distribution in the Ubatuba region, southeastern Brazilian coast using unsupervised machine learning technique
Marques, Alexandre Oliveira [UNESP]
biodetritus
bycatch
clustering
composition
environmental protection area
shelter
title_short Evaluation of caridean ecological distribution in the Ubatuba region, southeastern Brazilian coast using unsupervised machine learning technique
title_full Evaluation of caridean ecological distribution in the Ubatuba region, southeastern Brazilian coast using unsupervised machine learning technique
title_fullStr Evaluation of caridean ecological distribution in the Ubatuba region, southeastern Brazilian coast using unsupervised machine learning technique
title_full_unstemmed Evaluation of caridean ecological distribution in the Ubatuba region, southeastern Brazilian coast using unsupervised machine learning technique
title_sort Evaluation of caridean ecological distribution in the Ubatuba region, southeastern Brazilian coast using unsupervised machine learning technique
author Marques, Alexandre Oliveira [UNESP]
author_facet Marques, Alexandre Oliveira [UNESP]
de Sousa, Aline Nonato [UNESP]
Bernardes, Veronica Pereira [UNESP]
Bernardo, Camila Hipolito [UNESP]
Reis, Danielle Monique [UNESP]
Godoy, Amanda Thaís [UNESP]
Fransozo, Adilson [UNESP]
author_role author
author2 de Sousa, Aline Nonato [UNESP]
Bernardes, Veronica Pereira [UNESP]
Bernardo, Camila Hipolito [UNESP]
Reis, Danielle Monique [UNESP]
Godoy, Amanda Thaís [UNESP]
Fransozo, Adilson [UNESP]
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (UNESP)
Federal University of Rio Grande do Norte (UFRN)
dc.contributor.author.fl_str_mv Marques, Alexandre Oliveira [UNESP]
de Sousa, Aline Nonato [UNESP]
Bernardes, Veronica Pereira [UNESP]
Bernardo, Camila Hipolito [UNESP]
Reis, Danielle Monique [UNESP]
Godoy, Amanda Thaís [UNESP]
Fransozo, Adilson [UNESP]
dc.subject.por.fl_str_mv biodetritus
bycatch
clustering
composition
environmental protection area
shelter
topic biodetritus
bycatch
clustering
composition
environmental protection area
shelter
description We used the unsupervised machine learning technique to evaluate the environmental factors responsible for modulating the spatial and seasonal distribution of caridean shrimps from a southeastern region of the Brazilian coast. Samplings were collected from seven transects with an artisanal shrimp fishery boat with two double-rig nets. Samplings occurred every month from October 2008 to September 2009. The most frequently captured species were Exhippolysmata oplophoroides, Leander paulensis, and Nematopalaemon schmitti. The highest abundance of shrimps occurred in autumn at the II, III, and V transects, which present a higher amount of coarse sediment and biodetritic fragments on the bottom. During autumn, the temperatures were the highest and salinity values were the lowest. Data evaluation indicated efficiency in the visualization of interactions of different shrimp species and environmental data. This kind of sediment may be allowing shrimps to burrow in shelters that prevent predation. The seasons with high temperatures and low salinities can offer better conditions for the establishment of the studied species, despite the fact that there is no hypothesis to prove it. Additionally, the higher abundance of such shrimps coincides with vegetal debris deposition, which could serve as food and provide protection for these shrimps. In this region, the vegetation matter deposited at the bottom of the bay comes from the Atlantic Forest. Overall, the preservation of the coastal forest strongly influences the abundance of this taxon, as it provides protection and food for these shrimps.
publishDate 2021
dc.date.none.fl_str_mv 2021-01-01
2022-05-01T07:58:49Z
2022-05-01T07:58:49Z
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/10.1111/maec.12673
Marine Ecology.
1439-0485
0173-9565
http://hdl.handle.net/11449/233346
10.1111/maec.12673
2-s2.0-85111745362
url http://dx.doi.org/10.1111/maec.12673
http://hdl.handle.net/11449/233346
identifier_str_mv Marine Ecology.
1439-0485
0173-9565
10.1111/maec.12673
2-s2.0-85111745362
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Marine Ecology
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
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
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