Matching pollution with adaptive changes in mangrove plants by multivariate statistics. A case study, Rhizophora mangle from four neotropical mangroves in Brazil

Autores
Souza, Iara da Costa; Morozesk, Mariana; Duarte, Ian Drumond; Bonomo, Marina Marques; Rocha, Lívia Dorsch; Furlan, Larissa Maria; Arrivabene, Hiulana Pereira; Monferran, Magdalena Victoria; Matsumoto, Silvia Tamie; Milanez, Camilla Rozindo Dias; Wunderlin, Daniel Alberto; Fernandes, Marisa Narciso
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Roots of mangrove trees have an important role in depurating water and sediments by retaining metals that may accumulate in different plant tissues, affecting physiological processes and anatomy. The present study aimed to evaluate adaptive changes in root of Rhizophora mangle in response to different levels of chemical elements (metals/metalloids) in interstitial water and sediments from four neotropical mangroves in Brazil. What sets this study apart from other studies is that we not only investigate adaptive modifications in R. mangle but also changes in environments where this plant grows, evaluating correspondence between physical, chemical and biological issues by a combined set of multivariate statistical methods (pattern recognition). Thus, we looked to match changes in the environment with adaptations in plants. Multivariate statistics highlighted that the lignified periderm and the air gaps are directly related to the environmental contamination. Current results provide new evidences of root anatomical strategies to deal with contaminated environments. Multivariate statistics greatly contributes to extrapolate results from complex data matrixes obtained when analyzing environmental issues, pointing out parameters involved in environmental changes and also evidencing the adaptive response of the exposed biota. © 2014 Elsevier Ltd.
Fil: Souza, Iara da Costa. Universidade Federal do São Carlos; Brasil
Fil: Morozesk, Mariana. Universidade Federal do Espírito Santo; Brasil
Fil: Duarte, Ian Drumond. Universidade Federal do Espírito Santo; Brasil
Fil: Bonomo, Marina Marques. Universidade Federal do Espírito Santo; Brasil
Fil: Rocha, Lívia Dorsch. Universidade Federal do Espírito Santo; Brasil
Fil: Furlan, Larissa Maria. Universidade Federal do Espírito Santo; Brasil
Fil: Arrivabene, Hiulana Pereira. Universidade Federal do Espírito Santo; Brasil
Fil: Monferran, Magdalena Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Ciencia y Tecnología de Alimentos Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Ciencia y Tecnología de Alimentos Córdoba; Argentina
Fil: Matsumoto, Silvia Tamie. Universidade Federal do Espírito Santo; Brasil
Fil: Milanez, Camilla Rozindo Dias. Universidade Federal do Espírito Santo; Brasil
Fil: Wunderlin, Daniel Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Ciencia y Tecnología de Alimentos Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Ciencia y Tecnología de Alimentos Córdoba; Argentina
Fil: Fernandes, Marisa Narciso. Universidade Federal do São Carlos; Brasil
Materia
ESTUARY
HISTOCHEMISTRY AND RED MANGROVE
MULTIVARIATE ANALYSES
POLLUTION
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/185967
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/185967
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Matching pollution with adaptive changes in mangrove plants by multivariate statistics. A case study, Rhizophora mangle from four neotropical mangroves in BrazilSouza, Iara da CostaMorozesk, MarianaDuarte, Ian DrumondBonomo, Marina MarquesRocha, Lívia DorschFurlan, Larissa MariaArrivabene, Hiulana PereiraMonferran, Magdalena VictoriaMatsumoto, Silvia TamieMilanez, Camilla Rozindo DiasWunderlin, Daniel AlbertoFernandes, Marisa NarcisoESTUARYHISTOCHEMISTRY AND RED MANGROVEMULTIVARIATE ANALYSESPOLLUTIONhttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1Roots of mangrove trees have an important role in depurating water and sediments by retaining metals that may accumulate in different plant tissues, affecting physiological processes and anatomy. The present study aimed to evaluate adaptive changes in root of Rhizophora mangle in response to different levels of chemical elements (metals/metalloids) in interstitial water and sediments from four neotropical mangroves in Brazil. What sets this study apart from other studies is that we not only investigate adaptive modifications in R. mangle but also changes in environments where this plant grows, evaluating correspondence between physical, chemical and biological issues by a combined set of multivariate statistical methods (pattern recognition). Thus, we looked to match changes in the environment with adaptations in plants. Multivariate statistics highlighted that the lignified periderm and the air gaps are directly related to the environmental contamination. Current results provide new evidences of root anatomical strategies to deal with contaminated environments. Multivariate statistics greatly contributes to extrapolate results from complex data matrixes obtained when analyzing environmental issues, pointing out parameters involved in environmental changes and also evidencing the adaptive response of the exposed biota. © 2014 Elsevier Ltd.Fil: Souza, Iara da Costa. Universidade Federal do São Carlos; BrasilFil: Morozesk, Mariana. Universidade Federal do Espírito Santo; BrasilFil: Duarte, Ian Drumond. Universidade Federal do Espírito Santo; BrasilFil: Bonomo, Marina Marques. Universidade Federal do Espírito Santo; BrasilFil: Rocha, Lívia Dorsch. Universidade Federal do Espírito Santo; BrasilFil: Furlan, Larissa Maria. Universidade Federal do Espírito Santo; BrasilFil: Arrivabene, Hiulana Pereira. Universidade Federal do Espírito Santo; BrasilFil: Monferran, Magdalena Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Ciencia y Tecnología de Alimentos Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Ciencia y Tecnología de Alimentos Córdoba; ArgentinaFil: Matsumoto, Silvia Tamie. Universidade Federal do Espírito Santo; BrasilFil: Milanez, Camilla Rozindo Dias. Universidade Federal do Espírito Santo; BrasilFil: Wunderlin, Daniel Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Ciencia y Tecnología de Alimentos Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Ciencia y Tecnología de Alimentos Córdoba; ArgentinaFil: Fernandes, Marisa Narciso. Universidade Federal do São Carlos; BrasilPergamon-Elsevier Science Ltd2014-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/185967Souza, Iara da Costa; Morozesk, Mariana; Duarte, Ian Drumond; Bonomo, Marina Marques; Rocha, Lívia Dorsch; et al.; Matching pollution with adaptive changes in mangrove plants by multivariate statistics. A case study, Rhizophora mangle from four neotropical mangroves in Brazil; Pergamon-Elsevier Science Ltd; Chemosphere; 108; 8-2014; 115-1240045-6535CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.chemosphere.2014.02.066info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S004565351400335Xinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-29T12:12:31Zoai:ri.conicet.gov.ar:11336/185967instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-29 12:12:31.995CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Matching pollution with adaptive changes in mangrove plants by multivariate statistics. A case study, Rhizophora mangle from four neotropical mangroves in Brazil
title Matching pollution with adaptive changes in mangrove plants by multivariate statistics. A case study, Rhizophora mangle from four neotropical mangroves in Brazil
spellingShingle Matching pollution with adaptive changes in mangrove plants by multivariate statistics. A case study, Rhizophora mangle from four neotropical mangroves in Brazil
Souza, Iara da Costa
ESTUARY
HISTOCHEMISTRY AND RED MANGROVE
MULTIVARIATE ANALYSES
POLLUTION
title_short Matching pollution with adaptive changes in mangrove plants by multivariate statistics. A case study, Rhizophora mangle from four neotropical mangroves in Brazil
title_full Matching pollution with adaptive changes in mangrove plants by multivariate statistics. A case study, Rhizophora mangle from four neotropical mangroves in Brazil
title_fullStr Matching pollution with adaptive changes in mangrove plants by multivariate statistics. A case study, Rhizophora mangle from four neotropical mangroves in Brazil
title_full_unstemmed Matching pollution with adaptive changes in mangrove plants by multivariate statistics. A case study, Rhizophora mangle from four neotropical mangroves in Brazil
title_sort Matching pollution with adaptive changes in mangrove plants by multivariate statistics. A case study, Rhizophora mangle from four neotropical mangroves in Brazil
dc.creator.none.fl_str_mv Souza, Iara da Costa
Morozesk, Mariana
Duarte, Ian Drumond
Bonomo, Marina Marques
Rocha, Lívia Dorsch
Furlan, Larissa Maria
Arrivabene, Hiulana Pereira
Monferran, Magdalena Victoria
Matsumoto, Silvia Tamie
Milanez, Camilla Rozindo Dias
Wunderlin, Daniel Alberto
Fernandes, Marisa Narciso
author Souza, Iara da Costa
author_facet Souza, Iara da Costa
Morozesk, Mariana
Duarte, Ian Drumond
Bonomo, Marina Marques
Rocha, Lívia Dorsch
Furlan, Larissa Maria
Arrivabene, Hiulana Pereira
Monferran, Magdalena Victoria
Matsumoto, Silvia Tamie
Milanez, Camilla Rozindo Dias
Wunderlin, Daniel Alberto
Fernandes, Marisa Narciso
author_role author
author2 Morozesk, Mariana
Duarte, Ian Drumond
Bonomo, Marina Marques
Rocha, Lívia Dorsch
Furlan, Larissa Maria
Arrivabene, Hiulana Pereira
Monferran, Magdalena Victoria
Matsumoto, Silvia Tamie
Milanez, Camilla Rozindo Dias
Wunderlin, Daniel Alberto
Fernandes, Marisa Narciso
author2_role author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv ESTUARY
HISTOCHEMISTRY AND RED MANGROVE
MULTIVARIATE ANALYSES
POLLUTION
topic ESTUARY
HISTOCHEMISTRY AND RED MANGROVE
MULTIVARIATE ANALYSES
POLLUTION
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Roots of mangrove trees have an important role in depurating water and sediments by retaining metals that may accumulate in different plant tissues, affecting physiological processes and anatomy. The present study aimed to evaluate adaptive changes in root of Rhizophora mangle in response to different levels of chemical elements (metals/metalloids) in interstitial water and sediments from four neotropical mangroves in Brazil. What sets this study apart from other studies is that we not only investigate adaptive modifications in R. mangle but also changes in environments where this plant grows, evaluating correspondence between physical, chemical and biological issues by a combined set of multivariate statistical methods (pattern recognition). Thus, we looked to match changes in the environment with adaptations in plants. Multivariate statistics highlighted that the lignified periderm and the air gaps are directly related to the environmental contamination. Current results provide new evidences of root anatomical strategies to deal with contaminated environments. Multivariate statistics greatly contributes to extrapolate results from complex data matrixes obtained when analyzing environmental issues, pointing out parameters involved in environmental changes and also evidencing the adaptive response of the exposed biota. © 2014 Elsevier Ltd.
Fil: Souza, Iara da Costa. Universidade Federal do São Carlos; Brasil
Fil: Morozesk, Mariana. Universidade Federal do Espírito Santo; Brasil
Fil: Duarte, Ian Drumond. Universidade Federal do Espírito Santo; Brasil
Fil: Bonomo, Marina Marques. Universidade Federal do Espírito Santo; Brasil
Fil: Rocha, Lívia Dorsch. Universidade Federal do Espírito Santo; Brasil
Fil: Furlan, Larissa Maria. Universidade Federal do Espírito Santo; Brasil
Fil: Arrivabene, Hiulana Pereira. Universidade Federal do Espírito Santo; Brasil
Fil: Monferran, Magdalena Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Ciencia y Tecnología de Alimentos Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Ciencia y Tecnología de Alimentos Córdoba; Argentina
Fil: Matsumoto, Silvia Tamie. Universidade Federal do Espírito Santo; Brasil
Fil: Milanez, Camilla Rozindo Dias. Universidade Federal do Espírito Santo; Brasil
Fil: Wunderlin, Daniel Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Ciencia y Tecnología de Alimentos Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Ciencia y Tecnología de Alimentos Córdoba; Argentina
Fil: Fernandes, Marisa Narciso. Universidade Federal do São Carlos; Brasil
description Roots of mangrove trees have an important role in depurating water and sediments by retaining metals that may accumulate in different plant tissues, affecting physiological processes and anatomy. The present study aimed to evaluate adaptive changes in root of Rhizophora mangle in response to different levels of chemical elements (metals/metalloids) in interstitial water and sediments from four neotropical mangroves in Brazil. What sets this study apart from other studies is that we not only investigate adaptive modifications in R. mangle but also changes in environments where this plant grows, evaluating correspondence between physical, chemical and biological issues by a combined set of multivariate statistical methods (pattern recognition). Thus, we looked to match changes in the environment with adaptations in plants. Multivariate statistics highlighted that the lignified periderm and the air gaps are directly related to the environmental contamination. Current results provide new evidences of root anatomical strategies to deal with contaminated environments. Multivariate statistics greatly contributes to extrapolate results from complex data matrixes obtained when analyzing environmental issues, pointing out parameters involved in environmental changes and also evidencing the adaptive response of the exposed biota. © 2014 Elsevier Ltd.
publishDate 2014
dc.date.none.fl_str_mv 2014-08
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/185967
Souza, Iara da Costa; Morozesk, Mariana; Duarte, Ian Drumond; Bonomo, Marina Marques; Rocha, Lívia Dorsch; et al.; Matching pollution with adaptive changes in mangrove plants by multivariate statistics. A case study, Rhizophora mangle from four neotropical mangroves in Brazil; Pergamon-Elsevier Science Ltd; Chemosphere; 108; 8-2014; 115-124
0045-6535
CONICET Digital
CONICET
url http://hdl.handle.net/11336/185967
identifier_str_mv Souza, Iara da Costa; Morozesk, Mariana; Duarte, Ian Drumond; Bonomo, Marina Marques; Rocha, Lívia Dorsch; et al.; Matching pollution with adaptive changes in mangrove plants by multivariate statistics. A case study, Rhizophora mangle from four neotropical mangroves in Brazil; Pergamon-Elsevier Science Ltd; Chemosphere; 108; 8-2014; 115-124
0045-6535
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.chemosphere.2014.02.066
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S004565351400335X
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Pergamon-Elsevier Science Ltd
publisher.none.fl_str_mv Pergamon-Elsevier Science Ltd
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.10058

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