Statistical analysis of lake sediment geochemical data for understanding surface geological factors and processes: An example from Amazonian upland lakes, Brazil
Autor(a) principal: | |
---|---|
Data de Publicação: | 2019 |
Outros Autores: | , , , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1016/j.catena.2018.12.003 http://hdl.handle.net/11449/185468 |
Resumo: | Statistical evaluation applied to geochemical data of upland lake sediments and their catchment basins rocks from Serra dos Carajas was used to identify geochemical signatures associated with underlying processes, sediment provenances, and source-sink relationship. The lakes are Violao, Amendoim and Tres Irmas - TI1, TI2 and TI3. A centred log-ratio transformation (clr) was used prior to multivariate analyses in order to eliminate closure issues in compositional data. Due to the similarity between delta N-15 values and organic sources (mainly from C3 plants), the three lakes were clustered together. Violao Lake receives largest organic contribution from autochthonous sources, such as siliceous sponge spicules and algae, except for it shallower portion (WNW extension), which is more similar to TI2, having low delta N-15 values that are similar to the isotopic signature of upland swamps. The upper continental crust (UCC) normalization pattern shows that sediments are mainly enriched in Fe, P and Se, which is closely related to the catchment lithology. The distribution of elements in TI2 is significantly different from the other lakes, because it is dominated by organic carbon, while the other lakes are a mix of detritus and organic carbon. Factor Analysis (FA) using clr-transformed data distinguishes several geochemical assemblages in the sediments, with the major detritic groups being similar to catchment basin laterites: the Ti-Zr-Hf-Nb-Y-HREEs group corresponds to resistant minerals which remained stable during lateritization; the LREEs group reflects mobilization and reprecipitation by REE bearing minerals; and the Al-V-Cr-Sc association reflects metavolcanic rock. The Fe-P-Mo-As-Zn cluster in the sediments is attributed to Fe-oxyhydroxide precipitation, while TOC-SO3-Hg-Se group is controlled by organic matter. Principal Component Analysis (PCA) further indicates that detritic lake sediments are not directly derived from the parent rocks, but from weathered crusts, mainly ferruginous laterites and soils, which is consistent with their elements ratios. |
id |
UNSP_ee69095bd60a6a85effe060f4db7ee8d |
---|---|
oai_identifier_str |
oai:repositorio.unesp.br:11449/185468 |
network_acronym_str |
UNSP |
network_name_str |
Repositório Institucional da UNESP |
repository_id_str |
2946 |
spelling |
Statistical analysis of lake sediment geochemical data for understanding surface geological factors and processes: An example from Amazonian upland lakes, BrazilMultivariate statisticsGeochemical processesUpland lakesSedimentsAmazoniaSerra dos CarajasStatistical evaluation applied to geochemical data of upland lake sediments and their catchment basins rocks from Serra dos Carajas was used to identify geochemical signatures associated with underlying processes, sediment provenances, and source-sink relationship. The lakes are Violao, Amendoim and Tres Irmas - TI1, TI2 and TI3. A centred log-ratio transformation (clr) was used prior to multivariate analyses in order to eliminate closure issues in compositional data. Due to the similarity between delta N-15 values and organic sources (mainly from C3 plants), the three lakes were clustered together. Violao Lake receives largest organic contribution from autochthonous sources, such as siliceous sponge spicules and algae, except for it shallower portion (WNW extension), which is more similar to TI2, having low delta N-15 values that are similar to the isotopic signature of upland swamps. The upper continental crust (UCC) normalization pattern shows that sediments are mainly enriched in Fe, P and Se, which is closely related to the catchment lithology. The distribution of elements in TI2 is significantly different from the other lakes, because it is dominated by organic carbon, while the other lakes are a mix of detritus and organic carbon. Factor Analysis (FA) using clr-transformed data distinguishes several geochemical assemblages in the sediments, with the major detritic groups being similar to catchment basin laterites: the Ti-Zr-Hf-Nb-Y-HREEs group corresponds to resistant minerals which remained stable during lateritization; the LREEs group reflects mobilization and reprecipitation by REE bearing minerals; and the Al-V-Cr-Sc association reflects metavolcanic rock. The Fe-P-Mo-As-Zn cluster in the sediments is attributed to Fe-oxyhydroxide precipitation, while TOC-SO3-Hg-Se group is controlled by organic matter. Principal Component Analysis (PCA) further indicates that detritic lake sediments are not directly derived from the parent rocks, but from weathered crusts, mainly ferruginous laterites and soils, which is consistent with their elements ratios.Vale Institute of TechnologyConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Inst Tecnol Vale, Rua Boaventura da Silva 955, BR-66055090 Belem, Para, BrazilUniv Fed Para, Inst Geociencias, Programa Posgrad Geol & Geoquim, Av Augusto Correa 1 Guama, BR-66075110 Belem, Para, BrazilGeocon Environm Consulting, London, ON N6G 3H9, CanadaGerencia Meio Ambiente Minas Carajas, Dept Ferrosos Norte, Estr Raymundo Mascarenhas,S-N Mina N4, Parauapebas, Para, BrazilUniv Estadual Paulista, Inst Biociencias, Ctr Isotopos Estaveis, Rua Prof Dr Antonio Celso Wagner Zanin 250, BR-18618689 Botucatu, SP, BrazilUniv Estadual Paulista, Inst Biociencias, Ctr Isotopos Estaveis, Rua Prof Dr Antonio Celso Wagner Zanin 250, BR-18618689 Botucatu, SP, BrazilCNPq: 479182/2012-4CNPq: 442088/2014-0CNPq: 306108/2014-3CNPq: 302839/2016-0CNPq: 306450/2013-5Elsevier B.V.Inst Tecnol ValeUniv Fed ParaGeocon Environm ConsultingGerencia Meio Ambiente Minas CarajasUniversidade Estadual Paulista (Unesp)Sahoo, Prafulla KumarFelix Guimaraes, Jose TassoMartins Souza-Filho, Pedro WalfirPowell, Mike A.Silva, Marcio Sousa daMoraes, Aline MamedeAlves, RonnieLeite, Alessandro SabaNascimento Junior, WilsonRodrigues, Tarcisio MagevskiCosta, Vladimir Eliodoro [UNESP]Dall'Agnol, Roberto2019-10-04T12:35:41Z2019-10-04T12:35:41Z2019-04-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article47-62http://dx.doi.org/10.1016/j.catena.2018.12.003Catena. Amsterdam: Elsevier Science Bv, v. 175, p. 47-62, 2019.0341-8162http://hdl.handle.net/11449/18546810.1016/j.catena.2018.12.003WOS:000459358500006Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengCatenainfo:eu-repo/semantics/openAccess2024-04-11T17:47:18Zoai:repositorio.unesp.br:11449/185468Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-04-11T17:47:18Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Statistical analysis of lake sediment geochemical data for understanding surface geological factors and processes: An example from Amazonian upland lakes, Brazil |
title |
Statistical analysis of lake sediment geochemical data for understanding surface geological factors and processes: An example from Amazonian upland lakes, Brazil |
spellingShingle |
Statistical analysis of lake sediment geochemical data for understanding surface geological factors and processes: An example from Amazonian upland lakes, Brazil Sahoo, Prafulla Kumar Multivariate statistics Geochemical processes Upland lakes Sediments Amazonia Serra dos Carajas |
title_short |
Statistical analysis of lake sediment geochemical data for understanding surface geological factors and processes: An example from Amazonian upland lakes, Brazil |
title_full |
Statistical analysis of lake sediment geochemical data for understanding surface geological factors and processes: An example from Amazonian upland lakes, Brazil |
title_fullStr |
Statistical analysis of lake sediment geochemical data for understanding surface geological factors and processes: An example from Amazonian upland lakes, Brazil |
title_full_unstemmed |
Statistical analysis of lake sediment geochemical data for understanding surface geological factors and processes: An example from Amazonian upland lakes, Brazil |
title_sort |
Statistical analysis of lake sediment geochemical data for understanding surface geological factors and processes: An example from Amazonian upland lakes, Brazil |
author |
Sahoo, Prafulla Kumar |
author_facet |
Sahoo, Prafulla Kumar Felix Guimaraes, Jose Tasso Martins Souza-Filho, Pedro Walfir Powell, Mike A. Silva, Marcio Sousa da Moraes, Aline Mamede Alves, Ronnie Leite, Alessandro Saba Nascimento Junior, Wilson Rodrigues, Tarcisio Magevski Costa, Vladimir Eliodoro [UNESP] Dall'Agnol, Roberto |
author_role |
author |
author2 |
Felix Guimaraes, Jose Tasso Martins Souza-Filho, Pedro Walfir Powell, Mike A. Silva, Marcio Sousa da Moraes, Aline Mamede Alves, Ronnie Leite, Alessandro Saba Nascimento Junior, Wilson Rodrigues, Tarcisio Magevski Costa, Vladimir Eliodoro [UNESP] Dall'Agnol, Roberto |
author2_role |
author author author author author author author author author author author |
dc.contributor.none.fl_str_mv |
Inst Tecnol Vale Univ Fed Para Geocon Environm Consulting Gerencia Meio Ambiente Minas Carajas Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Sahoo, Prafulla Kumar Felix Guimaraes, Jose Tasso Martins Souza-Filho, Pedro Walfir Powell, Mike A. Silva, Marcio Sousa da Moraes, Aline Mamede Alves, Ronnie Leite, Alessandro Saba Nascimento Junior, Wilson Rodrigues, Tarcisio Magevski Costa, Vladimir Eliodoro [UNESP] Dall'Agnol, Roberto |
dc.subject.por.fl_str_mv |
Multivariate statistics Geochemical processes Upland lakes Sediments Amazonia Serra dos Carajas |
topic |
Multivariate statistics Geochemical processes Upland lakes Sediments Amazonia Serra dos Carajas |
description |
Statistical evaluation applied to geochemical data of upland lake sediments and their catchment basins rocks from Serra dos Carajas was used to identify geochemical signatures associated with underlying processes, sediment provenances, and source-sink relationship. The lakes are Violao, Amendoim and Tres Irmas - TI1, TI2 and TI3. A centred log-ratio transformation (clr) was used prior to multivariate analyses in order to eliminate closure issues in compositional data. Due to the similarity between delta N-15 values and organic sources (mainly from C3 plants), the three lakes were clustered together. Violao Lake receives largest organic contribution from autochthonous sources, such as siliceous sponge spicules and algae, except for it shallower portion (WNW extension), which is more similar to TI2, having low delta N-15 values that are similar to the isotopic signature of upland swamps. The upper continental crust (UCC) normalization pattern shows that sediments are mainly enriched in Fe, P and Se, which is closely related to the catchment lithology. The distribution of elements in TI2 is significantly different from the other lakes, because it is dominated by organic carbon, while the other lakes are a mix of detritus and organic carbon. Factor Analysis (FA) using clr-transformed data distinguishes several geochemical assemblages in the sediments, with the major detritic groups being similar to catchment basin laterites: the Ti-Zr-Hf-Nb-Y-HREEs group corresponds to resistant minerals which remained stable during lateritization; the LREEs group reflects mobilization and reprecipitation by REE bearing minerals; and the Al-V-Cr-Sc association reflects metavolcanic rock. The Fe-P-Mo-As-Zn cluster in the sediments is attributed to Fe-oxyhydroxide precipitation, while TOC-SO3-Hg-Se group is controlled by organic matter. Principal Component Analysis (PCA) further indicates that detritic lake sediments are not directly derived from the parent rocks, but from weathered crusts, mainly ferruginous laterites and soils, which is consistent with their elements ratios. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-10-04T12:35:41Z 2019-10-04T12:35:41Z 2019-04-01 |
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/10.1016/j.catena.2018.12.003 Catena. Amsterdam: Elsevier Science Bv, v. 175, p. 47-62, 2019. 0341-8162 http://hdl.handle.net/11449/185468 10.1016/j.catena.2018.12.003 WOS:000459358500006 |
url |
http://dx.doi.org/10.1016/j.catena.2018.12.003 http://hdl.handle.net/11449/185468 |
identifier_str_mv |
Catena. Amsterdam: Elsevier Science Bv, v. 175, p. 47-62, 2019. 0341-8162 10.1016/j.catena.2018.12.003 WOS:000459358500006 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Catena |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
47-62 |
dc.publisher.none.fl_str_mv |
Elsevier B.V. |
publisher.none.fl_str_mv |
Elsevier B.V. |
dc.source.none.fl_str_mv |
Web of Science 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_ |
1799965003226284032 |