Multivariate Statistical Analysis of the Phytoplankton Interactions with Physicochemical and Meteorological Parameters in Volcanic Crater Lakes from Azores

Detalhes bibliográficos
Autor(a) principal: Lopes, João
Data de Publicação: 2022
Outros Autores: Pinto, Afonso Silva, Eleutério, Telmo, Meirelles, Maria Gabriela, Vasconcelos, Helena Cristina
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/150794
Resumo: Publisher Copyright: © 2022 by the authors.
id RCAP_24299ab67208008d3a4fd2277e02e151
oai_identifier_str oai:run.unl.pt:10362/150794
network_acronym_str RCAP
network_name_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository_id_str 7160
spelling Multivariate Statistical Analysis of the Phytoplankton Interactions with Physicochemical and Meteorological Parameters in Volcanic Crater Lakes from AzoresANOVAAzoresPCA modelsphytoplanktonvolcanic lakesGeography, Planning and DevelopmentBiochemistryAquatic ScienceWater Science and TechnologySDG 13 - Climate ActionPublisher Copyright: © 2022 by the authors.This study aimed to identify the key factors influencing the phytoplankton development in four lakes on the island of São Miguel (Azores). We used a multivariate analysis of biological parameters (phytoplankton), physicochemical parameters, and meteorological data. Data were collected between 2003 and 2018 in the volcanic Lakes of Sete Cidades (Green and Blue), Fogo, and Furnas. The ecosystems of these bodies of water are increasingly vulnerable to anthropogenic activities (increasing human pressure) as well as to changing climate patterns. This analysis is the first exploratory approach to this dataset to explore trends and patterns of evolution from a multivariate perspective. This approach is also intended to improve understanding of the conditions that favor the emergence of different Cyanobacterial divisions. For this purpose, several statistical and chemometric methods were used, such as analysis of variance (ANOVA) and principal component analysis (PCA). Multivariate models combining biological and meteorological data focused from 2010 to 2012. The results from the PCA models showed that the abundance of Bacillariophyta, Dinophyta, and Cryptophyta phyla are correlated and appear to be influenced by high levels of precipitation, evaporation, and wind speed. On the other hand, the Cyanophyta, Chlorophyta, and Chrysophyta phyla appear to be more correlated with high values of air temperature, water temperature, and radiation. Also, the Euglenophyta phylum appears to be associated with low levels of precipitation, evaporation and wind speed, and high temperatures. Finally, we can conclude that these lakes have endured physicochemical parameters over the past 15 years, meaning that the measures adopted to monitor and protect the lakes are effective.LIBPhys-UNLDF – Departamento de FísicaRUNLopes, JoãoPinto, Afonso SilvaEleutério, TelmoMeirelles, Maria GabrielaVasconcelos, Helena Cristina2023-03-17T22:30:31Z2022-08-192022-08-19T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article21application/pdfhttp://hdl.handle.net/10362/150794engLopes, J., Pinto, A. S., Eleutério, T., Meirelles, M. G., & Vasconcelos, H. C. (2022). Multivariate Statistical Analysis of the Phytoplankton Interactions with Physicochemical and Meteorological Parameters in Volcanic Crater Lakes from Azores. Water (Switzerland), 14(16), [2548]. https://doi.org/10.3390/w141625482073-4441PURE: 56158724https://doi.org/10.3390/w14162548info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:33:13Zoai:run.unl.pt:10362/150794Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:54:19.306305Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Multivariate Statistical Analysis of the Phytoplankton Interactions with Physicochemical and Meteorological Parameters in Volcanic Crater Lakes from Azores
title Multivariate Statistical Analysis of the Phytoplankton Interactions with Physicochemical and Meteorological Parameters in Volcanic Crater Lakes from Azores
spellingShingle Multivariate Statistical Analysis of the Phytoplankton Interactions with Physicochemical and Meteorological Parameters in Volcanic Crater Lakes from Azores
Lopes, João
ANOVA
Azores
PCA models
phytoplankton
volcanic lakes
Geography, Planning and Development
Biochemistry
Aquatic Science
Water Science and Technology
SDG 13 - Climate Action
title_short Multivariate Statistical Analysis of the Phytoplankton Interactions with Physicochemical and Meteorological Parameters in Volcanic Crater Lakes from Azores
title_full Multivariate Statistical Analysis of the Phytoplankton Interactions with Physicochemical and Meteorological Parameters in Volcanic Crater Lakes from Azores
title_fullStr Multivariate Statistical Analysis of the Phytoplankton Interactions with Physicochemical and Meteorological Parameters in Volcanic Crater Lakes from Azores
title_full_unstemmed Multivariate Statistical Analysis of the Phytoplankton Interactions with Physicochemical and Meteorological Parameters in Volcanic Crater Lakes from Azores
title_sort Multivariate Statistical Analysis of the Phytoplankton Interactions with Physicochemical and Meteorological Parameters in Volcanic Crater Lakes from Azores
author Lopes, João
author_facet Lopes, João
Pinto, Afonso Silva
Eleutério, Telmo
Meirelles, Maria Gabriela
Vasconcelos, Helena Cristina
author_role author
author2 Pinto, Afonso Silva
Eleutério, Telmo
Meirelles, Maria Gabriela
Vasconcelos, Helena Cristina
author2_role author
author
author
author
dc.contributor.none.fl_str_mv LIBPhys-UNL
DF – Departamento de Física
RUN
dc.contributor.author.fl_str_mv Lopes, João
Pinto, Afonso Silva
Eleutério, Telmo
Meirelles, Maria Gabriela
Vasconcelos, Helena Cristina
dc.subject.por.fl_str_mv ANOVA
Azores
PCA models
phytoplankton
volcanic lakes
Geography, Planning and Development
Biochemistry
Aquatic Science
Water Science and Technology
SDG 13 - Climate Action
topic ANOVA
Azores
PCA models
phytoplankton
volcanic lakes
Geography, Planning and Development
Biochemistry
Aquatic Science
Water Science and Technology
SDG 13 - Climate Action
description Publisher Copyright: © 2022 by the authors.
publishDate 2022
dc.date.none.fl_str_mv 2022-08-19
2022-08-19T00:00:00Z
2023-03-17T22:30:31Z
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://hdl.handle.net/10362/150794
url http://hdl.handle.net/10362/150794
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Lopes, J., Pinto, A. S., Eleutério, T., Meirelles, M. G., & Vasconcelos, H. C. (2022). Multivariate Statistical Analysis of the Phytoplankton Interactions with Physicochemical and Meteorological Parameters in Volcanic Crater Lakes from Azores. Water (Switzerland), 14(16), [2548]. https://doi.org/10.3390/w14162548
2073-4441
PURE: 56158724
https://doi.org/10.3390/w14162548
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 21
application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
_version_ 1799138132412596224