Deriving phytoplankton size classes from satellite data: validation along a trophic gradient in the eastern Atlantic Ocean

Detalhes bibliográficos
Autor(a) principal: Brotas, Vanda
Data de Publicação: 2013
Outros Autores: Brewin, Robert J.W., Sá, Carolina, Brito, Ana C., Silva, Alexandra, Mendes, Carlos Rafael, Diniz, Tânia, Kaufmann, Manfred, Tarran, Glen, Groom, Steve B., Platt, Trevor, Sathyendranath, Shubha
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.13/3703
Resumo: In recent years, the global distribution of phytoplankton functional types (PFT) and phytoplankton size classes (PSC) has been determined by remote sensing. Many of these methods rely on interpretation of phytoplankton size or type from pigment data, but independent validation has been difficult due to lack of appropriate in situ data on cell size. This work uses in situ data (photosynthetic pigments concentration and cell abundances) from the north-east Atlantic, along a trophic gradient, sampled from 2005 to 2010, as well as Atlantic Meridional Transect (AMT) data for the same region, to test a previously developed conceptual model, which calculates the fractional contributions of pico-, nano- and micro-plankton to total phytoplankton chlorophyll biomass (Brewin et al., 2010). The application of the model proved to be successful, as shown by low mean absolute error between data and model fit. However, regional values obtained for the model parameters had some effect on the relative distribution of size classes as a function of chlorophyll-a, compared with the results according to the original model. The regional parameterisation yielded a dominance of micro-plankton contribution for chlorophyll-a concentrations greater than 0.5 mg m−3 , rather than from 1.3 mg m−3 in the original model. Intracellular chlorophyll-a (Chla) per cell, for each size class, was computed from the cell enumeration results (microscope counts and flow cytometry) and the chlorophyll-a concentration for that size class given by the model. The median intracellular chlorophyll-a values computed were 0.004, 0.224 and 26.78 pg Chla cell−1 for pico-, nano-, and micro-plankton respectively. This is generally consistent with the literature, thereby providing an indirect validation of the method based on pigments to assign size classes. Using a satellite-derived composite image of chlorophyll-a for the study area, a map of cell abundance was generated based on the computed intracellular chlorophyll-a for each size-class, thus extending the remote-sensing method for mapping size classes of phytoplankton from chlorophyll-a concentration to mapping cell numbers in each class. The map reveals the ubiquitous presence of pico-plankton, and shows that all size classes are more abundant in more productive areas.
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spelling Deriving phytoplankton size classes from satellite data: validation along a trophic gradient in the eastern Atlantic OceanPhytoplanktonCell-size structure and abundanceRemotely-sensed chlorophyll-aIntracellular chlorophyll-a content per size classEastern North Atlantic.Faculdade de Ciências da VidaIn recent years, the global distribution of phytoplankton functional types (PFT) and phytoplankton size classes (PSC) has been determined by remote sensing. Many of these methods rely on interpretation of phytoplankton size or type from pigment data, but independent validation has been difficult due to lack of appropriate in situ data on cell size. This work uses in situ data (photosynthetic pigments concentration and cell abundances) from the north-east Atlantic, along a trophic gradient, sampled from 2005 to 2010, as well as Atlantic Meridional Transect (AMT) data for the same region, to test a previously developed conceptual model, which calculates the fractional contributions of pico-, nano- and micro-plankton to total phytoplankton chlorophyll biomass (Brewin et al., 2010). The application of the model proved to be successful, as shown by low mean absolute error between data and model fit. However, regional values obtained for the model parameters had some effect on the relative distribution of size classes as a function of chlorophyll-a, compared with the results according to the original model. The regional parameterisation yielded a dominance of micro-plankton contribution for chlorophyll-a concentrations greater than 0.5 mg m−3 , rather than from 1.3 mg m−3 in the original model. Intracellular chlorophyll-a (Chla) per cell, for each size class, was computed from the cell enumeration results (microscope counts and flow cytometry) and the chlorophyll-a concentration for that size class given by the model. The median intracellular chlorophyll-a values computed were 0.004, 0.224 and 26.78 pg Chla cell−1 for pico-, nano-, and micro-plankton respectively. This is generally consistent with the literature, thereby providing an indirect validation of the method based on pigments to assign size classes. Using a satellite-derived composite image of chlorophyll-a for the study area, a map of cell abundance was generated based on the computed intracellular chlorophyll-a for each size-class, thus extending the remote-sensing method for mapping size classes of phytoplankton from chlorophyll-a concentration to mapping cell numbers in each class. The map reveals the ubiquitous presence of pico-plankton, and shows that all size classes are more abundant in more productive areas.ElsevierDigitUMaBrotas, VandaBrewin, Robert J.W.Sá, CarolinaBrito, Ana C.Silva, AlexandraMendes, Carlos RafaelDiniz, TâniaKaufmann, ManfredTarran, GlenGroom, Steve B.Platt, TrevorSathyendranath, Shubha2021-10-07T07:59:48Z2013-01-01T00:00:00Z2013-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.13/3703engBrotas, V., Brewin, R. J., Sá, C., Brito, A. C., Silva, A., Mendes, C. R., ... & Sathyendranath, S. (2013). Deriving phytoplankton size classes from satellite data: validation along a trophic gradient in the eastern Atlantic Ocean. Remote Sensing of Environment, 134, 66-77. https://doi.org/10.1016/j.rse.2013.02.01310.1016/j.rse.2013.02.013info: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:RCAAP2022-09-05T12:56:44Zoai:digituma.uma.pt:10400.13/3703Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T15:07:05.781830Repositório 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 Deriving phytoplankton size classes from satellite data: validation along a trophic gradient in the eastern Atlantic Ocean
title Deriving phytoplankton size classes from satellite data: validation along a trophic gradient in the eastern Atlantic Ocean
spellingShingle Deriving phytoplankton size classes from satellite data: validation along a trophic gradient in the eastern Atlantic Ocean
Brotas, Vanda
Phytoplankton
Cell-size structure and abundance
Remotely-sensed chlorophyll-a
Intracellular chlorophyll-a content per size class
Eastern North Atlantic
.
Faculdade de Ciências da Vida
title_short Deriving phytoplankton size classes from satellite data: validation along a trophic gradient in the eastern Atlantic Ocean
title_full Deriving phytoplankton size classes from satellite data: validation along a trophic gradient in the eastern Atlantic Ocean
title_fullStr Deriving phytoplankton size classes from satellite data: validation along a trophic gradient in the eastern Atlantic Ocean
title_full_unstemmed Deriving phytoplankton size classes from satellite data: validation along a trophic gradient in the eastern Atlantic Ocean
title_sort Deriving phytoplankton size classes from satellite data: validation along a trophic gradient in the eastern Atlantic Ocean
author Brotas, Vanda
author_facet Brotas, Vanda
Brewin, Robert J.W.
Sá, Carolina
Brito, Ana C.
Silva, Alexandra
Mendes, Carlos Rafael
Diniz, Tânia
Kaufmann, Manfred
Tarran, Glen
Groom, Steve B.
Platt, Trevor
Sathyendranath, Shubha
author_role author
author2 Brewin, Robert J.W.
Sá, Carolina
Brito, Ana C.
Silva, Alexandra
Mendes, Carlos Rafael
Diniz, Tânia
Kaufmann, Manfred
Tarran, Glen
Groom, Steve B.
Platt, Trevor
Sathyendranath, Shubha
author2_role author
author
author
author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv DigitUMa
dc.contributor.author.fl_str_mv Brotas, Vanda
Brewin, Robert J.W.
Sá, Carolina
Brito, Ana C.
Silva, Alexandra
Mendes, Carlos Rafael
Diniz, Tânia
Kaufmann, Manfred
Tarran, Glen
Groom, Steve B.
Platt, Trevor
Sathyendranath, Shubha
dc.subject.por.fl_str_mv Phytoplankton
Cell-size structure and abundance
Remotely-sensed chlorophyll-a
Intracellular chlorophyll-a content per size class
Eastern North Atlantic
.
Faculdade de Ciências da Vida
topic Phytoplankton
Cell-size structure and abundance
Remotely-sensed chlorophyll-a
Intracellular chlorophyll-a content per size class
Eastern North Atlantic
.
Faculdade de Ciências da Vida
description In recent years, the global distribution of phytoplankton functional types (PFT) and phytoplankton size classes (PSC) has been determined by remote sensing. Many of these methods rely on interpretation of phytoplankton size or type from pigment data, but independent validation has been difficult due to lack of appropriate in situ data on cell size. This work uses in situ data (photosynthetic pigments concentration and cell abundances) from the north-east Atlantic, along a trophic gradient, sampled from 2005 to 2010, as well as Atlantic Meridional Transect (AMT) data for the same region, to test a previously developed conceptual model, which calculates the fractional contributions of pico-, nano- and micro-plankton to total phytoplankton chlorophyll biomass (Brewin et al., 2010). The application of the model proved to be successful, as shown by low mean absolute error between data and model fit. However, regional values obtained for the model parameters had some effect on the relative distribution of size classes as a function of chlorophyll-a, compared with the results according to the original model. The regional parameterisation yielded a dominance of micro-plankton contribution for chlorophyll-a concentrations greater than 0.5 mg m−3 , rather than from 1.3 mg m−3 in the original model. Intracellular chlorophyll-a (Chla) per cell, for each size class, was computed from the cell enumeration results (microscope counts and flow cytometry) and the chlorophyll-a concentration for that size class given by the model. The median intracellular chlorophyll-a values computed were 0.004, 0.224 and 26.78 pg Chla cell−1 for pico-, nano-, and micro-plankton respectively. This is generally consistent with the literature, thereby providing an indirect validation of the method based on pigments to assign size classes. Using a satellite-derived composite image of chlorophyll-a for the study area, a map of cell abundance was generated based on the computed intracellular chlorophyll-a for each size-class, thus extending the remote-sensing method for mapping size classes of phytoplankton from chlorophyll-a concentration to mapping cell numbers in each class. The map reveals the ubiquitous presence of pico-plankton, and shows that all size classes are more abundant in more productive areas.
publishDate 2013
dc.date.none.fl_str_mv 2013-01-01T00:00:00Z
2013-01-01T00:00:00Z
2021-10-07T07:59:48Z
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/10400.13/3703
url http://hdl.handle.net/10400.13/3703
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Brotas, V., Brewin, R. J., Sá, C., Brito, A. C., Silva, A., Mendes, C. R., ... & Sathyendranath, S. (2013). Deriving phytoplankton size classes from satellite data: validation along a trophic gradient in the eastern Atlantic Ocean. Remote Sensing of Environment, 134, 66-77. https://doi.org/10.1016/j.rse.2013.02.013
10.1016/j.rse.2013.02.013
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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