Concentration and distribution of phytoplankton nitrogen and carbon in the Northwest Atlantic and Indian Ocean: A simple model with applications in satellite remote sensing
Despite the critical role phytoplankton play in marine biogeochemical cycles, direct methods for determining the content of two key elements in natural phytoplankton samples, nitrogen (N) and carbon (C), remain difficult, and such observations are sparse. Here, we extend an existing approach to deri...
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ftdoajarticles:oai:doaj.org/article:baed4083d97a49b087141be486adf9b1 2023-05-15T17:45:35+02:00 Concentration and distribution of phytoplankton nitrogen and carbon in the Northwest Atlantic and Indian Ocean: A simple model with applications in satellite remote sensing Giuseppe Maniaci Robert J. W. Brewin Shubha Sathyendranath 2022-11-01T00:00:00Z https://doi.org/10.3389/fmars.2022.1035399 https://doaj.org/article/baed4083d97a49b087141be486adf9b1 EN eng Frontiers Media S.A. https://www.frontiersin.org/articles/10.3389/fmars.2022.1035399/full https://doaj.org/toc/2296-7745 2296-7745 doi:10.3389/fmars.2022.1035399 https://doaj.org/article/baed4083d97a49b087141be486adf9b1 Frontiers in Marine Science, Vol 9 (2022) nitrogen carbon chlorophyll-a Redfield phytoplankton satellite Science Q General. Including nature conservation geographical distribution QH1-199.5 article 2022 ftdoajarticles https://doi.org/10.3389/fmars.2022.1035399 2022-12-30T19:39:55Z Despite the critical role phytoplankton play in marine biogeochemical cycles, direct methods for determining the content of two key elements in natural phytoplankton samples, nitrogen (N) and carbon (C), remain difficult, and such observations are sparse. Here, we extend an existing approach to derive phytoplankton N and C indirectly from a large dataset of in-situ particulate N and C, and Turner fluorometric chlorophyll-a (Chl-a), gathered in the off-shore waters of the Northwest Atlantic and the Arabian Sea. This method uses quantile regression (QR) to partition particulate C and N into autotrophic and non-autotrophic fractions. Both the phytoplankton C and N estimates were combined to compute the C:N ratio. The algal contributions to total N and C increased with increasing Chl-a, whilst the C:N ratio decreased with increasing Chl-a. However, the C:N ratio remained close to the Redfield ratio over the entire Chl-a range. Five different phytoplankton taxa within the samples were identified using data from high-performance liquid chromatography pigment analysis. All algal groups had a C:N ratio higher than Redfield, but for diatoms, the ratio was closer to the Redfield ratio, whereas for Prochlorococcus, other cyanobacteria and green algae, the ratio was significantly higher. The model was applied to remotely-sensed estimates of Chl-a to map the geographical distribution of phytoplankton C, N, and C:N in the two regions from where the data were acquired. Estimates of phytoplankton C and N were found to be consistent with literature values, indirectly validating the approach. The work illustrates how a simple model can be used to derive information on the phytoplankton elemental composition, and be applied to remote sensing data, to map pools of elements like nitrogen, not currently provided by satellite services. Article in Journal/Newspaper Northwest Atlantic Directory of Open Access Journals: DOAJ Articles Indian Frontiers in Marine Science 9 |
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Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
nitrogen carbon chlorophyll-a Redfield phytoplankton satellite Science Q General. Including nature conservation geographical distribution QH1-199.5 |
spellingShingle |
nitrogen carbon chlorophyll-a Redfield phytoplankton satellite Science Q General. Including nature conservation geographical distribution QH1-199.5 Giuseppe Maniaci Robert J. W. Brewin Shubha Sathyendranath Concentration and distribution of phytoplankton nitrogen and carbon in the Northwest Atlantic and Indian Ocean: A simple model with applications in satellite remote sensing |
topic_facet |
nitrogen carbon chlorophyll-a Redfield phytoplankton satellite Science Q General. Including nature conservation geographical distribution QH1-199.5 |
description |
Despite the critical role phytoplankton play in marine biogeochemical cycles, direct methods for determining the content of two key elements in natural phytoplankton samples, nitrogen (N) and carbon (C), remain difficult, and such observations are sparse. Here, we extend an existing approach to derive phytoplankton N and C indirectly from a large dataset of in-situ particulate N and C, and Turner fluorometric chlorophyll-a (Chl-a), gathered in the off-shore waters of the Northwest Atlantic and the Arabian Sea. This method uses quantile regression (QR) to partition particulate C and N into autotrophic and non-autotrophic fractions. Both the phytoplankton C and N estimates were combined to compute the C:N ratio. The algal contributions to total N and C increased with increasing Chl-a, whilst the C:N ratio decreased with increasing Chl-a. However, the C:N ratio remained close to the Redfield ratio over the entire Chl-a range. Five different phytoplankton taxa within the samples were identified using data from high-performance liquid chromatography pigment analysis. All algal groups had a C:N ratio higher than Redfield, but for diatoms, the ratio was closer to the Redfield ratio, whereas for Prochlorococcus, other cyanobacteria and green algae, the ratio was significantly higher. The model was applied to remotely-sensed estimates of Chl-a to map the geographical distribution of phytoplankton C, N, and C:N in the two regions from where the data were acquired. Estimates of phytoplankton C and N were found to be consistent with literature values, indirectly validating the approach. The work illustrates how a simple model can be used to derive information on the phytoplankton elemental composition, and be applied to remote sensing data, to map pools of elements like nitrogen, not currently provided by satellite services. |
format |
Article in Journal/Newspaper |
author |
Giuseppe Maniaci Robert J. W. Brewin Shubha Sathyendranath |
author_facet |
Giuseppe Maniaci Robert J. W. Brewin Shubha Sathyendranath |
author_sort |
Giuseppe Maniaci |
title |
Concentration and distribution of phytoplankton nitrogen and carbon in the Northwest Atlantic and Indian Ocean: A simple model with applications in satellite remote sensing |
title_short |
Concentration and distribution of phytoplankton nitrogen and carbon in the Northwest Atlantic and Indian Ocean: A simple model with applications in satellite remote sensing |
title_full |
Concentration and distribution of phytoplankton nitrogen and carbon in the Northwest Atlantic and Indian Ocean: A simple model with applications in satellite remote sensing |
title_fullStr |
Concentration and distribution of phytoplankton nitrogen and carbon in the Northwest Atlantic and Indian Ocean: A simple model with applications in satellite remote sensing |
title_full_unstemmed |
Concentration and distribution of phytoplankton nitrogen and carbon in the Northwest Atlantic and Indian Ocean: A simple model with applications in satellite remote sensing |
title_sort |
concentration and distribution of phytoplankton nitrogen and carbon in the northwest atlantic and indian ocean: a simple model with applications in satellite remote sensing |
publisher |
Frontiers Media S.A. |
publishDate |
2022 |
url |
https://doi.org/10.3389/fmars.2022.1035399 https://doaj.org/article/baed4083d97a49b087141be486adf9b1 |
geographic |
Indian |
geographic_facet |
Indian |
genre |
Northwest Atlantic |
genre_facet |
Northwest Atlantic |
op_source |
Frontiers in Marine Science, Vol 9 (2022) |
op_relation |
https://www.frontiersin.org/articles/10.3389/fmars.2022.1035399/full https://doaj.org/toc/2296-7745 2296-7745 doi:10.3389/fmars.2022.1035399 https://doaj.org/article/baed4083d97a49b087141be486adf9b1 |
op_doi |
https://doi.org/10.3389/fmars.2022.1035399 |
container_title |
Frontiers in Marine Science |
container_volume |
9 |
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1766148712123334656 |