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Obtaining phytoplankton diversity from ocean color: a scientific roadmap for future development

Obtaining phytoplankton diversity from ocean color: a scientific roadmap for future development
Obtaining phytoplankton diversity from ocean color: a scientific roadmap for future development
To improve our understanding of the role of phytoplankton for marine ecosystems and global biogeochemical cycles, information on the global distribution of major phytoplankton groups is essential. Although algorithms have been developed to assess phytoplankton diversity from space for over two decades, so far the application of these data sets has been limited. This scientific roadmap identifies user needs, summarizes the current state of the art, and pinpoints major gaps in long-term objectives to deliver space-derived phytoplankton diversity data that meets the user requirements. These major gaps in using ocean color to estimate phytoplankton community structure were identified as: (a) the mismatch between satellite, in situ and model data on phytoplankton composition, (b) the lack of quantitative uncertainty estimates provided with satellite data, (c) the spectral limitation of current sensors to enable the full exploitation of backscattered sunlight, and (d) the very limited applicability of satellite algorithms determining phytoplankton composition for regional, especially coastal or inland, waters. Recommendation for actions include but are not limited to: (i) an increased communication and round-robin exercises among and within the related expert groups, (ii) the launching of higher spectrally and spatially resolved sensors, (iii) the development of algorithms that exploit hyperspectral information, and of (iv) techniques to merge and synergistically use the various streams of continuous information on phytoplankton diversity from various satellite sensors' and in situ data to ensure long-term monitoring of phytoplankton composition.
2296-7745
Bracher, Astrid
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Bouman, Heather A.
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Brewin, Robert J.W.
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Bricaud, Annick
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Brotas, Vanda
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Ciotti, Aurea M.
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Clementson, Lesley
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Devred, Emmanuel
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Di Cicco, Annalisa
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Dutkiewicz, Stephanie
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Harman-Mountford, Nick J.
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Hickman, Anna E.
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Heironymi, Martin
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Hirata, Takafumi
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Losa, Svetlana N.
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Mouw, Colleen B
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Organelli, Emanuele
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Riatsos, Dionysos E.
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Uitz, Julia
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Vogt, Meike
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Wolanin, Aleksanra
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Bracher, Astrid
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Bouman, Heather A.
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Brewin, Robert J.W.
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Bricaud, Annick
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Brotas, Vanda
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Ciotti, Aurea M.
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Clementson, Lesley
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Devred, Emmanuel
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Di Cicco, Annalisa
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Dutkiewicz, Stephanie
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Harman-Mountford, Nick J.
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Hickman, Anna E.
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Heironymi, Martin
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Hirata, Takafumi
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Losa, Svetlana N.
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Mouw, Colleen B
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Organelli, Emanuele
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Riatsos, Dionysos E.
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Uitz, Julia
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Vogt, Meike
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Wolanin, Aleksanra
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Bracher, Astrid, Bouman, Heather A., Brewin, Robert J.W., Bricaud, Annick, Brotas, Vanda, Ciotti, Aurea M., Clementson, Lesley, Devred, Emmanuel, Di Cicco, Annalisa, Dutkiewicz, Stephanie, Harman-Mountford, Nick J., Hickman, Anna E., Heironymi, Martin, Hirata, Takafumi, Losa, Svetlana N., Mouw, Colleen B, Organelli, Emanuele, Riatsos, Dionysos E., Uitz, Julia, Vogt, Meike and Wolanin, Aleksanra (2017) Obtaining phytoplankton diversity from ocean color: a scientific roadmap for future development. Frontiers in Marine Science, 4. (doi:10.3389/fmars.2017.00055/full).

Record type: Article

Abstract

To improve our understanding of the role of phytoplankton for marine ecosystems and global biogeochemical cycles, information on the global distribution of major phytoplankton groups is essential. Although algorithms have been developed to assess phytoplankton diversity from space for over two decades, so far the application of these data sets has been limited. This scientific roadmap identifies user needs, summarizes the current state of the art, and pinpoints major gaps in long-term objectives to deliver space-derived phytoplankton diversity data that meets the user requirements. These major gaps in using ocean color to estimate phytoplankton community structure were identified as: (a) the mismatch between satellite, in situ and model data on phytoplankton composition, (b) the lack of quantitative uncertainty estimates provided with satellite data, (c) the spectral limitation of current sensors to enable the full exploitation of backscattered sunlight, and (d) the very limited applicability of satellite algorithms determining phytoplankton composition for regional, especially coastal or inland, waters. Recommendation for actions include but are not limited to: (i) an increased communication and round-robin exercises among and within the related expert groups, (ii) the launching of higher spectrally and spatially resolved sensors, (iii) the development of algorithms that exploit hyperspectral information, and of (iv) techniques to merge and synergistically use the various streams of continuous information on phytoplankton diversity from various satellite sensors' and in situ data to ensure long-term monitoring of phytoplankton composition.

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fmars-04-00055 - Version of Record
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Accepted/In Press date: 15 February 2017
Published date: 3 March 2017
Organisations: Ocean and Earth Science, Marine Biogeochemistry

Identifiers

Local EPrints ID: 411656
URI: https://eprints.soton.ac.uk/id/eprint/411656
ISSN: 2296-7745
PURE UUID: 4c7c5f50-0712-4b7b-a65b-8c2681d4cff8
ORCID for Anna E. Hickman: ORCID iD orcid.org/0000-0002-2774-3934

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Date deposited: 21 Jun 2017 16:33
Last modified: 10 Dec 2019 01:37

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Contributors

Author: Astrid Bracher
Author: Heather A. Bouman
Author: Robert J.W. Brewin
Author: Annick Bricaud
Author: Vanda Brotas
Author: Aurea M. Ciotti
Author: Lesley Clementson
Author: Emmanuel Devred
Author: Annalisa Di Cicco
Author: Stephanie Dutkiewicz
Author: Nick J. Harman-Mountford
Author: Anna E. Hickman ORCID iD
Author: Martin Heironymi
Author: Takafumi Hirata
Author: Svetlana N. Losa
Author: Colleen B Mouw
Author: Emanuele Organelli
Author: Dionysos E. Riatsos
Author: Julia Uitz
Author: Meike Vogt
Author: Aleksanra Wolanin

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