Estimation of the Potential Detection of Diatom Assemblages Based on Ocean Color Radiance Anomalies in the North Sea
Over the past years, a large number of new approaches in the domain of ocean-color have been developed, leading to a variety of innovative descriptors for phytoplankton communities. One of these methods, named PHYSAT, currently allows for the qualitative detection of five main phytoplankton groups f...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2017-12-01
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| Series: | Frontiers in Marine Science |
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| Online Access: | http://journal.frontiersin.org/article/10.3389/fmars.2017.00408/full |
| _version_ | 1828378042224869376 |
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| author | Anne-Hélène Rêve-Lamarche Séverine Alvain Marie-Fanny Racault David Dessailly Natacha Guiselin Cédric Jamet Vincent Vantrepotte Grégory Beaugrand |
| author_facet | Anne-Hélène Rêve-Lamarche Séverine Alvain Marie-Fanny Racault David Dessailly Natacha Guiselin Cédric Jamet Vincent Vantrepotte Grégory Beaugrand |
| author_sort | Anne-Hélène Rêve-Lamarche |
| collection | DOAJ |
| description | Over the past years, a large number of new approaches in the domain of ocean-color have been developed, leading to a variety of innovative descriptors for phytoplankton communities. One of these methods, named PHYSAT, currently allows for the qualitative detection of five main phytoplankton groups from ocean-color measurements. Even though PHYSAT products are widely used in various applications and projects, the approach is limited by the fact it identifies only dominant phytoplankton groups. This current limitation is due to the use of biomarker pigment ratios for establishing empirical relationships between in-situ information and specific ocean-color radiance anomalies in open ocean waters. However, theoretical explanations of PHYSAT suggests that it could be possible to detect more than dominance cases but move more toward phytoplanktonic assemblage detection. Thus, to evaluate the potential of PHYSAT for the detection of phytoplankton assemblages, we took advantage of the Continuous Plankton Recorder (CPR) survey, collected in both the English Channel and the North Sea. The available CPR dataset contains information on diatom abundance in two large areas of the North Sea for the period 1998-2010. Using this unique dataset, recurrent diatom assemblages were retrieved based on classification of CPR samples. Six diatom assemblages were identified in-situ, each having indicators taxa or species. Once this first step was completed, the in-situ analysis was used to empirically associate the diatom assemblages with specific PHYSAT spectral anomalies. This step was facilitated by the use of previous classifications of regional radiance anomalies in terms of shape and amplitude, coupled with phenological tools. Through a matchup exercise, three CPR assemblages were associated with specific radiance anomalies. The maps of detection of these specific radiances anomalies are in close agreement with current in-situ ecological knowledge. |
| first_indexed | 2024-04-14T08:19:59Z |
| format | Article |
| id | doaj.art-3cd2f8fa94554f548ddde86eac0ef16e |
| institution | Directory Open Access Journal |
| issn | 2296-7745 |
| language | English |
| last_indexed | 2024-04-14T08:19:59Z |
| publishDate | 2017-12-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Marine Science |
| spelling | doaj.art-3cd2f8fa94554f548ddde86eac0ef16e2022-12-22T02:04:14ZengFrontiers Media S.A.Frontiers in Marine Science2296-77452017-12-01410.3389/fmars.2017.00408299845Estimation of the Potential Detection of Diatom Assemblages Based on Ocean Color Radiance Anomalies in the North SeaAnne-Hélène Rêve-Lamarche0Séverine Alvain1Marie-Fanny Racault2David Dessailly3Natacha Guiselin4Cédric Jamet5Vincent Vantrepotte6Grégory Beaugrand7CNRS, Univ. Lille, Univ. Littoral Côte d'Opale, UMR 8187, LOG, Laboratoire d'Océanologie et de Géosciences, Lille, FranceCNRS, Univ. Lille, Univ. Littoral Côte d'Opale, UMR 8187, LOG, Laboratoire d'Océanologie et de Géosciences, Lille, FrancePlymouth Marine Laboratory, Plymouth, United KingdomUniv. Littoral Côte d'Opale, Univ. Lille, CNRS, UMR 8187, LOG, Laboratoire d'Océanologie et de Géosciences, Wimereux, FranceUniv. Littoral Côte d'Opale, Univ. Lille, CNRS, UMR 8187, LOG, Laboratoire d'Océanologie et de Géosciences, Wimereux, FranceUniv. Littoral Côte d'Opale, Univ. Lille, CNRS, UMR 8187, LOG, Laboratoire d'Océanologie et de Géosciences, Wimereux, FranceCNRS, Univ. Lille, Univ. Littoral Côte d'Opale, UMR 8187, LOG, Laboratoire d'Océanologie et de Géosciences, Wimereux, FranceCNRS, Univ. Lille, Univ. Littoral Côte d'Opale, UMR 8187, LOG, Laboratoire d'Océanologie et de Géosciences, Wimereux, FranceOver the past years, a large number of new approaches in the domain of ocean-color have been developed, leading to a variety of innovative descriptors for phytoplankton communities. One of these methods, named PHYSAT, currently allows for the qualitative detection of five main phytoplankton groups from ocean-color measurements. Even though PHYSAT products are widely used in various applications and projects, the approach is limited by the fact it identifies only dominant phytoplankton groups. This current limitation is due to the use of biomarker pigment ratios for establishing empirical relationships between in-situ information and specific ocean-color radiance anomalies in open ocean waters. However, theoretical explanations of PHYSAT suggests that it could be possible to detect more than dominance cases but move more toward phytoplanktonic assemblage detection. Thus, to evaluate the potential of PHYSAT for the detection of phytoplankton assemblages, we took advantage of the Continuous Plankton Recorder (CPR) survey, collected in both the English Channel and the North Sea. The available CPR dataset contains information on diatom abundance in two large areas of the North Sea for the period 1998-2010. Using this unique dataset, recurrent diatom assemblages were retrieved based on classification of CPR samples. Six diatom assemblages were identified in-situ, each having indicators taxa or species. Once this first step was completed, the in-situ analysis was used to empirically associate the diatom assemblages with specific PHYSAT spectral anomalies. This step was facilitated by the use of previous classifications of regional radiance anomalies in terms of shape and amplitude, coupled with phenological tools. Through a matchup exercise, three CPR assemblages were associated with specific radiance anomalies. The maps of detection of these specific radiances anomalies are in close agreement with current in-situ ecological knowledge.http://journal.frontiersin.org/article/10.3389/fmars.2017.00408/fullocean-colordiatom assemblagesNorth SeaCPRPHYSAT |
| spellingShingle | Anne-Hélène Rêve-Lamarche Séverine Alvain Marie-Fanny Racault David Dessailly Natacha Guiselin Cédric Jamet Vincent Vantrepotte Grégory Beaugrand Estimation of the Potential Detection of Diatom Assemblages Based on Ocean Color Radiance Anomalies in the North Sea Frontiers in Marine Science ocean-color diatom assemblages North Sea CPR PHYSAT |
| title | Estimation of the Potential Detection of Diatom Assemblages Based on Ocean Color Radiance Anomalies in the North Sea |
| title_full | Estimation of the Potential Detection of Diatom Assemblages Based on Ocean Color Radiance Anomalies in the North Sea |
| title_fullStr | Estimation of the Potential Detection of Diatom Assemblages Based on Ocean Color Radiance Anomalies in the North Sea |
| title_full_unstemmed | Estimation of the Potential Detection of Diatom Assemblages Based on Ocean Color Radiance Anomalies in the North Sea |
| title_short | Estimation of the Potential Detection of Diatom Assemblages Based on Ocean Color Radiance Anomalies in the North Sea |
| title_sort | estimation of the potential detection of diatom assemblages based on ocean color radiance anomalies in the north sea |
| topic | ocean-color diatom assemblages North Sea CPR PHYSAT |
| url | http://journal.frontiersin.org/article/10.3389/fmars.2017.00408/full |
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