Articles | Volume 20, issue 1
https://doi.org/10.5194/os-20-217-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/os-20-217-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Linking satellites to genes with machine learning to estimate phytoplankton community structure from space
Roy El Hourany
CORRESPONDING AUTHOR
Univ. Littoral Côte d’Opale, Univ. Lille, CNRS, IRD, UMR 8187, LOG, Laboratoire d’Océanologie et de Géosciences, 62930 Wimereux, France
Juan Pierella Karlusich
Institut de Biologie de l'Ecole Normale Supérieure (IBENS), Ecole Normale Supérieure, CNRS, INSERM, Université PSL, 75005 Paris, France
FAS Division of Science, Harvard University, Cambridge, MA, USA
Research Federation for the study of Global Ocean Systems Ecology and Evolution, FR2022/Tara GOSEE, 75016 Paris, France
Lucie Zinger
Institut de Biologie de l'Ecole Normale Supérieure (IBENS), Ecole Normale Supérieure, CNRS, INSERM, Université PSL, 75005 Paris, France
Research Federation for the study of Global Ocean Systems Ecology and Evolution, FR2022/Tara GOSEE, 75016 Paris, France
Naturalis Biodiversity Center, 2300 RA Leiden, the Netherlands
Hubert Loisel
Univ. Littoral Côte d’Opale, Univ. Lille, CNRS, IRD, UMR 8187, LOG, Laboratoire d’Océanologie et de Géosciences, 62930 Wimereux, France
Sorbonne Université, LOCEAN-IPSL, Laboratoire d'Océanographie et du Climat; Expérimentations et Approches Numériques, CNRS, IRD, MNHN, 75005 Paris, France
Chris Bowler
CORRESPONDING AUTHOR
Institut de Biologie de l'Ecole Normale Supérieure (IBENS), Ecole Normale Supérieure, CNRS, INSERM, Université PSL, 75005 Paris, France
Research Federation for the study of Global Ocean Systems Ecology and Evolution, FR2022/Tara GOSEE, 75016 Paris, France
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Georges Baaklini, Julien Brajard, Leila Issa, Gina Fifani, Laurent Mortier, and Roy El Hourany
Ocean Sci., 20, 1707–1720, https://doi.org/10.5194/os-20-1707-2024, https://doi.org/10.5194/os-20-1707-2024, 2024
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Understanding the flow of the Levantine Sea surface current is not straightforward. We propose a study based on learning techniques to follow interactions between water near the shore and further out at sea. Our results show changes in the coastal currents past 33.8° E, with frequent instances of water breaking away along the Lebanese coast. These events happen quickly and sometimes lead to long-lasting eddies. This study underscores the need for direct observations to improve our knowledge.
Stéphane Doléac, Marina Lévy, Roy El Hourany, and Laurent Bopp
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Georges Baaklini, Roy El Hourany, Milad Fakhri, Julien Brajard, Leila Issa, Gina Fifani, and Laurent Mortier
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We use machine learning to analyze the long-term variation of the surface currents in the Levantine Sea, located in the eastern Mediterranean Sea. We decompose the circulation into groups based on their physical characteristics and analyze their spatial and temporal variability. We show that most structures of the Levantine Sea are becoming more energetic over time, despite those of the western area remaining the most dominant due to their complex bathymetry and strong currents.
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The paper is a contribution to the study of phytoplankton pigment climatology from satellite ocean-color observations in the Senegalo–Mauritanian upwelling, which is a very productive region where in situ observations are lacking. We processed the satellite data with an efficient new neural network classifier. We were able to provide the climatological cycle of diatoms. This study may have an economic impact on fisheries thanks to better knowledge of phytoplankton dynamics.
Georges Baaklini, Julien Brajard, Leila Issa, Gina Fifani, Laurent Mortier, and Roy El Hourany
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Understanding the flow of the Levantine Sea surface current is not straightforward. We propose a study based on learning techniques to follow interactions between water near the shore and further out at sea. Our results show changes in the coastal currents past 33.8° E, with frequent instances of water breaking away along the Lebanese coast. These events happen quickly and sometimes lead to long-lasting eddies. This study underscores the need for direct observations to improve our knowledge.
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Biogeosciences, 20, 3273–3299, https://doi.org/10.5194/bg-20-3273-2023, https://doi.org/10.5194/bg-20-3273-2023, 2023
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Saeed Hariri, Sabrina Speich, Bruno Blanke, and Marina Lévy
Ocean Sci., 19, 1183–1201, https://doi.org/10.5194/os-19-1183-2023, https://doi.org/10.5194/os-19-1183-2023, 2023
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Tihomir S. Kostadinov, Lisl Robertson Lain, Christina Eunjin Kong, Xiaodong Zhang, Stéphane Maritorena, Stewart Bernard, Hubert Loisel, Daniel S. F. Jorge, Ekaterina Kochetkova, Shovonlal Roy, Bror Jonsson, Victor Martinez-Vicente, and Shubha Sathyendranath
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A compiled set of in situ data is vital to evaluate the quality of ocean-colour satellite data records. Here we describe the global compilation of bio-optical in situ data (spanning from 1997 to 2021) used for the validation of the ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI). The compilation merges and harmonizes several in situ data sources into a simple format that could be used directly for the evaluation of satellite-derived ocean-colour data.
Georges Baaklini, Roy El Hourany, Milad Fakhri, Julien Brajard, Leila Issa, Gina Fifani, and Laurent Mortier
Ocean Sci., 18, 1491–1505, https://doi.org/10.5194/os-18-1491-2022, https://doi.org/10.5194/os-18-1491-2022, 2022
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We use machine learning to analyze the long-term variation of the surface currents in the Levantine Sea, located in the eastern Mediterranean Sea. We decompose the circulation into groups based on their physical characteristics and analyze their spatial and temporal variability. We show that most structures of the Levantine Sea are becoming more energetic over time, despite those of the western area remaining the most dominant due to their complex bathymetry and strong currents.
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Alain de Verneil, Zouhair Lachkar, Shafer Smith, and Marina Lévy
Biogeosciences, 19, 907–929, https://doi.org/10.5194/bg-19-907-2022, https://doi.org/10.5194/bg-19-907-2022, 2022
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Zouhair Lachkar, Michael Mehari, Muchamad Al Azhar, Marina Lévy, and Shafer Smith
Biogeosciences, 18, 5831–5849, https://doi.org/10.5194/bg-18-5831-2021, https://doi.org/10.5194/bg-18-5831-2021, 2021
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This study documents and quantifies a significant recent oxygen decline in the upper layers of the Arabian Sea and explores its drivers. Using a modeling approach we show that the fast local warming of sea surface is the main factor causing this oxygen drop. Concomitant summer monsoon intensification contributes to this trend, although to a lesser extent. These changes exacerbate oxygen depletion in the subsurface, threatening marine habitats and altering the local biogeochemistry.
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Biogeosciences, 18, 4321–4349, https://doi.org/10.5194/bg-18-4321-2021, https://doi.org/10.5194/bg-18-4321-2021, 2021
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An alarming consequence of climate change is the oceanic primary production decline projected by Earth system models. These coarse-resolution models parameterize oceanic eddies. Here, idealized simulations of global warming with increasing resolution show that the decline in primary production in the eddy-resolved simulations is half as large as in the eddy-parameterized simulations. This stems from the high sensitivity of the subsurface nutrient transport to model resolution.
Clément Bricaud, Julien Le Sommer, Gurvan Madec, Christophe Calone, Julie Deshayes, Christian Ethe, Jérôme Chanut, and Marina Levy
Geosci. Model Dev., 13, 5465–5483, https://doi.org/10.5194/gmd-13-5465-2020, https://doi.org/10.5194/gmd-13-5465-2020, 2020
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In order to reduce the cost of ocean biogeochemical models, a multi-grid approach where ocean dynamics and tracer transport are computed with different spatial resolution has been developed in the NEMO v3.6 OGCM. Different experiments confirm that the spatial resolution of hydrodynamical fields can be coarsened without significantly affecting the resolved passive tracer fields. This approach leads to a factor of 7 reduction of the overhead associated with running a full biogeochemical model.
Khalil Yala, N'Dèye Niang, Julien Brajard, Carlos Mejia, Mory Ouattara, Roy El Hourany, Michel Crépon, and Sylvie Thiria
Ocean Sci., 16, 513–533, https://doi.org/10.5194/os-16-513-2020, https://doi.org/10.5194/os-16-513-2020, 2020
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The paper is a contribution to the study of phytoplankton pigment climatology from satellite ocean-color observations in the Senegalo–Mauritanian upwelling, which is a very productive region where in situ observations are lacking. We processed the satellite data with an efficient new neural network classifier. We were able to provide the climatological cycle of diatoms. This study may have an economic impact on fisheries thanks to better knowledge of phytoplankton dynamics.
André Valente, Shubha Sathyendranath, Vanda Brotas, Steve Groom, Michael Grant, Malcolm Taberner, David Antoine, Robert Arnone, William M. Balch, Kathryn Barker, Ray Barlow, Simon Bélanger, Jean-François Berthon, Şükrü Beşiktepe, Yngve Borsheim, Astrid Bracher, Vittorio Brando, Elisabetta Canuti, Francisco Chavez, Andrés Cianca, Hervé Claustre, Lesley Clementson, Richard Crout, Robert Frouin, Carlos García-Soto, Stuart W. Gibb, Richard Gould, Stanford B. Hooker, Mati Kahru, Milton Kampel, Holger Klein, Susanne Kratzer, Raphael Kudela, Jesus Ledesma, Hubert Loisel, Patricia Matrai, David McKee, Brian G. Mitchell, Tiffany Moisan, Frank Muller-Karger, Leonie O'Dowd, Michael Ondrusek, Trevor Platt, Alex J. Poulton, Michel Repecaud, Thomas Schroeder, Timothy Smyth, Denise Smythe-Wright, Heidi M. Sosik, Michael Twardowski, Vincenzo Vellucci, Kenneth Voss, Jeremy Werdell, Marcel Wernand, Simon Wright, and Giuseppe Zibordi
Earth Syst. Sci. Data, 11, 1037–1068, https://doi.org/10.5194/essd-11-1037-2019, https://doi.org/10.5194/essd-11-1037-2019, 2019
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A compiled set of in situ data is useful to evaluate the quality of ocean-colour satellite data records. Here we describe the compilation of global bio-optical in situ data (spanning from 1997 to 2018) used for the validation of the ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI). The compilation merges and harmonizes several in situ data sources into a simple format that could be used directly for the evaluation of satellite-derived ocean-colour data.
Zouhair Lachkar, Marina Lévy, and Shafer Smith
Biogeosciences, 15, 159–186, https://doi.org/10.5194/bg-15-159-2018, https://doi.org/10.5194/bg-15-159-2018, 2018
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This study provides a new contribution to our understanding of the coupling between the oxygen minimum zones (OMZs) and climate. It explores how idealized changes in summer and winter Indian monsoon winds affect the productivity of the Arabian Sea and the size and intensity of its OMZ. We find that intensification of Indian monsoon winds can amplify climate warming on decadal to centennial timescales.
Madhavan Girijakumari Keerthi, Matthieu Lengaigne, Marina Levy, Jerome Vialard, Vallivattathillam Parvathi, Clément de Boyer Montégut, Christian Ethé, Olivier Aumont, Iyyappan Suresh, Valiya Parambil Akhil, and Pillathu Moolayil Muraleedharan
Biogeosciences, 14, 3615–3632, https://doi.org/10.5194/bg-14-3615-2017, https://doi.org/10.5194/bg-14-3615-2017, 2017
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The northern Arabian Sea hosts a winter chlorophyll bloom, which exhibits strong interannual variability. The processes responsible for this interannual variation of the bloom are investigated using observations and a model. The interannual fluctuations of the winter bloom are largely related to the interannual mixed-layer depth (MLD) anomalies, which are driven by net heat flux anomalies. MLD controls the bloom amplitude through a modulation of nutrient turbulent fluxes into the mixed layer.
Parvathi Vallivattathillam, Suresh Iyyappan, Matthieu Lengaigne, Christian Ethé, Jérôme Vialard, Marina Levy, Neetu Suresh, Olivier Aumont, Laure Resplandy, Hema Naik, and Wajih Naqvi
Biogeosciences, 14, 1541–1559, https://doi.org/10.5194/bg-14-1541-2017, https://doi.org/10.5194/bg-14-1541-2017, 2017
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During late boreal summer and fall, the west coast of India (WCI) experiences hypoxia, which turns into anoxia during some years. We analyze a coupled physical–biogeochemical simulation over the 1960–2012 period to investigate the physical processes influencing oxycline interannual variability off the WCI. We show that fall WCI oxycline fluctuations are strongly related to Indian Ocean Dipole (IOD), with positive IODs preventing anoxia, while negative IODs do not necessarily result in anoxia.
André Valente, Shubha Sathyendranath, Vanda Brotas, Steve Groom, Michael Grant, Malcolm Taberner, David Antoine, Robert Arnone, William M. Balch, Kathryn Barker, Ray Barlow, Simon Bélanger, Jean-François Berthon, Şükrü Beşiktepe, Vittorio Brando, Elisabetta Canuti, Francisco Chavez, Hervé Claustre, Richard Crout, Robert Frouin, Carlos García-Soto, Stuart W. Gibb, Richard Gould, Stanford Hooker, Mati Kahru, Holger Klein, Susanne Kratzer, Hubert Loisel, David McKee, Brian G. Mitchell, Tiffany Moisan, Frank Muller-Karger, Leonie O'Dowd, Michael Ondrusek, Alex J. Poulton, Michel Repecaud, Timothy Smyth, Heidi M. Sosik, Michael Twardowski, Kenneth Voss, Jeremy Werdell, Marcel Wernand, and Giuseppe Zibordi
Earth Syst. Sci. Data, 8, 235–252, https://doi.org/10.5194/essd-8-235-2016, https://doi.org/10.5194/essd-8-235-2016, 2016
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A compiled set of in situ data is important to evaluate the quality of ocean-colour satellite data records. Here we describe the compilation of global bio-optical in situ data (spanning from 1997 to 2012) used for the validation of the ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI). The compilation merges and harmonizes several in situ data sources into a simple format that could be used directly for the evaluation of satellite-derived ocean-colour data.
P. R. Renosh, F. G. Schmitt, and H. Loisel
Nonlin. Processes Geophys., 22, 633–643, https://doi.org/10.5194/npg-22-633-2015, https://doi.org/10.5194/npg-22-633-2015, 2015
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Intermittent dynamics of particle size distribution in coastal waters is studied. Particle sizes are separated into four size classes: silt, fine, coarse and macro particles. The time series of each size class is derived, and their multiscaling properties studied. Similar analysis has been done for suspended particulate matter and total volume concentration. All quantities display a nonlinear moment function and a negative Hurst scaling exponent.
Related subject area
Approach: Remote Sensing | Properties and processes: Biological oceanography and marine ecology
Analyses of sea surface chlorophyll a trends and variability from 1998 to 2020 in the German Bight (North Sea)
Biophysical coupling of seasonal chlorophyll-a bloom variations and phytoplankton assemblages across the Peninsula Front in the Bransfield Strait
Felipe de Luca Lopes de Amorim, Areti Balkoni, Vera Sidorenko, and Karen Helen Wiltshire
Ocean Sci., 20, 1247–1265, https://doi.org/10.5194/os-20-1247-2024, https://doi.org/10.5194/os-20-1247-2024, 2024
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We studied the increasing or decreasing of chlorophyll a abundance in the German Bight. Chlorophyll a is the pigment present in algae that allows them to capture energy from the sun and indicates both the growth of the algae and the health of the environment. Most of the German Bight has decreasing chlorophyll a concentration in the analysed period. In addition, about 45 % of the changes happening in chlorophyll a were connected with changes in temperature.
Marta Veny, Borja Aguiar-González, Ángeles Marrero-Díaz, Tania Pereira-Vázquez, and Ángel Rodríguez-Santana
Ocean Sci., 20, 389–415, https://doi.org/10.5194/os-20-389-2024, https://doi.org/10.5194/os-20-389-2024, 2024
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This study examines the seasonal patterns of chlorophyll-a (chl-a) blooms in the Bransfield Strait using remote sensing data supported by novel and historical in situ observations. Through satellite data we show that we can identify two distinct phytoplankton niches along a thermal front known as the Peninsula Front: the Transitional Bellingshausen Water and Transitional Weddell Water pools. These findings enable the first climatological description of the chl-a blooms in the Bransfield Strait.
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Short summary
Satellite observations offer valuable information on phytoplankton abundance and community structure. Here, we employ satellite observations to infer seven phytoplankton groups at a global scale based on a new molecular method from Tara Oceans. The link has been established using machine learning approaches. The output of this work provides excellent tools to collect essential biodiversity variables and a foundation to monitor the evolution of marine biodiversity.
Satellite observations offer valuable information on phytoplankton abundance and community...