299 results on '"Uitz, Julia"'
Search Results
2. Globally Consistent Quantitative Observations of Planktonic Ecosystems
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Lombard, Fabien, Boss, Emmanuel, Waite, Anya M, Vogt, Meike, Uitz, Julia, Stemmann, Lars, Sosik, Heidi M, Schulz, Jan, Romagnan, Jean-Baptiste, Picheral, Marc, Pearlman, Jay, Ohman, Mark D, Niehoff, Barbara, Moeller, Klas M, Miloslavich, Patricia, Lara-Lpez, Ana, Kudela, Raphael, Lopes, Rubens M, Kiko, Rainer, Karp-Boss, Lee, Jaffe, Jules S, Iversen, Morten H, Frisson, Jean-Olivier, Fennel, Katja, Hauss, Helena, Guidi, Lionel, Gorsky, Gaby, Giering, Sarah LC, Gaube, Peter, Gallager, Scott, Dubelaar, George, Cowen, Robert K, Carlotti, Francois, Briseno-Avena, Christian, Berline, Leo, Benoit-Bird, Kelly, Bax, Nicholas, Batten, Sonia, Ayata, Sakina Dorothee, Artigas, Luis Felipe, and Appeltans, Ward
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plankton ,imaging ,OceanObs ,autonomous platforms ,global observing ,EOVs ,ECVs ,Oceanography ,Ecology - Published
- 2019
3. Community‐Level Responses to Iron Availability in Open Ocean Plankton Ecosystems
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Caputi, Luigi, Carradec, Quentin, Eveillard, Damien, Kirilovsky, Amos, Pelletier, Eric, Pierella Karlusich, Juan J, Rocha Jimenez Vieira, Fabio, Villar, Emilie, Chaffron, Samuel, Malviya, Shruti, Scalco, Eleonora, Acinas, Silvia G, Alberti, Adriana, Aury, Jean‐Marc, Benoiston, Anne‐Sophie, Bertrand, Alexis, Biard, Tristan, Bittner, Lucie, Boccara, Martine, Brum, Jennifer R, Brunet, Christophe, Busseni, Greta, Carratalà, Anna, Claustre, Hervé, Coelho, Luis Pedro, Colin, Sébastien, D'Aniello, Salvatore, Da Silva, Corinne, Del Core, Marianna, Doré, Hugo, Gasparini, Stéphane, Kokoszka, Florian, Jamet, Jean‐Louis, Lejeusne, Christophe, Lepoivre, Cyrille, Lescot, Magali, Lima‐Mendez, Gipsi, Lombard, Fabien, Lukeš, Julius, Maillet, Nicolas, Madoui, Mohammed‐Amin, Martinez, Elodie, Mazzocchi, Maria Grazia, Néou, Mario B, Paz‐Yepes, Javier, Poulain, Julie, Ramondenc, Simon, Romagnan, Jean‐Baptiste, Roux, Simon, Salvagio Manta, Daniela, Sanges, Remo, Speich, Sabrina, Sprovieri, Mario, Sunagawa, Shinichi, Taillandier, Vincent, Tanaka, Atsuko, Tirichine, Leila, Trottier, Camille, Uitz, Julia, Veluchamy, Alaguraj, Veselá, Jana, Vincent, Flora, Yau, Sheree, Kandels‐Lewis, Stefanie, Searson, Sarah, Dimier, Céline, Picheral, Marc, Bork, Peer, Boss, Emmanuel, Vargas, Colomban, Follows, Michael J, Grimsley, Nigel, Guidi, Lionel, Hingamp, Pascal, Karsenti, Eric, Sordino, Paolo, Stemmann, Lars, Sullivan, Matthew B, Tagliabue, Alessandro, Zingone, Adriana, Garczarek, Laurence, d'Ortenzio, Fabrizio, Testor, Pierre, Not, Fabrice, d'Alcalà, Maurizio Ribera, Wincker, Patrick, Bowler, Chris, Iudicone, Daniele, Gorsky, Gabriel, and Jaillon, Olivier
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Genetics ,Life Below Water ,Atmospheric Sciences ,Geochemistry ,Oceanography ,Meteorology & Atmospheric Sciences - Abstract
Predicting responses of plankton to variations in essential nutrients is hampered by limited in situ measurements, a poor understanding of community composition, and the lack of reference gene catalogs for key taxa. Iron is a key driver of plankton dynamics and, therefore, of global biogeochemical cycles and climate. To assess the impact of iron availability on plankton communities, we explored the comprehensive bio-oceanographic and bio-omics data sets from Tara Oceans in the context of the iron products from two state-of-the-art global scale biogeochemical models. We obtained novel information about adaptation and acclimation toward iron in a range of phytoplankton, including picocyanobacteria and diatoms, and identified whole subcommunities covarying with iron. Many of the observed global patterns were recapitulated in the Marquesas archipelago, where frequent plankton blooms are believed to be caused by natural iron fertilization, although they are not captured in large-scale biogeochemical models. This work provides a proof of concept that integrative analyses, spanning from genes to ecosystems and viruses to zooplankton, can disentangle the complexity of plankton communities and can lead to more accurate formulations of resource bioavailability in biogeochemical models, thus improving our understanding of plankton resilience in a changing environment.
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- 2019
4. Corrigendum: Reconstructing global chlorophyll-a variations using a non-linear statistical approach
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Martinez, Elodie, primary, Gorgues, Thomas, additional, Lengaigne, Matthieu, additional, Sauzède, Raphaëlle, additional, Menkes, Christophe, additional, Uitz, Julia, additional, Di Lorenzo, Emanuele, additional, and Fablet, Ronan, additional
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- 2024
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5. Seasonal variability of the phytoplankton biomass and its underlying processes in contrasted regions of the South Pacific Ocean based on BioGeoChemical-Argo observations
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Hermilly, Thomas, primary, Martinez, Elodie, additional, Uitz, Julia, additional, Cornec, Marin, additional, and Schmechtig, Catherine, additional
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- 2024
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6. Plan d'Activité Argo-France 2024
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Kolodziejczyk, Nicolas, André, Xavier, Cabanes, Cecile, Carval, Thierry, Coatanoan, Christine, D'Ortenzio, Fabrizio, Lebreton, Natanaele, Leymarie, Edouard, Maze, Guillaume, Poteau, Antoine, Le Traon, Pierre-yves, Schmechtig, Catherine, Sauzède, Raphaelle, Poffa, Noe, Thierry, Virginie, Uitz, Julia, Kolodziejczyk, Nicolas, André, Xavier, Cabanes, Cecile, Carval, Thierry, Coatanoan, Christine, D'Ortenzio, Fabrizio, Lebreton, Natanaele, Leymarie, Edouard, Maze, Guillaume, Poteau, Antoine, Le Traon, Pierre-yves, Schmechtig, Catherine, Sauzède, Raphaelle, Poffa, Noe, Thierry, Virginie, and Uitz, Julia
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Plan des activités d'Argo France (IR*, SNO et projets) pour l'année 2024
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- 2024
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7. Bilan Argo France 2023
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Kolodziejczyk, Nicolas, André, Xavier, Cabanes, Cecile, Carval, Thierry, Coatanoan, Christine, D'Ortenzio, Fabrizio, Lebreton, Natanaele, Leymarie, Edouard, Maze, Guillaume, Poteau, Antoine, Le Traon, Pierre-yves, Schmechtig, Catherine, Sauzède, Raphaelle, Poffa, Noe, Thierry, Virginie, Uitz, Julia, N. Kolodziejczyk, X. André, C. Cabanes, T. Carval, C. Coatanoan, F. D'Ortenzio, N. Lebreton, E. Leymarie, G. Maze, A. Poteau, P. -Y. Le Traon, C. Schmechtig, R. Sauzède, N. Poffa, S. Pouliquen, V. Thierry, J. Uitz, Kolodziejczyk, Nicolas, André, Xavier, Cabanes, Cecile, Carval, Thierry, Coatanoan, Christine, D'Ortenzio, Fabrizio, Lebreton, Natanaele, Leymarie, Edouard, Maze, Guillaume, Poteau, Antoine, Le Traon, Pierre-yves, Schmechtig, Catherine, Sauzède, Raphaelle, Poffa, Noe, Thierry, Virginie, Uitz, Julia, N. Kolodziejczyk, X. André, C. Cabanes, T. Carval, C. Coatanoan, F. D'Ortenzio, N. Lebreton, E. Leymarie, G. Maze, A. Poteau, P. -Y. Le Traon, C. Schmechtig, R. Sauzède, N. Poffa, S. Pouliquen, V. Thierry, and J. Uitz
- Abstract
Ce document n’est pas un compte rendu d’activités exhaustif du programme Argo-France, mais un bilan et une liste des faits marquants du programme pour l’année 2023. Des informations complémentaires sont disponibles dans le rapport AST 25 (18-22 Mars 2024, Southampton, UK).
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- 2024
8. Surface ocean microbiota determine cloud precursors
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Sellegri, Karine, Nicosia, Alessia, Freney, Evelyn, Uitz, Julia, Thyssen, Melilotus, Grégori, Gérald, Engel, Anja, Zäncker, Birthe, Haëntjens, Nils, Mas, Sébastien, Picard, David, Saint-Macary, Alexia, Peltola, Maija, Rose, Clémence, Trueblood, Jonathan, Lefevre, Dominique, D’Anna, Barbara, Desboeufs, Karine, Meskhidze, Nicholas, Guieu, Cécile, and Law, Cliff S.
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- 2021
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9. Reconstructing Global Chlorophyll-a Variations Using a Non-linear Statistical Approach.
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Martinez, Elodie, Gorgues, Thomas, Lengaigne, Matthieu, Sauzède, Raphaëlle, Menkes, Christophe, Uitz, Julia, Di Lorenzo, Emanuele, and Fablet, Ronan
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EL Nino ,OCEAN color ,SPATIO-temporal variation ,CHLOROPHYLL in water ,COLORIMETRY ,MACHINE learning ,OCEAN - Abstract
Monitoring the spatio-temporal variations of surface chlorophyll-a concentration (Chl, a proxy of phytoplankton biomass) greatly benefited from the availability of continuous and global ocean color satellite measurements from 1997 onward. These two decades of satellite observations are however still too short to provide a comprehensive description of Chl variations at decadal to multi-decadal timescales. This paper investigates the ability of a machine learning approach (a non-linear statistical approach based on Support Vector Regression, hereafter SVR) to reconstruct global spatio-temporal Chl variations from selected surface oceanic and atmospheric physical parameters. With a limited training period (13 years), we first demonstrate that Chl variability from a 32- years global physical-biogeochemical simulation can generally be skillfully reproduced with a SVR using the model surface variables as input parameters. We then apply the SVR to reconstruct satellite Chl observations using the physical predictors from the above numerical model and show that the Chl reconstructed by this SVR more accurately reproduces some aspects of observed Chl variability and trends compared to the model simulation. This SVR is able to reproduce the main modes of interannual Chl variations depicted by satellite observations in most regions, including El Niño signature in the tropical Pacific and Indian Oceans. In stark contrast with the trends simulated by the biogeochemical model, it also accurately captures spatial patterns of Chl trends estimated by satellite data, with a Chl increase in most extratropical regions and a Chl decrease in the center of the subtropical gyres, although the amplitude of these trends are underestimated by half. Results from our SVR reconstruction over the entire period (1979--2010) also suggest that the Interdecadal Pacific Oscillation drives a significant part of decadal Chl variations in both the tropical Pacific and Indian Oceans. Overall, this study demonstrates that non-linear statistical reconstructions can be complementary tools to in situ and satellite observations as well as conventional physical-biogeochemical numerical simulations to reconstruct and investigate Chl decadal variability. [ABSTRACT FROM AUTHOR]
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- 2024
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10. Challenges of modeling depth-integrated marine primary productivity over multiple decades: A case study at BATS and HOT
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Saba, Vincent S, Friedrichs, Marjorie A. M, Carr, Mary-Elena, Antoine, David, Armstrong, Robert A, Asanuma, Ichio, Aumont, Olivier, Bates, Nicholas R, Behrenfeld, Michael J, Bennington, Val, Bopp, Laurent, Bruggeman, Jorn, Buitenhuis, Erik T, Church, Matthew J, Ciotti, Aurea M, Doney, Scott C, Dowell, Mark, Dunne, John, Dutkiewicz, Stephanie, Gregg, Watson, Hoepffner, Nicolas, Hyde, Kimberly J. W, Ishizaka, Joji, Kameda, Takahiko, Karl, David M, Lima, Ivan, Lomas, Michael W, Marra, John, McKinley, Galen A, Melin, Frederic, Moore, J. Keith, Morel, Andre, O'Reilly, John, Salihoglu, Baris, Scardi, Michele, Smyth, Tim J, Tang, Shilin, Tjiputra, Jerry, Uitz, Julia, Vichi, Marcello, Waters, Kirk, Westberry, Toby K, and Yool, Andrew
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10.1029/2009GB003655 - Abstract
The performance of 36 models (22 ocean color models and 14 biogeochemical ocean circulation models (BOGCMs)) that estimate depth-integrated marine net primary productivity (NPP) was assessed by comparing their output to in situ 14C data at the Bermuda Atlantic Time series Study (BATS) and the Hawaii Ocean Time series (HOT) over nearly two decades. Specifically, skill was assessed based on the models' ability to estimate the observed mean, variability, and trends of NPP. At both sites, more than 90% of the models underestimated mean NPP, with the average bias of the BOGCMs being nearly twice that of the ocean color models. However, the difference in overall skill between the best BOGCM and the best ocean color model at each site was not significant. Between 1989 and 2007, in situ NPP at BATS and HOT increased by an average of nearly 2% per year and was positively correlated to the North Pacific Gyre Oscillation index. The majority of ocean color models produced in situ NPP trends that were closer to the observed trends when chlorophyll-a was derived from high-performance liquid chromatography (HPLC), rather than fluorometric or SeaWiFS data. However, this was a function of time such that average trend magnitude was more accurately estimated over longer time periods. Among BOGCMs, only two individual models successfully produced an increasing NPP trend (one model at each site). We caution against the use of models to assess multiannual changes in NPP over short time periods. Ocean color model estimates of NPP trends could improve if more high quality HPLC chlorophyll-a time series were available.
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- 2010
11. Inter-comparison of phytoplankton functional type phenology metrics derived from ocean color algorithms and Earth System Models
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Kostadinov, Tihomir S., Cabré, Anna, Vedantham, Harish, Marinov, Irina, Bracher, Astrid, Brewin, Robert J.W., Bricaud, Annick, Hirata, Takafumi, Hirawake, Toru, Hardman-Mountford, Nick J., Mouw, Colleen, Roy, Shovonlal, and Uitz, Julia
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- 2017
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12. Plan d'Actvité Argo France 2023
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Kolodziejczyk, Nicolas, André, Xavier, Cabanes, Cecile, Carval, Thierry, Coatanoan, Christine, D'Ortenzio, Fabrizio, Leymarie, Edouard, Lebreton, Nathanaele, Le Traon, Pierre-yves, Poffa, Noe, Pouliquen, Sylvie, Poteau, Antoine, Sauzede, Raphaelle, Schmechtig, Catherine, Thierry, Virginie, Uitz, Julia, Kolodziejczyk, Nicolas, André, Xavier, Cabanes, Cecile, Carval, Thierry, Coatanoan, Christine, D'Ortenzio, Fabrizio, Leymarie, Edouard, Lebreton, Nathanaele, Le Traon, Pierre-yves, Poffa, Noe, Pouliquen, Sylvie, Poteau, Antoine, Sauzede, Raphaelle, Schmechtig, Catherine, Thierry, Virginie, and Uitz, Julia
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Plan d'Activité prévisionnel de Argo France en 2023
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- 2023
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13. Bilan Argo France 2022
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Kolodziejczyk, Nicolas, André, Xavier, Cabanes, Cecile, Carval, Thierry, Coatanoan, Christine, D'Ortentzio, Fabrizion, Lebreton, Nathanaele, Leymarie, Edouard, Poteau, Antoine, Le Traon, Pierre-yves, Schmechtig, Catherine, Sauzede, Raphaelle, Poffa, Noe, Pouliquen, Sylvie, Thierry, Virginie, Uitz, Julia, Kolodziejczyk, Nicolas, André, Xavier, Cabanes, Cecile, Carval, Thierry, Coatanoan, Christine, D'Ortentzio, Fabrizion, Lebreton, Nathanaele, Leymarie, Edouard, Poteau, Antoine, Le Traon, Pierre-yves, Schmechtig, Catherine, Sauzede, Raphaelle, Poffa, Noe, Pouliquen, Sylvie, Thierry, Virginie, and Uitz, Julia
- Abstract
Ce document n’est pas un compte rendu d’activités exhaustif du programme Argo-France mais un bilan et une liste des faits marquants du programme pour l’année 2022. Des informations complémentaires sont disponibles dans le rapport AST 24 (20-24 Mars 2023, Halifax, Canada).
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- 2023
14. Assessing phytoplankton community composition from hyperspectral measurements of phytoplankton absorption coefficient and remote-sensing reflectance in open-ocean environments
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Uitz, Julia, Stramski, Dariusz, Reynolds, Rick A., and Dubranna, Jean
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- 2015
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15. The microbial carbon pump concept: Potential biogeochemical significance in the globally changing ocean
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Legendre, Louis, Rivkin, Richard B., Weinbauer, Markus G., Guidi, Lionel, and Uitz, Julia
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- 2015
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16. Influence of the phytoplankton community composition on the in situ fluorescence signal: Implication for an improved estimation of the chlorophyll-a concentration from BioGeoChemical-Argo profiling floats
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Petit, Flavien, primary, Uitz, Julia, additional, Schmechtig, Catherine, additional, Dimier, Céline, additional, Ras, Joséphine, additional, Poteau, Antoine, additional, Golbol, Melek, additional, Vellucci, Vincenzo, additional, and Claustre, Hervé, additional
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- 2022
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17. The underwater light field: lessons learnt from in situ BGC-Argo autonomous profilers and synergies with Earth observations
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Organelli, Emanuele, Leymarie, Edouard, Uitz, Julia, d'Ortenzio, Fabrizio, Zielinski, O, Boss, Emmanuel, Claustre, Hervé, and Uitz, Julia
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[SDU.STU.OC] Sciences of the Universe [physics]/Earth Sciences/Oceanography - Published
- 2022
18. Influence of the phytoplankton community composition on the fluorescence signal: Implication for a better estimation of chlorophyll a concentration from BGC-Argo profiling floats
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Petit, Flavien, Uitz, Julia, Claustre, Hervé, and Uitz, Julia
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[SDU.STU.OC] Sciences of the Universe [physics]/Earth Sciences/Oceanography - Abstract
Fluorescence is a practical method implemented in the BioGeoChemical-Argo (BGC-Argo) network for estimating the chlorophyll a concentration (Chla), a widely used proxy of phytoplankton biomass. Despite a strong correlation between the Chla and fluorescence signal on restricted spatial and temporal scales, large regional variations with a clear latitudinal gradient in the Chla-to-fluorescence ratio, referred to as “slope factor”, have been observed in the global ocean. This indicates the potential influence of phytoplankton community composition, resulting from the combined effects of phytoplankton absorption and quantum yield of fluorescence. As phytoplankton communities play a key role in global biogeochemical cycles, it is critical to understand their variability to accurately determine Chla. In order to examine the role of phytoplankton community composition on the fluorescence signal, we used a global concurrent dataset of Chla estimated from BGC-Argo float fluorescence measurements and High-Performance Liquid Chromatography determinations, as well as phytoplankton absorption measurements. The community composition of phytoplankton shows a strong influence on absorption, with smaller cells characterized by reduced package effect and high absorption by accessory pigments in the blue spectral region. The quantum yield of fluorescence presents a clear trend with lower values in oligotrophic areas than in high latitude regions. In oligotrophic regions, picophytoplankton exhibit low values of the fluorescence quantum yield, which we attribute to the non-photosynthetic pigment zeaxanthin. The present work, showing that the slope factor is significantly correlated to the size structure of phytoplankton communities, is a first step towards a better estimation of Chla from BGC-Argo floats. Different methods have been proposed for assessing community size structure from BGC-Argo floats and thus could be used to better constrain the calibration of fluorescence in Chla.
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- 2022
19. Variability in the fluorescence signal in relation to phytoplankton community composition and implications for the retrieval of the chlorophyll a concentration from BGC-Argo floats
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Petit, Flavien, Uitz, Julia, Claustre, Hervé, and Uitz, Julia
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[SDU.STU.OC] Sciences of the Universe [physics]/Earth Sciences/Oceanography - Published
- 2022
20. Recommendations for Plankton Measurements on OceanSITES Moorings With Relevance to Other Observing Sites
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Boss, Emmanuel, primary, Waite, Anya M., additional, Karstensen, Johannes, additional, Trull, Tom, additional, Muller-Karger, Frank, additional, Sosik, Heidi M., additional, Uitz, Julia, additional, Acinas, Silvia G., additional, Fennel, Katja, additional, Berman-Frank, Ilana, additional, Thomalla, Sandy, additional, Yamazaki, Hidekatsu, additional, Batten, Sonia, additional, Gregori, Gerald, additional, Richardson, Anthony J., additional, and Wanninkhof, Rik, additional
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- 2022
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21. Recommendations for plankton measurements on OceanSITES moorings with relevance to other observing sites
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Boss, Emmanuel S., Waite, Anya M., Karstensen, Johannes, Trull, Thomas W., Muller-Karger, Frank E., Sosik, Heidi M., Uitz, Julia, Acinas, Silvia G., Fennel, Katja, Berman-Frank, Ilana, Thomalla, Sandy J., Yamazaki, Hidekatsu, Batten, Sonia, Gregori, Gerald, Richardson, Anthony J., Wanninkhof, Rik, Boss, Emmanuel S., Waite, Anya M., Karstensen, Johannes, Trull, Thomas W., Muller-Karger, Frank E., Sosik, Heidi M., Uitz, Julia, Acinas, Silvia G., Fennel, Katja, Berman-Frank, Ilana, Thomalla, Sandy J., Yamazaki, Hidekatsu, Batten, Sonia, Gregori, Gerald, Richardson, Anthony J., and Wanninkhof, Rik
- Abstract
© The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Boss, E., Waite, A., Karstensen, J., Trull, T., Muller-Karger, F., Sosik, H., Uitz, J., Acinas, S., Fennel, K., Berman-Frank, I., Thomalla, S., Yamazaki, H., Batten, S., Gregori, G., Richardson, A., & Wanninkhof, R. Recommendations for plankton measurements on OceanSITES moorings with relevance to other observing sites. Frontiers in Marine Science, 9, (2022): 929436, https://doi.org/10.3389/fmars.2022.929436., Measuring plankton and associated variables as part of ocean time-series stations has the potential to revolutionize our understanding of ocean biology and ecology and their ties to ocean biogeochemistry. It will open temporal scales (e.g., resolving diel cycles) not typically sampled as a function of depth. In this review we motivate the addition of biological measurements to time-series sites by detailing science questions they could help address, reviewing existing technology that could be deployed, and providing examples of time-series sites already deploying some of those technologies. We consider here the opportunities that exist through global coordination within the OceanSITES network for long-term (climate) time series station in the open ocean. Especially with respect to data management, global solutions are needed as these are critical to maximize the utility of such data. We conclude by providing recommendations for an implementation plan., This work was partially supported from funding to SCOR WG 154 (P-OBS) provided by national committees of the Scientific Committee on Oceanic Research (SCOR) and from a grant to SCOR from the U.S. National Science Foundation (OCE-1840868). FM-K acknowledges the support provided for participation by the Marine Biodiversity Observation Network (MBON) sponsored by NASA, NOAA, ONR, BOEM. HS acknowledges support from the Simons Foundation.
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- 2022
22. Influence of the phytoplankton community composition on the in situ fluorescence signal: Implication for an improved estimation of the chlorophyll-a concentration from BioGeoChemical-Argo profiling floats
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Petit, Flavien, Uitz, Julia, Schmechtig, Catherine, Dimier, Céline, Ras, Joséphine, Poteau, Antoine, Golbol, Melek, Vellucci, Vincenzo, Claustre, Hervé, Petit, Flavien, Uitz, Julia, Schmechtig, Catherine, Dimier, Céline, Ras, Joséphine, Poteau, Antoine, Golbol, Melek, Vellucci, Vincenzo, and Claustre, Hervé
- Abstract
In-situ fluorescence is a widely used method to estimate the chlorophyll-a (Chla) concentration, a proxy of the phytoplankton biomass. With the emergence of autonomous platforms such as BioGeoChemical-Argo (BGC-Argo) profiling floats, its use has expanded to global scale observations. However, the relationship between in-situ fluorescence and Chla may vary significantly, leading to major discrepancies between oceanic regions. This study aims to investigate the main sources of the natural variability in the in-situ fluorescence signal in the global open ocean, specifically the influence of the phytoplankton community composition. In this view, we analyzed a combination of three datasets comprising concomitant measurements of in-situ fluorescence, pigment concentrations and phytoplankton absorption spectra. Two datasets cover several contrasted bioregions of the global ocean whereas the third one consists of a regional time series in the northwestern Mediterranean Sea, which allows to examine the effect of phytoplankton community composition on the fluorescence signal on the global, seasonal and vertical scales. We studied the variability of the two major drivers of the natural variability of the fluorescence process, i.e. the light absorption and the fluorescence quantum yield of phytoplankton, in regards of the variability of the pigment composition of the communities. The community composition correlates substantially with the Chla-to-fluorescence ratio, with high fluorescence values associated with phytoplankton communities dominated by large cells. This trend may be explained by the combined effects of the community composition on the phytoplankton absorption coefficient and the fluorescence quantum yield, and is consistently observed globally, seasonally and vertically. Non-photosynthetic pigments also appear to play a critical role in oligotrophic surface waters, leading to a reduction of the quantum yield of fluorescence. The results indicate that the phytopla
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- 2022
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23. Biological production in two contrasted regions of the Mediterranean Sea during the oligotrophic period: An estimate based on the diel cycle of optical properties measured by BGC-Argo profiling floats
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Barbieux, Marie, Uitz, Julia, Mignot, Alexandre, Roesler, Collin, Claustre, Hervé, Gentili, Bernard, Taillandier, Vincent, D'Ortenzio, Fabrizio, Loisel, Hubert, Poteau, Antoine, Leymarie, Edouard, Penkerc'H, Christophe, Schmechtig, Catherine, Bricaud, Annick, Barbieux, Marie, Uitz, Julia, Mignot, Alexandre, Roesler, Collin, Claustre, Hervé, Gentili, Bernard, Taillandier, Vincent, D'Ortenzio, Fabrizio, Loisel, Hubert, Poteau, Antoine, Leymarie, Edouard, Penkerc'H, Christophe, Schmechtig, Catherine, and Bricaud, Annick
- Abstract
This study assesses marine biological production of organic carbon based on the diel variability of bio-optical properties monitored by two BioGeoChemical-Argo (BGC-Argo) floats. Experiments were conducted in two distinct Mediterranean systems, the Northwestern Ligurian Sea and the Central Ionian Sea during summer months. We derived particulate organic carbon (POC) stock and gross community production integrated within the surface, euphotic and subsurface chlorophyll maximum (SCM) layers, using an existing approach applied to diel cycle measurements of the particulate beam attenuation (cp) and backscattering (bbp) coefficients. The diel cycle of cp provided a robust proxy for quantifying biological production in both systems; that of bbp was comparatively less robust. Derived primary production estimates vary by a factor of 2 depending upon the choice of the bio-optical relationship that converts the measured optical coefficient to POC, which is thus a critical step to constrain. Our results indicate a substantial, yet variable, contribution to the water column production of the SCM layer (16–42%). In the Ligurian Sea, the SCM is a seasonal feature that behaves as a subsurface biomass maximum (SBM) with the ability to respond to episodic abiotic forcing by increasing production. In contrast, in the Ionian Sea, the SCM is permanent, induced by phytoplankton photoacclimation and contributes moderately to water column production. These results emphasize the strong potential for transmissometers deployed on BGC-Argo profiling floats to quantify non-intrusively in situ biological production of organic carbon in the water column of stratified oligotrophic systems with recurring or permanent SCMs, which are widespread features in the global ocean.
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- 2022
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24. Recommendations for Plankton Measurements on OceanSITES Moorings With Relevance to Other Observing Sites
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Boss, Emmanuel, Waite, Anya M., Karstensen, Johannes, Trull, Tom, Muller-Karger, Frank, Sosik, Heidi M., Uitz, Julia, Acinas, Silvia G., Fennel, Katja, Berman-Frank, Ilana, Thomalla, Sandy, Yamazaki, Hidekatsu, Batten, Sonia, Gregori, Gerald, Richardson, Anthony J., Wanninkhof, Rik, Boss, Emmanuel, Waite, Anya M., Karstensen, Johannes, Trull, Tom, Muller-Karger, Frank, Sosik, Heidi M., Uitz, Julia, Acinas, Silvia G., Fennel, Katja, Berman-Frank, Ilana, Thomalla, Sandy, Yamazaki, Hidekatsu, Batten, Sonia, Gregori, Gerald, Richardson, Anthony J., and Wanninkhof, Rik
- Abstract
Measuring plankton and associated variables as part of ocean time-series stations has the potential to revolutionize our understanding of ocean biology and ecology and their ties to ocean biogeochemistry. It will open temporal scales (e.g., resolving diel cycles) not typically sampled as a function of depth. In this review we motivate the addition of biological measurements to time-series sites by detailing science questions they could help address, reviewing existing technology that could be deployed, and providing examples of time-series sites already deploying some of those technologies. We consider here the opportunities that exist through global coordination within the OceanSITES network for long-term (climate) time series station in the open ocean. Especially with respect to data management, global solutions are needed as these are critical to maximize the utility of such data. We conclude by providing recommendations for an implementation plan.
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- 2022
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25. Recommendations for Plankton Measurements on OceanSITES Moorings With Relevance to Other Observing Sites
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Scientific Committee on Oceanic Research, National Science Foundation (US), Simons Foundation, Agencia Estatal de Investigación (España), Boss, Emmanuel, Waite, Anya M., Karstensen, Johannes, Trull, Thomas W., Muller-Karger, Frank, Sosik, Heidi M., Uitz, Julia, Acinas, Silvia G., Fennel, Katja, Berman-Frank, Ilana, Thomalla, Sandy, Yamazaki, Hidekatsu, Batten, Sonia, Grégori, Gérald, Richardson, Anthony J., Wanninkhof, Rik, Scientific Committee on Oceanic Research, National Science Foundation (US), Simons Foundation, Agencia Estatal de Investigación (España), Boss, Emmanuel, Waite, Anya M., Karstensen, Johannes, Trull, Thomas W., Muller-Karger, Frank, Sosik, Heidi M., Uitz, Julia, Acinas, Silvia G., Fennel, Katja, Berman-Frank, Ilana, Thomalla, Sandy, Yamazaki, Hidekatsu, Batten, Sonia, Grégori, Gérald, Richardson, Anthony J., and Wanninkhof, Rik
- Abstract
Measuring plankton and associated variables as part of ocean time-series stations has the potential to revolutionize our understanding of ocean biology and ecology and their ties to ocean biogeochemistry. It will open temporal scales (e.g., resolving diel cycles) not typically sampled as a function of depth. In this review we motivate the addition of biological measurements to time-series sites by detailing science questions they could help address, reviewing existing technology that could be deployed, and providing examples of time-series sites already deploying some of those technologies. We consider here the opportunities that exist through global coordination within the OceanSITES network for long-term (climate) time series station in the open ocean. Especially with respect to data management, global solutions are needed as these are critical to maximize the utility of such data. We conclude by providing recommendations for an implementation plan
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- 2022
26. DMS dynamics in the most oligotrophic subtropical zones of the global ocean
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Belviso, Sauveur, Masotti, Italo, Tagliabue, Alessandro, Bopp, Laurent, Brockmann, P., Fichot, Cédric, Caniaux, Guy, Prieur, Louis, Ras, Joséphine, Uitz, Julia, Loisel, Hubert, Dessailly, David, Alvain, Séverine, Kasamatsu, Nobue, and Fukuchi, Mitsuo
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- 2012
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27. Variability of low-level clouds over the southern oceans
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Bazantay, Clément, primary, Jourdan, Olivier, additional, Mioche, Guillaume, additional, Delanoë, Julien, additional, Cazenave, Quitterie, additional, Uitz, Julia, additional, and Sellegri, Karine, additional
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- 2022
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28. Variations in the optical properties of a particle suspension associated with viral infection of marine bacteria
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Uitz, Julia, Stramski, Dariusz, Baudoux, Anne-Claire, Reynolds, Rick A., Wright, Vanessa M., Dubranna, Jean, and Azam, Farooq
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- 2010
29. Extreme Diversity in Noncalcifying Haptophytes Explains a Major Pigment Paradox in Open Oceans
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Liu, Hui, Probert, Ian, Uitz, Julia, Claustre, Hervé, Aris-Brosou, Stéphane, Frada, Miguel, Not, Fabrice, de Vargas, Colomban, and Berggren, W. A.
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- 2009
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30. Relating Phytoplankton Photophysiological Properties to Community Structure on Large Scales
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Uitz, Julia, Huot, Yannick, Bruyant, Flavienne, Babin, Marcel, Claustre, Hervé, and Claustre, Hervè
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- 2008
31. Biological production in two contrasted regions of the Mediterranean Sea during the oligotrophic period: an estimate based on the diel cycle of optical properties measured by BioGeoChemical-Argo profiling floats
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Barbieux, Marie, primary, Uitz, Julia, additional, Mignot, Alexandre, additional, Roesler, Collin, additional, Claustre, Hervé, additional, Gentili, Bernard, additional, Taillandier, Vincent, additional, D'Ortenzio, Fabrizio, additional, Loisel, Hubert, additional, Poteau, Antoine, additional, Leymarie, Edouard, additional, Penkerc'h, Christophe, additional, Schmechtig, Catherine, additional, and Bricaud, Annick, additional
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- 2022
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32. Reply on RC1
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Uitz, Julia, primary
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- 2021
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33. Correction: Kulk et al. Primary Production, an Index of Climate Change in the Ocean: Satellite-Based Estimates over Two Decades. Remote Sens. 2020, 12, 826
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Kulk, Gemma, primary, Platt, Trevor, additional, Dingle, James, additional, Jackson, Thomas, additional, Jönsson, Bror F., additional, Bouman, Heather A., additional, Babin, Marcel, additional, Brewin, Robert J. W., additional, Doblin, Martina, additional, Estrada, Marta, additional, Figueiras, Francisco G., additional, Furuya, Ken, additional, González-Benítez, Natalia, additional, Gudfinnsson, Hafsteinn G., additional, Gudmundsson, Kristinn, additional, Huang, Bangqin, additional, Isada, Tomonori, additional, Kovač, Žarko, additional, Lutz, Vivian A., additional, Marañón, Emilio, additional, Raman, Mini, additional, Richardson, Katherine, additional, Rozema, Patrick D., additional, van de Poll, Willem H., additional, Segura, Valeria, additional, Tilstone, Gavin H., additional, Uitz, Julia, additional, van Dongen-Vogels, Virginie, additional, Yoshikawa, Takashi, additional, and Sathyendranath, Shubha, additional
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- 2021
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34. A phytoplankton class-specific primary production model applied to the Kerguelen Islands region (Southern Ocean)
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Uitz, Julia, Claustre, Hervé, Griffiths, F. Brian, Ras, Joséphine, Garcia, Nicole, and Sandroni, Valérie
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- 2009
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35. NOUVELLE DISTRIBUTION VERTICALE GLOBALE DE LA CONCENTRATION DE CARBONE ORGANIQUE PARTICULAIRE ET DE CHLOROPHYLLE-A MAILLEE, UTILISANT L'APPRENTISSAGE AUTOMATIQUE POUR LE CMEMS
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Sauzède, Raphaëlle, Claustre, Hervé, Pannimpullath, Remanan, Uitz, Julia, Guinehut, Stéphanie, Collecte Localisation Satellites (CLS), Laboratoire d'océanographie de Villefranche (LOV), Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Shom, Ifremer, EuroGOOS AISBL, and Institut de la Mer de Villefranche, CNRS-INSU, Sorbonne Université, Villefranche-Sur-Mer, France
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Multi-observations ,Chlorophyll-a concentration ,Machine learning ,[SDE]Environmental Sciences ,CMEMS ,Particulate organic carbon - Abstract
International audience; As part of Copernicus Marine Environmental Monitoring Service (CMEMS), the multi-observations thematic assembly center aims to provide products based on observations and data fusion techniques (Guinehut et al., 2021). Sauzede et al., (2016) have demonstrated the potential of using hydrological measurements and ocean color satellite observations to infer the vertical distribution of backscattering coeffi cient, a proxy for the stock of particulate organic carbon (POC). The 'Satellite Ocean-Color merged with Argo data to infer bio-optical properties to depth' (SOCA) method is a neural-network-based method trained using the Biogeochemical-Argo database. SOCA has been upgraded to improve the POC retrieval and additionally retrieve the chlorophyll-a concentration (Chl). Using this method with CMEMS hydrological and satellite products, weekly 3-dimensional fi elds of POC and associated uncertainty were retrieved for the 1998-2018 period and made available from the CMEMS online portal since July 2020. The 3-dimensional products of SOCA-retrieved Chl will be made available by the end of 2021. Both of these products will be updated yearly as new input data become available. These new CMEMS products represent a most valuable source of data useful not only for supporting the quality control of Biogeochemical-Argo fl oat observations but also for data assimilation and initialization/validation of biogeochemical models.
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- 2021
36. NEW GLOBAL VERTICAL DISTRIBUTION OF GRIDDED PARTICULATE ORGANIC CARBON AND CHLOROPHYLL-A CONCENTRATION USING MACHINE LEARNING FOR CMEMS
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Sauzède, Raphaëlle, Claustre, Hervé, Pannimpullath, Remanan, Uitz, Julia, Guinehut, Stéphanie, and MORVAN, Gaël
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Multi-observations ,[SDE] Environmental Sciences ,Chlorophyll-a concentration ,Machine learning ,CMEMS ,Particulate organic carbon - Abstract
As part of Copernicus Marine Environmental Monitoring Service (CMEMS), the multi-observations thematic assembly center aims to provide products based on observations and data fusion techniques (Guinehut et al., 2021). Sauzede et al., (2016) have demonstrated the potential of using hydrological measurements and ocean color satellite observations to infer the vertical distribution of backscattering coeffi cient, a proxy for the stock of particulate organic carbon (POC). The 'Satellite Ocean-Color merged with Argo data to infer bio-optical properties to depth' (SOCA) method is a neural-network-based method trained using the Biogeochemical-Argo database. SOCA has been upgraded to improve the POC retrieval and additionally retrieve the chlorophyll-a concentration (Chl). Using this method with CMEMS hydrological and satellite products, weekly 3-dimensional fi elds of POC and associated uncertainty were retrieved for the 1998-2018 period and made available from the CMEMS online portal since July 2020. The 3-dimensional products of SOCA-retrieved Chl will be made available by the end of 2021. Both of these products will be updated yearly as new input data become available. These new CMEMS products represent a most valuable source of data useful not only for supporting the quality control of Biogeochemical-Argo fl oat observations but also for data assimilation and initialization/validation of biogeochemical models.
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- 2021
37. Deep maxima of phytoplankton biomass, primary production and bacterial production in the Mediterranean Sea
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Maranon, Emilio, Van Vambeke, France, Uitz, Julia, Boss, Emmanuel S, Dimier, Céline, Dinasquet, Julie, Engel, Anja, Haentjens, Nils, Perez-lorenzo, Maria, Taillandier, Vincent, Zancker, Birthe, Maranon, Emilio, Van Vambeke, France, Uitz, Julia, Boss, Emmanuel S, Dimier, Céline, Dinasquet, Julie, Engel, Anja, Haentjens, Nils, Perez-lorenzo, Maria, Taillandier, Vincent, and Zancker, Birthe
- Abstract
The deep chlorophyll maximum (DCM) is a ubiquitous feature of phytoplankton vertical distribution in stratified waters that is relevant to our understanding of the mechanisms that underpin the variability in photoautotroph ecophysiology across environmental gradients and has implications for remote sensing of aquatic productivity. During the PEACETIME (Process studies at the air-sea interface after dust deposition in the Mediterranean Sea) cruise, carried out from 10 May to 11 June 2017, we obtained 23 concurrent vertical profiles of phytoplankton chlorophyll a, carbon biomass and primary production, as well as heterotrophic prokaryotic production, in the western and central Mediterranean basins. Our main aims were to quantify the relative role of photoacclimation and enhanced growth as underlying mechanisms of the DCM and to assess the trophic coupling between phytoplankton and heterotrophic prokaryotic production. We found that the DCM coincided with a maximum in both the biomass and primary production but not in the growth rate of phytoplankton, which averaged 0.3 d−1 and was relatively constant across the euphotic layer. Photoacclimation explained most of the increased chlorophyll a at the DCM, as the ratio of carbon to chlorophyll a (C:Chl a) decreased from ca. 90–100 (g:g) at the surface to 20–30 at the base of the euphotic layer, while phytoplankton carbon biomass increased from ca. 6 mg C m−3 at the surface to 10–15 mg C m−3 at the DCM. As a result of photoacclimation, there was an uncoupling between chlorophyll a-specific and carbon-specific productivity across the euphotic layer. The ratio of fucoxanthin to total chlorophyll a increased markedly with depth, suggesting an increased contribution of diatoms at the DCM. The increased biomass and carbon fixation at the base of the euphotic zone was associated with enhanced rates of heterotrophic prokaryotic activity, which also showed a surface peak linked with warmer temperatures. Considering the phytoplankton
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- 2021
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38. Intercomparison of Phytoplankton functional types dynamics from satellite observations
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Bretagnon, Marine, Alvain, Séverine, Bracher, Astrid, Garnesson, Philippe, Losa, Svetlana N., Mangin, Antoine, Rêve, Anne-Hélène, Uitz, Julia, Xi, Hongyan, Hembise Fanton d'Andon, Odile, Bretagnon, Marine, Alvain, Séverine, Bracher, Astrid, Garnesson, Philippe, Losa, Svetlana N., Mangin, Antoine, Rêve, Anne-Hélène, Uitz, Julia, Xi, Hongyan, and Hembise Fanton d'Andon, Odile
- Abstract
Copernicus marine environment monitoring service (CMEMS) gives users access to a wide range of ocean descriptors. Both physics and biogeochemistry of the marine environment can be studied with complementary source of data, such as in situ data, modelling output and satellite observations at global scale and/or for European marginal seas. Among the ocean descriptors supplied as part of CMEMS, phytoplankton functional types (PFTs) describe the phytoplanktonic composition at global level or over European marginal seas. Studied phytoplankton assemblage is particularly important as it is the basis of the marine food-web. Composition of the first trophic level is a valuable indicator to infer the structure of the ecosystem and its health. Over the last decades, ocean colour remote sensing has been used to estimate the phytoplanktonic composition. The algorithms developed to estimate PFTs composition based on ocean colour observation can be classified in three categories: the spectral approaches, the abundance-based approaches (derived from the chlorophyll concentration) and the ecological approaches. The three approaches can lead to differences or, conversely, to similar patterns. Difference and similarity in PFTs estimation from remote sensing is a useful information for data assimilation or model simulation, as it provides indications on the uncertainties/variability associated to the PFT estimates. Indeed, PFT estimates from satellite observations are increasingly assimilated into ecological models to improve biogeochemical simulations, what highlights the importance to get an index or at least information describing the validity range of such PFTs estimates. In this study, four algorithms (two abundance-based, and two spectral approaches) are compared. The aim of this study is to compare the related PFT products spatially and temporally, and to study the agreement of their derived PFT phenology. This study proposes also to compare PFT algorithms developed for the glob
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- 2021
39. Med-BGC MIP: A Mediterranean biogeochemical models comparison
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Palmieri, Julien, Mignot, Alexandre, Dutay, Jean-Claude, Richon, Camille, Macias Moy, Diego, d’Ortenzio, Fabrizio, Schmechtig, Catherine, Uitz, Julia, Houpert, Loic, Lamouroux, Julien, Baklouti, Melika, Pages, Remi, Cosimo, Solidoro, Teruzzi, Anna, Lazzari, Paolo, Ciavatta, Stefano, Kay, Susan, Triantafyllou, George, Tsiaras, Kostas, Somot, Samuel, Palmieri, Julien, Mignot, Alexandre, Dutay, Jean-Claude, Richon, Camille, Macias Moy, Diego, d’Ortenzio, Fabrizio, Schmechtig, Catherine, Uitz, Julia, Houpert, Loic, Lamouroux, Julien, Baklouti, Melika, Pages, Remi, Cosimo, Solidoro, Teruzzi, Anna, Lazzari, Paolo, Ciavatta, Stefano, Kay, Susan, Triantafyllou, George, Tsiaras, Kostas, and Somot, Samuel
- Abstract
The Mediterranean Sea has been identified as a hotspot for climate change. Furthermore, its very diverse trophic regimes, in such a little area, make it an extremely interesting region from a biogeochemical perspective. Numerous studies aim at better understanding and representing the Mediterrenean dynamics and biogeochemistry through modeling. This is a crucial step in order to predict the future anthropogenic impacts on the Mediterranean Sea and their possible effects on its biogeochemistry, and all what depends on it. The number of models that simulate the Mediterranean biogeochemistry, and the data available to compare with are now sufficient to draw an overall picture of the Mediterranean Sea biogeochemical models state of the art. In this study, we gathered 10 biogeochemical simulations of the Mediterranean Sea, including 8 regional and 2 high-resolution global configurations. The simulations are compared with surface chlorophyll estimates derived from satellite observations; chlorophyll, nitrate, oxygen, and particulate organic carbon concentrations derived from BGC-Argo floats, and phytoplankton group-specific primary production estimated from ocean color satellite observations. Our first aim is to describe and compare all known Mediterranean biogeochemical models, and to highlight their specificity. This should give an insight into the current achievements, and expose what biogeochemical model products are hence available for further ecological analysis. Furthermore, a specific attention is given to how well each model performs in selected regions of the Mediterranean Sea, in order to understand which specific process is needed to adequately represent the different trophic regimes of the Mediterranean Sea.
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- 2021
40. Correction: Kulk et al. Primary Production, an Index of Climate Change in the Ocean: Satellite-Based Estimates over Two Decades. Remote Sens. 2020, 12, 826
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European Space Agency, Simons Foundation, Natural Environment Research Council (UK), Agencia Estatal de Investigación (España), Kulk, Gemma, Platt, Trevor, Dingle, James, Jackson, Thomas, Jönsson, Bror F., Bouman, Heather A., Babin, Marcel, Brewin, Robert J. W., Doblin, Martina, Estrada, Marta, Figueiras, F. G., Furuya, Ken, González, Natalia, Gudfinnsson, Hafsteinn G., Gudmundsson, Kristinn, Huang, Bangqin, Isada, Tomonori, Kovač, Žarko, Lutz, Vivian A., Marañón, Emilio, Raman, Mini, Richardson, Katherine, Rozema, Patrick D., Poll, Willem H. van de, Segura, Valeria, Tilstone, Gavin H., Uitz, Julia, Dongen-Vogels, Virginie van, Yoshikawa, Takashi, Sathyendranath, Shubha, European Space Agency, Simons Foundation, Natural Environment Research Council (UK), Agencia Estatal de Investigación (España), Kulk, Gemma, Platt, Trevor, Dingle, James, Jackson, Thomas, Jönsson, Bror F., Bouman, Heather A., Babin, Marcel, Brewin, Robert J. W., Doblin, Martina, Estrada, Marta, Figueiras, F. G., Furuya, Ken, González, Natalia, Gudfinnsson, Hafsteinn G., Gudmundsson, Kristinn, Huang, Bangqin, Isada, Tomonori, Kovač, Žarko, Lutz, Vivian A., Marañón, Emilio, Raman, Mini, Richardson, Katherine, Rozema, Patrick D., Poll, Willem H. van de, Segura, Valeria, Tilstone, Gavin H., Uitz, Julia, Dongen-Vogels, Virginie van, Yoshikawa, Takashi, and Sathyendranath, Shubha
- Abstract
Since the article “Primary Production, an Index of Climate Change in the Ocean: Satellite-Based Estimates over Two Decades” by Kulk et al. [1] was published, we discovered an error in the code of the primary production model, which crept in when the code was updated from the original version described by Platt and Sathyendranath (1988), Sathyendranath et al. (1995) and Longhurst et al. (1995) ([2,31,52] in [1]). The main error in the code led to a time interval for the integration of daily water-column primary production that was shorter than it should have been. As a consequence, daily surface irradiance and hence primary production were systematically underestimated by 20–25% for the entire time series. We also discovered that the Photosynthetic Active Radiation (PAR) products of the National Aeronautics and Space Administration (NASA) that were used to scale the daily light cycle were rounded down for 2003–2019 (MODIS years), which led to an additional but small underestimation of daily surface irradiance. In addition to addressing these errors, we have included a merged time series of the PAR product to remove inter-sensor biases (as described in the corrected text of Appendix B; see below). The main corrections increased our estimate of global annual primary production on average by +23.9% between 1998 and 2018, while the correction of the rounding error in the PAR products increased global annual primary production between 2003 and 2018 by +0.9%. Inclusion of the merged PAR product in the primary production model caused a −0.25% decrease in global annual primary production between 1998 and 2002 and a +0.08% increase between 2003 and 2010 (relative to the aforementioned +23.9% increase for the entire time series). Our estimate of global annual primary production between 1998 and 2018 now is 48.7 to 52.5 Gt C y−1 instead of the published estimate of 38.8 to 42.1 Gt C y−1. Although this is a substantial increase in the estimate of primary production, the results
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- 2021
41. Biological production in two contrasted regions of the Mediterranean Sea during the oligotrophic period: An estimate based on the diel cycle of optical properties measured by BGC-Argo profiling floats
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Barbieux, Marie, primary, Uitz, Julia, additional, Mignot, Alexandre, additional, Roesler, Collin, additional, Claustre, Hervé, additional, Gentili, Bernard, additional, Taillandier, Vincent, additional, D'Ortenzio, Fabrizio, additional, Loisel, Hubert, additional, Poteau, Antoine, additional, Leymarie, Edouard, additional, Penkerc'h, Christophe, additional, Schmechtig, Catherine, additional, and Bricaud, Annick, additional
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- 2021
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42. In situ and remote-sensed chlorophyll fluorescence as indicator of the physiological state of phytoplankton near the Isles Kerguelen (Southern Ocean)
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Timmermans, Klaas R., van der Woerd, Hendrik J., Wernand, Marcel R., Sligting, Merijn, Uitz, Julia, and de Baar, Hein J. W.
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- 2008
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43. Deep maxima of phytoplankton biomass, primary production and bacterial production in the Mediterranean Sea
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Marañón, Emilio, primary, Van Wambeke, France, additional, Uitz, Julia, additional, Boss, Emmanuel S., additional, Dimier, Céline, additional, Dinasquet, Julie, additional, Engel, Anja, additional, Haëntjens, Nils, additional, Pérez-Lorenzo, María, additional, Taillandier, Vincent, additional, and Zäncker, Birthe, additional
- Published
- 2021
- Full Text
- View/download PDF
44. Intercomparison of Phytoplankton functional types dynamics from satellite observations
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Bretagnon, Marine, primary, Alvain, Séverine, additional, Bracher, Astrid, additional, Garnesson, Philippe, additional, losa, Svetlana, additional, Mangin, Antoine, additional, Rêve, Anne-Hélène, additional, Uitz, Julia, additional, Xi, Hongyan, additional, and Hembise Fanton d'Andon, Odile, additional
- Published
- 2021
- Full Text
- View/download PDF
45. Recommendations for plankton measurements on the GO-SHIP program with relevance to other sea-going expeditions. GO-SHIP Report
- Author
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Boss, Emmanuel, Waite, Anya M, Uitz, Julia, Acinas, S.G. (Silvia), Sosik, Heidi M., Fennel, Katja, Berman-Frank, Ilana, Cornejo, Marcela, Thomalla, Sandy, Yamazaki, Hidekatsu, Batten, Sonia, Berg, Jorgen, Claustre, H. (Hervé), Grégori, Gérald, Karstensen, Johannes, Muller-Karger, F. (Frank), Richardson, A., Sloyan, Bernadette, Wanninkhof, Rik, Ras, Joséphine, Dimier, Céline, Cetinic, Ivona, Duforêt, Lucile, Clemenston, Lesley, Ferrera, I. (Isabel), Gasol, J.M. (Josep María), Massana, R. (Ramón), Sánchez, Pablo, and Sebastián-Caumel, M. (Marta)
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- 2020
46. SCOR Working Group 154 GO-SHIP Report
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Boss, Emmanuel, Waite, Anya M., Uitz, Julia, Acinas, Silvia G., Sosik, Heidi M., Fennel, Katja, Berman-Frank, Ilana, Cornejo, Marcela, Thomalla, Sandy, Yamazaki, Hidekatsu, Batten, Sonia, Berg, Jorgen, Claustre, Hervé, Grégori, Gérald, Karstensen, Johannes, Muller-Karger, Frank, Richardson, Anthony, Sloyan, Bernadette, Wanninkhof, Rik, Ras, Joséphine, Dimier, Céline, Cetinić, Ivona, Duforêt, Lucile, Clemenston, Lesley, Ferrera, Isabel, Gasol, Josep M., Massana, Ramon, Sánchez, Pablo, Sebastián, Marta, Sunagawa, Shinichi, Garczarek, Laurence, De Vargas, Colomban, Pesant, Stephane, Sullivan. Mathew, Campbell, Lisa, Brosnahan, Mike, Poulton, Nicole, Marie, Dominique, Gaube, Peter, Downie, Ryan, Kloser, Rudy, Lee, Wu-Jung, Sato, Mei, Roesler, Collin, Dall’Olmo, Giorgio, Slade, Wayne, Twardowski, Michael, Gardner, Wilford, Briggs, Nathan, Xing, Xiaogang, Organelli, Emanuelle, Frouin, Robert, Barone, Benedetto, McDonnel, Andrew, Liu, Yangyan, Chase, Alison, Miloslavich, Patricia, Lombard, Fabien, Behrenfeld, Michael, Jumars, Peter, Karp-Boss, Lee, and SCOR Working Group 154
- Subjects
Parameter Discipline::Biological oceanography::Other biological measurements ,Automated imaging of particles and zooplankton ,GO-SHIP ,Parameter Discipline::Biological oceanography::Biota abundance, biomass and diversity ,Ocean sensing ,Biological oceanography::Other biological measurements [Parameter Discipline] ,EOV ,Biological oceanography::Phytoplankton [Parameter Discipline] ,ECV ,Carbon ,Beam attenuation ,Parameter Discipline::Biological oceanography::Phytoplankton ,Spectral absorption and attenuation ,EBV ,Acoustic backscattering ,Ocean ecosystem ,Biological oceanography::Biota abundance, biomass and diversity [Parameter Discipline] ,Angular scattering ,Optical backscattering - Abstract
Tracking how ocean life is responding to increased human use and climate change will empower the global community to predict, mitigate, and manage our ocean. In this document we demonstrate the existence of mature technologies to measure ‘biology’ as a combination of biomass and diversity indicators across the plankton size spectrum. These are now ready to deploy within the GO-SHIP constraints Published SCOR WG members: Emmanuel Boss, Anya M Waite, Julia Uitz, Silvia G. Acinas, Heidi M. Sosik, Katja Fennel, Ilana Berman-Frank, Marcela Cornejo, Sandy Thomalla, Hidekatsu Yamazaki, Sonia Batten, Jorgen Berg, Hervé Claustre, Gérald Grégori, Johannes Kartensen, Frank Muller-Karger, Anthony Richardson, Bernadette Sloyan, Rik Wanninkhof. Experts on pigments and elemental analysis: Joséphine Ras, Céline Dimier, Ivona Cetinić, Lucile Duforêt, Lesley Clemenston. Experts on genetic sampling and analysis: Isabel Ferrera, Josep M. Gasol, Ramon Massana, Pablo Sánchez, Marta Sebastián, Shinichi Sunagawa, Laurence Garczarek, Colomban de Vargas, Stephane Pesant, Mathew Sullivan. Expert on quantitative imaging: Lionel Guidi, Rainer Kiko, Michael Kloster, Barbara Niehoff. Experts on flow cytometery: Lisa Campbell, Mike Brosnahan, Nicole Poulton, Dominique Marie. Experts on Bio-acoustical sensors: Peter Gaube, Ryan Downie, Rudy Kloser, Wu-Jung Lee, Mei Sato. Experts on Bio-optical sensors: Collin Roesler, Giorgio Dall’Olmo, Wayne Slade, Michael Twardowski, Wilford Gardner, Nathan Briggs, Xiaogang Xing, Emanuelle Organelli, Robert Frouin, Benedetto Barone, Andrew McDonnel, Yangyang Liu, Alison Chase. Additional experts consulted: Patricia Miloslavich, Fabien Lombard, Michael Behrenfeld, Peter Jumars, Lee Karp-Boss. We acknowledge reviews of the published draft document by Bernadette Sloyan, Rik Wanninkhof, Ed Urban, Jason Graf, Klas Ove Moller, Peer Fietzek, Rudy Kloser, and Richard Feely. Their comments helped improve this protocol significantly. The most substantial issues addressed after these reviews are bio-acoustics and measurements contributing to constrain the biological pump associated with calcifiers. Refereed Current 14.A Phytoplankton biomass and diversity Zooplankton biomass and diversity Particulate matter TRL 9 Actual system "mission proven" through successful mission operations (ground or space) Best Practice Standard Operating Procedure Genetic composition Ecosystem phenology Ecosystem distribution Community abundance Species distributions Species abundances Plankton Chlorophyll fluorometer Radiometers (including PAR) ADCP Quantitative echosounders UVP Automated imaging flow cytometery (IFCB) Automated flow cytometery (Cytosense)
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- 2020
47. Primary Production, an Index of Climate Change in the Ocean:Satellite-Based Estimates over Two Decades [+ correction]
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Kulk, Gemma, Platt, Trevor, Dingle, James, Jackson, Thomas, Jönsson, Bror F., Bouman, Heather A., Babin, Marcel, Brewin, Robert J. W., Doblin, Martina, Estrada, Marta, Figueiras, Francisco G., Furuya, Ken, González-benítez, Natalia, Gudfinnsson, Hafsteinn G., Gudmundsson, Kristinn, Huang, Bangqin, Isada, Tomonori, Kovač, Žarko, Lutz, Vivian A., Marañón, Emilio, Raman, Mini, Richardson, Katherine, Rozema, Patrick D., Poll, Willem H. Van De, Segura, Valeria, Tilstone, Gavin H., Uitz, Julia, Dongen-vogels, Virginie Van, Yoshikawa, Takashi, and Sathyendranath, Shubha
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- 2020
48. Reconstructing global chlorophyll-a variations using a non-linear statistical approach
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Martinez, Elodie, Gorgues, Thomas, Lengaigne, Matthieu, Fontana, Clément, Sauzède, Raphaëlle, Menkès, Christophe E., Uitz, Julia, Di Lorenzo, Emanuele, Fablet, Ronan, Laboratoire d'Océanographie Physique et Spatiale (LOPS), Institut de Recherche pour le Développement (IRD)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS), Ecosystèmes Insulaires Océaniens (UMR 241) (EIO), Université de la Polynésie Française (UPF)-Institut Louis Malardé [Papeete] (ILM), Institut de Recherche pour le Développement (IRD)-Institut de Recherche pour le Développement (IRD)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Institut de Recherche pour le Développement (IRD)-Muséum national d'Histoire naturelle (MNHN)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU), Ecologie marine tropicale des océans Pacifique et Indien (ENTROPIE [Nouvelle-Calédonie]), Ifremer - Nouvelle-Calédonie, Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Institut de Recherche pour le Développement (IRD [Nouvelle-Calédonie])-Université de la Nouvelle-Calédonie (UNC), Laboratoire d'océanographie de Villefranche (LOV), Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Georgia Institute of Technology [Atlanta], Lab-STICC_IMTA_CID_TOMS, Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC), École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT), Département Signal et Communications (IMT Atlantique - SC), IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Institut de Recherche pour le Développement (IRD)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche pour le Développement (IRD)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Université de la Polynésie Française (UPF)-Institut Louis Malardé [Papeete] (ILM), Institut de Recherche pour le Développement (IRD), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Institut de Recherche pour le Développement (IRD [Nouvelle-Calédonie])-Ifremer - Nouvelle-Calédonie, Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Université de la Nouvelle-Calédonie (UNC), École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique (IMT Atlantique), and IMT Atlantique (IMT Atlantique)
- Subjects
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere ,machine learning ,[STAT.ML]Statistics [stat]/Machine Learning [stat.ML] ,decadel variability ,global scale ,phytoplankton variability ,satellite ocean color ,decadal variability - Abstract
International audience; Monitoring the spatio-temporal variations of surface chlorophyll-a concentration (Chl, a proxy of phytoplankton biomass) greatly benefited from the availability of continuous and global ocean color satellite measurements from 1997 onward. These two decades of satellite observations are however still too short to provide a comprehensive description of Chl variations at decadal to multi-decadal timescales. This paper investigates the ability of a machine learning approach (a non-linear statistical approach based on Support Vector Regression, hereafter SVR) to reconstruct global spatio-temporal Chl variations from selected surface oceanic and atmospheric physical parameters. With a limited training period (13 years), we first demonstrate that Chl variability from a 32-years global physical-biogeochemical simulation can generally be skillfully reproduced with a SVR using the model surface variables as input parameters. We then apply the SVR to reconstruct satellite Chl observations using the physical predictors from the above numerical model and show that the Chl reconstructed by this SVR more accurately reproduces some aspects of observed Chl variability and trends compared to the model simulation. This SVR is able to reproduce the main modes of interannual Chl variations depicted by satellite observations in most regions, including El Niño signature in the tropical Pacific and Indian Oceans. In stark contrast with the trends simulated by the biogeochemical model, it also accurately captures spatial patterns of Chl trends estimated by satellite data, with a Chl increase in most extratropical regions and a Chl decrease in the center of the subtropical gyres, although the amplitude of these trends are underestimated by half. Results from our SVR reconstruction over the entire period (1979–2010) also suggest that the Interdecadal Pacific Oscillation drives a significant part of decadal Chl variations in both the tropical Pacific and Indian Oceans. Overall, this study demonstrates that non-linear statistical reconstructions can be complementary tools to in situ and satellite observations as well as conventional physical-biogeochemical numerical simulations to reconstruct and investigate Chl decadal variability.
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- 2020
49. Effect of natural iron fertilization on carbon sequestration in the Southern Ocean
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Blain, Stephane, Queguiner, Bernard, Armand, Leanne, Belviso, Sauveur, Bombled, Bruno, Bopp, Laurent, Bowie, Andrew, Brunet, Christian, Brussaard, Corina, Carlotti, Francois, Christaki, Urania, Corbiere, Antoine, Durand, Isabelle, Ebersbach, Frederike, Fuda, Jean-Luc, Garcia, Nicole, Gerringa, Loes, Griffiths, Brian, Guigue, Catherine, Guillerm, Christophe, Jacquet, Stephanie, Jeandel, Catherine, Laan, Patrick, Lefevre, Dominique, Lo Monaco, Claire, Malits, Andrea, Mosseri, Julie, Obernosterer, Ingrid, Park, Young-Hyang, Picheral, Marc, Pondaven, Philippe, Remenyi, Thomas, Sandroni, Valerie, Sarthou, Geraldine, Savoye, Nicolas, Scouarnec, Lionel, Souhaut, Marc, Thuiller, Doris, Timmermans, Klaas, Trull, Thomas, Uitz, Julia, van Beek, Pieter, Veldhuis, Marcel, Vincent, Dorothee, Viollier, Eric, Vong, Lilita, and Wagener, Thibaut
- Subjects
Environmental issues ,Science and technology ,Zoology and wildlife conservation - Abstract
Author(s): Stéphane Blain (corresponding author) [1]; Bernard Quéguiner [1]; Leanne Armand [1]; Sauveur Belviso [2]; Bruno Bombled [2]; Laurent Bopp [2]; Andrew Bowie [3, 4]; Christian Brunet [5]; Corina Brussaard [...]
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- 2007
- Full Text
- View/download PDF
50. Enhancement of phytoplankton biomass leeward of Tahiti as observed by Biogeochemical-Argo floats
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Sauzède, Raphaëlle, Martinez, Elodie, Maes, Christophe, De Fommervault, Orens Pasqueron, Poteau, Antoine, Mignot, Alexandre, Claustre, Hervé, Uitz, Julia, Oziel, Laurent, Maamaatuaiahutapu, Keitapu, Rodier, Martine, Schmechtig, Catherine, Laurent, Victoire, Sauzède, Raphaëlle, Martinez, Elodie, Maes, Christophe, De Fommervault, Orens Pasqueron, Poteau, Antoine, Mignot, Alexandre, Claustre, Hervé, Uitz, Julia, Oziel, Laurent, Maamaatuaiahutapu, Keitapu, Rodier, Martine, Schmechtig, Catherine, and Laurent, Victoire
- Abstract
The South Pacific Subtropical Gyre (SPSG) is a vast and remote oceanic system where the variability in phytoplankton biomass and production is still largely uncertain due to the lack of in situ biogeochemical observations. The SPSG is an oligotrophic environment where the ecosystem is controlled predominantly by nutrient depletion in surface waters. However, this dynamic is altered in the vicinity of islands where increased biological activity occurs (i.e. the island mass effect, IME). This study mainly focuses on in situ observations which show evidence of an IME leeward of Tahiti (17.7°S - 149.5°W), French Polynesia. Physical and biogeochemical observations collected with two Biogeochemical-Argo profiling floats are used to investigate the dynamics of phytoplankton biomass. Data from the first float, drifting from April 2015 to November 2016 over >1000 km westward of Tahiti, describe the open ocean conditions. The second float, deployed leeward of Tahiti in October 2015, stayed within 45 km off Tahiti for three months before it stopped communicating. In the oligotrophic central SPSG, our observations show that the deepening of the deep chlorophyll maximum (DCM) from winter to summer is light-driven and that the wintertime increase in chlorophyll a concentration in the upper layer is likely to be due to the process of photoacclimation, consistent with previous observations in oligotrophic environments. In contrast, leeward of Tahiti, the DCM widens toward the surface during late spring in association with a biological enhancement in the upper layer. Using Biogeochemical-Argo data, meteorological data from Tahiti, Hybrid Coordinate Ocean Model outputs and satellite-derived products (i.e., horizontal currents and associated fronts), the physical mechanisms involved in producing this biological enhancement leeward of Tahiti have been investigated. The IME occurs during a period of strong precipitation and in a zone of weak currents downstream of the island. We conject
- Published
- 2020
- Full Text
- View/download PDF
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