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1. Author Correction: Pathways to sustaining tuna-dependent Pacific Island economies during climate change

Author

Bell, Johann D, Senina, Inna, Adams, Timothy, Aumont, Olivier, Calmettes, Beatriz, Clark, Sangaalofa, Dessert, Morgane, Gehlen, Marion, Gorgues, Thomas, Hampton, John, Hanich, Quentin, Harden-Davies, Harriet, Hare, Steven R, Holmes, Glen, Lehodey, Patrick, Lengaigne, Matthieu, Mansfield, William, Menkes, Christophe, Nicol, Simon, Ota, Yoshitaka, Pasisi, Coral, Pilling, Graham, Reid, Chis, Ronneberg, Espen, Gupta, Alex Sen, Seto, Katherine L, Smith, Neville, Taei, Sue, Tsamenyi, Martin, and Williams, Peter

Subjects
Environmental Sciences, Climate Action, Engineering, Environmental sciences
Abstract

Correction to: Nature Sustainability. Published online 29 July 2021. In the version of this article originally published, there was an error in Supplementary Figure 15 where the current x-axis labels for Skipjack percentage of biomass change were also applied for the Yellowfin and Bigeye graphs; x-axis labels are now revised for all graphs in the online version of the article.

Published
2023

2. Pathways to sustaining tuna-dependent Pacific Island economies during climate change

Author

Bell, Johann D, Senina, Inna, Adams, Timothy, Aumont, Olivier, Calmettes, Beatriz, Clark, Sangaalofa, Dessert, Morgane, Gehlen, Marion, Gorgues, Thomas, Hampton, John, Hanich, Quentin, Harden-Davies, Harriet, Hare, Steven R, Holmes, Glen, Lehodey, Patrick, Lengaigne, Matthieu, Mansfield, William, Menkes, Christophe, Nicol, Simon, Ota, Yoshitaka, Pasisi, Coral, Pilling, Graham, Reid, Chis, Ronneberg, Espen, Gupta, Alex Sen, Seto, Katherine L, Smith, Neville, Taei, Sue, Tsamenyi, Martin, and Williams, Peter

Subjects
Climate Action
Abstract

Climate-driven redistribution of tuna threatens to disrupt the economies of Pacific Small Island Developing States (SIDS) and sustainable management of the world’s largest tuna fishery. Here we show that by 2050, under a high greenhouse gas emissions scenario (RCP 8.5), the total biomass of three tuna species in the waters of ten Pacific SIDS could decline by an average of 13% (range = −5% to −20%) due to a greater proportion of fish occurring in the high seas. The potential implications for Pacific Island economies in 2050 include an average decline in purse-seine catch of 20% (range = −10% to −30%), an average annual loss in regional tuna-fishing access fees of US$90 million (range = −US$40 million to –US$140 million) and reductions in government revenue of up to 13% (range = −8% to −17%) for individual Pacific SIDS. Redistribution of tuna under a lower-emissions scenario (RCP 4.5) is projected to reduce the purse-seine catch from the waters of Pacific SIDS by an average of only 3% (range = −12% to +9%), indicating that even greater reductions in greenhouse gas emissions, in line with the Paris Agreement, would provide a pathway to sustainability for tuna-dependent Pacific Island economies. An additional pathway involves Pacific SIDS negotiating within the regional fisheries management organization to maintain the present-day benefits they receive from tuna, regardless of the effects of climate change on the distribution of the fish.

Published
2021

9. Net primary productivity estimates and environmental variables in the Arctic Ocean: An assessment of coupled physical-biogeochemical models.

Author

Lee, Younjoo, Matrai, Patricia, Friedrichs, Marjorie, Saba, Vincent, Aumont, Olivier, Babin, Marcel, Buitenhuis, Erik, Chevallier, Matthieu, de Mora, Lee, Dessert, Morgane, Dunne, John, Ellingsen, Ingrid, Feldman, Doron, Frouin, Robert, Gehlen, Marion, Gorgues, Thomas, Ilyina, Tatiana, Jin, Meibing, John, Jasmin, Lawrence, Jon, Manizza, Manfredi, Menkes, Christophe, Perruche, Coralie, Le Fouest, Vincent, Popova, Ekaterina, Romanou, Anastasia, Samuelsen, Annette, Schwinger, Jörg, Séférian, Roland, Stock, Charles, Tjiputra, Jerry, Tremblay, L, Ueyoshi, Kyozo, Vichi, Marcello, Yool, Andrew, and Zhang, Jinlun

Abstract

The relative skill of 21 regional and global biogeochemical models was assessed in terms of how well the models reproduced observed net primary productivity (NPP) and environmental variables such as nitrate concentration (NO3), mixed layer depth (MLD), euphotic layer depth (Zeu), and sea ice concentration, by comparing results against a newly updated, quality-controlled in situ NPP database for the Arctic Ocean (1959-2011). The models broadly captured the spatial features of integrated NPP (iNPP) on a pan-Arctic scale. Most models underestimated iNPP by varying degrees in spite of overestimating surface NO3, MLD, and Zeu throughout the regions. Among the models, iNPP exhibited little difference over sea ice condition (ice-free versus ice-influenced) and bottom depth (shelf versus deep ocean). The models performed relatively well for the most recent decade and toward the end of Arctic summer. In the Barents and Greenland Seas, regional model skill of surface NO3 was best associated with how well MLD was reproduced. Regionally, iNPP was relatively well simulated in the Beaufort Sea and the central Arctic Basin, where in situ NPP is low and nutrients are mostly depleted. Models performed less well at simulating iNPP in the Greenland and Chukchi Seas, despite the higher model skill in MLD and sea ice concentration, respectively. iNPP model skill was constrained by different factors in different Arctic Ocean regions. Our study suggests that better parameterization of biological and ecological microbial rates (phytoplankton growth and zooplankton grazing) are needed for improved Arctic Ocean biogeochemical modeling.

Published
2016

10. Contrasted Trends in Chlorophyll‐a Satellite Products.

Author

Pauthenet, Etienne, Martinez, Elodie, Gorgues, Thomas, Roussillon, Joana, Drumetz, Lucas, Fablet, Ronan, and Roux, Maïlys

Subjects
CONVOLUTIONAL neural networks, CARBON cycle, MARINE biomass, THEMATIC mapper satellite, MACHINE learning, MARINE phytoplankton, ECOSYSTEMS, MARINE ecology
Abstract

Phytoplankton sustains marine ecosystems and influences the global carbon cycle. This study analyzes trends in surface chlorophyll‐a concentration (Schl), a proxy for phytoplankton biomass, using six of the most widely used merged satellite products. Significant regional variations are observed, with contrasting trends observed among different products. To assess if these trends can be related to changes in the environment or to bias in radiometric products, a convolutional neural network is used to examine the relationship between physical ocean variables versus Schl. The results suggest that the merging algorithm of Globcolour‐GSM is not reliable for trend detection and that observed changes in Schl after 2012/2016 are not supported by changes of the physical ocean. These results emphasize the need for careful interpretation of satellite‐derived Schl trends and highlight the potential of machine learning in understanding the complex interactions in marine ecosystems. Plain Language Summary: This study investigates trends in surface concentration of chlorophyll‐a (Schl), a proxy of phytoplankton biomass in the ocean. Our study reveals different trends according to the considered satellite products, challenging previous assumptions relating some Schl negative trends to the anthropogenic signal. To investigate the reliability of these trends, a machine learning approach is applied, showing that the observed changes in Schl trends may not always be related to changes in some physical ocean properties but sometimes to sensor drift. These findings underscore the importance of considering multiple factors when interpreting Schl trends and highlight the potential of advanced statistical tools in understanding marine ecosystems. Key Points: An analysis of remotely sensed surface chlorophyll‐a concentration reveals contrasted trends between available merged productsA convolutional neural network can effectively reconstruct surface chlorophyll‐a concentration from the properties of the ocean surfaceRecent trends in surface chlorophyll‐a concentration merged products are not all supported by changes in properties of the ocean surface [ABSTRACT FROM AUTHOR]

Published
2024
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11. Reconstructing Global Chlorophyll-a Variations Using a Non-linear Statistical Approach.

Author

Martinez, Elodie, Gorgues, Thomas, Lengaigne, Matthieu, Sauzède, Raphaëlle, Menkes, Christophe, Uitz, Julia, Di Lorenzo, Emanuele, and Fablet, Ronan

Subjects
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]

Published
2024
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13. Contrasting responses of the Ocean's Oxygen Minimum Zones to artificial re-oxygenation

Author

Beghoura, Houda, Gorgues, Thomas, Fransner, Filippa, Auger, Pierre-amaël, and Memery, Laurent

Subjects
Artificial reoxygenation, Oxygen Minimum Zone, Dynamic transport, Deoxygenation, Nitrogen cycle, Ocean biogeochemistry
Abstract

Studies assessing potential measures to counteract the marine deoxygenation attributed to anthropogenic activities have been conducted in a few coastal environments and at regional scale, but not yet on a global scale. One way toward global scale artificial oxygenation would be to use oxygen produced as a by-product from hydrogen-production through electrolysis. The low-carbon footprint renewable production of hydrogen from offshore wind energy offers such a possibility. Here, we assessed the potential of this artificial oxygenation method on a global scale using a coupled physical-biogeochemical numerical model. The anthropogenic oxygen source scenario assumes worldwide adoption of hydrogen, considering demographic changes and the feasibility of offshore wind turbine deployment. Following this scenario, artificial oxygenation had a negligible effect on the overall oxygen inventory (an increase of 0,07 %) but showed a reduction in the overall volume of Oxygen Minimum Zones (OMZ) between 1,1–2,4 %. Despite the decrease in the mean OMZ volume globally, OMZs display distinct and contrasting regional patterns notably due to the oxygen impacts on the nitrogen cycle. Artificial oxygenation can inhibit denitrification resulting in a net gain of nitrate that promotes locally and remotely increased biological productivity and consequent respiration. Increased respiration could ultimately lead to an oxygen loss at and beyond injection sites as in the Tropical Pacific and Indian Ocean and particularly expand the Bay of Bengal OMZ. In contrast, the tropical OMZ shrinkage in the Atlantic Ocean is attributed to oxygen enrichment induced by advective transport into the OMZ, while the absence of denitrification in this area precludes any biochemical feedback effect on oxygen levels. These results suggest that the impacts of artificial oxygenation on oxygen concentrations and ecosystems are highly non-linear. It can produce unexpected regional responses that can occur beyond the injection sites which make them difficult to forecast.

Published
2023

15. A Multi-Mode Convolutional Neural Network to reconstruct satellite-derived chlorophyll-a time series in the global ocean from physical drivers

Author

Roussillon, Joana, Fablet, Ronan, Gorgues, Thomas, Drumetz, Lucas, Littaye, Jean, Martinez, Elodie, Roussillon, Joana, Fablet, Ronan, Gorgues, Thomas, Drumetz, Lucas, Littaye, Jean, and Martinez, Elodie

Abstract

Time series of satellite-derived chlorophyll-a concentration (Chl, a proxy of phytoplankton biomass), continuously generated since 1997, are still too short to investigate the low-frequency variability of phytoplankton biomass (e.g. decadal variability). Machine learning models such as Support Vector Regression (SVR) or Multi-Layer Perceptron (MLP) have recently proven to be an alternative approach to mechanistic ones to reconstruct Chl synoptic past time-series before the satellite era from physical predictors. Nevertheless, the relationships between phytoplankton and its physical surrounding environment were implicitly considered homogeneous in space, and training such models on a global scale does not allow one to consider known regional mechanisms. Indeed, the global ocean is commonly partitioned into biogeochemical provinces (BGCPs) into which phytoplankton growth is supposed to be governed by regionally-”homogeneous” processes. The time-evolving nature of those provinces prevents imposing a priori spatially-fixed boundary constraints to restrict the learning phase. Here, we propose to use a multi-mode Convolutional Neural Network (CNN), which can spatially learn and combine different modes, to globally account for interregional variabilities. Each mode is associated with a CNN submodel, standing for a mode-specific response of phytoplankton biomass to the physical forcing. Beyond improving performance reconstruction, we show that the different modes appear regionally consistent with the ocean dynamics and that they may help to get new insights into physical-biogeochemical processes controlling phytoplankton spatio-temporal variability at global scale.

Published
2023
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16. Potential impacts of microplastic on zooplankton at the global scale

Author

Richon, Camille, Gorgues, Thomas, Paul-Pont, Ika, and Maes, Christophe

Subjects
grazing, modeling, Biogeochemistry, microplastic, ocean, Zooplankton
Abstract

Experimental studies have recently shown that microplastics (MPs) may negatively impact ocean zooplankton. In response to high concentrations of MP, zooplankton may switch their grazing preferences towards smaller prey in order to avoid accidental MP ingestion. Moreover, MP ingestion decreases overall grazing rates of zooplankton. Such modifications of zooplankton activity may have profound biogeochemical impacts since zooplankton grazing is a key step for the regulation of ocean biogeochemical cycles. In this study, we used a 3D coupled physical-biogeochemical model that represents microplastic distribution (NEMO/PISCES-PLASTIC) in order to simulate MP impacts on zooplankton grazing at the global scale. Moreover, our simulations produced an upper estimate of the global MP sink from zooplankton grazing. Our results indicate that impacts of MP on zooplankton are limited to MP accumulation areas (e.g. the subtropical gyres). In these regions, we observed that MP impacts led to a decrease in zooplankton grazing rates over 10%, which led to a somewhat counter-intuitive decrease in primary production. This decrease is explained by the loss of recycling and remineralization of nutrient following the decline of zooplankton grazing activity. Additionally, our results indicate that MP ingestion by zooplankton may constitute an important sink which may impact MP budget over the entire water column. Also see: https://micro2022.sciencesconf.org/426268/document, In MICRO 2022, Online Atlas Edition: Plastic Pollution from MACRO to nano

Published
2022
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20. Zooplankton exposure to microplastics at the global scale: Influence of vertical distribution and seasonality

Author

Richon, Camille, Gorgues, Thomas, Paul-Pont, Ika, and Maes, Christophe

Subjects
zooplankton, microplastics, modeling, contamination, global ocean
Abstract

The file contains all variables used to produce results in Richon et al., 2022 "Zooplankton exposure to microplastics at the global scale : influence of vertical distribution and seasonality" DOI: 10.3389/fmars.2022.947309

Published
2022
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21. Zooplankton exposure to microplastics at global scale: Influence of vertical distribution and seasonality

Author

Richon, Camille, Gorgues, Thomas, Paul-pont, Ika, Maes, Christophe, Richon, Camille, Gorgues, Thomas, Paul-pont, Ika, and Maes, Christophe

Abstract

Microplastics (MPs) are ubiquitous contaminants in the ocean. Zooplankton is thus widely exposed to MP ingestion. Here, we use a global coupled physical–biogeochemical model enriched with a 3D representation of MPs to assess the global zooplankton exposure to MPs. As expected, our results indicate that water MP concentration is the highest in the surface layers of subtropical gyres and coastal areas close to major MP sources, which is mostly due to floating MPs, while neutral MPs contaminate the mesopelagic zone. Additionally, we showed that floating MPs may be also transported to the mesopelagic waters during the seasonal deepening of the mixed layer depth. We then estimate zooplankton exposure to MPs based on water MP concentrations, plankton biomass, and zooplankton grazing rate. Two main drivers lead to high zooplankton exposure to MPs: 1) high water MP contamination and 2) intense grazing activity. Seasonally, re-stratification of surface waters may lead to MP vertical concentration coinciding with planktonic blooms, thus increasing contamination risk.

Published
2022
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22. Diazotrophy as a key driver of the response of marine net primary productivity to climate change

Author

Bopp, Laurent, Aumont, Olivier, Kwiatkowski, Lester, Clerc, Corentin, Dupont, Leonard, Ethe, Christian, Gorgues, Thomas, Seferian, Roland, Tagliabue, Alessandro, Bopp, Laurent, Aumont, Olivier, Kwiatkowski, Lester, Clerc, Corentin, Dupont, Leonard, Ethe, Christian, Gorgues, Thomas, Seferian, Roland, and Tagliabue, Alessandro

Abstract

The impact of anthropogenic climate change on marine net primary production (NPP) is a reason for concern because changing NPP will have widespread consequences for marine ecosystems and their associated services. Projections by the current generation of Earth system models have suggested decreases in global NPP in response to future climate change, albeit with very large uncertainties. Here, we make use of two versions of the Institut Pierre-Simon Laplace Climate Model (IPSL-CM) that simulate divergent NPP responses to similar high-emission scenarios in the 21st century and identify nitrogen fixation as the main driver of these divergent NPP responses. Differences in the way N fixation is parameterised in the marine biogeochemical component PISCES (Pelagic Interactions Scheme for Carbon and Ecosystem Studies) of the IPSL-CM versions lead to N-fixation rates that are either stable or double over the course of the 21st century, resulting in decreasing or increasing global NPP, respectively. An evaluation of these two model versions does not help constrain future NPP projection uncertainties. However, the use of a more comprehensive version of PISCES, with variable nitrogen-to-phosphorus ratios as well as a revised parameterisation of the temperature sensitivity of N fixation, suggests only moderate changes in globally averaged N fixation in the 21st century. This leads to decreasing global NPP, in line with the model-mean changes of a recent multi-model intercomparison. Lastly, despite contrasting trends in NPP, all our model versions simulate similar and significant reductions in planktonic biomass. This suggests that projected plankton biomass may be a more robust indicator than NPP of the potential impact of anthropogenic climate change on marine ecosystems across models.

Published
2022
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27. Neural Network Approaches to Reconstruct Phytoplankton Time-Series in the Global Ocean.

Author

Martinez, Elodie, Brini, Anouar, Gorgues, Thomas, Drumetz, Lucas, Roussillon, Joana, Tandeo, Pierre, Maze, Guillaume, and Fablet, Ronan

Subjects
OCEAN color, MACHINE learning, MULTILAYER perceptrons, CHLOROPHYLL in water, PHYTOPLANKTON, DEEP learning, CARBON cycle
Abstract

Phytoplankton plays a key role in the carbon cycle and supports the oceanic food web. While its seasonal and interannual cycles are rather well characterized owing to the modern satellite ocean color era, its longer time variability remains largely unknown due to the short time-period covered by observations on a global scale. With the aim of reconstructing this longer-term phytoplankton variability, a support vector regression (SVR) approach was recently considered to derive surface Chlorophyll-a concentration (Chl, a proxy of phytoplankton biomass) from physical oceanic model outputs and atmospheric reanalysis. However, those early efforts relied on one particular algorithm, putting aside the question of whether different algorithms may have specific behaviors. Here, we show that this approach can also be applied on satellite observations and can even be further improved by testing performances of different machine learning algorithms, the SVR and a neural network with dense layers (a multi-layer perceptron, MLP). The MLP, thanks to its ability to capture complex non-linear relationships, outperforms the SVR to capture satellite Chl spatial patterns (correlation of 0.75 vs. 0.65 on a global scale, respectively) along with its interannual variability and trend, despite an underestimated amplitude. Among deep learning algorithms, neural network such as MLP models appear to be promising tools to investigate phytoplankton long-term time-series. [ABSTRACT FROM AUTHOR]

Published
2022
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28. Pathways to sustaining tuna-dependent Pacific Island economies during climate change

Author

Bell, Johann D., Senina, Inna, Adams, Timothy, Aumont, Olivier, Calmettes, Beatriz, Clark, Sangaalofa, Dessert, Morgane, Gehlen, Marion, Gorgues, Thomas, Hampton, John, Hanich, Quentin, Harden-davies, Harriet, Hare, Steven R., Holmes, Glen, Lehodey, Patrick, Lengaigne, Matthieu, Mansfield, William, Menkes, Christophe, Nicol, Simon, Ota, Yoshitaka, Pasisi, Coral, Pilling, Graham, Reid, Chis, Ronneberg, Espen, Gupta, Alex Sen, Seto, Katherine L., Smith, Neville, Taei, Sue, Tsamenyi, Martin, Williams, Peter, Bell, Johann D., Senina, Inna, Adams, Timothy, Aumont, Olivier, Calmettes, Beatriz, Clark, Sangaalofa, Dessert, Morgane, Gehlen, Marion, Gorgues, Thomas, Hampton, John, Hanich, Quentin, Harden-davies, Harriet, Hare, Steven R., Holmes, Glen, Lehodey, Patrick, Lengaigne, Matthieu, Mansfield, William, Menkes, Christophe, Nicol, Simon, Ota, Yoshitaka, Pasisi, Coral, Pilling, Graham, Reid, Chis, Ronneberg, Espen, Gupta, Alex Sen, Seto, Katherine L., Smith, Neville, Taei, Sue, Tsamenyi, Martin, and Williams, Peter

Abstract

Climate-driven redistribution of tuna threatens to disrupt the economies of Pacific Small Island Developing States (SIDS) and sustainable management of the world’s largest tuna fishery. Here we show that by 2050, under a high greenhouse gas emissions scenario (RCP 8.5), the total biomass of three tuna species in the waters of ten Pacific SIDS could decline by an average of 13% (range = −5% to −20%) due to a greater proportion of fish occurring in the high seas. The potential implications for Pacific Island economies in 2050 include an average decline in purse-seine catch of 20% (range = −10% to −30%), an average annual loss in regional tuna-fishing access fees of US$90 million (range = −US$40 million to –US$140 million) and reductions in government revenue of up to 13% (range = −8% to −17%) for individual Pacific SIDS. Redistribution of tuna under a lower-emissions scenario (RCP 4.5) is projected to reduce the purse-seine catch from the waters of Pacific SIDS by an average of only 3% (range = −12% to +9%), indicating that even greater reductions in greenhouse gas emissions, in line with the Paris Agreement, would provide a pathway to sustainability for tuna-dependent Pacific Island economies. An additional pathway involves Pacific SIDS negotiating within the regional fisheries management organization to maintain the present-day benefits they receive from tuna, regardless of the effects of climate change on the distribution of the fish.

Published
2021
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29. Neural Network Approaches to Reconstruct Phytoplankton Time-Series in the Global Ocean

Author

Martinez, Elodie, Brini, A., Gorgues, Thomas, Drumetz, L., Roussillon, J., Tandeo, P., Maeze, G., Fablet, R., 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), 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), 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), Interdisciplinary Graduate School for the Blue planet, ANR-17-EURE-0015,ISBlue,Interdisciplinary Graduate School for the Blue planet(2017), 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), IMT Atlantique (IMT Atlantique), 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 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)

Subjects
ocean color, multi-layer perceptron, physical predictors, [SDE.IE]Environmental Sciences/Environmental Engineering, Science, [SDE]Environmental Sciences, phytoplankton time-series reconstruction, [INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE], support vector regression, neural networks, [SDU.STU.OC]Sciences of the Universe [physics]/Earth Sciences/Oceanography
Abstract

International audience; Phytoplankton plays a key role in the carbon cycle and supports the oceanic food web. While its seasonal and interannual cycles are rather well characterized owing to the modern satellite ocean color era, its longer time variability remains largely unknown due to the short time-period covered by observations on a global scale. With the aim of reconstructing this longer-term phytoplankton variability, a support vector regression (SVR) approach was recently considered to derive surface Chlorophyll-a concentration (Chl, a proxy of phytoplankton biomass) from physical oceanic model outputs and atmospheric reanalysis. However, those early efforts relied on one particular algorithm, putting aside the question of whether different algorithms may have specific behaviors. Here, we show that this approach can also be applied on satellite observations and can even be further improved by testing performances of different machine learning algorithms, the SVR and a neural network with dense layers (a multi-layer perceptron, MLP). The MLP outperforms the SVR to capture satellite Chl (correlation of 0.6 vs. 0.17 on a global scale, respectively) along with its seasonal and interannual variability, despite an underestimated amplitude. Among deep learning algorithms, neural network such as MLP models appear to be promising tools to investigate phytoplankton long-term time-series.

Published
2020

31. Revisiting the La NiA[+ or -]a 1998 phytoplankton blooms in the equatorial Pacific

Author

Gorgues, Thomas, Menkes, C., Slemons, L., Aumont, O., Dandonneau, Y., Radenac, M.-H., Alvain, S., and Moulin, C.

Subjects
Ecosystems -- Models, Ecosystems -- Analysis, Chlorophyll -- Models, Chlorophyll -- Analysis, Earth sciences
Abstract

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.dsr.2009.12.008 Byline: Thomas Gorgues (a), C. Menkes (b), L. Slemons (c), O. Aumont (d), Y. Dandonneau (e), M.-H. Radenac (f), S. Alvain (g), C. Moulin (g) Keywords: La NiA[+ or -]a; ENSO; Equatorial Pacific; Phytoplankton; Blooms; 1997-1998; Iron; Model Abstract: A biogeochemical model of the tropical Pacific has been used to assess the impact of interannual variability in a western Pacific iron source on the iron-limited ecosystem of the central and eastern Pacific during the 1997-1998 El NiA[+ or -]o. A reference simulation and two simulations with an iron source in the western Pacific have been performed. The two 'source' simulations differed only in the temporal variability of the iron source. In the variable source simulation, the iron concentration in the source region was proportional to the velocity of the New Guinea Coastal Undercurrent (NGCUC). In the constant source simulation, the same time-averaged concentration of iron was imposed with no temporal variability. The variable source was designed to mimic variations of iron flux from the northeast slope of New Guinea to the NGCUC due to modulation of sedimentary iron resuspension as previously hypothesized. Through the comparison of these simulations, it appeared that: (i) an iron source in the NGCUC, regardless of its source variability, increases biomass in the eastern equatorial Pacific because of the greater eastward iron flux by the Equatorial Undercurrent and (ii) a variable NGCUC iron source does not change the temporal variability of eastern Pacific chlorophyll, and in particular the timing and intensity of the June 1998 bloom. To explain eastern Pacific biological variability, local rather than remote processes are needed, such as wind-driven upwelling, the local depth of the thermocline, tropical instability waves and biological processes such as high grazing pressure. Therefore, while the western Pacific sources of dissolved iron are important in our model to sustain annually integrated equatorial Pacific production, they are unlikely to strongly constrain the timing of blooms in the central and eastern Pacific such as during the 1998 La NiA[+ or -]a. Author Affiliation: (a) IUEM - LPO, Centre IRD de bretagne, 29280 Plouzane, France (b) LOCEAN - IRD Noumea, BP A5, Noumea, 98848, New Caledonia (c) School of Oceanography, University of Washington, Seattle, WA98105, United States (d) LPO, Centre IRD de bretagne, 29280 Plouzane, France (e) LOCEAN/IPSL,75252 PARIS Cedex 05, France (f) LEGOS, 31400 Toulouse, France (g) ISPL/LSCE, CEA-CNRS-UVSQ, 91191 Gif-sur-Yvette, France Article History: Received 29 May 2009; Revised 22 December 2009; Accepted 27 December 2009

Published
2010

32. International conference ICAWA 2017 and 2018 : extended book of abstract : the AWA project : ecosystem approach to the management of fisheries and the marine environment in West African waters

Author

Brochier, Timothée, Auger, Pierre-Amaël, Estrade, P., Ba, Aliou, Koné, V., Mbaye, B.C., Ndoye, S., Thiaw, M., Trong, H.N., Mchich, R., Auger, Pierre, Bah, A., Thiaw, D., Machu, Eric, Capet, Xavier, Pecquerie, Laure, Lett, Christophe, Gorgues, Thomas, Brehmer, Patrice, Brehmer, Patrice (ed.), Diogoul, N. (collab.), Zenk, C. (collab.), Vareilles, M. de (collab.), Keenlyside, N. (collab.), Nascimento, J.M. (collab.), Ramos, V. M. (collab.), Sow, B.A. (collab.), Fock, H. (collab.), Schmidt, J. (collab.), Ekau, W. (collab.), Mbaye, A. (collab.), Fall. A. (collab.), Monteiro, I. (collab.), Kouassi, A.M. (collab.), Silva, O. (collab.), Brochier, Timothée (collab.), Sall. M. (collab.), Mayif, M. (collab.), Koné, V. (collab.), Gorgues, Thomas (collab.), Ferreira Santos, C. (collab.), Bamy, I.L. (collab.), Barry, I. (collab.), Sidibe, M. (collab.), and Diadhou, H. (collab.)

Abstract

Since the onset of AWA, a number of studies have focused on the management and ecology in West Africa. Here we provide a short insight of the main highlights on a selection of contrasted modelling case studies. Understanding the functioning of the ecosystem is essential to promote ecosystem approach to fisheries management and the marine environment (EAMME) and path providing advices to decision makers and managers. In the EAMME, the civil society addressed various questions to AWA on which specific models have been developed to provide at least first insight to the answers, e.g., on the effect of artificial reef implementation in marine protected area; the possible equilibriums between national fisheries sharing a same trans-boundary fish stock; the feedback between local exploitation, fish market and fisheries mobility, the responses of a fishery to economic, biologic and management parameters, the spatial variability of primary productivity as well oceanographic circulation at regional level or the fish egg advection over the continental shelf. More complex modelling exercise have also been conducted taking advantage of previous research led on sardinella aurita. In this way a coupled model taking into account environmental variability, fish growth and spatial behaviour was developed. We present as example new hypothesis on adult mediated connectivity between EEZ, inter-annual variability and interest to work on climate change with such model. We propose a prospective of what further research could be conducted to continue to bring up relevant information for a sub-regional EAMME in North West Africa fostering exchanges between modellers and marine scientists and all stakeholders.

Published
2019

35. Reconstructing global chlorophyll-a variations using a non-linear statistical approach

Author

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.

Published
2020

36. Monitoring the Influence of the Mesoscale Ocean Dynamics on Phytoplanktonic Plumes around the Marquesas Islands Using Multi-Satellite Missions

Author

Cassianides, Angelina, Martinez, Elodie, Maes, Christophe, Carton, Xavier, Gorgues, Thomas, Cassianides, Angelina, Martinez, Elodie, Maes, Christophe, Carton, Xavier, and Gorgues, Thomas

Abstract

The Marquesas islands are a place of strong phytoplanktonic enhancement, whose original mechanisms have not been explained yet. Several mechanisms such as current−bathymetry interactions or island run-off can fertilize waters in the immediate vicinity or downstream of the islands, allowing phytoplankton enhancement. Here, we took the opportunity of an oceanographic cruise carried out at the end of 2018, to combine in situ and satellite observations to investigate two phytoplanktonic blooms occurring north and south of the archipelago. First, Lagrangian diagnostics show that both chlorophyll-a concentrations (Chl) plumes are advected from the islands. Second, the use of Finite-size Lyaponov Exponent and frontogenesis diagnostics reveal how the Chl plumes are shaped by the passage of a mesoscale cyclonic eddy in the south and by a converging front and finer-scale dynamic activity in the north. Our results based on these observations provide clues to the hypothesis of a fertilization from the islands themselves allowing phytoplankton to thrive. They also highlight the role of advection to disperse and shape the Chl plumes in two regions with contrasting dynamical regimes

Published
2020
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39. International conference ICAWA 2017 and 2018 : extended book of abstract : the AWA project : ecosystem approach to the management of fisheries and the marine environment in West African waters

Author

Auger, Pierre-Amaël, Gorgues, Thomas, Machu, Éric, Brochier, Timothée, Brehmer, Patrice, Aumont, Olivier, 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), Unité de modélisation mathématique et informatique des systèmes complexes [Bondy] (UMMISCO), Institut de Recherche pour le Développement (IRD [France-Nord])-Institut de la francophonie pour l'informatique-Université Cheikh Anta Diop [Dakar, Sénégal] (UCAD)-Université Gaston Bergé (Saint-Louis, Sénégal)-Université Cadi Ayyad [Marrakech] (UCA)-Université de Yaoundé I-Sorbonne Université (SU), Laboratoire des Sciences de l'Environnement Marin (LEMAR) (LEMAR), Institut de Recherche pour le Développement (IRD)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Université de Brest (UBO)-Institut Universitaire Européen de la Mer (IUEM), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche pour le Développement (IRD), Nucleus for European Modeling of the Ocean (NEMO R&D ), 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)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), 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), Brehmer, Patrice, HORIZON, IRD, Brehmer, Patrice (ed.), Diogoul, N. (collab.), Zenk, C. (collab.), Vareilles, M. de (collab.), Keenlyside, N. (collab.), Nascimento, J.M. (collab.), Ramos, V. M. (collab.), Sow, B.A. (collab.), Fock, H. (collab.), Schmidt, J. (collab.), Ekau, W. (collab.), Mbaye, A. (collab.), Fall. A. (collab.), Monteiro, I. (collab.), Kouassi, A.M. (collab.), Silva, O. (collab.), Brochier, Timothée (collab.), Sall. M. (collab.), Mayif, M. (collab.), Koné, V. (collab.), Gorgues, Thomas (collab.), Ferreira Santos, C. (collab.), Bamy, I.L. (collab.), Barry, I. (collab.), Sidibe, M. (collab.), Diadhou, H. (collab.), 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), Université de Yaoundé I-Institut de la francophonie pour l'informatique-Université Cheikh Anta Diop [Dakar, Sénégal] (UCAD)-Université Gaston Bergé (Saint-Louis, Sénégal)-Université Cadi Ayyad [Marrakech] (UCA)-Sorbonne Université (SU)-Institut de Recherche pour le Développement (IRD [France-Nord]), Institut de Recherche pour le Développement (IRD)-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 national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), 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)-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)), and 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)

Subjects
[SDE.BE] Environmental Sciences/Biodiversity and Ecology, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, [SDE.MCG] Environmental Sciences/Global Changes, AFRIQUE DE L'OUEST, AFRIQUE DU NORD, [SDU.OCEAN] Sciences of the Universe [physics]/Ocean, Atmosphere, [SDE.MCG]Environmental Sciences/Global Changes, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, ATLANTIQUE
Abstract

ICAWA : International Conference AWA, Lanzarote, ESP, 17-/04/2018 - 20/04/2018; An analysis based on a multi-decadal physical–biogeochemical hindcast simulation (1980-2009) was conducted to characterize the drivers of the spatial distribution of phytoplankton biomass and production in the north-west (NW) African upwelling system. To that end, a comparative box analysis representing homogeneous sub-regions in the NW African upwelling system has been conducted. The sub-regions have been defined using the near-surface horizontal circulation patterns. In each box, we analysed the dynamics of primary productivity and nutrients with regard to advective and diffusive matter fluxes at the boundaries and local biological production and/or uptake. The nature and variability of the matter exported from the coastal margin to the adjacent open ocean were also subsequently depicted. This variability of the primary production may impact the distribution and abundance of fish populations, and their associated fisheries, on a large range of timescales.

Published
2018

41. How abiotic sedimentary particulate iron may impact the dissolved iron distribution and may change our understanding on global ocean biogeochemical cycles ?

Author

Beghoura, Houda, Gorgues, Thomas, Aumont, Olivier, Planquette, Hélène, Tagliabue, Alessandro, 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), Nucleus for European Modeling of the Ocean (NEMO R&D ), 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)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), 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), Laboratoire des Sciences de l'Environnement Marin (LEMAR) (LEMAR), Institut de Recherche pour le Développement (IRD)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Université de Brest (UBO)-Institut Universitaire Européen de la Mer (IUEM), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Department of Earth Ocean and Ecological Sciences [Liverpool], University of Liverpool, 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), 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)-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)), 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), and Institut de Recherche pour le Développement (IRD)-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 national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)

Subjects
[SDU.STU]Sciences of the Universe [physics]/Earth Sciences, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, ComputingMilieux_MISCELLANEOUS, [SDU.STU.OC]Sciences of the Universe [physics]/Earth Sciences/Oceanography
Abstract

International audience

Published
2019

42. International conference ICAWA 2017 and 2018 : extended book of abstract : the AWA project : ecosystem approach to the management of fisheries and the marine environment in West African waters

Author

Brehmer, Patrice (ed.), Diogoul, N. (collab.), Zenk, C. (collab.), Vareilles, M. de (collab.), Keenlyside, N. (collab.), Nascimento, J.M. (collab.), Ramos, V. M. (collab.), Sow, B.A. (collab.), Fock, H. (collab.), Schmidt, J. (collab.), Ekau, W. (collab.), Mbaye, A. (collab.), Fall. A. (collab.), Monteiro, I. (collab.), Kouassi, A.M. (collab.), Silva, O. (collab.), Brochier, Timothée (collab.), Sall. M. (collab.), Mayif, M. (collab.), Koné, V. (collab.), Gorgues, Thomas (collab.), Ferreira Santos, C. (collab.), Bamy, I.L. (collab.), Barry, I. (collab.), Sidibe, M. (collab.), and Diadhou, H. (collab.)

Published
2019

44. Simulated changes in the particulate carbon export efficiency due to diel vertical migration of zooplankton in the North Atlantic

Author

Gorgues, Thomas, Aumont, Olivier, Memery, Laurent, Gorgues, Thomas, Aumont, Olivier, and Memery, Laurent

Abstract

Diel vertical migration (DVM) of zooplankton has been recognized to influence the biological pump by releasing carbon and nutrients at depth. However, uncertainties regarding the magnitude, spatial occurrence and variability of this “active transport”, as well as its impact on the carbon export, remain. To tackle these questions, a cost‐effective parameterization of the DVM is included into a regional biogeochemical model simulating the North Atlantic. In addition to a reference simulation in which no DVM is simulated, two relative biomasses of migrating zooplankton (30% and 60%) have been tested. It leads to an active to passive export ratio in agreement with published estimations and to an increase in the carbon export efficiency at 1000m between 20 and 40%. However, this effect is partially canceled out by a simulated primary production decrease. DVM differently impacts contrasted North Atlantic regions with the largest effect on export efficiency found in the subtropical area. Key Points Model evaluation of the zooplankton diurnal vertical migration (DVM) impacts in the North Atlantic. DVM increases the effectiveness of the carbon export. DVM, in model experiments, decrease primary production, which almost cancels out the above mentioned more efficient export.

Published
2019
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45. Impact of inorganic particles of sedimentary origin on global dissolved iron and phytoplankton distribution

Author

Beghoura, H., Gorgues, Thomas, Aumont, Olivier, Planquette, Helene, Tagliabue, A., Auger, P.‐a., Beghoura, H., Gorgues, Thomas, Aumont, Olivier, Planquette, Helene, Tagliabue, A., and Auger, P.‐a.

Abstract

Iron is known to be the limiting nutrient for the phytoplankton growth over ~40% of the global ocean and to impact the structure of marine ecosystems. Dissolved iron (DFe) is assumed to be the only form available to phytoplankton while particulate iron (PFe) has mostly been considered for its role in the biogenic iron remineralization and induced scavenging. Therefore, most studies focused on the nature of DFe external sources to the ocean (i.e. aeolian dust, riverine fluxes, hydrothermal sources and sediment) and their quantification, which still remain uncertain. Among these external sources, the sedimentary sources have been shown to be underestimated. Moreover, the iron supply from sediments has been documented to be often larger in the particle fraction. Here, we test the impacts of an iron sediment source of inorganic particulate iron (PFeInorg) on global DFe and phytoplankton distribution. We use experimentally acquired knowledge to test a parameterization of a PFeInorg pool in a global biogeochemical model and compare with published indirect estimation. Depending on the parameterization of its dissolution and sinking speed, the PFeInorg can noticeably enrich water masses in DFe during its transport from the sediment to the open ocean, notably in regions not usually accessible to external DFe inputs. Indeed, the fact that DFe is prone to scavenging, reduces the impact of equivalent Fe inputs from sediments in the dissolved form in those regions far from the sediment sources. PFeInorg thereby has the potential to fuel the phytoplankton growth in offshore regions impacting the coastal‐offshore chlorophyll gradient.

Published
2019
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46. Role of Iron in the Marquesas Island Mass Effect

Author

Raapoto, Hirohiti, Martinez, Elodie, Petrenko, Anne, Doglioli, Andrea, Gorgues, Thomas, Sauzède, Raphaëlle, Maamaatuaiahutapu, Keitapu, Maes, Christophe, Menkes, Christophe, Lefèvre, Jérôme, Raapoto, Hirohiti, Martinez, Elodie, Petrenko, Anne, Doglioli, Andrea, Gorgues, Thomas, Sauzède, Raphaëlle, Maamaatuaiahutapu, Keitapu, Maes, Christophe, Menkes, Christophe, and Lefèvre, Jérôme

Abstract

A remarkable chlorophyll‐a concentration (Chl, a proxy of phytoplankton biomass) plume can be noticed on remotely sensed ocean color observations at the boundary separating the equatorial mesotrophic from the subtropical oligotrophic waters in the central South Pacific Ocean. This prominent biological feature is known as the island mass effect of the Marquesas archipelago. Waters surrounding these islands present high macronutrient concentrations but an iron depletion. In this study, the origin of Chl enhancement is investigated using a modeling approach. Four simulations based on identical physical and biogeochemical forcings but with different iron sources are conducted and analyzed. Only simulations considering an iron input from the island sediments present similar patterns (despite being too weak) of vertical and horizontal Chl distributions as compared to biogeochemical‐Argo profiling float and satellite observations. In addition, simulations with no other iron input than the boundary forcings reveal the relative importance of remote processes in modulating the seasonal pattern of Chl around the archipelago through horizontal advection of nutrient‐rich waters from the equator toward the archipelago and vertical mixing uplifting deep nutrient‐rich waters toward the upper lit layer.

Published
2019
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47. Contrasted Trends in Chlorophyll‐aSatellite Products

Author

Pauthenet, Etienne, Martinez, Elodie, Gorgues, Thomas, Roussillon, Joana, Drumetz, Lucas, Fablet, Ronan, and Roux, Maïlys

Abstract

Phytoplankton sustains marine ecosystems and influences the global carbon cycle. This study analyzes trends in surface chlorophyll‐aconcentration (Schl), a proxy for phytoplankton biomass, using six of the most widely used merged satellite products. Significant regional variations are observed, with contrasting trends observed among different products. To assess if these trends can be related to changes in the environment or to bias in radiometric products, a convolutional neural network is used to examine the relationship between physical ocean variables versus Schl. The results suggest that the merging algorithm of Globcolour‐GSM is not reliable for trend detection and that observed changes in Schl after 2012/2016 are not supported by changes of the physical ocean. These results emphasize the need for careful interpretation of satellite‐derived Schl trends and highlight the potential of machine learning in understanding the complex interactions in marine ecosystems. This study investigates trends in surface concentration of chlorophyll‐a(Schl), a proxy of phytoplankton biomass in the ocean. Our study reveals different trends according to the considered satellite products, challenging previous assumptions relating some Schl negative trends to the anthropogenic signal. To investigate the reliability of these trends, a machine learning approach is applied, showing that the observed changes in Schl trends may not always be related to changes in some physical ocean properties but sometimes to sensor drift. These findings underscore the importance of considering multiple factors when interpreting Schl trends and highlight the potential of advanced statistical tools in understanding marine ecosystems. An analysis of remotely sensed surface chlorophyll‐aconcentration reveals contrasted trends between available merged productsA convolutional neural network can effectively reconstruct surface chlorophyll‐aconcentration from the properties of the ocean surfaceRecent trends in surface chlorophyll‐aconcentration merged products are not all supported by changes in properties of the ocean surface An analysis of remotely sensed surface chlorophyll‐aconcentration reveals contrasted trends between available merged products A convolutional neural network can effectively reconstruct surface chlorophyll‐aconcentration from the properties of the ocean surface Recent trends in surface chlorophyll‐aconcentration merged products are not all supported by changes in properties of the ocean surface

Published
2024
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48. Modelling N2 fixation related to Trichodesmium sp.: driving processes and impacts on primary production in the tropical Pacific Ocean

Author

Dutheil, Cyril, Aumont, Olivier, Gorgues, Thomas, Lorrain, Anne, BONNET, Sophie, Rodier, Martine, DUPOUY, Cecile, Shiozaki, Takuhei, Menkès, Christophe E., Institut de Recherche pour le Développement (IRD [Nouvelle-Calédonie]), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), 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), Nucleus for European Modeling of the Ocean (NEMO R&D ), 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)-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)), 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)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS), Laboratoire des Sciences de l'Environnement Marin (LEMAR) (LEMAR), Institut de Recherche pour le Développement (IRD)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Université de Brest (UBO)-Institut Universitaire Européen de la Mer (IUEM), Institut de Recherche pour le Développement (IRD)-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 national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche pour le Développement (IRD), Institut méditerranéen d'océanologie (MIO), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS), Ecosystèmes Insulaires Océaniens (UMR 241) (EIO), 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), Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Océan et variabilité du climat (VARCLIM), OUTPACE, BIOSOPE,MOORSPICE, DIAPALIS, NECTALIS, PANDORA, Mirai, 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), 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)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), 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), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Université de la Polynésie Française (UPF)-Institut Louis Malardé [Papeete] (ILM), and 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)

Subjects
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, ACL, EQUATORIAL PACIFIC, DIAZOTROPH-DERIVED NITROGEN, [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph], ENVIRONMENTAL CONTROLS, CARBON, BUOYANCY REGULATION, PHOSPHATE AVAILABILITY, DINITROGEN-FIXATION, MARINE CYANOBACTERIUM, CYANOBACTERIUM-TRICHODESMIUM, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, IRON LIMITATION
Abstract

Dinitrogen fixation is now recognized as one of the major sources of bio-available nitrogen in the ocean. Thus, N2 fixation sustains a significant part of the global primary production by supplying the most common limiting nutrient for phytoplankton growth. The “Oligotrophy to UlTra-oligotrophy PACific Experiment” (OUTPACE) improved the data coverage of the western tropical South Pacific, an area recently recognized as a hotspot of N2 fixation. This new development leads us to develop and test an explicit N2 fixation formulation based on the Trichodesmium physiology (the most studied nitrogen fixer) within a 3-D coupled dynamical–biogeochemical model (ROMS-PISCES). We performed a climatological numerical simulation that is able to reproduce the main physical (e.g. sea surface temperature) and biogeochemical patterns (nutrient and chlorophyll concentrations, as well as N2 fixation) in the tropical Pacific. This simulation displayed a Trichodesmium regional distribution that extends from 150∘ E to 120∘ W in the south tropical Pacific, and from 120∘ E to 140∘ W in the north tropical Pacific. The local simulated maximuma were found around islands (Hawaii, Fiji, Samoa, New Caledonia, Vanuatu). We assessed that 15 % of the total primary production may be due to Trichodesmium in the low-nutrient low-chlorophyll regions (LNLC) of the tropical Pacific. Comparison between our explicit and the often used (in biogeochemical models) implicit parameterization of N2 fixation showed that the latter leads to an underestimation of N2 fixation rates by about 25 % in LNLC regions. Finally, we established that iron fluxes from island sediments control the spatial distribution of Trichodesmium biomasses in the western tropical South Pacific. Note, this last result does not take into account the iron supply from rivers and hydrothermal sources, which may well be of importance in a region known for its strong precipitation rates and volcanic activity.

Published
2018

49. Role of Iron in the Marquesas Island Mass Effect

Author

Raapoto, Hirohiti, primary, Martinez, Elodie, additional, Petrenko, Anne, additional, Doglioli, Andrea, additional, Gorgues, Thomas, additional, Sauzède, Raphaëlle, additional, Maamaatuaiahutapu, Keitapu, additional, Maes, Christophe, additional, Menkes, Christophe, additional, and Lefèvre, Jérôme, additional

Published
2019
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