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  • 2005-2009  (15)
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  • 1
    ISSN: 1365-2486
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Biology , Energy, Environment Protection, Nuclear Power Engineering , Geography
    Notes: Ecosystem processes are important determinants of the biogeochemistry of the ocean, and they can be profoundly affected by changes in climate. Ocean models currently express ecosystem processes through empirically derived parameterizations that tightly link key geochemical tracers to ocean physics. The explicit inclusion of ecosystem processes in models will permit ecological changes to be taken into account, and will allow us to address several important questions, including the causes of observed glacial–interglacial changes in atmospheric trace gases and aerosols, and how the oceanic uptake of CO2 is likely to change in the future. There is an urgent need to assess our mechanistic understanding of the environmental factors that exert control over marine ecosystems, and to represent their natural complexity based on theoretical understanding. We present a prototype design for a Dynamic Green Ocean Model (DGOM) based on the identification of (a) key plankton functional types that need to be simulated explicitly to capture important biogeochemical processes in the ocean; (b) key processes controlling the growth and mortality of these functional types and hence their interactions; and (c) sources of information necessary to parameterize each of these processes within a modeling framework. We also develop a strategy for model evaluation, based on simulation of both past and present mean state and variability, and identify potential sources of validation data for each. Finally, we present a DGOM-based strategy for addressing key questions in ocean biogeochemistry. This paper thus presents ongoing work in ocean biogeochemical modeling, which, it is hoped will motivate international collaborations to improve our understanding of the role of the ocean in the climate system.
    Type of Medium: Electronic Resource
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  • 2
    Publication Date: 2022-05-25
    Description: © 2008 Author(s). This work is distributed under the Creative Commons Attribution License. The definitive version was published in Biogeosciences 5 (2008): 95-109, doi:10.5194/bg-5-95-2008
    Description: Due to the low atmospheric input of phosphate into the open ocean, it is one of the key nutrients that could ultimately control primary production and carbon export into the deep ocean. The observed trend over the last 20 years has shown a decrease in the dissolved inorganic phosphate (DIP) pool in the North Pacific gyre, which has been correlated to the increase in di-nitrogen (N2) fixation rates. Following a NW-SE transect, in the Southeast Pacific during the early austral summer (BIOSOPE cruise), we present data on DIP, dissolved organic phosphate (DOP) and particulate phosphate (PP) pools along with DIP turnover times (TDIP) and N2 fixation rates. We observed a decrease in DIP concentration from the edges to the centre of the gyre. Nevertheless the DIP concentrations remained above 100 nmol L−1 and T DIP was more than 6 months in the centre of the gyre; DIP availability remained largely above the level required for phosphate limitation to occur and the absence of Trichodesmium spp and low nitrogen fixation rates were likely to be controlled by other factors such as temperature or iron availability. This contrasts with recent observations in the North Pacific Ocean at the ALOHA station and in the western Pacific Ocean at the same latitude (DIAPALIS cruises) where lower DIP concentrations (〈20 nmol L−1) and T DIP 〈50 h were measured during the summer season in the upper layer. The South Pacific gyre can be considered a High Phosphate Low Chlorophyll (HPLC) oligotrophic area, which could potentially support high N2 fixation rates and possibly carbon dioxide sequestration, if the primary ecophysiological controls, temperature and/or iron availability, were alleviated.
    Description: This research was funded by the Centre National de la Recherche Scientifique (CNRS), the Institut des Sciences de l’Univers (INSU), the Centre National d’Etudes Spatiales (CNES), the European Space Agency (ESA), The National Aeronautics and Space Administration (NASA) and the Natural Sciences and Engineering Research Council of Canada (NSERC). This work is funded in part by the French Research and Education council.
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Format: application/pdf
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  • 3
    Publication Date: 2022-05-26
    Description: © 2007 Author(s) et al. This is an open-access article distributed under the terms of a Creative Commons License. The definitive version was published in Biogeosciences 4 (2007): 941-956, doi:10.5194/bg-4-941-2007
    Description: Predicting heterotrophic bacteria and phytoplankton specific growth rates (μ) is of great scientific interest. Many methods have been developed in order to assess bacterial or phytoplankton μ. One widely used method is to estimate μ from data obtained on biomass or cell abundance and rates of biomass or cell production. According to Kirchman (2002), the most appropriate approach for estimating μ is simply to divide the production rate by the biomass or cell abundance estimate. Most methods using this approach to estimate μ are based on carbon (C) incorporation rates and C biomass measurements. Nevertheless it is also possible to estimate μ using phosphate (P) data. We showed that particulate phosphate (PartP) can be used to estimate biomass and that the P uptake rate to PartP ratio can be employed to assess μ. Contrary to other methods using C, this estimator does not need conversion factors and provides an evaluation of μ for both autotrophic and heterotrophic organisms. We report values of P-based μ in three size fractions (0.2–0.6; 0.6–2 and 〉2 μm) along a Southeast Pacific transect, over a wide range of P-replete trophic status. P-based μ values were higher in the 0.6–2 μm fraction than in the 〉2 μm fraction, suggesting that picoplankton-sized cells grew faster than the larger cells, whatever the trophic regime encountered. Picoplankton-sized cells grew significantly faster in the deep chlorophyll maximum layer than in the upper part of the photic zone in the oligotrophic gyre area, suggesting that picoplankton might outcompete 〉2 μm cells in this particular high-nutrient, low-light environment. P-based μ attributed to free-living bacteria (0.2-0.6 μm) and picoplankton (0.6–2 μm) size-fractions were relatively low (0.11±0.07 d−1 and 0.14±0.04 d−1, respectively) in the Southeast Pacific gyre, suggesting that the microbial community turns over very slowly.
    Description: This research was funded by the Centre National de la Recherche Scientifique (CNRS), the Institut des Sciences de l’Univers (INSU), the Centre National d’Etudes Spatiales (CNES), the European Space Agency (ESA), The National Aeronautics and Space Administration (NASA) and the Natural Sciences and Engineering Research Council of Canada (NSERC). This work is funded in part by the French Research and Education council.
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Format: application/pdf
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  • 4
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    In:  Supplement to: Stramski, Dariusz; Reynolds, Rick A; Babin, Marcel; Kaczmarek, S; Lewis, Marlon R; Röttgers, Rüdiger; Sciandra, Antoine; Stramska, M; Twardowski, Michael S; Franz, B A; Claustre, Hervé (2008): Relationships between the surface concentration of particulate organic carbon and optical properties in the eastern South Pacific and eastern Atlantic Oceans. Biogeosciences, 5, 171-201, https://doi.org/10.5194/bg-5-171-2008
    Publication Date: 2024-05-11
    Description: We have examined several approaches for estimating the surface concentration of particulate organic carbon, POC, from optical measurements of spectral remote-sensing reflectance, Rrs(Lambda), using field data collected in tropical and subtropical waters of the eastern South Pacific and eastern Atlantic Oceans. These approaches include a direct empirical relationship between POC and the blue-to-green band ratio of reflectance, Rrs(Lambda B)/Rrs(555), and two-step algorithms that consist of relationships linking reflectance to an inherent optical property IOP (beam attenuation or backscattering coefficient) and POC to the IOP. We considered two-step empirical algorithms that exclusively include pairs of empirical relationships and two-step hybrid algorithms that consist of semianalytical models and empirical relationships. The surface POC in our data set ranges from about 10 mg/m**3 within the South Pacific Subtropical Gyre to 270 mg/m**3 in the Chilean upwelling area, and ancillary data suggest a considerable variation in the characteristics of particulate assemblages in the investigated waters. The POC algorithm based on the direct relationship between POC and Rrs(Lambda B)/Rrs(555) promises reasonably good performance in the vast areas of the open ocean covering different provinces from hyperoligotrophic and oligotrophic waters within subtropical gyres to eutrophic coastal upwelling regimes characteristic of eastern ocean boundaries. The best error statistics were found for power function fits to the data of POC vs. Rrs(443)/Rrs(555) and POC vs. Rrs(490)/Rrs(555). For our data set that includes over 50 data pairs, these relationships are characterized by the mean normalized bias of about 2% and the normalized root mean square error of about 20%. We recommend that these algorithms be implemented for routine processing of ocean color satellite data to produce maps of surface POC with the status of an evaluation data product for continued work on algorithm development and refinements. The two-step algorithms also deserve further attention because they can utilize various models for estimating IOPs from reflectance, offer advantages for developing an understanding of bio-optical variability underlying the algorithms, and provide flexibility for regional or seasonal parameterizations of the algorithms.
    Keywords: ANT-XXIII/1; Bay of Biscay; Canarias Sea; Celtic Sea; CT; CTD/Rosette; CTD-RO; English Channel; Light meter; LM; MSD; Multi Sensor Device; Polarstern; PS69; PS69/001-1; PS69/001-2; PS69/001-3; PS69/002-1; PS69/002-2; PS69/002-3; PS69/004-1; PS69/004-2; PS69/004-3; PS69/005-1; PS69/005-2; PS69/005-3; PS69/006-5; PS69/006-6; PS69/006-7; PS69/007-1; PS69/007-2; PS69/007-3; PS69/008-1; PS69/008-2; PS69/008-3; PS69/009-1; PS69/009-2; PS69/009-3; PS69/010-1; PS69/010-2; PS69/010-3; PS69/011-4; PS69/011-5; PS69/012-1; PS69/012-2; PS69/012-3; PS69/013-1; PS69/013-2; PS69/013-3; PS69/014-2; PS69/014-6; PS69/014-7; PS69/014-8; PS69/015-1; PS69/015-2; PS69/015-3; PS69/016-1; PS69/016-2; PS69/016-3; PS69/017-1; PS69/017-2; PS69/017-3; PS69/018-2; PS69/018-5; PS69/018-6; PS69/019-1; PS69/019-2; PS69/019-3; PS69/020-1; PS69/020-2; PS69/020-3; PS69/021-2; PS69/021-4; PS69/021-7; PS69/021-8; PS69/022-1; PS69/022-2; PS69/022-3; PS69/023-1; PS69/023-2; PS69/023-3; PS69/024-1; PS69/024-2; PS69/024-3; PS69/025-1; PS69/025-2; PS69/025-4; PS69/026-2; PS69/026-6; PS69/027-1; PS69/027-2; PS69/027-3; PS69/1-track; PS69/Fish; PS69/Snorkel; South Atlantic Ocean; Underway cruise track measurements
    Type: Dataset
    Format: application/zip, 11 datasets
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  • 5
    Publication Date: 2024-05-11
    Keywords: ANT-XXIII/1; Carbon, organic, particulate; CT; DATE/TIME; DEPTH, water; Element analyser CHN; LATITUDE; LONGITUDE; Nitrogen, organic, particulate; Polarstern; PS69; PS69/1-track; Sample code/label; Underway cruise track measurements
    Type: Dataset
    Format: text/tab-separated-values, 99 data points
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  • 6
    Publication Date: 2024-05-11
    Keywords: ANT-XXIII/1; Bay of Biscay; Canarias Sea; Carbon, organic, particulate; Celtic Sea; CTD/Rosette; CTD-RO; Date/Time of event; DEPTH, water; Element analyser CHNS; Elevation of event; English Channel; Event label; Latitude of event; Longitude of event; Nitrogen, organic, particulate; Polarstern; PS69; PS69/001-3; PS69/002-3; PS69/004-3; PS69/005-3; PS69/006-7; PS69/007-3; PS69/008-3; PS69/009-3; PS69/010-3; PS69/011-5; PS69/012-3; PS69/013-3; PS69/014-2; PS69/015-3; PS69/016-3; PS69/017-3; PS69/018-2; PS69/019-3; PS69/020-3; PS69/021-2; PS69/022-3; PS69/023-3; PS69/024-3; PS69/025-2; PS69/026-2; PS69/027-3; South Atlantic Ocean
    Type: Dataset
    Format: text/tab-separated-values, 240 data points
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  • 7
    Publication Date: 2024-05-11
    Keywords: ANT-XXIII/1; Backscattering meter, HydroScat-6; Bay of Biscay; Canarias Sea; Celtic Sea; CTD/Rosette; CTD-RO; Date/Time of event; DEPTH, water; Elevation of event; English Channel; Event label; Latitude of event; Longitude of event; MSD; Multi Sensor Device; Optical backscattering coefficient, 420 nm; Optical backscattering coefficient, 442 nm; Optical backscattering coefficient, 470 nm; Optical backscattering coefficient, 510 nm; Optical backscattering coefficient, 550 nm; Optical backscattering coefficient, 589 nm; Optical backscattering coefficient, 620 nm; Optical backscattering coefficient, 671 nm; Polarstern; PS69; PS69/001-1; PS69/002-1; PS69/004-1; PS69/005-1; PS69/006-5; PS69/007-2; PS69/008-1; PS69/009-1; PS69/010-1; PS69/011-5; PS69/012-1; PS69/013-1; PS69/014-6; PS69/015-1; PS69/016-1; PS69/017-1; PS69/018-5; PS69/019-1; PS69/020-1; PS69/021-7; PS69/022-1; PS69/023-1; PS69/024-1; PS69/025-4; PS69/026-6; PS69/027-1; South Atlantic Ocean
    Type: Dataset
    Format: text/tab-separated-values, 41572 data points
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  • 8
    Publication Date: 2024-05-11
    Keywords: ANT-XXIII/1; Bay of Biscay; Canarias Sea; Celtic Sea; Date/Time of event; DEPTH, water; Elevation of event; English Channel; Event label; Latitude of event; Light meter; LM; Longitude of event; Polarstern; PS69; PS69/001-2; PS69/002-2; PS69/004-2; PS69/005-2; PS69/006-6; PS69/007-1; PS69/008-2; PS69/009-2; PS69/010-2; PS69/011-4; PS69/012-2; PS69/013-2; PS69/014-8; PS69/015-2; PS69/016-2; PS69/017-2; PS69/019-2; PS69/020-2; PS69/021-4; PS69/022-2; PS69/023-2; PS69/024-2; PS69/025-1; PS69/027-2; Radiance, upward at 339 nm; Radiance, upward at 380 nm; Radiance, upward at 412 nm; Radiance, upward at 442 nm; Radiance, upward at 470 nm; Radiance, upward at 490 nm; Radiance, upward at 509 nm; Radiance, upward at 532 nm; Radiance, upward at 554 nm; Radiance, upward at 589 nm; Radiance, upward at 620 nm; Radiance, upward at 665 nm; Radiance, upward at 683 nm; Roll angle; Sample code/label; SeaWiFS Profiling Multichannel Radiometer (SPMR); South Atlantic Ocean; Spectral irradiance, downward at 339 nm; Spectral irradiance, downward at 380 nm; Spectral irradiance, downward at 412 nm; Spectral irradiance, downward at 442 nm; Spectral irradiance, downward at 470 nm; Spectral irradiance, downward at 490 nm; Spectral irradiance, downward at 509 nm; Spectral irradiance, downward at 532 nm; Spectral irradiance, downward at 554 nm; Spectral irradiance, downward at 589 nm; Spectral irradiance, downward at 620 nm; Spectral irradiance, downward at 665 nm; Spectral irradiance, downward at 683 nm; Tilt angle
    Type: Dataset
    Format: text/tab-separated-values, 123306 data points
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  • 9
    Publication Date: 2024-05-11
    Keywords: ANT-XXIII/1; Backscattering meter, HydroScat-6; Bay of Biscay; Canarias Sea; Celtic Sea; Date/Time of event; DEPTH, water; Elevation of event; English Channel; Event label; Latitude of event; Longitude of event; MSD; Multi Sensor Device; Optical backscattering coefficient, 420 nm; Optical backscattering coefficient, 442 nm; Optical backscattering coefficient, 470 nm; Optical backscattering coefficient, 510 nm; Optical backscattering coefficient, 550 nm; Optical backscattering coefficient, 589 nm; Optical backscattering coefficient, 620 nm; Optical backscattering coefficient, 671 nm; Polarstern; PS69; PS69/001-1; PS69/002-1; PS69/004-1; PS69/005-1; PS69/006-5; PS69/007-2; PS69/008-1; PS69/009-1; PS69/010-1; PS69/012-1; PS69/013-1; PS69/014-6; PS69/015-1; PS69/017-1; PS69/018-5; PS69/019-1; PS69/020-1; PS69/021-7; PS69/022-1; PS69/023-1; PS69/024-1; PS69/025-4; PS69/026-6; PS69/027-1; South Atlantic Ocean
    Type: Dataset
    Format: text/tab-separated-values, 37568 data points
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  • 10
    Publication Date: 2024-05-11
    Keywords: ANT-XXIII/1; Bay of Biscay; Canarias Sea; Celtic Sea; CTD/Rosette; CTD-RO; Date/Time of event; DEPTH, water; Elevation of event; English Channel; Event label; Latitude of event; Longitude of event; MSD; Multi Sensor Device; Optical beam attenuation coefficient with pure seawater subtracted at 488 nm; Optical beam attenuation coefficient with pure seawater subtracted at 660 nm; Polarstern; PS69; PS69/001-1; PS69/002-1; PS69/004-1; PS69/005-1; PS69/006-5; PS69/007-2; PS69/008-1; PS69/009-1; PS69/010-1; PS69/011-5; PS69/012-1; PS69/013-1; PS69/014-6; PS69/015-1; PS69/016-1; PS69/017-1; PS69/018-5; PS69/019-1; PS69/020-1; PS69/021-7; PS69/022-1; PS69/023-1; PS69/024-1; PS69/025-4; PS69/026-6; PS69/027-1; South Atlantic Ocean; Transmissometer, WET Labs, C-Star
    Type: Dataset
    Format: text/tab-separated-values, 10438 data points
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