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  • 1
    Electronic Resource
    Electronic Resource
    Ecosystem dynamics based on plankton functional types for global ocean biogeochemistry models (2005)
    Oxford, UK : Blackwell Science Ltd
    Global change biology 11 (2005), S. 0 
    Details
    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
    URL: http://dx.doi.org/10.1111/j.1365-2486.2005.1004.x
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    Paper (German National Licenses)
    Fulltext
  • 2
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    Globally Consistent Quantitative Observations of Planktonic Ecosystems (2019)
    Frontiers
    In:  Frontiers in Marine Science, 6 . Art.Nr. 196.
    Details
    Publication Date: 2022-01-31
    Description: In this paper we review on the technologies available to make globally quantitative observations of particles, in general, and plankton, in particular, in the world oceans, and for sizes varying from sub-micron to centimeters. Some of these technologies have been available for years while others have only recently emerged. Use of these technologies is critical to improve understanding of the processes that control abundances, distributions and composition of plankton, provide data necessary to constrain and improve ecosystem and biogeochemical models, and forecast changes in marine ecosystems in light of climate change. In this paper we begin by providing the motivation for plankton observations, quantification and diversity qualification on a global scale. We then expand on the state-of-the-art, detailing a variety of relevant and (mostly) mature technologies and measurements, including bulk measurements of plankton, pigment composition, uses of genomic, optical, acoustical methods and analysis using particles counters, flow cytometers and quantitative imaging devices. We follow by highlighting the requirements necessary for a plankton observing system, the approach to achieve it and associated challenges. We conclude with ranked action-item recommendations for the next ten years to move towards our vision of a holistic ocean-wide plankton observing system. Particularly, we suggest to begin with a demonstration project on a GO-SHIP line and/or a long-term observation site and expand from there ensuring that issues associated with methods, observation tools, data analysis, quality assessment and curation are addressed early in the implementation. Global coordination is key for the success of this vision and will bring new insights on processes associated with nutrient regeneration, ocean production, fisheries, and carbon sequestration.
    Type: Article , PeerReviewed
    Format: text
    DOI: 10.3389/fmars.2019.00196
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 3
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    Surface ocean microbiota determine cloud precursors (2021)
    Nature Research
    Details
    Publication Date: 2024-02-07
    Description: One pathway by which the oceans influence climate is via the emission of sea spray that may subsequently influence cloud properties. Sea spray emissions are known to be dependent on atmospheric and oceanic physicochemical parameters, but the potential role of ocean biology on sea spray fluxes remains poorly characterized. Here we show a consistent significant relationship between seawater nanophytoplankton cell abundances and sea-spray derived Cloud Condensation Nuclei (CCN) number fluxes, generated using water from three different oceanic regions. This sensitivity of CCN number fluxes to ocean biology is currently unaccounted for in climate models yet our measurements indicate that it influences fluxes by more than one order of magnitude over the range of phytoplankton investigated.
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
    Format: text
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 4
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    Recommendations for Plankton Measurements on OceanSITES Moorings With Relevance to Other Observing Sites (2022)
    Frontiers
    Details
    Publication Date: 2024-02-07
    Description: Measuring plankton and associated variables as part of ocean time-series stations has the potential to revolutionize our understanding of ocean biology and ecology and their ties to ocean biogeochemistry. It will open temporal scales (e.g., resolving diel cycles) not typically sampled as a function of depth. In this review we motivate the addition of biological measurements to time-series sites by detailing science questions they could help address, reviewing existing technology that could be deployed, and providing examples of time-series sites already deploying some of those technologies. We consider here the opportunities that exist through global coordination within the OceanSITES network for long-term (climate) time series station in the open ocean. Especially with respect to data management, global solutions are needed as these are critical to maximize the utility of such data. We conclude by providing recommendations for an implementation plan.
    Type: Article , PeerReviewed
    Format: text
    Location Call Number Limitation Availability
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 5
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    Deep maxima of phytoplankton biomass, primary production and bacterial production in the Mediterranean Sea (2021)
    Copernicus Publications (EGU)
    Details
    Publication Date: 2024-02-07
    Description: The deep chlorophyll maximum (DCM) is a ubiquitous feature of phytoplankton vertical distribution in stratified waters that is relevant to our understanding of the mechanisms that underpin the variability in photoautotroph ecophysiology across environmental gradients and has implications for remote sensing of aquatic productivity. During the PEACETIME (Process studies at the air-sea interface after dust deposition in the Mediterranean Sea) cruise, carried out from 10 May to 11 June 2017, we obtained 23 concurrent vertical profiles of phytoplankton chlorophyll a, carbon biomass and primary production, as well as heterotrophic prokaryotic production, in the western and central Mediterranean basins. Our main aims were to quantify the relative role of photoacclimation and enhanced growth as underlying mechanisms of the DCM and to assess the trophic coupling between phytoplankton and heterotrophic prokaryotic production. We found that the DCM coincided with a maximum in both the biomass and primary production but not in the growth rate of phytoplankton, which averaged 0.3 d−1 and was relatively constant across the euphotic layer. Photoacclimation explained most of the increased chlorophyll a at the DCM, as the ratio of carbon to chlorophyll a (C:Chl a) decreased from ca. 90–100 (g:g) at the surface to 20–30 at the base of the euphotic layer, while phytoplankton carbon biomass increased from ca. 6 mg C m−3 at the surface to 10–15 mg C m−3 at the DCM. As a result of photoacclimation, there was an uncoupling between chlorophyll a-specific and carbon-specific productivity across the euphotic layer. The ratio of fucoxanthin to total chlorophyll a increased markedly with depth, suggesting an increased contribution of diatoms at the DCM. The increased biomass and carbon fixation at the base of the euphotic zone was associated with enhanced rates of heterotrophic prokaryotic activity, which also showed a surface peak linked with warmer temperatures. Considering the phytoplankton biomass and turnover rates measured at the DCM, nutrient diffusive fluxes across the nutricline were able to supply only a minor fraction of the photoautotroph nitrogen and phosphorus requirements. Thus the deep maxima in biomass and primary production were not fuelled by new nutrients but likely resulted from cell sinking from the upper layers in combination with the high photosynthetic efficiency of a diatom-rich, low-light acclimated community largely sustained by regenerated nutrients. Further studies with increased temporal and spatial resolution will be required to ascertain if the peaks of deep primary production associated with the DCM persist across the western and central Mediterranean Sea throughout the stratification season.
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
    Format: text
    Format: text
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 6
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    The MAREDAT global database of high performance liquid chromatography marine pigment measurements - Gridded data product (NetCDF) - Contribution to the MAREDAT World Ocean Atlas of Plankton Functional Types (2013)
    PANGAEA
    Details
    Publication Date: 2023-03-27
    Keywords: MAREMIP; MARine Ecosystem Model Intercomparison Project
    Type: Dataset
    Format: application/zip, 8.5 MBytes
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    DATA PANGAEA
  • 7
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    Phytoplankton pigment concentrations from various expeditions, analysed by HPLC by the Laboratoire d'Oceanographie de Villefranche (LOV) (2013)
    PANGAEA
    In:  Laboratoire d'Océanographie de Villefranche
    Details
    Publication Date: 2023-01-13
    Description: Phytoplankton photosynthetic pigment concentrations from various expeditions, analysed by HPLC by the Laboratoire d'Oceanographie de Villefranche (LOV).
    Type: Dataset
    Format: application/zip, 42 datasets
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    DATA PANGAEA
  • 8
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    Global compilation of chlorophyll fluorescence profiles from several data bases, and from published and unpublished individual sources (2015)
    PANGAEA
    In:  Supplement to: Sauzède, Raphaëlle; Lavigne, Héloïse; Claustre, Hervé; Uitz, Julia; Schmechtig, Catherine; D'Ortenzio, Fabrizio; Guinet, Christophe; Pesant, Stephane (2015): Vertical distribution of chlorophyll a concentration and phytoplankton community composition from in situ fluorescence profiles: a first database for the global ocean. Earth System Science Data, 7(2), 261-273, https://doi.org/10.5194/essd-7-261-2015
    Details
    Publication Date: 2023-02-24
    Description: The present data set includes 268,127 vertical in situ fluorescence profiles obtained from several available online databases and from published and unpublished individual sources. Metadata about each profiles are given in the file provided here in further details. The majority of profiles comes from the National Oceanographic Data Center (NODC) and the fluorescence profiles acquired by Bio-Argo floats available on the Oceanographic Autonomous Observations (OAO) platform (63.7% and 12.5% respectively). Different modes of acquisition were used to collect the data presented in this study: (1) CTD profiles are acquired using a fluorometer mounted on a CTD-rosette; (2) OSD (Ocean Station Data) profiles are derived from water samples and are defined as low resolution profiles; (3) the UOR (Undulating Oceanographic Recorder) profiles are acquired by a 〈fish〉 equipped with a fluorometer and towed by a research vessel; (4) PA profiles are acquired by autonomous platforms (here profiling floats or elephant seals equipped with a fluorometer). Data acquired from gliders are not included in the compilation.
    Keywords: Bio-Argo; French Bio-Argo project (funded by CNES-TOSCA); RemOcean; Remotely Sensed Biogeochemical Cycles in the Ocean
    Type: Dataset
    Format: application/zip, 639.3 MBytes
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    DATA PANGAEA
  • 9
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    Global data product of chlorophyll a concentration and phytoplankton community composition (microphytoplankton, nanophytoplankton and picophytoplankton) computed from in situ fluorescence profiles (2015)
    PANGAEA
    In:  Supplement to: Sauzède, Raphaëlle; Lavigne, Héloïse; Claustre, Hervé; Uitz, Julia; Schmechtig, Catherine; D'Ortenzio, Fabrizio; Guinet, Christophe; Pesant, Stephane (2015): Vertical distribution of chlorophyll a concentration and phytoplankton community composition from in situ fluorescence profiles: a first database for the global ocean. Earth System Science Data, 7(2), 261-273, https://doi.org/10.5194/essd-7-261-2015
    Details
    Publication Date: 2023-02-24
    Description: In vivo chlorophyll a fluorescence, a proxy of chlorophyll a concentration, is one of the most frequently measured biogeochemical property in the ocean. Thousands of profiles are available from historical databases and the integration of fluorescence sensors to autonomous platforms led to a significant increase of chlorophyll fluorescence profiles acquisition. To date, benefits of such numerous data available have not yet been included in global analysis. A total of 268,184 raw chlorophyll fluorescence profiles were collected and subjected to a 10-steps quality control procedure (see supplementary literature publication). The present data product was generated from the remaining 48,600 chlorophyll fluorescence profiles. These were inter-calibrated, converted to total chlorophyll a concentration and phytoplankton community composition (i.e. microphytoplankton, nanophytoplankton and picophytoplankton) using the FLAVOR method (see further details). The data span a time period of 1958-2015, with observations from all oceanic basins and all seasons, and with depths ranging from the surface to a median sampling maximum depth of around 700m. The present data product was obtained by modelling phytoplankton biomass and composition from in situ fluorescence profiles and therefore, individual profiles should NOT BE USED as discrete observations. The correct use of the present data product is to investigate regional or temporal trends, for example to improve the open ocean climatologies of chlorophyll a concentration. This data product is intended as a living data set, with the expectation to retrieve and model additional in situ chlorophyll fluorescence profiles, especially from autonomous acquisition platforms.
    Keywords: Bio-Argo; French Bio-Argo project (funded by CNES-TOSCA); RemOcean; Remotely Sensed Biogeochemical Cycles in the Ocean
    Type: Dataset
    Format: application/zip, 397 MBytes
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    DATA PANGAEA
  • 10
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    Pigment concentration database of the sea surface layer collected during the Tara Pacific Expedition 2016-2018 (2022)
    PANGAEA
    Details
    Publication Date: 2024-01-06
    Description: The Tara Pacific expedition (2016-2018) sampled coral ecosystems around 32 islands in the Pacific Ocean, and sampled the surface of oceanic waters at 249 locations, resulting in the collection of nearly 58,000 samples. The expedition was designed to systematically study corals, fish, plankton, and seawater, and included the collection of samples for advanced biogeochemical, molecular, and imaging analysis. Here we provide a pigment concentrations database originating from 545 stations sampled during the expedition. Pigment were measured by High Performance Liquid Chromatography. This pigment database provides high quality measurements of the major taxonomic pigments including chlorophylls a, b and c, peridinin, 19'-butanoyloxyfucoxanthin, fucoxanthin, neoxanthin, prasinoxanthin, violaxanthin, 19'-hexanoyloxyfucoxanthin, diadinoxanthin, antheraxanthin, alloxanthin, diatoxanthin, zeaxanthin, lutein, divinyl chlorophyll b, chlorophyll b, divinyl chlorophyll a, chlorophyll a, carotene and bacteriochlorophyll a, which can be used to estimate phytoplankton community composition.
    Keywords: 19'-Hexanoyloxy-4-ketofucoxanthin; 19-Butanoyloxyfucoxanthin; 19-Hexanoyloxyfucoxanthin; Alloxanthin; Antheraxanthin; Bacteriochlorophyll a; Carotene; Chlorophyll a; Chlorophyll a + divinyl chlorophyll a + chlorophyllide a; Chlorophyll b; Chlorophyll b + divinyl chlorophyll b; Chlorophyll c1+c2; Chlorophyll c3; Chlorophyllide a; Comment; Depth, bottom/max; Depth, top/min; DEPTH, water; Diadinoxanthin; Diatoxanthin; Divinyl chlorophyll a; DOLPHIN-CARBOY; Environmental feature; Event label; Fondation Tara Expeditions; FondTara; Fucoxanthin; HANDHELD-BUCKET; HANDHELD-NISKIN; High Performance Liquid Chromatography (HPLC); Lutein; Myxoxanthophyll; Neoxanthin; OA000-I00-S00; OA000-I01-S02; OA000-I04-S01; OA000-I04-S02; OA000-I04-S03; OA000-I04-S04; OA000-I05-S01; OA000-I05-S02; OA000-I05-S03; OA000-I06-S01; OA000-I06-S02; OA000-I06-S03; OA000-I07-S01; OA000-I07-S02; OA000-I07-S03; OA000-I08-S01; OA000-I08-S02; OA000-I08-S03; OA000-I09-S01; OA000-I09-S02; OA000-I09-S03; OA000-I10-S01; OA000-I10-S02; OA000-I10-S03; OA000-I12-S01; OA000-I12-S02; OA000-I12-S03; OA000-I13-S01; OA000-I13-S02; OA000-I13-S03; OA000-I14-S01; OA000-I14-S02; OA000-I14-S03; OA000-I15-S01; OA000-I15-S02; OA000-I15-S03; OA000-I16-S01; OA000-I16-S02; OA000-I16-S03; OA000-I17-S01; OA000-I17-S02; OA000-I17-S03; OA000-I18-S01; OA000-I18-S02; OA000-I18-S03; OA000-I19-S01; OA000-I19-S02; OA000-I19-S03; OA000-I19-S04; OA000-I20-S01; OA000-I20-S02; OA000-I20-S03; OA000-I21-S01; OA000-I21-S02; OA000-I21-S03; OA000-I22-S01; OA000-I22-S02; OA000-I22-S03; OA000-I23-S01; OA000-I23-S02; OA000-I23-S03; OA000-I24-S01; OA000-I24-S02; OA000-I24-S03; OA000-I25-S01; OA000-I25-S02; OA000-I25-S03; OA000-I25-S04; OA000-I25-S05; OA000-I26-S01; OA000-I26-S02; OA000-I26-S03; OA000-I27-S01; OA000-I27-S02; OA000-I28-S01; OA000-I28-S02; OA000-I28-S03; OA000-I29-S01; OA000-I29-S02; OA000-I29-S03; OA000-I30-S01; OA000-I30-S02; OA000-I30-S03; OA000-I31-S01; OA000-I31-S02; OA000-I31-S03; OA000-I32-S01; OA000-I32-S02; OA000-I32-S03; OA000-I32-S04; OA000-TS5-S11; OA000-TS5-S12; OA000-TS5-S21; OA000-TS5-S22; OA000-TS5-S31; OA000-TS5-S41; OA000-TS5-S51; OA000-TS6-S11; OA000-TS6-S12; OA000-TS6-S21; OA000-TS6-S22; OA000-TS7-P01; OA000-TS7-P03; OA002-I00-S00; OA003-I00-S00; OA004-I00-S00; OA005-I00-S00; OA006-I00-S00; OA007-I00-S00; OA008-I00-S00; OA009-I00-S00; OA010-I00-S00; OA011-I00-S00; OA012-I00-S00; OA013-I00-S00; OA014-I00-S00; OA015-I00-S00; OA016-I00-S00; OA017-I00-S00; OA018-I00-S00; OA019-I00-S00; OA020-I00-S00; OA021-I00-S00; OA022-I00-S00; OA023-I00-S00; OA024-I00-S00; OA025-I00-S00; OA026-I00-S00; OA027-I00-S00; OA028-I00-S00; OA029-I03-S00; OA030-I03-S00; OA031-I00-S00; OA032-I00-S00; OA033-I00-S00; OA034-I00-S00; OA035-I00-S00; OA036-I00-S00; OA037-I00-S00; OA038-I00-S00; OA039-I00-S00; OA040-I00-S00; OA041-I04-S00; OA042-I04-S00; OA043-I04-S00; OA044-I04-S00; OA045-I00-S00; OA046-I00-S00; OA047-I00-S00; OA048-I05-S00; OA049-I05-S00; OA050-I05-S00; OA051-I00-S00; OA052-I00-S00; OA053-I06-S00; OA054-I06-S00; OA055-I06-S00; OA056-I00-S00; OA057-I00-S00; OA058-I00-S00; OA059-I07-S00; OA060-I07-S00; OA061-I07-S00; OA062-I00-S00; OA063-I08-S00; OA064-I08-S00; OA065-I00-S00; OA066-I09-S00; OA067-I09-S00; OA068-I10-S00; OA069-I10-S00; OA070-I10-S00; OA071-I10-S00; OA072-I11-S00; OA073-I11-S00; OA074-I11-S00; OA075-I12-S00; OA076-I12-S00; OA077-I12-S00; OA078-I00-S00; OA079-I00-S00; OA080-I13-S00; OA081-I13-S00; OA082-I13-S00; OA083-I13-S00; OA084-I00-S00; OA085-I00-S00; OA086-I00-S00; OA087-I00-S00; OA088-I00-S00; OA089-I14-S00; OA090-I14-S00; OA091-I14-S00; OA092-I15-S00; OA093-I15-S00; OA094-I00-S00; OA095-I16-S00; OA096-I00-S00; OA097-I00-S00; OA098-I00-S00; OA099-I00-S00; OA100-I00-S00; OA101-I00-S00; OA102-I00-S00; OA103-I00-S00; OA104-I00-S00; OA105-I00-S00; OA106-I00-S00; OA107-I00-S00; OA108-I00-S00; OA109-I00-S00; OA110-I00-S00; OA111-I00-S00; OA112-I00-S00; OA113-I00-S00; OA114-I00-S00; OA115-I00-S00; OA116-I00-S00; OA117-I00-S00; OA118-I00-S00; OA119-I00-S00; OA121-I00-S00; OA122-I00-S00; OA123-I00-S00; OA124-I00-S00; OA125-I00-S00; OA126-I00-S00; OA127-I18-S00; OA128-I18-S00; OA129-I18-S00; OA130-I18-S00; OA131-I00-S00; OA132-I00-S00; OA133-I00-S00; OA134-I00-S00; OA135-I00-S00; OA136-I00-S00; OA137-I00-S00; OA138-I00-S00; OA139-I00-S00; OA140-I19-S00; OA141-I19-S00; OA142-I19-S00; OA143-I19-S00; OA144-I00-S00; OA145-I20-S00; OA146-I20-S00; OA147-I00-S00; OA148-I21-S00; OA149-I21-S00; OA150-I00-S00; OA151-I00-S00; OA152-I00-S00; OA153-I00-S00; OA154-I00-S00; OA155-I22-S00; OA156-I23-S00; OA157-I23-S00; OA158-I23-S00; OA159-I23-S00; OA160-I24-S00; OA161-I24-S00; OA162-I24-S00; OA164-I00-S00; OA165-I00-S00; OA166-I25-S00; OA167-I26-S00; OA168-I26-S00; OA169-I00-S00; OA170-I27-S00; OA171-I27-S00; OA172-I28-S00; OA173-I00-S00; OA174-I00-S00; OA175-I00-S00; OA176-I00-S00; OA177-I00-S00; OA178-I00-S00; OA179-I00-S00; OA180-I00-S00; OA181-I00-S00; OA182-I00-S00; OA183-I00-S00; OA184-I00-S00; OA185-I00-S00; OA186-I00-S00; OA187-I00-S00; OA188-I00-S00; OA189-I00-S00; OA190-I29-S00; OA191-I29-S00; OA192-I00-S00; OA193-I00-S00; OA194-I00-S00; OA195-I00-S00; OA196-I00-S00; OA197-I00-S00; OA198-I00-S00; OA199-I00-S00; OA202-I00-S00; OA203-I00-S00; OA204-I00-S00; OA205-I00-S00; OA206-I00-S00; OA207-I00-S00; OA208-I00-S00; OA209-I00-S00; OA210-I00-S00; OA211-I00-S00; OA212-I00-S00; OA213-I00-S00; OA214-I00-S00; OA216-I30-S00; OA217-I00-S00; OA218-I00-S00; OA220-I31-S00; OA221-I31-S00; OA222-I00-S00; OA223-I00-S00; OA224-I00-S00; OA225-I00-S00; OA226-I00-S00; OA227-I00-S00; OA228-I00-S00; OA229-I00-S00; OA230-I32-S00; OA232-I32-S00; OA233-I00-S00; OA234-I00-S00; OA235-I00-S00; OA236-I00-S00; OA237-I00-S00; OA238-I00-S00; OA239-I00-S00; OA240-I00-S00; OA241-I00-S00; OA242-I00-S00; OA243-I00-S00; OA244-I00-S00; OA245-I00-S00; OA246-I00-S00; OA247-I00-S00; OA249-I00-S00; Pacific; Peridinin; Phaeophorbide a; Phaeophytin a; Phytoplankton; pigments; Prasinoxanthin; Quality assurance; Quality code; Sample code/label; Sample comment; Sample ID; SCUBA-3X10; SCUBA-PUMP; SV Tara; TARA_20160530T1315Z_D_O-SRF_DOLPHIN-CARBOY; TARA_20160531T1315Z_D_O-SRF_DOLPHIN-CARBOY; TARA_20160601T0804Z_D_O-SRF_DOLPHIN-CARBOY; TARA_20160602T0834Z_D_O-SRF_DOLPHIN-CARBOY; TARA_20160604T0948Z_D_O-SRF_DOLPHIN-CARBOY; TARA_20160606T1034Z_D_O-SRF_DOLPHIN-CARBOY; TARA_20160607T1623Z_D_O-SRF_DOLPHIN-CARBOY; TARA_20160608T1203Z_D_O-SRF_DOLPHIN-CARBOY; TARA_20160609T1040Z_D_O-SRF_DOLPHIN-CARBOY; TARA_20160610T1138Z_D_O-SRF_DOLPHIN-CARBOY; TARA_20160611T1145Z_D_O-SRF_DOLPHIN-CARBOY; TARA_20160613T1333Z_D_O-SRF_DOLPHIN-CARBOY; TARA_20160614T1233Z_D_O-SRF_DOLPHIN-CARBOY; TARA_20160615T1139Z_D_O-SRF_DOLPHIN-CARBOY; TARA_20160616T1205Z_D_O-SRF_DOLPHIN-CARBOY; TARA_20160617T1118Z_D_O-SRF_DOLPHIN-CARBOY; TARA_20160618T1222Z_D_O-SRF_DOLPHIN-CARBOY; TARA_20160619T1845Z_D_O-SRF_HANDHELD-BUCKET; TARA_20160620T1223Z_D_O-SRF_DOLPHIN-CARBOY; TARA_20160621T1258Z_D_O-SRF_DOLPHIN-CARBOY; TARA_20160622T1304Z_D_O-SRF_DOLPHIN-CARBOY; TARA_20160623T1254Z_D_O-SRF_DOLPHIN-CARBOY; TARA_20160624T1304Z_D_O-SRF_DOLPHIN-CARBOY; TARA_20160625T1339Z_D_O-SRF_DOLPHIN-CARBOY; TARA_20160626T1347Z_D_O-SRF_DOLPHIN-CARBOY; TARA_20160627T1249Z_D_O-SRF_DOLPHIN-CARBOY; TARA_20160706T1359Z_D_O-SRF_DOLPHIN-CARBOY; TARA_20160712T1528Z_D_O-SRF_DOLPHIN-CARBOY; TARA_20160718T1408Z_D_C-CSW-C010_SCUBA-PUMP; TARA_20160816T1423Z_D_I-SRF_DOLPHIN-CARBOY; TARA_20160817T1420Z_D_I-SRF_DOLPHIN-CARBOY; TARA_20160818T1624Z_D_O-SRF_DOLPHIN-CARBOY; TARA_20160819T1423Z_D_O-SRF_DOLPHIN-CARBOY; TARA_20160820T1418Z_D_O-SRF_DOLPHIN-CARBOY; TARA_20160822T1415Z_D_O-SRF_DOLPHIN-CARBOY; TARA_20160823T1425Z_D_O-SRF_DOLPHIN-CARBOY; TARA_20160824T1457Z_D_O-SRF_DOLPHIN-CARBOY; TARA_20160825T1432Z_D_O-SRF_DOLPHIN-CARBOY; TARA_20160827T1445Z_D_O-SRF_DOLPHIN-CARBOY; TARA_20160828T1438Z_D_O-SRF_DOLPHIN-CARBOY; TARA_20160829T1419Z_D_O-SRF_DOLPHIN-CARBOY; TARA_20160830T1322Z_D_I-SRF_DOLPHIN-CARBOY; TARA_20160831T0157Z_N_I-SRF_DOLPHIN-CARBOY; TARA_20160831T1333Z_D_I-SRF_DOLPHIN-CARBOY; TARA_20160903T2124Z_D_S-SRF_ZODIAC-PUMP;
    Type: Dataset
    Format: text/tab-separated-values, 34819 data points
    Location Call Number Limitation Availability
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    DATA PANGAEA
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