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  • 1
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    PANGAEA
    In:  Supplement to: Sauzède, Raphaëlle; Lavigne, Héloise; 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
    Publication Date: 2019-02-11
    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268,127 vertical in situ fluorescence profiles obtained from several available online databases and from published and unpublished individual sources.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.
    Type: Dataset
    Format: application/zip, 639.0 MBytes
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  • 2
  • 3
    facet.materialart.
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    PANGAEA
    In:  Supplement to: Sauzède, Raphaëlle; Lavigne, Héloise; 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
    Publication Date: 2019-02-11
    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.
    Type: Dataset
    Format: application/zip, 397.0 MBytes
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  • 4
    Publication Date: 2017-01-24
    Description: Ocean color remote sensing of chlorophyll concentration has revolutionized our understanding of the biology of the oceans. However, a comprehensive understanding of the structure and function of oceanic ecosystems requires the characterization of the spatio-temporal variability of various phytoplankton functional types (PFTs), which have differing biogeochemical roles. Thus, recent bio-optical algorithm developments have focused on retrieval of various PFTs. It is important to validate and inter-compare the existing PFT algorithms; however direct comparison of retrieved variables is non-trivial because in those algorithms PFTs are defined differently. Thus, it is more plausible and potentially more informative to focus on emergent properties of PFTs, such as phenology. Furthermore, ocean color satellite PFT data sets can play a pivotal role in informing and/or validating the biogeochemical routines of Earth System Models. Here, the phenological characteristics of 10 PFT satellite algorithms and 7 latest-generation climate models from the Coupled Model Inter-comparison Project (CMIP5) are intercompared as part of the International Satellite PFT Algorithm Inter-comparison Project. The comparison is based on monthly satellite data (mostly SeaWiFS) for the 2003–2007 period. The phenological analysis is based on the fraction of microplankton or a similar variable for the satellite algorithms and on the carbon biomass due to diatoms for the climate models. The seasonal cycle is estimated on a per-pixel basis as a sumof sinusoidal harmonics, derived from the Discrete Fourier Transform of the variable time series. Peak analysis is then applied to the estimated seasonal signal and the following phenological parameters are quantified for each satellite algorithm and climate model: seasonal amplitude, percent seasonal variance, month of maximum, and bloom duration. Secondary/double blooms occur in many areas and are also quantified. The algorithms and the models are quantitatively compared based on these emergent phenological parameters. Results indicate that while algorithms agree to a first order on a global scale, large differences among themexist; differences are analyzed in detail for two Longhurst regions in the North Atlantic: North Atlantic Drift Region (NADR) and North Atlantic Subtropical Gyre West (NASW). Seasonal cycles explain the most variance in zonal bands in the seasonally-stratified subtropics at about 30° latitude in the satellite PFT data. The CMIP5 models do not reproduce this pattern, exhibiting higher seasonality in mid and high-latitudes and generally much more spatially homogeneous patterns in phenological indices compared to satellite data. Satellite data indicate a complex structure of double blooms in the Equatorial region and mid-latitudes, and single blooms on the poleward edges of the subtropical gyres. In contrast, the CMIP5 models showsingle annual blooms over most of the ocean except for the Equatorial band and Arabian Sea.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , NonPeerReviewed
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  • 5
    Publication Date: 2019-02-13
    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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  • 6
    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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  • 7
    Publication Date: 2018-06-06
    Description: The objective of the present study is to examine the potential of using the near-surface total chlorophyll a concentration (C(sub surf)), as it can be derived from ocean color observation, to infer the column-integrated and the vertical distribution of the phytoplanktonic biomass, both in a quantitative way and in a qualitative way (z.e., in terms of community structure). Within this context, a large HPLC (High Performance Liquid Chromatography) pigment database has been analyzed. It includes 2419 vertical pigment profiles, all sampled in Case-1 waters with various trophic states. The relationshps between C(sub surf) and the total chlorophyll alpha vertical distribution, as previously derived by Morel and Berthon, are fully confirmed, as the present results coincide with the previous ones. This agreement allows to go further, namely to examine the possibility of extracting relationships between C(sub surf) and the vertical composition of the algal assemblages. Thanks to the detailed pigment composition available from HPLC measurements, the contribution of three size classes (micro-, nano-, and pico-phytoplankton) to the local total chlorophyll a concentration can be assessed. Corroborating previous findings (e.g., large species dominate in eutrophc environments, whereas tiny phytoplankton prevail in oligotrophic zones), the results lead to a statistically based parameterization. The predictive skill of this parameterization is successfully tested on a separate data set. With such a tool, the vertical total chlorophyll a profiles associated with each size class can be inferred from the sole knowledge of C(sub surf). By combining this tool with satellite ocean color data, it becomes conceivable to quantify on a global scale the phytoplankton biomass associated with each of the three size classes.
    Keywords: Exobiology
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  • 8
    Publication Date: 2014-07-23
    Description: The concept of phytoplankton functional types has emerged as a useful approach to classifying phytoplankton. It finds many applications in addressing some serious contemporary issues facing science and society. Its use is not without challenges, however. As noted earlier, there is no universally-accepted set of functional types, and the types used have to be carefully selected to suit the particular problem being addressed. It is important that the sum total of all functional types matches all phytoplankton under consideration. For example, if in a biogeochemical study, we classify phytoplankton as silicifiers, calcifiers, DMS-producers and nitrogen fix- ers, then there is danger that the study may neglect phytoplankton that do not contribute in any significant way to those functions, but may nevertheless be a significant contributor to, say primary production. Such considerations often lead to the adoption of a category of “other phytoplankton” in models, with no clear defining traits assigned them, but that are nevertheless necessary to close budgets on phytoplankton processes. Since this group is a collection of all phytoplankton that defy classification according to a set of traits, it is difficult to model their physi- ological processes. Our understanding of the diverse functions of phytoplankton is still growing, and as we recognize more functions, there will be a need to balance the desire to incorporate the increasing number of functional types in models against observational challenges of identifying and mapping them adequately. Modelling approaches to dealing with increasing functional diversity have been proposed, for example, using the complex adaptive systems theory and system of infinite diversity, as in the work of Bruggemann and Kooijman (2007). But it is unlikely that remote-sensing approaches might be able to deal with anything but a few prominent functional types. As long as these challenges are explicitly addressed, the functional- type concept should continue to fill a real need to capture, in an economic fashion, the diversity in phytoplankton, and remote sensing should continue to be a useful tool to map them. Remote sensing of phytoplankton functional types is an emerging field, whose potential is not fully realised, nor its limitations clearly established. In this report, we provide an overview of progress to date, examine the advantages and limitations of various methods, and outline suggestions for further development. The overview provided in this chapter is intended to set the stage for detailed considerations of remote-sensing applications in later chapters. In the next chapter, we examine various in situ methods that exist for observing phytoplankton functional types, and how they relate to remote-sensing techniques. In the subsequent chapters, we review the theoretical and empirical bases for the existing and emerging remote-sensing approaches; assess knowledge about the limitations, assumptions, and likely accuracy or predictive skill of the approaches; provide some preliminary comparative analyses; and look towards future prospects with respect to algorithm development, validation studies, and new satellite mis- sions.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Inbook , NonPeerReviewed
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  • 9
    Publication Date: 2017-01-24
    Description: The IOCCG-supported workshop “Phytoplankton Composition from Space: towards a validation strategy for satellite algorithms” was organized as a follow-up to the Phytoplankton Functional Types from Space splinter session, held at the International Ocean Colour Science Meeting (Germany, 2013). The specific goals of the workshop were to: 1. Provide a summary of the status of activities from relevant IOCCG working groups, the 2nd PFT intercomparison working group, PFT validation data sets and other research developments. 2. Provide a PFT validation strategy that considers the different applications of PFT products: and seeks community consensus on datasets and analysis protocols. 3. Discuss possibilities for sustaining ongoing PFT algorithm validation and intercomparison activities. The workshop included 15 talks, breakout sessions and plenary discussions. Talks covered community algorithm intercomparison activity updates, review of established and novel methods for PFT validation, validation activities for specific applications and space-agency requirements for PFT products and validation. These were followed by general discussions on (a) major recommendations for global intercomparison initiative in respect to validation, intercomparison and user’s guide; (b) developing a community consensus on which data sets for validation are optimal and which measurement and analysis protocols should be followed to support sustained validation of PFT products considering different applications; (c) the status of different validation data bases and measurement protocols for different PFT applications, and (d) engagement of the various user communities for PFT algorithms in developing PFT product specifications. From these discussions, two breakout groups provided in depth discussion and recommendations on (1) validation of current algorithms and (2) work plan to prepare for validation of future missions. Breakout group 1 provided an action list for progressing the current international community validation and intercomparison activity. Breakout group 2 provided the following recommendations towards developing a future validation strategy for satellite PFT products: 1. Establish a number of validation sites that maintain measurements of a key set of variables. 2. This set of variables should include: • Phytoplankton pigments from HPLC, phycobilins from spectrofluorometry • Phytoplankton cell counts and ID, volume / carbon estimation and imaging (e.g. from flow cytometry, FlowCam, FlowCytobot type technologies) • Inherent optical properties (e.g. absorption, backscattering, VSF) • Hyperspectral radiometry (both above and in-water) • Particle size distribution • Size-fractionated measurements of pigments and absorption • Genetic / -omics data 3. Undertake an intercomparison of methods / instruments over several years at a few sites to understand our capabilities to fully characterize the phytoplankton community. 4. Organise workshops to address the following topics: • Techniques for particle analysis, characterization and classification • Engagement with modellers and understanding end-user requirements • Data storage and management, standards for data contributors, data challenges In conclusion, the workshop was assessed to have fulfilled its goals. A follow-on meeting will be organized during the International Ocean Colour Science Meeting 2015 in San Francisco. Specific follow-on actions are listed at the end of the report.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Book , NonPeerReviewed
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  • 10
    Publication Date: 2017-03-06
    Description: To improve our understanding of the role of phytoplankton for marine ecosystems and global biogeochemical cycles, information on the global distribution of major phytoplankton groups is essential. Although algorithms have been developed to assess phytoplankton diversity from space for over two decades, so far the application of these data sets has been limited. This scientific roadmap identifies user needs, summarizes the current state of the art, and pinpoints major gaps in long-term objectives to deliver space-derived phytoplankton diversity data that meets the user requirements. These major gaps in using ocean color to estimate phytoplankton community structure were identified as: (a) the mismatch between satellite, in situ and model data on phytoplankton composition, (b) the lack of quantitative uncertainty estimates provided with satellite data, (c) the spectral limitation of current sensors to enable the full exploitation of backscattered sunlight, and (d) the very limited applicability of satellite algorithms determining phytoplankton composition for regional, especially coastal or inland, waters. Recommendation for actions include but are not limited to: (i) an increased communication and round-robin exercises among and within the related expert groups, (ii) the launching of higher spectrally and spatially resolved sensors, (iii) the development of algorithms that exploit hyperspectral information, and of (iv) techniques to merge and synergistically use the various streams of continuous information on phytoplankton diversity from various satellite sensors' and in situ data to ensure long-term monitoring of phytoplankton composition.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , NonPeerReviewed
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