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    AuthorBrewin, Robert J.W. (1)Gittings, John (1)Hoteit, Ibrahim (1)Jones, Burton (1)Kheireddine, Malika (1)View MoreDepartmentBiological and Environmental Sciences and Engineering (BESE) Division (1)Earth Science and Engineering Program (1)Marine Science Program (1)Physical Sciences and Engineering (PSE) Division (1)Red Sea Research Center (RSRC) (1)JournalRemote Sensing of Environment (1)KAUST Acknowledged Support UnitAnalytical Core Lab (1)KAUST baseline fund (1)KAUST Coastal and Marine Resources Core Lab (1)
    KAUST Office of Sponsored Research (OSR) (1)
    KAUST Grant Number
    REP/1/3268-01-01 (1)
    URF/1/2979-01-01 (1)PublisherElsevier BV (1)SubjectChlorophyll (1)Ocean colour (1)Phytoplankton (1)Red Sea (1)Remote sensing (1)View MoreTypeArticle (1)Year (Issue Date)2019 (1)Item AvailabilityEmbargoed (1)

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    Remotely sensing phytoplankton size structure in the Red Sea

    Gittings, John; Brewin, Robert J.W.; Raitsos, Dionysios E.; Kheireddine, Malika; Ouhssain, Mustapha; Jones, Burton; Hoteit, Ibrahim (Remote Sensing of Environment, Elsevier BV, 2019-10-09) [Article]
    Phytoplankton size structure impacts ocean food-web dynamics and biogeochemical cycling, and is thus an important ecological indicator that can be utilised to quantitatively evaluate the state of marine ecosystems. Potential alterations to size structure are predicted to occur in tropical regions under future scenarios of climate change. Therefore, there is an increasing requirement for the synoptic monitoring of phytoplankton size structure in marine systems. The Red Sea remains a comparatively unexplored tropical marine ecosystem, particularly with regards to its large-scale biological dynamics. Using an in situ pigment dataset acquired in the Red Sea, we parameterise a two-component, abundance-based phytoplankton size model and apply it to remotely-sensed observations of chlorophyll-a (Chl-a) concentration, to infer Chl-a in two size classes of phytoplankton, small cells <2 μm in size (picophytoplankton) and large cells >2 μm in size. Satellite-derived estimates of phytoplankton size structure are in good agreement with corresponding in situ measurements and also capture the spatial variability related to regional mesoscale dynamics. Our analysis reveals that, for the estimation of Chl-a in the two size classes, the model performs comparably or in some cases better, to validations in other oceanic regions. Our model parameterisation will be useful for future studies on the seasonal and interannual variability of phytoplankton size classes in the Red Sea, which may ultimately be relevant for understanding trophic linkages between phytoplankton size structure and fisheries, and the development of marine management strategies.
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