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  • 11
    Online Resource
    Online Resource
    Frontiers Media SA ; 2022
    In:  Frontiers in Marine Science Vol. 9 ( 2022-10-3)
    In: Frontiers in Marine Science, Frontiers Media SA, Vol. 9 ( 2022-10-3)
    Abstract: Understanding seasonal and multiyear variability of primary producers’ populations in the Mauritanian coastal upwelling system along the northwestern African margin may help to predict future impact of climate change (e.g., nutrient availability, productivity, and phyto- and zooplankton dynamics). For this, continuous, long time-series are required. A major challenge in obtaining these time-series is the logistics associated with the uninterrupted, in-situ sampling over several years. Sediment traps represent a reliable alternative. In this study, we assess the variations of the diatom community in samples almost continuously collected between June 2003 and March 2020 with 17 sediment traps deployed at site CBeu (=Cape Blanc eutrophic), located at c. 20°N-18°45’W, offshore Mauritania in the Canary Current Eastern Boundary Upwelling Ecosystems (CC-EBUE). In addition to describing the multiyear dynamics of the total diatom flux and major shifts in the species-specific composition of the populations, our study addresses questions such as ( i ) how constant is the intrannual pattern of populations’ occurrence, ( ii ) what the amplitude of annual changes is, and ( iii ) how populations’ shifts relate to physical setting dynamics. Matching the occurrence of most intense seasonal upwelling, highest diatom flux maxima mainly occur in spring and summer between 2003 and 2020. The diverse diatom community (e.g., benthic, coastal upwelling, coastal planktonic, and open-ocean diatoms) closely follows the annual cycle of atmospheric and hydrologic conditions. Benthic diatoms dominate during spring and summer (e.g., upwelling season), while open-ocean diatoms contribute the most in fall and winter when the upper water column stratifies. As no persistent –either decreasing or increasing trend of diatom productivity over the 17 sampled years, our results are at odds with Bakun’s hypothesis of upwelling intensification. Anchoring temporal changes of diatoms in a wider environmental frame allows for insights into the complex dynamics of the Mauritanian upwelling ecosystem and the populations’ response to climate forcing. This helps in establishing the scientific basis for modeling future states of the CC-EBUE and/or comparable environments.
    Type of Medium: Online Resource
    ISSN: 2296-7745
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2757748-X
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  • 12
    In: Deep Sea Research Part I: Oceanographic Research Papers, Elsevier BV, Vol. 117 ( 2016-11), p. 107-119
    Type of Medium: Online Resource
    ISSN: 0967-0637
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2016
    detail.hit.zdb_id: 1500309-7
    detail.hit.zdb_id: 1146810-5
    SSG: 14
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  • 13
    Online Resource
    Online Resource
    Springer Science and Business Media LLC ; 2020
    In:  Scientific Reports Vol. 10, No. 1 ( 2020-04-08)
    In: Scientific Reports, Springer Science and Business Media LLC, Vol. 10, No. 1 ( 2020-04-08)
    Abstract: While Ocean modeling has made significant advances over the last decade, its complex biological component is still oversimplified. In particular, modeling organisms in the ocean system must integrate parameters to fit both physiological and ecological behaviors that are together very difficult to determine. Such difficulty occurs for modeling Pelagia noctiluca . This jellyfish has a high abundance in the Mediterranean Sea and could contribute to several biogeochemical processes. However, gelatinous zooplanktons remain poorly represented in biogeochemical models because uncertainties about their ecophysiology limit our understanding of their potential role and impact. To overcome this issue, we propose, for the first time, the use of the Statistical Model Checking Engine (SMCE), a probability-based computational framework that considers a set of parameters as a whole. Contrary to standard parameter inference techniques, SMCE identifies sets of parameters that fit both laboratory-culturing observations and in situ patterns while considering uncertainties. Doing so, we estimated the best parameter sets of the ecophysiological model that represents the jellyfish growth and degrowth in laboratory conditions as well as its size. Behind this application, SMCE remains a computational framework that supports the projection of a model with uncertainties in broader contexts such as biogeochemical processes to drive future studies.
    Type of Medium: Online Resource
    ISSN: 2045-2322
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2020
    detail.hit.zdb_id: 2615211-3
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