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    QUANTIFYING NITROGEN REMOVAL POTENTIAL OF BOTTOM CAGE (C. VIRGINICA) AQUACULTURE

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    No. of downloads: 35

    Date
    2022
    Author
    Shenoy, Stefenie
    Advisor
    Harris, Lora A
    Testa, Jeremy M
    DRUM DOI
    https://doi.org/10.13016/he7s-fzar
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    Abstract
    While management strategies for human-caused nutrient pollution have improved over the last decade, eutrophication and its ecological effects remain primary concerns in many coastal marine systems. In-water nutrient removal techniques are being explored for potential use as a management strategy, including oyster aquaculture operations. Where abundant, oysters have been shown to exhibit denitrifying potential beyond that which is assimilated into shell and tissue biomass. While nitrogen cycling dynamics are well studied and modeled on natural and restored reefs, equivalent processes within oyster aquaculture operations are less defined. This study adapts an existing mechanistic model of oyster filtration, biodeposition, and particle transport to capture the influence of an aquaculture farm on local sediment-water chemical fluxes. Modifications included (1) revising the spatial domain to represent an array of bottom cages, and (2) integrating an existing bioenergetics module to mechanistically couple simulated seston removal from the water column via filtration and subsequent biodeposition by simulating oyster growth. Model simulations included a variety of oyster densities, farm sizes, natural reef, and no oyster scenarios. Two seasonal sampling campaigns of a bottom cage aquaculture site provided model forcing and validation data. Model output revealed complex relationships among oyster density and distribution, farm size, oyster growth and biodeposition. The estimated rates of net nitrogen removal suggest increased potential for oyster aquaculture operations to receive credits above what is currently being realized, and the calculations of such removal for management purposes should consider lease-specific configurations and environmental parameters.
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    http://hdl.handle.net/1903/29418
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    DRUM is brought to you by the University of Maryland Libraries
    University of Maryland, College Park, MD 20742-7011 (301)314-1328.
    Please send us your comments.
    Web Accessibility