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Surveys of deepwater surface sediments using a van Veen Grab in Ningaloo Marine Park, Western Australia (WAMSI Node 3 Project 1 Subproject 3.1.1)

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Research Data Australia2024-12-14 收录
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https://researchdata.edu.au/surveys-deepwater-surface-subproject-311/681400
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A total of 335 sediment samples were collected over the 2006/2007 surveys providing broad coverage of Ningaloo Marine Park. Sampling sites were chosen to include geomorphic provinces across the shelf from the base of the fore reef slope/inner shelf to the outer continental shelf/upper slope. A widely spaced systematic grid of samples was used in order to characterise each region and these were stratified by depth contours across the shelf up to the edge of Ningaloo Marine Park State boundary. Positions were fixed using a Global Positioning System (GPS) and imported directly into ArcGISTM for live onboard spatial analysis. Grabs were dropped at or close to towed video stations to obtain habitat linkages to surficial sediment facies, and infer biological activity and sediment transport pathways from sedimentary bedforms identified on the towed video data. Physical factors including geomorphology, sediment composition, mobility of substrate, bathymetry, the hardness and roughness of the seabed and water depth will be significant in describing the distribution of benthic biota and classifying habitat types over the region. The relationships determined at this scale will improve our understanding of habitat variability and be used to aid in the production of offshore habitat maps for Ningaloo Marine Park.The sediment/substrate data will provide ground-truthing and add value to the acoustic backscatter data from the single and multi beam surveys completed in 2006/2007. The van Veen grab sampler collects surface and subsurface material to a depth of ~10 cm.Sediment fractions were separated for; grain size, component analysis, taxonomy of main biological constituents, and X - ray diffraction (XRD) for the determination of ratios of carbonate mineralogy.
提供机构:
Australian Ocean Data Network
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