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  1. Article ; Online: Multispectral multibeam backscatter response of heterogeneous rhodolith beds.

    Menandro, Pedro S / Misiuk, Benjamin / Brown, Craig J / Bastos, Alex C

    Scientific reports

    2023  Volume 13, Issue 1, Page(s) 20220

    Abstract: Acoustic backscatter has been used as a tool to map the seafloor in greater detail and plays an increasingly important role in seafloor mapping to meet multiple ocean management needs. An outstanding challenge to the use of backscatter for seafloor ... ...

    Abstract Acoustic backscatter has been used as a tool to map the seafloor in greater detail and plays an increasingly important role in seafloor mapping to meet multiple ocean management needs. An outstanding challenge to the use of backscatter for seafloor mapping is the distinction between acoustically similar substrates, such as mixed sediments from rhodoliths. Rhodolith beds are a biogenic substrate that provides important ecological services, and are typically classified as a single categorical substrate type-though nodules coverage may be spatially variable. Recently, multispectral acoustic backscatter has demonstrated great potential to improve thematic seafloor mapping compared to single-frequency systems. This work employs multispectral multibeam backscatter and underwater imagery to characterize and map rhodolith beds in the Costa das Algas Marine Protected Area (Brazil). A support vector machine classifier was used to classify multifrequency backscatter mosaics according to rhodolith classes identified from underwater imagery. Results suggest that multispectral backscatter is effective both in providing information for mapping different proportions of rhodolith coverage and in predicting the presence or absence of these nodules. The backscatter of the lowest frequency was the most useful for distinguishing variable proportions of rhodolith coverage, and the two higher frequencies were better predictors of presence and absence.
    Language English
    Publishing date 2023-11-18
    Publishing country England
    Document type Journal Article
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-023-46240-7
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Book ; Online: Seafloor sediment characterization to improve estimate of organic carbon standing stocks in continental shelves

    Brenan, Catherine / Kienast, Markus / Maselli, Vittorio / Algar, Christopher / Misiuk, Benjamin / Brown, Craig J.

    eISSN:

    2024  

    Abstract: Continental shelf sediments contain some of the largest stocks of organic carbon (OC) on Earth and play a vital role in influencing the global carbon cycle. Quantifying how much OC is stored in shelf sediments and determining its residence time is key to ...

    Abstract Continental shelf sediments contain some of the largest stocks of organic carbon (OC) on Earth and play a vital role in influencing the global carbon cycle. Quantifying how much OC is stored in shelf sediments and determining its residence time is key to assessing how human activities can accelerate the process of OC remineralization into carbon dioxide. Spatial variations in terrestrial carbon stocks are well studied and mapped at high resolution, but our knowledge of the distribution of marine OC in different seafloor settings is still very limited, particularly in the highly dynamic and spatially variable shelf environments. The lack of knowledge reduces our ability to understand and predict how much and for how long oceans sequester CO 2 . In this study, we use high-resolution multibeam echosounder (MBES) data from the Eastern Shore Islands offshore Nova Scotia (Canada), combined with OC measurements from discrete samples, to assess the distribution of OC content in seafloor sediments. We derive three different spatial estimates of organic carbon: i) assuming a homogenous seafloor the carbon stock estimates were scaled to the entire study region; ii) using a high-resolution substrate map, the estimates were scaled to the areas of soft substrate only, and, finally, iii) using Empirical Bayesian Regression Kriging (EBRK) regression prediction within the area of soft substrate, carbon stock estimates in areas of soft substrate were refined to account for spatial variability in the concentration of OC. These three distinct spatial models yielded dramatically different estimates of average standing stock of OC in our study area, 1275, 259 and 203 Mt of OC respectively. Our study demonstrates that high-resolution mapping is critically important for improved estimates of OC stocks on continental shelves, and to the identification of carbon hotspots that need to be considered in seabed management and climate mitigation strategies.
    Subject code 550 ; 333
    Language English
    Publishing date 2024-01-19
    Publishing country de
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: A multiscale approach to mapping seabed sediments.

    Misiuk, Benjamin / Lecours, Vincent / Bell, Trevor

    PloS one

    2018  Volume 13, Issue 2, Page(s) e0193647

    Abstract: Benthic habitat maps, including maps of seabed sediments, have become critical spatial-decision support tools for marine ecological management and conservation. Despite the increasing recognition that environmental variables should be considered at ... ...

    Abstract Benthic habitat maps, including maps of seabed sediments, have become critical spatial-decision support tools for marine ecological management and conservation. Despite the increasing recognition that environmental variables should be considered at multiple spatial scales, variables used in habitat mapping are often implemented at a single scale. The objective of this study was to evaluate the potential for using environmental variables at multiple scales for modelling and mapping seabed sediments. Sixteen environmental variables were derived from multibeam echosounder data collected near Qikiqtarjuaq, Nunavut, Canada at eight spatial scales ranging from 5 to 275 m, and were tested as predictor variables for modelling seabed sediment distributions. Using grain size data obtained from grab samples, we tested which scales of each predictor variable contributed most to sediment models. Results showed that the default scale was often not the best. Out of 129 potential scale-dependent variables, 11 were selected to model the additive log-ratio of mud and sand at five different scales, and 15 were selected to model the additive log-ratio of gravel and sand, also at five different scales. Boosted Regression Tree models that explained between 46.4 and 56.3% of statistical deviance produced multiscale predictions of mud, sand, and gravel that were correlated with cross-validated test data (Spearman's ρmud = 0.77, ρsand = 0.71, ρgravel = 0.58). Predictions of individual size fractions were classified to produce a map of seabed sediments that is useful for marine spatial planning. Based on the scale-dependence of variables in this study, we concluded that spatial scale consideration is at least as important as variable selection in seabed mapping.
    MeSH term(s) Ecosystem ; Geologic Sediments ; Models, Statistical ; Oceans and Seas ; Spatial Analysis
    Language English
    Publishing date 2018
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ISSN 1932-6203
    ISSN (online) 1932-6203
    DOI 10.1371/journal.pone.0193647
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

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