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    Elsevier
    In:  EPIC3Data in Brief, Elsevier, 46, pp. 108790-108790, ISSN: 2352-3409
    Publication Date: 2024-02-06
    Description: The German Bight (North Sea) is a centre of development of offshore wind energy. In the near future, windfarms will cover a significant part (about 25%) of the German Exclusive Economic Zone. In order to understand and assess potential effects of the construction and early operational phase of offshore wind turbines on the marine environment, an extensive research programme was carried out at Germany's first offshore windfarm alpha ventus. Here, data are presented on macroinfauna and local sediment characteristics collected as part of this programme. Grab samples were taken annually in autumn in 2008 (baseline), 2009 (construction phase) and 2010 and 2011 (early operational phase). Sampling stations were located along transects between adjacent turbines inside the windfarm and in two reference areas with similar environmental conditions in terms of sediment characteristics and water depth. A total of 336 samples were taken inside the windfarm and 192 samples in the reference areas. Sediment characteristics were described in terms of grain size distribution and organic content. The infauna was taxonomically analysed and quantified in terms of abundance and biomass. One-hundred three infauna taxa were identified, mainly belonging to the polychaetes, crustaceans and bivalves, living in fine to medium sandy soft bottom in water depths ranging from -27 m to -30 m. The data can be useful in meta-analyses of renewable energies impacts. Additionally, the data can support species distribution modelling to gain a better understanding of species' requirements and habitats as a basis for spatial planning scenarios and the evaluation of the ecological status of the marine environment. Moreover, the data can serve as baseline data for future monitoring and management of nearby protected areas where environmental conditions are comparable to those of the present study area.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
    Format: application/pdf
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