Wageningen Marine Research, P.O. Box 57, 1780 AB, Den Helder, the Netherlands; Wageningen University, Aquatic Ecology and Water Quality Management Group, Droevendaalsesteeg 3a, 6708 PD, Wageningen, the Netherlands.
Royal Belgian Institute for Natural Science, Operational Directorate Natural Environment, Vautierstraat 29, 1000, Brussels, Belgium.
J Environ Manage. 2022 Aug 1;315:115173. doi: 10.1016/j.jenvman.2022.115173. Epub 2022 May 5.
Over the last years, the development of offshore renewable energy installations such as offshore wind farms led to an increasing number of man-made structures in marine environments. Since 2009, benthic impact monitoring programs were carried out in wind farms installed in the southern North Sea. We collated and analyzed data sets from three major monitoring programs. Our analysis considered a total of 2849 sampling points converted to a set of biodiversity response metrics. We analyzed biodiversity changes related to the implementation of offshore wind farms and generalized the correlation of these changes with spatial and temporal patterns. Our results demonstrate that depth, season and distance to structure (soft-bottom community) consistently determined diversity indicators and abundance parameters, whereas the age and the country affiliation were significantly related to some but not all indices. The water depth was the most important structuring factor for fouling communities while seasonal effects were driving most of the observed changes in soft-sediment communities. We demonstrate that a meta-analysis can provide an improved level of understanding of ecological patterns on large-scale effects of anthropogenic structures on marine biodiversity, which were not visible in single monitoring studies. We believe that meta-analyses should become an indispensable tool for management of offshore wind farm effects in the future, particularly in the view of the foreseen development of offshore renewable energies. This might lead to a better picture and more comprehensive view on potential alterations. However, this requires a modern open-source data policy and data management, across institutions and across national borders.
在过去的几年中，海上可再生能源设施（如海上风电场）的发展导致海洋环境中人造结构的数量不断增加。自 2009 年以来，在北海南部安装的风电场中开展了海底影响监测计划。我们整理和分析了三个主要监测计划的数据。我们的分析考虑了总共 2849 个采样点，转换为一组生物多样性响应指标。我们分析了与海上风电场实施相关的生物多样性变化，并概括了这些变化与空间和时间模式的相关性。我们的结果表明，水深、季节和与结构（软底群落）的距离一致地决定了多样性指标和丰度参数，而年龄和国家隶属关系与一些但不是所有指数显著相关。水深是污损生物群落的最重要结构因素，而季节性影响则是驱动软泥沙群落中大多数观察到变化的主要因素。我们证明，荟萃分析可以提高对人为结构对海洋生物多样性的大尺度影响的生态模式的理解水平，这在单个监测研究中是无法看到的。我们认为，荟萃分析应该成为未来管理海上风电场影响的不可或缺的工具，特别是考虑到海上可再生能源的预期发展。这可能会对潜在的变化有一个更清晰和更全面的认识。然而，这需要一个现代的开源数据政策和数据管理，跨越机构和国家边界。
