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.
- Benthic biodiversity
- Generalized additive modelling
- North sea
- Offshore wind farms