The publication by BioConsult SH and IBL Umweltplanung is part of a study based on data from aerial surveys of divers (red-throated and black-throated divers) over a period of two decades. The data were collected as part of monitoring programmes for 20 offshore wind farm projects in the German Bight.
We used a joint-likelihood Bayesian spatial model to compare the distribution of divers prior to the large-scale expansion of offshore wind energy (2001–2008) to their distribution in the years after the studied wind farms went operational (2017–2021).
The German Offshore Wind Energy Association (BWO) funded the overall study. This part of the results has now been published in the Journal of Environmental Management.
Displacement varies between wind farm clusters
The results show that displacement effects of offshore wind farms on divers can vary considerably in spatial terms. Both the intensity and the spatial extent of the observed effects varied between different wind farm clusters. The displacement patterns were partly significantly asymmetrical.
A single avoidance radius can therefore not adequately describe the effects of offshore wind farms on the distribution of birds. A spatially differentiated analysis is thus particularly important for the assessment of cumulative impacts and marine spatial planning.
At the same time, the differences between the areas studied suggest that the reaction of divers cannot be explained solely by the presence of or distance from an offshore wind farm. Location- and use-related factors could also be of importance. These include flow conditions and food availability, the wind farm layout as well as shipping traffic or fishing activities near the wind farms. The significance of the individual factors remains the subject of further research.
Statistical approach can be applied to other research questions
Another important part of the publication focuses on the developed statistical method. Although the method was developed in this study based on divers and offshore wind farms, it is not limited to this species group or to offshore wind energy.
Based on suitable monitoring data, the approach allows examining spatial changes in the distribution of other species in detail and assessing the impacts of human activities.
To encourage further use and development, the complete programme code is freely available on GitHub. Code and input data are also permanently archived on Zenodo. The analysis can thus be retraced, reproduced, tested and adapted for other studies.
