Large-scale effects of offshore wind farms on seabirds of high conservation concern.

The North Sea is a key area worldwide for the installation of offshore wind farms (OWFs). We analysed data from multiple sources to quantify the effects of OWFs on seabirds from the family Gaviidae (loons) in the German North Sea. The distribution and abundance of loons changed substantially from the period before to the period after OWF construction. Densities of loons were significantly reduced at distances of up to 9-12 km from the OWF footprints. Abundance declined by 94% within the OWF + 1 km zone and by 52% within the OWF + 10 km zone. The observed redistribution was a large-scale effect, with birds aggregating within the study area at large distances from the OWFs. Although renewable energies will be needed to provide a large share of our energy demands in the future, it is necessary to minimize the costs in terms of less-adaptable species, to avoid amplifying the biodiversity crisis.

Analysis of local habitat selection and large-scale attraction/avoidance based on animal tracking data: is there a single best method?

BACKGROUND: New wildlife telemetry and tracking technologies have become available in the last decade, leading to a large increase in the volume and resolution of animal tracking data. These technical developments have been accompanied by various statistical tools aimed at analysing the data obtained by these methods. METHODS: We used simulated habitat and tracking data to compare some of the different statistical methods frequently used to infer local resource selection and large-scale attraction/avoidance from tracking data. Notably, we compared spatial logistic regression models (SLRMs), spatio-temporal point process models (ST-PPMs), step selection models (SSMs), and integrated step selection models (iSSMs) and their interplay with habitat and animal movement properties in terms of statistical hypothesis testing. RESULTS: We demonstrated that only iSSMs and ST-PPMs showed nominal type I error rates in all studied cases, whereas SSMs may slightly and SLRMs may frequently and strongly exceed these levels. iSSMs appeared to have on average a more robust and higher statistical power than ST-PPMs. CONCLUSIONS: Based on our results, we recommend the use of iSSMs to infer habitat selection or large-scale attraction/avoidance from animal tracking data. Further advantages over other approaches include short computation times, predictive capacity, and the possibility of deriving mechanistic movement models.

Northern gannets (Morus bassanus) are strongly affected by operating offshore wind farms during the breeding season.

Northern gannets (Morus bassanus) have been ranked as one of the most vulnerable species in terms of collision with offshore wind farm (OWF) turbines, and strong avoidance of OWFs has been documented for this species. Gannets increasingly encounter OWFs within the ranges of their largest breeding colonies along the European coasts. However, information on their actual reactions to OWFs during the breeding season is lacking. We investigated the possible effects of OWFs located 23-35 km north of the colony on Helgoland in the southern North Sea on breeding gannets. GPS tags were applied to 28 adult gannets breeding on Helgoland for several weeks over 2 years. Most gannets (89%) predominantly avoided the OWFs in both years, but 11% frequently entered them when foraging or commuting between the colony and foraging areas. Flight heights inside the OWFs were close to the rotor-blade zone, especially for individuals predominantly avoiding the OWFs. Gannets preferred distances of 250-450 m to the turbines when being inside the OWF. A point process modelling approach revealed that the gannets resource selection of the OWF area compared with the surroundings (outside OWF = up to 15 km from the OWF border) was reduced by 21% in 2015 and 37% in 2016. This study provides the first detailed characterisation of individual reactions of gannets to OWFs during the breeding season and one of the first comprehensive studies of OWF effects on this species based on telemetry data. The documented effects need to be considered during the planning processes for future OWFs, especially those located close to large seabird breeding colonies.

Effects of offshore windfarms on seabird abundance: Strong effects in spring and in the breeding season.

The increasing development of offshore wind farms (OWFs) worldwide leads to possible conflicts with the ecological requirements of top predators that largely depend on offshore areas. Seabird species exhibit different behavioural reactions to OWFs, ranging from avoidance resulting in habitat loss, to attraction causing an increased risk of colliding with the turbines. We investigated how OWFs affected the densities and distributions of guillemots and kittiwakes breeding in the southern North Sea and if the effects varied among seasons using a 'before-after control impact' (BACI) analysis approach based on a large-scale and long-term dataset covering 14 years before and 3 years after the construction of OWFs. Guillemot relative density in the OWF decreased by 63% in spring, and by 44% in the breeding season. Kittiwake relative density in the OWF decreased by 45% in the breeding season, and not significantly by 10% in spring. We furthermore estimated the response radii to the OWF for both species and seasons, finding that guillemots showed a response radius of ~9 km in spring and kittiwakes a radius of ~20 km in the breeding season. The results underline the value of large-scale and long-term assessments considering seasonal variation throughout the yearly cycle. The here provided information on the seasonally different reactions of seabirds to OWFs adds substantially to our current knowledge and provides the necessary basis for reliable estimations of OWF effects on guillemots and kittiwakes. Such evaluations are urgently needed for future planning and management recommendations to decision-makers.

Operational offshore wind farms and associated ship traffic cause profound changes in distribution patterns of Loons (Gavia spp.).

Seabirds select suitable habitats at sea, but these habitats may be strongly impacted by marine spatial planning, including the construction of offshore wind farms (OWFs) and the associated ship traffic. Loons (Gavia spp.) are particularly vulnerable to anthropogenic activities and are also of high conservation status, making them particularly relevant to marine planning processes. We investigated the effects of OWF construction and ship traffic on Loon distributions in the German North Sea on a large spatial scale, using a 'before-after' control impact analysis approach and a long-term data set. Many OWFs were built in or close to core areas of Loon distributions. Loons showed significant shifts in their distribution in the 'after' period and subsequently aggregated between two OWF clusters, indicating the remaining suitable habitat. The decrease in Loon abundance became significant as far as about 16 km from the closest OWF. Ship traffic also had a significant negative impact on Loons, indicating that OWFs deterred Loons through the combined effect of ship traffic and the wind turbines themselves. This study provides the first analysis of the extensive effects of OWFs and ships on Loons on a large spatial scale. The results provide an essential baseline for future marine spatial planning processes in the German North Sea and elsewhere.