A new method for quantifying redistribution of seabirds within operational offshore wind farms finds no evidence of within-wind farm displacement

Abstract

The climate crisis is driving a rapid increase in size and number of offshore wind farms to reduce carbon emissions from electricity generation. However, there are concerns about the potential impact of offshore wind farms on the marine environment. Seabirds are considered to be at risk of being displaced from preferred foraging habitat, by construction and operation of offshore wind farms, resulting in reduced energy intake or elevated energetic costs and consequent decreases in survival and/or productivity. Typically, displacement or avoidance behaviour is assessed by comparing abundance and spatial distributions of seabirds before and after an offshore wind farm is constructed. However, seabird distributions are highly variable through time and space and so discerning a change in distribution caused by an offshore wind farm from other environmental variables can be challenging. We present a new method that controls for temporal variation by examining the location of individual seabirds relative to turbines. Mean seabird density at different distances from individual turbines (0-400m) was calculated from data collected on a total of 12 digital aerial surveys of the Beatrice Offshore Wind Farm (UK), in May-August in 2019 and 2021. Mean densities of common guillemot (Uria aalge), razorbill (Alca torda), Atlantic puffin (Fratercula arctica) and black-legged kittiwake (Rissa tridactyla), both flying and sat on the water, were calculated. If the presence of turbines had no effect on seabird distribution, there should be no relationship between distance from turbine and seabird density. This was tested by simulating a relocation of turbines, relative to seabird distribution, and recalculating seabird density over 0-400m from simulated turbine locations. This was repeated to generate a bootstrapped distribution of expected densities against which observed density was compared. If displacement was occurring, mean observed density close to turbines would be significantly lower than expected density, derived from the bootstrap distribution. Overall, observed mean density did not differ significantly from expected density, i.e. no displacement effect was detected. There was a slight tendency for guillemot and razorbill, when sat on the water, to be at higher densities than expected, near turbines, suggestive of possible attraction to turbines, and for flying birds to be at lower densities than expected, near turbines, suggestive of possible avoidance. No flying razorbills were recorded within 100m of turbines but sample sizes were small. Kittiwake tended to show no avoidance or attraction behaviour, although flying kittiwake density was slightly lower than expected at 200m from turbines. Puffins sat on the water were recorded in densities similar to the expected density. Overall, no effect of turbine rotor speed was found, i.e. birds were not more likely to be displaced/avoid turbines at higher or lower rotor speeds. The results of the turbine relocation analysis gave a more consistent and more easily interpreted assessment of displacement/avoidance behaviour than the typical approaches of comparing abundance and seabird distribution through time. We strongly encourage application of this new approach to post-construction spatial distribution data from other offshore wind farms, to build the evidence base on the effects of offshore wind farms on seabirds.