Citation

Overview
GPS tracking is a valuable tool for increasing our understanding of bird behaviour. In this study, researchers used tracking technology to investigate movements of Amber-listed Lesser Black-backed Gulls around offshore wind farms. Their results reveal a detailed picture of both avoidance of and attraction towards turbines in this species, which may be used to inform future collision risk assessments.
In more detail
This project was supported by the Natural Environment Research Council, Ørsted and Natural England, and also drew from a previous tracking study funded by the Department for Business, Energy and Industrial Strategy Offshore Energy Strategic Environmental Assessment research programme, and the Marine Renewable Energy and the Environment project (funded by Highlands and Islands Enterprise, the European Regional Development Fund, and the Scottish Funding Council). Thanks to the Cumbria Wildlife Trust and Natural England for permissions and to all helping with fieldwork and discussion. Comments from anonymous reviewers improved this manuscript.
Abstract
Movements through or use of offshore wind farms by seabirds while commuting or foraging may increase the potential for collision with turbine blades. Collision Risk Models (CRMs) provide a method for estimating potential impacts of wind farms on seabird populations, but are sensitive to input parameters, including avoidance rates. Refining understanding of avoidance through the use of high-resolution empirical movement data has the potential to inform assessments of the collision impacts of offshore wind farms on seabird populations. In this study we assessed the movements of Global Positioning System (GPS) tagged lesser black-backed gulls Larus fuscus from a breeding colony in northwest England to estimate the species’ Avoidance Rate (AR) and Avoidance/Attraction Index (AAI) to nearby offshore wind farms. To investigate both macro-(0-4 km) and meso-scale (0-200 m) responses to wind turbines we used calculations of AR and AAI based on simulated vs. observed tracks. We found that birds exhibited an AR of -0.15 (95% CI [-0.44, 0.06]), indicating a degree of attraction within 4 km of the wind farms. However, AAI values varied with distance from the wind farm boundaries, with a degree of avoidance displayed between 3-4 km, which weakened as distance bands approach wind farm boundaries. Meso-scale avoidance/attraction was assessed with regard to the nearest individual turbine, and flight height relative to the rotor height range (RHR) of the nearest turbine. We found attraction to increase below the RHR at distances <70 m, while avoidance increased within the RHR at distances approaching the turbine. We explore how high-resolution tracking data can be used to improve our knowledge of avoidance and attraction behaviour in lesser black-backed gulls to established wind farms, and so inform assessments of collision impacts.