DOI: 10.5061/dryad.dp2ms
title: Data from: Modelling flight heights of lesser black-backed gulls and great skuas from GPS: a Bayesian approach

description: Wind energy generation is increasing globally, and associated
 environmental impacts must be considered. The risk of seabirds colliding
 with offshore wind turbines is influenced by flight height, and flight
 height data usually come from observers on boats, making estimates in
 daylight in fine weather. GPS tracking provides an alternative and
 generates flight height information in a range of conditions, but the raw
 data have associated error. Here, we present a novel analytical solution
 for accommodating GPS error. We use Bayesian state-space models to
 describe the flight height distributions and the error in altitude
 measured by GPS for lesser black-backed gulls and great skuas, tracked
 throughout the breeding season. We also examine how location and light
 levels influence flight height. Lesser black-backed gulls flew lower by
 night than by day, indicating that this species would be less likely to
 encounter turbine blades at night, when birds’ ability to detect and avoid
 them might be reduced. Gulls flew highest over land and lowest near the
 coast. For great skuas, no significant relationships were found between
 flight height, time of day and location. We consider four ‘collision risk
 windows’, corresponding to the airspace swept by rotor blades for
 different offshore wind turbine designs. We found the highest proportion
 of birds at risk for a 22–250 m turbine (up to 9% for great skuas and 34%
 for lesser black-backed gulls) and the lowest for a 30–258 m turbine. Our
 results suggest lesser black-backed gulls are at greater risk of collision
 than great skuas, especially by day. Synthesis and applications. Our novel
 modelling approach is an effective way of resolving the error associated
 with GPS tracking data. We demonstrate its use on GPS measurements of
 altitude, generating important information on how breeding seabirds use
 their environment. This approach and the associated data also provide
 information to improve avian collision risk assessments for offshore wind
 farms. Our modelling approach could be applied to other GPS data sets to
 help manage the ecological needs of seabirds and other species at a time
 when the pressures on the marine environment are growing.
description: Lesser Black-backed Gull
 flight height dataThis file was created
 with R. 'Bird.id', 'date_time', 'latitude',
 'longitude', 'altitude', 'positiondop' and
 'speed' were collected by GPS tags. 'Positiondop' is
 dilution of precision. 'Altitude' is measured in m and
 'speed' in km/h. 'Marine' denotes observations over
 land (0) or sea (1), derived from overlaying the GPS measurements on a map
 in ArcGIS. 'Coastal' donates observations at sea but within 200
 m of the coast (1) or further from the coast (0), again derived in ArcGIS.
 Tidal data ('tidal.state' in m) were from the British
 Oceanographic Data Centre
 (https://www.bodc.ac.uk/data/online_delivery/ntslf/), using tide gauge
 from Harwich. Surface elevation ('land_height' in m) was
 obtained from the Shuttle Radar Topography Mission 90 m digital elevation
 data (http://srtm.csi.cgiar.org/http://srtm.csi.cgiar.org/), aggregated at
 the 1 km square level. Sunrise and sunset information was obtained using
 the NOAA Sunrise/Sunset Calculator
 (http://www.srrb.noaa.gov/highlights/sunrise/sunrise.html).Great Skua flight height dataThis file was created with R. 'Bird.id', 'date_time', 'latitude', 'longitude', 'altitude', 'positiondop' and 'speed' were collected by GPS tags. 'Positiondop' is dilution of precision. 'Altitude' is measured in m and 'speed' in km/h. 'Marine' denotes observations over land (0) or sea (1), derived from overlaying the GPS measurements on a map in ArcGIS. Tidal data ('tidal.state' in m) were from the British Oceanographic Data Centre (https://www.bodc.ac.uk/data/online_delivery/ntslf/), using tide gauge from Lerwick and Wick. Surface elevation ('land_height' in m) was obtained from the Shuttle Radar Topography Mission 90 m digital elevation data (http://srtm.csi.cgiar.org/http://srtm.csi.cgiar.org/), aggregated at the 1 km square level. Sunrise and sunset information was obtained using the NOAA Sunrise/Sunset Calculator (http://www.srrb.noaa.gov/highlights/sunrise/sunrise.html).