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Using kernel density estimation to explore habitat use by seabirds at a marine renewable wave energy test facility
Institution:1. University of California Santa Cruz, Department of Applied Mathematics and Statistics, Center for Stock Assessment Research, Santa Cruz, CA 95060, USA;2. Alaska Fisheries Science Center, NOAA, 7600 Sand Point Way NE, Seattle, WA 98115, USA;3. U.S. Fish and Wildlife Service, Anchorage, AK 99503, USA;4. NOAA, Pacific Marine Environmental Laboratory, 7600 Sand Point Way NE, Seattle, WA 98115, USA;5. Tern Again Consulting, 811 Ocean Drive Loop, Homer, AK 99603, USA;6. School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA 98195, USA;1. SMRU Consulting Canada, Suite 510, 1529 6th Avenue West, Vancouver, BC V6J 1R1, Canada;2. Department of Statistics and Actuarial Science, Simon Fraser University, Burnaby, BC V5A 1S6, Canada;3. SMRU Consulting USA, PO Box 764, Friday Harbor, WA 98250, USA;4. SMRU Consulting Europe, New Technology Centre, North Haugh, St Andrews, Fife KY16 9SR, Scotland;5. Pacific Northwest National Laboratory, 1100 Dexter Ave N, Suite 400, Seattle, WA, USA;6. Sea Mammal Research Unit, Scottish Oceans Institute, University of St. Andrews, St. Andrews, Fife KY16 8LB, Scotland;1. Natural England, Sterling House, Dix’s Field, Exeter, Devon, United Kingdom;2. ECON Ecological Consultancy Ltd, Norwich, Norfolk, United Kingdom;3. Allen & Mellon Environmental Ltd, Belfast, United Kingdom;4. Joint Nature Conservation Committee, Inverdee House, Aberdeen, United Kingdom;5. Industry Nature Conservation Association, Redcar, North Yorkshire, United Kingdom;6. Footprint Ecology, Forest Office, Wareham, Dorset, United Kingdom;7. Northern Ireland Environment Agency, Belfast, United Kingdom;8. Natural Resources Wales, Bangor, Wales, United Kingdom;9. Birmingham, United Kingdom
Abstract:If Scottish Government targets are met, the equivalent of 100% of Scotland's electricity demand will be generated from renewable sources by 2020. There are several possible risks posed to seabirds from marine renewable energy installations (MREIs) and many knowledge gaps still exist around the extent to which seabird habitats can overlap with MREIs. In this study, underlying seasonal and interannual variation in seabird distributions was investigated using kernel density estimation (KDE) to identify areas of core habitat use. This allowed the potential interactions between seabirds and a wave energy converter (WEC) to be assessed. The distributions of four seabird species were compared between seasons, years, and in the presence and absence of WECs. Although substantial interannual variation existed in baseline years prior to WEC deployment, the KDEs for all four species analysed were closer to the mooring points in the presence of a WEC in at least one season. The KDEs for all four species also increased in area in at least one season in the presence of a WEC. The KDEs of the northern fulmar and great skua overlapped the mooring points during spring in the presence of a device. The density of observations close to the mooring points increased for great skua, northern gannet, and northern fulmar during summer in the presence of a device. These results suggest that none of the four species analysed have shown avoidance or an extreme change in distribution as a result of the presence of a WEC. The continued monitoring of seabirds during WEC deployments is necessary to provide further data on how distributions may change in response to the presence of WECs.
Keywords:Wet renewables  Seabird distributions  Spatial overlap  Wave energy converter  Environmental impacts
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