Year-round distribution of Northeast Atlantic seabird populations: applications for population management and marine spatial planning

Fauchald, Per; Tarroux, Arnaud; Amélineau, Françoise; Bråthen, Vegard Sandøy; Descamps, Sébastien; Ekker, Morten; Helgason, Halfdan Helgi; Johansen, Malin Kjellstadli; Merkel, Benjamin; Moe, Børge; Åström, Jens; Anker-Nilssen, Tycho; Bjørnstad, Oskar; Chastel, Olivier; Christensen-Dalsgaard, Signe; Danielsen, Jóhannis; Daunt, Francis ORCID: https://orcid.org/0000-0003-4638-3388; Dehnhard, Nina; Erikstad, Kjell Einar; Ezhov, Alexey; Gavrilo, Maria; Hallgrimsson, Gunnar Thor; Hansen, Erpur Snær; Harris, Mike; Helberg, Morten; Jónsson, Jón Einar; Kolbeinsson, Yann; Krasnov, Yuri; Langset, Magdalene; Lorentsen, Svein-Håkon; Lorentzen, Erlend; Newell, Mark; Olsen, Bergur; Reiertsen, Tone Kristin; Systad, Geir Helge; Thompson, Paul; Thórarinsson, Thorkell Lindberg; Wanless, Sarah; Wojczulanis-Jakubas, Katarzyna; Strøm, Hallvard. 2021 Year-round distribution of Northeast Atlantic seabird populations: applications for population management and marine spatial planning. Marine Ecology Progress Series, 676. 255-276. https://doi.org/10.3354/meps13854

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Abstract/Summary

Tracking data of marine predators are increasingly used in marine spatial management. We developed a spatial data set with estimates of the monthly distribution of 6 pelagic seabird species breeding in the Northeast Atlantic. The data set was based on year-round global location sensor (GLS) tracking data of 2356 adult seabirds from 2006-2019 from a network of seabird colonies, data describing the physical environment and data on seabird population sizes. Tracking and environmental data were combined in monthly species distribution models (SDMs). Cross-validations were used to assess the transferability of models between years and breeding locations. The analyses showed that birds from colonies close to each other (<500 km apart) used the same nonbreeding habitats, while birds from distant colonies (>1000 km) used colony-specific and, in many cases, non-overlapping habitats. Based on these results, the SDM from the nearest model colony was used to predict the distribution of all seabird colonies lying within a species-specific cut-off distance (400-500 km). Uncertainties in the predictions were estimated by cluster bootstrap sampling. The resulting data set consisted of 4692 map layers, each layer predicting the densities of birds from a given species, colony and month across the North Atlantic. This data set represents the annual distribution of 23.5 million adult pelagic seabirds, or 87% of the Northeast Atlantic breeding population of the study species. We show how the data set can be used in population and spatial management applications, including the detection of population-specific nonbreeding habitats and identifying populations influenced by marine protected areas.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.3354/meps13854
UKCEH and CEH Sections/Science Areas:	Biodiversity (Science Area 2017-) UKCEH Fellows
ISSN:	0171-8630
Additional Information. Not used in RCUK Gateway to Research.:	Open Access paper - full text available via Official URL link.
Additional Keywords:	Fulmarus glacialis, Rissa tridactyla, Uria aalge, Uria lomvia, Alle alle, Fratercula arctica, marine spatial planning, SEATRACK
NORA Subject Terms:	Ecology and Environment
Date made live:	01 Nov 2021 16:08 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/531329

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