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

• Published in: Marine Ecology Progress Series
• Main Authors: Fauchald, P, Tarroux, A, Amélineau, F, Bråthen, Vs, Descamps, S, Ekker, M, Helgason, Hh, Johansen, Mk, Merkel, B, Moe, B, Åström, J, Anker-Nilssen, T, Bjørnstad, O, Chastel, Olivier, Christensen-Dalsgaard, S, Danielsen, J, Daunt, F, Dehnhard, N, Erikstad, Ke, Ezhov, A, Gavrilo, M, Hallgrimsson, Gt, Hansen, Es, Harris, M, Helberg, M, Jónsson, Je, Kolbeinsson, Y, Krasnov, Y, Langset, M, Lorentsen, Sh, Lorentzen, E, Newell, M, Olsen, B, Reiertsen, Tk, Systad, Gh, Thompson, P, Thórarinsson, Tl, Wanless, S, Wojczulanis-Jakubas, K, Strøm, H
• Other Authors: Centre d'Études Biologiques de Chizé - UMR 7372 (CEBC), La Rochelle Université (ULR)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2021
• Subjects: Fulmarus glacialis; Rissa tridactyla; Uria aalge; Uria lomvia; Alle alle; Fratercula arctica; Marine spatial planning; SEATRACK; [SDE]Environmental Sciences; fratercula; North Atlantic; Northeast Atlantic; rissa tridactyla; uria
• Online Access: https://hal.science/hal-03349343; https://doi.org/10.3354/meps13854

International audience Abstract: Tracking data of marine predators are increasingly used in marine spatial management. We developed a spatial dataset with estimates of the monthly distribution of six pelagic seabird species breeding in the Northeast Atlantic. The dataset is 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). The uncertainties in predictions were estimated by cluster bootstrap sampling. The resulting dataset consists of 4692 map layers, each layer predicting the densities of birds from a given species, colony and month across the North Atlantic. The dataset 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 dataset 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.