Aim  An understanding of the non‐breeding distribution and ecology of migratory species is necessary for successful conservation. Many seabirds spend the non‐breeding season far from land, and information on their distribution during this time is very limited. The black‐legged kittiwake, Rissa tridactyla, is a widespread and numerous seabird in the North Atlantic and Pacific, but breeding populations throughout the Atlantic range have declined recently. To help understand the reasons for the declines, we tracked adults from colonies throughout the Atlantic range over the non‐breeding season using light‐based geolocation. Location  North Atlantic. Methods  Geolocation data loggers were deployed on breeding kittiwakes from 19 colonies in 2008 and 2009 and retrieved in 2009 and 2010. Data from 236 loggers were processed and plotted using GIS. Size and composition of wintering populations were estimated using information on breeding population size. Results  Most tracked birds spent the winter in the West Atlantic, between Newfoundland and the Mid‐Atlantic Ridge, including in offshore, deep‐water areas. Some birds (mainly local breeders) wintered in the North Sea and west of the British Isles. There was a large overlap in winter distributions of birds from different colonies, and colonies closer to each other showed larger overlap. We estimated that 80% of the 4.5 million adult kittiwakes in the Atlantic wintered west of the Mid‐Atlantic Ridge, with only birds from Ireland and western Britain staying mainly on the European side. Main conclusions  The high degree of mixing in winter of kittiwakes breeding in various parts of the Atlantic range implies that the overall population could be sensitive to potentially deteriorating environmental conditions in the West Atlantic, e.g. owing to lack of food or pollution. Our approach to estimating the size and composition of wintering populations should contribute to improved management of birds faced with such challenges.

We found that synchronous fluctuations of two congeneric seabird species across the entire Arctic and sub-Arctic regions were associated with changes in sea surface temperatures (SST) that were linked to two climate shifts, in 1977 and again in 1989. As the SST changes linked to climate shifts were congruent at the scale of ocean basins, fluctuations of these species occurred similarly at continental or basin scale. Changes in colony sizes were examined for a decade following climate shifts. The magnitude of the SST shift was more important than its direction in determining the subsequent rate of population change. Seabirds declined when the SST shift was large and increased when the shift was small, although the effect differed between the Arctic-breeding species and the more temperate-breeding congener. The Arctic species, Thick-billed Murre (Uria lomvia) increased most rapidly when SST warmed slightly, while the temperate species, Common Murre (Uria aalge) showed most rapid increase with moderate cooling. Both showed negative trends with large temperature shifts in either direction. This pattern was replicated during both climate oscillations. Negative population trends in seabirds presumably indicate the alteration of underlying food webs. Hence, similar widespread fluctuations in response to climate shifts are likely for other ecosystem components (marine mammals, fish, and invertebrates).

Abstract1. The natural environment of the Arctic is changing rapidly owing to climate change. At the same time in many countries including Russia the region is attracting growing attention of decisionmakers and business communities. In light of the above it is necessary to protect the biodiversity of the regional marine ecosystems in the most effective way possible, namely by establishing a network of marine protected areas.2. Identifying conservation priority areas is a key step towards this goal. To achieve it, a study based on a systematic conservation planning approach was conducted. An expanded group of experts used the MARXAN algorithm to produce initial results, then discussed and refined them to select 47 conservation priority areas in the Russian Arctic seas.3. The resulting network covers nearly 25% of the Russian Arctic seas, which guarantees proportional representation of their biodiversity as well as achieving connectivity, sustainability and naturalness. This was largely made possible by the selected methodology, based on the MARXAN decision support tool supplemented by extensive post-analysis that helped fill any gaps inevitable in the formal approach.4. Although available data were sparse, and of varying quality and a single regionalization scheme could not be used (as is often the case for such areas), the selected approach has proven successful for such a large area that covers both the coastal zone and parts of the High Seas. Such an approach could be used further to identify marine protected areas throughout the Arctic Ocean. Kudersky, 2004;Pavlov & Sundet, 2011;Spiridonov & Zalota, 2017) and sea ice habitat loss (Amstrup, Marcot, & Douglas, 2008;Moore & Huntington, 2008). Perhaps equally important, these changes lead to greater human presence in the region (Huettmann, 2012;Jørgensen et al., 2016;Wenzel et al., 2016). This could take many forms from increased oil and gas exploration and production, intensified shipping, fishing, aquaculture and tourism as well as greater military presence.In recent years serious efforts to protect marine biodiversity have been undertaken worldwide and the Russian Arctic seas are no exception. The Arctic is receiving growing attention in Russia as politicians, investors, media and the general public are pushing for a comeback after the country's withdrawal from the region in the 1990s. There are two approaches to conservation that prevail in the world today. One is based on industries regulations that are introduced alongside measures to protect or manage particular species or stocks (Roff & Zacharias, 2011). The other centres on areabased conservation measures and is widely regarded as effective (Roff & Zacharias, 2011;Spiridonov et al., 2012). In the Russian Arctic the latter remains less common. The region has seven Strictly Protected Natural Reserves, or zapovedniks (IUCN Ia), three National Parks (IUCN II), four Preserves (IUCN IV/VI), one Natural Monument (IUCN III) and 41 Regional Protected Areas (IUCN Ib), but their primary purpose is to protect terr...

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.