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Migration is a common trait among many animals allowing the exploitation of spatiotemporally variable resources. It often implies high energetic costs to cover large distances, for example between breeding and wintering grounds. For flying or swimming animals, the adequate use of winds and currents can help reduce the associated energetic costs. Migratory seabirds are good models because they dwell in habitats characterized by strong winds while undertaking very long migrations. We tested the hypothesis that seabirds migrate through areas with favourable winds. To that end, we used the SEATRACK dataset, a multi-colony geolocator tracking dataset, for two North Atlantic seabirds with contrasting flight capabilities, the black-legged kittiwake Rissa tridactyla and the Atlantic puffin Fratercula arctica, and wind data from the ERA5 climate reanalysis model. Both species had on average positive wind support during migration. Their main migratory routes were similar and followed seasonally prevailing winds. The general migratory movement had a loop-shape at the scale of the North Atlantic, with an autumn route (southward) along the east coast of Greenland, and a spring route (northward) closer to the British Isles. While migrating, both species had higher wind support in spring than in autumn. Kittiwakes migrated farther and benefited from higher wind support than puffins on average. The variation in wind conditions encountered while migrating was linked to the geographical location of the colonies. Generally, northernmost colonies had a better wind support in autumn while the southernmost colonies had a better wind support in spring, with some exceptions. Our study helps understanding how the physical environment shapes animal migration, which is crucial to further predict how migrants will be impacted by ongoing environmental changes.

The Working Group on the Integrated Assessment of the Central Arctic Ocean (WGICA) aims to provide a holistic analysis of the present and future status of the Central Arctic Ocean (CAO) ecosystem and human activities therein. Climate change reduces sea ice, increases light penetration, causes regionally variable trends in stratification and mixing of the water column, increases inflow in both the Atlantic and Pacific sectors, and heating of waters at the surface and extending deeper. These changes in turn affect primary production and cascade through the foodweb to ice-associated fauna, zooplankton, fish, benthos, seabirds, and marine mammals. These changes may be exacerbated by increasing human activities in and around the CAO, including increasing pollution from ship traffic and from the transport of contaminants to the ecoregion by rivers and ocean currents. The number of ships and distances travelled are increasing and it is anticipated that both commercial and tourist traffic by sea and air will continue to rise. The CAO is a sink for many pollutants such as microplastics, which have been found in sea ice and wildlife. Current and future threats to the ecoregion from human activities and pressures also include increased risk of oil spills and biodiversity loss if ocean mining expands into the Arctic. While the Agreement to Prevent Unregulated Fishing in the High Seas Portion of the Central Arctic Ocean entered into force in June 2021 bans commercial fishing in the high seas of the CAO, fish populations continue to be impacted by the effects of a warming ocean, retreating ice cover, and acidification. These threats have important ecological and policy implications for the entire foodweb and the Arctic community. During this past year, WGICA has further studied and described human activities and resulting pressures. In the next three years, WGICA will identify ecological, economic, social and institutional research questions, f

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.

Each winter, the North Atlantic Ocean is the stage for numerous cyclones, the most severe ones leading to seabird mass-mortality events called “winter wrecks.” During these, thousands of emaciated seabird carcasses are washed ashore along European and North American coasts. Winter cyclones can therefore shape seabird population dynamics by affecting survival rates as well as the body condition of surviving individuals and thus their future reproduction. However, most often the geographic origins of impacted seabirds and the causes of their deaths remain unclear. We performed the first ocean-basin scale assessment of cyclone exposure in a seabird community by coupling winter tracking data for ∼1,500 individuals of five key North Atlantic seabird species (Alle alle, Fratercula arctica, Uria aalge, Uria lomvia, and Rissa tridactyla) and cyclone locations. We then explored the energetic consequences of different cyclonic conditions using a mechanistic bioenergetics model and tested the hypothesis that cyclones dramatically increase seabird energy requirements. We demonstrated that cyclones of high intensity impacted birds from all studied species and breeding colonies during winter but especially those aggregating in the Labrador Sea, the Davis Strait, the surroundings of Iceland, and the Barents Sea. Our broad-scale analyses suggested that cyclonic conditions do not increase seabird energy requirements, implying that they die because of the unavailability of their prey and/or their inability to feed during cyclones. Our study provides essential information on seabird cyclone exposure in a context of marked cyclone regime changes due to global warming.

Identifying drivers of population trends in migratory species is difficult, as they can face many stressors while moving through different areas and environments during the annual cycle. To understand the potential of migrants to adjust to perturbations, it is critical to study the connection of different areas used by different populations during the annual cycle (i.e. migratory connectivity). Using a large-scale tracking data set of 662 individual seabirds from 2 sympatric auk meta-populations (common guillemots Uria aalge and Brünnich’s guillemots U. lomvia) breeding in 12 colonies throughout the Northeast Atlantic, we estimated migratory connectivity in seasonal space use as well as occupied environmental niches. We found strong migratory connectivity, within and between species. This was apparent through a combination of seasonal space use and occupied environmental niches. Brünnich’s guillemot populations grouped into 2 and common guillemot populations into 5 previously undescribed spatiotemporal clusters. Common guillemot populations clustered in accordance with the variable population trends exhibited by the species, while Brünnich’s guillemot populations are declining everywhere where known within the study area. Individuals from different breeding populations in both species were clustered in their space and environmental use, utilising only a fraction of the potential species-wide range. Further, space use varied among seasons, emphasising the variable constraints faced by both species during the different stages of their annual cycle. Our study highlights that considering spatiotemporal dynamics, not only in space but also in occupied environmental niches, improves our understanding of migratory connectivity and thus population vulnerability in the context of global change.

We explored the implications of reaching the Paris Agreement Objective of limiting global warming to <2°C for the future winter distribution of the North Atlantic seabird community. We predicted and quantified current and future winter habitats of five North Atlantic Ocean seabird species (Alle alle, Fratercula arctica, Uria aalge, Uria lomvia and Rissa tridactyla) using tracking data for ~1500 individuals through resource selection functions based on mechanistic modeling of seabird energy requirements, and a dynamic bioclimate envelope model of seabird prey. Future winter distributions were predicted to shift with climate change, especially when global warming exceed 2°C under a “no mitigation” scenario, modifying seabird wintering hotspots in the North Atlantic Ocean. Our findings suggest that meeting Paris agreement objectives will limit changes in seabird selected habitat location and size in the North Atlantic Ocean during the 21st century. We thereby provide key information for the design of adaptive marine‐protected areas in a changing ocean.

Aim: In migratory species, individuals often use fixed and individual‐specific migration strategies, which we term individual migration strategy fidelity (IMSF). Our goal was to test if guillemots have flexible or fixed individual migration strategies (i.e. IMSF), if this behaviour is consistent across large parts of the genus’ range and if they were philopatric to geographical sites or a habitat feature. Location: North Atlantic. Taxon: Uria spp. Methods: We quantified consistent individual differences in inter‐annual spatial distribution and habitat occupied throughout the non‐breeding period using a large geolocator tracking dataset of 729 adult seabirds breeding at 13 colonies across the Northeast Atlantic and repeatedly tracked up to 7 years over a 9‐year period. Additionally, we used a similarity index to calculate relative fidelity to either geographical sites or habitats and linear mixed‐effects models to assess persistence of spatial site fidelity over multiple years. Results: Both guillemot species exhibited IMSF across a large part of the genus’ range which persisted over multiple years. Individuals of both species and almost all colonies showed fidelity to geographical sites and not to specific habitats. Main conclusions: Guillemots show IMSF that is best explained by site familiarity (fidelity to specific sites) rather than habitat specialization (fidelity to specific habitats). In the context of rapidly changing environments, favourable habitats may permanently shift locations and hence species displaying IMSF driven by site familiarity—such as the genus Uria—may not be able to adjust their migration strategies sufficiently fast to sustain individual fitness and ensure population persistence.

Continental slopes – steep regions between the shelf break and abyssal ocean – play key roles in the climatology and ecology of the Arctic Ocean. Here, through review and synthesis, we find that the narrow slope regions contribute to ecosystem functioning disproportionately to the size of the habitat area (∼6% of total Arctic Ocean area). Driven by inflows of sub-Arctic waters and steered by topography, boundary currents transport boreal properties and particle loads from the Atlantic and Pacific Oceans along-slope, thus creating both along and cross-slope connectivity gradients in water mass properties and biomass. Drainage of dense, saline shelf water and material within these, and contributions of river and meltwater also shape the characteristics of the slope domain. These and other properties led us to distinguish upper and lower slope domains; the upper slope (shelf break to ∼800 m) is characterized by stronger currents, warmer sub-surface temperatures, and higher biomass across several trophic levels (especially near inflow areas). In contrast, the lower slope has slower-moving currents, is cooler, and exhibits lower vertical carbon flux and biomass. Distinct zonation of zooplankton, benthic and fish communities result from these differences. Slopes display varying levels of system connectivity: (1) along-slope through property and material transport in boundary currents, (2) cross-slope through upwelling of warm and nutrient rich water and down-welling of dense water and organic rich matter, and (3) vertically through shear and mixing. Slope dynamics also generate separating functions through (1) along-slope and across-slope fronts concentrating biological activity, and (2) vertical gradients in the water column and at the seafloor that maintain distinct physical structure and community turnover. At the upper slope, climatic change is manifested in sea-ice retreat, increased heat and mass transport by sub-Arctic inflows, surface warming, and altered vertical