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Bird migration is commonly defined as a seasonal movement between breeding and non-breeding grounds. It generally involves relatively straight and directed large-scale movements, with a latitudinal change, and specific daily activity patterns comprising less or no foraging and more traveling time. Our main objective was to describe how this general definition applies to seabirds. We investigated migration characteristics of 6 pelagic seabird species (little auk Alle alle, Atlantic puffin Fratercula arctica, common guillemot Uria aalge, Brünnich’s guillemot U. lomvia, black-legged kittiwake Rissa tridactyla and northern fulmars Fulmarus glacialis). We analysed an extensive geolocator positional and saltwater immersion dataset from 29 colonies in the North-East Atlantic and across several years (2008-2019). We used a novel method to identify active migration periods based on segmentation of time series of track characteristics (latitude, longitude, net-squared displacement). Additionally, we used the saltwater immersion data of geolocators to infer bird activity. We found that the 6 species had, on average, 3 to 4 migration periods and 2 to 3 distinct stationary areas during the non-breeding season. On average, seabirds spent the winter at lower latitudes than their breeding colonies and followed specific migration routes rather than non-directionally dispersing from their colonies. Differences in daily activity patterns were small between migratory and stationary periods, suggesting that all species continued to forage and rest while migrating, engaging in a ‘fly-and-forage’ migratory strategy. We thereby demonstrate the importance of habitats visited during seabird migrations as those that are not just flown over, but which may be important for re-fuelling.

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 ∼ 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. at-sea distributioncyclonesenergy expenditureGLS trackingseabird migrationseascape ecology North Atlantic winter cyclones starve seabirds

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 (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.

Seabird-fishery interactions are a common phenomenon of conservation concern. Here, we highlight how light-level geolocators provide promising opportunities to study these interactions. By examining raw light data, it is possible to detect encounters with artificial lights at night, while conductivity data give insight on seabird behaviour during encounters. We used geolocator data from 336 northern fulmars Fulmarus glacialis tracked from 12 colonies in the North-East Atlantic and Barents Sea during the non-breeding season to (1) confirm that detections of artificial lights correspond to encounters with fishing vessels by comparing overlap between fishing effort and both the position of detections and the activity of birds during encounters, (2) assess spatial differences in the number of encounters among wintering areas and (3) test whether some individuals forage around fishing vessels more often than others. Most (88.1%) of the tracks encountered artificial light at least once, with 9.5 ± 0.4 (SE) detections on average per 6 mo non-breeding season. Encounters occurred more frequently where fishing effort was high, and birds from some colonies had higher probabilities of encountering lights at night. During encounters, fulmars spent more time foraging and less time resting, strongly suggesting that artificial lights reflect the activity of birds around fishing vessels. Inter-individual variability in the probability of encountering light was high (range: 0-68 encounters per 6 mo non-breeding season), meaning that some individuals were more often associated with fishing vessels than others, independently of their colony of origin. Our study highlights the potential of geolocators to study seabird-fishery interactions at a large scale and a low cost.

Gulls are monomorphic in plumage characteristics but show a sexual size dimorphism where males are larger than females. In this study, we use discriminant function analyses (DFA) and generalised linear modelling (GLM) to provide sexing criteria based on morphometrics for adult and fledgling Lesser Black-backed Gulls Larus fuscus in Iceland. Males were significantly larger than females in all variables measured and this was the case for both age classes. For DFA the best sexing model for adults included skull length, bill depth and tarsus length and classified correctly 99.1% of the individuals sampled. For GLM only two variables, skull length and tarsus length, were needed for 100% classification of adult birds. The best sexing model for fledglings included skull length and tarsus length and classified correctly 89.4–91.5% of the individuals sampled, depending on the method. Individual sexing probability was much higher for adults than for fledglings, independent of the method used. However, indiv...

Background Foraging strategies of seabird species often vary considerably between and within individuals. This variability is influenced by a multitude of factors including age, sex, stage of annual life cycle, reproductive status, individual specialization and environmental conditions. Results Using GPS-loggers, we investigated factors affecting foraging flight characteristics (total duration, maximal range, total distance covered) of great skuas Stercorarius skua of known sex breeding on Bjørnøya, Svalbard, the largest colony in the Barents Sea region. We examined influence of sex (females are larger than males), phase of breeding (incubation, chick-rearing), reproductive status (breeders, failed breeders) and bird ID (they are known for individual foraging specialization). Our analyses revealed that only bird ID affected foraging flight characteristics significantly, indicating a high degree of plasticity regardless of sex, reproductive status or phase of breeding. We recognized three main groups of individuals: 1) those preying mainly on other seabirds in the breeding colonies (6%), 2) those foraging at sea (76%) and kleptoparasiting other seabirds and/or foraging on fish and/or offal discarded by fishing vessels, and 3) those alternating between preying on other seabirds in breeding colonies and foraging at sea (18%). Despite marked size sexual dimorphism, we found no apparent sex differences in flight characteristics. Birds after egg- or chick-loss and thus not constrained as central foragers did not modify their foraging flights. Conclusions Great skuas breeding on Bjørnøya displayed a high degree of plasticity regardless of sex, reproductive status or phase of breeding. We recognized groups of individuals regularly preying in the seabird colonies, foraging at sea, and alternating between both strategies. This suggests foraging specialization of some individuals.