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Biologgers enable real‐time collection of detailed behavioural and physiological data from wide‐ranging animals, including seabirds inhabiting remote regions. However, the number of studies using tracking devices has not been matched by research exploring the behavioural and fitness costs of deployment, and the effects on data reliability. We assessed how GPS loggers, video loggers, and time depth recorders (TDRs) affect the behaviour, physiology, and reproductive performance of European shags Gulosus aristotelis breeding on Sklinna, Norway. The loggers varied in mass, attachment location and deployment duration, allowing comparison of their relative effects. Birds without loggers served as controls to assess logger‐related changes in adult body mass, chick growth, reproductive success, and survival. Birds with longer‐term tail‐mounted GPS loggers and leg‐mounted TDRs showed altered foraging behaviour, including shorter trips and dives, compared to birds with tail‐mounted GPS and TDRs of the same weight, instrumented for only two days. A mean loss in body mass was experienced by adult birds regardless of the logger type used, while chick growth rate dropped to 20% of that observed in control nests when video, TDR and GPS loggers (~ 4% of body mass) were deployed together. Logger attachments did not impact reproductive success, and overall logger birds showed higher survival than controls. However, female survival was lower than that of males among birds fitted with video and long‐term GPS loggers. Our results demonstrate the importance of measuring behavioural and physiological effects that can scale over time. The advances in our understanding of animal ecology and behaviour generated by biologging have been impressive, but there is a need to consider the impacts on animal welfare and data quality. Consistent reporting of logger deployment details is essential to assess biologging impacts across species and refine protocols that account for device weight, drag and attachment location.

For marine top predators like seabirds, the oceans represent a multitude of habitats regarding oceanographic conditions and food availability. Worldwide, these marine habitats are being altered by changes in climate and increased anthropogenic impact. This is causing a growing concern on how seabird populations might adapt to these changes. Understanding how seabird populations respond to fluctuating environmental conditions and to what extent behavioral flexibility can buffer variations in food availability can help predict how seabirds may cope with changes in the marine environment. Such knowledge is important to implement proper long-term conservation measures intended to protect marine predators. We explored behavioral flexibility in choice of foraging habitat of chick-rearing black-legged kittiwakes Rissa tridactyla during multiple years. By comparing foraging behavior of individuals from two colonies with large differences in oceanographic conditions and distances to predictable feeding areas at the Norwegian shelf break, we investigated how foraging decisions are related to intrinsic and extrinsic factors. We found that proximity to the shelf break determined which factors drove the decision to forage there. At the colony near the shelf break, time of departure from the colony and wind speed were most important in driving the choice of habitat. At the colony farther from the shelf break, the decision to forage there was driven by adult body condition. Birds furthermore adjusted foraging behavior metrics according to time of the day, weather conditions, body condition, and the age of the chicks. The study shows that kittiwakes have high degree of flexibility in their behavioral response to a variable marine environment, which might help them buffer changes in prey distribution around the colonies. The flexibility is, however, dependent on the availability of foraging habitats near the colony. central-place foragers, foraging decisions, GPS tracking, resource allocation, seabird

Many countries are developing offshore wind farms to provide renewable energy, yet such developments can harm biodiversity. Seabirds are a highly threatened group of birds and can be impacted by wind farms through lethal collisions and via sub‐lethal displacement effects. However, we do not have a comprehensive understanding of the impacts of offshore wind farms on seabird populations, particularly outside of the breeding season. We developed an individual‐based model to predict the non‐breeding season impacts of offshore wind farms on seabirds. We used long‐term tracking data obtained from geolocation‐immersion loggers to estimate population‐level distributions and activity budgets. We simulated individual behaviour, movement, wind farm interactions (collision and displacement) and any resulting lethal or sub‐lethal effects. We demonstrated our model by assessing the impact of 10 simulated offshore wind farms on two populations that breed in Norway: common guillemots Uria aalge (Sklinna) and black‐legged kittiwakes Rissa tridactyla (Ålesund). We quantified collision risk in kittiwakes and sub‐lethal displacement effects in guillemots and converted these effects into a change in survival or end of season body mass as a proxy for condition. We predicted that 49.6% of guillemots breeding at Sklinna would experience displacement effects during the non‐breeding season. As the energetic impact of displacement is relatively unknown, we modelled a range of possible displacement costs and present several impact scenarios, with adult mortality levels ranging from 0% to 5.32% and end of season body masses of 97.12%–99.84% compared to those resulting from an unimpacted scenario. Despite 98.9% of kittiwakes flying through at least one wind farm footprint, we only predicted collisions in 0.055% of the population; this low mortality was primarily driven by low overlap between the modelled height of the turbine rotors and the probable flight height of kittiwakes. Practical implication: Our model provides a tool that can be used to assess the non‐breeding season impacts of OWFs on seabird populations, improving sustainability when developing renewable energy infrastructure. We highlight several key limitations as areas of research that are required to reduce uncertainty when predicting impacts. Our model is reproducible and adaptable for use on other species or for other marine threats. Sammendrag Mange land etablerer nå havvindanlegg for å kunne produsere fornybar energi. En slik utbygging kan imidlertid påvirke det biologiske mangfoldet negativt. Sårbare sjøfuglarter risikerer for eksempel økt dødelighet ved kollisjon med turbinene, og kan bli fortrengt fra viktige beite‐ og leveområder hvilket kan påvirke kroppskondisjon og overlevelse. Vi mangler imidlertid en helhetlig forståelse av den samlede påvirkning av havvindanlegg på sjøfuglbestander, især utenfor hekkesesongen. Vi utviklet en individbasert modell for å predikere påvirkningen fra havvindanlegg på sjøfugl utenfor hekkesesongen. Med utgangspunkt i lange tidsserier med sporingsdata fra lys‐ og saltvannsloggere, beregnet vi sjøfuglenes utbredelse og aktivitetsbudsjetter på populasjonsnivå. Vi simulerte sjøfuglenes individuelle bevegelse, atferd, energiforbruk og interaksjon med havvindanlegg, og estimerte eventuelle dødelige eller sub‐letale effekter. Vi demonstrerer modellen gjennom en vurdering av påvirkningen fra ti simulerte havvindanlegg på to norske hekkebestander av sjøfugl: lomvi Uria aalge (fra Sklinna) og krykkje Rissa tridactyla (fra Ålesund). For krykkje estimerte vi kollisjonsrisikoen. For lomvi estimerte vi de sub‐letale effektene av fortrengning fra næringsområdene, og estimerte hvordan denne fortrengningen førte til endringer i overlevelse eller kroppskondisjon ved slutten av sesongen basert på energibudsjetter og endring i kroppsvekt. Vi predikerte at 49,6% av lomviene som hekker på Sklinna vil oppleve å bli fortrengt av havvindanlegg utenfor hekkesesongen. Siden den energetiske effekten av fortrenging er usikker, modellerte vi ulike kostnader ved fortrengningen, og presenterer ulike effektscenarioer med mortalitetsnivåer fra 0 til 5,32% og kroppsmasse ved slutten av sesongen fra 97,12 til 99,84% sammenlignet med et nulleffekt scenario. Til tross for at 98,9% av de modellerte krykkjene fløy gjennom vindparkens fotavtrykk minst en gang i løpet av perioden, predikerte vi bare tre faktiske kollisjoner (0,055%). Dette skyldes at den modellert høyden på turbinbladene var betydelig høyere enn den typiske flygehøyden til krykkjene. Modellen som er utviklet kan brukes til å vurdere effekten av havvindanlegg på sjøfuglbestander utenfor hekkeperioden, og vil dermed gi nyttig informasjon ved utvikling av fornybar energi til havs. Vi identifiserer viktige begrensninger hvor et bedre kunnskapsgrunnlag vil redusere usikkerheten i beregningen av effekter. Modellen er reproduserbar, og kan tilpasses for bruk på andre arter og marine påvirkningsfaktorer. A novel individual‐based model to predict the impacts of offshore wind farms on seabirds during the non‐breeding season, using long‐term tracking data from SEATRACK. We demonstrate the model by simulating wind farm impacts on two Norwegian populations: common guillemots from Sklinna (sub‐lethal displacement effects) and black‐legged kittiwakes from Ålesund (lethal collisions). The model helps reduce uncertainty in marine spatial planning, supporting more sustainable development of offshore renewable energy.

The general decline of seabird populations worldwide raises large concerns. Although multiple factors are interacting to cause the observed trends, increased mortality from incidental bycatch in fisheries has proven to be important for many species. However, the bulk of published knowledge is derived from longline fisheries, whereas bycatch in gillnet fisheries is less studied and even overlooked in some areas. We present seabird bycatch data from a 10-year time-series of fishery data from the large fleet of small-vessels fishing with gillnets along the Norwegian coast—a large area and fishery with no prior estimates of seabird bycatch. In general, we document high rates of incidental bycatch (averaging 0.0023 seabirds/ net, or approximately 0.08 seabirds/fishing trip). This results in an estimated annual bycatch between 1580 and 11500 (95% CI) birds in this fishery. There was a surprisingly high percentage (43%) of surface-feeding seabirds in the bycatch, with northern fulmar being the most common species. Among the diving seabirds caught, common guillemot was most numerous. Our findings suggest that coastal gillnet fisheries represent a more general threat to a wider range of seabird populations, as opposed to longline fisheries where surface-feeding seabird species seem to dominate the bycatch. The bycatch estimates for the Norwegian gillnet-fishery varied in time, between areas, and with fishing depth and distance from the coast, but we found no clear trends in relation to the type of gillnets used. The results enabled us to identify important spatio-temporal trends in the seabird bycatch, which can allow for the development and implementation of more specific mitigation measures. While specific time closures might be an efficient option to reduce bycatch for diving seabirds, measures such as gear modification and reduction in release of wastewater during fishing operation are probably a more effective mitigation approach for reducing bycatch of surface-feeding seabirds.

In seasonal environments, organisms are expected to optimally schedule reproduction within an annual range of environmental conditions. Latitudinal gradients generate a range of seasonality to which we can expect adaptations to have evolved, and can be used to explore drivers of timing strategies across species’ distribution ranges. This study compares the timing of egg hatching in four seabird species (Atlantic puffin Fratercula arctica, black-legged kittiwake Rissa tridactyla, common guillemot Uria aalge, and Brünnich’s guillemot U. lomvia) covering a subarctic to Arctic latitudinal gradient along the Norwegian coast to Svalbard (65–79°N). Hatching was significantly delayed by an estimated 1.7, 2.3, and 1.9 d per latitudinal degree for puffins, kittiwakes, and common guillemots, respectively, but was not delayed for Brünnich’s guillemots. Hatching distributions revealed an increase in intra-annual breeding synchronicity along a latitudinal gradient for kittiwakes only, whereas the two guillemots exhibited high hatching synchronicity at all colonies. We used this large-scale, multispecies timing data series to discuss constraints, adaptations, and mechanisms affecting breeding timing, a necessary step to recognize risks to populations and predict future ecosystem change. Arctic; Fratercula arctica; hatching timing; inter-annual variability; Rissa tridactyla; seasonality; spatial phenology; Uria aalge; Uria lomvia. Received

Introduction: Offshore wind energy development (OWED) has been identified as a major contributor to the aspired growth in Norwegian renewable energy production. Spatially explicit vulnerability assessments are necessary to select sites that minimize the harm to biodiversity, including seabird populations. Distributional data of seabirds in remote areas are scarce, and to identify vulnerable areas, species, and seasons it is necessary to combine data sets and knowledge from different sources.Methods: In this study, we combined seabird tracking data, data from dedicated coastal and seabird at-sea surveys, and presence-only data from citizen science databases to develop habitat suitability maps for 55 seabird species in four seasons throughout the Norwegian exclusive economic zone; in total 1 million km 2 in the Northeast Atlantic. The habitat suitability maps were combined with species-specific vulnerability indicators to yield maps of seabird vulnerability to offshore wind farms (OWFs). The resulting map product can be used to identify the relative vulnerability of areas prospected for OWED with respect to seabird collision and habitat displacement. More detailed assessments can be done by splitting the spatial indicators into seasonal and species-specific components.Results and Discussion: Associated with higher diversity of seabirds near the coast, the cumulative vulnerability indicator showed a strong declining gradient from the coast to offshore waters while the differences in vulnerability between ocean areas and seasons were negligible. Although the present map product represents the best currently available knowledge, the indicators are associated with complex uncertainties related to known and unknown sampling biases. The indicators should therefore be used cautiously, they should be updated regularly as more data become available, and we recommend that more detailed environmental impact assessments based on dedicated seabird surveys, tracking of birds from potentially affected populations and population viability analyses are conducted in areas ultimately selected for OWED.

Human activity in the coastal zone is increasing worldwide, putting a number of seabird species under pressure. Norway is no exception to this development, and with > 35% of the NE Atlantic population of the currently declining European shag (Gulosus aristotelis) population, Norway has an international responsibility for the conservation of this species, and its important foraging habitats during breeding. We analysed tracking data from shags breeding in five colonies along the Norwegian coast spread over a latitudinal gradient of > 1700 km. We identified foraging locations and associated environmental characteristics. Using model cross-validation, we assessed the transferability of habitat models, both spatially (across colonies) and temporally (within colonies and across years), based on three modelling approaches: Training datasets consisted either of the data from one year at one colony, all years at one colony, or all years from all colonies except the testing colony. Across colonies, foraging activity was associated with shallow depths, proximity to colony, and the presence of kelp forests, while sea surface temperature and sea surface height contributed little to model fit. Transferability of habitat use across colonies was low when based on the training data from only one year and one colony and improved little when using several years of data from one colony for training the models. Transferability was very high for all colonies if the training dataset consisted of data from all years and all colonies except the one to be predicted. Our results highlight the importance of multi-year and multi-colony studies and show that it is possible to make sound finescale predictions of important foraging areas for breeding shags without the need to track birds in every colony. This facilitates much needed management of coastal marine ecosystems and the protection of the most important feeding areas for breeding shags. expectation-maximization binary clustering (EMBC), Norwegian coastal zone, kelp forest, bathymetry, foraging range, sea surface temperature, sea surface height, model transferability

Validation of age estimation from tooth cementum growth layers was conducted for 32 polar bears (Ursus maritimus) of known age, by two readers. Both readers correctly estimated age for 24% of the bears, and 50-53% were within the year of correct age. The age of young animals (age 1-8) was overestimated, while ages for bears over 8 years were underestimated. Comparison between the readings of the two readers indicated that the precision was low. Further, one of the readers reread tooth slides earlier prepared and read by another age estimation laboratory. There was a large discrepancy between these readings indicating a bias in the ages estimated. We conclude that age estimation of polar bears can be difficult, particularly in populations where individuals may forage throughout the year. As tooth growth layers may deposit differently for bears from different areas, and as different laboratories may read the same slides according to different criteria, an evaluation of the methods should be conducted for all populations, based on a significant number of tooth slides, with a broad age range, from animals of known age.

Seabird populations have declined worldwide, and several of the potential threats are of anthropogenic origin. To understand how changes in seabird populations relate to environmental conditions it is important to know the functional relationships between prey availability and foraging behaviour, prey choice and breeding performance over several years. This was studied by linking breeding success of European shag Phalacrocorax aristotelis to variation in diet composition, and investigating the underlaying mechanism driving this variation, primarily based on be - havioural costs associated with foraging, such as foraging range and diving effort. We obtained demographic data and foraging trip metrics (using GPS-loggers and time−depth recorders) from a shag colony at Sklinna, Central Norway, during the 2011−2016 breeding seasons. Breeding population size was closely and positively correlated with breeding success, which in turn was positively correlated with the proportion of saithe Pollachius virens in the diet. When the dietary proportion of uncommon prey species increased, breeding success decreased. Breeding success was negatively influenced by increasing distance travelled and accumulated dive depths on an annual basis. Summed dive depths were greatest when prey species other than saithe dominated the diet. We found that in years with low availability of saithe fewer shags bred, and those that did had lower breeding success. This indicates that in years with poor feeding conditions, there might not be sufficient resources in the foraging area to support the whole breeding population of shags.

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.