Six pelagic seabird species of the North Atlantic engage in a fly-and-forage strategy during their migratory movements

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.publishedVersio

Dose dependent effects of plumage-oiling on thermoregulation of common eiders Somateria mollissima residing in water

Thermoregulatory effects which occur during the first hours after plumage-oiling were studied under laboratory conditions by measuring the metabolic heat production of common eiders (Somateria mollissima) which were resting in water for up to three hours. The ducks were exposed to 10-70 mL Statfjord A crude oil while residing in water inside a respiration chamber at 5.5°C. The study demonstrated a dose-and time-dependent effect of plumage oiling on metabolic heat production during the first three hours after contact with the oil. The results indicate that the immediate, short-term effects following initial contact with oil at sea are lesser in scale than those which occur after the birds have preened the oil into a greater part of their plumage. After plumage contamination with 70 mL crude oil, the rate of heat loss exceeded the thermoregulatory heat production capacity and the eiders became hypothermic within 70 minutes after contamination

Age, body mass, mass change and dispersal distance of suckling and weaned grey seal (Halichoerus grypus) pups

Grey seal, Halichoerus grypus, pups in the breeding colony at Froan, Norway, have a bimodal pattern of early aquatic behaviour. About 40% of the pups spend their time ashore to save energy, which can be allocated to growth or deposition of energy-rich adipose tissue. The other 60% of the pups enter the sea during suckling and the early postweaning period, and disperse to other locations within the breeding colony. Pups may swim distances up to 12 km. Neonatal aquatic dispersal behaviour may lead to increased energy expenditure for thermoregulation and swimming, and thus lead to a low rate of body mass gain during suckling and a high rate of body mass loss after weaning. Thus, we examined relationships between natal aquatic dispersal behaviour and change in body mass (DeltaBM) in suckling and weaned pups. Suckling pups that had dispersed >2000 m had a significantly lower DBM than suckling pups that dispersed <2000 m or that did not disperse. In weaned pups, there were no effects of aquatic dispersal behaviour on DBM. We suggest that the bimodal natal aquatic dispersal behaviour in grey seals at the study site reflects two different strategies for postweaning survival: to stay ashore and get fat, or to take a swim and acquire diving and feeding skills

Arctic-breeding seabirds’ hotspots in space and time - A methodological framework for year-round modelling of environmental niche and abundance using light-logger data

Fauchald, P., Tarroux, A., Bråthen, V. S., Descamps, S., Ekker, M., Helgason, H. H., Merkel, B., Moe, B., Åström, J., Strøm, H. 2019. Arctic-breeding seabirds’ hotspots in space and time -a methodological framework for year-round modelling of abundance and environmen-tal niche using light-logger data. NINA Report 1657. Norwegian Institute for Nature Re-search. By positioning a large number of seabirds throughout the year using miniaturized geoloca-tors (GLS), the SEATRACK program provides a unique dataset on the seasonal distribution of seabirds from colonies in Russia (Barents and White Seas), Norway (incl. Svalbard and Jan Mayen), Iceland, Faroe Islands and the British Isles. Combining this extensive dataset with data on population sizes has for the first time made it possible to develop seasonal estimates of the spatial distribution of Northeast Atlantic seabirds. In this report, we document the workflow and methods used to develop monthly estimates of the distribution of seabirds from colonies covered by the SEATRACK design. The work-flow presented here consists of three steps, starting from pre-processed GLS data. First, because the position data from the loggers represent “presence-only” data, it is vital to re-move sampling biases before using the data to make interpretations of the spatial distribu-tion. Therefore, in step 1 we developed a tailored algorithm, IRMA (Informed Random Move-ment Algorithm), to reduce biases and fill gaps in the dataset due to various factors such as polar day/night, equinox and positions over land. IRMA uses available information and data to triangulate new positions and does ultimately provide a dataset where sampling biases has been reduced to a minimum. In the next step, we combined the position dataset with environmental data to model the habitat of each SEATRACK colony throughout the year. Environmental variables included remote sensing data of oceanography and primary pro-duction, and data on bathymetry. We used standard Species Distribution Models (SDM) on presence-only data to model the habitat used by each SEATRACK colony in each month. Finally, in step 3 we combined the predictions from the habitat models with available data on the populations covered by the SEATRACK design to provide predictions on seabird spatial distribution and abundance. A colony database was compiled to address the popu-lation sizes, and spatial analyses were conducted to justify a distance-rule for assigning the colonies in the colony database to the nearest SEATRACK colony. Based on the distance rule, we predicted the habitat for each colony covered by the SEATRACK design and weighted the estimates with population size. According to the distance-rule, the SEATRACK design covered from 74% to 96% of the Northeast Atlantic populations, depending on spe-cies. Analyses and predictions were done for six common pelagic seabirds: Northern fulmar (Ful-marus glacialis), black-legged kittiwake (Rissa tridactyla), common guillemot (Uria aalge), Brünnich’s guillemot (Uria lomvia), little auk (Alle alle) and Atlantic puffin (Fratercula arctica). The resulting datasets represent monthly estimates of the number of birds from a specific breeding population in each cell of a 0.1° x 0.1° raster grid covering the entire North Atlantic. Monthly outputs were produced for each combination of species and colony, resulting in a dataset of more than 9619 raster maps. The gridded data are provided NetCDF files, one per species, and a short R-script is provided for reading, plotting and aggregating the data. An interactive mapping tool will be made available through the SEATRACK website. Appli-cations for the new tool include marine spatial planning, environmental impact- and risk as-sessments as well as assessments of seabird responses to environmental and climate change

An automated procedure (v2.0) to obtain positions from light-level geolocators in large-scale tracking of seabirds. A method description for the SEATRACK project

Bråthen, V.S., Moe, B., Amélineau, F., Ekker, M., Fauchald, P.,Helgason, H.H., Johansen, M. K., Merkel, B., Tarroux, A., Åström, J. & Strøm, H. 2021. An automated procedure (v2.0) to obtain positions from light-level geolocators in large-scale tracking of seabirds. A method description for the SEATRACK project. NINA Report 1893. Norwegian Institute for Nature Research. Partners in the SEATRACK project have since 2014 deployed >14 000 light-level geolocators on 11 species of seabirds to study their non-breeding distribution in the North Atlantic. Geolocator tags are ideal for large-scale tracking of seabirds being cheap and small. The tags contains a clock and a light sensor that register light levels at fixed intervals. These data are stored in the internal memory and are obtained when the tag is recovered from the bird. From these data two positions per day are calculated by estimating latitude from the length of day and night, and longitude from time of mid-day and mid-night. However, positions cannot be obtained from recorded light-data during the polar night or midnight sun. Further, the latitudinal accuracy is unreliable close to spring and autumn equinox when the length of day and night is similar across the earth. Using a threshold method, we first identify twilight events, which is the time when light-levels cross a predefined threshold that separate day from night. However, the light-level recordings are affected by environmental factors and the behaviour of the bird that may shade the geolocator or expose it to artificial light. As such, the accuracy is low compared to GPS or Argos tracking devices. A common approach has therefore been to improve the identification of these twilight events by manually inspecting the light-level data. This process is, however, time-consuming and prone to not being fully consistent and reproducible among different persons applying it. In this report, we describe an automated procedure (v2.0) for obtaining the basic positional dataset in SEATRACK from raw light-level data. The procedure automatically filters and edits the twilight events used for calculating positions. It further removes unrealistic positions using filters on equinox periods, speed, distribution, angle, distance, variation in timing of twilights and midnight sun periods, and produces double smoothed positions. Calibration of sun elevation angles, crucial for producing the final positions, is performed on each track and is the only part involving subjective assessment, but we show that it can be performed consistently and with a high repeatability. SEATRACK processes light data from >1000 geolocators after each field season, and the database has become one of the largest seabird tracking databases in the world. The automated procedure (v2.0) is a very cost-efficient method for such large-scale tracking and is consistent and reproducible. We have recently updated the entire database using this procedure, replacing all previous data based on the manual procedure and the first version of the automated procedure (v1.0). This report describes the methods used to obtain positions from geolocators in the SEATRACK project. As the described procedure replace our previous manual method, we show comparisons of the two procedures. The report also provides examples of how to read and visualize the positional data and can serve as the reference for the methods and as a tool for using the data