International audienceSatellite telemetry data are a key source of animal distribution information for marine ecosystem management and conservation activities. We used two decades of telemetry data from the East Antarctic sector of the Southern Ocean. Habitat utilization models for the spring/summer period were developed for six highly abundant, wide-ranging meso- and top-predator species: Adélie Pygoscelisadeliae and emperor Aptenodytes forsteri penguins, light-mantled albatross Phoebetria palpebrata , Antarctic fur seals Arctocephalus gazella , southern elephant seals Mirounga leonina , and Weddell seals Leptony-chotes weddellii . The regional predictions from these models were combined to identify areas utilized by multiple species, and therefore likely to be of particular ecological significance. These areas were distributed across the longitudinal breadth of the East Antarctic sector, and were characterized by proximity to breeding colonies, both on the Antarctic continent and on subantarctic islands to the north, and by sea-ice dynamics, particularly locations of winter polynyas. These areas of important habitat were also congruent with many of the areas reported to be showing the strongest regional trends in sea ice seasonality. Th e results emphasize the importance of on-shore and sea-ice processes to Antarctic marine ecosystems. Our study provides ocean-basin-scale predictions of predator habitat utilization, an assessment of contemporary habitat use against which future changes can be assessed, and is of direct relevance to current conservation planning and spatial management efforts

Animal ecology is shaped by energy costs, yet it is difficult to measure finescale energy expenditure in the wild. Because metabolism is often closely correlated with mechanical work, accelerometers have the potential to provide detailed information on energy expenditure of wild animals over fine temporal scales. Nonetheless, accelerometry needs to be validated on wild animals, especially across different locomotory modes. We merged data collected on 20 thick-billed murres (Uria lomvia) from miniature accelerometers with measurements of daily energy expenditure over 24 h using doubly labelled water. Across three different locomotory modes (swimming, flying and movement on land), dynamic body acceleration was a good predictor of daily energy expenditure as measured independently by doubly labelled water (R 2 ¼ 0.73).The most parsimonious model suggested that different equations were needed to predict energy expenditure from accelerometry for flying than for surface swimming or activity on land (R 2 ¼ 0.81). Our results demonstrate that accelerometers can provide an accurate integrated measure of energy expenditure in wild animals using many different locomotory modes.

Measuring the costs of soaring, gliding and flapping flight in raptors is challenging, but essential for understanding their ecology. Among raptors, vultures are scavengers that have evolved highly efficient soaring-gliding flight techniques to minimize energy costs to find unpredictable food resources. Using electrocardiogram, GPS and accelerometer bio-loggers, we report the heart rate (HR) of captive griffon vultures (Gyps fulvus and G. himalayensis) trained for freely-flying. HR increased three-fold at take-off (characterized by prolonged flapping flight) and landing (>300 beats-per-minute, (bpm)) compared to baseline levels (80–100 bpm). However, within 10 minutes after the initial flapping phase, HR in soaring/gliding flight dropped to values similar to baseline levels, i.e. slightly lower than theoretically expected. However, the extremely rapid decrease in HR was unexpected, when compared with other marine gliders, such as albatrosses. Weather conditions influenced flight performance and HR was noticeably higher during cloudy compared to sunny conditions when prolonged soaring flight is made easier by thermal ascending air currents. Soaring as a cheap locomotory mode is a crucial adaptation for vultures who spend so long on the wing for wide-ranging movements to find food.