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Marine predators are integral to the functioning of marine ecosystems, and their consumption requirements should be integrated into ecosystem-based management policies. However, estimating prey consumption in diving marine predators requires innovative methods as predator-prey interactions are rarely observable. We developed a novel method, validated by animal-borne video, that uses tri-axial acceleration and depth data to quantify prey capture rates in chinstrap penguins (Pygoscelis antarctica). These penguins are important consumers of Antarctic krill (Euphausia superba), a commercially harvested crustacean central to the Southern Ocean food web. We collected a large data set (n = 41 individuals) comprising overlapping video, accelerometer and depth data from foraging penguins. Prey captures were manually identified in videos, and those observations were used in supervised training of two deep learning neural networks (convolutional neural network (CNN) and V-Net). Although the CNN and V-Net architectures and input data pipelines differed, both trained models were able to predict prey captures from new acceleration and depth data (linear regression slope of predictions against video-observed prey captures = 1.13; R2 approximate to 0.86). Our results illustrate that deep learning algorithms offer a means to process the large quantities of data generated by contemporary bio-logging sensors to robustly estimate prey capture events in diving marine predators.

Ecological niche theory predicts sympatric species to show segregation in their spatio-temporal habitat utilization or diet as a strategy to avoid competition. Similarly, within species individuals may specialize on specific dietary resources or foraging habitats. Such individual specialization seems to occur particularly in environments with predictable resource distribution and limited environmental variability. Still, little is known about how seasonal environmental variability affects segregation of resources within species and between closely related sympatric species. The aim of the study was to investigate the foraging behaviour of three closely related and sympatrically breeding fulmarine petrels (Antarctic petrels Thalassoica antarctica, cape petrels Daption capense and southern fulmars Fulmarus glacialoides) in a seasonally highly variable environment (Prydz Bay, Antarctica) with the aim of assessing inter- and intraspecific overlap in utilized habitat, timing of foraging and diet and to identify foraging habitat preferences. We used GPS loggers with wet/dry sensors to assess spatial habitat utilization over the entire breeding season. Trophic overlap was investigated using stable isotope analysis based on blood, feathers and egg membranes. Foraging locations were identified using wet/dry data recorded by the GPS loggers and expectation-maximization binary clustering. Foraging habitat preferences were modelled using generalized additive models and model cross-validation. During incubation and chick-rearing, the utilization distribution of all three species overlapped significantly and species also overlapped in the timing of foraging during the day—partly during incubation and completely during chick-rearing. Isotopic centroids showed no significant segregation between at least two species for feathers and egg membranes, and among all species during incubation (reflected by blood). Within species, there was no individual specialization in foraging sites or environmental space. Furthermore, no single environmental covariate predicted foraging activity along trip trajectories. Instead, best-explanatory environmental covariates varied within and between individuals even across short temporal scales, reflecting a highly generalist behaviour of birds. Our results may be explained by optimal foraging theory. In the highly productive but spatio-temporally variable Antarctic environment, being a generalist may be key to finding mobile prey—even though this increases the potential for competition within and among sympatric species.

The use of biologging instruments has greatly improved our understanding of the behaviour, physiology and ecology of free-ranging marine mammals. However, handling wild animals and attaching instruments to streamlined bodies can cause stress and potentially influence behaviour and swimming/diving energetics. The goals of this study, undertaken on Bouvetøya, were (1) to determine if the first trip to sea after instrumentation is representative of subsequent trips in lactating Antarctic fur seals, to explore potential handling effects and assess possible biases in having multiple short-duration deployments (inflating N, using a limited number of tags) and (2) to evaluate potential effects of two different instrument combinations (SMRU satellite data relay loggers and very high frequency radio transmitters versus Wildlife Computers time–depth recorders and very high frequency radio transmitters) on trip durations, dive parameters, female body condition and pup growth. Handling did not appear to have any effects on the parameters studied; data from the first and second trips did not differ significantly. This implies that multiple short-term deployments are unlikely to result in biased data in this species. Instrument type did have measurable effects; time-at-sea was greater and pup growth was lower for pairs in which mothers carried bulkier instruments. This suggests that instrument streamlining is important to avoid negative impacts and that bulkier equipment should be deployed on lactating females with caution and only for short periods. The study highlights that instrument effects should be taken into account when comparing data from experiments collected using different equipment packages. Keywords: Bioenergetics; biologging; instrument effects; SRDLs; TDRs; VHFs.

Miniature electronic data recorders and transmitters have revolutionized the way we study animals over the past decades, particularly marine animals at sea. But, very recently, animal-borne instruments have also been designed and implemented that provide in situ hydrographic data from parts of the oceans where little or no other data are currently available (even from beneath the ice in polar regions). Ocean data is delivered from animal-borne instruments via satellites in near real-time, which would enrich the Global Ocean Observing System if animal-borne instruments were deployed systematically. In the last 10 years, studies involving more than 10 countries (Australia, Brazil, Canada, France, Germany, Greenland, Norway, South Africa, UK, USA) have demonstrated how highly accurate oceanographic sensors, integrated into standard animal, biologging instruments, can provide data of equal or better quality than XBT/XCTD data. Here, we present some of the pioneering studies and demonstrate that we now have enough information for many marine species to predict where they will go – within reasonable limits. Thus, we can direct sampling effort to particularly interesting and productive regions and maximize data return. In the future, biologging could certainly play an important part in the Global Ocean Observing System, by providing complementary data to more traditional sampling technologies - especially in the high latitudes. This paper will make a core contribution to the Plenary Sessions 4A, 4B and 5A and will be relevant to 2A, 2B and 3A.