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Our study makes use of a fortuitous oceanographic data set collected around the remote sub-Antarctic island of Bouvetøya by a conductivity–temperature–depth recorder (CTD) integrated with a satellite-relayed data logger deployed on an adult female southern elephant seal (Mirounga leonina) to describe the seasonal evolution of the western shelf waters. The instrumented seal remained in waters over the shelf for 259 days, collecting an average of 2.6 (±0.06) CTD profiles per day, providing hydrographic data encompassing the late austral summer and the entire winter. These data document the thermal stratification of the upper water layer due to summer surface heating of the previous year's Antarctic Surface Water, giving way to a cold subsurface layer at about 100 m as the austral winter progressed, with a concomitant increase in salinity of the upper layer. Upper Circumpolar Deep Water was detected at a depth of approximately 200 m along the western shelf of Bouvetøya throughout the year. These oceanographic data represent the only seasonal time series for this region and the second such animal–instrument oceanographic time series in the sub-Antarctic domain of the Southern Ocean.

The Antarctic fur seal (Arctocephalus gazella) is a key marine predator in the Southern Ocean, a region that has recently started to show changes as a result of global climate change. Here, carbon (δ 13 C) and nitrogen (δ 15 N) stable isotope analyses on whole blood and plasma samples were used to examine the isotopic niche of lactating female Antarctic fur seals. Using recently developed Bayesian approaches to determine changes in isotopic niche, a significant increase in δ 13 C and δ 15 N was found between 1997 and 2015; this change occurred at an average rate of 0.067‰ (δ 13 C) and 0.072‰ (δ 15 N) per year over this period. This suggests that a marked isotopic niche shift has occurred over this period, which very likely corresponds to a shift in diet towards prey at a higher trophic level, such as fish (replacing krill). Although our sampling design prevented us from exploring a seasonal trend in a conclusive manner, our data suggest that concurrent increases in δ 13 C and δ 15 N might occur as the breeding season progresses. At a seasonal scale, an average decrease of −0.7‰ per month (95% confidence interval=[−0.9; −0.6]) in δ 13 C might have occurred, concurrently with an average increase of 1.1‰ per month in δ 15 N. The results of this study constitute the first isotopic assessment for female Antarctic fur seals from Bouvetøya and provide a baseline for the use of this predator species as a sentinel of the marine trophic system in one of the least studied areas within this species' distributional range.

Species with similar ecological requirements that overlap in range tend to segregate their niches to minimize competition for resources. However, the niche segregation possibilities for centrally foraging predators that breed on isolated Subantarctic islands may be reduced by spatial constraints and limitations in the availability of alternative prey. In this study we examined spatial and trophic aspects of the foraging niches of two sympatrically breeding penguin species, macaroni (Eudyptes chrysolophus; MAC) and chinstrap (Pygoscelis antarcticus; CHIN) penguins, at Bouvetøya over two breeding seasons. To measure at-sea movements and diving behaviour, 90 MACs and 49 CHINs were equipped with GPS loggers and dive recorders during two austral summer breeding seasons (2014/15 and 2017/18). In addition, blood samples from tracked birds were analysed for stable isotopes to obtain dietary information. CHINs displayed marked interannual variation in foraging behaviour, diving deeper, utilizing a larger foraging area and displaying enriched values of δ15N in 2014/15 compared to the 2017/18 breeding season. In contrast, MACs dove to similar depths and showed similar δ15N values, while consistently utilizing larger foraging areas compared to CHINs. We suggest that low krill abundances in the waters around Bouvetøya during the 2014/15 season resulted in CHINs shifting toward a diet that increased their niche overlap with MACs. Our findings may partly explain the decreasing number of breeding CHINs at the world’s most remote island, Bouvetøya, while also highlighting the importance of characterizing niche overlap of species using multi-season data sets.

There is increasing interest in using higher-trophic level predators as ecosystem indicators because their performance is presumed to be linked to the overall function of the ecosystem that supports them. In the southwest Atlantic sector of the Southern Ocean, Antarctic krill (Euphausia superba) supports huge predator populations as well as a growing commercial fishery. To utilize information from the ecosystem in an adaptive framework for sustainably managing krill catch levels, performance indices of krill predators have been proposed as a proxy for krill abundance. However, there are several potentially confounding sources of variability that might impact predator performance such as the effects of environmental variability and fishing pressure on krill availability at scales relevant to predators. In this context, our study capitalises on the occurrence of an unexpected El Niño event to characterise how environmental variability can drive changes in predator foraging behaviour. We demonstrate a clear link between coastal downwelling and changes in the at-sea habitat usage of chinstrap penguins (Pygoscelis antarctica) foraging in a local krill fishing area. Penguins tracked from their breeding colonies on Powell Island, Antarctic Peninsula, undertook fewer, longer foraging trips during the downwelling-affected season compared with the season where no such downwelling was detected, suggesting that changes in climate-driven oceanography may have reduced krill availability along the northern shelf of the island. Our study demonstrates that penguin foraging behaviour is modified by scale-dependent processes, which if not accounted for may result in erroneous conclusions being drawn when using penguins as bioindicators of krill abundance.

Krillscan software was developed to automatically process echosounder data and achieve an accelerated and transparent analysis of backscatter data that allows calculation of target biomass. Herein, the fishery for Antarctic krill (Euphausia superba, Henceforth Krill) was used as a case study to develop the approach. Implementation of a sustainable management strategy for the krill fishery is complicated by a lack of regularly updated krill abundance data on spatiotemporal scales of the fishery. To increase krill biomass data availability, automatic echosounder data processing and swarm detection software was tested against traditional manual scrutinization with LSSS software and agreed with only minor offsets in estimated nautical area scattering coefficients. In addition to automatic processing and data transfer, Krillscan also has a graphical user interface to supervise automatic krill swarm detection. Echogram size can be compressed up to 100 times and raw data are processed faster than generated, thereby enabling near-real time analysis and data transfer. Compressed data can be transmitted online to allow fishing vessels to conduct surveys without having scientific personnel with special expertise on board.

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.

Antarctic fur seal (Arctocephalus gazella) colonies are found on sub-Antarctic islands around the continent. These islands experience a range of conditions in terms of physical and biological habitat, creating a natural laboratory to investigate local genetic adaptation. One striking habitat difference is in the availability of Euphausia superba krill as prey, which has led to A. gazella exhibiting a range of diets. A. gazella in some colonies consume exclusively krill, while their conspecifics in other colonies feed mainly on fish and consume few to no krill. To investigate potential adaptations to these different prey fields, reduced representation genome sequencing was conducted on A. gazella from the 8 major colonies. Twenty-seven genomic regions exhibiting signatures of natural selection were identified. Two of these genomic regions were clearly associated with seals living in krill-dominated areas or those in fish-dominated areas. Twenty-two additional genomic regions under selection showed a pattern consistent with prey differences as the driver of selection after historical migrations from krill-dominated habitats where lineages evolved to present krill-poor habitat areas were taken into account. Only 1 of the genomic regions identified appeared to be explained by any other environmental variable analysed (depth). Genomic regions under prey-driven selection included genes associated with regulation of gene expression, skeletal development, and lipid metabolism. Adaptation to local prey has implications for spatial management of this species and for the potential impacts of climate- or harvest-driven reductions in krill abundance on these seals. KEY WORDS: Arctocephalus gazella · Double digest restriction-site associated DNA sequencing · ddRAD · Diet · Euphausia superba · Natural selection

Antarctic krill <i>Euphausia superba</i>, a keystone species in the Southern Ocean, is highly relevant for studying effects of climate-related shifts on management systems. Krill provides a key link between primary producers and higher trophic levels and supports the largest regional fishery. Any major perturbation in the krill population would have severe ecological and economic ramifications. We review the literature to determine how climate change, in concert with other environmental changes, alters krill habitat, affects spatial distribution/abundance, and impacts fisheries management. Findings recently reported on the effects of climate change on krill distribution and abundance are inconsistent, however, raising questions regarding methods used to detect changes in density and biomass. One recent study reported a sharp decline in krill densities near their northern limit, accompanied by a poleward contraction in distribution in the Southwest Atlantic sector. Another recent study found no evidence of long-term decline in krill density or biomass and reported no evidence of a poleward shift in distribution. Moreover, with predicted decreases in phytoplankton production, vertical foraging migrations to the seabed may become more frequent, also impacting krill production and harvesting. Potentially cumulative impacts of climate change further compound the management challenge faced by CCAMLR, the organization responsible for conservation of Antarctic marine living resources: to detect changes in the abundance, distribution, and reproductive performance of krill and krill-dependent predator stocks and to respond to such change by adjusting its conservation measures. Based on CCAMLR reports and documents, we review the institutional framework, outline how climate change has been addressed within this organization, and examine the prospects for further advances toward ecosystem risk assessment and an adaptive management system.

Southern Ocean ecosystems are under pressure from resource exploitation and climate change1,2. Mitigation requires the identification and protection of Areas of Ecological Significance (AESs), which have so far not been determined at the ocean-basin scale. Here, using assemblage-level tracking of marine predators, we identify AESs for this globally important region and assess current threats and protection levels. Integration of more than 4,000 tracks from 17 bird and mammal species reveals AESs around sub-Antarctic islands in the Atlantic and Indian Oceans and over the Antarctic continental shelf. Fishing pressure is disproportionately concentrated inside AESs, and climate change over the next century is predicted to impose pressure on these areas, particularly around the Antarctic continent. At present, 7.1% of the ocean south of 40°S is under formal protection, including 29% of the total AESs. The establishment and regular revision of networks of protection that encompass AESs are needed to provide long-term mitigation of growing pressures on Southern Ocean ecosystems.

The Retrospective Analysis of Antarctic Tracking Data (RAATD) is a Scientific Committee for Antarctic Research project led jointly by the Expert Groups on Birds and Marine Mammals and Antarctic Biodiversity Informatics, and endorsed by the Commission for the Conservation of Antarctic Marine Living Resources. RAATD consolidated tracking data for multiple species of Antarctic meso- and top-predators to identify Areas of Ecological Significance. These datasets and accompanying syntheses provide a greater understanding of fundamental ecosystem processes in the Southern Ocean, support modelling of predator distributions under future climate scenarios and create inputs that can be incorporated into decision making processes by management authorities. In this data paper, we present the compiled tracking data from research groups that have worked in the Antarctic since the 1990s. The data are publicly available through biodiversity.aq and the Ocean Biogeographic Information System. The archive includes tracking data from over 70 contributors across 12 national Antarctic programs, and includes data from 17 predator species, 4060 individual animals, and over 2.9 million observed locations.