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Bycatch of nontarget species can contribute to overfishing and slow efforts to rebuild fish stocks. Controlling bycatch is fundamental to sustainable fishing and maintaining healthy populations of target species. The Antarctic krill (Euphausia superba) fishery is the largest volume fishery in the Southern Ocean. Understanding the significance of bycatch and its diversity is critical to managing this keystone species. Registered bycatch data from the Antarctic krill fishery in the southwest Atlantic sector of the Southern Ocean were analysed. Observers collected data following an internationally agreed method during the 2010–2020 fishing seasons, with a 20 (± 9) % coverage of fishing activity of Total catch of Antarctic krill which increased from 200,000 tonnes to 450,000 tonnes, with the greatest increase over the last 3 years. Except in 2010 (2.2%), the bycatch ratio was stable and ranged 0.1–0.3%. Fish dominated the bycatch, followed by tunicates and other crustaceans. Observer coverage was high, and bycatch levels were generally low across gear types. Given that accurate information on bycatch is important for sustaining developing fisheries, maintaining high observer coverage of this fishery will be important for detecting impacts from a warming climate and for moving back into historical fishing grounds.

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.

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.

The stock assessment model for the Antarctic krill fishery is a population model operating on daily timesteps, which permits modeling within-year patterns of some population dynamics. We explored the effects of including within-year patterns in natural and fishing mortality on catch limits of krill, by incorporating temporal presence of key predator species and contemporary temporal trends of the fishing fleet. We found that inclusion of within-year variation in natural and fishing mortalities increased catch limits. Fishing mortality had a greater effect than natural mortality despite differences in top-down predation on krill, and potentially increased catch limits by 24% compared to the baseline model. Additionally, the stock assessment model allowed a higher catch limit when fishing was during peak summer months than autumn. Number of days with active fishing was negatively related to precautionary catch limits. Future stock assessments should incorporate contemporary spatiotemporal fishing trends and consider implementing additional ecosystem components into the model.

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

Estimates of the distribution and density of Antarctic krill (Euphausia superba Dana, 1850) were derived from a large-scale survey conducted during the austral summer in the Southwest Atlantic sector of the Southern Ocean and across the Scotia Sea in 2018–19, the ‘2018–19 Area 48 Survey’. Survey vessels were provided by Norway, the Association of Responsible Krill harvesting companies and Aker BioMarine AS, the United Kingdom, Ukraine, Republic of Korea, and China. Survey design followed the transects of the Commission for the Conservation of Antarctic Marine Living Resources synoptic survey, carried out in 2000 and from regular national surveys performed in the South Atlantic sector by the U.S., China, Republic of Korea, Norway, and the U.K. The 2018–19 Area 48 Survey represents only the second large-scale survey performed in the area and this joint effort resulted in the largest ever total transect line (19,500 km) coverage carried out as one single exercise in the Southern Ocean. We delineated and integrated acoustic backscatter arising from krill swarms to produce distribution maps of krill areal biomass density and standing stock (biomass) estimates. Krill standing stock for the Area 48 was estimated to be 62.6 megatonnes (mean density of 30 g m–2 over 2 million km2) with a sampling coefficient variation of 13%. The highest mean krill densities were found in the South Orkney Islands stratum (93.2 g m–2) and the lowest in the South Georgia Island stratum (6.4 g m–2). The krill densities across the strata compared to those found during the previous survey indicate some regional differences in distribution and biomass. It is currently not possible to assign any such differences or lack of differences between the two survey datasets to longer term trends in the environment, krill stocks or fishing pressure.