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ABSTRACT Understanding diet composition is essential for unravelling trophic interactions in aquatic ecosystems. DNA metabarcoding, utilising various variable regions of the 18S rRNA gene, is increasingly employed to investigate zooplankton diet composition. However, accurate results depend on rapid inactivation of digestive enzymes and DNA nucleases through proper sample processing and preservation. In this study, we compare the prey communities of Antarctic krill retrieved from the 18S variable regions V4 and V7 and assess how different processing treatments affect the detected prey composition of both krill and salps. Our findings highlight the critical importance of prompt sample processing for species with highly efficient digestive enzymes, such as krill, to preserve rapidly digested prey, including gelatinous plankton. Comparative analyses of the V4 and V7 regions revealed significantly different prey communities within the same krill samples, indicating that these regions may not be suitable for direct comparisons within or across studies. To complement molecular approaches, we also analyse fatty acids (FA) as trophic markers which provide insights into dietary habits over both short and long time scales. By comparing FA signals from stomach and tissue samples of the same krill and salp individuals, we identified significant differences in trophic markers representing different plankton groups. These findings emphasise the necessity of separating digestive tract from tissue to distinguish between short- and long-term diet signals. Furthermore, integrating FA analysis with metabarcoding offers valuable insights into zooplankton digestion efficiency across taxonomic levels. This combined approach enhances our understanding of zooplankton feeding ecology and trophic interactions in marine ecosystems.

Understanding how marine predators structure and adjust their foraging in response to prey field characteristics is a longstanding objective in marine ecology. This is particularly challenging in Southern Ocean ecosystems, where logistical and financial constraints hinder assessment of predator foraging and prey field information at relevant spatial and temporal scales. Here, we examine how Adélie penguins, Pygoscelis adeliae, a key Southern Ocean indicator species, perform and organize their foraging behaviour during two contrasting years of krill (Euphausia superba) abundance. Using multiyear krill acoustic data from King George Island in the West Antarctic Peninsula (WAP), we assess broad seasonal conditions in krill availability. We also analyse a suite of penguin biologging data (spatial location, dive and accelerometry-derived activities) during the same period to identify broad behavioural differences in their bout-diving activity, a classical measure of the temporal organization of foraging in diving predators. During years of high krill abundance and availability, penguins performed shorter dive bouts (consisting of shallower and shorter-duration dives), which were more concentrated in time and space. Despite these differences in bout structure, prey capture attempts occurred at the same rate within bouts. These findings challenge traditional interpretations assuming that increased bout durations (and related proxies of prey capture effort) signal increased krill patch abundance and profitability. Although additional data are required to understand the full scope of penguin bout diving and krill prey field associations, our work improves understanding of penguin behavioural variation and provides insights into how foraging behaviours could potentially be used to interpret krill availability at predator- and management-relevant scales.

Euphausia superba is a well-known Antarctic crustacean of great economic and ecological importance, whose management requires accurate and precise abundance and distribution estimates. Such estimates are difficult to achieve given the remoteness, extension, and large spatio-temporal variability of its geographic distribution. Acoustic data collected on board krill fishing vessels during normal fishing operation has a great potential to enhance such abundance and distribution estimates. In the present work we test the hypothesis that design-free hydroacoustic data collected during regular fishing operations can be used to produce abundance and distribution estimates with similar accuracy and precision than design-based scientific surveys. Thus, we produced and compared distribution and abundance estimates produced using either design-free hydroacoustic data collected during regular fishing operations or design-based data from scientific surveys conducted off the South Orkney Islands during summer 2017 and 2019. Following a Bayesian geostatistical approach that considered and fitted simultaneously the spatial and temporal correlation of the data, we tested different auto-correlation structures and selected the most informative models. The comparison included the means and coefficients of variation (CV) of the probability of presence (p), conditional density (d) and relative abundance index (RAI) estimates. In addition, we also simulated scenarios of parallel and orthogonal transects and obtained RAI estimates from each scenario to compare with design-based and design-free estimates for each year. In 2017, the mean RAI estimated using design-free data (94 421 m2; CV: 14 %) was ∼ 50 % higher than the one estimated with design-based data (60 232 m2; CV: 42 %), both within the fishing area. In 2019, the mean RAI estimated using design-free data (509 413 m2 CV: 6 %) was ∼ 5-fold higher than the one obtained using design-based data (113 654 m2; CV: 33 %) in the same area. Design-free RAI estimates were highly sensitive to extrapolating the inference area from fishing to the high-density sub-area. On the other hand, changing from an hourly-resolved spatio-temporal model to a purely spatial model resulted in neglectable changes. Despite observed differences in mean estimates, both methods identified similar areas of high presence and density of Antarctic krill north and north-west of the South Orkney Islands. The 2017 estimate from design-free data was probably affected by a larger dispersion of krill, and a less observed effective area during regular fishing operations. Our results show that despite using state-of-the-art methods for processing and analyzing design-free, acoustic data collected by the fishing fleet, it still yielded unreliable RAI estimates. The bias and uncertainty related to design-free data were reduced when parallel or orthogonal transects were applied although orthogonal transects yielded results with increased accuracy as they were only 21 % lower and 0.02 % higher than the true value in 2017 and 2019, respectively. Other possible approach to minimize bias would be integrating hydroacoustic information from multiple vessels.

The management strategy for the Antarctic krill (Euphausia superba) fishery is being revised. A key aim is to spatially and temporally allocate catches in a manner that minimizes impacts to both the krill stock and dependent predators. This process requires spatial information on the distribution and abundance of krill, yet gaps exist for an important fishing area surrounding the South Orkney Islands in the south Scotia Sea. To fill this need, we create a dynamic distribution model for krill in this region. We used data from a spatially and temporally consistent acoustic survey (2011-2020) and year-specific environmental covariates within a two-part hurdle model. The model successfully captured observed spatial and temporal patterns in krill density. The covariates found to be most important included distance from shelf break, distance from summer sea ice extent, and salinity. The northern and eastern shelf edges of the South Orkney Islands were areas of consistently high krill density and displayed strong spatial overlap between intense fishing activity and foraging chinstrap penguins. High mean krill density was also linked to oceanographic features located within the Weddell Sea. Our data suggest that years in which these features were closer to the South Orkney shelf were also years of positive Southern Annular Mode and higher observed krill densities. Our findings highlight existing fishery?predator?prey overlap in the region and support the hypothesis that Weddell Sea oceanography may play a role in transporting krill into this region. These results will feed into the next phase of krill fisheries management assessment.

Understanding the connection between maturity stages and morphology in relation to size selectivity in trawls is essential for assessing the impact of various fishing gear on the population structures of harvested species, their fishing mortality rates, and the efficiency of the gear used. The Antarctic krill (Euphausia superba) fishery is the largest in the Southern Ocean by volume, and there is increasing interest in expanding the industry. The krill fishery employs different trawl designs and is not currently subject to technical regulations specifying the types of fishing gear and mesh sizes that can legally be used. There is a need to establish a robust model predicting size selectivity that includes the morphological variation in the population of krill. Male and female Antarctic krill are described with 12 maturity stages, from juveniles to sexually mature adults, each with distinct morphological features. The current study established a morphological description of each individual krill maturity stage to identify and parameterize what determines size selectivity using the FISHSELECT framework. This framework is used to predict size selectivity for each of the different stages in various mesh sizes and openings relevant to the krill fishery, in both actual and virtual populations. The results can be used to assess size selectivity for specific fishing gears and population structures, facilitating more accurate understanding and modeling of the fishery’s impact on the demographic composition of the krill stock.

The fishery for Antarctic krill (Euphausia superba) is the largest by tonnage in the Southern Ocean, and understanding its population dynamics is essential for the sustainable management of this fishery. The standard method for calculating Antarctic krill biomass relies on hydroacoustic survey data and incorporates krill body length data collected concurrently. Traditional scientific acoustic surveys involve manually measuring the body lengths of individual krill caught using fine- meshed nets or trawls along acoustic transects. This work is resource-demanding and could represent a source of human error. To address these challenges, we develop and test an alternative, more automated method for estimating krill body length data by employing an in-trawl stereo camera system. This system collects images that are automatically processed by a custom-trained machine learning model. The results from the machine learning model are then compared to manually measured krill subsampled from the total catch of the corresponding trawl hauls. We demonstrated the ability to extract body lengths from underwater images. However, our results highlighted uncertainties, which we propose addressing by incorporating more advanced camera technology and optimizing the observation section of the small-meshed two-layer krill trawl.

Antarctic krill (Euphausia superba) are integral to Southern Ocean pelagic ecosystems. Winters with extensive sea ice have been linked to high post-larval krill recruitment the following spring, suggesting that sea ice plays a critical role in larval overwinter survival. As the ocean warms and sea ice declines under climate change, understanding the mechanisms linking sea ice and krill recruitment is increasingly urgent. To address this, we developed a qualitative network model (QNM) that integrates evidence-based and hypothesized interactions to explore larval overwinter survival and growth under future climate scenarios in the southwest Atlantic sector. Our model highlights habitat-specific impacts, with substantial declines predicted for the North Antarctic Peninsula continental shelf due to reduced autumn primary productivity and warming. In contrast, survival may improve in open-ocean habitats under cooler scenarios that enhance sea-ice-associated processes, such as food availability and refuge. The inclusion of hypothesized mechanisms, such as sea-ice terraces providing refuge from predation, strengthened these conclusions and highlighted critical uncertainties, including the influence of glacial melt on food web dynamics. These findings demonstrate the value of QNMs in complementing quantitative approaches, offering a framework for identifying critical mechanisms, addressing knowledge gaps, and guiding future field and laboratory studies to improve predictions of krill responses to climate change.

Antarctic krill meal (KM) (Euphausia superba) as a substitute for fishmeal in aquatic animal diets is gaining popularity worldwide. A quantitative approach investigating the efficacy of using this protein on the production performance of aquatic animals remains widely limited. Here, we employed a meta-analysis to quantify the overall effects (Hedges’g [g] value effect size) of KM on the specific growth rate (SGR), feed conversion ratio (FCR), protein efficiency ratio (PER), and survival rate (SR) of several aquaculture species. A total of 22 records published during 2006 to 2022 from different countries, targeting 14 aquatic species, were employed in the present study. Overall, KM has a high nutritional value relative to fishmeal, particularly from the high protein and amino acid composition. Dietary KM significantly increased the overall effect size of SGR (g = 1.92) (P = 0.001); the positive effect was illustrated in marine species (g = 1.32 to 9.10) (P < 0.05) and sturgeon (Acipenser gueldenstaedtii) (g = 6.59) (P < 0.001). The overall g value for FCR (−2.42) was significantly improved compared to the control group (P < 0.001). The inclusion of KM in aquatic animal diets did not affect g value of PER (1.52, 95% confidence interval: −1.04 to 4.07) and survival rate (0.08, 95% confidence interval: −0.63 to 0.79) (P = 0.252 and 0.208, respectively). The meta-regression models indicated that SGR of rainbow trout (Oncorhynchus mykiss) was significantly correlated with dietary KM by a positive linear model (P = 0.022). The cod and sturgeon (A. gueldenstaedtii) appeared to efficiently utilize krill-containing diets as illustrated by a negative linear model (P = 0.011 and P = 0.024, respectively) between dietary KM and FCR. Dietary KM positively correlated with PER for Atlantic cod (P = 0.021). Our meta-analysis highlighted the significant outcome of KM in diets for aquaculture species by reducing pressure on forage fish from marine resources and sparing edible foods. Specifically, including KM significantly reduced economic fish-in fish-out (eFIFO) in four taxa—the top forage fish consumers (P < 0.05): marine fish, salmon, shrimp, and trout. The meta-analysis revealed the decreased food-competition feedstuff in diets for important aquaculture species (P < 0.05) fed dietary KM. The outlook for efficient use of KM from marine resources in aquafeeds was elucidated in the present work.

Temporal distributions of Antarctic krill (Euphausia superba) density and aggregation types were characterized and compared using Nortek Signature100 and SIMRAD Wideband Autonomous Transceiver (WBAT) upward-looking echosounders. Noise varied between the two echosounders. With the Signature100, it was necessary to correct data for background, transient, and impulse noises, while the WBAT data needed to be corrected for background noise only. For selected regions with no visible backscatter, the signal-to-noise ratio of Sv values (i.e. the ratio between the signal and the background noise level) did not vary between the two echosounders. Surface echo backscatter was similar during similar time periods. Descriptive metrics were used to quantify spatial and temporal krill vertical distributions: volume backscatter, mean depth, center of mass, inertia, equivalent area, aggregation index, and proportion occupied. Krill backscatter density differed between the two instruments but was detected at similar mean depths. Krill aggregations were identified at each mooring location and classified in three types based on morphological characteristics. Each type of aggregation shape differed at the two spatially separated moorings, while the acoustic density of each aggregation type was similar. The Signature100 detected a lower number of krill aggregations (n = 133) compared to the WBAT (n = 707). Although both instruments can be used for autonomous deployment and sampling of krill over extended periods, there is a strong caveat for the use of the Signature100 due to significant differences in noise characteristics and krill detection.

Southern Ocean phytoplankton form the base of the Antarctic food web, influencing higher trophic levels through biomass and community structure. We examined phytoplankton distribution and abundance in the Indian Sector of the Southern Ocean during austral summer as part a multidisciplinary ecosystem survey: Trends in Euphausiids off Mawson, Predators and Oceanography (TEMPO, 2021). Sampling covered six meridional transects from 55-80°E, and from 62°S or 63°S to the ice edge. To determine phytoplankton groups, CHEMTAX analysis was undertaken on pigments measured using HPLC. Diatoms were the dominant component of phytoplankton communities, explaining 56% of variation in chlorophyll a (Chl a), with haptophytes also being a major component. Prior to sampling the sea ice had retreated in a south-westerly direction, leading to shorter ice-free periods in the west (< 44 days, ≤65°E) compared to east (> 44 days, ≥70°E), inducing a strong seasonal effect. The east was nutrient limited, indicated by low-iron forms of haptophytes, and higher silicate:nitrate drawdown ratios (5.1 east vs 4.3 west), pheophytin a (phaeo) concentrations (30.0 vs 18.4 mg m-2) and phaeo:Chl a ratios (1.06 vs 0.53). Biological influences were evident at northern stations between 75-80°E, where krill “super-swarms” and feeding whales were observed. Here, diatoms were depleted from surface waters likely due to krill grazing, as indicated by high phaeo:Chl a ratios (> 0.75), and continued presence of haptophytes, associated with inefficient filtering or selective grazing by krill. Oceanographic influences included deeper mixed layers reducing diatom biomass, and a bloom to the north of the southern Antarctic Circumpolar Current Front in the western survey area thought to be sinking as waters flowed from west to east. Haptophytes were influenced by the Antarctic Slope Front with high-iron forms prevalent to the south only, showing limited iron transfer from coastal waters. Cryptophytes were associated with meltwater, and greens (chlorophytes + prasinophytes) were prevalent below the mixed layer. The interplay of seasonal, biological and oceanographic influences on phytoplankton populations during TEMPO had parallels with processes observed in the BROKE and BROKE-West voyages conducted 25 and 15 years earlier, respectively. Our research consolidates understanding of the krill ecosystem to ensure sustainable management in East Antarctic waters.

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.

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 krill (Euphausia superba) and Ice krill (Euphausia crystallorophias) are key species within Southern Ocean marine ecosystems. Given their importance in regional food webs, coupled with the uncertain impacts of climate change, the on-going recovery of krill-eating marine mammals, and the expanding commercial fishery for Antarctic krill, there is an increasing need to improve current estimates of their circumpolar habitat distribution. Here, we provide an estimate of the austral summer circumpolar habitat distribution of both species using an ensemble of habitat models and updated environmental covariates. Our models were able to resolve the segregated habitats of both species. We find that extensive potential habitat for Antarctic krill is mainly situated in the open ocean and concentrated in the Atlantic sector of the Southern Ocean, while Ice krill habitat was concentrated more evenly around the continent, largely over the continental shelf. Ice krill habitat was mainly predicted by surface oxygen concentration and water column temperature, while Antarctic krill was additionally characterized by mixed layer depth, distance to the continental shelf edge, and surface salinity. Our results further improve understanding about these key species, helping inform sustainable circumpolar management practices.

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.

Survival of larval Antarctic krill (Euphausia superba) during winter is largely dependent upon the presence of sea ice as it provides an important source of food and shelter. We hypothesized that sea ice provides additional benefits because it hosts fewer competitors and provides reduced predation risk for krill larvae than the water column. To test our hypothesis, zooplankton were sampled in the Weddell-Scotia Confluence Zone at the ice-water interface (0–2 m) and in the water column (0–500 m) during August–October 2013. Grazing by mesozooplankton, expressed as a percentage of the phytoplankton standing stock, was higher in the water column (1.97 ± 1.84%) than at the ice-water interface (0.08 ± 0.09%), due to a high abundance of pelagic copepods. Predation risk by carnivorous macrozooplankton, expressed as a percentage of the mesozooplankton standing stock, was significantly lower at the ice-water interface (0.83 ± 0.57%; main predators amphipods, siphonophores and ctenophores) than in the water column (4.72 ± 5.85%; main predators chaetognaths and medusae). These results emphasize the important role of sea ice as a suitable winter habitat for larval krill with fewer competitors and lower predation risk. These benefits should be taken into account when considering the response of Antarctic krill to projected declines in sea ice. Whether reduced sea-ice algal production may be compensated for by increased water column production remains unclear, but the shelter provided by sea ice would be significantly reduced or disappear, thus increasing the predation risk on krill larvae.

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.