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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.

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.

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.

The Southern Ocean is a major sink of anthropogenic CO2 and an important foraging area for top trophic level consumers. However, iron limitation sets an upper limit to primary productivity. Here we report on a considerably dense late summer phytoplankton bloom spanning 9000 km2 in the open ocean of the eastern Weddell Gyre. Over its 2.5 months duration, the bloom accumulated up to 20 g C m−2 of organic matter, which is unusually high for Southern Ocean open waters. We show that, over 1997–2019, this open ocean bloom was likely driven by anomalies in easterly winds that push sea ice southwards and favor the upwelling of Warm Deep Water enriched in hydrothermal iron and, possibly, other iron sources. This recurring open ocean bloom likely facilitates enhanced carbon export and sustains high standing stocks of Antarctic krill, supporting feeding hot spots for marine birds and baleen whales.

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.

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.

In the Southern Ocean, large-scale phytoplankton blooms occur in open water and the sea-ice zone (SIZ). These blooms have a range of fates including physical advection, downward carbon export, or grazing. Here, we determine the magnitude, timing and spatial trends of the biogeochemical (export) and ecological (foodwebs) fates of phytoplankton, based on seven BGC-Argo floats spanning three years across the SIZ. We calculate loss terms using the production of chlorophyll—based on nitrate depletion—compared with measured chlorophyll. Export losses are estimated using conspicuous chlorophyll pulses at depth. By subtracting export losses, we calculate grazing-mediated losses. Herbivory accounts for ~90% of the annually-averaged losses (169 mg C m−2 d−1), and phytodetritus POC export comprises ~10%. Furthermore, export and grazing losses each exhibit distinctive seasonality captured by all floats spanning 60°S to 69°S. These similar trends reveal widespread patterns in phytoplankton fate throughout the Southern Ocean SIZ.

Global climate change is significantly affecting marine life off the northern tip of the Antarctic Peninsula, but little is known about microbial ecology in this area. The main goal of this study was to investigate the bacterioplankton community structure in surface waters using pyrosequencing and to determine factors influencing this community. Pelagibacterales and Rhodobacterales (Alphaproteobacteria), Oceanospirillales and Alteromonadales (Gammaproteobacteria), and Flavobacteriales (Bacteroidetes) were the core taxa in our samples, and the five most relatively abundant genera were Pelagibacter, Polaribacter, Octadecabacter, group HTCC2207 and Sulfitobacter. Although nutrients and chlorophyll a (chl a) contributed more to bacterioplankton community structure than water masses or depth, only 30.39% of the variance could be explained by the investigated environmental factors, as revealed by RDA and pRDA. No significant difference with respect to nutrients and chl a was observed among water masses or depth, as indicated by ANOVA. Furthermore, significant correlations among the dominant bacterial genera were more common than correlations between dominant genera and environmental factors, as revealed by Spearman analysis. We conclude that nutrients and chl a become homogeneous and that interpopulation interactions may have a central role in influencing the bacterial community structure in surface waters off the northern tip of the Antarctic Peninsula during the summer.

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

Abstract Southern hemisphere humpback whales (Megaptera novaeangliae) rely on summer prey abundance of Antarctic krill (Euphausia superba) to fuel one of the longest-known mammalian migrations on the planet. It is hypothesized that this species, already adapted to endure metabolic extremes, will be one of the first Antarctic consumers to show measurable physiological change in response to fluctuating prey availability in a changing climate; and as such, a powerful sentinel candidate for the Antarctic sea-ice ecosystem. Here, we targeted the sentinel parameters of humpback whale adiposity and diet, using novel, as well as established, chemical and biochemical markers, and assembled a time trend spanning 8 years. We show the synchronous, inter-annual oscillation of two measures of humpback whale adiposity with Southern Ocean environmental variables and climate indices. Furthermore, bulk stable isotope signatures provide clear indication of dietary compensation strategies, or a lower trophic level isotopic change, following years indicated as leaner years for the whales. The observed synchronicity of humpback whale adiposity and dietary markers, with climate patterns in the Southern Ocean, lends strength to the role of humpback whales as powerful Antarctic sea-ice ecosystem sentinels. The work carries significant potential to reform current ecosystem surveillance in the Antarctic region.

In this reported study, a novel high-performance thin-layer chromatography (HPTLC) method was developed for the detection and quantification of the toxic substance di(2-ethylhexyl) adipate (DEHA) in Antarctic krill. This procedure was based on the extraction of DEHA by ultrasonic solvent extraction with anhydrous ethanol, silica-gel column chromatographic separation, HPTLC detection and quantification using petroleum ether/ethyl acetate/ acetone/glacial acetic acid (29:1:0.5:2d*, v/v/v/v) as the developing solvent and bromine thymol blue solution as the chromogenic agent. The content of DEHA in freeze-dried Antarctic krill was found to be ca. 0.63 ± 0.05 mg/g. The structure of DEHA in the Antarctic krill was subsequently determined by gas chromatography–mass spectrometry (GC-MS) and infrared chromatography, which verified the presence of this compound in the krill. The HPTLC method exhibited excellent accuracy, with a recovery of 97.1–101.6% and good precision with a relative standard deviation of 2.47–4.90%. The DEHA in Antarctic krill oil was extracted by n-hexane and detected using the same method described above, which verified that DEHA was also present in krill oil at a concentration of ca. 2.16 ± 0.08 mg/g. The presence of DEHA in kill oil is very concerning because of its demonstrated harmful ecotoxicity, and since Antarctic krill is the key link in the food chain in the Antarctic coastal marine ecosystem. The adverse effects of DEHA on Antarctic krill and the source of DEHA will be explored in future research.