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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.

Understanding population connectivity in the marine realm is crucial for conserving biodiversity, managing fisheries, and predicting species responses to environmental change. This is particularly important in Antarctic waters, where unique evolutionary histories and extreme conditions shape marine biodiversity. The longfin icedevil Aethotaxis mitopteryx is an elusive notothenioid fish endemic to Antarctic waters. To explore population connectivity in A. mitopteryx, we used RAD-seq to investigate the genetic differentiation of two populations, one from the Eastern Weddell Sea and the other from the Eastern Antarctic Peninsula, two regions of ecological relevance greatly impacted by climate change. Despite spatial separation, analyses revealed no significant genetic differentiation between the two populations, suggesting extensive gene flow. A pronounced genetic distinction was, however, observed between males and females. This differentiation was largely localized to a specific chromosome, implying a genetic sex determination system with males being the heterogametic sex. These findings contribute novel insights into the genetic structure of A. mitopteryx populations and expand our understanding of genetic mechanisms in Antarctic fish. This study provides a foundation for further investigations into the evolutionary and ecological implications of sex chromosome differentiation in extreme environments.

Understanding population connectivity in the marine realm is crucial for conserving biodiversity, managing fisheries, and predicting species responses to environmental change. This is particularly important in Antarctic waters, where unique evolutionary histories and extreme conditions shape marine biodiversity. The longfin icedevil Aethotaxis mitopteryx is an elusive notothenioid fish endemic to Antarctic waters. To explore population connectivity in A. mitopteryx, we used RAD-seq to investigate the genetic differentiation of two populations, one from the Eastern Weddell Sea and the other from the Eastern Antarctic Peninsula, two regions of ecological relevance greatly impacted by climate change. Despite spatial separation, analyses revealed no significant genetic differentiation between the two populations, suggesting extensive gene flow. A pronounced genetic distinction was, however, observed between males and females. This differentiation was largely localized to a specific chromosome, implying a genetic sex determination system with males being the heterogametic sex. These findings contribute novel insights into the genetic structure of A. mitopteryx populations and expand our understanding of genetic mechanisms in Antarctic fish. This study provides a foundation for further investigations into the evolutionary and ecological implications of sex chromosome differentiation in extreme environments.

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.