Krill Aggregations Research Articles

Field comparison of Antarctic krill (Euphausia superba) backscatter and aggregation types using NORTEK and SIMRAD echosounders

Abstract 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 energy content and demographic composition of Antarctic krill (Euphausia superba) swarms in East Antarctica

Antarctic krill (Euphausia superba) aggregations are important in the Southern Ocean ecosystem; however, the amount of energy that krill swarms contain is unknown. We assessed the population structure of E. superba swarms in East Antarctica for two different sectors corresponding to the study areas of the ENRICH (2019) and TEMPO (2021) voyages. We also estimated swarm energy content based on calorific values for whole animals and key tissues (gonads, digestive gland, and muscle). A relationship between the energy content of muscle and gonads in gravid and adult females was detected: The higher the energy content in muscle tissue, the lower the energy content in the gonad tissue. This relationship was consistent for different female maturity stages, suggesting a trade-off in energy allocation between somatic growth and reproduction. Females will redirect energy to gonad development at the expense of somatic growth. Total swarm energy was calculated using the volumetric density of each swarm estimated from an acoustic survey. Four swarm types (A-D) were determined based on the body length and maturity stage of the individuals. The highest energy contents were found in Type B swarms, composed predominantly of adult males and females, and Type D swarms, comprising mostly gravid females. Trends in swarm demographic composition and energy content were consistent between surveys. We recommend swarm energy be incorporated into ecosystem models to represent energy transfer to top predators.

At-sea distribution of marine predators around South Georgia during austral winter, with implications for fisheries management

The sub-Antarctic island of South Georgia is surrounded by highly productive waters, supporting dense aggregations of Antarctic krill (Euphausia superba), a vital food source for globally important seabird and marine mammal populations. These waters also support a commercial fishery for Antarctic krill. Regular monitoring of key krill predator species is undertaken at South Georgia to detect any changes in the ecosystem in response to harvesting activities. This monitoring provides essential data but is focused on land-breeding animals during the austral summer, whilst the krill fishery operates exclusively in winter. Here, we report the results of at-sea surveys to investigate abundance and distribution of krill-dependent predators from winter 2010 and 2011, which represented a “poor” krill year and “good” krill year, respectively. Correspondingly in 2011 higher numbers of krill predators were observed; notably Antarctic fur seals (Arctocephalus gazella) across the northern shelf. Spatial overlap between fur seals and the krill fishery occurred mainly within the krill fishery hotspot to the north-east, highlighting the potential for locally high levels of competition. Cetaceans were observed during both survey years, but in low numbers compared to recent studies. Gentoo penguins (Pygoscelis papua) were the most frequently observed penguin species, showing an inshore distribution and almost no overlap with the krill fishery. Diving-petrels (Pelecanoides spp.) were the most abundant flying seabirds, observed across all transects, with particularly high densities to the south in early winter 2010. In conclusion, this survey provides valuable baseline data on the distribution of South Georgia’s predators during the winter months.

К ВОПРОСУ ОБ ОПРЕДЕЛЕНИИ ПРОМЫСЛОВОГО ЗАПАСА АНТАРКТИЧЕСКОГО КРИЛЯ EUPHAUSIA SUPERBA В РАЙОНЕ АНТАРКТИЧЕСКОГО ПОЛУОСТРОВА ПО ДАННЫМ ТРАЛОВЫХ УЛОВОВ КОММЕРЧЕСКИХ СУДОВ

Background. The assessment of the density and total biomass of the Antarctic krill aggregations has been conducted based on the commercial catches by the fishing and krill harvesting trawlers (supertrawlers) “Konstruktor Koshkin” (“Design Engineer Koshkin”) in 2006 and “More Sodruzhestva” (“Commonwealth Sea”) in 2017 in the Bransfield Strait (FAO Subarea 48.1). Relevance. Recommencement of the Russian krill harvesting necessitates timely strategical characterization of the krill aggregations with regard to their prospective exploitation. This work is aimed at the identification of the density and biomass of the Antarctic krill aggregations in 2006 and 2017, which have been calculated by the volumetric (net) method based on the catches by the commercial vessels in the Bransfield Strait. Methods. A midwater rope trawl of the 74/600 m design with the mesh size 20 mm in the krill-targeting insertion was used as a fishing gear. Estimation of the biomass was done using the isoline method. The catchability coefficient was considered to be 1. Mapping of the biomass density values was conducted with Golden Software Surfer 9 and QGIS 2.18.16. Confidence intervals for the average variation were calculated with 95 % probability. Results. The decrease in the average density of the krill biomass at the harvesting sites in the Bransfield Strait in 2017 (18.0±0.23 g/m3) as compared to 2006 (32.5±0.40 g/m3) has been identified; it resulted from the krill aggregations scattering over the increased area. The total krill biomass in the aggregations in 2006 and 2017 was 2678.3±65.07 thousand t and 2743.1±68.70 thousand t, respectively. Conclusion. Based on the commercial trawl catches, the volumetric method allows for the expedient estimation of the density and biomass of the krill aggregations with the size composition optimal for their exploitation. Taking into consideration that the commercial trawls capture the relatively large-sized krill preferred by the krill-dependent predators, the volumetric method makes it possible to estimate the volume of their food reserves. Exploitable krill stock in the aggregations in the Bransfield Strait in 2017 remained virtually unchanged as compared to that of 2006 and amounted to 2.7 million t.

Characterizing Antarctic air-breathing predator dive patterns on a common prey base from stationary echosounders

Diving patterns of air-breathing predators were monitored from three moored subsurface upward-looking echosounders. Complete and partial dive profiles were visible on active acoustic records as echoes that started and/or returned to the surface. Dive metrics: maximum dive depths, durations, and wiggle count were measured and angles, distances, and velocities, were calculated at each site. Dive shapes ‘U’, ‘V’ and ‘W’ were derived using the number of wiggles and the percentage of dive bottom time. Dive profiles were classified into four types with type 1 dives being short in total duration and distance, low velocities, small angles, shallow, and linked to ‘U’ and ‘W’ shapes. Type 2 dives were short in distance, had low velocities, shallow depths, and were linked to ‘V’ dives. Dive types 3 and 4 had higher velocities, larger angles, longer total durations, and were deeper than types 1 and 2. Observed dive types could correspond to travelling, exploring, and foraging predator behaviors. Significant predator-prey overlaps occurred with predator dive profile counts correlated with krill aggregation thickness, density, and depth. This study demonstrates the utility of using stationary active acoustics to identify predator dive profiles with a simultaneous characterization of the potential prey field.

U-MSAA-Net: A Multiscale Additive Attention-Based Network for Pixel-Level Identification of Finfish and Krill in Echograms

This paper addresses the detection of finfish and krill in echograms. Finfish, in particular Pacific hake, are used both as human food and fish meal. Krill, harvested for aquaculture and aquariums, are a primary food source for finfish, including hake. Thus, spatial distributions of hake follow that of krill. Stock assessments need an accurate differentiation of krill from finfish (hake) in acoustic echograms. This paper proposes a semantic segmentation paradigm for the pixel-level classification of multi-frequency information to detect co-occurring finfish and krill. This paradigm is highly relevant for identifying cloud-like, diffuse krill aggregations that are intertwined with small, often sparse and sometimes dense schools of finfish. We propose U-MSAA-Net, a deep learning U-Net-like framework with novel multi-scale additive attention (MSAA) modules. MSAA modules allow us to leverage all contextual and local information from feature maps available at any given level of the decoding phase of the network, yielding an efficient suppression of the feature responses from regions with lesser semantic value. Experimental results on a new finfish and krill data set spanning across nine months of acoustic data and covering various situations show that U-MSAA-Net outperforms both traditional, texture-based machine learning methods, and deep learning methods based on state-of-the-art semantic segmentation networks. Additional experiments on a data set containing schools of herring and salmon confirm the versatility of U-MSAA-Net and its superiority in terms of accuracy and ability to detect schools of varying sizes. U-MSAA-Net is the first step in creating a comprehensive tool for stock and ecosystem assessments.

Material properties and broadband backscatter measurements of individual euphausiids from the California coastal ecosystem

During the 14–24 May 2019 leg of the NOAA juvenile rockfish survey, zooplankton and small nekton were sampled off the coast of Northern California using a midwater trawl. This talk will focus on three euphausiid species (E. pacifica, T. spinifera, N. difficilis) which were present in most catches. Krill morphology (size and shape) and animal density relative to seawater were measured for 175 live (or very recently expired) individuals. Roughly 150 individual krill were frozen and brought back to land for mass measurements. Soundspeed relative to seawater was measured for 15 mixed-species aggregations of krill. Broadband (38–73 and 130–210 kHz) and narrowband (38, 50, 70, 120, 150, and 200 kHz) backscatter measurements were made on 32 live (or very recently expired) individual krill. These empirical measurements were then compared to predictive backscatter measurements using scattering model parameters measured for those individuals (when available). Differences between predicted and measured backscatter were generally small, although there were individual krill where measurements at some frequencies varied significantly (i.e. more than 3dB). Understanding the variability in scattering model inputs among and within these species, and the accuracy of scattering model predictions provides context (i.e. uncertainty estimates) for acoustic measures (or indices) of krill biomass.

Antarctic krill (Euphausia superba) distributions, aggregation structures, and predator interactions in Bransfield Strait

The Antarctic krill, Euphausia superba, is a major component of the Southern Ocean’s ecosystem. Limited high-resolution data on the relative importance of oceanographic processes on the behavioral responses of krill at traditional predator foraging grounds constitutes a major obstacle in the understanding of krill-environment coupling and ecosystem-based management of this resource. Aggregation structures of krill and predator interactions were investigated using active acoustic data collected by WBAT echosounders deployed on moorings in two hydrographically different sites in Bransfield Strait. Near Nelson Island, water flows from the northwest to southeast while Deception Island is influenced by stronger net current velocities from the southwest to northeast. Krill aggregations were identified and then classified in three clusters using a swarm-identification algorithm and hierarchical clustering using aggregation morphological characteristics: acoustic density, mean depth, center of mass, inertia, equivalent area, aggregation index, and proportion occupied. A total of 693 and 736 aggregations were detected at the mooring sites close to Nelson and Deception Islands. The three aggregation categories ranged from high to low densities, evenness, and dispersion and were distributed throughout the water column. Krill aggregation density distribution and mean thickness are influenced by krill mean depth, current velocities and direction. The majority of observed predator dive profiles occurred over the aggregation type with highest krill densities at both Nelson and Deception Islands, and within the first 25 m of the water column. The heterogeneity of krill aggregations potentially impacts predator foraging strategies and predator–krill interactions in the hydrodynamically active Bransfield Strait.

Automatic classification of acoustically detected krill aggregations: A case study from Southern Ocean

Acoustic surveys represent the standard methodology to assess the spatial distribution and abundance of pelagic organisms characterized by aggregative behaviour. The species identification of acoustically observed aggregations is usually performed by taking into account the biological sampling and according to expert-based knowledge. The precision of survey estimates, such as total abundance and spatial distribution, strongly depends on the efficiency of acoustic and biological sampling as well as on the species identification. In this context, the automatic identification of specific groups based on energetic and morphological features could improve the species identification process, allowing to improve the precision of survey estimates or to overcome problems related to biases in biological sampling. In the present study, we test the use of well-known unsupervised clustering methods focusing on two important krill species namely Euphausia superba and Euphausia crystallorophias. In order to obtain a reference classification, the observed echoes were first classified according to specific criteria based on two parameters accounting for the acoustic response at 38 kHz and 120 kHz. Different clustering methods combined with three distance metrics were then tested working on a wider set of parameters, accounting for the depth of insonified aggregation as well as for energetic and morphological features. The clustering performances were then evaluated by comparing the reference classification to the one obtained by clustering. Obtained results showed that the k-means performs better than the considered hierarchical methods. Our findings also evidenced that working on a specific set of variables rather than on all available ones highly impact k-means performances.

Non-negative Intensity for Target Strength Identification in Marine Ecosystem Research

In this paper, we propose non-negative intensity (NNI) as an alternative intensity-based technique for target strength identification in marine ecosystem research. NNI identifies local surface regions of a body with positive-only sound power contributions. NNI is employed for sound scattering by fluid-loaded, fluid-filled elastic structures with weak scattering boundary conditions. Three numerical case studies are presented for which fully coupled fluid-structure interaction models based on the finite element method (FEM) and the boundary element method (BEM) are developed. To validate the three-way coupling between the structural and fluid domains, an elastic shell submerged in water and filled with different internal fluids is initially considered. Results for the scattered acoustic intensity obtained numerically are compared with analytical results from the literature. Models representing Antarctic krill of simple and complex geometry are developed. A 3×3 cylinder array representing a simplified aggregation of krill is also presented. Target strength is calculated using both the scattered intensity and NNI for different incident excitation angles. Results for NNI identify the surface regions of an individual organism or group of organisms with the greatest contribution to the scattered sound at the target strength locations.

Social exploitation of extensive, ephemeral, environmentally controlled prey patches by supergroups of rorqual whales

Large groups of animals aggregate around resource hotspots, with group size often influenced by the heterogeneity of the environment. In most cases, the foraging success of individuals within groups is interdependent, scaling either constructively or destructively with group size. Here we used biologging tags, acoustic prey mapping, passive acoustic recording of social cues and remote sensing of surface currents to investigate an alternative scenario in which large, dense aggregations of southeast Atlantic humpback whales, Megaptera novaeangliae , and northeast Pacific blue whales, Balaenoptera musculus , were each associated with ephemeral krill aggregations large enough such that their availability to predators appeared to be influenced more by environmental features than by consumption, implying independence of group size and consumption rates. We found that the temporal scale and spatial extent of oceanographic drivers were consistent with the temporal scale and locations of predator aggregations, and additionally found that groups formed above bathymetric features known to promote zooplankton concentration. Additionally, we found calling behaviour counter-indicative of competition: blue whale foraging calls were anomalously high during observed aggregation time periods, suggesting signalling behaviour that could alert conspecifics to the location of high-quality resources. Modelled results suggest that the use of social information reduces the time required for individuals to discover and exploit high-quality resources, allowing for more efficient foraging without apparent costs to the caller. Thus, rorqual whales foraging in these environments appear to exhibit a social foraging strategy whereby a behaviour with negligible individual costs (signalling) provides information that enhances group foraging efficiency. The population density dependence of this social foraging strategy may help explain why some rorqual species were at first slow to recover from human exploitation, but have since increased more rapidly. • Large, dense prey patches were found near supergroups of rorqual whales. • Ephemeral patches formed when surface features intersected with bathymetry. • Blue whales increased social call production during observed aggregation events. • Rorqual whale foraging appears to be enhanced when social information is utilized.

Acoustic Detection of Krill Scattering Layer in the Terra Nova Bay Polynya, Antarctica

Krill play a crucial role in the transfer of energy in the marine food web, connecting primary producers and the upper trophic levels in the Terra Nova Bay polynya (TNBP), which is part of the Ross Sea marine protected area. Despite the substantial ecological importance of krill, there are few studies on their distribution and abundance in the TNBP. An acoustic survey was conducted on 7‒14 January 2019 in the TNBP, Ross Sea, using a Simrad EK60 echosounder (38 and 120 kHz) aboard the icebreaker RV Araon. The most commonly used range of the difference of the mean volume backscattering strength (2–16 dB) was applied to distinguish krill. The acoustic data (120 kHz) were extracted to examine the krill distribution characteristics. The study area was divided into low-value areas and high-value areas based on the third quartile of the nautical area scattering coefficient. The results showed that the krill aggregations were distributed in three layers at depths of 0‒30 m, 70‒110 m, and 270‒300 m. The interpolated environmental parameters associated with the backscattering strength were compared. High-value areas of krill coincided with relatively low temperature, low salinity, and high chlorophyll, although very weak correlations were found. The primary goal of this study was to understand the vertical and horizontal distributions of krill acoustic biomass and to relate the observed patterns to the dominant environmental conditions.

Planning for success: Leveraging two ecosystem models to support development of an Antarctic marine protected area

Efforts are underway to forward a marine protected area (MPA) in the Western Antarctic Peninsula, guided by an internationally agreed framework of protected area objectives. Preliminary MPA boundaries were evaluated against some of these objectives using a static, map-based process, yet further assessment and additional objectives could be addressed with dynamic approaches. Here, the MPA's evaluation was expanded using the joint application of two published dynamic ecosystem models to further appraise the MPA. These models also considered potential impacts of climate change in the region, and greater insight can be gained from using them together rather than independently. Both models projected the proposed MPA could increase ecosystem viability in the region by reducing potential population declines, especially of penguins. These benefits manifested even when the impacts of climate change occurred over the long term, and likely accrued due to protection of areas important for krill aggregation and predator foraging. Model outcomes also suggested possible improvements to the preliminary MPA boundaries to reinforce these benefits. Using the two structurally distinct models together increased confidence in results and the potential for an MPA to meet multiple policy objectives in the region, and the paper further details the process of translating outcomes into timely decision support for stakeholders. Modelling results were regularly communicated using established formal and informal channels, ensuring model-derived advice directly supported policy needs. Collectively, the work demonstrates the process and value of leveraging existing ecosystem models, quickly adapting models to policy needs, and developing actionable advice for policy makers.

Links in the trophic chain: modeling functional relationships between in situ oceanography, krill, and blue whale distribution under different oceanographic regimes

The response of marine predators to global climate change and shifting ocean conditions is tightly linked with their environment and prey. Environmental data are frequently used as proxies for prey availability in marine predator distribution models, as the ephemeral nature of prey makes sampling difficult. For this reason, the functional, ecological links between environment, prey, and predator are rarely described or explicitly tested. We used 3 years of vessel-based whale survey data paired with oceanographic sampling and hydroacoustic backscatter to model trophic relationships between water column structure, krill availability, and blue whaleBalaenoptera musculus brevicaudadistribution in New Zealand’s South Taranaki Bight region under typical (2014 and 2017) and warm (2016) austral summer oceanographic regimes. The warm regime was characterized by a shallower mixed layer, and a stronger, thicker, and warmer thermocline. Boosted regression tree models showed that krill metrics predicted blue whale distribution (typical regime = 36% versus warm regime = 64% cross-validated deviance explained) better than oceanography (typical regime = 19% versus warm regime = 31% cross-validated deviance explained). However, oceanographic features that predicted more krill aggregations (typical regime) and higher krill density (warm regime) aligned closely with the features that predicted higher probability of blue whale presence in each regime. Therefore, this study confirms that environmental drivers of prey availability can serve as suitable proxies for blue whale distribution. Considering changing ocean conditions that may influence the distribution of marine predators, these findings emphasize the need for models based on functional relationships, and calibrated across a broad range of conditions, to inform effective conservation management.

Plankton or benthos: where krill belongs in Spitsbergen fjords? (Svalbard Archipelago, Arctic)

This study couples observations of krill (Thysanoessa inermis, Thysanoessa longicaudata, Thysanoessa rashii) from Tucker trawl nets and cameras, trying to test hypothesis that in the glaciated fjords of Svalbard most of the euphausiids biomass is located in near-bottom habitat and explains why in this region there are a substantial part of the krill population near the sea floor. Photographic material from the summers of 2013–2017 shows large numbers of near-bottom euphausiids (39% of the total krill biomass in Hornsund and 41% in Kongsfjorden), which reached a maximum density of 751 ± 224 indiv. m−3 in Kongsfjorden, 731 ± 198 indiv. m−3 in Hornsund, and 426 ± 124 indiv. m−3 in Adventfjorden. Regional distribution of near-bottom aggregations of krill seem to be associated with close proximity to the glacier front rather than with depth. The highest densities were located in the glacial bays. Where and why these aggregations occur is probably complicated and dependent on many environmental factors acting together. However, the dominant factors seem to be sedimentation and estuarine circulation. No krill aggregations were found during the winter cruise. The dominating species was T. inermis which made up 90% of the community. Other krill species—T. rashii and T. longicaudata, made up 6% and 4%, respectively. In the summer, aggregations of other macrozooplankton were also observed: amphipods of the genus Themisto and chaetognaths of the genera Eukrohnia and Parasagitta. Euphausiid densities in the water column (from Tucker trawl hauls) were an order of magnitude lower (0.33 indiv. m−3 for Kongsfjorden and 0.61 indiv. m−3 for Hornsund) than those of the near-bottom aggregations observed on cameras system. At most stations, the krill exhibited a behaviour, known as “nose diving” in the sediment, which is likely related to feeding. Observation of this phenomenon may indicate that krill (mostly T. inermis), found near the bottom of Spitsbergen fjords, is looking for food there. Near-bottom aggregations of zooplankton, mainly krill, are common in glacial bays and can be important in the function of the fjord ecosystem. Our research proves that the zooplankton biomass can be highly underestimated if only Tucker trawl sampling is done, due to neglecting the near-bottom layer in this type of method.

Behavioural responses of humpback whales to food-related chemical stimuli.

Baleen whales face the challenge of finding patchily distributed food in the open ocean. Their relatively well-developed olfactory structures suggest that they could identify the specific odours given off by planktonic prey such as krill aggregations. Like other marine predators, they may also detect dimethyl sulfide (DMS), a chemical released in areas of high marine productivity. However, dedicated behavioural studies still have to be conducted in baleen whales in order to confirm the involvement of chemoreception in their feeding ecology. We implemented 56 behavioural response experiments in humpback whales using two food-related chemical stimuli, krill extract and DMS, as well as their respective controls (orange clay and vegetable oil) in their breeding (Madagascar) and feeding grounds (Iceland and Antarctic Peninsula). The whales approached the stimulus area and stayed longer in the trial zone during krill extract trials compared to control trials, suggesting that they were attracted to the chemical source and spent time exploring its surroundings, probably in search of prey. This response was observed in Iceland, and to a lesser extend in Madagascar, but not in Antarctica. Surface behaviours indicative of sensory exploration, such as diving under the stimulus area and stopping navigation, were also observed more often during krill extract trials than during control trials. Exposure to DMS did not elicit such exploration behaviours in any of the study areas. However, acoustic analyses suggest that DMS and krill extract both modified the whales’ acoustic activity in Madagascar. Altogether, these results provide the first behavioural evidence that baleen whales actually perceive prey-derived chemical cues over distances of several hundred metres. Chemoreception, especially olfaction, could thus be used for locating prey aggregations and for navigation at sea, as it has been shown in other marine predators including seabirds.

Phytoplankton odor modifies the response of Euphausia superba to flow

Antarctic krill, Euphausia superba, are critical components of the Antarctic food web as well as important targets for conservation and management. Krill behavior has important effects on demographic properties and aggregation characteristics, but remains incompletely known. Krill clearly respond to different environmental stimuli such as light, flow and chemicals, but few studies have quantified these behaviors. We examined the behavior of krill in well-quantified current speeds in a laboratory flume and examined interactions of phytoplankton odor and flow. Krill are sensitive to flow speeds as low as 1 mm s−1, and flow polarizes krill swimming and orientation in the up-current direction. Phytoplankton odor increases the sensitivity of krill to flow, and induces area-restricted search behaviors that presumably allow krill to exploit food patches efficiently. The ability to quantify krill behavior could have important consequences for understanding demographic processes and the properties of krill aggregations.

Characterization of Frequency and Aggregation of the Antarctic Krill (Euphausia superba) Using Acoustics

In this study, the dB difference and characteristics of krill swarms inhabiting Subarea 48.1, which includes the west and south of the South Shetland Island and the Elephant Island peripheries, were estimated to distinguish Antarctic krill, using acoustics. From April 13 to 24, 2016, acoustic data were collected along 24 survey lines using the frequencies 38 and 120 kHz, and middle trawling was performed at 7 stations. Using the difference between the dB values of two volume backscattering strength (Sv) frequencies (38 and 120 kHz), a clear acoustic distinction could be made between Antarctic krill (4.9 to 12.0 dB) and fish (−4.0 to −0.2 dB). The distributions and mean Sv of krill swarms in the Elephant Island peripheries and south of South Shetland Island were higher than those in the west of South Shetland Island. The mean length/ height ratio of krill swarms in the west of the South Shetland Island (64.5) was higher than that in the south (35.9) and the Elephant Island peripheries (33.8), with the length of the aggregations exceeding their height. Most krill swarms were distributed between the surface layer (less than 10 m below sea level) and within 200 m of water depth. These results are expected to serve as baseline data for evaluating krill density and biomass by distinguishing them from fish, using acoustics.

Factors that affect the nearshore aggregations of Antarctic krill in a biological hotspot

Antarctic krill, Euphausia superba, is a highly abundant and ecologically important zooplankton species in the Southern Ocean. Regions of elevated Antarctic krill biomass exist around Antarctica, often as a result of the concentrating effect of bathymetry and ocean currents. Such areas are considered biological hotspots and are key foraging grounds for numerous top predators in the region. A hotspot of Antarctic krill biomass exists off the southern extent of Anvers Island, Western Antarctic Peninsula, and supports a population of Adélie penguins that feed almost exclusively on it, as well as numerous other top predators. We investigated the spatio-temporal variability in Antarctic krill biomass and aggregation structure over four consecutive summer seasons, identifying environmental factors that were responsible. We identified three distinct krill aggregation types (Large-dense, Small-close and Small-sparse), and found that the relative proportion of each type to total aggregation numbers varied significantly between survey days. Large-dense aggregations occurred more frequently when westerly winds predominated and when the local mixed tide was in the diurnal regime. Small-close aggregations were also more frequent during diurnal tides and were negatively correlated with phytoplankton biomass. Small-sparse aggregations, on the other hand, were more prevalent when the mixed tide was in the semi-diurnal phase. We suggest that, under certain conditions (i.e. diurnal tides and westerly winds), the biological hotspot in the nearshore waters off Palmer Station, Anvers Island, functions as a zone of accumulation, concentrating krill biomass. Our findings provide important information on the dynamics of Antarctic krill at the local scale.

Measurement of the volume-backscattering spectrum from an aggregation of Antarctic krill and inference of their length-frequency distribution

Antarctic krill, Euphausia superba, were observed using a broadband echosounder and their length-density distribution was inferred from the echo data through a least square inversion. The observation was conducted in the Indian Ocean sector of the Southern Ocean in January 2014. The transmit signal was a 10-ms linear frequency-modulated signal with a frequency sweep of 20–200 kHz. A large aggregation of Antarctic krill was observed at a sampling station over the continental shelf. The volume-backscattering strengths in the frequency range of 85–187 kHz were determined from the observed echoes. In addition, the signal-to-noise ratio at each frequency was estimated and the measured volume-backscattering strengths were evaluated before inversion for accurate inferences. In this inversion, Antarctic krill were modeled as prolate spheroids and the target strengths were predicted by the distorted-wave Born approximation. The acoustically inferred mean length was in good agreement with the mode length determined by a net sampling performed immediately after the echo sampling. Also, the acoustically inferred length-frequency distribution was in reasonable agreement with the determined one from the net samples.