Multi-frequency Echosounder Research Articles

Prevalence of Chinook salmon is higher for southern than for northern resident killer whales in summer hot-spot feeding areas.

Differences in the availability of prey may explain the low numbers of southern resident killer whales and the increase in northern resident killer whales in British Columbia and Washington State. However, in-situ data on the availability of their preferred prey (Chinook salmon, Oncorhynchus tshawytscha) in the core feeding areas used by these two populations of fish-eating killer whales have been lacking to test this hypothesis. We used multi-frequency echosounders (38, 70, 120, and 200 kHz) to estimate densities of adult Chinook (age-4+, > 81 cm) within 16 hot-spot feeding areas used by resident killer whales during summer 2020 in the Salish Sea and North Island Waters. We found Chinook were generally concentrated within 50 m from the bottom in the deep waters, and tended to be absent near the surface in the shallow waters (< 50 m). In general, the densities of Chinook we encountered were highest as the fish entered the Salish Sea (from Swiftsure Bank in the south) and Johnstone Strait (from Queen Charlotte Strait to the north)-and declined as fish migrated eastward along the shoreline of Vancouver Island. Median densities of Chinook for all sampled areas combined were 0.4 ind.·1000 m-2 in northern resident foraging areas, and 0.9 ind.·1000 m-2 in southern resident killer whale areas (p < 0.05, Mann-Whitney U test). Thus, Chinook salmon were twice as prevalent within the hot-spot feeding areas of southern versus northern resident killer whales. This implies that southern resident killer whales have greater access to Chinook salmon compared to northern residents during summer-and that any food shortage southern residents may be encountering is occurring at other times of year, or elsewhere in their range.

Deep Semisupervised Semantic Segmentation in Multifrequency Echosounder Data

Multifrequency echosounder data can provide a broad understanding of the underwater environment in a noninvasive manner. The analysis of echosounder data is, hence, a topic of great importance for the marine ecosystem. Semantic segmentation, a deep learning-based analysis method predicting the class attribute of each acoustic intensity, has recently been in the spotlight of the fisheries and aquatic industry since its result can be used to estimate the abundance of marine organisms. However, a fundamental problem with current methods is the massive reliance on the availability of large amounts of annotated training data, which can only be acquired through expensive handcrafted annotation processes, making such approaches unrealistic in practice. As a solution to this challenge, we propose a novel approach, where we leverage a small amount of annotated data (supervised deep learning) and a large amount of readily available unannotated data (unsupervised learning), yielding a new data-efficient and accurate <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">semisupervised</i> semantic segmentation method, all embodied into a single end-to-end trainable convolutional neural network architecture. Our method is evaluated on representative data from a sandeel survey in the North Sea conducted by the Norwegian Institute of Marine Research. The rigorous experiments validate that our method achieves comparable results utilizing only 40% of the annotated data on which the supervised method is trained, by leveraging unannotated data.

Acoustic micronektonic distribution and density is structured by macroscale oceanographic processes across 17–48° N latitudes in the North Atlantic Ocean

This study investigates the large-scale distribution patterns of the acoustic scattering layers and micronekton density across the Northeast Atlantic Ocean during daylight hours. A research cruise on board R/V “Kronprins Haakon” was conducted during May 2019 from Cape Verde to Bay of Biscay. Hydrological data were obtained at 20 conductivity-temperature-depth sensor (CTD) stations. To estimate the micronekton densities in front of the trawl, an autonomous echo sounder (120 or 200 kHz) on the headrope of the macroplankton trawl was used. Acoustic data were also collected along the cruise track using ship-mounted multi-frequency echo sounders (backscatter at 18 and 38 kHz was analyzed). Acoustic observations (both at 18, 38 and 120/200 kHz) showed clear patterns in the horizontal distribution of the micronekton during daytime with higher backscatter and echo densities in the south of the study area (from 17 to 37° N), and the absence of high backscatter in the surface from 37 to 45° N. Backscatter and echo densities were found to be significantly influenced by: temperature, salinity, and oxygen, as well as depth and time of the day.

Acoustic Classification of Juvenile Pacific Salmon (Oncorhynchus spp) and Pacific Herring (Clupea pallasii) Schools Using Random Forests

Acoustic surveys are the standard approach for evaluating many fish stocks around the world. The analysis of such survey data requires the accurate echo-classification of target species. This classification is often challenging as many organisms exhibit overlapping characteristics in terms of shape, acoustic amplitude, and behavior. In this study, a random forest approach was used to distinguish juvenile Pacific salmon (Oncorhynchus spp) from Pacific herring (Clupea pallasii) aggregations using the acoustic and morphological characteristics of their echo traces. The acoustic data was collected with an autonomous, multi-frequency echosounder deployed on the seafloor in the Discovery Islands, British Columbia from May to September 2015. The model was able to differentiate juvenile Pacific salmon from Pacific herring with a 98% accuracy. School depth and school mean volume backscattering strength were the most important predictors in determining the school classification. This study supports other publications suggesting that random forests represent a promising approach to acoustic target classification in fisheries science.

Southern resident killer whales encounter higher prey densities than northern resident killer whales during summer

The decline of southern resident killer whales (Orcinus orca) may be due to a shortage of prey, but there is little data to test this hypothesis. We compared the availability of prey (Chinook salmon, Oncorhynchus tshawytscha) sought by southern residents in Juan de Fuca Strait during summer with the abundance and distribution of Chinook available to the much larger and growing population of northern resident killer whales feeding in Johnstone Strait. We used ship-based multifrequency echosounders to identify differences in prey fields that may explain the dynamics of these two killer whale populations. Contrary to expectations, we found that both killer whale habitats had patchy distributions of prey that did not differ in their frequencies of occurrence, nor in the size compositions of individual fish. However, the density of fish within each patch was 4–6 times higher in the southern resident killer whale habitat. These findings do not support the hypothesis that southern resident killer whales are experiencing a prey shortage in the Salish Sea during summer and suggest a combination of other factors is affecting overall foraging success.

Where do the fish come from, and where do they go? Seasonal observations of pelagic fishes from echosounder moorings in the Chukchi sea

Recent summer surveys of the Chukchi Sea determined that pelagic fishes were dominated by large numbers of age-0 Arctic cod and walleye pollock, while adult fishes are comparatively scarce. Modeling based on regional currents indicates that these age-0 fishes are likely advected to the north in fall; however, the source and fate of these fishes remains unclear as this region is seasonally ice-covered. To determine the movement and variability of this age-0 gadid population, bottom-moored multifrequency echosounders were deployed at three locations in the northeastern Chukchi Sea from 2017-2019. These observations indicate that the abundance and composition of the pelagic community on the Chukchi Sea shelf is highly variable over seasonal time scales. Fish abundance was very low in winter, increased in May, and reached peak abundance in late summer. Target strength and diel vertical migration of fishes increased in summer, indicating that this is a key period for growth. Age-0 gadids were displaced to the northeast, consistent with the dominant advection on the shelf. Fish speeds and headings were strongly correlated with local currents, providing evidence that these small age-0 fishes are primarily being passively transported and behavior plays a limited role in population distribution.

Internal solitary waves on the NW African shelf: A heuristic approach to localize diapycnal mixing hotspots

Turbulent mixing on continental shelves plays roles in the structure and dynamics of marine ecosystems, nutrient cycling, primary production and dispersion of pollutants. Describing and understanding internal wave dynamics enables improved mapping of mixing over continental shelves, especially in complex environments where many processes may interact, such as in upwelling systems. This paper describes internal wave propagation and dissipation in the Moroccan upwelling system using a comprehensive set of hydrographic observations made during two in situ surveys. The acoustic backscatter of the echosounder is shown to be a rapid and convenient survey tool for detecting internal solitary waves (ISWs) on large spatial scales, through the high-frequency oscillation of the zooplankton layer during nighttime conditions. Along ISW trains, enhanced diapycnal mixing episodes are observed with increased dissipation coefficients in the thermocline (O(10-7 W kg-1)), associated with overturning up to 6 m. Mixing due to internal wave soliton packets shows large spatial and temporal variability, but contributes to the overall mixing processes and is responsible for large intermittent variations in the thermocline position. The joint use of a multifrequency echosounder and a current profiler ADCP allows mixing to be quantified (via the Richardson number) on large spatial scales. Validation and use of this method in other coastal regions could be useful to determine regional mixing parameterization in numerical models.

Atlantic deepwater ecosystem observatory network: Patterns of acoustic backscatter and community structure of the U.S. Outer Continental Shelf

Three nodes in the Atlantic Deepwater Ecosystem Observatory Network (ADEON) network on the U.S. Mid- and South Atlantic Outer Continental Shelf (OCS) contain an upward looking, multi-frequency echosounder system. Data was collected from November 2017–December 2020 at these sites extending from the OCS waters of Virginia down to Florida. Along shelf backscatter comparisons were made for general scattering groups related to fish and zooplankton across time and latitude. Unique seasonal patterns were observed across sites both in terms of volume backscatter magnitude and community structure. Measurements made within this research program will serve as a baseline for pattern and trend analyses of acoustic backscatter related to ecosystem components of this traditionally under sampled, offshore region. Study concept, oversight, and funding were provided by BOEM under Contract No. M16PC00003, in partnership with ONR and NOAA. Funding for ship time was provided under separate contracts by ONR, Code 32.

Pelagic forage fish distribution in a dynamic shelf ecosystem – Thermal demands and zooplankton prey distribution

The fine-scale distribution of pelagic forage fish is shaped by competing factors as fish optimise foraging while avoiding predation. We investigated the distribution of forage fish in surface waters of a dynamic coastal environment during two spring seasons to examine their distribution in relation to environmental variables. Using a multi-frequency echosounder and a towed Laser Optical Plankton Counter (LOPC), we investigated the effects of bathymetry, temperature, chlorophyll a concentration and zooplankton biomass on forage fish density. Relationships between fish density and these variables were consistent between surveys, despite large differences in total acoustic energy attributed to fish. Fish density showed a strong positive relationship with bathymetry and water temperature, and no relationship with surface zooplankton biomass density or chlorophyll a. This mismatch between fish and zooplankton may be caused by differences in the way fish perceive the distribution of prey versus temperature and predators in shallow coastal waters. Seeking out warmer temperatures along the shelf break may also improve fish physiological performance when cooler spring temperatures are below their thermal optimum. Understanding the distribution of coastal forage fish may contribute to interpreting nearshore movements of their predators.

Combined eDNA and Acoustic Analysis Reflects Diel Vertical Migration of Mixed Consortia in the Gulf of Mexico

Oceanic diel vertical migration (DVM) constitutes the daily movement of various mesopelagic organisms migrating vertically from depth to feed in shallower waters and return to deeper water during the day. Accurate classification of taxa that participate in DVM remains non-trivial, and there can be discrepancies between methods. DEEPEND consortium (www.deependconsortium.org) scientists have been characterizing the diversity and trophic structure of pelagic communities in the northern Gulf of Mexico (nGoM). Profiling has included scientific echosounders to provide accurate and quantitative estimates of organismal density and timing as well as quantitative net sampling of micronekton. The use of environmental DNA (eDNA) can detect uncultured microbial taxa and the remnants that larger organisms leave behind in the environment. eDNA offers the potential to increase understanding of the DVM and the organisms that participate. Here we used real-time shipboard echosounder data to direct the sampling of eDNA in seawater at various time-points during the ascending and descending DVM. This approach allowed the observation of shifts in eDNA profiles concurrent with the movement of organisms in the DVM as measured by acoustic sensors. Seawater eDNA was sequenced using a high-throughput metabarcoding approach. Additionally, fine-scale acoustic data using an autonomous multifrequency echosounder was collected simultaneously with the eDNA samples and changes in organism density in the water column were compared with changes in eDNA profiles. Our results show distinct shifts in eukaryotic taxa such as copepods, cnidarians, and tunicates, over short timeframes during the DVM. These shifts in eDNA track changes in the depth of sound scattering layers of organisms and the density of organisms around the CTD during eDNA sampling. Dominant taxa in eDNA samples were mostly smaller organisms that may be below the size limit for acoustic detection, while taxa such as teleost fish were much less abundant in eDNA data compared to acoustic data. Overall, these data suggest that eDNA, may be a powerful new tool for understanding the dynamics and composition of the DVM, yet challenges remain to reconcile differences among sampling methodologies.

Acoustic classification in multifrequency echosounder data using deep convolutional neural networks

Abstract Acoustic target classification is the process of assigning observed acoustic backscattering intensity to an acoustic category. A deep learning strategy for acoustic target classification using a convolutional network is developed, consisting of an encoder and a decoder, which allow the network to use pixel information and more abstract features. The network can learn features directly from data, and the learned feature space may include both frequency response and school morphology. We tested the method on multifrequency data collected between 2007 and 2018 during the Norwegian sandeel survey. The network was able to distinguish between sandeel schools, schools of other species, and background pixels (including seabed) in new survey data with an F1 score of 0.87 when tested against manually labelled schools. The network separated schools of sandeel and schools of other species with an F1 score of 0.94. A traditional school classification algorithm obtained substantially lower F1 scores (0.77 and 0.82) when tested against the manually labelled schools. To train the network, it was necessary to develop sampling and preprocessing strategies to account for unbalanced classes, inaccurate annotations, and biases in the training data. This is a step towards a method to be applied across a range of acoustic trawl surveys.

Mesopelagic Sound Scattering Layers of the High Arctic: Seasonal Variations in Biomass, Species Assemblage, and Trophic Relationships

Mesopelagic sound scattering layers (SSL) are ubiquitous in all oceans. Pelagic organisms within the SSL play important roles as prey for higher trophic levels and in climate regulation through the biological carbon pump. Yet, the biomass and species composition of SSL in the Arctic Ocean remain poorly documented, particularly in winter. A multifrequency echosounder detected a SSL north of Svalbard, from 79.8°N to 81.4°N, in January 2016, August 2016, and January 2017. Midwater trawl sampling confirmed that the SSL comprised zooplankton and pelagic fish of boreal and Arctic origins. Juvenile beaked redfish dominated the fish assemblage in January and Arctic cod in August. The macrozooplankton community mainly comprised the medusa Cyanea capillata, the amphipod Themisto libellula, and the euphausiids Meganyctiphanes norvegica in August and Thysanoessa inermis in January. The SSL was located in the Atlantic Water mass, between 200-700 m in August and between 50-500 m in January. In January, the SSL was shallower and weaker above the deeper basin, where less Atlantic Water penetrated. The energy content available in the form of lipids within the SSL was significantly higher in summer than winter. The biomass within the SSL was >12-fold higher in summer, and the diversity of fish was slightly higher than in winter (12 vs. 9 species). We suggest that these differences are mainly related to life history and ontogenetic changes resulting in a descent towards the seafloor, outside the mesopelagic layer, in winter. In addition, some fish species of boreal origin, such as the spotted barracudina, did not seem to survive the polar night when advected from the Atlantic into the Arctic. Others, mainly juvenile beaked redfish, were abundant in both summer and winter, implying that the species can survive the polar night and possibly extend its range into the high Arctic. Fatty-acid trophic markers revealed that Arctic cod mainly fed on calanoid copepods while juvenile beaked redfish targeted krill (Thysanoessa spp.). The relatively high biomass of Arctic cod in August and of redfish in January thus suggests a shift within the SSL, from a Calanus-based food web in summer to a krill-based food web during winter.

Broadband classification and statistics of echoes from aggregations of fish measured by long-range, mid-frequency sonar.

For horizontal-looking sonar systems operating at mid-frequencies (1-10 kHz), scattering by fish with resonant gas-filled swimbladders can dominate seafloor and surface reverberation at long-ranges (i.e., distances much greater than the water depth). This source of scattering, which can be difficult to distinguish from other sources of scattering in the water column or at the boundaries, can add spatio-temporal variability to an already complex acoustic record. Sparsely distributed, spatially compact fish aggregations were measured in the Gulf of Maine using a long-range broadband sonar with continuous spectral coverage from 1.5 to 5 kHz. Observed echoes, that are at least 15 decibels above background levels in the horizontal-looking sonar data, are classified spectrally by the resonance features as due to swimbladder-bearing fish. Contemporaneous multi-frequency echosounder measurements (18, 38, and 120 kHz) and net samples are used in conjunction with physics-based acoustic models to validate this approach. Furthermore, the fish aggregations are statistically characterized in the long-range data by highly non-Rayleigh distributions of the echo magnitudes. These distributions are accurately predicted by a computationally efficient, physics-based model. The model accounts for beam-pattern and waveguide effects as well as the scattering response of aggregations of fish.

Multisensor Acoustic Tracking of Fish and Seabird Behavior Around Tidal Turbine Structures in Scotland

Despite rapid development of marine renewable energy, relatively little is known of the immediate and future impacts on the surrounding ecosystems. Quantifying the behavior and distribution of animals around marine renewable energy devices is crucial for understanding, predicting, and potentially mitigating any threats posed by these installations. The Flow and Benthic Ecology 4D (FLOWBEC) autonomous seabed platform integrated an Imagenex multibeam echosounder and a Simrad EK60 multifrequency echosounder to monitor marine life in a 120 $^{\circ}$ sector over ranges up to 50 m, seven to eight times per second. Established target detection algorithms fail within MRE sites, due to high levels of backscatter generated by the turbulent physical dynamics, limiting and biasing analysis to only periods of low current speed. This study presents novel algorithms to extract diving seabirds, fish, and fish schools from the intense backscatter caused by turbulent dynamics in flows of 4 m s $^{{-1}}$ . Filtering, detection, and tracking using a modified nearest neighbor algorithm provide robust tracking of animal behavior using the multibeam echosounder. Independent multifrequency target detection is demonstrated using the EK60 with optimally calculated thresholds, scale-sensitive filters, morphological exclusion, and frequency-response characteristics. This provides sensitive and reliable detection throughout the entire water column and at all flow speeds. Dive profiles, depth preferences, predator–prey interactions, and fish schooling behavior can be analyzed, in conjunction with the hydrodynamic impacts of marine renewable energy devices. Coregistration of targets between the acoustic instruments increases the information available, providing quantitative measures including frequency response from the EK60, and target morphology and behavioral interactions from the multibeam echosounder. The analyses draw on deployments at a tidal energy site in Scotland to compare the presence and absence of renewable energy structures across a range of physical and trophic levels over complete spring-neap tidal cycles. These results can be used to inform how animals forage in these sites and whether individuals face collision risks. This quantitative information can de-risk the licensing process and, with a greater mechanistic understanding at demonstration scales, its predictive power could reduce the monitoring required at future arrays.

Acoustic identification of marine species using a feature library

Sonars and echosounders are widely used for remote sensing of life in the marine environment. There is an ongoing need to make the acoustic identification of marine species more correct and objective and thereby reduce the uncertainty of acoustic abundance estimates. In our work, data from multi-frequency echosounders working simultaneously with nearly identical and overlapping acoustic beams are processed stepwise in a modular sequence to improve data, detect schools and categorize acoustic targets by means of the Large Scale Survey System software (LSSS). Categorization is based on the use of an acoustic feature library whose main components are the relative frequency responses. The results of the categorization are translated into acoustic abundance of species. The method is tested on acoustic data from the Barents Sea, the Norwegian Sea and the North Sea, where the target species were capelin (Mallotus villosus L.), Atlantic mackerel (Scomber scombrus L.) and sandeel (Ammodytes marinus L.), respectively. Manual categorization showed a high conformity with automatic categorization for all surveys, especially for schools.

Heterogeneity of deep scattering layer shapes the Bahamian mesopelagic ecosystem

We explored deep scattering layers off the Bahamas where the beaked whales have been historically observed. By comparing the habitats frequently used by the beaked whales with the ones rarely utilized, we examined the differences in mesopelagic ecosystem potentially driving the whales’ prey habitat through bottom-up control. Using ship-based multifrequency echosounders and direct net sampling, we identified common layer structures characterized by the diffuse, broad layers (>100 m in thickness) observed across the study site. Within those diffuse layers, we occasionally observed distinctively bounded intense layers (~20 m in thickness) located at the upper edges. Instead of a specific layer structure dominating the habitat characteristics, we found that heterogeneity of the layer structures shaped the preferred habitat of beaked whales. Frequently used habitat was characterized by evenly distributed diffuse layers alone, or combined with patchy thin layers. Less-used habitat showed diverse characteristics such as diffuse layers combined with highly variable patchiness of the thin layers. The layer depth, its thickness, and frequency response were not related to the preference of the habitats. Heterogeneity of the layer structures reveals the dynamics of the mesopelagic ecosystem, potentially impacting higher trophic levels.

Model for the Processing and Estimation of Dual Frequency Echo Sounder Observations in Detailed Bathymetries

ABSTRACTThe dataset acquired by an echo sounder generally comprises outliers and erroneous measurements which must be automatically processed. The main aim of this research is the development and validation of an algorithm which permits detecting outliers, estimating their real value from data acquired with a multifrequency echo sounder, and verifying the measure according to the desired accuracy. The process considers the nature of the seabed and improves the density and number of lectures without globally compromising the precision, but enhancing it in areas with anomalous measurements. Twenty-nine percent of this type of measurements, which would have been otherwise rejected, have been estimated.

An assessment of the use of ocean gliders to undertake acoustic measurements of zooplankton: the distribution and density of Antarctic krill (Euphausia superba) in the Weddell Sea.

A calibrated 120 kHz single‐beam echo‐sounder was integrated into an ocean glider and deployed in the Weddell Sea, Southern Ocean. The glider was deployed for two short periods in January 2012, in separate survey boxes on the continental shelf to the east of the Antarctic Peninsula, to assess the distribution of Antarctic krill (Euphausia superba). During the glider missions, a research vessel undertook acoustic transects using a calibrated, hull‐mounted, multi‐frequency echo‐sounder. Net hauls were taken to validate acoustic targets and parameterize acoustic models. Krill targets were identified using a thresholded schools analysis technique (SHAPES), and acoustic data were converted to krill density using the stochastic distorted‐wave Born approximation (SDWBA) target strength model. A sensitivity analysis of glider pitch and roll indicated that, if not taken into account, glider orientation can impact density estimates by up to 8‐fold. Glider‐based, echo‐sounder—derived krill density profiles for the two survey boxes showed features coherent with ship‐borne measurements, with peak densities in both boxes around a depth of 60 m. Monte Carlo simulation of glider subsampling of ship‐borne data showed no significant difference from observed profiles. Simulated glider dives required at least an order of magnitude more time than the ship to similarly estimate the abundance of krill within the sample regions. These analyses highlight the need for suitable sampling strategies for glider‐based observations and are our first steps toward using autonomous underwater vehicles for ecosystem assessment and long‐term monitoring. With appropriate survey design, gliders can be used for estimating krill distribution and abundance.

Broadband classification and statistics of long-range, mid-frequency sonar measurements of aggregations of fish

Scattering from fish can constitute a significant portion of the high-amplitude echoes in the case of a horizontal-looking sonar system operating at mid-frequencies (1–10 kHz). In littoral environments, reverberation from fish with resonant gas-filled swimbladders can dominate bottom and surface reverberation and add spatio-temporal variability to an already complex acoustic record. Measurements of sparsely distributed, spatially compact fish aggregations have been conducted in the Gulf of Maine using a long-range, broadband sonar with continuous coverage over the frequency band of 1.5–5 kHz. Concurrent downward-looking, multi-frequency echosounder measurements (18, 38, and 120 kHz), and net samples of fish are used in conjunction with physics-based acoustic models to classify and statistically characterize the long-range fish echoes. A significant number of echoes, which are at least 15 dB above background levels, were observed in the long-range data and classified as due to mixed assemblages of swimbladder-bearing fish. These aggregations of fish produce highly non-Rayleigh distributions of echo magnitudes. The probability density functions of the echoes are accurately predicted by a computationally efficient, physics-based model that accounts for beam-pattern and waveguide effects as well as the scattering response of aggregations of fish. [Work supported by the U.S. Office of Naval Research.]

The effect of depth on the target strength of a humpback whale (Megaptera novaeangliae).

Marine mammals are very seldom detected and tracked acoustically at different depths. The air contained in body cavities, such as lungs or swimbladders, has a significant effect on the acoustic energy backscattered from whale and fish species. Target strength data were obtained while a humpback whale (Megaptera novaeangliae) swam at the surface and dove underneath a research vessel, providing valuable multi-frequency echosounder recordings of its scattering characteristics from near surface to a depth of about 240 m. Increasing depth dramatically influenced the backscattered energy coming from the large cetacean. This study is tightly linked to the ultimate goal of developing an automated whale detection system for mitigation purposes.