Dual-frequency Identification Sonar Research Articles

Estimating spawning green sturgeon (Acipenser medirostris Ayres, 1854) abundance in the Sacramento River using side-scan sonar and N-mixture models

Current estimates of the threatened southern distinct population segment of the North American green sturgeon ( Acipenser medirostris) combine a plot-sampling density estimator with Dual frequency IDentification SONar (DIDSON) and adaptive resolution imaging sonar (ARIS) sonar data. From 2020 to 2022, we annually collected images of all known green sturgeon aggregations and compared the established method to an N-mixture model using side-scan sonar images. We compared 18 different N-mixture model combinations and chose an overdispersed Poisson model that produced estimated abundances of 742, 1286, and 1208 for 2020–2022, respectively. These numbers are ∼2 times greater than the previous method and, if sustained, would fulfill a key criterion for green sturgeon recovery. N-mixture models are known to be sensitive to violations of assumptions, such as the highly dispersed data from our study that caused serious issues, and we recommend practitioners make judicious use of overdispersion and goodness-of-fit tests and be able to identify parameter confounding between detectability and abundance estimates. For our green sturgeon, we recommend simpler population estimates and to focus future energy on reducing variability in the data collection process.

Understanding the temporal dynamics of a lowland river fish community at a hazardous intake and floodgate to inform safe operation

Entrainment and mortality of freshwater fish at hazardous pumping station intakes used for Flood Risk Management (FRM) are of global concern. Although upstream and downstream passage of diadromous fish has received considerable attention, the ecological behaviours of river-resident fish at these structures and how to protect these species from entrainment is poorly-understood. At a lowland flood-relief pumping station and floodgate situated off-channel (River Foss) to the main-river Yorkshire Ouse (York, England), multi-beam sonar (Dual-Frequency Identification Sonar: DIDSON) was used over a pluriannual (three years) period to investigate diel movements of river-resident fish in response to the variations in temperature, hydrology and pump and floodgate operation, and to determine fish-friendly management options. Diel lateral movements of thousands of river-resident fish between the main-river, floodgate operated channel (River Foss) and off-channel pump forebay were predominantly during the crepuscular period and daytime, proposing important considerations for when managers should operate pumps and associated flood infrastructure. Seasonal diel movements increased throughout winter during a baseline year (no pump operation) and overwintering behaviour was influenced by cooling river temperatures. A Generalized Linear Mixed Model (GLMM) revealed fish entered the off-channel forebay when river levels were stable and not when they were rising or falling, suggesting hydrological stability was important for the ecological function of this fish community. Two years of impact data (pumps operated) then revealed pump operations severely disrupted the ecological functions of local fish populations, which was also uniquely quantified over two independent 24h periods during which temporal fish counts were reduced by 85%. A trial period where the floodgate was lowered ahead of dawn significantly reduced fish immigration into the hazardous forebay when compared to two different hydrological periods. Modifying when the floodgate and pumps operate, including lowering the floodgate ahead of fish immigration at dawn, and starting pumps during the night (but not day), are therefore promising non-engineered management options to prevent immigration of fish into the hazardous off-channel pump forebay and to reduce entrainment and mortality risk during pump operation.

Fish size spectra from imaging sonar reveal variation in habitat use across nearshore coastal ecosystems

Structured coastal habitats provide foraging opportunities and refuge from predation for fish species of varying size and function. However, comprehensive assessments of fish communities among ecosystems are challenging because of biases arising across traditional sampling methods that target subsets of the community in different habitats (e.g. traps, seines, trawls, or visual census). Here, we used dual-frequency identification sonar (DIDSON) to examine shallow, nearshore habitat use by fishes in multiple structured habitats (seagrass, coral reefs, oyster reefs, rocky reefs, mangroves, woody debris, and docks) relative to soft-sediment habitat across 4 study locations ranging from tropical to temperate: Bocas del Toro, Panama, and Florida, Maryland, and California, USA. We then examined the distribution of individual fish sizes using size-spectra analysis. For temperate docks (Maryland) and eelgrass beds (California), size-spectra slopes were less steep than for soft-sediment habitats, indicating that larger fish associated with these structured habitats. No differences in slopes were identified for (sub)tropical Florida or Panama, although spectra intercepts from docks were higher in each location relative to soft sediment, denoting higher total abundance. Our results suggest geographically stratified habitat use with a tendency towards comparatively greater importance of structure in determining fish size distribution at higher latitudes, and greater importance of structured habitat in governing total abundance at lower latitudes. This study also demonstrates the potential of imaging sonar as a new tool for revealing variation in fish communities among habitats at local to continental scales.

Acoustic Imaging Observes Predator–Prey Interactions between Bull Trout and Migrating Sockeye Salmon Smolts

AbstractAnnual migrations by juvenile Pacific salmon Oncorhynchus spp. smolts are predictable, presenting opportunities for predators to exploit these seasonal prey pulses. Directly observing predator–prey interactions to understand factors affecting predation may be possible via dual‐frequency identification sonar (DIDSON) acoustic imaging. Within Chilko Lake, British Columbia, prior telemetry and stomach content analyses suggested that the out‐migration of Sockeye Salmon Oncorhynchus nerka smolts influences the movements and aggregations of Bull Trout Salvelinus confluentus that feed extensively on smolts during their out‐migration. Bull Trout captured at a government‐installed counting fence exhibited high consumption of smolts, but it is only assumed that feeding occurred directly at the fence. We used DIDSON to assess fine‐scale predator–prey interactions between Sockeye Salmon smolts and Bull Trout over 10 d during the 2016 smolt out‐migration. We found that smolt–Bull Trout interactions were correlated with smolt densities at the counting fence, consistent with the prior diet studies in the system. Predator–prey interactions were also coupled with nocturnal migratory behaviors of Sockeye Salmon smolts, presumably to minimize predation risk. These results demonstrate that DIDSON technology can record interactions between predators and migrating prey at a resolution that can identify variability in space and time and provide insight on the role of anthropogenic structures (e.g., counting fences) in mediating such interactions.

Out of the shadows: automatic fish detection from acoustic cameras

AbstractEfficacious monitoring of fish stocks is critical for efficient management. Multibeam acoustic cameras, that use sound-reflectance to generate moving pictures, provide an important alternative to traditional video-based methods that are inoperable in turbid waters. However, acoustic cameras, like standard video monitoring methods, produce large volumes of imagery from which it is time consuming and costly to extract data manually. Deep learning, a form of machine learning, can be used to automate the processing and analysis of acoustic data. We used convolutional neural networks (CNNs) to detect and count fish in a publicly available dual-frequency identification sonar (DIDSON) dataset. We compared three types of detections, direct acoustic, acoustic shadows, and a combination of direct and shadows. The deep learning model was highly reliable at detecting fish to obtain abundance data using acoustic data. Model accuracy for counts-per-image was improved by the inclusion of shadows (F1 scores, a measure of the model accuracy: direct 0.79, shadow 0.88, combined 0.90). Model accuracy for MaxN per video was high for all three types of detections (F1 scores: direct 0.90, shadow 0.90, combined 0.91). Our results demonstrate that CNNs are a powerful tool for automating underwater acoustic data analysis. Given this promise, we suggest broadening the scope of testing to include a wider range of fish shapes, sizes, and abundances, with a view to automating species (or ‘morphospecies’) identification and counts.

Combining fixed-location count data and movement data to estimate abundance of a lake sturgeon spawning run: a framework for riverine migratory species

Estimating abundance of migrating fishes is challenging. While sonars can be deployed continuously, improper assumptions about unidirectional migration and complete spatial coverage can lead to inaccurate estimates. To address these challenges, we present a framework for combining fixed-location count data from a dual-frequency identification sonar (DIDSON) with movement data from acoustic telemetry to estimate spawning run abundance of lake sturgeon (Acipenser fulvescens). Acoustic telemetry data were used to estimate the probability of observing a lake sturgeon on the DIDSON and to determine the probability that a lake sturgeon passing the DIDSON site had passed the site previously during the season. Combining probabilities with DIDSON counts, using a Bayesian integrated model, we estimated the following abundances: 99 (42–215 credible interval, CI) in 2017, 131 (82–248 CI) in 2018, and 92 (47–184 CI) in 2019. Adding movement data generated better inferences on count data by incorporating fish behavior (e.g., multiple migrations in a single season) and its uncertainty into abundance estimates. This framework can be applied to count and movement data to estimate abundance of spawning runs of other migratory fishes in riverine systems.

Evaluation of three methods for manually counting fish in dam turbines using DIDSON

Mortality of fish entering the turbine draft tube (DT) from the tailrace is common during turbine startup or dewatering in Brazilian hydropower dams. Mortality can be reduced if such operations occur when few fish are present in the DT, but estimating abundance therein using traditional gears (e.g., cast net, gillnet, hook-and-line) is constrained by flow and access. We deployed a Dual frequency IDentification SONar (DIDSON) to record and count fish in the DT for the first time using an innovative approach. Methods used elsewhere for manual counting fish in DIDSON images generated dissimilar results. Therefore, we compared three methods of counting fish manually in the frames of DIDSON software from two Brazilian dams: numerical counting (number of fish in the frame), qualitative counting (percent of the frame occupied by fish), and intersection counting (number of intersections of the grid frame with fish). We assumed that the numerical counting provided the best estimates of the true value but could not be used in 32.2% of the frames from one of the dams due to the presence of uncountable aggregation of fish, bubble curtain, or poor contrast between fish and the DT floor. Qualitative counting was the most congruent, whereas intersection counting was the least, based on comparisons with numerical counting.

Optimising the Workflow for Fish Detection in DIDSON (Dual-Frequency IDentification SONar) Data with the Use of Optical Flow and a Genetic Algorithm

DIDSON acoustic cameras provide a way to collect temporally dense, high-resolution imaging data, similar to videos. Detection of fish targets on those videos takes place in a manual or semi-automated manner, typically assisted by specialised software. Exploiting the visual nature of the recordings, tools and techniques from the field of computer vision can be applied in order to facilitate the relatively involved workflows. Furthermore, machine learning techniques can be used to minimise user intervention and optimise for specific detection and tracking scenarios. This study explored the feasibility of combining optical flow with a genetic algorithm, with the aim of automating motion detection and optimising target-to-background segmentation (masking) under custom criteria, expressed in terms of the result. A 1000-frame video sequence sample with sparse, smoothly moving targets, reconstructed from a 125 s DIDSON recording, was analysed under two distinct scenarios, and an elementary detection method was used to assess and compare the resulting foreground (target) masks. The results indicate a high sensitivity to motion, as well as to the visual characteristics of targets, with the resulting foreground masks generally capturing fish targets on the majority of frames, potentially with small gaps of undetected targets, lasting for no more than a few frames. Despite the high computational overhead, implementation refinements could increase computational feasibility, while an extension of the algorithms, in order to include the steps of target detection and tracking, could further improve automation and potentially provide an efficient tool for the automated preliminary assessment of voluminous DIDSON data recordings.

Environmental factors influencing annual sucker (Catostomus sp.) migration into a Great Lakes tributary

Fish migration in rivers is a growing area of concern as mounting anthropogenic influences, particularly fragmentation from dams and barriers, constitute major threats to global river species diversity. Barriers can impede the movement of fishes between areas critical to the completion of their lifecycle, affecting both population and ecosystem viability. In response, fish passage solutions have been identified as a critical need to maintain fisheries viability in the Laurentian Great Lakes, and around the world. Pivotal to the success of these fish passage solutions is a more complete understanding of the movement phenology and environmental cues that instigate migration. We used a dual-frequency identification sonar (DIDSON) to evaluate environmental triggers of river entry during spring and summer for three size classes of migratory fishes in the Boardman River, a Lake Michigan tributary. Our results indicate that medium size fish (>30 cm and < 50 cm), primarily composed of white sucker Catostomus commersonii and longnose sucker Catostomus catostomus were 21% more likely to enter the river at sunset and 25% less likely at midnight in comparison to midday. Entry rates of medium fish increased 6% for every 1 °C increase in river temperature, 4% for every 1 m3/s increase in river discharge from the day prior, and were reduced by 1% for every 10 cm increase in lake level. Understanding these processes in the tributaries of the Great Lakes is important to inform the fish passage solutions currently being developed for the Boardman River, and to inform management regulations for Great Lakes migratory fishes.

Acoustic camera and net surveys reveal that nursery enhancement at living shorelines may be restricted to the marsh platform

Rapid human development in coastal areas is introducing significant amounts of novel habitat and leading to widespread habitat simplification. To predict how species will respond to these changes, it is important to understand how organisms interact with novel habitats versus naturally existing habitats. In this study, we used traditional fish sampling gear (fyke nets and minnow traps) and a Dual-Frequency Identification Sonar (DIDSON) to conduct fish surveys along natural and modified estuarine shorelines in North Carolina, USA. The overall objective of our study was to investigate how fish abundance and other community metrics change as a function of shoreline type (natural marsh, living shoreline, or bulkhead), sampling location (marsh platform or the shallow subtidal area offshore of the structure), and time of day (day or night). Using fyke nets, we caught significantly more fish and recorded higher species richness on the marsh platform at living shorelines versus natural marsh shorelines. However, we found no significant differences in fish abundance in the shallow unvegetated habitats seaward of the different shoreline types, which may have been affected by low sampling efficiency and replication when sampled using minnow traps and the DIDSON. Our findings, in conjunction with similar studies, may reflect a localized shoreline effect where the nursery enhancement observed at living shoreline sites is restricted to the living component of the shoreline (i.e., the marsh). Additionally, the preliminary results from our limited daytime versus nighttime DIDSON sampling show no significant differences in fish detections. This contrasts with many previous studies using traditional fish sampling techniques that report substantially higher fish catches at night. This unexpected finding is worthy of additional research as it may suggest that traditional fish sampling techniques are underestimating fish abundances during the day, perhaps due to visual gear avoidance. Ultimately, a careful consideration of the social and ecological goals of any shoreline stabilization project is needed before choosing a final design; however, maximizing habitat restoration and limiting the use of artificial materials is likely to confer the greatest ecological benefit.

Acoustic characterization of juvenile Pacific salmon distributions along an eco-engineered seawall

A mobile dual-frequency identification sonar (DIDSON) was used to characterize juvenile Pacific salmon (Oncorhynchus spp.) daytime use of armored and eco-engineered seawall habitats along an urbanized shoreline in Puget Sound, Washington, USA. Eco-engineering included intertidal benches to elevate the seafloor, a textured seawall to provide refuge and encourage invertebrate colonization, and glass blocks in an overhanging sidewalk to increase ambient light. A DIDSON multibeam sonar gave salmon counts twice that of visual surveys, and was thus deemed effective as a mobile sampling tool for small fish (~40-90 mm) and can be advantageous relative to visual methods depending on research goals, habitats, and ambient light levels. Increased salmon presence in the eco-engineered intertidal corridor relative to traditional seawall and pier habitats showed that the combination of increased light, reduced infrastructure (e.g. pier pilings), increased texture, and a shallower seafloor improves habitat function for juvenile salmon. High densities of juvenile salmon along pier ends show that salmon also use alternative migration pathways, with unknown energetic costs and predations risks.

Assessment of silver eel (Anguilla anguilla) route selection at a water-regulating weir using an acoustic camera

Riverine dams and weirs present silver eels with multiple migration routes during their downstream migrations. In relation to dams, understanding route selection is important for estimating silver eel escapement, especially where mortality rates vary among routes. On the lower River Shannon, Ireland, a water-regulating weir presents silver eels with two potential migration routes, the natural river channel and a headrace canal leading to a hydropower station. Route selection at the weir was investigated using a dual-frequency identification sonar (DIDSON) and replicated mark–recapture experiments. The proportion of eels migrating via the headrace canal was strongly related to the proportion of total flow diverted to that route (R2=0.827, P&amp;lt;0.001), suggesting that eel route selection was passive. The active swimming speeds of eels (median=0.16m s−1), observed with the acoustic camera, did not greatly exceed water velocity and further suggested that eels were largely carried by the current. Knowledge of the relationship among flow, water velocity and eel route selection highlighted the potential to strategically alter hydropower-generating protocols to maximise silver eel passage via safer routes, and enhance survival.

Improved Fish Counting Method Accurately Quantifies High‐Density Fish Movement in Dual‐Frequency Identification Sonar Data Files from a Coastal Wetland Environment

AbstractThere are many ways to quantify fish movement through shallow‐water habitats, but most noninvasive methods (e.g., visual counts) are not effective in turbid coastal wetland waters of the Great Lakes. Dual‐frequency identification sonar (DIDSON) technology (Sound Metrics) offers a noninvasive, hydroacoustic‐based approach to characterize fish movement in wetlands and other habitats by collecting highly detailed fish movement data regardless of light and water quality conditions. High‐resolution data can be analyzed to estimate fish movement in areas where visual observations are difficult. However, enumerating a complex mix of fish sizes by manually counting fish visible in echogram files requires training and is very time consuming. Therefore, four counting techniques were tested to estimate fish abundance from DIDSON echograms that were collected at a hydrologically reconnected coastal wetland in the Great Lakes. Briefly, the four counting methods were (1) manually viewing the entire length of the echogram (full‐hour manual count), (2) manually viewing subsections of the echogram before generating fish estimates by per‐minute average (subsample manual count), (3) using Echoview automated software to generate automated estimates, and (4) using DIDSON viewer software to generate automated estimates. Over 800 echogram‐hours were recorded over a 9‐month period at an open‐flow water control structure connecting a coastal wetland to a tributary to Lake Erie. Commercial fish tracking software (Echoview) and custom software scripts from Milne Technologies were used to semi‐automate fish count estimates for a small subset of data. Semi‐automated software counts were compared to manual counts of identical data files to assess differences in accuracy, cost, processing time, and counter effort. Semi‐automated fish count estimates using Echoview and custom pre‐ and postprocessing software scripts did not differ from baseline manual counts, suggesting that the semi‐automated count process could be a reliable tool to increase efficiency when processing large DIDSON data sets.

Upstream migration of fishes downstream of an under-construction hydroelectric dam and implications for the operation of fish passage facilities

Fish behavior measurements are important for river and fishery scientists to protect fish resources and for ecological engineers to guide ecosystem conservation but they can pose a practical challenge. In this study, an acoustic camera was used to observe the migration patterns of fish species downstream of an under-construction hydroelectric dam, the Lianghekou dam in the middle Yalong River, China. The fixed-point method was employed to continuously measure fish migration using a dual-frequency identification sonar (DIDSON) during the spawning periods from April to August. The fish number and length measured by sonar were in fairly good agreement with the results of manual counting and field fishing, respectively. The results showed that the number of fish individuals migrating upstream (NFU) and fish length varied monthly and diurnally, and the NFU measured at dark twilight were 2–3 times greater than those measured during the daytime. The analysis showed that the upstream migratory behavior is dominated by the combined actions of river discharge, water temperature, and time of day. Based on the results, we suggest that the suitable operation time for future fish passage facilities could be when the river discharge ranges from 500 m3/s to 1500 m3/s and the water temperature ranges from 13 °C to 16 °C when the fishes in the study area mostly migrated upstream. The optimal operation time could be at night when the river discharge and water temperature are approximately 1000 m3/s and 15 °C, respectively. Although the indirect evidence of fish migration was recorded at a single location, this study reveals the great potential of acoustic cameras for measuring fish migration behavior downstream from hydropower stations which could be helpful for fish passage studies and fish resource conservation in China.

Behavioural responses of eel (Anguilla anguilla) approaching a large pumping station with trash rack using an acoustic camera (DIDSON)

AbstractEuropean eel, Anguilla anguilla L., migrating to the sea encounter many man‐made structures that can hamper and delay migration or induce mortality. Studying small‐scale behavioural movements in front of these man‐made structures could provide insight in further mitigating adverse effects. The behaviour of eel approaching a trash rack in front of a large pumping station was investigated using a dual‐frequency identification sonar (DIDSON). Eels approaching the trash rack swam through the rack (40.5%) but also showed turning behaviour at (44.7%) or in front of the rack (14.7%). Eels approaching the rack had varying body positions, predominantly head or tail first, but also curled up into a ball or drifted sideways. After turning in front or at the trash rack, eels showed upstream and downwards swimming towards the canal bottom. The results suggest a stepwise response to potential cues, when firstly the body position is changed in such a way that secondly, later on, enhances eventual fast upstream escapement when perceived necessary. Implications for management of these behavioural observations are discussed.

Investigating the Effects of Different LED Wavelengths on Aggregation and Swimming Behavior of Chub Mackerel (Scomber japonicus)

Efficient fish aggregation systems are essential for catching chub mackerel (Scomber japonicus), which is a major target of purse seine fisheries in South Korea. To aid the development of such systems, this study used a Dual frequency IDentification SONar acoustic camera and a visual camera to investigate the effects of light emission diode (LED) aggregation systems of different light wavelengths on the frequency of occurrence and swimming behavior of chub mackerel. The experiment was performed using 50 individuals in a circular tank (diameter, 6.0 m × height, 1.5 m). The LED aggregation systems emitted blue light (454 nm), white light (545 nm + 560 nm), yellow light (596 nm), and red light (634 nm). At night, initial swimming speed increased in response to the four LED systems, and stabilized over time. Frequency of occurrence was highest under blue light, followed by yellow light, white light, and red light, in this order, and, according to wavelength at daytime and at nighttime, it was highest under blue light. The swimming speed of the mackerel school showed an increasing trend over time for all LED aggregation systems, and, for blue light, there was a large, rapid increase in swimming speed.

Manual fish length measurement accuracy for adult river fish using an acoustic camera (DIDSON).

Total lengths (LT ) of 50 free-swimming fish in a tank, silver carp Hypophthalmichthys molitrix and rainbow trout Oncorhynchus mykiss, were measured using a DIDSON (Dual-frequency IDentification SONar) camera. Using Sound Metrics software, multiple measurements of each fish (LT , side aspect angle and distance from the camera) at different times were analysed by two experienced operators while a subset of data was analysed by two inexperienced operators. The main result showed high variability in intra-fish LT measurements. The number of measurements required to minimise errors and to obtain robust fish measurements (true LT ± 3 cm) was estimated by a bootstrap method. Three to five measurements per fish were recommended for fish surveys in rivers. In this experimental study, aiming to reproduce river conditions, no evidence of fish position (side aspect angle and distance from the camera) effect was detected, but an operator effect (partially explained by training) was observed. General linear mixed models also showed that lengths of the smallest fish (LT < 57 cm) were overestimated and lengths of the largest fish (LT > 57 cm) were underestimated in comparison with their true lengths. In conclusion, we highlight that this technology, like any monitoring methods, returns imperfect observations. We advise DIDSON users to ensure that measurements are carried out correctly in order to draw accurate conclusion from this new technology.

Application of Dual-frequency Identification Sonar to detection of visible damages of underwater hydraulic structures

Based on the limitation of the conventional methods to the detection of visible damages underwater to the hydraulic structures, along with the characteristics of the visible damages, we suggest the application of Dual-frequency Identification Sonar technology for its detection. This paper illustrates how Dual-frequency Identification Sonar technology works and puts forward the method of detection. The application of Dual-frequency Identification Sonar technology has been carried out in engineering practice and the result indicates that the technology performs well in the detection of visible damages underwater to the hydraulic structures.

Bioacoustic application on fisheries management in an artificial reefs’ ecological reserve of Bohai Gulf China

Various techniques have been used in marine fishery resources assessment. Among those, acoustic techniques have high efficiency and wide adaptability, and are environment friendly. Therefore, acoustic techniques played a key/indispensable role in the field of ecosystem-based fishery management. Acoustic surveys were conducted during the wet (May) and dry (November) seasons in 2016 in the artificial reefs ecological reserve of Bohai Gulf and a nearby control region to understand the current situation of fishery resources and explore the effectiveness of underwater artificial constructions by a dual-frequency identification sonar (DIDSON) and a scientific split-beam echosounder (120 KHz, Simrad EY60). Fish densities in various seasons and regions showed significant differences and interaction, with a maximum value of 358020.34 ind/n.mile2 in the artificial reefs’ region and a minimum value of 71898.35 ind/n.mile2 in the control region during the wet season. Fish densities in defined parallel transects revealed a roughly southward migration trend of small-size individuals from wet season to dry season. Single echo detections in the artificial reefs region demonstrated a wider target strength (TS) range (− 60 ~ − 30 dB vs − 60 ~ − 51 dB) and higher mean TS values (− 55.87 dB vs − 58.31 dB) than the control region both in the wet and dry seasons, which indicated a more complicated and stable fish community structure in the artificial reefs area. The vertical distribution of single echo detections tracked by the echoview post-processing system showed an apparent downward gathering effect. A positive correlation between TS and water depth was discovered from Pearson correlation analysis in the artificial reefs region during the dry season.

An underwater observation dataset for fish classification and fishery assessment

Using Dual-Frequency Identification Sonar (DIDSON), fishery acoustic observation data was collected from the Ocqueoc River, a tributary of Lake Huron in northern Michigan, USA. Data were collected March through July 2013 and 2016 and included the identification, via technology or expert analysis, of eight fish species as they passed through the DIDSON’s field of view. A set of short DIDSON clips containing identified fish was curated. Additionally, two other datasets were created that include visualizations of the acoustic data and longer DIDSON clips. These datasets could complement future research characterizing the abundance and behavior of valued fishes such as walleye (Sander vitreus) or white sucker (Catostomus commersonii) or invasive fishes such as sea lamprey (Petromyzon marinus) or European carp (Cyprinus carpio). Given the abundance of DIDSON data and the fact that a portion of it is labeled, these data could aid in the creation of machine learning tools from DIDSON data, particularly for invasive sea lamprey which are amply represented and a destructive invader of the Laurentian Great Lakes.