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We describe the application of two types of stereo camera systems in fisheries research, including the design, calibration, analysis techniques, and precision of the data obtained with these systems. The first is a stereo video system deployed by using a quick-responding winch with a live feed to provide species- and size composition data adequate...
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... addition to length measurements, the three-di- mensional coordinates extracted from the still-frame images provided data on the position and orientation of walleye Pollock in relation to the trawl (Fig. 5). These data were used to determine distances of pollock targets to trawl components for position of fish and to calculate tilt and yaw for orientation of ...
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... yaw angles were easily calculated by using the same points in im- ages (head and tail) derived for fish lengths (Fig. 10). To calculate the position of fish within the trawl addi- tional corresponding points along the trawl panel were identified and their three-dimensional coordinates were determined by the triangulation process outlined above (Fig. ...
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Biomass estimates of several species of Alaskan rockfishes exhibit large interannual variations. Because rockf ishes are long lived and relatively slow growing, large, short-term shifts in population abundance are not likely. We attribute the variations in biomass estimates to the high variability in the spatial distribution of rockf ishes that is...
Citations
... The underwater stereo video was also used to determine population counts and spatial and temporal frequencies, incorporating detection and identification [34]. Stereo vision is also integrated for video-based tracking [35], fish volume monitoring [36] or abundance [37], and 3D tracking of free-swimming fish [38]. ...
Monitoring the status of culture fish is an essential task for precision aquaculture using a smart underwater imaging device as a non-intrusive way of sensing to monitor freely swimming fish even in turbid or low-ambient-light waters. This paper developed a two-mode underwater surveillance camera system consisting of a sonar imaging device and a stereo camera. The sonar imaging device has two cloud-based Artificial Intelligence (AI) functions that estimate the quantity and the distribution of the length and weight of fish in a crowded fish school. Because sonar images can be noisy and fish instances of an overcrowded fish school are often overlapped, machine learning technologies, such as Mask R-CNN, Gaussian mixture models, convolutional neural networks, and semantic segmentation networks were employed to address the difficulty in the analysis of fish in sonar images. Furthermore, the sonar and stereo RGB images were aligned in the 3D space, offering an additional AI function for fish annotation based on RGB images. The proposed two-mode surveillance camera was tested to collect data from aquaculture tanks and off-shore net cages using a cloud-based AIoT system. The accuracy of the proposed AI functions based on human-annotated fish metric data sets were tested to verify the feasibility and suitability of the smart camera for the estimation of remote underwater fish metrics.
... More recently, there has been a greater emphasis on applying optical approaches. Underwater observations have had a wide application in fisheries to monitor the fishing gear and fish behavior during the capture process (DeCelles et al., 2017;Graham et al., 2004;Kilpatrick et al., 2011;Rosen and Holst, 2013;Williams et al., 2010) and during the past few years, there have been many developments in the application of computer vision to the analysis of underwater images and to the size and species recognition of fish (Álvarez-Ellacuría et al., 2020;Ditria et al., 2020;Garcia et al., 2020;Yu et al., 2020). ...
Catch monitoring during demersal trawling is important to help fishers around the globe to cope with high bycatches. Information about catch composition during towing will allow fishers to identify and react to the presence of unwanted catch and undertake actions to avoid them during trawling. In demersal trawl fisheries, catch monitoring by the optical devices is typically challenged by the poor quality of underwater observations due to sediment mobilized during the towing process. In this study we develop, test and quantify the effect of a demersal trawl modification including sediment suppressing sheet and an in-trawl image acquisition system for catch monitoring during bottom trawling. The system is demonstrated on low-headline trawls that are typically used in mixed Nephrops-directed fisheries. We show that fitting a sediment suppressing sheet in the front part of the gear reduces the amount of mobilized sediment by half at three test positions inside the gear. When this sheet is used in combination with an in-trawl image acquisition system placed in the aft part of the trawl it is possible to obtain clear images of the catch during demersal trawling on the soft muddy grounds.
... For example, Optical probes such as the Underwater Vision Profiler (Picheral et al., 2010), the Laser-Optical Plankton Counter (Basedow et al., 2013;Herman & Harvey, 2006), the Video Plankton Recorder (Sainmont et al., 2014), and the Light frame On-sight Key species Investigation system (Schmid et al., 2016;Schulz et al., 2010) all use light sources and optical sensors to assess the vertical distribution and abundance of zooplankton. Researchers and the industry alike increasingly use high-definition (HD) video cameras or stereo-cameras mounted on trawls to document the catchability of different species or size classes of fish (Boldt et al., 2018;Underwood et al., 2020;Williams et al., 2010). Such camera systems, when used in dim environments, rely on external light sources to distinguish, and identify marine animals at depth. ...
The globally widespread adoption of Artificial Light at Night (ALAN) began in the mid‐20th century. Yet, it is only in the last decade that a renewed research focus has emerged into its impacts on ecological and biological processes in the marine environment that are guided by natural intensities, moon phase, natural light and dark cycles and daily light spectra alterations. The field has diversified rapidly from one restricted to impacts on a handful of vertebrates, to one in which impacts have been quantified across a broad array of marine and coastal habitats and species. Here we review the current understanding of ALAN impacts in diverse marine ecosystems. The review presents the current state of knowledge across key marine and coastal ecosystems (sandy and rocky shores, coral reefs and pelagic) and taxa (birds and sea turtles), introducing how ALAN can mask seabirds and sea turtles navigation, cause changes in animals predation patterns and failure of coral spawning synchronization, as well as inhibition of zooplankton Diel Vertical Migration. Mitigation measures are recommended, however, while strategies for mitigation were easily identified, barriers to implementation are poorly understood. Finally, we point out knowledge gaps that if addressed would aid in the prediction and mitigation of ALAN impacts in the marine realm.
... Care must be taken when interpreting habitat distribution models generated from these data as the results may reflect changes in sampling effort or survey design rather than the distribution of the stock . Much of the data for the juvenile through adult stages were from bottom trawl surveys that do not adequately sample untrawlable habitat (Williams et al., 2010;Rooper et al., 2012). Habitat distribution models based on these observations may be biased for some species such as rockfish that utilize untrawlable grounds . ...
Over the past two decades, numerous ecosystem surveys and process studies have emerged to monitor and assess the large marine ecosystems of Alaska. Several regional collaborative integrated ecosystem research projects (IERPs) were conducted to gain understanding of fish population fluctuations in relation to the surrounding environment. The Gulf of Alaska (GOA) IERP is one example of such an effort. Products of this program include a suite of in situ observations from fully integrated ecosystem surveys, laboratory experiments of physical thresholds for fish condition, and high-resolution oceanographic, planktonic, and habitat distribution models. When coupled, the synthesis products of this program can be utilized to understand system connectivity and highlight the primary ecosystem drivers of the GOA. Much of this information was included in annual GOA ecosystem status reports through individual indicator contributions. However, assimilation of these data into single-species stock assessments has remained limited. We provide a clear and direct avenue for including the products of these IERPs through the new ecosystem and socioeconomic profile (ESP) framework that identifies mechanistic relationships and tests ecosystem linkages within the stock assessment process. We present a case study using a data synthesis of the five commercially and ecologically valuable focal species of the GOAIERP (sablefish, pollock, Pacific cod, arrowtooth flounder, and Pacific ocean perch). Information was organized along the categories of distribution, phenology, and condition by life history stage to develop life history narratives for each species. These narratives identified critical ecosystem processes that could impact survival of each species. We then used habitat distribution models, seasonal phenology, and energy allocation strategies to sequentially reduce two gridded temperature datasets to reflect the life experience of the stock. This method essentially aligns ecosystem information at a spatial and temporal scale relevant to a stock and creates informed indicators that could then be related to a stock assessment parameter of interest, such as recruitment. Informed temperature indicators differed in magnitude and variability when compared to non-informed indicators and demonstrating species and stage-specific thermal preferences. The difference between the informed indicators and the non-informed indicators can also highlight thresholds and trends in habitat preference that could be further investigated with targeted process studies or laboratory experiments. The coordinated nature of the IERP allowed for the creation of these informed indicators that would not be possible with the results of any one process study. Both the stock-specific narratives and the informed indicators can be included into the ESPs for further monitoring and development. This integration ensures that the identified ecosystem linkages are evaluated concurrently with the stock assessment and ultimately transferred to fishery managers in an efficient and effective format for informing management decisions.
... Bottom trawls are currently the most commonly used fishery independent survey tool for groundfish (Gunderson, 1993); however, research continues to demonstrate that trawls may not be effective in rugose habitats, which may significantly impact the survey data products as well as the tool being a relatively destructive way to sample (Zimmermann, 2003;Pirtle et al., 2015). Alternatively, other methodologies and technologies are being considered to survey "untrawlable habitats" (Tolimieri et al., 2008;Williams et al., 2010). Technologies, such as hydroacoustic and underwater video, are being examined as potentially more efficient and cost-effective than traditional survey methods. ...
New survey technologies are needed to survey untrawlable habitats in a cost-effective and nonlethal manner with minimal impacts on habitat and nontarget species. Here, we test the efficacy of integrating data from a suspended underwater camera with acoustic data to generate population estimates for nearshore Black (Sebastes melanops), Blue (Sebastes mystinus), and Deacon Rockfish (Sebastes diaconus). We surveyed Seal Rock Reef near Newport, Oregon, and compared our results to population estimates derived from a mark–recapture study conducted at the same reef. We compared fish density estimates from video deployments to those calculated from applying published target strength to length regression models to our acoustics data. Densities derived from the acoustics, using a generalized physoclist target strength to length model, were significantly different from densities derived from video; conversely, a rockfish-specific target strength to length model generated densities that were not statistically different from video densities. To assess whether, and how, fish behaviour was influenced by the presence of an underwater camera, we deployed our camera under the acoustic transducer. No statistical difference was observed in the acoustic density of fish before, during, or after camera deployment. Our work suggests that combining acoustic and stereo video data provided a similar population estimate to historic survey results, but an accurate acoustic density estimate was dependent on using the proper acoustic target–strength model. We contend that combining camera data with hydroacoustic data is effective for surveying rockfish in untrawlable habitats.
... Trawl sampling is also an important part of acoustic-trawl surveys, where the species composition of the trawl catches provide information for assigning the acoustic backscatter to taxa, the length distribution of individual fish for conversion of acoustic energy into fish abundance or biomass, and information about age composition (Simmonds and MacLennan, 2005). Recent work has shown that a trawl equipped with underwater cameras can provide much of the same information without the need to capture fish (Williams et al., 2010;Rosen and Holst, 2013). While species and sizes can be resolved from images, some information, like determining age and diet, still depends on physical sampling. ...
Fish counts and species information can be obtained from images taken within trawls, which enables trawl surveys to operate without extracting fish from their habitat, yields distribution data at fine scale for better interpretation of acoustic results, and can detect fish that are not retained in the catch due to mesh selection. To automate the process of image-based fish detection and identification, we trained a deep learning algorithm (RetinaNet) on images collected from the trawl-mounted Deep Vision camera system. In this study, we focused on the detection of blue whiting, Atlantic herring, Atlantic mackerel, and mesopelagic fishes from images collected in the Norwegian sea. To address the need for large amounts of annotated data to train these models, we used a combination of real and synthetic images, and obtained a mean average precision of 0.845 on a test set of 918 images. Regression models were used to compare predicted fish counts, which were derived from RetinaNet classification of fish in the individual image frames, with catch data collected at 20 trawl stations. We have automatically detected and counted fish from individual images, related these counts to the trawl catches, and discussed how to use this in regular trawl surveys.
... Prior to deployment, the cameras were calibrated following methods described in Williams et al. (2010), using the Matlab Camera Calibration Toolbox (Bouguet, 2014). The calibration procedure corrected for distortion of the images due to the lens and viewport optics, as well as solving for the epipolar geometry between the two cameras. ...
... Underwater stereo-cameras provide an efficient and alternative method to observe and measure fish in areas that are difficult to sample Williams et al., 2010) and have increasingly been used to sample pelagic fish populations (Boldt et al., 2018). Stereo-camera images enabled quantified calculations on PSL that were observed in situ. ...
... Our results support past evidence (Williams et al., 2010) that stereo-based optical sampling is a viable method for augmenting alternate forms of abundance estimations. Stereo-cameras allow quantitative surveys of abundance and can also be used to observe and quantify the behavior of fish. ...
Forage fish and fish associated with particular benthic habitats (e.g., rockfishes, sand eels, sand lances) may be particularly difficult to assess through standard survey methodologies. Stereo-cameras, video, and automated visual data may serve as useful complementary tools to provide insight into the dynamics of these species. Visual methods may be used not only to estimate abundance and distribution, but also to inform important biological metrics and life history attributes. We explored the application of these methods to assess Pacific sand lance (Ammodytes personatus), a forage fish associated with benthic sediments, using a combination of directed observations from a manned submersible and quantitative analysis of fixed image footage obtained with a stereo-camera. This research provides a better understanding of how in situ observations and automated image analysis might complement other methods to estimate fish abundance, distribution, habitat, and behavior. Visual data were compared to data collected via directed sampling using physical extraction methods at the same site in the same year. Submersible observations provided new insights on the physical conditions and habitat. Visual observations confirmed wavefield morphologies previously identified through multibeam acoustic imagery and measured attributes relevant to the physical oceanography of the water column above this benthic habitat feature. Visual observations also informed understanding of light penetration, relevant to diurnal cues for seasonal progression and diel vertical migration and foraging. Submersible observations provided insights into abundance, schooling dynamics, and behavioral attributes, including avoidance in response to physical disturbance and aggregation in presence of artificial light. Quantitative analysis of stereo-camera data in center-edge and north-south transects determined that fish abundance and length distribution was relatively uniform throughout this particular benthic habitat. Estimates of measurement error associated with stereo-cameras were calculated and correction factors identified. Mean lengths estimated in visual data and in physical specimens were closely matched, though variance in visual data measurements was far greater. This error was reduced when filtering data on the basis of orthogonal position or incidence angle relative to the camera. Our research provides important insights to the presence, distribution, abundance, and movement of Pacific sand lance within benthic sand wavefield habitats. Our research also provides insight to the applications, opportunities, and constraints to observation-based sampling methods, including the use of manned submersibles and automated stereo-cameras.
... However, precise determination of fish length was not possible here using only one camera. Further studies with video observation of fish interacting with selective devices will require the development of a stereovision system to accurately quantify fish length, position and orientation [56]. ...
Knowledge about fish behavior is crucial to be able to influence the capture process and catch species composition. The rapid expansion of the use of underwater cameras has facilitated unprecedented opportunities for studying the behavior of species interacting with fishing gears in their natural environment. This technological advance would greatly benefit from the parallel development of dedicated methodologies accounting for right-censored observations and variable observation periods between individuals related to instrumental, environmental and behavioral events. In this paper we proposed a methodological framework, based on a parametric Weibull mixture model, to describe the process of escapement attempts through time, test effects of covariates and estimate the probability that a fish will attempt to escape. We additionally proposed to better examine the escapement process at the individual level with regard to the temporal dynamics of escapement over time. Our approach was used to analyze gadoids swimming and escapement behaviors collected using a video set up in front of a selective device known to improve selectivity on gadoids in the extension of a bottom trawl. Comparison of the fit of models indicates that i) the instantaneous rate of escape attempts is constant over time and that the escapement process can be modelled using an exponential law; ii) the mean time before attempting to escape increases with the increasing number of attempts; iii) more than 80% of the gadoids attempted to escape through the selective device; and iv) the estimated probability of success was around 15%. Effects of covariates on the probability of success were investigated using binomial regression but none of them were significant. The data set collected is insufficient to make general statements, and further observations are required to properly investigate the effect of intrinsic and extrinsic factors governing gadoids behavior in trawls. This methodology could be used to better characterize the underlying behavioral process of fish in other parts of a bottom trawl or in relation to other fishing gears.
... Although we are not aware of previous stereo video camera applications on existing observatories, they have been widely used in fisheries and ecological applications, including deep-sea applications (e.g. Harvey & Shortis 1998, Shortis et al. 2008, Williams et al. 2010, 2018, Bonin et al. 2011, Merritt et al. 2011, Shortis & Abdo 2016. It is important that these devices not be under user control, because they must provide the maximum stability of views over time (i.e. ...
Four operational factors, together with high development cost, currently limit the use of ocean observatories in ecological and fisheries applications: 1) limited spatial coverage, 2) limited integration of multiple types of technologies, 3) limitations in the experimental design for in situ studies, and 4) potential unpredicted bias in monitoring outcomes due to the infrastructure's presence and functioning footprint. To address these limitations, we propose a novel concept of a standardised 'ecosystem observatory module' structure composed of a central node and three tethered satellite pods together with permanent mobile platforms. The module would be designed with a rigid spatial configuration to optimise overlap among multiple observation technologies, each providing 360° coverage of a cylindrical or hemi-spherical volume around the module, including permanent stereo video cameras, acoustic imaging sonar cameras, horizontal multibeam echosounders, and a passive acoustic array. The incorporation of multiple integrated observation technologies would enable unprecedented quantification of macrofaunal composition, abundance, and density surrounding the module, as well as the ability to track the movements of individual fishes and macroinvertebrates. Such a standardised modular design would allow for the hierarchical spatial connection of observatory modules into local module clusters and larger geographic module networks providing synoptic data within and across linked ecosystems suitable for fisheries and ecosystem-level monitoring on multiple scales.
... A validation study was conducted in 2014 using an underwater stereo camera system (Williams et al., 2010). The stereo camera system is highly desirable for region-wide surveys because it can generate large sample sizes (8-10 deployments per day at depths of up to 800 m are routinely achievable) potentially across a large region, where each deployment can sample ∼1,100 m 2 during a 15-min transect. ...
Resource managers in the United States and worldwide are tasked with identifying and mitigating trade-offs between human activities in the deep sea (e.g., fishing, energy development, and mining) and their impacts on habitat-forming invertebrates, including deep-sea corals, and sponges (DSCS). Related management decisions require information about where DSCS occur and in what densities. Species distribution modeling (SDM) provides a cost-effective means of identifying potential DSCS habitat over large areas to inform these management decisions and data collection. Here we describe good practices for DSCS SDM, especially in the context of data collection and management applications. Managers typically need information regarding DSCS encounter probabilities, densities, and sizes, defined at sub-regional to basin-wide scales and validated using subsequent, targeted data collections. To realistically achieve these goals, analysts should integrate available data sources in SDMs including fine-scale visual sampling and broad-scale resource surveys (e.g., fisheries trawl surveys), include environmental predictor variables representing multiple spatial scales, model residual spatial autocorrelation, and quantify prediction uncertainty. When possible, models fitted to presence-absence and density data are preferred over models fitted only to presence data, which are difficult to validate and can confound estimated probability of occurrence or density with sampling effort. Ensembles of models can provide robust predictions, while multi-species models leverage information across taxa, and facilitate community inference. To facilitate the use of models by managers, predictions should be expressed in units that are widely understood and validated at an appropriate spatial scale using a sampling design that provides strong statistical inference. We present three case studies for the Pacific Ocean that illustrate good practices with respect to data collection, modeling, and validation; these case studies demonstrate it is possible to implement our good practices in real-world settings.
