PelagiCam: a novel underwater imaging system with computer vision for semi-automated monitoring of mobile marine fauna at offshore structures

Environmental monitoring tools and strategies in salmon net-pen aquaculture

As global salmon production accelerates in response to higher consumer demand for seafood, so does the need for sophisticated monitoring strategies to enable and maintain ethically sound, productive, and environmentally friendly production of fish. Innovative technologies are needed to ensure proper water quality, react to unfavorable hydrodynamic conditions, monitor for changes in fish health, and minimize ecological interactions with indigenous aquatic life, including fish escapes. Automated sensors connected wirelessly to data stations, visualization aids, and acoustic and physical tagging technologies are emerging tools capable of detecting environmental stress and its associated behavioral changes in farmed fish. Computer modeling of the monitoring data collected from a single salmon farm or collection of farms sharing a data network can be used to spot environmental trends vital for anticipating some of the consequences of climate change. Environmental regulations governing salmon farming in coastal areas are becoming more stringent in response to public pressures to protect coastal and ocean resources and to provide for multipurpose use of marine resources. As net-pen salmon aquaculture expands globally, new technologies will be essential to collect and interpret the anticipated larger volumes of data needed to meet these stringent regulatory requirements and to safeguard the high investment costs inherent in salmon farming. Integr Environ Assess Manag 2022;18:950-963. © SETAC.

Use of a 360-Degree Underwater Camera to Characterize Artificial Reef and Fish Aggregating Effects around Marine Energy Devices

Marine energy devices must be attached to the seafloor by their foundations, pilings, or anchors, and will have other parts in the water column like the devices themselves, mooring lines, and power export cables running along the seafloor. The installation and presence of these artificial structures will create physical changes that can disrupt or create new habitats, and potentially alter the behavior of mobile organisms such as fish around a device by attracting them to these new artificial reefs and fish aggregating devices. In this study, we tested a new approach for monitoring fish activity around a marine energy device anchor: a 360-degree underwater camera to keep the target (a wave energy converter’s anchor) in the field of view of the camera. The camera was deployed in three configurations (hand-held, tripod, video lander) at sites with different hydrodynamics and underwater visibilities. The video lander was the best configuration: very stable, versatile, and easy to handle. The 360-degree field of view enabled observing and counting fishes, which were more abundant at dusk than dawn or noon, around the anchor. Despite remaining challenges, 360-degree cameras are useful tools for monitoring animal interactions with marine energy devices.

A low-cost, long-term underwater camera trap network coupled with deep residual learning image analysis

Understanding long-term trends in marine ecosystems requires accurate and repeatable counts of fishes and other aquatic organisms on spatial and temporal scales that are difficult or impossible to achieve with diver-based surveys. Long-term, spatially distributed cameras, like those used in terrestrial camera trapping, have not been successfully applied in marine systems due to limitations of the aquatic environment. Here, we develop methodology for a system of low-cost, long-term camera traps (Dispersed Environment Aquatic Cameras), deployable over large spatial scales in remote marine environments. We use machine learning to classify the large volume of images collected by the cameras. We present a case study of these combined techniques’ use by addressing fish movement and feeding behavior related to halos, a well-documented benthic pattern in shallow tropical reefscapes. Cameras proved able to function continuously underwater at deployed depths (up to 7 m, with later versions deployed to 40 m) with no maintenance or monitoring for over five months and collected a total of over 100,000 images in time-lapse mode (by 15 minutes) during daylight hours. Our ResNet-50-based deep learning model achieved 92.5% overall accuracy in sorting images with and without fishes, and diver surveys revealed that the camera images accurately represented local fish communities. The cameras and machine learning classification represent the first successful method for broad-scale underwater camera trap deployment, and our case study demonstrates the cameras’ potential for addressing questions of marine animal behavior, distributions, and large-scale spatial patterns.

What’s in My Toolkit? A Review of Technologies for Assessing Changes in Habitats Caused by Marine Energy Development

Marine energy devices are installed in highly dynamic environments and have the potential to affect the benthic and pelagic habitats around them. Regulatory bodies often require baseline characterization and/or post-installation monitoring to determine whether changes in these habitats are being observed. However, a great diversity of technologies is available for surveying and sampling marine habitats, and selecting the most suitable instrument to identify and measure changes in habitats at marine energy sites can become a daunting task. We conducted a thorough review of journal articles, survey reports, and grey literature to extract information about the technologies used, the data collection and processing methods, and the performance and effectiveness of these instruments. We examined documents related to marine energy development, offshore wind farms, oil and gas offshore sites, and other marine industries around the world over the last 20 years. A total of 120 different technologies were identified across six main habitat categories: seafloor, sediment, infauna, epifauna, pelagic, and biofouling. The technologies were organized into 12 broad technology classes: acoustic, corer, dredge, grab, hook and line, net and trawl, plate, remote sensing, scrape samples, trap, visual, and others. Visual was the most common and the most diverse technology class, with applications across all six habitat categories. Technologies and sampling methods that are designed for working efficiently in energetic environments have greater success at marine energy sites. In addition, sampling designs and statistical analyses should be carefully thought through to identify differences in faunal assemblages and spatiotemporal changes in habitats.

Geographical variation in the carbon, nitrogen, and phosphorus content of blue mussels, Mytilus edulis

Shellfish farming contributes to nutrient removal in coastal and estuarine systems, as bivalves incorporate nutrients into their tissues and shells, which is removed from the marine system on harvest. Fourteen locations around the UK were surveyed to explore geographic variation in carbon, nitrogen and phosphorus content of tissue and shell in blue mussels. Phosphorus in tissue had a significant negative relationship with mean annual seawater temperature for both rope and bottom cultured sites. Per tonne of live mussel, rope culture removed significantly more nitrogen (8.50 ± 0.59 kg) and phosphorus (0.95 ± 0.07 kg) than bottom cultured (5.00 ± 0.013 kg nitrogen and 0.43 ± 0.01 kg phosphorus). Bottom culture, however, provides significantly more C removal in shell (60.15 ± 0.77 kg) than in rope cultured (46.12 ± 1.69 kg). Further studies are required to examine the effect of growth rate, on the nitrogen and phosphorus remediation, and carbon stored in shell, of rope culture and bottom cultured mussel aquaculture.

In situ and low-cost monitoring of particles falling from freshwater animals: from microplastics to parasites

A simple and low-cost method of monitoring and collecting particulate matter detaching from (or interacting with) aquatic animals is described using a novel device based on an airlift pump principle applied to floating cages. The efficiency of the technique in particle collection is demonstrated using polyethylene microspheres interacting with a cyprinid fish (Carassius carassius) and a temporarily parasitic stage (glochidia) of an endangered freshwater mussel (Margaritifera margaritifera) dropping from experimentally infested host fish (Salmo trutta). The technique enables the monitoring of temporal dynamics of particle detachment and their continuous collection both in the laboratory and in situ, allowing the experimental animals to be kept under natural water quality regimes and reducing the need for handling and transport. The technique can improve the representativeness of current experimental methods used in the fields of environmental parasitology, animal feeding ecology and microplastic pathway studies in aquatic environments. In particular, it makes it accessible to study the physiological compatibility of glochidia and their hosts, which is an essential but understudied autecological feature in mussel conservation programs worldwide. Field placement of the technique can also aid in outreach programs with pay-offs in the increase of scientific literacy of citizens concerning neglected issues such as the importance of fish hosts for the conservation of freshwater mussels.

Adaptable Monitoring Package Development and Deployment: Lessons Learned for Integrated Instrumentation at Marine Energy Sites

Integrated instrumentation packages are an attractive option for environmental and ecological monitoring at marine energy sites, as they can support a range of sensors in a form factor compact enough for the operational constraints posed by energetic waves and currents. Here we present details of the architecture and performance for one such system—the Adaptable Monitoring Package—which supports active acoustic, passive acoustic, and optical sensing to quantify the physical environment and animal presence at marine energy sites. we describe cabled and autonomous deployments and contrast the relatively limited system capabilities in an autonomous operating mode with more expansive capabilities, including real-time data processing, afforded by shore power or in situ power harvesting from waves. Across these deployments, we describe sensor performance, outcomes for biological target classification algorithms using data from multibeam sonars and optical cameras, and the effectiveness of measures to limit biofouling and corrosion. On the basis of these experiences, we discuss the demonstrated requirements for integrated instrumentation, possible operational concepts for monitoring the environmental and ecological effects of marine energy converters using such systems, and the engineering trade-offs inherent in their development. Overall, we find that integrated instrumentation can provide powerful capabilities for observing rare events, managing the volume of data collected, and mitigating potential bias to marine animal behavior. These capabilities may be as relevant to the broader oceanographic community as they are to the emerging marine energy sector.

The Hierarchic Treatment of Marine Ecological Information from Spatial Networks of Benthic Platforms

Measuring biodiversity simultaneously in different locations, at different temporal scales, and over wide spatial scales is of strategic importance for the improvement of our understanding of the functioning of marine ecosystems and for the conservation of their biodiversity. Monitoring networks of cabled observatories, along with other docked autonomous systems (e.g., Remotely Operated Vehicles [ROVs], Autonomous Underwater Vehicles [AUVs], and crawlers), are being conceived and established at a spatial scale capable of tracking energy fluxes across benthic and pelagic compartments, as well as across geographic ecotones. At the same time, optoacoustic imaging is sustaining an unprecedented expansion in marine ecological monitoring, enabling the acquisition of new biological and environmental data at an appropriate spatiotemporal scale. At this stage, one of the main problems for an effective application of these technologies is the processing, storage, and treatment of the acquired complex ecological information. Here, we provide a conceptual overview on the technological developments in the multiparametric generation, storage, and automated hierarchic treatment of biological and environmental information required to capture the spatiotemporal complexity of a marine ecosystem. In doing so, we present a pipeline of ecological data acquisition and processing in different steps and prone to automation. We also give an example of population biomass, community richness and biodiversity data computation (as indicators for ecosystem functionality) with an Internet Operated Vehicle (a mobile crawler). Finally, we discuss the software requirements for that automated data processing at the level of cyber-infrastructures with sensor calibration and control, data banking, and ingestion into large data portals.