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The United Nations (UN)’s call for a decade of “ecosystem restoration” was prompted by the need to address the extensive impact of anthropogenic activities on natural ecosystems. Marine ecosystem restoration is increasingly necessary due to increasing habitat degredation in deep waters (>200 m depth). At these depths, which are far beyond those accessible by divers, only established and emerging robotic platforms such as remotely operated vehicles (ROVs), autonomous underwater vehicles (AUVs), landers, and crawlers can operate through manipulators and multiparametric sensor arrays (e.g., optoacoustic imaging, omics, and environmental probes). The use of advanced technologies for deep-sea ecosystem restoration can provide: ① high-resolution three-dimensional (3D) imaging and acoustic mapping of substrates and key taxa, ② physical manipulation of substrates and key taxa, ③ real-time supervision of remote operations and long-term ecological monitoring, and ④ the potential to work autonomously. Here, we describe how robotic platforms with in situ manipulation capabilities and payloads of innovative sensors could autonomously conduct active restoration and monitoring across large spatial scales. We expect that these devices will be particularly useful in deep-sea habitats, such as ① reef-building cold-water corals, ② soft-bottom bamboo corals, and ③ soft-bottom fishery resources that have already been damaged by offshore industries (i.e., fishing and oil/gas).

Life on our planet likely evolved in the ocean, and thus exo-oceans are key habitats to search for extraterrestrial life. We conducted a data-driven bibliographic survey on the astrobiology literature to identify emerging research trends with marine science for future synergies in the exploration for extraterrestrial life in exo-oceans. Based on search queries, we identified 2592 published items since 1963. The current literature falls into three major groups of terms focusing on (1) the search for life on Mars, (2) astrobiology within our Solar System with reference to icy moons and their exo-oceans, and (3) astronomical and biological parameters for planetary habitability. We also identified that the most prominent research keywords form three key-groups focusing on (1) using terrestrial environments as proxies for Martian environments, centred on extremophiles and biosignatures, (2) habitable zones outside of “Goldilocks” orbital ranges, centred on ice planets, and (3) the atmosphere, magnetic field, and geology in relation to planets’ habitable conditions, centred on water-based oceans.

Abstract The automatic classification of marine species based on images is a challenging task for which multiple solutions have been increasingly provided in the past two decades. Oceans are complex ecosystems, difficult to access, and often the images obtained are of low quality. In such cases, animal classification becomes tedious. Therefore, it is often necessary to apply enhancement or pre-processing techniques to the images, before applying classification algorithms. In this work, we propose an image enhancement and classification pipeline that allows automated processing of images from benthic moving platforms. Deep-sea (870 m depth) fauna was targeted in footage taken by the crawler “Wally” (an Internet Operated Vehicle), within the Ocean Network Canada (ONC) area of Barkley Canyon (Vancouver, BC; Canada). The image enhancement process consists mainly of a convolutional residual network, capable of generating enhanced images from a set of raw images. The images generated by the trained convolutional residual network obtained high values in metrics for underwater imagery assessment such as UIQM (~ 2.585) and UCIQE (2.406). The highest SSIM and PSNR values were also obtained when compared to the original dataset. The entire process has shown good classification results on an independent test data set, with an accuracy value of 66.44% and an Area Under the ROC Curve (AUROC) value of 82.91%, which were subsequently improved to 79.44% and 88.64% for accuracy and AUROC respectively. These results obtained with the enhanced images are quite promising and superior to those obtained with the non-enhanced datasets, paving the strategy for the on-board real-time processing of crawler imaging, and outperforming those published in previous papers.

This work proposes the experimentation of an innovative hydraulic dredge for clam fishing (Chamelea gallina) in the Adriatic Sea (Italy). This innovative gear aimed at increasing the selectivity of the typical hydraulic dredge used currently, while at the same reducing the impact on benthos through the conception, installation, and experimentation of innovative technological solutions, consisting mainly of a vibrating bottom panel on the dredge and a “warning device” on the dredge mouth. Comparative experiments of the traditional vs. the modified gear, employing two boats fishing in parallel on the northern coast of Abruzzi (Adriatic Sea) and contrasting the catch with both paired comparisons and through modelling, showed that the innovative hydraulic dredge retains fewer undersize clams while yielding similar amounts of commercial product, moreover of higher quality; at the same time, it takes on board less discard, and catches significantly less vagile fauna. In short, the innovative gear is gaining five times over a list of six parameters considered as positive and/or advantageous for the clam fishery. The results allow proposals of potential improvements to clam-fishing instruments to make the selection processes more effective while promoting a lower impacting fishery, which is essential for clam management.

The Norway lobster, Nephrops norvegicus, supports a key European fishery. Stock assessments for this species are mostly based on trawling and UnderWater TeleVision (UWTV) surveys. However, N. norvegicus are burrowing organisms and these survey methods are unable to sample or observe individuals in their burrows. To account for this, UWTV surveys generally assume that “1 burrow system = 1 animal”, due to the territorial behavior of N. norvegicus. Nevertheless, this assumption still requires in-situ validation. Here, we outline how to improve the accuracy of current stock assessments for N. norvegicus with novel ecological monitoring technologies, including: robotic fixed and mobile camera-platforms, telemetry, environmental DNA (eDNA), and Artificial Intelligence (AI). First, we outline the present status and threat for overexploitation in N. norvegicus stocks. Then, we discuss how the burrowing behavior of N. norvegicus biases current stock assessment methods. We propose that state-of-the-art stationary and mobile robotic platforms endowed with innovative sensors and complemented with AI tools could be used to count both animals and burrows systems in-situ, as well as to provide key insights into burrowing behavior. Next, we illustrate how multiparametric monitoring can be incorporated into assessments of physiology and burrowing behavior. Finally, we develop a flowchart for the appropriate treatment of multiparametric biological and environmental data required to improve current stock assessment methods.

Ocean observatories collect large volumes of video data, with some data archives now spanning well over a few decades, and bringing the challenges of analytical capacity beyond conventional processing tools. The analysis of such vast and complex datasets can only be achieved with appropriate machine learning and Artificial Intelligence (AI) tools. The implementation of AI monitoring programs for animal tracking and classification becomes necessary in the particular case of deep-sea cabled observatories, as those operated by Ocean Networks Canada (ONC), where Petabytes of data are now collected each and every year since their installation. Here, we present a machine-learning and computer vision automated pipeline to detect and count sablefish (Anoplopoma fimbria), a key commercially exploited species in the N-NE Pacific. We used 651 hours of video footage obtained from three long-term monitoring sites in the NEPTUNE cabled observatory, in Barkley Canyon, on the nearby slope, and at depths ranging from 420 to 985 m. Our proposed AI sablefish detection and classification pipeline was tested and validated for an initial 4.5 month period (Sep 18 2019-Jan 2 2020), and was a first step towards validation for future processing of the now decade-long video archives from Barkley Canyon. For the validation period, we trained a YOLO neural network on 2917 manually annotated frames containing sablefish images to obtain an automatic detector with a 92% Average Precision (AP) on 730 test images, and a 5-fold cross-validation AP of 93% (± 3.7%). We then ran the detector on all video material (i.e., 651 hours from a 4.5 month period), to automatically detect and annotate sablefish. We finally applied a tracking algorithm on detection results, to approximate counts of individual fishes moving on scene and obtain a time series of proxy sablefish abundance. Those proxy abundance estimates are among the first to be made using such a large volume of video data from deep-sea settings. We discuss our AI results for application on a decade-long video monitoring program, and particularly with potential for complementing fisheries management practices of a commercially important species.

Scientific, industrial and societal needs call urgently for the development and establishment of intelligent, cost-effective and ecologically sustainable monitoring protocols and robotic platforms for the continuous exploration of marine ecosystems. Internet Operated Vehicles (IOVs) such as crawlers, provide a versatile alternative to conventional observing and sampling tools, being tele-operated, (semi-) permanent mobile platforms capable of operating on the deep and coastal seafloor. Here we present outstanding observations made by the crawler “Wally” in the last decade at the Barkley Canyon (BC, Canada, NE Pacific) methane hydrates site, as a part of the NEPTUNE cabled observatory. The crawler followed the evolution of microhabitats formed on and around biotic and/or abiotic structural features of the site (e.g., a field of egg towers of buccinid snails, and a colonized boulder). Furthermore, episodic events of fresh biomass input were observed (i.e., the mass transport of large gelatinous particles, the scavenging of a dead jellyfish and the arrival of macroalgae from shallower depths). Moreover, we report numerous faunal behaviors (i.e., sablefish rheo- and phototaxis, the behavioral reactions and swimming or resting patterns of further fish species, encounters with octopuses and various crab intra- and interspecific interactions). We report on the observed animal reactions to both natural and artificial stimuli (i.e., crawler’s movement and crawler light systems). These diverse observations showcase different capabilities of the crawler as a modern robotic monitoring platform for marine science and offshore industry. Its long deployments and mobility enable its efficiency in combining the repeatability of long-term studies with the versatility to opportunistically observe rarely seen incidents when they occur, as highlighted here. Finally, we critically assess the empirically recorded ecological footprint and the potential impacts of crawler operations on the benthic ecosystem of the Barkley Canyon hydrates site, together with potential solutions to mitigate them into the future.

The use of marine cabled video observatories with multiparametric environmental data collection capability is becoming relevant for ecological monitoring strategies. Their ecosystem surveying can be enforced in real time, remotely, and continuously, over consecutive days, seasons, and even years. Unfortunately, as most observatories perform such monitoring with fixed cameras, the ecological value of their data is limited to a narrow field of view, possibly not representative of the local habitat heterogeneity. Docked mobile robotic platforms could be used to extend data collection to larger, and hence more ecologically representative areas. Among the various state-of-the-art underwater robotic platforms available, benthic crawlers are excellent candidates to perform ecological monitoring tasks in combination with cabled observatories. Although they are normally used in the deep sea, their high positioning stability, low acoustic signature, and low energetic consumption, especially during stationary phases, make them suitable for coastal operations. In this paper, we present the integration of a benthic crawler into a coastal cabled observatory (OBSEA) to extend its monitoring radius and collect more ecologically representative data. The extension of the monitoring radius was obtained by remotely operating the crawler to enforce back-and-forth drives along specific transects while recording videos with the onboard cameras. The ecological relevance of the monitoring-radius extension was demonstrated by performing a visual census of the species observed with the crawler’s cameras in comparison to the observatory’s fixed cameras, revealing non-negligible differences. Additionally, the videos recorded from the crawler’s cameras during the transects were used to demonstrate an automated photo-mosaic of the seabed for the first time on this class of vehicles. In the present work, the crawler travelled in an area of 40 m away from the OBSEA, producing an extension of the monitoring field of view (FOV), and covering an area approximately 230 times larger than OBSEA’s camera. The analysis of the videos obtained from the crawler’s and the observatory’s cameras revealed differences in the species observed. Future implementation scenarios are also discussed in relation to mission autonomy to perform imaging across spatial heterogeneity gradients around the OBSEA.

Deep-sea ecosystems are reservoirs of biodiversity that are largely unexplored, but their exploration and biodiscovery are becoming a reality thanks to biotechnological advances (e.g., omics technologies) and their integration in an expanding network of marine infrastructures for the exploration of the seas, such as cabled observatories. While still in its infancy, the application of environmental DNA (eDNA) metabarcoding approaches is revolutionizing marine biodiversity monitoring capability. Indeed, the analysis of eDNA in conjunction with the collection of multidisciplinary optoacoustic and environmental data, can provide a more comprehensive monitoring of deep-sea biodiversity. Here, we describe the potential for acquiring eDNA as a core component for the expanding ecological monitoring capabilities through cabled observatories and their docked Internet Operated Vehicles (IOVs), such as crawlers. Furthermore, we provide a critical overview of four areas of development: (i) Integrating eDNA with optoacoustic imaging; (ii) Development of eDNA repositories and cross-linking with other biodiversity databases; (iii) Artificial Intelligence for eDNA analyses and integration with imaging data; and (iv) Benefits of eDNA augmented observatories for the conservation and sustainable management of deep-sea biodiversity. Finally, we discuss the technical limitations and recommendations for future eDNA monitoring of the deep-sea. It is hoped that this review will frame the future direction of an exciting journey of biodiscovery in remote and yet vulnerable areas of our planet, with the overall aim to understand deep-sea biodiversity and hence manage and protect vital marine resources.

The burrowing crustacean decapod Nephrops norvegicus is a significant species in European Atlantic and Mediterranean fisheries. Research over the decades has mainly focused on behavioral and physiological aspects related to the burrowing lifestyle, since animals can only be captured by trawls when engaged in emergence on the seabed. Here, we performed a global bibliographic survey of all the scientific literature retrieved in SCOPUS since 1965, and terminology maps were produced with the VOSviewer software to reveal established and emerging research areas. We produced three term-map plots: term clustering, term citation, and term year. The term clustering network showed three clusters: fishery performance, assessment, and management; biological cycles in growth, reproduction, and behavior; and finally, physiology and ecotoxicology, including food products. The term citation map showed that intense research is developed on ecotoxicology and fishery management. Finally, the term year map showed that the species was first studied in its morphological and physiological aspects and more recently in relation to fishery and as a food resource. Taken together, the results indicate scarce knowledge on how burrowing behavior and its environmental control can alter stock assessment, because of the poor use of current and advanced monitoring technologies.

The deep sea (i.e., >200 m depth) is a highly dynamic environment where benthic ecosystems are functionally and ecologically connected with the overlying water column and the surface. In the aphotic deep sea, organisms rely on external signals to synchronize their biological clocks. Apart from responding to cyclic hydrodynamic patterns and periodic fluctuations of variables such as temperature, salinity, phytopigments, and oxygen concentration, the arrival of migrators at depth on a 24-h basis (described as Diel Vertical Migrations; DVMs), and from well-lit surface and shallower waters, could represent a major response to a solar-based synchronization between the photic and aphotic realms. In addition to triggering the rhythmic behavioral responses of benthic species, DVMs supply food to deep seafloor communities through the active downward transport of carbon and nutrients. Bioluminescent species of the migrating deep scattering layers play a not yet quantified (but likely important) role in the benthopelagic coupling, raising the need to integrate the efficient detection and quantification of bioluminescence into large-scale monitoring programs. Here, we provide evidence in support of the benefits for quantifying and continuously monitoring bioluminescence in the deep sea. In particular, we recommend the integration of bioluminescence studies into long-term monitoring programs facilitated by deep-sea neutrino telescopes, which offer photon counting capability. Their Photo-Multiplier Tubes and other advanced optical sensors installed in neutrino telescope infrastructures can boost the study of bioluminescent DVMs in concert with acoustic backscatter and video imagery from ultra-low-light cameras. Such integration will enhance our ability to monitor proxies for the mass and energy transfer from the upper ocean into the deep-sea Benthic Boundary Layer (BBL), a key feature of the ocean biological pump and crucial for monitoring the effects of climate-change. In addition, it will allow for investigating the role of deep scattering DVMs in the behavioral responses, abundance and structure of deep-sea benthic communities. The proposed approach may represent a new frontier for the study and discovery of new, taxon-specific bioluminescence capabilities. It will thus help to expand our knowledge of poorly described deep-sea biodiversity inventories and further elucidate the connectivity between pelagic and benthic compartments in the deep-sea.

Future mining of polymetallic nodules in the Clarion Clipperton Zone (Northeastern Pacific) is expected to affect all benthic ecosystems. The diversity, distribution, and environmental functions of microorganisms inhabiting abyssal sediments are barely understood. To understand consequences of deep-sea mining, experimental in vitro systems needs to be established to test hypotheses on the environmental impact of mining. For this, 40 bacterial strains, belonging to proteobacteria, actinobacteria and firmicutes were isolated from deep-sea sediments and nodules sampled at depths of ≥ 4000 m. Phenotypic characterization revealed a strong inter-species and moderate intra-species variability. Determination of metal minimum inhibitory concentrations indicated the presence of acute manganese-resistant bacteria such as Rhodococcus erythropolis (228.9 mM), Loktanella cinnabarina (57.2 mM), and Dietzia maris (14.3 mM) that might be suitable systems for testing the effects of release of microbes from nodules and their interactions with sediment particles in plumes generated during mining. Comparative genomic analysis indicated the presence of manganese efflux systems relevant for future transcriptomics or proteomics approaches with environmental samples and might serve in paving the way to develop model systems including representative organisms which are currently not cultivable. Monitoring deep-sea mining activity at abyssal depth is a challenge that has to be tackled. We proposed the use of API strips as a fast on-board methodology for bacterial monitoring as an indicator for sediment plume dispersions within the water column.

The anthropogenic impact of polymetallic nodule harvesting in the Clarion-Clipperton Fracture Zone is expected to strongly affect the benthic ecosystem. To predict the long-term, industrial-scale impact of nodule mining on the deep-sea environment and to improve the reliability of the sediment plume model, information about the specific characteristics of deep-sea particles is needed. Discharge simulations of mining-related fine-grained (median diameter ≈ 20 μm) sediment plumes at concentrations of 35–500 mg L–1 (dry weight) showed a propensity for rapid flocculation within 10 to 135 min, resulting in the formation of large aggregates up to 1100 μm in diameter. The results indicated that the discharge of elevated plume concentrations (500 mg L–1) under an increased shear rate (G ≥ 2.4 s–1) would result in improved efficiency of sediment flocculation. Furthermore, particle transport model results suggested that even under typical deep-sea flow conditions (G ≈ 0.1 s–1), rapid deposition of particles could be expected, which would restrict heavy sediment blanketing (several centimeters) to a smaller fall-out area near the source, unless subsequent flow events resuspended the sediments. Planning for in situ tests of these model projections is underway

Mechatronic and soft robotics are taking inspiration from the animal kingdom to create new high-performance robots. Here, we focused on marine biomimetic research and used innovative bibliographic statistics tools, to highlight established and emerging knowledge domains. A total of 6980 scientific publications retrieved from the Scopus database (1950–2020), evidencing a sharp research increase in 2003–2004. Clustering analysis of countries collaborations showed two major Asian-North America and European clusters. Three significant areas appeared: (i) energy provision, whose advancement mainly relies on microbial fuel cells, (ii) biomaterials for not yet fully operational soft-robotic solutions; and finally (iii), design and control, chiefly oriented to locomotor designs. In this scenario, marine biomimicking robotics still lacks solutions for the long-lasting energy provision, which presently hinders operation autonomy. In the research environment, identifying natural processes by which living organisms obtain energy is thus urgent to sustain energy-demanding tasks while, at the same time, the natural designs must increasingly inform to optimize energy consumption.

Deep-sea environmental datasets are ever-increasing in size and diversity, as technological advances lead monitoring studies towards long-term, high-frequency data acquisition protocols. This study presents examples of pre-analysis data treatment steps applied to the environmental time series collected by the Internet Operated Deep-sea Crawler “Wally” during a 7-year deployment (2009–2016) in the Barkley Canyon methane hydrates site, off Vancouver Island (BC, Canada). Pressure, temperature, electrical conductivity, flow, turbidity, and chlorophyll data were subjected to different standardizing, normalizing, and de-trending methods on a case-by-case basis, depending on the nature of the treated variable and the range and scale of the values provided by each of the different sensors. The final pressure, temperature, and electrical conductivity (transformed to practical salinity) datasets are ready for use. On the other hand, in the cases of flow, turbidity, and chlorophyll, further in-depth processing, in tandem with data describing the movement and position of the crawler, will be needed in order to filter out all possible effects of the latter. Our work evidences challenges and solutions in multiparametric data acquisition and quality control and ensures that a big step is taken so that the available environmental data meet high quality standards and facilitate the production of reliable scientific results.

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.

Knowledge of the processes shaping deep-sea benthic communities at seasonal scales in cold-seep environments is incomplete. Cold seeps within highly dynamic regions, such as submarine canyons, where variable current regimes may occur, are particularly understudied. Novel Internet Operated Vehicles (IOVs), such as tracked crawlers, provide new techniques for investigating these ecosystems over prolonged periods. In this study a benthic crawler connected to the NEPTUNE cabled infrastructure operated by Ocean Networks Canada was used to monitor community changes across 60 m2 of a cold-seep area of the Barkley Canyon, North East Pacific, at ~890 m depth within an Oxygen Minimum Zone (OMZ). Short video-transects were run at 4-h intervals during the first week of successive calendar months, over a 14 month period (February 14th 2013 to April 14th 2014). Within each recorded transect video megafauna abundances were computed and changes in environmental conditions concurrently measured. The responses of fauna to environmental conditions as a proxy of seasonality were assessed through analysis of abundances in a total of 438 video-transects (over 92 h of total footage). 7698 fauna individuals from 6 phyla (Cnidaria, Ctenophora, Arthropoda, Echinodermata, Mollusca, and Chordata) were logged and patterns in abundances of the 7 most abundant taxa (i.e. rockfish Sebastidae, sablefish Anoplopoma fimbria, hagfish Eptatretus stoutii, buccinids (Buccinoidea), undefined small crabs, ctenophores Bolinopsis infundibulum, and Scyphomedusa Poralia rufescens) were identified. Patterns in the reproductive behaviour of the grooved tanner crab (Chionnecetes tanneri) were also indicated. Temporal variations in biodiversity and abundance in megabenthic fauna was significantly influenced by variabilities in flow velocity flow direction (up or down canyon), dissolved oxygen concentration and month of study. Also reported here for the first time are transient mass aggregations of grooved tanner crabs through these depths of the canyon system, in early spring and likely linked to the crab's reproductive cycle.

Three benthic megafaunal species (i.e. sablefish Anoplopoma fimbria; pacific hagfish Eptatretus stoutii and a group of juvenile crabs) were tested for diel behavioral patterns at the methane hydrates site of Barkley Canyon (890 m depth), off Vancouver Island (BC, Canada). Fluctuations of animal counts in linear video-transects conducted with the Internet Operated Deep-Sea Crawler "Wally" in June, July and December of 2013, were used as proxy of population activity rhythms. Count time series and environmental parameters were analyzed under the hypothesis that the environmental conditioning of activity rhythms depends on the life habits of particular species (i.e. movement type and trophic level). Non-linear least squares modeling of biological time series revealed significant diel periods for sablefish in summer and for hagfish and crabs in December. Combined cross-correlation and redundancy (RDA) analyses showed strong relationships among environmental fluctuations and detected megafauna. In particular, sablefish presence during summer months was related to flow magnitude, while the activity of pacific hagfish and juvenile crabs in December correlated with change in chemical parameters (i.e. chlorophyll and oxygen concentrations, respectively). Waveform analyses of animal counts and environmental variables confirmed the phase delay during the 24 h cycle. The timing of detection of sablefish occurred under low flow velocities, a possible behavioral adaptation to the general hypoxic conditions. The proposed effect of chlorophyll concentrations on hagfish counts highlights the potential role of phytodetritus as an alternative food source for this opportunistic feeder. The juvenile crabs seemed to display a cryptic behavior, possibly to avoid predation, though this was suppressed when oxygen levels were at a minimum. Our results highlight the potential advantages such mobile observation platforms offer in multiparametric deep-sea monitoring in terms of both spatial and temporal resolution and add to the vastly understudied field of diel rhythms of deep-sea megafauna.