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The term environmental DNA (eDNA) indicates the genomic DNA deriving from many different organisms that can be found in an environmental sample. eDNA comprises DNA molecules that are released in the environment (e.g. skin cells, mucous, sperm, faeces, blood) and can be con-centrated and isolated by collecting and analysing sediment, water, ice or air samples (Taberlet et al., 2012). [...]

Recent advances in robotic design, autonomy and sensor integration create solutions for the exploration of deep-sea environments,transferable to the oceans of icy moons. Marine platforms do not yet have the mission autonomy capacity of their space counterparts (e.g., the state of the art Mars Perseverance rover mission), although different levels of autonomous navigation and mapping, as well as sampling, are an extant capability. In this setting their increasingly biomimicked designs may allow access to complex environmental scenarios, with novel, highly-integrated life-detecting, oceanographic and geochemical sensor packages. Here, we lay an outlook for the upcoming advances in deep-sea robotics through synergies with space technologies within three major research areas: biomimetic structure and propulsion (including power storage and generation), artificial intelligence and cooperative networks, and life-detecting instrument design. New morphological and material designs, with miniaturized and more diffuse sensor packages, will advance robotic sensing systems. Artificial intelligence algorithms controlling navigation and communications will allow the further development of the behavioral biomimicking by cooperating networks. Solutions will have to be tested within infrastructural networks of cabled observatories, neutrino telescopes, and off-shore industry sites with agendas and modalities that are beyond the scope of our work, but could draw inspiration on the proposed examples for the operational combination of fixed and mobile platforms.

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.

Environmental DNA (eDNA) comprises intra- and extra-cellular DNA molecules that are released in the environment and can be traced back to the source organism by analysing an environmental sample, such as water or sediment. While many limitations still exist, the coupling and integration of eDNA sampling with both traditional methods (direct capture) and/or other non-invasive approaches (imaging and acoustic data) has great potential to enhance monitoring capabilities of the marine environment. In addition, emerging technologies (including portable sequencers) are enabling the development of protocols for near real-time in situ applications of eDNA analysis. Our aim is to develop, test and implement eDNA metabarcoding protocols capable of being installed onto marine platforms such as marine fixed or mobile infrastructures (e.g. fixed observatories, platforms, research vessels) to provide real-time data of support to fisheries and other megafauna monitoring programs. An initial protocol has been already tested in laboratory conditions using a MinION portable sequencer (Oxford Nanopore Technologies), with preliminary results showing promising results in generating fish community profiles from eDNA samples collected at depth along the Northeast Atlantic continental shelf. Furter protocol development is ongoing and will include complete processing of environmental samples, from collection to High Throughput Sequencing (HTS) and bioinformatic analysis, in remote conditions. Specifically, results of protocol validation and implementation will be presented after execution in three contexts: (i) an aquarium with known species richness (Galway Atlantaquaria, Ireland); (ii) an open water fixed observatory equipped with a full suite of sensors including video (the Acqua Alta platform (Northern Adriatic Sea, Italy)); and (iii) offshore on board a research vessel during acoustic fisheries surveys (the Marine Institute's RV Celtic Explorer, Ireland). The inclusion of eDNA in the m

Coordinated systems composed by fixed and mobile robotic platforms are used for the ecological monitoring of megafauna across ecological gradients (oceanographic, geomorphological and substrate characteristics across the bathymetry of the slope and through water column layers) continuously at a high temporal frequency. None of these platforms is branching into estuarine and river areas, providing the coupling of ecological gradients that encompass marine and inland waters. Here, we propose a conceptual scheme to bring forward that integration, by establishing the principles of a network of fixed platforms working not only with HD imaging but also with advanced optoacoustic tools that works in turbid waters. This sensor dotation may be expanded by tools for augmented species presence detection beyond the HD and optoacoustic imaging, such as Passive Acoustic Monitoring and omics approaches (eDNA). Detection by acoustic and molecular markers can be cross-validated against libraries of images. The use of land-docked crawlers may allow stepping-stone observations between patches to spatially scale local data, extending the ecological representativeness of local observations. Those infrastructures may be of a special relevance for legally prescribed monitoring of endangered European eel (Anguilla anguilla), but also for other species, including anadromous Salmo salar in increasingly impacted coastal-river areas

European North Atlantic ranavirus (ENARV, Iridoviridae), is a ranavirus species recently isolated from lumpfish (Cyclopterus lumpus, L.), which are used as cleaner fish in Atlantic salmon (Salmo salar) farming in Northern Europe. This study aimed to investigate (1) the virulence of ENARV isolates from Ireland, Iceland and the Faroe Islands to lumpfish; (2) horizontal transmission between lumpfish; and (3) virulence to Atlantic salmon parr. Lumpfish were challenged in a cohabitation model using intraperitoneally (IP) injected shedders, and naïve cohabitants. IP challenge with isolates from Iceland (1.9 × 107 TCID50 ml-1 ) and the Faroe Islands (5.9 × 107 TCID50 ml-1) reduced survival in lumpfish, associated with consistent pathological changes. IP challenge with the Irish strain (8.6 × 105 TCID50 ml-1) did not significantly reduce survival in lumpfish, but the lower challenge titre complicated interpretation. Horizontal transmission occurred in all strains tested, but no clinical impact was demonstrated in cohabitants. Salmon parr were challenged by IP injection with the Irish isolate, no virulence or virus replication were demonstrated. A ranavirus qPCR assay, previously validated for fish ranaviruses, was first used to detect ENARV in tissues of both in lumpfish and Atlantic salmon. This study provides the first data on the assessment of virulence of ENARV isolates to lumpfish and salmon, guidelines for the diagnosis of ENARV infection, and poses a basis for further investigations into virulence markers.

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

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., Peer Reviewed, Article signat per 31 autors/es: Jacopo Aguzzi, Damianos Chatzievangelou, Nathan J. Robinson, Nixon Bahamon, Alan Berry, Marc Carreras, Joan Batista Company, Corrado Costa, Joaquin del Rio Fernandez, Ahmad Falahzadeh, Spyros Fifas, Sascha Flögel, Jordi Grinyó, Jonás Pall Jonasson, Patrik Jonsson, Colm Lordan, Mathieu Lundy, Simone Marini, Michela Martinelli, Ivan Masmitja, Luca Mirimin, Atif Naseer, Joan Navarro, Narcís Palomeras, Giacomo Picardi, Cristina Silva, Sergio Stefanni , Maria Vigo, Yolanda Vila, Adrian Weetman i Jennifer Doyle., Postprint (published version)

Recent advances in robotic design, autonomy and sensor integration create solutions for the exploration of deep-sea environments, transferable to the oceans of icy moons. Marine platforms do not yet have the mission autonomy capacity of their space counterparts (e.g., the state of the art Mars Perseverance rover mission), although different levels of autonomous navigation and mapping, as well as sampling, are an extant capability. In this setting their increasingly biomimicked designs may allow access to complex environmental scenarios, with novel, highly-integrated life-detecting, oceanographic and geochemical sensor packages. Here, we lay an outlook for the upcoming advances in deep-sea robotics through synergies with space technologies within three major research areas: biomimetic structure and propulsion (including power storage and generation), artificial intelligence and cooperative networks, and life-detecting instrument design. New morphological and material designs, with miniaturized and more diffuse sensor packages, will advance robotic sensing systems. Artificial intelligence algorithms controlling navigation and communications will allow the further development of the behavioral biomimicking by cooperating networks. Solutions will have to be tested within infrastructural networks of cabled observatories, neutrino telescopes, and off-shore industry sites with agendas and modalities that are beyond the scope of our work, but could draw inspiration on the proposed examples for the operational combination of fixed and mobile platforms

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., This research has been funded within the framework of the following project activities: ARIM (Autonomous Robotic Sea-Floor Infrastructure for Benthopelagic Monitoring; MarTERA ERA-Net Cofound); RESBIO (TEC2017-87861-R; Ministerio de Ciencia, Innovación y Universidades); JERICO-S3: (Horizon 2020; Grant Agreement no. 871153); ENDURUNS (Research Grant Agreement H2020-MG-2018-2019-2020 n.824348); Slovenian Research Agency (Research Core Funding Nos. P1-0237 and P1-0255 and project ARRS-RPROJ-JR-J1-3015). We also profited of the funding from the Spanish Government through the “Severo Ochoa Centre of Excellence” accreditation (CEX2019-000928-S) and Italian Ministry of Education (MIUR) under the “Bando premiale FOE 2015” (nota prot. N. 850, dd. 27 ottobre 2017) with the project EarthCruisers “EARTH’s CRUst Imagery for Investigating Seismicity, Volcanism, and Marine Natural Resources in the Sicilian Offshore”. Ocean Networks Canada was funded through Canada Foundation for Innovation-Major Science Initiative (CFI-MSI) fund 30199., Peer Reviewed, Postprint (published version)

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

In a recent paper, “Environmental DNA: What's behind the term? Clarifying the terminology and recommendations for its future use in biomonitoring,” Pawlowski et al. argue that the term eDNA should be used to refer to the pool of DNA isolated from environmental samples, as opposed to only extra-organismal DNA from macro-organisms. We agree with this view. However, we are concerned that their proposed two-level terminology specifying sampling environment and targeted taxa is overly simplistic and might hinder rather than improve clear communication about environmental DNA and its use in biomonitoring. This terminology is based on categories that are often difficult to assign and uninformative, and it overlooks a fundamental distinction within eDNA: the type of DNA (organismal or extra-organismal) from which ecological interpretations are derived.

Cabled observatories are marine infrastructures equipped with biogeochemical and oceanographic sensors as well as High-Definition video and audio equipment, hence providing unprecedented opportunities to study marine biotic and abiotic components. Additionally, non-invasive monitoring approaches such as environmental DNA (eDNA) metabarcoding have further enhanced the ability to characterize marine life. Although the use of non-invasive tools beholds great potential for the sustainablemonitoring of biodiversity and declining natural resources, such techniques are rarely used in parallel and understanding their limitations is challenging. Thus, this study combined Underwater Video (UV) with eDNA metabarcoding data to produce marine fish community profiles over a 2 months period in situ at a cabled observatory in the northeast Atlantic (SmartBay Ireland). By combining both approaches, an increased number of fish could be identified to the species level (total of 22 species), including ecologically and economically important species such as Atlantic cod, whiting, mackerel and monkfish

In a recent paper, “Environmental DNA: What's behind the term? Clarifying the terminology and recommendations for its future use in biomonitoring,” Pawlowski et al. argue that the term eDNA should be used to refer to the pool of DNA isolated from environmental samples, as opposed to only extra-organismal DNA from macro-organisms. We agree with this view. However, we are concerned that their proposed two-level terminology specifying sampling environment and targeted taxa is overly simplistic and might hinder rather than improve clear communication about environmental DNA and its use in biomonitoring. This terminology is based on categories that are often difficult to assign and uninformative, and it overlooks a fundamental distinction within eDNA: the type of DNA (organismal or extra-organismal) from which ecological interpretations are derived.

Cabled video-observatories offer new opportunities to monitor fish species at frequencies and durations never attained before, quantifying the behavioural activities of their individuals, and providing ancillary data to inform stock assessment (in a fishery-independent manner). In this context, our objective was to improve the ecological monitoring capability of SmartBay observatory (20 m depth, Galway Bay, Ireland), through a pilot study dedicated to tracking of fish counts (as a proxy of populations activity rhythms), in a context where species behaviour and consequent community turnover may occur at different temporal cycles (i.e. tidal versus day-night). In order to understand how animals can regulate their behavioural activity upon those cycles, we enforced a time-lapse (1 h interval) image collection and concomitant multiparametric oceanographic plus acoustic data acquisition continuously during 24 h, over 30 days in August 2018 (when turbidity is at minimum). For each image, we classified and then counted all visible fish and derived count time series. Periodogram and waveform analyses were used to calculate their fluctuations' periodicity (i.e. the ruling cycle) and phase (i.e. peak timing in relation to the cycle). A total of 12 marine teleost species were pictured with Trisopterus minutus, Trachurus trachurus and Chelidonichthys lucerna characterized by day-night related rhythms, while others, such as Trisopterus luscus and Gadus morhua, were influenced by the tidal cycle. 24 h count patterns were compared together and investigated for time-based ecological niche-partitioning in a wave and current-affected soundscape. These findings were discussed in relation to the ecology of species and the feasibility of promising observatory-based monitoring applications in fishery assessment practices, when targeted species have commercial value., Dr. J. Aguzzi and J. del Rio are members of the CSIC-UPC Associated Unit “Tecnoterra”, managing the OBSEA platform, an EMSO testing-site. This work was developed within the framework of the Projects ADVANCE (H2020 INFRAIA-2014-2015 grant agreement 654410, Jerico-Next TNA), RESBIO (TEC2017-87861-R) and ARIM (Autonomous Robotic sea-floor Infrastructure for benthopelagic Monitoring; MarTERA ERA-Net Cofound). The SmartBay cabled observatory was funded by Science Foundation Ireland (SFI) as part of an SFI Research Infrastructure Award under Grant No. 12/RI/233., Peer Reviewed, Postprint (author's final draft)

Cabled video-observatories offer new opportunities to monitor fish species at frequencies and durations never attained before, quantifying the behavioural activities of their individuals, and providing ancillary data to inform stock assessment (in a fishery-independent manner). In this context, our objective was to improve the ecological monitoring capability of SmartBay observatory (20 m depth, Galway Bay, Ireland), through a pilot study dedicated to tracking of fish counts (as a proxy of populations activity rhythms), in a context where species behaviour and consequent community turnover may occur at different temporal cycles (i.e. tidal versus day-night). In order to understand how animals can regulate their behavioural activity upon those cycles, we enforced a time-lapse (1 h interval) image collection and concomitant multiparametric oceanographic plus acoustic data acquisition continuously during 24 h, over 30 days in August 2018 (when turbidity is at minimum). For each image, we classified and then counted all visible fish and derived count time series. Periodogram and waveform analyses were used to calculate their fluctuations' periodicity (i.e. the ruling cycle) and phase (i.e. peak timing in relation to the cycle). A total of 12 marine teleost species were pictured with Trisopterus minutus, Trachurus trachurus and Chelidonichthys lucerna characterized by day-night related rhythms, while others, such as Trisopterus luscus and Gadus morhua, were influenced by the tidal cycle. 24 h count patterns were compared together and investigated for time-based ecological niche-partitioning in a wave and current-affected soundscape. These findings were discussed in relation to the ecology of species and the feasibility of promising observatory-based monitoring applications in fishery assessment practices, when targeted species have commercial value