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In July 2020, Japan undertook the first deep-sea mining test of cobalt-rich crusts on the summit of Takuyo-Daigo Seamount within their exclusive economic zone (EEZ). Seabed mining regulations are currently being developed by the International Seabed Authority (ISA)1; however, a lack of experimental data has so far constrained our understanding of the associated impacts, particularly from the release of sediment plumes.2 The area of sediment re-deposition from the crust mining test was determined using modeled data and in situ observations. To investigate biological impacts, variations in seabed megafauna (animals > 1 cm) were quantified from seabed imagery collected around the excavation site before, 1 month, and 13 months after the test in areas both inside and outside (adjacent) expected deposition. Observable responses varied across community components: densities of sessile animals were similar between deposition and adjacent areas throughout the study; mobile epifauna were less abundant only in the deposition area following disturbance; and highly mobile swimmers showed reduced densities after the test in both deposition and adjacent areas following disturbance. These results stress that monitoring of highly mobile taxa may be essential to fully assess disturbance extent and magnitude. Fish may avoid areas even outside plume deposition, possibly owing to the creation of suboptimal feeding patches resulting from deposition. Our findings suggest sufficiently large (>300 × 300 m), distant, and representative control areas are essential to optimally map deep-sea mining impacts in ferromanganese crust habitats to ensure impact assessments encompass the full range of functional components in the megabenthic community (including mobile fishes) that typically inhabit seamounts.

Abyssal plain communities rely on the overlying water column for a settling flux of organic matter. The origin and rate of this flux as well as the controls on its fine-scale spatial distribution following seafloor settlement are largely unquantified. This is particularly true across regions where anthropogenically-induced seafloor disturbance has occurred. Here, we observed, quantified and mapped a mass deposition event of gelatinous zooplankton carcasses (pyrosomes) in July-September 2015 across one such physically disturbed region in the Peru Basin polymetallic nodule province (4150 m). Seafloor in this area was disturbed with a plough harrow in 1989 (as part of the DISCOL experiment) causing troughs in the sediment. Other parts were disturbed with an epibenthic sled (EBS) during a cruise in 2015 resulting in steep-walled, U-shaped troughs. We investigated two hypotheses: a) gelatinous food falls contribute significantly to the abyssal plain carbon pump and b) physical seafloor disturbance influences abyssal distribution of organic matter. We combined optical and bathymetric seafloor observations, to analyze pyrosome distribution on seabeds with different levels of disturbance. 2954 pyrosome colonies and associated taxa were detected in > 14,000 seafloor images. The mean regional carbon (C) deposition associated with pyrosome carcasses was significant compared to the flux of particulate organic C (182 to 1543%), and the total respired benthic C flux in the DISCOL Experimental Area (39 to 184%). EBS-disturbed seafloor tracks contained 72 times more pyrosome-associated C than an undisturbed reference site, and up to 4 times more than an area disturbed in 1989. Deposited pyrosomes collected had a higher proportion of labile fatty acids compared to the sediment. We document the temporal and spatial extent of an abyssal food fall event with unprecedented detail and show that physical seafloor disturbance results in the accumulation of detrital material. Such accumulat

Abyssal polymetallic nodule fields represent a unique deep-sea habitat. The hard substratum provided by nodules is thought to increase habitat complexity, promoting the occurrence of highly diverse abyssal assemblages. However, hard substratum in these habitats is also available as outcropping rock fragments, but their contribution to habitat heterogeneity has been largely overlooked. Here, we assessed if the type and size of hard substratum can modulate benthic biodiversity at local scales within the Clarion Clipperton Zone (N Pacific abyss). We compared megafauna (animals >10 mm) assemblages in nodule bearing habitats with those in areas containing rocks in addition to nodules. We found a lower faunal density but a clearly higher diversity and more heterogenous composition in the assemblages of rock bearing areas compared to those with only nodules. In addition, hard substratum patch size appeared to positively influence the size of some taxa, like bamboo corals. These results suggest that rocks, in addition to nodules, constitute keystone structures enhancing habitat heterogeneity at local scales within nodule fields. Rock areas appear common in some abyssal plains and may make regionally-important contributions to abyssal biodiversity, suggesting that they may be relevant to include in conservation efforts.

Massive swarms of the red crab, Pleuroncodes planipes (Stimpson 1860), a species of squat lobster, are a dominant functional component of the upwelling ecosystem in the eastern Pacific Ocean (Boyd 1967, Smith et al. 1975). These swarms can wash ashore on the coast creating mass depositions of crustacean carcasses, a striking phenomenon that has been long documented in Baja California and California (Boyd 1967, Aurioles-Gamboa et al. 1994). However, little is known about the fate of crab swarms transported offshore by oceanic currents. In May 2015, using an autonomous deep-sea robot, we discovered an unexpectedly large fall of red crab carcasses (> 1000 carcasses ha-1 ) at 4050 m depth on the abyssal Pacific seafloor (Fig. 1), almost 1500 km away from their spawning areas off the NW American coast. Several questions arise from this novel finding that may help unveil additional close linkages in nutritional transport between processes at the sea surface and the remote abyssal seafloor.

To protect the range of habitats, species, and ecosystem functions in the Clarion Clipperton Zone (CCZ), a region of interest for deep-sea polymetallic nodule mining in the Pacific, nine Areas of Particular Environmental Interest (APEIs) have been designated by the International Seabed Authority (ISA). The APEIs are remote, rarely visited and poorly understood. Here we present and synthesise all available observations made at APEI-6, the most north eastern APEI in the network, and assess its representativity of mining contract areas in the eastern CCZ. The two studied regions of APEI-6 have a variable morphology, typical of the CCZ, with hills, plains and occasional seamounts. The seafloor is predominantly covered by fine-grained sediments, and includes small but abundant polymetallic nodules, as well as exposed bedrock. The oceanographic parameters investigated appear broadly similar across the region although some differences in deep-water mass separation were evident between APEI-6 and some contract areas. Sediment biogeochemistry is broadly similar across the area in the parameters investigated, except for oxygen penetration depth, which reached >2 m at the study sites within APEI-6, deeper than that found at UK1 and GSR contract areas. The ecology of study sites in APEI-6 differs from that reported from UK1 and TOML-D contract areas, with differences in community composition of microbes, macrofauna, xenophyophores and metazoan megafauna. Some species were shared between areas although connectivity appears limited. We show that, from the available information, APEI-6 is partially representative of the exploration areas to the south yet is distinctly different in several key characteristics. As a result, additional APEIs may be warranted and caution may need to be taken in relying on the APEI network alone for conservation, with other management activities required to help mitigate the impacts of mining in the CCZ.

This paper recommends best practice for the use of open nomenclature (ON) signs applicable to image-based faunal analyses. It is one of numerous initiatives to improve biodiversity data input to improve the reliability of biological datasets and their utility in informing policy and management. Image-based faunal analyses are increasingly common but have limitations in the level of taxonomic precision that can be achieved, which varies among groups and imaging methods. This is particularly critical for deep-sea studies owing to the difficulties in reaching confident species-level identifications of unknown taxa. ON signs indicate a standard level of identification and improve clarity, precision and comparability of biodiversity data. Here we provide examples of recommended usage of these terms for input to online databases and preparation of morphospecies catalogues. Because the processes of identification differ when working with physical specimens and with images of the taxa, we build upon previously provided recommendations for specific use with image-based identifications.

The relationship between polymetallic nodules (Mn nodules) and deep-sea stratigraphy is relatively poorly studied and the role of sediment thickness in determining nodule occurrence is an active field of research. This study utilizes geophysical observations from three types of autonomous underwater vehicle (AUV) data (multi-beam bathymetry, sub-bottom profiles and underwater photography) in order to assess this relationship. Multi-beam bathymetry was processed with a pattern recognition approach for producing objective geomorphometric classes of the seafloor for examining their relation to sediment thickness and nodule occurrence. Sub-bottom profiles were used for extracting sediment thickness along a dense network of tracklines. Close-range AUV-photography data was used for automated counting of polymetallic nodules and their geometric features and it served as ground truth data. It was observed that higher nodule occurrence were related to layers with increased sediment thickness. This evidence reveals the role of local seafloor heterogeneity in nodule formation and suggests that unique patterns of local stratigraphy may affect geochemical processes that promote polymetallic nodule development at local scales.

Due to the predicted future demand for critical metals, abyssal plains covered with polymetallic nodules are currently being prospected for deep-seabed mining. Deep-seabed mining will lead to significant sediment disturbance over large spatial scales and for extended periods of time. The environmental impact of a small-scale sediment disturbance was studied during the ‘DISturbance and reCOLonization’ (DISCOL) experiment in the Peru Basin in 1989 when 10.8 km2 of seafloor were ploughed with a plough harrow. Here, we present a detailed description of carbon-based food-web models constructed from various datasets collected in 2015, 26 years after the experiment. Detailed observations of the benthic food web were made at three distinct sites: inside 26-year old plough tracks (IPT, subjected to direct impact from ploughing), outside the plough tracks (OPT, exposed to settling of resuspended sediment), and at reference sites (REF, no impact). The observations were used to develop highly-resolved food-web models for each site that quantified the carbon (C) fluxes between biotic (ranging from prokaryotes to various functional groups in meio-, macro-, and megafauna) and abiotic (e.g. detritus) compartments. The model outputs were used to estimate total system throughput, i.e., the sum of all C flows in the food web (the ‘ecological size’ of the system), and microbial loop functioning, i.e., the C-cycling through the prokaryotic compartment for each site. Both the estimated total system throughput and the microbial loop cycling were significantly reduced (by 16% and 35%, respectively) inside the plough tracks compared to the other two sites. Site differences in modelled faunal respiration varied among the different faunal compartments. Overall, modelled faunal respiration appeared to have recovered to, or exceeded reference values after 26-years. The model results indicate that food-web functioning, and especially the microbial loop, have not recovered from the disturbance th

With the mining of polymetallic nodules from the deep-sea seafloor once more evoking commercial interest, decisions must be taken on how to most efficiently regulate and monitor physical and community disturbance in these remote ecosystems. Image-based approaches allow non-destructive assessment of the abundance of larger fauna to be derived from survey data, with repeat surveys of areas possible to allow time series data collection. At the time of writing, key underwater imaging platforms commonly used to map seafloor fauna abundances are autonomous underwater vehicles (AUVs), remotely operated vehicles (ROVs) and towed camera “ocean floor observation systems” (OFOSs). These systems are highly customisable, with cameras, illumination sources and deployment protocols changing rapidly, even during a survey cruise. In this study, eight image datasets were collected from a discrete area of polymetallic-nodule-rich seafloor by an AUV and several OFOSs deployed at various altitudes above the seafloor. A fauna identification catalogue was used by five annotators to estimate the abundances of 20 fauna categories from the different datasets. Results show that, for many categories of megafauna, differences in image resolution greatly influenced the estimations of fauna abundance determined by the annotators. This is an important finding for the development of future monitoring legislation for these areas. When and if commercial exploitation of these marine resources commences, robust and verifiable standards which incorporate developing technological advances in camera-based monitoring surveys should be key to developing appropriate management regulations for these regions.

We report on preliminary observations of the abyssal megafauna communities in the exclusive economic zone of Kiribati, a huge abyssal area with few previous studies. These observations also provide useful context for marine minerals exploration within the exclusive economic zone (EEZ) and for the neighboring Clarion Clipperton Zone (CCZ), where deep-sea mining operations are planned. Seafloor images collected during seabed mining exploration were used to characterize megafaunal communities (fauna > 1 cm) in three abyssal plain areas in the eastern Kiribati EEZ (study area extending from 1 to 5°N and 173 to 156°W). Additionally, hydrographic features in each of the survey locations were inferred by reference to near-seabed current flows modeled using open-sourced oceanographic data. The images showed a dominance of foraminiferal organisms. Metazoan communities were high in morphospecies richness but had low density. These general patterns were comparable to abyssal megabenthic communities in the CCZ. There was evidence of spatial variation between the assemblages in Kiribati, but there was a relatively large pool of shared morphospecies across the entire study area. Low metazoan density limited detailed assessment of spatial variation and diversity at local scales. This finding is instructive of the levels of sampling effort required to determine spatial patterns in low density abyssal communities. The results of this study are preliminary observations that will be useful to guide future biological survey design and marine spatial planning strategies.

The evaluation of large amounts of digital image data is of growing importance for biology, including for the exploration and monitoring of marine habitats. However, only a tiny percentage of the image data collected is evaluated by marine biologists who manually interpret and annotate the image contents, which can be slow and laborious. In order to overcome the bottleneck in image annotation, two strategies are increasingly proposed: “citizen science” and “machine learning”. In this study, we investigated how the combination of citizen science, to detect objects, and machine learning, to classify megafauna, could be used to automate annotation of underwater images. For this purpose, multiple large data sets of citizen science annotations with different degrees of common errors and inaccuracies observed in citizen science data were simulated by modifying “gold standard” annotations done by an experienced marine biologist. The parameters of the simulation were determined on the basis of two citizen science experiments. It allowed us to analyze the relationship between the outcome of a citizen science study and the quality of the classifications of a deep learning megafauna classifier. The results show great potential for combining citizen science with machine learning, provided that the participants are informed precisely about the annotation protocol. Inaccuracies in the position of the annotation had the most substantial influence on the classification accuracy, whereas the size of the marking and false positive detections had a smaller influence.