ALBERT

Description: Commercial-scale mining for polymetallic nodules could have a major impact on the deepsea environment, but the effects of these mining activities on deep-sea ecosystems are very poorly known. The first commercial test mining for polymetallic nodules was carried out in 1970. Since then a number of small-scale commercial test mining or scientific disturbance studies have been carried out. Here we evaluate changes in faunal densities and diversity of benthic communities measured in response to these 11 simulated or test nodule mining disturbances using meta-analysis techniques. We find that impacts are often severe immediately after mining, with major negative changes in density and diversity of most groups occurring. However, in some cases, the mobile fauna and small-sized fauna experienced less negative impacts over the longer term. At seven sites in the Pacific, multiple surveys assessed recovery in fauna over periods of up to 26 years. Almost all studies show some recovery in faunal density and diversity for meiofauna and mobile megafauna, often within one year. However, very few faunal groups return to baseline or control conditions after two decades. The effects of polymetallic nodule mining are likely to be long term. Our analyses show considerable negative biological effects of seafloor nodule mining, even at the small scale of test mining experiments, although there is variation in sensitivity amongst organisms of different sizes and functional groups, which have important implications for ecosystem responses. Unfortunately, many past studies have limitations that reduce their effectiveness in determining responses. We provide recommendations to improve future mining impact test studies. Further research to assess the effects of test-mining activities will inform ways to improve mining practices and guide effective environmental management of mining activities.

Description: Highlights • Total modeled carbon cycling at disturbed sites is lower than at reference sites. • Projected microbial loop functioning is reduced 26 years after sediment disturbance. • Estimated faunal respiration has recovered from sediment disturbance. • Estimated microbial respiration has not recovered from the sediment disturbance. Abstract 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 that was inflicted on the abyssal site 26 years ago.

Description: Highlights • The proposed method automatically assesses the abundance of poly-metallic nodules on the seafloor. • No manually created feature reference set is required. • Large collections of benthic images from a range of acquisition gear can be analysed efficiently. Abstract Underwater image analysis is a new field for computational pattern recognition. In academia as well as in the industry, it is more and more common to use camera-equipped stationary landers, autonomous underwater vehicles, ocean floor observatory systems or remotely operated vehicles for image based monitoring and exploration. The resulting image collections create a bottleneck for manual data interpretation owing to their size. In this paper, the problem of measuring size and abundance of poly-metallic nodules in benthic images is considered. A foreground/background separation (i.e. separating the nodules from the surrounding sediment) is required to determine the targeted quantities. Poly-metallic nodules are compact (convex), but vary in size and appear as composites with different visual features (color, texture, etc.). Methods for automating nodule segmentation have so far relied on manual training data. However, a hand-drawn, ground-truthed segmentation of nodules and sediment is difficult (or even impossible) to achieve for a sufficient number of images. The new ES4C algorithm (Evolutionary tuned Segmentation using Cluster Co-occurrence and a Convexity Criterion) is presented that can be applied to a segmentation task without a reference ground truth. First, a learning vector quantization groups the visual features in the images into clusters. Secondly, a segmentation function is constructed by assigning the clusters to classes automatically according to defined heuristics. Using evolutionary algorithms, a quality criterion is maximized to assign cluster prototypes to classes. This criterion integrates the morphological compactness of the nodules as well as feature similarity in different parts of nodules. To assess its applicability, the ES4C algorithm is tested with two real-world data sets. For one of these data sets, a reference gold standard is available and we report a sensitivity of 0.88 and a specificity of 0.65. Our results show that the applied heuristics, which combine patterns in the feature domain with patterns in the spatial domain, lead to good segmentation results and allow full automation of the resource-abundance assessment for benthic poly-metallic nodules.

Description: Future deep-sea mining for polymetallic nodules in abyssal plains will negatively impact the benthic ecosystem, but it is largely unclear whether this ecosystem will be able to recover from mining disturbance and if so, to what extent and at what timescale. During the "DISturbance and reCOLonization" (DISCOL) experiment, a total of 22% of the seafloor within a 10.8km2 circular area of the nodule-rich seafloor in the Peru Basin (SE Pacific) was ploughed in 1989 to bury nodules and mix the surface sediment. This area was revisited 0.1, 0.5, 3, 7, and 26 years after the disturbance to assess macrofauna, invertebrate megafauna and fish density and diversity. We used this unique abyssal faunal time series to develop carbon-based food web models for each point in the time series using the linear inverse modeling approach for sediments subjected to two disturbance levels: (1) outside the plough tracks; not directly disturbed by plough, but probably suffered from additional sedimentation; and (2) inside the plough tracks. Total faunal carbon stock was always higher outside plough tracks compared with inside plough tracks. After 26 years, the carbon stock inside the plough tracks was 54% of the carbon stock outside plough tracks. Deposit feeders were least affected by the disturbance, with modeled respiration, external predation, and excretion rates being reduced by only 2.6% inside plough tracks compared with outside plough tracks after 26 years. In contrast, the respiration rate of filter and suspension feeders was 79.5% lower in the plough tracks after 26 years. The "total system throughput" (T..), i.e., the total sum of modeled carbon flows in the food web, was higher throughout the time series outside plough tracks compared with the corresponding inside plough tracks area and was lowest inside plough tracks directly after the disturbance (8.63 × 10−3±1.58 × 10−5mmolCm−2d−1). Even 26 years after the DISCOL disturbance, the discrepancy of T.. between outside and inside plough tracks was still 56%. Hence, C cycling within the faunal compartments of an abyssal plain ecosystem remains reduced 26 years after physical disturbance, and a longer period is required for the system to recover from such a small-scale sediment disturbance experiment.

Description: Highlights • Seafloor geomorphology was important in the structuring of abyssal megafauna. • Differences in megafaunal community ecology were found between all landscape types. • Lower megafauna density & diversity in a bathymetric valley than flat and ridge areas. • Large samples, collected by AUV, were required to make robust ecological conclusions. The potential for imminent polymetallic nodule mining in the Clarion Clipperton Fracture Zone (CCZ) has attracted considerable scientific and public attention. This concern stems from both the extremely large seafloor areas that may be impacted by mining, and the very limited knowledge of the fauna and ecology of this region. The environmental factors regulating seafloor ecology are still very poorly understood. In this study, we focus on megafaunal ecology in the proposed conservation zone ‘Area of Particular Environmental Interest 6′ (study area centred 17°16′N, 122°55′W). We employ bathymetric data to objectively define three landscape types in the area (a level bottom Flat, an elevated Ridge, a depressed Trough; water depth 3950–4250 m) that are characteristic of the wider CCZ. We use direct seabed sampling to characterise the sedimentary environment in each landscape, detecting no statistically significant differences in particle size distributions or organic matter content. Additional seafloor characteristics and data on both the metazoan and xenophyophore components of the megafauna were derived by extensive photographic survey from an autonomous underwater vehicle. Image data revealed that there were statistically significant differences in seafloor cover by nodules and in the occurrence of other hard substrata habitat between landscapes. Statistically significant differences in megafauna standing stock, functional structuring, diversity, and faunal composition were detected between landscapes. The Flat and Ridge areas exhibited a significantly higher standing stock and a distinct assemblage composition compared to the Trough. Geomorphological variations, presumably regulating local bottom water flows and the occurrence of nodule and xenophyophore test substrata, between study areas may be the mechanism driving these assemblage differences. We also used these data to assess the influence of sampling unit size on the estimation of ecological parameters. We discuss these results in the contexts of regional benthic ecology and the appropriate management of potential mining activities in the CCZ and elsewhere in the deep ocean.

Description: 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.

Description: The potential for imminent abyssal polymetallic nodule exploitation has raised considerable scientific attention. The interface between the targeted nodule resource and sediment in this unusual mosaic habitat promotes the development of some of the most biologically diverse communities in the abyss. However, the ecology of these remote ecosystems is still poorly understood, so it is unclear to what extent and timescale these ecosystems will be affected by, and could recover from, mining disturbance. Using data inferred from seafloor photo-mosaics, we show that the effects of simulated mining impacts, induced during the “DISturbance and reCOLonization experiment” (DISCOL) conducted in 1989, were still evident in the megabenthos of the Peru Basin after 26 years. Suspension-feeder presence remained significantly reduced in disturbed areas, while deposit-feeders showed no diminished presence in disturbed areas, for the first time since the experiment began. Nevertheless, we found significantly lower heterogeneity diversity in disturbed areas and markedly distinct faunal compositions along different disturbance levels. If the results of this experiment at DISCOL can be extrapolated to the Clarion-Clipperton Zone, the impacts of polymetallic nodule mining there may be greater than expected, and could potentially lead to an irreversible loss of some ecosystem functions, especially in directly disturbed areas.

Description: Abyssal polymetallic nodule fields constitute an unusual deep-sea habitat. The mix of soft sediment and the hard substratum provided by nodules increases the complexity of these environments. Hard substrata typically support a very distinct fauna to that of seabed sediments, and its presence can play a major role in the structuring of benthic assemblages. We assessed the influence of seafloor nodule cover on the megabenthos of a marine conservation area (area of particular environmental interest 6) in the Clarion Clipperton Zone (3950–4250 m water depth) using extensive photographic surveys from an autonomous underwater vehicle. Variations in nodule cover (1–20%) appeared to exert statistically significant differences in faunal standing stocks, some biological diversity attributes, faunal composition, functional group composition, and the distribution of individual species. The standing stock of both the metazoan fauna and the giant protists (xenophyophores) doubled with a very modest initial increase in nodule cover (from 1% to 3%). Perhaps contrary to expectation, we detected little if any substantive variation in biological diversity along the nodule cover gradient. Faunal composition varied continuously along the nodule cover gradient. We discuss these results in the context of potential seabed-mining operations and the associated sustainable management and conservation plans. We note in particular that successful conservation actions will likely require the preservation of areas comprising the full range of nodule cover and not just the low cover areas that are least attractive to mining.

Description: 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.

Description: Highlights • All known observations for Area of Particular Environmental Interest 6 presented. • Assess morphology, sediments, nodules, oceanography, biogeochemistry and ecology. • APEI-6 partially representative of nearby exploration areas yet clear differences. • Present scientific synthesis and management implications for Clarion Clipperton Zone. 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.