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  • OceanRep  (13)
  • Frontiers  (6)
  • Nature Research  (5)
  • AMS (American Meteorological Society)  (2)
  • Springer Nature
  • 1
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    Spread, Behavior, and Ecosystem Consequences of Conventional Munitions Compounds in Coastal Marine Waters (2018)
    Frontiers
    In:  Frontiers in Marine Science, 5 . Art.Nr. 141.
    Details
    Publication Date: 2021-04-23
    Description: Coastal marine environments are contaminated globally with a vast quantity of unexploded ordnance and munitions from intentional disposal. These munitions contain organic explosive compounds as well as a variety of metals, and represent point sources of chemical pollution to marine waters. Most underwater munitions originate from World Wars at the beginning of the twentieth century, and metal munitions housings have been impacted by extensive corrosion over the course of the following decades. As a result, the risk of munitions-related contaminant release to the water column is increasing. The behavior of munitions compounds is well-characterized in terrestrial systems and groundwater, but is only poorly understood in marine systems. Organic explosive compounds, primarily nitroaromatics and nitramines, can be degraded or transformed by a variety of biotic and abiotic mechanisms. These reaction products exhibit a range in biogeochemical characteristics such as sorption by particles and sediments, and variable environmental behavior as a result. The reaction products often exhibit increased toxicity to biological receptors and geochemical controls like sorption can limit this exposure. Environmental samples typically show low concentrations of munitions compounds in water and sediments (on the order of ng/L and μg/kg, respectively), and ecological risk appears generally low. Nonetheless, recent work demonstrates the possibility of sub-lethal genetic and metabolic effects. This review evaluates the state of knowledge on the occurrence, fate, and effect of munition-related chemical contaminants in the marine environment. There remain a number of knowledge gaps that limit our understanding of munitions-related contaminant spread and effect, and the need for additional work is made all the more urgent by increasing risk of release to the environment.
    Type: Article , PeerReviewed
    Format: text
    DOI: 10.3389/fmars.2018.00141
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 2
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    Compact-Morphology-based poly-metallic Nodule Delineation (2017)
    Nature Research
    In:  Scientific Reports, 7 (13338 ).
    Details
    Publication Date: 2020-06-18
    Description: Poly-metallic nodules are a marine resource considered for deep sea mining. Assessing nodule abundance is of interest for mining companies and to monitor potential environmental impact. Optical seafloor imaging allows quantifying poly-metallic nodule abundance at spatial scales from centimetres to square kilometres. Towed cameras and diving robots acquire high-resolution imagery that allow detecting individual nodules and measure their sizes. Spatial abundance statistics can be computed from these size measurements, providing e.g. seafloor coverage in percent and the nodule size distribution. Detecting nodules requires segmentation of nodule pixels from pixels showing sediment background. Semi-supervised pattern recognition has been proposed to automate this task. Existing nodule segmentation algorithms employ machine learning that trains a classifier to segment the nodules in a high-dimensional feature space. Here, a rapid nodule segmentation algorithm is presented. It omits computation-intense feature-based classification and employs image processing only. It exploits a nodule compactness heuristic to delineate individual nodules. Complex machine learning methods are avoided to keep the algorithm simple and fast. The algorithm has successfully been applied to different image datasets. These data sets were acquired by different cameras, camera platforms and in varying illumination conditions. Their successful analysis shows the broad applicability of the proposed method.
    Type: Article , PeerReviewed
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    DOI: 10.1038/s41598-017-13335-x
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 3
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    An acquisition, curation and management workflow for sustainable, terabyte-scale marine image analysis (2018)
    Nature Research
    In:  Scientific Data, 5 (180181).
    Details
    Publication Date: 2021-03-19
    Description: Optical imaging is a common technique in ocean research. Diving robots, towed cameras, drop-cameras and TV-guided sampling gear: all produce image data of the underwater environment. Technological advances like 4K cameras, autonomous robots, high-capacity batteries and LED lighting now allow systematic optical monitoring at large spatial scale and shorter time but with increased data volume and velocity. Volume and velocity are further increased by growing fleets and emerging swarms of autonomous vehicles creating big data sets in parallel. This generates a need for automated data processing to harvest maximum information. Systematic data analysis benefits from calibrated, geo-referenced data with clear metadata description, particularly for machine vision and machine learning. Hence, the expensive data acquisition must be documented, data should be curated as soon as possible, backed up and made publicly available. Here, we present a workflow towards sustainable marine image analysis. We describe guidelines for data acquisition, curation and management and apply it to the use case of a multi-terabyte deep-sea data set acquired by an autonomous underwater vehicle.
    Type: Article , PeerReviewed
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    DOI: 10.1038/sdata.2018.181
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 4
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    Biological effects 26 years after simulated deep-sea mining (2019)
    Nature Research
    In:  Scientific Reports, 9 (Article 8040).
    Details
    Publication Date: 2022-01-31
    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.
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
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    DOI: 10.1038/s41598-019-44492-w
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 5
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    Numerical Simulation of Deep-Sea Sediment Transport Induced by a Dredge Experiment in the Northeastern Pacific Ocean (2021)
    Frontiers
    Details
    Publication Date: 2024-02-07
    Description: Predictability of the dispersion of sediment plumes induced by potential deep-sea mining activities is still very limited due to operational limitations on in-situ observations required for a thorough validation and calibration of numerical models. Here we report on a plume dispersion experiment carried out in the German license area for the exploration of polymetallic nodules in the northeastern tropical Pacific Ocean in 4,200 m water depth. The dispersion of a sediment plume induced by a small-scale dredge experiment in April 2019 was investigated numerically by employing a sediment transport module coupled to a high-resolution hydrodynamic regional ocean model. Various aspects including sediment characteristics and ocean hydrodynamics were examined to obtain the best statistical agreement between sensor-based observations and model results. Results show that the model is capable of reproducing suspended sediment concentration and redeposition patterns observed during the dredge experiment. Due to a strong southward current during the dredging, the model predicts no sediment deposition and plume dispersion north of the dredging tracks. The sediment redeposition thickness reaches up to 9 mm directly next to the dredging tracks and 0.07 mm in about 320 m away from the dredging center. The model results suggest that seabed topography and variable sediment release heights above the seafloor cause significant changes especially for the low sedimentation pattern in the far-field area. Near-bottom mixing is expected to strongly influence vertical transport of suspended sediment.
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
    Format: text
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 6
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    An automated image-based workflow for detecting megabenthic fauna in optical images with examples from the Clarion–Clipperton Zone (2023)
    Nature Research
    Details
    Publication Date: 2024-02-07
    Description: Recent advances in optical underwater imaging technologies enable the acquisition of huge numbers of high-resolution seafloor images during scientific expeditions. While these images contain valuable information for non-invasive monitoring of megabenthic fauna, flora and the marine ecosystem, traditional labor-intensive manual approaches for analyzing them are neither feasible nor scalable. Therefore, machine learning has been proposed as a solution, but training the respective models still requires substantial manual annotation. Here, we present an automated image-based workflow for Megabenthic Fauna Detection with Faster R-CNN (FaunD-Fast). The workflow significantly reduces the required annotation effort by automating the detection of anomalous superpixels, which are regions in underwater images that have unusual properties relative to the background seafloor. The bounding box coordinates of the detected anomalous superpixels are proposed as a set of weak annotations, which are then assigned semantic morphotype labels and used to train a Faster R-CNN object detection model. We applied this workflow to example underwater images recorded during cruise SO268 to the German and Belgian contract areas for Manganese-nodule exploration, within the Clarion–Clipperton Zone (CCZ). A performance assessment of our FaunD-Fast model showed a mean average precision of 78.1% at an intersection-over-union threshold of 0.5, which is on a par with competing models that use costly-to-acquire annotations. In more detail, the analysis of the megafauna detection results revealed that ophiuroids and xenophyophores were among the most abundant morphotypes, accounting for 62% of all the detections within the surveyed area. Investigating the regional differences between the two contract areas further revealed that both megafaunal abundance and diversity was higher in the shallower German area, which might be explainable by the higher food availability in form of sinking organic material that decreases from east-to-west across the CCZ. Since these findings are consistent with studies based on conventional image-based methods, we conclude that our automated workflow significantly reduces the required human effort, while still providing accurate estimates of megafaunal abundance and their spatial distribution. The workflow is thus useful for a quick but objective generation of baseline information to enable monitoring of remote benthic ecosystems.
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
    Format: text
    Format: archive
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 7
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    Quantitatively Monitoring Bubble-Flow at a Seep Site Offshore Oregon: Field Trials and Methodological Advances for Parallel Optical and Hydroacoustical Measurements (2022)
    Frontiers
    Details
    Publication Date: 2024-02-07
    Description: Two lander-based devices, the Bubble-Box and GasQuant-II, were used to investigate the spatial and temporal variability and total gas flow rates of a seep area offshore Oregon, United States. The Bubble-Box is a stereo camera–equipped lander that records bubbles inside a rising corridor with 80 Hz, allowing for automated image analyses of bubble size distributions and rising speeds. GasQuant is a hydroacoustic lander using a horizontally oriented multibeam swath to record the backscatter intensity of bubble streams passing the swath plain. The experimental set up at the Astoria Canyon site at a water depth of about 500 m aimed at calibrating the hydroacoustic GasQuant data with the visual Bubble-Box data for a spatial and temporal flow rate quantification of the site. For about 90 h in total, both systems were deployed simultaneously and pressure and temperature data were recorded using a CTD as well. Detailed image analyses show a Gaussian-like bubble size distribution of bubbles with a radius of 0.6–6 mm (mean 2.5 mm, std. dev. 0.25 mm); this is very similar to other measurements reported in the literature. Rising speeds ranged from 15 to 37 cm/s between 1- and 5-mm bubble sizes and are thus, in parts, slightly faster than reported elsewhere. Bubble sizes and calculated flow rates are rather constant over time at the two monitored bubble streams. Flow rates of these individual bubble streams are in the range of 544–1,278 mm 3 /s. One Bubble-Box data set was used to calibrate the acoustic backscatter response of the GasQuant data, enabling us to calculate a flow rate of the ensonified seep area (∼1,700 m 2 ) that ranged from 4.98 to 8.33 L/min (5.38 × 10 6 to 9.01 × 10 6 CH 4 mol/year). Such flow rates are common for seep areas of similar size, and as such, this location is classified as a normally active seep area. For deriving these acoustically based flow rates, the detailed data pre-processing considered echogram gridding methods of the swath data and bubble responses at the respective water depth. The described method uses the inverse gas flow quantification approach and gives an in-depth example of the benefits of using acoustic and optical methods in tandem.
    Type: Article , PeerReviewed
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 8
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    Inter-Comparison of the Spatial Distribution of Methane in the Water Column From Seafloor Emissions at Two Sites in the Western Black Sea Using a Multi-Technique Approach (2021)
    Frontiers
    Details
    Publication Date: 2024-02-07
    Description: Understanding the dynamics and fate of methane (CH 4 ) release from oceanic seepages on margins and shelves into the water column, and quantifying the budget of its total discharge at different spatial and temporal scales, currently represents a major scientific undertaking. Previous works on the fate of methane escaping from the seafloor underlined the challenge in both, estimating its concentration distribution and identifying gradients. In April 2019, the Envri Methane Cruise has been conducted onboard the R/V Mare Nigrum in the Western Black Sea to investigate two shallow methane seep sites at ∼120 m and ∼55 m water depth. Dissolved CH 4 measurements were conducted with two continuous in-situ sensors: a membrane inlet laser spectrometer (MILS) and a commercial methane sensor (METS) from Franatech GmbH. Additionally, discrete water samples were collected from CTD-Rosette deployment and standard laboratory methane analysis was performed by gas chromatography coupled with either purge-and-trap or headspace techniques. The resulting vertical profiles (from both in situ and discrete water sample measurements) of dissolved methane concentration follow an expected exponential dissolution function at both sites. At the deeper site, high dissolved methane concentrations are detected up to ∼45 m from the seabed, while at the sea surface dissolved methane was in equilibrium with the atmospheric concentration. At the shallower site, sea surface CH 4 concentrations were four times higher than the expected equilibrium value. Our results seem to support that methane may be transferred from the sea to the atmosphere, depending on local water depths. In accordance with previous studies, the shallower the water, the more likely is a sea-to-atmosphere transport of methane. High spatial resolution surface data also support this hypothesis. Well localized methane enriched waters were found near the surface at both sites, but their locations appear to be decoupled with the ones of the seafloor seepages. This highlights the need of better understanding the processes responsible for the transport and transformation of the dissolved methane in the water column, especially in stratified water masses like in the Black Sea.
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
    Format: text
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 9
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    Monitoring of Anthropogenic Sediment Plumes in the Clarion-Clipperton Zone, NE Equatorial Pacific Ocean (2022)
    Frontiers
    Details
    Publication Date: 2024-02-07
    Description: The abyssal seafloor in the Clarion-Clipperton Zone (CCZ) in the NE Pacific hosts the largest abundance of polymetallic nodules in the deep sea and is being targeted as an area for potential deep-sea mining. During nodule mining, seafloor sediment will be brought into suspension by mining equipment, resulting in the formation of sediment plumes, which will affect benthic and pelagic life not naturally adapted to any major sediment transport and deposition events. To improve our understanding of sediment plume dispersion and to support the development of plume dispersion models in this specific deep-sea area, we conducted a small-scale, 12-hour disturbance experiment in the German exploration contract area in the CCZ using a chain dredge. Sediment plume dispersion and deposition was monitored using an array of optical and acoustic turbidity sensors and current meters placed on platforms on the seafloor, and by visual inspection of the seafloor before and after dredge deployment. We found that seafloor imagery could be used to qualitatively visualise the redeposited sediment up to a distance of 100 m from the source, and that sensors recording optical and acoustic backscatter are sensitive and adequate tools to monitor the horizontal and vertical dispersion of the generated sediment plume. Optical backscatter signals could be converted into absolute mass concentration of suspended sediment to provide quantitative data on sediment dispersion. Vertical profiles of acoustic backscatter recorded by current profilers provided qualitative insight into the vertical extent of the sediment plume. Our monitoring setup proved to be very useful for the monitoring of this small-scale experiment and can be seen as an exemplary strategy for monitoring studies of future, upscaled mining trials. We recommend that such larger trials include the use of AUVs for repeated seafloor imaging and water column plume mapping (optical and acoustical), as well as the use of in-situ particle size sensors and/or particle cameras to better constrain the effect of suspended particle aggregation on optical and acoustic backscatter signals.
    Type: Article , PeerReviewed
    Format: text
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 10
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    Implementation of an automated workflow for image-based seafloor classification with examples from manganese-nodule covered seabed areas in the Central Pacific Ocean (2022)
    Nature Research
    Details
    Publication Date: 2024-02-07
    Description: Mapping and monitoring of seafloor habitats are key tasks for fully understanding ocean ecosystems and resilience, which contributes towards sustainable use of ocean resources. Habitat mapping relies on seafloor classification typically based on acoustic methods, and ground truthing through direct sampling and optical imaging. With the increasing capabilities to record high-resolution underwater images, manual approaches for analyzing these images to create seafloor classifications are no longer feasible. Automated workflows have been proposed as a solution, in which algorithms assign pre-defined seafloor categories to each image. However, in order to provide consistent and repeatable analysis, these automated workflows need to address e.g., underwater illumination artefacts, variances in resolution and class-imbalances, which could bias the classification. Here, we present a generic implementation of an Automated and Integrated Seafloor Classification Workflow (AI-SCW). The workflow aims to classify the seafloor into habitat categories based on automated analysis of optical underwater images with only minimal amount of human annotations. AI-SCW incorporates laser point detection for scale determination and color normalization. It further includes semi-automatic generation of the training data set for fitting the seafloor classifier. As a case study, we applied the workflow to an example seafloor image dataset from the Belgian and German contract areas for Manganese-nodule exploration in the Pacific Ocean. Based on this, we provide seafloor classifications along the camera deployment tracks, and discuss results in the context of seafloor multibeam bathymetry. Our results show that the seafloor in the Belgian area predominantly comprises densely distributed nodules, which are intermingled with qualitatively larger-sized nodules at local elevations and within depressions. On the other hand, the German area primarily comprises nodules that only partly cover the seabed, and these occur alongside turned-over sediment (artificial seafloor) that were caused by the settling plume following a dredging experiment conducted in the area.
    Type: Article , PeerReviewed
    Format: text
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    OceanRep: Article in a Scientific Journal - peer-reviewed
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