Articles | Volume 17, issue 12
https://doi.org/10.5194/bg-17-3115-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/bg-17-3115-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
19 Jun 2020
Research article |
| 19 Jun 2020
| 19 Jun 2020
Megafauna community assessment of polymetallic-nodule fields with cameras: platform and methodology comparison
GEOMAR Helmholtz Centre for Ocean Research, Kiel, Germany
Autun Purser
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany
Daniel Langenkämper
Biodata Mining Group, Bielefeld University, Bielefeld, Germany
Inken Suck
GEOMAR Helmholtz Centre for Ocean Research, Kiel, Germany
James Taylor
Senckenberg am Meer, Wilhelmshaven, Germany
Daphne Cuvelier
MARE – Marine and Environmental Sciences Centre, IMAR – Instituto do Mar, Horta, Portugal
Centro OKEANOS, Universidade dos Açores, Horta, Portugal
Lidia Lins
Department of Biology, Ghent University, Ghent, Belgium
Erik Simon-Lledó
National Oceanography Centre, Southampton, UK
Yann Marcon
University of Bremen, MARUM Center for Marine Environmental Sciences, Bremen, Germany
Department of Geosciences, University of Bremen, Bremen, Germany
Daniel O. B. Jones
National Oceanography Centre, Southampton, UK
Tim Nattkemper
Biodata Mining Group, Bielefeld University, Bielefeld, Germany
Kevin Köser
GEOMAR Helmholtz Centre for Ocean Research, Kiel, Germany
Martin Zurowietz
Biodata Mining Group, Bielefeld University, Bielefeld, Germany
Jens Greinert
GEOMAR Helmholtz Centre for Ocean Research, Kiel, Germany
Jose Gomes-Pereira
Naturalist, Lda., Atlantic Naturalist Association, Horta, Portugal
Centro OKEANOS, Universidade dos Açores, Horta, Portugal
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Cited
25 citations as recorded by crossref.
- The COSMUS expedition: seafloor images and acoustic bathymetric data from the PS124 expedition to the southern Weddell Sea, Antarctica A. Purser et al. 10.5194/essd-14-3635-2022
- Unsupervised Knowledge Transfer for Object Detection in Marine Environmental Monitoring and Exploration M. Zurowietz & T. Nattkemper 10.1109/ACCESS.2020.3014441
- Importance of Spatial Autocorrelation in Machine Learning Modeling of Polymetallic Nodules, Model Uncertainty and Transferability at Local Scale I. Gazis & J. Greinert 10.3390/min11111172
- Deep-Sea Mining—A Bibliometric Analysis of Research Focus, Publishing Structures, International and Inter-Institutional Cooperation R. Kleiv & M. Thornhill 10.3390/min12111383
- Improving coral monitoring by reducing variability and bias in cover estimates from seabed images E. Curtis et al. 10.1016/j.pocean.2024.103214
- Deepdive: Leveraging Pre-trained Deep Learning for Deep-Sea ROV Biota Identification in the Great Barrier Reef R. Deo et al. 10.1038/s41597-024-03766-3
- Comparing the Performance of a Remotely Operated Vehicle, a Drop Camera, and a Trawl in Capturing Deep-Sea Epifaunal Abundance and Diversity S. de Mendonça & A. Metaxas 10.3389/fmars.2021.631354
- Role of polymetallic-nodule dependent fauna on carbon cycling in the eastern Clarion-Clipperton Fracture Zone (Pacific) T. Stratmann 10.3389/fmars.2023.1151442
- Taxonomic assessment of deep-sea decapod crustaceans collected from polymetallic nodule fields of the East Pacific Ocean using an integrative approach M. Christodoulou et al. 10.1007/s12526-022-01284-2
- A review of megafauna diversity and abundance in an exploration area for polymetallic nodules in the eastern part of the Clarion Clipperton Fracture Zone (North East Pacific), and implications for potential future deep-sea mining in this area K. Uhlenkott et al. 10.1007/s12526-022-01326-9
- Underwater Animal Identification and Classification Using a Hybrid Classical-Quantum Algorithm S. Pravin et al. 10.1109/ACCESS.2023.3343120
- An automated image-based workflow for detecting megabenthic fauna in optical images with examples from the Clarion–Clipperton Zone B. Mbani et al. 10.1038/s41598-023-35518-5
- Deep-sea benthic structures and substrate types influence the distribution of functional groups in the Wallaby-Zenith Fracture Zone (East Indian Ocean) Y. Niyazi et al. 10.1016/j.dsr.2024.104268
- The megafauna community from an abyssal area of interest for mining of polymetallic nodules B. De Smet et al. 10.1016/j.dsr.2021.103530
- Assessing plume impacts caused by polymetallic nodule mining vehicles P. Weaver et al. 10.1016/j.marpol.2022.105011
- Seabed video and still images from the northern Weddell Sea and the western flanks of the Powell Basin A. Purser et al. 10.5194/essd-13-609-2021
- Deep learning–assisted biodiversity assessment in deep-sea benthic megafauna communities: a case study in the context of polymetallic nodule mining D. Cuvelier et al. 10.3389/fmars.2024.1366078
- Making marine image data FAIR T. Schoening et al. 10.1038/s41597-022-01491-3
- Discovery of Paleodictyon in the Indian Ocean K. Gerdes et al. 10.1007/s12526-021-01231-7
- Short and decadal impacts of seafloor physical perturbation on the abundances of Lebensspuren ‘traces of life’ in the Peru Basin manganese nodule province I. Vornsand et al. 10.1007/s12526-024-01405-z
- Deep learning based deep-sea automatic image enhancement and animal species classification V. Lopez-Vazquez et al. 10.1186/s40537-023-00711-w
- Integrating Multidisciplinary Observations in Vent Environments (IMOVE): Decadal Progress in Deep-Sea Observatories at Hydrothermal Vents M. Matabos et al. 10.3389/fmars.2022.866422
- Evidence for a single population expansion event across 24,000 km: the case of the deep-sea scavenging amphipod Abyssorchomene distinctus D. Dupont et al. 10.1007/s10750-023-05447-5
- Microbes as marine habitat formers and ecosystem engineers R. Danovaro et al. 10.1038/s41559-024-02407-7
- Recovery of Paleodictyon patterns after simulated mining activity on Pacific nodule fields L. Boehringer et al. 10.1007/s12526-021-01237-1
25 citations as recorded by crossref.
- The COSMUS expedition: seafloor images and acoustic bathymetric data from the PS124 expedition to the southern Weddell Sea, Antarctica A. Purser et al. 10.5194/essd-14-3635-2022
- Unsupervised Knowledge Transfer for Object Detection in Marine Environmental Monitoring and Exploration M. Zurowietz & T. Nattkemper 10.1109/ACCESS.2020.3014441
- Importance of Spatial Autocorrelation in Machine Learning Modeling of Polymetallic Nodules, Model Uncertainty and Transferability at Local Scale I. Gazis & J. Greinert 10.3390/min11111172
- Deep-Sea Mining—A Bibliometric Analysis of Research Focus, Publishing Structures, International and Inter-Institutional Cooperation R. Kleiv & M. Thornhill 10.3390/min12111383
- Improving coral monitoring by reducing variability and bias in cover estimates from seabed images E. Curtis et al. 10.1016/j.pocean.2024.103214
- Deepdive: Leveraging Pre-trained Deep Learning for Deep-Sea ROV Biota Identification in the Great Barrier Reef R. Deo et al. 10.1038/s41597-024-03766-3
- Comparing the Performance of a Remotely Operated Vehicle, a Drop Camera, and a Trawl in Capturing Deep-Sea Epifaunal Abundance and Diversity S. de Mendonça & A. Metaxas 10.3389/fmars.2021.631354
- Role of polymetallic-nodule dependent fauna on carbon cycling in the eastern Clarion-Clipperton Fracture Zone (Pacific) T. Stratmann 10.3389/fmars.2023.1151442
- Taxonomic assessment of deep-sea decapod crustaceans collected from polymetallic nodule fields of the East Pacific Ocean using an integrative approach M. Christodoulou et al. 10.1007/s12526-022-01284-2
- A review of megafauna diversity and abundance in an exploration area for polymetallic nodules in the eastern part of the Clarion Clipperton Fracture Zone (North East Pacific), and implications for potential future deep-sea mining in this area K. Uhlenkott et al. 10.1007/s12526-022-01326-9
- Underwater Animal Identification and Classification Using a Hybrid Classical-Quantum Algorithm S. Pravin et al. 10.1109/ACCESS.2023.3343120
- An automated image-based workflow for detecting megabenthic fauna in optical images with examples from the Clarion–Clipperton Zone B. Mbani et al. 10.1038/s41598-023-35518-5
- Deep-sea benthic structures and substrate types influence the distribution of functional groups in the Wallaby-Zenith Fracture Zone (East Indian Ocean) Y. Niyazi et al. 10.1016/j.dsr.2024.104268
- The megafauna community from an abyssal area of interest for mining of polymetallic nodules B. De Smet et al. 10.1016/j.dsr.2021.103530
- Assessing plume impacts caused by polymetallic nodule mining vehicles P. Weaver et al. 10.1016/j.marpol.2022.105011
- Seabed video and still images from the northern Weddell Sea and the western flanks of the Powell Basin A. Purser et al. 10.5194/essd-13-609-2021
- Deep learning–assisted biodiversity assessment in deep-sea benthic megafauna communities: a case study in the context of polymetallic nodule mining D. Cuvelier et al. 10.3389/fmars.2024.1366078
- Making marine image data FAIR T. Schoening et al. 10.1038/s41597-022-01491-3
- Discovery of Paleodictyon in the Indian Ocean K. Gerdes et al. 10.1007/s12526-021-01231-7
- Short and decadal impacts of seafloor physical perturbation on the abundances of Lebensspuren ‘traces of life’ in the Peru Basin manganese nodule province I. Vornsand et al. 10.1007/s12526-024-01405-z
- Deep learning based deep-sea automatic image enhancement and animal species classification V. Lopez-Vazquez et al. 10.1186/s40537-023-00711-w
- Integrating Multidisciplinary Observations in Vent Environments (IMOVE): Decadal Progress in Deep-Sea Observatories at Hydrothermal Vents M. Matabos et al. 10.3389/fmars.2022.866422
- Evidence for a single population expansion event across 24,000 km: the case of the deep-sea scavenging amphipod Abyssorchomene distinctus D. Dupont et al. 10.1007/s10750-023-05447-5
- Microbes as marine habitat formers and ecosystem engineers R. Danovaro et al. 10.1038/s41559-024-02407-7
- Recovery of Paleodictyon patterns after simulated mining activity on Pacific nodule fields L. Boehringer et al. 10.1007/s12526-021-01237-1
Latest update: 26 Dec 2024
Short summary
Seafloor imaging is widely used in marine science and industry to explore and monitor areas of interest. The selection of the most appropriate imaging gear and deployment strategy depends on the target application. This paper compares imaging platforms like autonomous vehicles or towed camera frames and different deployment strategies of those in assessing the megafauna abundance of polymetallic-nodule fields. The deep-sea mining industry needs that information for robust impact monitoring.
Seafloor imaging is widely used in marine science and industry to explore and monitor areas of...
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