Megafauna community assessment of polymetallic-nodule fields with cameras: platform and methodology comparison
<p>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 asses...
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doaj-c566140a901d4e03bbce3c89d0b475c72020-11-25T03:08:44ZengCopernicus PublicationsBiogeosciences1726-41701726-41892020-06-01173115313310.5194/bg-17-3115-2020Megafauna community assessment of polymetallic-nodule fields with cameras: platform and methodology comparisonT. Schoening0A. Purser1D. Langenkämper2I. Suck3J. Taylor4D. Cuvelier5D. Cuvelier6L. Lins7E. Simon-Lledó8Y. Marcon9Y. Marcon10D. O. B. Jones11T. Nattkemper12K. Köser13M. Zurowietz14J. Greinert15J. Gomes-Pereira16J. Gomes-Pereira17GEOMAR Helmholtz Centre for Ocean Research, Kiel, GermanyAlfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, GermanyBiodata Mining Group, Bielefeld University, Bielefeld, GermanyGEOMAR Helmholtz Centre for Ocean Research, Kiel, GermanySenckenberg am Meer, Wilhelmshaven, GermanyMARE – Marine and Environmental Sciences Centre, IMAR – Instituto do Mar, Horta, PortugalCentro OKEANOS, Universidade dos Açores, Horta, PortugalDepartment of Biology, Ghent University, Ghent, BelgiumNational Oceanography Centre, Southampton, UKUniversity of Bremen, MARUM Center for Marine Environmental Sciences, Bremen, GermanyDepartment of Geosciences, University of Bremen, Bremen, GermanyNational Oceanography Centre, Southampton, UKBiodata Mining Group, Bielefeld University, Bielefeld, GermanyGEOMAR Helmholtz Centre for Ocean Research, Kiel, GermanyBiodata Mining Group, Bielefeld University, Bielefeld, GermanyGEOMAR Helmholtz Centre for Ocean Research, Kiel, GermanyCentro OKEANOS, Universidade dos Açores, Horta, PortugalNaturalist, Lda., Atlantic Naturalist Association, Horta, Portugal<p>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.</p>https://www.biogeosciences.net/17/3115/2020/bg-17-3115-2020.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
T. Schoening A. Purser D. Langenkämper I. Suck J. Taylor D. Cuvelier D. Cuvelier L. Lins E. Simon-Lledó Y. Marcon Y. Marcon D. O. B. Jones T. Nattkemper K. Köser M. Zurowietz J. Greinert J. Gomes-Pereira J. Gomes-Pereira |
spellingShingle |
T. Schoening A. Purser D. Langenkämper I. Suck J. Taylor D. Cuvelier D. Cuvelier L. Lins E. Simon-Lledó Y. Marcon Y. Marcon D. O. B. Jones T. Nattkemper K. Köser M. Zurowietz J. Greinert J. Gomes-Pereira J. Gomes-Pereira Megafauna community assessment of polymetallic-nodule fields with cameras: platform and methodology comparison Biogeosciences |
author_facet |
T. Schoening A. Purser D. Langenkämper I. Suck J. Taylor D. Cuvelier D. Cuvelier L. Lins E. Simon-Lledó Y. Marcon Y. Marcon D. O. B. Jones T. Nattkemper K. Köser M. Zurowietz J. Greinert J. Gomes-Pereira J. Gomes-Pereira |
author_sort |
T. Schoening |
title |
Megafauna community assessment of polymetallic-nodule fields with cameras: platform and methodology comparison |
title_short |
Megafauna community assessment of polymetallic-nodule fields with cameras: platform and methodology comparison |
title_full |
Megafauna community assessment of polymetallic-nodule fields with cameras: platform and methodology comparison |
title_fullStr |
Megafauna community assessment of polymetallic-nodule fields with cameras: platform and methodology comparison |
title_full_unstemmed |
Megafauna community assessment of polymetallic-nodule fields with cameras: platform and methodology comparison |
title_sort |
megafauna community assessment of polymetallic-nodule fields with cameras: platform and methodology comparison |
publisher |
Copernicus Publications |
series |
Biogeosciences |
issn |
1726-4170 1726-4189 |
publishDate |
2020-06-01 |
description |
<p>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.</p> |
url |
https://www.biogeosciences.net/17/3115/2020/bg-17-3115-2020.pdf |
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