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Biogeosciences An interactive open-access journal of the European Geosciences Union
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© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 14 Oct 2019

Submitted as: research article | 14 Oct 2019

Review status
A revised version of this preprint is currently under review for the journal BG.

Megafauna community assessment of polymetallic nodule fields with cameras: Platform and methodology comparison

Timm Schoening1, Autun Purser2, Daniel Langenkämper3, Inken Suck1, James Taylor4, Daphne Cuvelier5,6, Lidia Lins7, Erik Simon-Lledó8, Yann Marcon9, Daniel O. B. Jones8, Tim Nattkemper3, Kevin Köser1, Martin Zurowietz3, Jose Gomes-Pereira10,6, and Jens Greinert1 Timm Schoening et al.
  • 1GEOMAR Helmholtz Centre for Ocean Research, Kiel, Germany
  • 2Alfred Wegener Helmholtz Institute for Polar and Marine Studies, Bremerhaven, Germany
  • 3Bielefeld University, Bielefeld, Germany
  • 4Senckenberg, Wilhelmshaven, Germany
  • 5MARE – Marine and environmental sciences centre/IMAR – Instituto do Mar
  • 6Centro OKEANOS – Universidade dos Açores, Horta, Portugal
  • 7Ghent University, Ghent, Belgium
  • 8National Oceanography Centre, University of Southampton Waterfront Campus, Southampton, UK
  • 9MARUM, Bremen, Germany
  • 10Naturalist, Lda. and Atlantic Naturalist Association, Horta, Portugal

Abstract. With the mining of polymetallic nodules from the deep sea seafloor again approaching commercial viability, 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 larger fauna abundances to be derived from survey data, with repeat surveys of areas possible to allow time series data collection. At time of writing key underwater imaging platforms commonly used to map seafloor fauna abundances are Automated Underwater Vehicles (AUVs), Remotely Operated Vehicles (ROVs) and towed camera Ocean Floor Observation Systems (OFOSs). These systems are highly customisable, with mounted cameras, illumination systems and deployment protocols rapidly changing over time, and even within survey cruises. In this study 8 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 5 annotators to estimate the abundances of 20 fauna categories from the different data sets. 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, to ensure best monitoring practice, unambiguous rules on how camera-based monitoring surveys should be conducted, and with what equipment, must be put in place.

Timm Schoening et al.

Interactive discussion

Status: final response (author comments only)
Status: final response (author comments only)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

Timm Schoening et al.

Timm Schoening et al.


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Publications Copernicus
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 manuscript 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. Deepsea 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...