PeerJ (Oct 2023)

Towards a scientific community consensus on designating Vulnerable Marine Ecosystems from imagery

  • Amy R. Baco,
  • Rebecca Ross,
  • Franziska Althaus,
  • Diva Amon,
  • Amelia E. H. Bridges,
  • Saskia Brix,
  • Pål Buhl-Mortensen,
  • Ana Colaco,
  • Marina Carreiro-Silva,
  • Malcolm R. Clark,
  • Cherisse Du Preez,
  • Mari-Lise Franken,
  • Matthew Gianni,
  • Genoveva Gonzalez-Mirelis,
  • Thomas Hourigan,
  • Kerry Howell,
  • Lisa A. Levin,
  • Dhugal J. Lindsay,
  • Tina N. Molodtsova,
  • Nicole Morgan,
  • Telmo Morato,
  • Beatriz E. Mejia-Mercado,
  • David O’Sullivan,
  • Tabitha Pearman,
  • David Price,
  • Katleen Robert,
  • Laura Robson,
  • Ashley A. Rowden,
  • James Taylor,
  • Michelle Taylor,
  • Lissette Victorero,
  • Les Watling,
  • Alan Williams,
  • Joana R. Xavier,
  • Chris Yesson

DOI
https://doi.org/10.7717/peerj.16024
Journal volume & issue
Vol. 11
p. e16024

Abstract

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Management of deep-sea fisheries in areas beyond national jurisdiction by Regional Fisheries Management Organizations/Arrangements (RFMO/As) requires identification of areas with Vulnerable Marine Ecosystems (VMEs). Currently, fisheries data, including trawl and longline bycatch data, are used by many RFMO/As to inform the identification of VMEs. However, the collection of such data creates impacts and there is a need to collect non-invasive data for VME identification and monitoring purposes. Imagery data from scientific surveys satisfies this requirement, but there currently is no established framework for identifying VMEs from images. Thus, the goal of this study was to bring together a large international team to determine current VME assessment protocols and establish preliminary global consensus guidelines for identifying VMEs from images. An initial assessment showed a lack of consistency among RFMO/A regions regarding what is considered a VME indicator taxon, and hence variability in how VMEs might be defined. In certain cases, experts agreed that a VME could be identified from a single image, most often in areas of scleractinian reefs, dense octocoral gardens, multiple VME species’ co-occurrence, and chemosynthetic ecosystems. A decision flow chart is presented that gives practical interpretation of the FAO criteria for single images. To further evaluate steps of the flow chart related to density, data were compiled to assess whether scientists perceived similar density thresholds across regions. The range of observed densities and the density values considered to be VMEs varied considerably by taxon, but in many cases, there was a statistical difference in what experts considered to be a VME compared to images not considered a VME. Further work is required to develop an areal extent index, to include a measure of confidence, and to increase our understanding of what levels of density and diversity correspond to key ecosystem functions for VME indicator taxa. Based on our results, the following recommendations are made: 1. There is a need to establish a global consensus on which taxa are VME indicators. 2. RFMO/As should consider adopting guidelines that use imagery surveys as an alternative (or complement) to using bycatch and trawl surveys for designating VMEs. 3. Imagery surveys should also be included in Impact Assessments. And 4. All industries that impact the seafloor, not just fisheries, should use imagery surveys to detect and identify VMEs.

Keywords