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

Author:

Baco Amy R.1,Ross Rebecca2ORCID,Althaus Franziska3,Amon Diva45,Bridges Amelia E. H.6,Brix Saskia7ORCID,Buhl-Mortensen Pål2,Colaco Ana8ORCID,Carreiro-Silva Marina8,Clark Malcolm R.9,Du Preez Cherisse1011,Franken Mari-Lise12,Gianni Matthew13,Gonzalez-Mirelis Genoveva2,Hourigan Thomas14ORCID,Howell Kerry6,Levin Lisa A.15,Lindsay Dhugal J.16ORCID,Molodtsova Tina N.17ORCID,Morgan Nicole1,Morato Telmo8,Mejia-Mercado Beatriz E.1,O’Sullivan David18,Pearman Tabitha19,Price David82021ORCID,Robert Katleen22,Robson Laura23,Rowden Ashley A.924,Taylor James7,Taylor Michelle25,Victorero Lissette2627,Watling Les28,Williams Alan3,Xavier Joana R.2930ORCID,Yesson Chris31ORCID

Affiliation:

1. Earth, Ocean, and Atmospheric Sciences, Florida State University, Tallahassee, FL, United States

2. Institute of Marine Research, Bergen, Norway

3. CSIRO Environment, Hobart, Australia

4. SpeSeas, D’Abadie, Trinidad and Tobago

5. Marine Science Institute, University of California, Santa Barbara, Santa Barbara, California, United States

6. School of Biological and Marine Science, University of Plymouth, Plymouth, United Kingdom

7. Senckenberg am Meer, German Center for Marine Biodiversity Research (DZMB), Senckenberg Nature Research Society, Hamburg, Germany

8. Okeanos-University of the Azores, Horta, Portugal

9. National Institute of Water & Atmospheric Research, Wellington, New Zealand

10. Fisheries and Oceans Canada, Sidney, Canada

11. University of Victoria, Victoria, British Columbia, Canada

12. University of Cape Town, Cape Town, South Africa

13. Deep-Sea Conservation Coalition, Amsterdam, Netherlands

14. National Oceanic & Atmospheric Administration, Washington, D.C., United States

15. Scripps Institution of Oceanography, University of California, San Diego, California, United States

16. Japan Agency for Marine-Earth Science and Technology, Yokosuka, Japan

17. Shirshov Institute of Oceanology RAS, Moscow, Russia

18. INFOMAR & Marine Institute, Galway, Ireland

19. South Atlantic Environmental Research Institute, Stanley, Falkland Islands

20. The National Oceanography Centre, Southampton, United Kingdom

21. University of Southampton, Southampton, United Kingdom

22. Fisheries and Marine Institute of Memorial University, St. John’s, Canada

23. Joint Nature Conservation Committee, Peterborough, United Kingdom

24. Victoria University of Wellington, Wellington, New Zealand

25. School of Life Sciences, University of Essex, Essex, United Kingdom

26. Norwegian Institute for Water Research, Bergen, Norway

27. University of Aveiro, CESAM, Aveiro, Portugal

28. University of Hawaii at Manoa, Honolulu, United States

29. Department of Biological Sciences, University of Bergen, Bergen, Norway

30. CIIMAR, Interdisciplinary Centre of Marine and Environmental Research, CIIMAR, University of Porto, Matsosinhos, Portugal

31. Zoological Society of London, London, United Kingdom

Abstract

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.

Publisher

PeerJ

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

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