TY  - JOUR
JF  - PeerJ
PB  - PeerJ
A1  - Baco, Amy R
A1  - Ross, Rebecca
A1  - Althaus, Franziska
A1  - Amon, Diva
A1  - Bridges, Amelia EH
A1  - Brix, Saskia
A1  - Buhl-Mortensen, Pål
A1  - Colaco, Ana
A1  - Carreiro-Silva, Marina
A1  - Clark, Malcolm R
A1  - Du Preez, Cherisse
A1  - Franken, Mari-Lise
A1  - Gianni, Matthew
A1  - Gonzalez-Mirelis, Genoveva
A1  - Hourigan, Thomas
A1  - Howell, Kerry
A1  - Levin, Lisa A
A1  - Lindsay, Dhugal J
A1  - Molodtsova, Tina N
A1  - Morgan, Nicole
A1  - Morato, Telmo
A1  - Mejia-Mercado, Beatriz E
A1  - O'Sullivan, David
A1  - Pearman, Tabitha
A1  - Price, David
A1  - Robert, Katleen
A1  - Robson, Laura
A1  - Rowden, Ashley A
A1  - Taylor, James
A1  - Taylor, Michelle
A1  - Victorero, Lissette
A1  - Watling, Les
A1  - Williams, Alan
A1  - Xavier, Joana R
A1  - Yesson, Chris
KW  - Areas beyond national jurisdiction
KW  -  Deep-Sea imagery
KW  -  Significant adverse impacts
KW  -  VME indicator taxa
KW  -  Vulnerable marine ecosystems
KW  -  Ecosystem
KW  -  Conservation of Natural Resources
KW  -  Fisheries
VL  - 11
N1  - © 2023 Baco et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/).
UR  - https://doi.org/10.7717/peerj.16024
ID  - discovery10180515
N2  - 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.
AV  - public
Y1  - 2023///
TI  - Towards a scientific community consensus on designating Vulnerable Marine Ecosystems from imagery
ER  -