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.
Keywords:
Areas beyond national jurisdiction; Deep-Sea imagery; Significant adverse impacts; VME indicator taxa; Vulnerable marine ecosystems.
© 2023 Baco et al.
Publication types
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Research Support, Non-U.S. Gov't
MeSH terms
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Conservation of Natural Resources* / methods
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Ecosystem*
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Fisheries
Grants and funding
The Deep Ocean Stewardship Initiative (DOSI) provided a means to develop international collaborations such as this one. Publication costs for this manuscript were provided by the Arcadia Fund of the United Kingdom through the Deep Ocean Stewardship Initiative. Central North Pacific density data were collected using funding from NSF Grant numbers OCE-1334652 to Amy R. Baco and OCE-1334675 to Brendan Roark. Norwegian density data was collected by the MAREANO programme funded by the Norwegian Government. The Canadian Pacific seamount density data were collected during the NA097 expedition thanks to funding from the Northeast Pacific Seamount Expedition Partners (Fisheries and Oceans Canada, Ocean Networks Canada, the Council of the Haida Nation, Oceana Canada), with technical support from Ocean Exploration Trust. Irish density data was collected by the SeaRover project which was co-funded by the Irish Government and the European Maritime & Fisheries Fund 2014-2020. Density data were collected as part of RRS James Cook JC36 and JC125 (Whittard Canyon), RV Celtic Explorer CE14011 (SORBEH, Rockall Escarpment) and CE18008 (TOSCA, Charlie Gibbs Fracture Zone). CE JC-36 was funded through the Natural Environment Research Council and HERMIONE (EU FP7 project, Grant agreement 226354). JC125 was funded by the ERC CODEMAP project (Grant no 258482). The CE14011 and CE18008 expeditions were supported by the Irish Marine Institute through the Marine Research Sub-Programme of the Irish Government Tabitha Pearman was a PhD student in the NERC-funded SPITFIRE Doctoral Training Programme (Grant number NE/L002531/1). For the image in Figure 4B, sponge images and data were acquired in the scope of the SponGES project, which received funding from the European Union’s Horizon 2020 research and innovation programme under Grant agreement No. 679849. Density data from New Zealand seamounts provided by Malcolm Clark from a Seamount recovery survey funded by NIWA, Ministry for Primary Industries (project BEN2014-02) and Ministry for Business, Innovation and Employment (Vulnerable Deep-Sea Communities project DSCA153, contract CO1X0906). Density data from seamounts off southern Australia was provided by Alan Williams and Franziska Althaus. Funding for the collection of imagery and density data was provided by the CSIRO Wealth from Oceans Flagship, and the Department of Water, Environment, Heritage and the Arts, and completed with the assistance of staff from Australia’s Marine National Facility; image analysis was supported through the Commonwealth Environment Research Facilities (CERF) programme, an Australian Government initiative, and in particular by the CERF Marine Biodiversity Hub. The Australian seamount imagery were collected on the SS200611 survey funded by the CSIRO Wealth from Oceans Flagship, and the Australian Department of Water, Environment, Heritage and the Arts. Funding for collecting density data from the imagery was provided by the Commonwealth Environment Research Facilities (CERF) Marine Biodiversity Hub. Data were collected and processed as part of the Department for Business, Enterprise and Regulatory Reform’s Strategic Environmental Assessment 7 process and the Department for Environment, Food and Rural Affairs’ offshore Special Areas for Conservation programme. Amy R. Baco’s time in preparing this manuscript and analyses were supported by NSF Grant OCE-1851365. Lisa A. Levin received support from US NOAA Grant NA19OAR0110305. Tina N. Molodtsova received support from Minobrnauki of the Russian Federation State, Assignment No. FMWE-2021-0008. Ana Colaco is supported by Investigadores MarAZ (ACORES-01-0145-FEDER-000140) and Foundation for Science and Technology (FCT) I.P. through the FCT-IP Program Stimulus of Scientific Employment (CEECIND/00101/2021) and through national funds through the strategic project UIDB/05634/2020 and UIDP/05634/2020. Joana R. Xavier’s research is supported by national funds through FCT Foundation for Science and Technology within the scope of UIDB/04423/2020, UIDP/04423/2020, and CEECIND/00577/2018. Kerry Howell is supported by the MISSION ATLANTIC project funded by the European Union’s Horizon 2020 Research and Innovation Program under grant agreement No. 639 862428, and the UKRI GCRF funded One Ocean Hub NE/S008950/1. Rebecca Ross, Pål Buhl-Mortensen, and Genoveva Gonzalez-Mirelis were supported by the Institute of Marine Research, Norway and the MAREANO programme which is funded by the Norwegian Government. Chris Yesson is supported by funding from Research England. Diva J. Amon received funding from the European Union’s Horizon 2020 Research and Innovation Program under the Marie Skłodowska-Curie grant agreement number 747946. Diva also received funding from UC Santa Barbara’s Benioff Ocean Science Laboratory. Lissette Victorero was funded by the Norwegian Research Council project number 287934. David Price was supported by the PO2020 project DeepWalls (ACORES-01-0145-FEDER-000124) and Natural Environmental Research Council (Grant number NE/N012070/1). James Taylor and Saskia Brix were financially supported by the German Science Foundation (DFG) Grant numbers MerMet 17–15 and 17–06. Additionally James Taylor was supported under DFG contract no. BR 3843/5-1. Telmo Morato, Marina Carreiro-Silva, and Ana Colaço also received funds through the FCT–Foundation for Science and Technology, I.P., under the project OKEANOS UIDB/05634/2020 and UIDP/05634/2020 and through the FCT Regional Government of the Azores under the project M1.1.A/REEQ.CIENTÍFICO UI&D/2021/010. Marina Carreiro-Silva and Telmo Morato were supported by Program Stimulus of Scientific Employment (CCCIND/03346/2020 and CCCIND/03345/2020, respectively) from the Fundação para a Ciência e Tecnologia. Cross-ministerial Strategic Innovation Promotion Program (SIP), Japan. Japan Agency for Marine-Earth Science and Technology (JAMSTEC) institutional funding. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.