PeerJ spoke to Dr. Amy R. Baco at Florida State University about the recently published PeerJ Life & Environment article Towards a scientific community consensus on designating Vulnerable Marine Ecosystems from imagery. The article is featured in the IABO Hub. The IABO Hub is the publishing home of the International Association for Biological Oceanography, and features the latest biological oceanography research published by the members of IABO.
Can you tell us a bit about yourself?
I am a Professor at Florida State University. My research interests focus on the evolution, ecology, and connectivity of benthic marine organisms. There will always be an imperative for basic research, but the reality of rising anthropogenic impacts on the world’s oceans means that scientists must also consider their species or ecosystem of interest in a more applied context. My research merges both of these directives by using traditional ecological tools alongside genetic/genomic tools to answer basic questions about the ecology of marine benthic invertebrates, with a goal of informing management and conservation of these species.
Can you briefly explain the research you published in PeerJ?
Many scientists around the world were working independently on a similar question, given the UN Food and Agriculture Organization regulations for deep-sea Vulnerable Marine Ecosystems (VMEs) on the high seas, how can VMEs be identified from seafloor images. We recognized after many of our presentations at a conference that we were all working towards the same goal, and that working together would allow us to produce guidelines that could be used more consistently across regions. This publications represents the discussions of that large group of scientists and managers, and the first-level answers to how we would determine if an image showed a VME.
What did you discover and where? What was significant about your findings?
We found that even though the deep-sea communities we see in different parts of the world may have different species, most of the authors had similar opinions on what constituted a VME. Therefore, for certain types of images we could have consensus agreement that those images definitely depicted a VME. Building on this we deconstructed what was it about the images that led us to the conclusion that it was a VME and designed a flow chart that we hope will allow for a more quantitative and efficient approach to VME designation. We also identified areas where more work is needed, for example, determining how large of an area communities need to cover to be considered a VME will be the next project of our group.
Anything else you would like to add?
This publication represents an enormous team effort on the part of the 33 authors. I am grateful for the input from all of these diverse collaborators, which strengthened our manuscript considerably.
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