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  • benthic observatory; Deep-ocean Environmental Long-term Observatory System; Deep sea; DELOS; Time series  (1)
  • ocean observing  (1)
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  • 1
    Publication Date: 2023-03-27
    Description: These data list the fish counts and densities observed using time-lapse cameras at the two DELOS observatory platforms, located at 1400 m water depth on the Angolan continental margin between February 2009 and July 2016. Timelapse photographs were captured from both the "Near Field" (NF; 7.90°S, 12.14°E) and "Far Field" (FF; 7.95°S, 12.28°E) DELOS observatories using a Kongsberg OE14-208 5.1 megapixel digital camera and a Kongsberg OE11-242 flash. Where appropriate: Fish counts are listed as no. individuals observed per photograph. Fish densities are listed as no. individuals observed per photograph, per calendar month, and multiplied by 1000. The DELOS platforms (DELOS A and DELOS B) are under Angolan jurisdiction and all activities must abide by Angolan law. As such, any person intending to publish DELOS data in any form is required to obtain prior permission from the National Concessionaire (Sonangol). Permission can be requested via Robert O'Brien at BP UK (Robert.OBrien@uk.bp.com) or the DELOS PI Dr. David Bailey (David.Bailey@glasgow.ac.uk). This process is not intended as a deterrent and applications to use DELOS data are welcomed. Participating Institutions: BP Exploration, BP Angola, University of Aberdeen, MBARI, National Oceanography Centre, INIP - Angola Instituto Nacional de Investigação Pesqueira (Angolan National Institute of Fisheries), Texas A&M University, Glasgow University
    Keywords: benthic observatory; Deep-ocean Environmental Long-term Observatory System; Deep sea; DELOS; Time series
    Type: Dataset
    Format: application/zip, 3 datasets
    Location Call Number Limitation Availability
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  • 2
    Publication Date: 2022-10-11
    Description: © The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Smith, L., Cimoli, L., LaScala-Gruenewald, D., Pachiadaki, M., Phillips, B., Pillar, H., Stopa, J., Baumann-Pickering, S., Beaulieu, S., Bell, K., Harden-Davies, H., Gjerde, K., Heimbach, P., Howe, B., Janssen, F., Levin, L., Ruhl, H., Soule, A., Stocks, K., Vardaro, M.F., Wright, D. The Deep Ocean Observing Strategy: addressing global challenges in the deep sea through collaboration. Marine Technology Society Journal, 56(3), (2022): 50–66, https://doi.org/10.4031/mtsj.56.3.11.
    Description: The Deep Ocean Observing Strategy (DOOS) is an international, community-driven initiative that facilitates collaboration across disciplines and fields, elevates a diverse cohort of early career researchers into future leaders, and connects scientific advancements to societal needs. DOOS represents a global network of deep-ocean observing, mapping, and modeling experts, focusing community efforts in the support of strong science, policy, and planning for sustainable oceans. Its initiatives work to propose deep-sea Essential Ocean Variables; assess technology development; develop shared best practices, standards, and cross-calibration procedures; and transfer knowledge to policy makers and deep-ocean stakeholders. Several of these efforts align with the vision of the UN Ocean Decade to generate the science we need to create the deep ocean we want. DOOS works toward (1) a healthy and resilient deep ocean by informing science-based conservation actions, including optimizing data delivery, creating habitat and ecological maps of critical areas, and developing regional demonstration projects; (2) a predicted deep ocean by strengthening collaborations within the modeling community, determining needs for interdisciplinary modeling and observing system assessment in the deep ocean; (3) an accessible deep ocean by enhancing open access to innovative low-cost sensors and open-source plans, making deep-ocean data Findable, Accessible, Interoperable, and Reusable, and focusing on capacity development in developing countries; and finally (4) an inspiring and engaging deep ocean by translating science to stakeholders/end users and informing policy and management decisions, including in international waters.
    Description: Funding for the DOOS comes from the U.S. National Science Foundation AccelNet program, Award #2114717.
    Keywords: FAIR data principles ; deep ocean ; multi-disciplinary ; ocean observing ; science policy and planning
    Repository Name: Woods Hole Open Access Server
    Type: Article
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