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  • 1
    Publication Date: 2024-02-08
    Keywords: Bottle, Niskin; Campaign; CTD/Rosette; CTD-RO; Deep-sea Sponge Grounds Ecosystems of the North Atlantic; DEPTH, water; Discovery (2013); DY081; DY081_12; DY081_36; DY081_5; DY081_50; DY081_CTD02; DY081_ROV327; DY081_ROV335; DY081_ROV338; EUROFLEET2; Event label; geochemical archives; HUD16/19_018; HUD16/19_020; HUD16/19_392; HUD2016019; Hudson; ICY-LAB; Isotope CYcling in the LABrador Sea; isotopes; LATITUDE; Location; LONGITUDE; New operational steps towards an alliance of European research fleets; NIS; Porifera; Remote operated vehicle; ROV; Sample ID; silicic acid; Silicon; South Atlantic Ocean; SponGES; δ29Si; δ29Si, error; δ30Si; δ30Si, error
    Type: Dataset
    Format: text/tab-separated-values, 152 data points
    Location Call Number Limitation Availability
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  • 2
    Publication Date: 2024-02-08
    Keywords: BC; Box corer; Campaign; CE15011; CE15011_27; CE15011_28; CE15011_35; CE15011_44; Celtic Explorer; Deep-sea Sponge Grounds Ecosystems of the North Atlantic; DEPTH, water; Device type; Discovery (2013); DY081; DY081_11; DY081_36; DY081_5; DY081_50; DY081_ROV327; DY081_ROV330; DY081_ROV335; DY081_ROV338; EUROFLEET2; Event label; geochemical archives; HUD16/19_010; HUD16/19_383; HUD16/19_391; HUD16/19_395; HUD2016019; Hudson; ICY-LAB; Isotope CYcling in the LABrador Sea; isotopes; LATITUDE; Location; LONGITUDE; Martha L. Black; MLB2017001; MLB2017001_SB_01; New operational steps towards an alliance of European research fleets; North Atlantic; Porifera; Remote operated vehicle; ROV; Sample ID; silicic acid; South Atlantic Ocean; Species; SponGES; Sponge spiculae, δ29Si; Sponge spiculae, δ29Si, standard deviation; Sponge spiculae, δ30Si; Sponge spiculae, δ30Si, standard deviation
    Type: Dataset
    Format: text/tab-separated-values, 666 data points
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  • 3
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    In:  Supplement to: Hendry, Katharine R; Cassarino, Lucie; Bates, Stephanie L; Culwick, Timothy; Frost, Molly; Goodwin, Claire; Howell, Kerry (2019): Silicon isotopic systematics of deep-sea sponge grounds in the North Atlantic. Quaternary Science Reviews, 210, 1-14, https://doi.org/10.1016/j.quascirev.2019.02.017
    Publication Date: 2024-02-08
    Description: This data release contains the stable silicon isotope composition of deep sea sponges collected from the North Atlantic, and co-located seawater silicon isotopic compositions. Three sites were surveyed: the Labrador Sea, Nova Scotia and Porcupine Bight. The samples were collected as part of the European Research Council project ICY-LAB (ERC-2015-STG grant agreement number 678371), EU Horizon 2020 project SponGES (H2020-BG-2015-2 grant agreement number 679849), and EU Seventh Framework Programme EUROFLEETS2 (FP7/2007-2013 grant agreement number 312762).
    Keywords: Deep-sea Sponge Grounds Ecosystems of the North Atlantic; EUROFLEET2; geochemical archives; ICY-LAB; Isotope CYcling in the LABrador Sea; isotopes; New operational steps towards an alliance of European research fleets; Porifera; silicic acid; SponGES
    Type: Dataset
    Format: application/zip, 2 datasets
    Location Call Number Limitation Availability
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  • 4
    Publication Date: 2017-01-27
    Description: Anthropogenic litter is present in all marine habitats, from beaches to the most remote points in the oceans. On the seafloor, marine litter, particularly plastic, can accumulate in high densities with deleterious consequences for its inhabitants. Yet, because of the high cost involved with sampling the seafloor, no large-scale assessment of distribution patterns was available to date. Here, we present data on litter distribution and density collected during 588 video and trawl surveys across 32 sites in European waters. We found litter to be present in the deepest areas and at locations as remote from land as the Charlie-Gibbs Fracture Zone across the Mid-Atlantic Ridge. The highest litter density occurs in submarine canyons, whilst the lowest density can be found on continental shelves and on ocean ridges. Plastic was the most prevalent litter item found on the seafloor. Litter from fishing activities (derelict fishing lines and nets) was particularly common on seamounts, banks, mounds and ocean ridges. Our results highlight the extent of the problem and the need for action to prevent increasing accumulation of litter in marine environments.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev , info:eu-repo/semantics/article
    Format: application/pdf
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  • 5
    Publication Date: 2022-10-26
    Description: © The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Howell, K. L., Hilario, A., Allcock, A. L., Bailey, D. M., Baker, M., Clark, M. R., Colaco, A., Copley, J., Cordes, E. E., Danovaro, R., Dissanayake, A., Escobar, E., Esquete, P., Gallagher, A. J., Gates, A. R., Gaudron, S. M., German, C. R., Gjerde, K. M., Higgs, N. D., Le Bris, N., Levin, L. A., Manea, E., McClain, C., Menot, L., Mestre, N. C., Metaxas, A., Milligan, R. J., Muthumbi, A. W. N., Narayanaswamy, B. E., Ramalho, S. P., Ramirez-Llodra, E., Robson, L. M., Rogers, A. D., Sellanes, J., Sigwart, J. D., Sink, K., Snelgrove, P. V. R., Stefanoudis, P., V., Sumida, P. Y., Taylor, M. L., Thurber, A. R., Vieira, R. P., Watanabe, H. K., Woodall, L. C., & Xavier, J. R. A blueprint for an inclusive, global deep-sea ocean decade field program. Frontiers in Marine Science, 7, (2020): 584861, doi:10.3389/fmars.2020.584861.
    Description: The ocean plays a crucial role in the functioning of the Earth System and in the provision of vital goods and services. The United Nations (UN) declared 2021–2030 as the UN Decade of Ocean Science for Sustainable Development. The Roadmap for the Ocean Decade aims to achieve six critical societal outcomes (SOs) by 2030, through the pursuit of four objectives (Os). It specifically recognizes the scarcity of biological data for deep-sea biomes, and challenges the global scientific community to conduct research to advance understanding of deep-sea ecosystems to inform sustainable management. In this paper, we map four key scientific questions identified by the academic community to the Ocean Decade SOs: (i) What is the diversity of life in the deep ocean? (ii) How are populations and habitats connected? (iii) What is the role of living organisms in ecosystem function and service provision? and (iv) How do species, communities, and ecosystems respond to disturbance? We then consider the design of a global-scale program to address these questions by reviewing key drivers of ecological pattern and process. We recommend using the following criteria to stratify a global survey design: biogeographic region, depth, horizontal distance, substrate type, high and low climate hazard, fished/unfished, near/far from sources of pollution, licensed/protected from industry activities. We consider both spatial and temporal surveys, and emphasize new biological data collection that prioritizes southern and polar latitudes, deeper (〉 2000 m) depths, and midwater environments. We provide guidance on observational, experimental, and monitoring needs for different benthic and pelagic ecosystems. We then review recent efforts to standardize biological data and specimen collection and archiving, making “sampling design to knowledge application” recommendations in the context of a new global program. We also review and comment on needs, and recommend actions, to develop capacity in deep-sea research; and the role of inclusivity - from accessing indigenous and local knowledge to the sharing of technologies - as part of such a global program. We discuss the concept of a new global deep-sea biological research program ‘Challenger 150,’ highlighting what it could deliver for the Ocean Decade and UN Sustainable Development Goal 14.
    Description: Development of this paper was supported by funding from the Scientific Committee on Oceanic Research (SCOR) awarded to KH and AH as working group 159 co-chairs. KH, BN, and KS are supported by the UKRI funded One Ocean Hub NE/S008950/1. AH work is supported by the CESAM (UIDP/50017/2020 + 1432 UIDB/50017/2020) that is funded by Fundação para a Ciência e a Tecnologia (FCT)/MCTES through national funds. AA is supported by Science Foundation Ireland and the Marine Institute under the Investigators Program Grant Number SFI/15/IA/3100 co-funded under the European Regional Development Fund 2014–2020. AC is supported through the FunAzores -ACORES 01-0145-FEDER-000123 grant and by FCT through strategic project UID/05634/2020 and FCT and Direção-Geral de Politica do Mar (DGPM) through the project Mining2/2017/005. PE is funded by national funds (OE), through FCT in the scope of the framework contract foreseen in the numbers 4, 5 and 6 of the article 23, of the Decree-Law 57/2016, of August 29, changed by Law 57/2017, of July 19. SG research is supported by CNRS funds. CG is supported by an Independent Study Award and the Investment in Science Fund at WHOI. KG gratefully acknowledges support from Synchronicity Earth. LL is funded by the NOAA Office of Ocean Exploration and Research (NA19OAR0110305) and the US National Science Foundation (OCE 1634172). NM is supported by FCT and DGPM, through the project Mining2/2017/001 and the FCT grants CEECIND/00526/2017, UIDB/00350/2020 + UIDP/00350/2020. SR is funded by the FCTgrant CEECIND/00758/2017. JS is supported by ANID FONDECYT #1181153 and ANID Millennium Science Initiative Program #NC120030. JX research is funded by the European Union’s Horizon 2020 research and innovation program through the SponGES project (grant agreement no. 679849) and further supported by national funds through FCT within the scope of UIDB/04423/2020 and UIDP/04423/2020. The Natural Sciences and Engineering Council of Canada supports AM and PVRS. MB and the Deep-Ocean Stewardship Initiative are supported by Arcadia - A charitable fund of Lisbet Rausing and Peter Baldwin. BN work is supported by the NERC funded Arctic PRIZE NE/P006302/1.
    Keywords: Deep sea ; Blue economy ; Ocean Decade ; Biodivercity ; Essential ocean variables
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 6
    Publication Date: 2017-05-09
    Description: Anthropogenic litter is present in all marine habitats, from beaches to the most remote points in the oceans. On the seafloor, marine litter, particularly plastic, can accumulate in high densities with deleterious consequences for its inhabitants. Yet, because of the high cost involved with sampling the seafloor, no large-scale assessment of distribution patterns was available to date. Here, we present data on litter distribution and density collected during 588 video and trawl surveys across 32 sites in European waters. We found litter to be present in the deepest areas and at locations as remote from land as the Charlie-Gibbs Fracture Zone across the Mid-Atlantic Ridge. The highest litter density occurs in submarine canyons, whilst the lowest density can be found on continental shelves and on ocean ridges. Plastic was the most prevalent litter item found on the seafloor. Litter from fishing activities (derelict fishing lines and nets) was particularly common on seamounts, banks, mounds and ocean ridges. Our results highlight the extent of the problem and the need for action to prevent increasing accumulation of litter in marine environments.
    Type: Article , PeerReviewed
    Format: text
    Location Call Number Limitation Availability
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  • 7
    Publication Date: 2023-09-21
    Description: The Central and South Atlantic represents a vast ocean area and is home to a diverse range of ecosystems and species. Nevertheless, and similar to the rest of the global south, the area is comparatively understudied yet exposed to increasing levels of multisectoral pressures. To counteract this, the level of scientific exploration in the Central and South Atlantic has increased in recent years and will likely continue to do so within the context of the United Nations (UN) Decade of Ocean Science for Sustainable Development. Here, we compile the literature to investigate the distribution of previous scientific exploration of offshore (30 m+) ecosystems in the Central and South Atlantic, both within and beyond national jurisdiction, allowing us to synthesise overall patterns of biodiversity. Furthermore, through the lens of sustainable management, we have reviewed the existing anthropogenic activities and associated management measures relevant to the region. Through this exercise, we have identified key knowledge gaps and undersampled regions that represent priority areas for future research and commented on how these may be best incorporated into, or enhanced through, future management measures such as those in discussion at the UN Biodiversity Beyond National Jurisdiction negotiations. This review represents a comprehensive summary for scientists and managers alike looking to understand the key topographical, biological, and legislative features of the Central and South Atlantic.
    Type: Book chapter , PeerReviewed
    Format: text
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  • 8
    Publication Date: 2024-02-14
    Description: Machine learning covers a large set of algorithms that can be trained to identify patterns in data. Thanks to the increase in the amount of data and computing power available, it has become pervasive across scientific disciplines. We first highlight why machine learning is needed in marine ecology. Then we provide a quick primer on machine learning techniques and vocabulary. We built a database of & SIM;1000 publications that implement such techniques to analyse marine ecology data. For various data types (images, optical spectra, acoustics, omics, geolocations, biogeochemical profiles, and satellite imagery), we present a historical perspective on applications that proved influential, can serve as templates for new work, or represent the diversity of approaches. Then, we illustrate how machine learning can be used to better understand ecological systems, by combining various sources of marine data. Through this coverage of the literature, we demonstrate an increase in the proportion of marine ecology studies that use machine learning, the pervasiveness of images as a data source, the dominance of machine learning for classification-type problems, and a shift towards deep learning for all data types. This overview is meant to guide researchers who wish to apply machine learning methods to their marine datasets.
    Type: Article , PeerReviewed
    Format: text
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  • 9
    Publication Date: 2024-03-25
    Description: Imaging is increasingly used to capture information on the marine environment thanks to the improvements in imaging equipment, devices for carrying cameras and data storage in recent years. In that context, biologists, geologists, computer specialists and end-users must gather to discuss the methods and procedures for optimising the quality and quantity of data collected from images. The 4 th Marine Imaging Workshop was organised from 3-6 October 2022 in Brest (France) in a hybrid mode. More than a hundred participants were welcomed in person and about 80 people attended the online sessions. The workshop was organised in a single plenary session of presentations followed by discussion sessions. These were based on dynamic polls and open questions that allowed recording of the imaging community’s current and future ideas. In addition, a whole day was dedicated to practical sessions on image analysis, data standardisation and communication tools. The format of this edition allowed the participation of a wider community, including lower-income countries, early career scientists, all working on laboratory, benthic and pelagic imaging. This article summarises the topics addressed during the workshop, particularly the outcomes of the discussion sessions for future reference and to make the workshop results available to the open public.
    Type: Article , NonPeerReviewed
    Format: text
    Format: archive
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