Description: The deep ocean below 200 m water depth is the least observed, but largest habitat on our planet by volume and area. Over 150 years of exploration has revealed that this dynamic system provides critical climate regulation, houses a wealth of energy, mineral, and biological resources, and represents a vast repository of biological diversity. A long history of deep-ocean exploration and observation led to the initial concept for the Deep-Ocean Observing Strategy (DOOS), under the auspices of the Global Ocean Observing System (GOOS). Here we discuss the scientific need for globally integrated deep-ocean observing, its status, and the key scientific questions and societal mandates driving observing requirements over the next decade. We consider the Essential Ocean Variables (EOVs) needed to address deep-ocean challenges within the physical, biogeochemical, and biological/ecosystem sciences according to the Framework for Ocean Observing (FOO), and map these onto scientific questions. Opportunities for new and expanded synergies among deep-ocean stakeholders are discussed, including academic-industry partnerships with the oil and gas, mining, cable and fishing industries, the ocean exploration and mapping community, and biodiversity conservation initiatives. Future deep-ocean observing will benefit from the greater integration across traditional disciplines and sectors, achieved through demonstration projects and facilitated reuse and repurposing of existing deep-sea data efforts. We highlight examples of existing and emerging deep-sea methods and technologies, noting key challenges associated with data volume, preservation, standardization, and accessibility. Emerging technologies relevant to deep-ocean sustainability and the blue economy include novel genomics approaches, imaging technologies, and ultra-deep hydrographic measurements. Capacity building will be necessary to integrate capabilities into programs and projects at a global scale. Progress can be facilitated by Open Science and Findable, Accessible, Interoperable, Reusable (FAIR) data principles and converge on agreed to data standards, practices, vocabularies, and registries. We envision expansion of the deep-ocean observing community to embrace the participation of academia, industry, NGOs, national governments, international governmental organizations, and the public at large in order to unlock critical knowledge contained in the deep ocean over coming decades, and to realize the mutual benefits of thoughtful deep-ocean observing for all elements of a sustainable ocean.

Description: © The Author(s), 2018]. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Global Ecology and Biogeography 27 (2018): 760-786, doi:10.1111/geb.12729.

Description: The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community‐led open‐source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene. The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record. BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km2 (158 cm2) to 100 km2 (1,000,000,000,000 cm2). BioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year. BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.

Description: European Research Council and EU, Grant/Award Number: AdG‐250189, PoC‐727440 and ERC‐SyG‐2013‐610028; Natural Environmental Research Council, Grant/Award Number: NE/L002531/1; National Science Foundation, Grant/Award Number: DEB‐1237733, DEB‐1456729, 9714103, 0632263, 0856516, 1432277, DEB‐9705814, BSR‐8811902, DEB 9411973, DEB 0080538, DEB 0218039, DEB 0620910, DEB 0963447, DEB‐1546686, DEB‐129764, OCE 95‐21184, OCE‐ 0099226, OCE 03‐52343, OCE‐0623874, OCE‐1031061, OCE‐1336206 and DEB‐1354563; National Science Foundation (LTER) , Grant/Award Number: DEB‐1235828, DEB‐1440297, DBI‐0620409, DEB‐9910514, DEB‐1237517, OCE‐0417412, OCE‐1026851, OCE‐1236905, OCE‐1637396, DEB 1440409, DEB‐0832652, DEB‐0936498, DEB‐0620652, DEB‐1234162 and DEB‐0823293; Fundação para a Ciência e Tecnologia, Grant/Award Number: POPH/FSE SFRH/BD/90469/2012, SFRH/BD/84030/2012, PTDC/BIA‐BIC/111184/2009; SFRH/BD/80488/2011 and PD/BD/52597/2014; Ciência sem Fronteiras/CAPES, Grant/Award Number: 1091/13‐1; Instituto Milenio de Oceanografía, Grant/Award Number: IC120019; ARC Centre of Excellence, Grant/Award Number: CE0561432; NSERC Canada; CONICYT/FONDECYT, Grant/Award Number: 1160026, ICM PO5‐002, CONICYT/FONDECYT, 11110351, 1151094, 1070808 and 1130511; RSF, Grant/Award Number: 14‐50‐00029; Gordon and Betty Moore Foundation, Grant/Award Number: GBMF4563; Catalan Government; Marie Curie Individual Fellowship, Grant/Award Number: QLK5‐CT2002‐51518 and MERG‐CT‐2004‐022065; CNPq, Grant/Award Number: 306170/2015‐9, 475434/2010‐2, 403809/2012‐6 and 561897/2010; FAPESP (São Paulo Research Foundation), Grant/Award Number: 2015/10714‐6, 2015/06743‐0, 2008/10049‐9, 2013/50714‐0 and 1999/09635‐0 e 2013/50718‐5; EU CLIMOOR, Grant/Award Number: ENV4‐CT97‐0694; VULCAN, Grant/Award Number: EVK2‐CT‐2000‐00094; Spanish, Grant/Award Number: REN2000‐0278/CCI, REN2001‐003/GLO and CGL2016‐79835‐P; Catalan, Grant/Award Number: AGAUR SGR‐2014‐453 and SGR‐2017‐1005; DFG, Grant/Award Number: 120/10‐2; Polar Continental Shelf Program; CENPES – PETROBRAS; FAPERJ, Grant/Award Number: E‐26/110.114/2013; German Academic Exchange Service; sDiv; iDiv; New Zealand Department of Conservation; Wellcome Trust, Grant/Award Number: 105621/Z/14/Z; Smithsonian Atherton Seidell Fund; Botanic Gardens and Parks Authority; Research Council of Norway; Conselleria de Innovació, Hisenda i Economia; Yukon Government Herschel Island‐Qikiqtaruk Territorial Park; UK Natural Environment Research Council ShrubTundra Grant, Grant/Award Number: NE/M016323/1; IPY; Memorial University; ArcticNet. DOI: 10.13039/50110000027. Netherlands Organization for Scientific Research in the Tropics NWO, grant W84‐194. Ciências sem Fronteiras and Coordenação de Pessoal de Nível Superior (CAPES, Brazil), Grant/Award Number: 1091/13‐1. National Science foundation (LTER), Award Number: OCE‐9982105, OCE‐0620276, OCE‐1232779. FCT ‐ SFRH / BPD / 82259 / 2011. U.S. Fish and Wildlife Service/State Wildlife federal grant number T‐15. Australian Research Council Centre of Excellence for Coral Reef Studies (CE140100020). Australian Research Council Future Fellowship FT110100609. M.B., A.J., K.P., J.S. received financial support from internal funds of University of Lódź. NSF DEB 1353139. Catalan Government fellowships (DURSI): 1998FI‐00596, 2001BEAI200208, MECD Post‐doctoral fellowship EX2002‐0022. National Science Foundation Award OPP‐1440435. FONDECYT 1141037 and FONDAP 15150003 (IDEAL). CNPq Grant 306595‐2014‐1

Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Levin, L. A., Bett, B. J., Gates, A. R., Heimbach, P., Howe, B. M., Janssen, F., McCurdy, A., Ruhl, H. A., Snelgrove, P., Stocks, K., I., Bailey, D., Baumann-Pickering, S., Beaverson, C., Benfield, M. C., Booth, D. J., Carreiro-Silva, M., Colaco, A., Eble, M. C., Fowler, A. M., Gjerde, K. M., Jones, D. O. B., Katsumata, K., Kelley, D., Le Bris, N., Leonardi, A. P., Lejzerowicz, F., Macreadie, P., I., McLean, D., Meitz, F., Morato, T., Netburn, A., Pawlowski, J., Smith, C. R., Sun, S., Uchida, H., Vardaro, M. F., Venkatesan, R., & Weller, R. A. Global observing needs in the deep ocean. Frontiers in Marine Science, 6, (2019):241, doi: 10.3389/fmars.2019.00241.

Description: The deep ocean below 200 m water depth is the least observed, but largest habitat on our planet by volume and area. Over 150 years of exploration has revealed that this dynamic system provides critical climate regulation, houses a wealth of energy, mineral, and biological resources, and represents a vast repository of biological diversity. A long history of deep-ocean exploration and observation led to the initial concept for the Deep-Ocean Observing Strategy (DOOS), under the auspices of the Global Ocean Observing System (GOOS). Here we discuss the scientific need for globally integrated deep-ocean observing, its status, and the key scientific questions and societal mandates driving observing requirements over the next decade. We consider the Essential Ocean Variables (EOVs) needed to address deep-ocean challenges within the physical, biogeochemical, and biological/ecosystem sciences according to the Framework for Ocean Observing (FOO), and map these onto scientific questions. Opportunities for new and expanded synergies among deep-ocean stakeholders are discussed, including academic-industry partnerships with the oil and gas, mining, cable and fishing industries, the ocean exploration and mapping community, and biodiversity conservation initiatives. Future deep-ocean observing will benefit from the greater integration across traditional disciplines and sectors, achieved through demonstration projects and facilitated reuse and repurposing of existing deep-sea data efforts. We highlight examples of existing and emerging deep-sea methods and technologies, noting key challenges associated with data volume, preservation, standardization, and accessibility. Emerging technologies relevant to deep-ocean sustainability and the blue economy include novel genomics approaches, imaging technologies, and ultra-deep hydrographic measurements. Capacity building will be necessary to integrate capabilities into programs and projects at a global scale. Progress can be facilitated by Open Science and Findable, Accessible, Interoperable, Reusable (FAIR) data principles and converge on agreed to data standards, practices, vocabularies, and registries. We envision expansion of the deep-ocean observing community to embrace the participation of academia, industry, NGOs, national governments, international governmental organizations, and the public at large in order to unlock critical knowledge contained in the deep ocean over coming decades, and to realize the mutual benefits of thoughtful deep-ocean observing for all elements of a sustainable ocean.

Description: Preparation of this manuscript was supported by NNX16AJ87A (NASA) Consortium for Ocean Leadership, Sub-Award No. SA16-33. AC was supported by FCT-Investigador contract (IF/00029/2014/CP1230/CT0002). LL was supported by a NASA subaward from the Consortium for Ocean Leadership. AG and HR were supported by Horizon 2020, EU Project “EMSO Link” grant ID 731036. AG, BB, DJ, and HR contributions were supported by the UK Natural Environment Research Council Climate Linked Atlantic Section Science project (NE/R015953/1). JP was funded by the Swiss Network for International Studies, and the Swiss National Science Foundation (grant 31003A_179125). TM was supported by Program Investigador FCT (IF/01194/2013), IFCT Exploratory Project (IF/01194/2013/CP1199/CT0002), H2020 Atlas project (GA 678760), and the H2020 MERCES project (GA 689518). This is PMEL contribution number 4965.

Description: The rate of discovery of reefs of the cold-water coral Lophelia pertusa (Linnaeus, 1758) has been remarkable, and attributable to the increased use of underwater video. These reefs form a major three-dimensional habitat in deeper waters where little other ‘cover’ for fish is available. They are common in the eastern North Atlantic, and occur at least in the western North Atlantic and off central Africa. There are also other non-reef records of Lophelia in the Atlantic, and in Indian and Pacific oceans. Thus, not only are these reefs a significant habitat on a local scale, but they may also provide an important habitat over a very wide geographic scale. The present study examined the association of fish species with Lophelia in the Northeast Atlantic, including the Trondheimsfjord and Sula Ridge in Norway, Kosterfjord in Sweden, Darwin Mounds west of Scotland, and Rockall Bank, Rockall Trough and Porcupine Seabight off Ireland. The fish fauna associated with a shipwreck west of Shetland was also studied. Data were collected from 11 study sites at 8 locations, using 52 hours of video and 15 reels of still photographs. Video and still photographs were collected from (1) manned submersible, (2) surface controlled remotely operated vehicle (ROV), (3) a towed “hopper” camera, (4) wide angle survey photography (WASP), (5) seabed high resolution imaging platform (SHRIMP), and (6) an in situ time-lapse camera “Bathysnap”. It was possible to identify 90 % of fish observed to species level and 6.5 % to genus or family level. Only 3.5 % of the fish were not identifiable. A guide to the fishes is given at http://www.ecoserve.ie/projects/aces/. Twenty-five species of fishes from 17 families were recorded over all the sites, of which 17 were of commercial importance and comprised 82 % of fish individuals observed. These commercial fish species contribute 90 % of commercial fish tonnage in the North Atlantic. The habitats sampled were comprised of 19 % reef, 20 % transitional zone (i.e. between living coral and debris zone), 25 % coral debris and 36 % off-reef seabed. Depth was the most significant parameter in influencing the fish associated with the reefs, both at the species and family level. There was a complete separation of sites above and below 400–600 m depth by multi-dimensional scaling (MDS) analysis. Less distinct assemblages of fish species were associated with each habitat. Fish species richness and abundance was greater on the reef than surrounding seabed. In fact, 92 % of species, and 80 % of individual fish were associated with the reef. The present data indicates that these reefs have a very important functional role in deep-water ecosystems as fish habitat.

Description: Marine imaging studies have unique constraints on the data collected requiring a tool for defining the biological scope to facilitate data discovery, quality evaluation, sharing and reuse. Defining the ‘target population’ is way of scoping biological sampling or observations by setting the pool of organisms to be observed or sampled. It is used in survey design and planning, to determine statistical inference, and is critical for data interpretation and reuse (both images and derived data). We designed a set of attributes for defining and recording the target population in biological studies using marine photography, incorporating ecological and environmental delineation and marine imaging method constraints. We describe how this definition may be altered and recorded at different phases of a project. The set of attributes records the definition of the target population in a structured metadata format to enhance data FAIRness. It is designed as an extension to the image FAIR Digital Objects metadata standard, and we map terms to other biological data standards where possible. This set of attributes serves a need to update ecological metadata to align with new remotely-sensed data, and can be applied to other remotely-sensed ecological image data.

Description: Highlights • Seafloor geomorphology was important in the structuring of abyssal megafauna. • Differences in megafaunal community ecology were found between all landscape types. • Lower megafauna density & diversity in a bathymetric valley than flat and ridge areas. • Large samples, collected by AUV, were required to make robust ecological conclusions. The potential for imminent polymetallic nodule mining in the Clarion Clipperton Fracture Zone (CCZ) has attracted considerable scientific and public attention. This concern stems from both the extremely large seafloor areas that may be impacted by mining, and the very limited knowledge of the fauna and ecology of this region. The environmental factors regulating seafloor ecology are still very poorly understood. In this study, we focus on megafaunal ecology in the proposed conservation zone ‘Area of Particular Environmental Interest 6′ (study area centred 17°16′N, 122°55′W). We employ bathymetric data to objectively define three landscape types in the area (a level bottom Flat, an elevated Ridge, a depressed Trough; water depth 3950–4250 m) that are characteristic of the wider CCZ. We use direct seabed sampling to characterise the sedimentary environment in each landscape, detecting no statistically significant differences in particle size distributions or organic matter content. Additional seafloor characteristics and data on both the metazoan and xenophyophore components of the megafauna were derived by extensive photographic survey from an autonomous underwater vehicle. Image data revealed that there were statistically significant differences in seafloor cover by nodules and in the occurrence of other hard substrata habitat between landscapes. Statistically significant differences in megafauna standing stock, functional structuring, diversity, and faunal composition were detected between landscapes. The Flat and Ridge areas exhibited a significantly higher standing stock and a distinct assemblage composition compared to the Trough. Geomorphological variations, presumably regulating local bottom water flows and the occurrence of nodule and xenophyophore test substrata, between study areas may be the mechanism driving these assemblage differences. We also used these data to assess the influence of sampling unit size on the estimation of ecological parameters. We discuss these results in the contexts of regional benthic ecology and the appropriate management of potential mining activities in the CCZ and elsewhere in the deep ocean.

Description: The potential for imminent abyssal polymetallic nodule exploitation has raised considerable scientific attention. The interface between the targeted nodule resource and sediment in this unusual mosaic habitat promotes the development of some of the most biologically diverse communities in the abyss. However, the ecology of these remote ecosystems is still poorly understood, so it is unclear to what extent and timescale these ecosystems will be affected by, and could recover from, mining disturbance. Using data inferred from seafloor photo-mosaics, we show that the effects of simulated mining impacts, induced during the “DISturbance and reCOLonization experiment” (DISCOL) conducted in 1989, were still evident in the megabenthos of the Peru Basin after 26 years. Suspension-feeder presence remained significantly reduced in disturbed areas, while deposit-feeders showed no diminished presence in disturbed areas, for the first time since the experiment began. Nevertheless, we found significantly lower heterogeneity diversity in disturbed areas and markedly distinct faunal compositions along different disturbance levels. If the results of this experiment at DISCOL can be extrapolated to the Clarion-Clipperton Zone, the impacts of polymetallic nodule mining there may be greater than expected, and could potentially lead to an irreversible loss of some ecosystem functions, especially in directly disturbed areas.

Description: Abyssal polymetallic nodule fields constitute an unusual deep-sea habitat. The mix of soft sediment and the hard substratum provided by nodules increases the complexity of these environments. Hard substrata typically support a very distinct fauna to that of seabed sediments, and its presence can play a major role in the structuring of benthic assemblages. We assessed the influence of seafloor nodule cover on the megabenthos of a marine conservation area (area of particular environmental interest 6) in the Clarion Clipperton Zone (3950–4250 m water depth) using extensive photographic surveys from an autonomous underwater vehicle. Variations in nodule cover (1–20%) appeared to exert statistically significant differences in faunal standing stocks, some biological diversity attributes, faunal composition, functional group composition, and the distribution of individual species. The standing stock of both the metazoan fauna and the giant protists (xenophyophores) doubled with a very modest initial increase in nodule cover (from 1% to 3%). Perhaps contrary to expectation, we detected little if any substantive variation in biological diversity along the nodule cover gradient. Faunal composition varied continuously along the nodule cover gradient. We discuss these results in the context of potential seabed-mining operations and the associated sustainable management and conservation plans. We note in particular that successful conservation actions will likely require the preservation of areas comprising the full range of nodule cover and not just the low cover areas that are least attractive to mining.

Description: Massive swarms of the red crab Pleuroncodes planipes (Stimpson, 1860), a species of squat lobster, are a dominant functional component of the upwelling ecosystem in the eastern Pacific Ocean (Boyd, 1967; Smith et al., 1975). These swarms can wash ashore on the coast, creating mass depositions of crustacean carcasses, a striking phenomenon that has been long documented in Baja California and California (Aurioles-Gamboa et al., 1994; Boyd, 1967). However, little is known about the fate of crab swarms transported offshore by oceanic currents. In May 2015, using an autonomous deep-sea robot, we discovered an unexpectedly large fall of red crab carcasses (〉1000 carcasses ha−1) at a depth of 4050 m on the abyssal Pacific seafloor (Figure 1), almost 1500 km from their spawning areas off the northwest American coast. Several questions arise from this unexpected finding that may help unveil additional close linkages in nutritional transport between processes at the sea surface and the remote abyssal seafloor.