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  • Wiley  (9)
  • PANGAEA  (4)
  • 2020-2024  (13)
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Keywords
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Year
  • 1
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    Metadata, flow cytometry data, and NCBI-Accession numbers (16S, 18S, COI, and SNP data) for fan-shaped sponges and seawater from the Cantabrian Sea in summer 2017 (2020)
    PANGAEA
    Details
    Publication Date: 2023-03-25
    Description: Connectivity is a fundamental process driving the persistence of marine populations and their adaptation potential in response to environmental change. In this study, we analysed the population genetics of two morphologically highly similar deep-sea sponge clades (Phakellia hirondellei and the 'Topsentia-and-Petromica (TaP)' clade) at three locations in the Cantabrian Sea. Sponge taxonomy was assessed by spicule analyses, as well as by 18S sequencing and COI sequencing. The corresponding host microbiome was analysed by 16S rRNA gene sequencing. In addition we set up an oceanographic modelling framework, for which we used seawater flow cytometry data (derived from bottom depths of CTD casts) as ground-truthing data.
    Keywords: Accession number, genetics; amplicon sequencing; Angeles Alvarino; Area/locality; Bacteria; Bay of Biscay; CTD/Rosette; CTD1; CTD10; CTD11; CTD12; CTD13; CTD14; CTD15; CTD2; CTD3; CTD4; CTD5; CTD6; CTD7; CTD8; CTD9; CTD-RO; Date/Time of event; Deep-sea Sponge Grounds Ecosystems of the North Atlantic; DEPTH, water; DR10; DR15; DR4; DR7; DR9; Dredge, rock; DRG_R; Event label; flow cytometry; Flow cytometry; Geology, comment; Latitude of event; Longitude of event; Measurement conducted; Method/Device of event; Phytoplankton; population genetics; Porifera; Sample code/label; Sample ID; single-nucleotide polymorphisms (SNPs); SponGES; SponGES_0617; SPONGES_0617_04-DR4; SPONGES_0617_07-CTD1; SPONGES_0617_12-CTD2; SPONGES_0617_13-CTD3; SPONGES_0617_15-DR7; SPONGES_0617_18-CTD4; SPONGES_0617_19-CTD5; SPONGES_0617_23-DR9; SPONGES_0617_24-CTD6; SPONGES_0617_27-CTD7; SPONGES_0617_28-DR10; SPONGES_0617_29-CTD8; SPONGES_0617_40-CTD9; SPONGES_0617_42-CTD10; SPONGES_0617_46-CTD11; SPONGES_0617_49-CTD12; SPONGES_0617_55-CTD13; SPONGES_0617_58-CTD14; SPONGES_0617_60-DR15; SPONGES_0617_61-CTD15
    Type: Dataset
    Format: text/tab-separated-values, 550 data points
    Location Call Number Limitation Availability
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    DATA PANGAEA
  • 2
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    Shapefile of Atlantic Seabed Areas - Results of a basin-wide cluster analysis of the Atlantic near seafloor environment (2022)
    PANGAEA
    Details
    Publication Date: 2024-04-20
    Description: This data set presents the results of an automated cluster analysis using Gaussian mixture models of the entire Atlantic seafloor environment. The analysis was based on eight global datasets and their derivatives: Bathymetry, slope, terrain ruggedness index, topographic position index, sediment thickness, POC flux, salinity, dissolved oxygen, temperature, current velocity, and phytoplankton abundance in surface waters along with seasonal variabilities (see Source data set). We obtained nine seabed areas (SBAs) that portray the Atlantic seafloor that are shown as polygons in the data set. The attribute table holds short descriptions of each SBA as well as about the colours used in the accompanying paper publication. Data sets like this can be used for further analysis like e.g. for landscape ecology metrics to identify regions of interest. The compressed file further contains a style file that can be used to directly load the correct style in the QGIS software package.
    Keywords: Atlantic; Atlantic_Ocean_Seabed_Areas; Atlantic Ocean; Binary Object; Binary Object (File Size); Classification; cluster analysis; Cluster analysis; ecology metrics; File content; Horizontal datum; iAtlantic; Integrated Assessment of Atlantic Marine Ecosystems in Space and Time; landscape; landscape metrics; Latitude, northbound; Latitude, southbound; Longitude, eastbound; Longitude, westbound; multivariate; seafloor; Vertical datum
    Type: Dataset
    Format: text/tab-separated-values, 10 data points
    Location Call Number Limitation Availability
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    DATA PANGAEA
  • 3
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    Atlantic seep mussels larval dispersal simulations and genetic data (2023)
    PANGAEA
    Details
    Publication Date: 2024-04-20
    Description: These data aim at evaluating the hypothesis of long-distance dispersal across the North Atlantic and the Equatorial Atlantic belt for the cold seep mussels Gigantidas childressi, G. mauritanicus, Bathymodiolus heckerae and B. boomerang. We combined mitochondrial Cox1 barcoding of some mussel specimens from both sides of the Atlantic (American vs European/African margins) with larval dispersal trajectories simulated from the VIKING20X model of the Atlantic circulation at a spatial scale not yet investigated. Larval dispersal modelling data correspond to transports of larvae over one year in surface waters from 21 geographic localities over 5 consecutive years (2015, 2016, 2017, 2018 and 2019) and 5 spawning dates (November, December, January, February and March) per year. Genetic data correspond to the geo-referenced sequences obtained for the 4 mussel species from some of the localities where larvae have been released during the modelling approach.
    Keywords: Analysis; Atlantic; Atlantic_Larval_Dispersal_Modelling_Experiment; Barbados_Prism_Kick_em_Jenny_crater_(KJC); Barbados_Prism_Trinidad_prism_(TRI); Barbados Prism; Bathymodiolus; Binary Object; Binary Object (File Size); Binary Object (Media Type); Cold seeps; DATE/TIME; ELEVATION; Equatorial Atlantic belt; Event label; EXP; Experiment; Experiment duration; File content; Gigantidas; Gulf_of_Guinea_Guiness_(GUIN); Gulf_of_Guinea_Nigeria_margin_(NM); Gulf_of_Guinea_West_Africa_margin_(WAM); Gulf_of_Mexico_Alaminos_Canyon_(AC); Gulf_of_Mexico_Brine_Pool_(BP); Gulf_of_Mexico_Louisiana_Slope_(LS); Gulf of Guinea; Gulf of Mexico; iAtlantic; Integrated Assessment of Atlantic Marine Ecosystems in Space and Time; larval dispersal; LATITUDE; Location; LONGITUDE; Mid-Atlantic_Ridge_Logatchev_seeps_(LOG); Mid-Atlantic Ridge; Model; Mussel; N_Mid-Atlantic_Ridge_Atlantis_Fracture_Zone_(LOST); NE_Atlantic_margin_Gulf_of_Cadiz_(GC); NE_Atlantic_margin_SWIM_fault_(SWIM); NE Atlantic margin; North_Brazil_margin_Amazon_fan_(AM); North Atlantic; North Brazil margin; North Mid-Atlantic Ridge; Ocean and sea region; Particles; South_Brazil_margin_Sao_Paulo_1_(SP); South_Brazil_margin_Sao_Paulo_2_(SPD); South Brazil margin; Speed, swimming; Temperature, water; US_Atlantic_Margin_Baltimore_Canyon_(BC); US_Atlantic_Margin_Bodie_Island_(BI); US_Atlantic_Margin_New_England_(NE); US_Atlantic_Margin_Norfolk_Canyon_(NC); US Atlantic Margin; West_Africa_Margin_Arguin_bank_(ARG); West_Africa_Margin_Cadamostro_Seamount_(CS); West Africa Margin
    Type: Dataset
    Format: text/tab-separated-values, 5252 data points
    Location Call Number Limitation Availability
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    DATA PANGAEA
  • 4
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    Atlantic seep mussels larval dispersal predictions under climate changes (2024)
    PANGAEA
    Details
    Publication Date: 2024-04-20
    Description: A projection of larval dispersal patterns of Atlantic cold seep mussels Gigantidas childressi, G. mauritanicus, Bathymodiolus heckerae and B. boomerang was carried out for the next 50 years under the constraint of global warming predicted by the IPCC for the most pessismistic scenario. Simulations were run at +00 years, +25 years and +50 years from initial years of 2014 to 2019 (+00Y) at 21 locations on the US, European and African coasts using the VIKING20X model, in which the Atlantic water temperatures predicted by the FOCI model were forced to the future dates. The dataset consists of a number of 5775 simulations carried out over 5 years X 5 spawning dates per prediction period (+00Y, +25Y, +50Y) with, for predictions at +25Y and +50Y, a repetition of simulations per quantile (0.025, 0.16, 0.5, 0.67 and 0.975) to take into account for the most extreme variations in water mass temperatures predicted by the FOCI model for a given date.
    Keywords: Analysis; Atlantic; Atlantic_Larval_Dispersal_Modelling_Experiment; Barbados_Prism_Kick_em_Jenny_crater_(KJC); Barbados_Prism_Trinidad_prism_(TRI); Barbados Prism; Bathymodiolus; Binary Object; Binary Object (File Size); Binary Object (Media Type); Climate change predictions; DATE/TIME; ELEVATION; Event label; EXP; Experiment; Experiment duration; File content; Gigantidas; Gulf_of_Guinea_Guiness_(GUIN); Gulf_of_Guinea_Nigeria_margin_(NM); Gulf_of_Guinea_West_Africa_margin_(WAM); Gulf_of_Mexico_Alaminos_Canyon_(AC); Gulf_of_Mexico_Brine_Pool_(BP); Gulf_of_Mexico_Louisiana_Slope_(LS); Gulf of Guinea; Gulf of Mexico; iAtlantic; Index; Integrated Assessment of Atlantic Marine Ecosystems in Space and Time; larval dispersal modelling; LATITUDE; Location; LONGITUDE; Mid-Atlantic_Ridge_Logatchev_seeps_(LOG); Mid-Atlantic Ridge; Model; N_Mid-Atlantic_Ridge_Atlantis_Fracture_Zone_(LOST); NE_Atlantic_margin_Gulf_of_Cadiz_(GC); NE_Atlantic_margin_SWIM_fault_(SWIM); NE Atlantic margin; North_Brazil_margin_Amazon_fan_(AM); North Brazil margin; North Mid-Atlantic Ridge; Ocean and sea region; Particles; Quantile; Regime; seep mussels; South_Brazil_margin_Sao_Paulo_1_(SP); South_Brazil_margin_Sao_Paulo_2_(SPD); South Brazil margin; Speed, swimming; Temperature, water; US_Atlantic_Margin_Baltimore_Canyon_(BC); US_Atlantic_Margin_Bodie_Island_(BI); US_Atlantic_Margin_New_England_(NE); US_Atlantic_Margin_Norfolk_Canyon_(NC); US Atlantic Margin; VIKING20X; West_Africa_Margin_Arguin_bank_(ARG); West_Africa_Margin_Cadamostro_Seamount_(CS); West Africa Margin
    Type: Dataset
    Format: text/tab-separated-values, 74550 data points
    Location Call Number Limitation Availability
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    DATA PANGAEA
  • 5
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    Late 20th Century Indian Ocean Heat Content Gain Masked by Wind Forcing (2020)
    AGU (American Geophysical Union) | Wiley
    Details
    Publication Date: 2023-02-08
    Description: Rapid increases in upper 700‐m Indian Ocean heat content (IOHC) since the 2000s have focused attention on its role during the recent global surface warming hiatus. Here, we use ocean model simulations to assess distinct multidecadal IOHC variations since the 1960s and explore the relative contributions from wind stress and buoyancy forcing regionally and with depth. Multidecadal wind forcing counteracted IOHC increases due to buoyancy forcing from the 1960s to the 1990s. Wind and buoyancy forcing contribute positively since the mid‐2000s, accounting for the drastic IOHC change. Distinct timing and structure of upper ocean temperature changes in the eastern and western Indian Ocean are linked to the pathway how multidecadal wind forcing associated with the Interdecadal Pacific Oscillation is transmitted and affects IOHC through local and remote winds. Progressive shoaling of the equatorial thermocline—of importance for low‐frequency variations in Indian Ocean Dipole occurrence—appears to be dominated by multidecadal variations in wind forcing.
    Type: Article , PeerReviewed
    Format: text
    Location Call Number Limitation Availability
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 6
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    The Submesoscale Kinetic Energy Cascade: Mesoscale Absorption of Submesoscale Mixed-Layer Eddies and Frontal Downscale Fluxes (2020)
    AMS (American Meteorological Society) | Wiley
    Details
    Publication Date: 2023-02-08
    Description: Mesoscale eddies can be strengthened by the absorption of submesoscale eddies resulting from mixed-layer baroclinic instabilities. This is shown for mesoscale eddies in the Agulhas Current system by investigating the kinetic energy cascade with a spectral and a coarse-graining approach in two model simulations of the Agulhas region. One simulation resolves mixed-layer baroclinic instabilities and one does not. When mixed-layer baroclinic instabilities are included, the largest submesoscale near-surface fluxes occur in winter-time in regions of strong mesoscale activity for upscale as well as downscale directions. The forward cascade at the smallest resolved scales occurs mainly in frontogenetic regions in the upper 30 m of the water column. In the Agulhas ring path, the forward cascade changes to an inverse cascade at a typical scale of mixed-layer eddies (15 km). At the same scale, the largest sources of the upscale flux occur. After the winter, the maximum of the upscale flux shifts to larger scales. Depending on the region, the kinetic energy reaches the mesoscales in spring or early summer aligned with the maximum of mesoscale kinetic energy. This indicates the importance of submesoscale flows for the mesoscale seasonal cycle. A case study shows that the underlying process is the mesoscale absorption of mixed-layer eddies. When mixed-layer baroclinic instabilities are not included in the simulation, the open-ocean upscale cascade in the Agulhas ring path is almost absent. This contributes to a 20 %-reduction of surface kinetic energy at mesoscales larger than 100 km when submesoscale dynamics are not resolved by the model.
    Type: Article , PeerReviewed
    Format: text
    Location Call Number Limitation Availability
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 7
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    On timescales and reversibility of the ocean's response to enhanced Greenland Ice Sheet melting in comprehensive climate models (2022)
    AGU (American Geophysical Union) | Wiley
    Details
    Publication Date: 2024-02-07
    Description: Warming of the North Atlantic region in climate history often was associated with massive melting of the Greenland Ice Sheet. To identify the meltwater’s impacts and isolate these from internal variability and other global warming factors, we run single-forcing simulations including small ensembles using three complex climate models differing only in their ocean components. In 200-year long pre-industrial climate simulations, we identify robust consequences of abruptly increasing Greenland runoff by 0.05 Sv: sea-level rise of 44±10 cm, subpolar North Atlantic surface cooling of 0.7˚C and a moderate AMOC decline of 1.1–2.0 Sv. The latter two emerge in under three decades—and reverse on the same timescale after the perturbation ends in year 100. The ocean translates the step-change perturbation into a multi-decadal to centennial signature in the deep overturning circulation. In all simulations, internal variability creates notable uncertainty in estimating trends, time of emergence and duration of the response.
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
    Format: text
    Format: text
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 8
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    Freshwater Contributions to Decadal Variability of the Indonesian Throughflow (2023)
    AGU (American Geophysical Union) | Wiley
    Details
    Publication Date: 2024-02-07
    Description: The Makassar Strait, the main passageway of the Indonesian Throughflow (ITF), is an important component of Indo-Pacific climate through its inter-basin redistribution of heat and freshwater. Observational studies suggest that wind-driven freshwater advection from the marginal seas into the Makassar Strait modulates the strait's surface transport. However, direct observations are too short (〈15 years) to resolve variability on decadal timescales. Here we use a series of global ocean simulations to assess the advected freshwater contributions to ITF transport across a range of timescales. The simulated seasonal and interannual freshwater dynamics are consistent with previous studies. On decadal timescales, we find that wind-driven advection of South China Sea (SCS) waters into the Makassar Strait modulates upper-ocean ITF transport. Atmospheric circulation changes associated with Pacific decadal variability appear to drive this mechanism via Pacific lower-latitude western boundary current interactions that affect the SCS circulation. Key Points: - A global ocean model is used to show how freshwater impacts the decadal variability of transport through the main Indonesian Throughflow pathway - Wind-driven advection of South China Sea freshwater induces an upstream pressure gradient that reduces transport - Freshwater input is modulated by atmospheric circulation changes associated with Pacific decadal variability
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
    Format: text
    Format: text
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 9
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    Changing Spatial Patterns of Deep Convection in the Subpolar North Atlantic (2021)
    AGU (American Geophysical Union) | Wiley
    Details
    Publication Date: 2024-02-07
    Description: Deep convection and associated deep water formation are key processes for climate variability, since they impact the oceanic uptake of heat and trace gases and alter the structure and strength of the global overturning circulation. For long, deep convection in the subpolar North Atlantic was thought to be confined to the central Labrador Sea in the western subpolar gyre (SPG). However, there is increasing observational evidence that deep convection also has occurred in the eastern SPG south of Cape Farewell and in the Irminger Sea, in particular, in 2015–2018. Here we assess this recent event in the context of the temporal evolution of spatial deep convection patterns in the SPG since the mid-twentieth century, using realistic eddy-rich ocean model simulations. These reveal a large interannual variability with changing contributions of the eastern SPG to the total deep convection volume. Notably, in the late 1980s to early 1990s, the period with highest deep convection intensity in the Labrador Sea related to a persistent positive phase of the North Atlantic Oscillation, the relative contribution of the eastern SPG was small. In contrast, in 2015–2018, deep convection occurred with an unprecedented large relative contribution of the eastern SPG. This is partly linked to a smaller north-westward extent of deep convection in the Labrador Sea compared to previous periods of intensified deep convection, and may be a first fingerprint of freshening trends in the Labrador Sea potentially associated with enhanced Greenland melting and the oceanic advection of the 2012–2016 eastern North Atlantic fresh anomaly.
    Type: Article , PeerReviewed
    Format: text
    Format: text
    Format: video
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    Location Call Number Limitation Availability
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 10
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    Toward ocean hindcasts in earth system models: AMOC variability in a partially coupled model at eddying resolution (2022)
    AGU (American Geophysical Union) | Wiley
    Details
    Publication Date: 2024-02-07
    Description: While forced ocean hindcast simulations are useful for a wide range of applications, a key limitation is their inability to simulate ocean-atmosphere feedbacks. As a consequence, they need to rely on artificial choices such as sea surface salinity restoring and other corrections affecting the surface freshwater fluxes. Fully coupled models overcome these limitations, but lack the correct timing of variability due to weaker observational constraints. This leads to a mismatch between forced and coupled models on interannual to decadal timescales. A possibility to combine the advantages of both modelling strategies is to apply a partial coupling (PCPL), i.e. replacing the surface winds stress in the ocean component by wind stress derived from reanalysis. To identify the capabilities, limitations and possible use cases of partial coupling, we perform a fully coupled, two partially coupled and an ocean-only experiment using an all-Atlantic nested ocean configuration at eddying resolution in a global climate model. We show that the correct timing of Atlantic Meridional Overturning Circulation (AMOC) variability in PCPL experiments is robust on timescales below 5 years. Mid-latitude wind stress curl changes contribute to decadal AMOC variability, but North Atlantic buoyancy fluxes are not significantly altered by incorporating reanalysed wind stress anomalies, limiting the success of PCPL on this timescale. Long term trends of the AMOC in PCPL mode are consistent with fully coupled model experiments under historic atmospheric boundary conditions, suggesting that a partially coupled model is still able to simulate the important ocean-atmosphere feedbacks necessary to maintain a stable AMOC.
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
    Format: text
    Format: text
    Location Call Number Limitation Availability
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    OceanRep: Article in a Scientific Journal - peer-reviewed
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