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844 results for “South Atlantic”
Seasonal Distribution of Ammonia-Oxidizing Archaea and Ammonia-Oxidation Rates in the South Atlantic Bight from April to November 2014
Previous work in nearshore waters of the Georgia USA coast has demonstrated mid-summer peaks in the abundance of Thaumarchaeota (blooms with 100 to 1,000-fold increases) accompanied by spikes in nitrite concentration. These studies were performed at one location, so the areal extent of the bloom is unknown, nor has it been demonstrated conclusively that it develops in inshore waters. We collected data on rates of ammonia oxidation and the distribution of Thaumarchaeota, ammonia-oxidizing Betaproteobacteria (AOB), nitrite-oxidizing Nitrospina and environmental variables during 6 cruises aboard the UNOLS vessel R/V Savannah from April to November 2014 on transects of the South Atlantic Bight to evaluate the areal extent and timing of the bloom. This data set includes measurements of Chlorophyll-a concentration, PAR attenuation coefficient, oxygen concenrations, temperature, salinity and nitogenous nutrient concentrations (nitrite, nitrite + nitrate, ammonium, urea), and estimates of Archaea, bacteria and diatom gene concentration based on quantitative PCR.
Concentrations, turnover rates and fluxes of polyamines in coastal waters of the South Atlantic Bight during April and October 2011
Polyamines are short-chain aliphatic compounds containing multiple amine groups. They are important components of the cytosol of eukaryotes and are present at mmol/L concentrations inside phytoplankton cells, while complex polyamines play a role in biosilica deposition. Concentrations of polyamines measured in seawater are typically in the sub nmol/L range, implying rapid and efficient uptake by osmotrophs, likely bacterioplankton. We measured turnover rates of three polyamines (putrescine, spermidine and spermine) using 3H-labeled compounds and determined their concentrations by HPLC to estimate polyamine contributions to dissolved organic matter and bacterioplankton carbon and nitrogen demand. These measurements were made on transects from the inner shelf to the Gulf Stream across the South Atlantic Bight (SAB) during April and October of 2011 and in salt marsh estuaries on the Georgia coast during August of 2011 and April of 2012. This data set includes measurements of water column variables (temperature, salinity, biogenic Silica), nutrients (nitrite, nitrate+nitrite, ammonium and dissolved inorganic nitrogen), and concentrations and turnover rates of polyamine compounds.
Seasonal Evolution of Terrigenous Dissolved Organic Matter in the South Atlantic Bight off Georgia in 2014
Six surveys of the central South Atlantic Bight (SAB) off of Georgia were conducted in 2014. The primary objective of the research cruises was to characterize estuary-shelf exchange and the dispersal of freshwater into the coastal ocean around Sapelo Island off the Georgia coast. The surveys, in April, May, July, August, September, and November, were intended to sample shelf conditions under different seasons. Most of the sampling stations were located at the mouth of the estu-aries around Sapelo Island and over the inner and mid-shelf (<60 km offshore). Eighty samples from transects extending across the shelf from the mouths of the Altamaha River and of Sapelo Sound were selected for the analyses of molecular composition using ultrahigh resolution mass spectrometry (Fourier transform ion cyclotron reso-nance mass spectrometry [FT-ICR MS]) and stable carbon iso-topic signatures (delta 13C). This data set includes spectral analysis of the DOM, including spectral slope (275-295nm wavelength), terrigenous peaks from mass spectrometry analysis, and a computed terrigenous index indicating fraction of terrigenous DOM in water samples.
Oyster Paleobiology along the South Atlantic Coast of the United States
This dataset includes morphometric data collected from 37,805 oyster shells (Crassostrea virginica) from 15 Late Archaic (ca. 4500-3500 cal. BP) through Mississippian (ca. 1150 – 370 cal. BP) period archaeological sites situated along the South Atlantic Coast of the United States. Variations in oyster size is an important proxy for paleoenvironment and human population pressures. These data are part of a larger project examining oyster ecosystem stability and Native American oyster harvesting practices over the last 5,000 years. Oyster measurements were collected by many undergraduate and graduate students from multiple universities. Carey Garland added to and cleaned the data sheet between August 2018 and May 2019. The dataset was structured to include the Island, site name, time period, and provenience (e.g., unit, level, etc.) associated with each oyster measured. The original oyster database contains sensitive information, such as the specific location of archaeological sites. If a professional archaeologist needs site location information, they can contact the Georgia Archaeological Site File.
The Blue Carbon of Southern South West Atlantic salt marshes and their biotic and abiotic drivers
<p>Organic carbon stocks, salt marsh plant biomass, crab burrow abundances and diameters. This data was generated by sampling at 11 salt marsh sites along 3000 km of coastal line in southern SW Atlantic coast in South America. Organic carbon stocks and burial rates extarcted from other publications and used to update global estimates are also included with their respective references. Values of biotic and abiotic drivers included in the Structural Equation Model (SEM) to evaluate their roles in belowground organic carbon stocks.</p>
Dataset for the adjustment of a wave forecasting system for the deep waters of the South Atlantic Ocean and for the southern coast of Brazil: Numerical Wave Experiment in the South of Brazil (NWESB).
<p>This dataset corresponds to the input files of the test domains used for the simulations of the coupled GFS (Global Forecast System) and WAVEWATCH III models in the waters of the South Atlantic Ocean and in waters of the Brazilian Southeastern during the passage of a cold front and the presence of strong pressure gradient between a low-pressure system and a high-pressure system. In the files generated by WAVEWATCH III, wave fields are presented from 2016-03-25 14:00:00, which is the date from when the model it stabilizes. Also contained in this dataset are the files of the GFS model wind fields, the bathymetry files (eTOPO1) and the files of the bathymetry entries in WAVEWATCH III.</p> <p>All files with suffix 2 correspond to the geographic region 70°W to 4°W longitude and 55°S to 13°S latitude and all files with suffix 3 correspond to the geographic region 70°W at 20°W longitude and 55°S at 13°S latitude.</p> <p><strong>ww3-2.inp</strong> and <strong>Bathymetry2.ascii</strong> are the input configuration files for WAVEWATCH III bathymetry and bathymetry (in ASCII format) respectively for the WW3-2 domain. <strong>gfs-2.nc</strong> is the input file of the winds obtained from the outputs of the GFS model (in NetCDF format) for the WW3-2 domain. <strong>ww3-2.nc</strong> is the WAVEWATCH III model output file with the simulated waves for the WW3-2 domain.</p> <p><strong>ww3-3.inp</strong> and <strong>Bathymetry3.ascii</strong> are the input configuration files for WAVEWATCH III bathymetry and bathymetry (in ASCII format) respectively for the WW3-3 domain. <strong>gfs-3.nc</strong> is the input file of the winds obtained from the outputs of the GFS model (in NetCDF format) for the WW3-3 domain. <strong>ww3-3.nc</strong> is the WAVEWATCH III model output file with the simulated waves for the WW3-3 domain.</p> <p>The GFS model files contain data every 6 hours and the WAVEWATCH III model files contain data every 1 hour. All files have a spatial resolution of 0.25° (27.78 km).</p> <p> </p> <p><strong>Other data that complement this dataset:</strong></p> <p><strong><a href="https://figshare.com/articles/figure/Complementary_figures_of_Parameter_adjustments_of_the_GFS_WAVEWATCH_III_coupled_models_in_Southern_Brazil/16726375"><em>Complementary figures of Parameter adjustments of the GFS – WAVEWATCH III coupled models in Southern Brazil.</em></a></strong></p> <p><em><strong><a href="https://figshare.com/articles/dataset/Dataset_for_the_adjustment_of_a_wave_forecasting_system_for_the_deep_waters_of_the_South_Atlantic_Ocean_and_for_the_southern_coast_of_Brazil_Output_files_in_GrADS_format_/16767058">Dataset for the adjustment of a wave forecasting system for the deep waters of the South Atlantic Ocean and for the southern coast of Brazil (Output files in GrADS format).</a></strong></em></p> <p> </p> <p> </p>
SO-WISE South Atlantic Ocean and Indian Ocean Observational Constraints
<p>This dataset contains an initial set of curated and processed oceanographic observations collected as part of a joint effort between the EU SO-CHIC project and a UKRI Future Leaders Fellowship. It is partly intended to be used as a set of observational constraints for a Weddell Gyre region state estimate, although it can be used for more general analysis purposes as well. It has been used as part of an unsupervised clustering analysis [see Jones (2022) for software and Jones and Zhou (2022) for labelled dataset, see references]. </p> <p><strong>Overall spatial and temporal coverage</strong></p> <ul> <li>Latitude: 85°S-30°S</li> <li>Longitude: 65°W-80°E</li> <li>Time: 1974-2020</li> </ul> <p><strong>Contents</strong></p> <ul> <li>CPOM_SSH: sea-ice corrected sea surface height </li> <li>CTD: temperature and salinity profiles from ship-based CTD casts </li> <li>FLOATS: temperature and salinity profiles from Argo floats </li> <li>SEALS: temperature and salinity profiles from seal-mounted profilers</li> <li>Stress_and_EKE: sea-ice corrected surface stress and EKE </li> <li>XBT: temperature and salinity profiles from expendable bathythermographs (XBTs)</li> </ul> <p><strong>Profile quality control</strong></p> <p>We only consider profiles with good position and time flags, as well as good temperature, salinity, and pressure measurements with good flags. Duplicated profiles are identified when multiple profiles are found within 24 hours over the same 2 km x 2 km grid cell, and only one profile within the spatio-temporal window is used. We then used the MITprof toolbox (Forget, G., 2017) to pre-process the selected profiles, re-gridding them onto 72 standard pressure levels; the vertical interval varies from 20 dbar at the surface to 100 dbar in the deep ocean. </p> <p><strong>SSH processing</strong></p> <p>SSH data is sea-ice corrected version provided by the Centre for Polar Observation and Modelling (CPOM) in the UK. It is composed by two satellite missions, Envisat (2004/05-2012/03) and Cryosat-2 (2010/07-2020/04). The data is available in montly along-track format. A gaussian 300km filter, ±3 std outliner removal and 0.5x0.25 deg interpolation is applied to grid the data. Intersatellite offset is removed using the overlapped period between two missions using the mean difference map. SSH is referenced to EIGEN6C4 geoid to obtain the dynamic ocean topography feild for the computation of geostrophic velocity. See the README in the Stress_and_EKE directory for more information. </p> <p><strong>Sources</strong></p> <ul> <li>Argo floats: <a href="http://argo.ucsd.edu">http://argo.ucsd.edu</a></li> <li>World Ocean Database: <a href="https://www.ncei.noaa.gov/products/world-ocean-database">https://www.ncei.noaa.gov/products/world-ocean-database</a></li> <li>MEOP-CTD Database (seal profilers): <a href="https://www.meop.net/">https://www.meop.net/</a></li> <li>CDRv4 available via NSIDC: <a href="https://nsidc.org/data/G02202">https://nsidc.org/data/G02202</a></li> <li>Polar Pathfinder sea ice drift data via NSIDC: <a href="https://nsidc.org/data/nsidc-0116">https://nsidc.org/data/nsidc-0116</a></li> </ul> <p><strong>Version</strong></p> <p>This is a pre-production version, in that it has not yet been used with a state estimate. </p>
Historical shorelines for the Atlantic barrier islands of Virginia south of Chincoteague Inlet, 1949-2006
Historical shorelines for the Virginia barrier islands from Fishermans Island to Wallops Island were compiled from various remote sensing and ground-based sources. The COAST dataset (Dolan et al. 1978, Dolan et al. 1990) tabulated shoreline position based on historic aerial orthophotographs at transects spaced 50 meters apart located along the mid-Atlantic coast of the United States (South Carolina to New Jersey); only data for the Virginia barrier islands (1949-1988) are presented here. COASTS data are supplemented with more recent shoreline data digitized from aerial imagery (USGS 1994 and VGIN 2002) and collected with GPS (Fenster 2006). Baselines and transects used both to reconstruct the COASTS data and to produce shoreline positions and calculate shoreline rates of change using DSAS are also included. Note: there are some unresolved georeferencing issues that cause inconsistencies in the shorelines from different base data frames. Data from different data frames should be integrated with caution. Future versions of this dataset will resolve these issues.
Water Body Checklists 2019: South Atlantic Species List
Species checklists created using effechecka and modified polygons from IHO. The polygons were reduced in resolution.<p></p>List of species collected from the South Atlantic Ocean region using effechecka and a modified polygon from the International Hydrographic Association.
Water Body Checklists: South Atlantic Species List
Species checklists created using effechecka and modified polygons from IHO. The polygons were reduced in resolution.<p></p>List of species collected from the South Atlantic Ocean region using effechecka and a modified polygon from the International Hydrographic Association.
Supporting Data for "Identifying the Origins of Nanoplastics in the Abyssal South Atlantic Using Backtracking Lagrangian Simulations with Fragmentation"
<p>Supporting Data for "Identifying the Origins of Nanoplastics in the Abyssal South Atlantic Using Backtracking Lagrangian Simulations with Fragmentation", published in the Ocean and Coastal Research Journal. The repository consists of the code used for the simulations and analysis, and the supplementary information document associated with the main manuscript, the Lagrangian simulation outputs and aditional data used for the analysis.</p>
Sampling Effort Metadata for the Central and South Atlantic Offshore and Deep-Sea Benthos
<p>Metadata containing information on the sampling of benthic taxa in => 30 m water depth in the Central and South Atlantic. This data was compiled as part of a baseline review of the science, policy and management of the region (Bridges et al. in press). Metadata was compiled from sources identified through a literature search and information provided by members of the Challenger 150 Central and South Atlantic Regional Scientific Research Working Group.</p> <p>Version 1 (November, 2022): Metadata used in the Bridges et al. (in press) gap analysis with the exclusion of sensitive datasets (Atkinson et al. In prep). These are in the process of being made open access and will be added in due course. </p> <p> </p> <p><strong>References</strong></p> <p>Atkinson et al in prep. SeaMap FBIP.</p> <p>Bridges. A.E.H., Howell, K.L., Amaro, T., Atkinson, L., Barnes, D.K.A., Bax, N., Bell, J.B., Bernardino, A.F., Beuck, L., Braga-Henriques, A., Brandt, A., Bravo, M.E., Brix, S., Butt, S., Carranza, A., Doti, B.L., Elegbede, I.O., Esquete, P., Freiwald, A., Gaudron, S.M., Guilhon, M., Hebbeln, D., Horton, T., Kainge, P., Kaiser, S., Lauretta, D., Limongi, P., Mcquaid, K.A., Milligan, R.J., Miloslavich, P., Narayanaswamy, B.E., Orejas, C., Paulus, S., Pearman, T.R.R., Perez, J.A., Ross, R.E., Saeedi, H., Shimabukuro, M., Sink, K., Stevenson, A., Taylor, M., Titschack, J., Vieira, R.P., Vinha, B. & Wienberg, C. Review of the Central and South Atlantic Shelf and Deep-Sea Benthos: Science, Policy and Management. <em>Oceanography and Marine Biology: An Annual Review</em>.</p> <p> </p>
Fig. 3 in Revision of Bairdiella (Sciaenidae: Perciformes) from the western South Atlantic, with insights into its diversity and biogeography
Fig. 3. The Atlantic coast of North, Central, and South America showing the geographic distribution of Bairdiella goeldi sp. nov. (yellow = molecular north–northeastern lineage, light blue = molecular southeastern lineage, white = no molecular data), B. ronchus (red), and B. veraecrucis (green). Some symbols represent more than one locality or a large number of specimens.
Figure 1 in The hermit crab Sympagurus dimorphus (Anomura: Parapaguridae) at the edge of its range in the south-western Atlantic Ocean: population and morphometry features
Figure 1. Sympagurus dimorphus. Densities (number of individuals/100 m2) in the sampling areas from 2002 through 2006. Left column shows presence/absence data including all sampling sites, and right column shows densities on a relative scale.
Fig. 2 in Early Pleistocene lineages of Bagre bagre (Linnaeus, 1766) (Siluriformes: Ariidae), from the Atlantic coast of South America, with insights into the demography and biogeography of the species
Fig. 2. Phylogenetic tree of the Bayesian Inference of the Bagre derived from the concatenated database of the Cytb 1 and ATPase 8/6 genes. Only unique haplotype are included here. The first value on each branch corresponds to the ML support value and the second one to the BI. Only support values and posterior probabilities above 60% are shown. Grey = northern Brazilian coast lineage, including the semi-arid sector of the northeast coast; Black = southern Brazilian coast.
Fig. 6 in Early Pleistocene lineages of Bagre bagre (Linnaeus, 1766) (Siluriformes: Ariidae), from the Atlantic coast of South America, with insights into the demography and biogeography of the species
Fig. 6. Scatterplots of the principal components PC1 and PC2, obtained from the analysis of one meristic and nine morphometric variables in Bagre bagre, with factor loadings for the first principal components. Abbreviations: E, east Brazilian coast; h, humid northeastern coast of Brazil; N, northern Brazilian coast; sa, semi-arid northeastern coast of Brazil; S, southeast Brazilian coast.
Fig. 4 in Early Pleistocene lineages of Bagre bagre (Linnaeus, 1766) (Siluriformes: Ariidae), from the Atlantic coast of South America, with insights into the demography and biogeography of the species
Fig. 4. Genealogiesofthehaplotypesof (A) themitochondrial Cytb gene, based on the TIM2+I+G evolutionary model, and (B) the mitochondrial ATPase 8/6 gene, based on the HKY+G model. Green = northern Brazilian coast influenced by the Amazon–Orinoco plume, Light blue = semi-arid northeastern coast, Orange = southeastern coast.
Fig. 1 in Early Pleistocene lineages of Bagre bagre (Linnaeus, 1766) (Siluriformes: Ariidae), from the Atlantic coast of South America, with insights into the demography and biogeography of the species
Fig. 1. Geographic distribution of the two Bagre bagre lineages found in South America [red triangle = northern Brazilian coast, including region dominated by the plume of the Amazon and Orinoco rivers and semi-arid sector of Brazilian northeast coast (light blue = mouth of the Orinoco River; black circle = Macapá, AP; dark blue circle = Bragança, PA; yellow = São Luis, MA; green = Fortaleza, CE), and inverted black triangle = eastern and southern Brazilian coast, including the humid sector of the northeast coast (white circle = Santos, SP)] showing the number of specimens analyzed in each region (not bold = morphological analysis, and bold = molecular analysis). Green = northern Brazilian coast influenced by the Amazon– Orinoco plume, Light blue = semi-arid northeastern coast of Brazil; Dark blue = humid northeastern coast of Brazil, Yellow = east coast, and Orange = southeast coast).
Fig. 3 in Early Pleistocene lineages of Bagre bagre (Linnaeus, 1766) (Siluriformes: Ariidae), from the Atlantic coast of South America, with insights into the demography and biogeography of the species
Fig. 3. Bayesian strict clock chronogram based on the 1535 bps of the concatenated genes (Cytb and ATPase 8/6). The calibration points and evolutionary rates were based on Betancur-R. & Armbruster (2009).
Fig. 7. A in Early Pleistocene lineages of Bagre bagre (Linnaeus, 1766) (Siluriformes: Ariidae), from the Atlantic coast of South America, with insights into the demography and biogeography of the species
Fig. 7. A. Occurrence of Bagre bagre, Bagre marinus and other species of the genera Amphiarius, Aspistor, Cathorops, Genidens, Notarius, and Sciades, on the Atlantic coast of South America. Numbers of the lots deposited in zoological collections.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.