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487 results for “South coast”
Survey of small mammals using trapping data on all Virginia Coast Reserve barrier islands south of Parramore Island (inclusive) 1975-1978
During 1975 and 1977 live-trapping surveys of small-mammals of the Virginia Barrier Islands were conducted. Primary species encountered were Oryzomys palustris, Mus musculus, Micrutus pennsylvanicus, Rattus norvegicus, Cryptotis parva, and Peromyscus leucopus. Data is presented as primary trapping records giving the date of capture, island, species, sex and reproductive condition of the captured animal. Each animal was tagged to allow individual identification upon recapture. Each island was typically trapped for 8 days in two 4-day sessions.
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.
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>
Dataset on the dental morphology and occlusal dental wear of pre-colonial societies of the South and Southeast Coast of Brazil
<p>This dataset compiles information on dental morphology and occlusal dental wear of 431 individuals exhumed from coastal and riverine sites of the South and Southeast Coast of Brazil, dated between approximately 10,000 to 1,000 years before present. Dental traits were scored according to the Arizona State University Dental Anthropology System (ASUDAS) (Scott and Irish, 2017; Turner II et al., 1991). Few additional mandibular traits were added following Hauser and Stefano (1989). Occlusal dental wear was scored according to the method described in Smith (1984).</p> <p>Sex and age at death estimations derive from previous studies (Estevam, 2020; Fischer, 2012; Neves et al., 2005; Silva, 2005; Tognoli, 2016; Wesolowski, 2007). When this information was not available from previous studies, it was assessed by the first author (Fidalgo, 2021) using standard protocol methods (Buikstra and Ubelaker, 1994). Further detailed information and description of each variable can be consulted within the “description” and “dental grades” sheets in the excel file.</p> <p>The dataset is part of a PhD project developed at the Museu de Arqueologia e Etnologia da Universidade de São Paulo, carried by Daniel Fidalgo and advised by Veronica Wesolowski and Mark Hubbe (Fidalgo, 2021). Manuscripts have already been published using this data (Fidalgo et al., 2021a, 2021b). All research was funded by Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP), grants 17/20637-4 and 19/18289-3. It was also supported by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) grant 001.</p>
Buoy and Other Sensors Data at the South East Coast of Iceland (Höfn area) on Nov 20 - 24, 2020
<p>This dataset contains the information about sea state and environmental parameters in the area of tidal inlet near Höfn city, South East coast of Iceland. Buoy data is given with original half-hour time spacing. Wind and tidal sensors' data are given with the original 10 min time spacing. All of the given parameters did not undergo any re-interpolation, filtering or any other processing.</p> <p>structure of the "Buoy_data_20201120T010100_to_20201124T125900.csv" file</p> <pre><code>Comma-separated values'(.csv) table (217 rows 3 columns) with the the following fields: 1st column: time in the format dd-Mmm-yyyy HH:MM:SS; 2nd column: Significant wave height (Hs) in meters (m); 3rd column Peak wave period in seconds (s).</code></pre> <p>structure of the "Sea_level_tide_wind_data_20201120T010100_to_20201124T125900.csv" file (originally data was obtained from the <a href="http://vedur.mogt.is/harbor/index.php?action=ReadingsDrillDown&harborid=4&stationid=1011">web page</a> of Weather information system MogT ehf. Hornafjörður, Iceland - the corresponding table fields' names are doubled in Icelandic for convenience) </p> <pre><code>Comma-separated values'(.csv) table (649 rows 5 columns) with the the following fields: 1st column: time in the format dd-mm-yyyy HH:MM:SS; 2nd column: observed sea level (Sjávarhæð) in meters (m); 3rd column astronomical tide (Flóðatafla) in meters (m); 4th column wind speed (Vindur) in meters per second (m/s); 5th column wind direction (Vindátt) in degrees (deg).</code></pre> <p>The corresponding data chunks are published after the kind allowance of the data owners: Vignir Júlíusson and Greipur Sigurðsson.</p> <p> </p>
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.
FIGURE 3 A, C in A new species of Strongylodesma Lévi, 1969 (Porifera; Demospongiae; Poecilosclerida; Latrunculiidae) from Aliwal Shoal on the east coast of South Africa
FIGURE 3 A, C. Skeletal architecture of the holotype (SAM H 5083) (A, 100 X; C, 50 X); C. Skeletal architecture showing the clear mesohyl region below the paratangential layer of anisostrongyles (100 X); B. Skeletal architecture of the paratype (SAF 94 23) (50 X); D. Skeletal architecture showing the region of convoluted tracts of anisostrongyles (100 X).
FIGURE 2. A in A new species of Strongylodesma Lévi, 1969 (Porifera; Demospongiae; Poecilosclerida; Latrunculiidae) from Aliwal Shoal on the east coast of South Africa
FIGURE 2. A. Gross morphology of Strongylodesma aliwaliensis sp. nov. (SAM H 5083); B. A close up frame of the fungiform areolate porefields and cylindrical oscules of Strongylodesma aliwaliensis sp. nov. (SAM H 5083); C. Smooth anisostrongyles with one end narrower within Strongylodesma aliwaliensis sp. nov. (Anisostrongyles) (1000 X).
FIGURE 6. A in A new species of Australian frog (Myobatrachidae: Uperoleia) from the New South Wales mid-north coast sandplains
FIGURE 6. A representative oscillogram (above) and spectrogram (below) of the advertisement call of Uperoleia mahonyi sp. nov., Oyster Cove, NSW. The x-axis is time in seconds.
Holocene relative sea-level data from the Atlantic coasts of South America
<p>This spreadsheet is a complete record of the Holocene sea-level proxies in the southwestern Atlantic, from Brazil to Argentina following the HOLSEA template. </p>
Algal Epiphyte Biomass from Seagrass Tissue Along the South Texas Coast (2011 - 2021)
<p>Estimates of algal epiphytic biomass are made from separate leaf samples of entire shoots. Leaf samples for epiphytic biomass must be processed within three days of collection. In the laboratory, epiphytes are separated from a known leaf area using a scalpel or razor blade. Scraped material is then collected and retained on pre-weighed glass fiber filters. The collected epiphytic biomass and scraped seagrass leaves are then dried to a constant weight at 60°C for determination of dry weight biomass. Samples were taken at six sites along the Texas coast from 2011 - 2021.</p>
Figure 1 in Are fisheries regulations influencing the biology and reproduction of the surmullet Mullus surmuletus Linnaeus, 1758 on the south-eastern coasts of France (NW Mediterranean)?
Figure 1. – Sampling sites in West, AMA (Adjacent Marine Protected Area of Hyères Bay) and East zones on the south-eastern coast of France, NW Mediterranean Sea.
Figure 4 in Are fisheries regulations influencing the biology and reproduction of the surmullet Mullus surmuletus Linnaeus, 1758 on the south-eastern coasts of France (NW Mediterranean)?
Figure 4. – Percentages of both sexes and females:males sex-ratio of Mullus surmuletus by zone (A) and season (B).
Figure 3 in Are fisheries regulations influencing the biology and reproduction of the surmullet Mullus surmuletus Linnaeus, 1758 on the south-eastern coasts of France (NW Mediterranean)?
Figure 3. – Mean (± SE) total length (TL, cm) of Mullus surmuletus in West, AMA and East zones. N: number of analyzed individuals per sex in zones. Values with the same post-hoc letters (red for females, blue for males) are not significantly different (p> 0.05).
Figure 2 in Are fisheries regulations influencing the biology and reproduction of the surmullet Mullus surmuletus Linnaeus, 1758 on the south-eastern coasts of France (NW Mediterranean)?
Figure 2. – Percentage of individuals of Mullus surmuletus analyzed by two-cm size class (total length in cm) and by sex. N: number of individuals, F: females, M: males, Undet.: unidentified group includes immature individuals and those whose sex could not be identified.
ScienceDex guides
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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.