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693 results for “mouth”
Biocomplexity at North Temperate Lakes LTER: Coordinated Field Studies: Large Mouth Bass Growth 2006
Lakeshore residential development is associated with changes in littoral habitat, riparian habitat, and ecosystem function with potential impacts ramifying through aquatic food webs. Effects of these changes on economically important game fishes may vary with fish size. We investigated largemouth bass (Micropterus salmoides) size-specific growth rates across 16 lakes spanning the range of lakeshore residential development in Wisconsin’s Northern Highland Lake District using a longitudinal multilevel model. Growth rates of small fish had a strong positive relationship with lakeshore residential development. The strength of the relationship decreased with length and became increasingly negative for fish longer than 210 mm. This pattern may be driven by a release from density-dependent growth, shifts in available prey sources, reduced macrophyte cover, or angling-induced selection pressures. Regardless of the mechanism, our results indicate, relative to undeveloped lakes, largemouth bass in highly developed lakes take 1.5 growing seasons longer to enter the fishery (356 mm).
Initial Sample of HYPERNETS Hyperspectral Water Reflectance Measurements for Satellite Validation at the mouth of the Gironde Estuary, MAFR site (France)
<p>The HYPERNETS project (www.hypernets.eu) has the overall aim to ensure that high quality in situ measurements are available to support the (VNIR/SWIR) optical Copernicus products. Therefore, it established a new autonomous hyperspectral spectroradiometer (HYPSTAR® - www.hypstar.eu) dedicated to land and water surface reflectance validation with instrument pointing capabilities. In the prototype phase, the instrument is being deployed at 24 sites covering a range of water and land types and a range of climatic and logistic conditions. This dataset provides the first published data for the HYPERNETS site at the Gironde Estuary, MAGEST Network, in France (MAFR). It is a subset of the complete data record which consists of the best quality MAFR measurements which could be used for satellite validation. </p> <p>The provided NetCDF files are the L2A hypernets products with water leaving radiance and reflectances without NIR Similarity Correction (see Ruddick et al., 2006, DOI:<a href="http://dx.doi.org/10.2307/3841124">10.2307/3841124</a>). The reflectance in the L2A products is the Water Reflectance without NIR Similarity Correction (referred to as reflectance_nosc in the file) defined as:</p> <p><span class="math-tex"><em>ρ</em><em>w</em><em>n</em><em>o</em><em>s</em><em>c</em>=<em>π</em>(<em>L</em><em>u</em>−<em>ρ</em><em>F</em><em>L</em><em>d</em>)/<em>E</em><em>d</em></span></p> <p>where Lu is the upwelling radiance (at 40° zenith angle, and, 90° or 135° azimuth angle relative to the sun), Ld is the downwelling radiance (at 140° zenith angle, and, 90° or 135° azimuth angle relative to the sun). Ed is the (hemispherical) downwelling irradiance (i.e. including both direct solar and diffuse sky irradiance).</p> <p>These reflectances have dimensions of wavelength and series, where each series is a set of measurements for the computation of a water reflectance measurement. In addition to variables for wavelength and bandwidth, the files also contain variables that provide for each series the acquisition time, viewing and solar angles, and quality flags (typically no flags are set in the data provided in this dataset). These NetCDF files also contain further relevant metadata as attributes. See https://hypernets-processor.readthedocs.io/ for further info.</p> <p>The HYPSTAR®-SR (Standard Range) instruments deployed at each land HYPERNETS site consist of a VNIR sensor and autonomously collect data between 380-1000 nm at various viewing geometries and send it to a central server for quality control and processing. The VNIR sensor spans 1330 channels between 380 and 1000 nm with a FWHM of 3 nm. The hypernets_processor (Goyens et al. 2021, DOI: <a href="https://doi.org/10.1109/IGARSS47720.2021.9553738">10.1109/IGARSS47720.2021.9553738</a>; De Vis et al. in prep.) automatically processes all this data into various products, including the L2A surface reflectance product provided here. The current dataset is limited to the 400-900 nm range. Uncertainties are not yet included.</p> <p>To obtain this dataset, we start from the full MAFR data record and omit all the data that do not pass all of the quality checks performed as part of the hypernets_processor. In addition, an additional screening procedure was developed to supply the best quality data suitable for satellite validation:</p> <p>1. The coefficient of variation in water reflectance is below 10% in the 600-700 nm range</p>
Hourly water chemistry measurements at the mouth of West Falmouth Harbor, MA, USA from 2005 to 2019 and 2023
West Falmouth Harbor (West Falmouth, MA, USA) has been experiencing a dramatic increase in nitrogen loading from an upgradient municipal wastewater treatment facility since the early 2000s. As part of a long-term study into the effects of this nitrogen enrichment, we have been measuring water chemistry at the mouth of the harbor to calculate exchange between the harbor and adjacent coastal waters of Buzzards Bay. Water samples were taken hourly over 24- to 48-hour periods during several periods in 2005-2009, 2014, 2017, 2019, and 2023. Data from 2005-2009 were collected year-round; samples from 2014 and later were collected during June through August. Samples were processed for ammonium, phosphate, nitrate + nitrite, total nitrogen, and total phosphorus unless otherwise notated. During some sampling years, additional samples were run for silicate, chlorophyll, total dissolved nitrogen, total dissolved phosphorus, dissolved organic carbon, particulate organic carbon, and particulate organic nitrogen. Salinity is reported for all samples. Samples were collected with an ISCO autosampler and stored on ice until analysis. Full analysis details and quality control methods are available in Hayn et al. 2014 (doi: 10.1007/s12237-013-9699-8) and Hayn 2025 (doi: 10.7298/btm6-ba76).
Digital Elevation Model (DEM) of Doboy Sound at the mouth of the Duplin River near Sapelo Island, Georgia
The purpose of this study was to map the bathymetry of Doboy Sound near the mouth of the Duplin River adjacent to Sapelo Island, Georgia. This study extends a previous bathymetry mapping project conducted in 2009. The primary objective of the Duplin River project in 2009 was to provide data in support of understanding the sediment and water exchange process between intertidal areas and tidal creeks of the Duplin River. The Center for Marine and Wetland Studies (CMWS) surveyed the Doboy Sound using the Simrad EM3002D Multibeam Echosounder (MBES) in April 2011. A digital elevation model (DEM) was then developed based on the depth survey data.
PIE LTER, Year 2018, 15 minute interval, water quality measurements of water column temperature, salinity, oxygen, and depth near the mouth of Plum Island Sound, Massachusetts
Year 2018, 15 minute measurements of water column temperature, salinity, oxygen and depth in Plum Island Sound at the Ipswich Bay Yacht Club, Ipswich, MA.
Global reanalysis of riverine water levels at the river mouth
<p>Dataset prepared for manuscript "The effect of surge on riverine flood hazard and impact in deltas globally" (Eilander <em>et al </em>2020)</p> <p>This dataset includes water level data and discharge at 3433 river mouth locations globally, including several components of nearshore still water levels based on a model framework for global compound flood simulations. We usedof runoff from tier 2 of the EartH2Observe (E2O) project (Dutra <em>et al</em> 2017, Schellekens <em>et al</em> 2017) with meteorological forcing from ERA-Interim (Dee <em>et al</em> 2011) and MSWEP v1.2 (Beck <em>et al</em> 2017), surge levels from the Global Tide and Surge Reanalysis (GTSR) based on the GTSM model (Muis <em>et al</em> 2016), and tide levels from the FES2012 model (Carrere <em>et al</em> 2012). These runoff and dynamic sea level (surge and tide) data were used to force the global river routing model CaMa-Flood (Yamazaki <em>et al</em> 2011) to simulate riverine water levels.</p> <p>The accompanying excel file provides an table explaining the data dimensions, variables and metadata.</p>
From the Horse's Mouth: The Words We Use to Teach Diverse Student Groups Across Three Continents
<p>Word frequency pairs for courses A, B, C from: </p> <p>Brett A. Becker, Daniel Gallagher, Paul Denny, James Prather, Colleen Gostomski, Kelli Norris, and Garrett Powell. 2022. From the Horse’s Mouth: The Words We Use to Teach Diverse Student Groups Across Three Continents. In Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V. 1 (SIGCSE 2022), March 3–5, 2022, Providence, RI, USA. ACM, New York, NY, USA, 7 pages. https://doi.org/10.1145/3478431.3499392</p> <p><strong>When referring to this dataset, please cite the above article. That contains the DOI of this dataset. Please do not cite this dataset directly without citing the article.</strong></p>
Anechoic McVAMPIRE – Anechoic Multichannel Varying Mouth Position Impulse Response Dataset
<p>This dataset contains impulse responses (IRs) that were recorded in an anechoic room. The recording setup imitates the geometry of a minivan with eight seats arranged in three seat rows. The IRs were captured with 14 overhead microphones positioned in the imaginary car roof using a built-in mouth simulator of a head and torso simulator (HATS) at eight passenger seat positions with eleven orientations each. In addition, the dataset contains IRs measured with four lateral loudspeakers imitating door loudspeakers, as well as a noise floor recording.</p> <p>This dataset supplements the <a href="https://doi.org/10.5281/zenodo.12806684">In-Car McVAMPIRE</a> dataset which was captured with an identical microphone setup in a real car. Both datasets can be used to simulate speech in a car from different seats with different speaker orientations including the loudspeaker-enclosure-microphone (LEM) system under anechoic or realistic, reverberant conditions.</p>
Kingdom of Saudi Arabia. al-Ḥasāʾ, Jabal al-Qāra (جَبَل ٱلْقَارَة). Pottery production, kiln mouth being fed, 1970.
<p>[KSA QAR 1970.15] Kingdom of Saudi Arabia. al-Ḥasāʾ, Jabal al-Qāra. Pottery production, kiln mouth being fed, as documented 1970.</p>
Marine macrobenthic assemblages off Bevano River mouth (2019)
<p>This dataset provides the abundance (ind. m<sup>-2</sup>) of marine macrobenthic invertebrate species at 39 random sampling points from 0.5 to 8 m depth along the coast (5 km) off the NATURA 2000 site IT4070009 "Ortazzo, Ortazzino e Foce del Torrente Bevano", sampled from 22 May to 4 July, 2019. Sediment grain size and organic matter are also provided.</p> <p>The dataset is provided in three formats: </p> <p>- Microsoft Excel XLSX file, including 3 sheets (Dataset, Fields and units, Taxonomy) </p> <p>- CSV files (UTF-8), 3 files corresponding to the 3 sheets of the Excel file </p> <p>- ESRI Shapefile (UTF-8, geometry point, EPSG:4326 - WGS 84)</p> <p>The dataset includes 39 records, one for each sampling point, and 111 fields. The first 12 fields are described in Table 4). The following fields concern the abundance of the identified taxa as individuals preserved in alcohol sorted and classified under microscope (ind. m<sup>-2</sup> ± 10). All the dataset fields are described in the file “Fields and units”, while the taxonomic related information for each taxon is provided in the file “Taxonomy”. Information extracted from the World Register of Marine Species (WoRMS; <a href="https://marinespecies.org/">https://marinespecies.org/</a>) is provided here.</p> <p>A total of 99 soft bottom taxa belonging to the Phyla Annelida (29), Arthropoda (28), Cnidaria (1), Echinodermata (2), Mollusca (37), Nemertea (1), and Phoronida (1) were identified. Of these, 51 have been recognized at species level.</p> <p>This dataset comes from the project "Characterization of the mouth area of the Bevano River and identification of strategies for the conservation and enhancement of nursery areas for protected species of commercial interest", carried out by the Interdepartmental Research Center for Environmental Sciences (CIRSA) of the Alma Mater Studiorum University of Bologna. The project was financed by the Emilia-Romagna Region (call FLAG Costa dell'Emilia-Romagna 2018) with funds from the European Union (FEAMP 2014/2020, Action 2.A.a, "Marine and lagoon habitats - Studies and research"), and took place from January to August 2019 (Abbiati et al., 2019 DOI: <a href="http://doi.org/10.5281/zenodo.4016598">10.5281/zenodo.4016598</a>). This dataset has been revised and completed within the project "Ecosystem for Sustainable Transition in Emilia-Romagna" (Code: ECS_00000033 - CUP: B33D21019790006; Mission 04 Education and research - Component 2 From research to business Investment 1.5 - NextGenerationEU) .</p> <p> </p> <p>First 12 fields in the dataset.</p> <table> <tbody> <tr> <td> <p><strong>Field</strong></p> </td> <td> <p><strong>Darwin Core term</strong></p> </td> <td> <p><strong>Unit</strong></p> </td> <td> <p><strong>Precision</strong></p> </td> <td> <p><strong>Note</strong></p> </td> </tr> <tr> <td> <p>locationID</p> </td> <td> <p>locationID</p> </td> <td> <p>NA</p> </td> <td> <p>NA</p> </td> <td> <p>Sampling location identifier (ID) specific to the data set</p> </td> </tr> <tr> <td> <p>samplingDate</p> </td> <td> <p>eventDate</p> </td> <td> <p>YYYY-MM-DD</p> </td> <td> <p>NA</p> </td> <td> <p>Conforms to ISO 8601-1:2019</p> </td> </tr> <tr> <td> <p>samplingTime</p> </td> <td> <p>eventTime</p> </td> <td> <p>HH:MM</p> </td> <td> <p>± 10 min</p> </td> <td> <p>Central European Summer Time CEST (UTC+2) conforms to ISO 8601-1:2019</p> </td> </tr> <tr> <td> <p>decimalLatitude</p> </td> <td> <p>decimalLatitude</p> </td> <td> <p>decimal degrees</p> </td> <td> <p>± 0.00001</p> </td> <td> <p>WGS84 (EPSG: 4326) - WAAS/EGNOS enabled GPS position</p> </td> </tr> <tr> <td> <p>decimalLongitude</p> </td> <td> <p>decimalLongitude</p> </td> <td> <p>decimal degrees</p> </td> <td> <p>± 0.00001</p> </td> <td> <p>WGS84 (EPSG: 4326) - WAAS/EGNOS enabled GPS position</p> </td> </tr> <tr> <td> <p>Depth</p> </td> <td> <p>maximumDepthInMeters</p> </td> <td> <p>m</p> </td> <td> <p>± 0.1</p> </td> <td> <p>Mean Lower Low Water - measured with echosounder or depth gauge corrected by tide gauge of Porto Corsini (RA)</p> </td> </tr> <tr> <td> <p>SamplingGear</p> </td> <td> <p>NA</p> </td> <td> <p>NA</p> </td> <td> <p>NA</p> </td> <td> <p>Van Veen grab operated from boat or bailer manually operated by diver inside a cylindrical frame</p> </td> </tr> <tr> <td> <p>SamplingArea</p> </td> <td> <p>NA</p> </td> <td> <p>m^2</p> </td> <td> <p>± 0.001</p> </td> <td> <p>Sampler size</p> </td> </tr> <tr> <td> <p>Mud</p> </td> <td> <p>NA</p> </td> <td> <p>% dry mass</p> </td> <td> <p>± 0.1%</p> </td> <td> <p><63 µ wet sieved recovered on Whatman filter paper and then dried at 80°C for 24 hours before weighing at ± 0.00001 g</p> </td> </tr> <tr> <td> <p>FineSand</p> </td> <td> <p>NA</p> </td> <td> <p>% dry mass</p> </td> <td> <p>± 0.1%</p> </td> <td> <p>250-63 µ wet sieved recovered on Whatman filter paper and then dried at 80°C for 24 hours before weighing at ± 0.00001 g</p> </td> </tr> <tr> <td> <p>MediumSand</p> </td> <td> <p>NA</p> </td> <td> <p>% dry mass</p> </td> <td> <p>± 0.1%</p> </td> <td> <p>>250 µ wet sieved recovered on Whatman filter paper and then dried at 80°C for 24 hours before weighing at ± 0.00001 g</p> </td> </tr> <tr> <td> <p>OrganicMatter</p> </td> <td> <p>NA</p> </td> <td> <p>% dry mass</p> </td> <td> <p>± 0.1%</p> </td> <td> <p>Loss on Ignition (LOI%) at 450°C 8h and weighted at ± 0.00001 g</p> </td> </tr> <tr> <td> <p>Actiniaria</p> </td> <td> <p>NA</p> </td> <td> <p>ind. m^-2</p> </td> <td> <p>± 10</p> </td> <td> <p>Individuals preserved in alcohol sorted and classified under microscope</p> </td> </tr> </tbody> </table>
Striped venus clam (Chamelea gallina) abundance, size, and biomass off Bevano River mouth (2019)
<p>This dataset provides the abundance (ind. m<sup>-2</sup>) of the striped venus clams, <em>Chamelea gallina</em> (Linnaeus, 1758), at 71 random sampling points (Fig. 3) from 0.5 to 8 m depth along the coast (5 km) off the NATURA 2000 site IT4070009 "Ortazzo, Ortazzino e Foce del Torrente Bevano", sampled from 22 May to 4 July, 2019. Where available, the mean and standard deviation of shell length (i.e. the maximum distance between anterior and posterior margins) of <em>Chamelea gallina </em>determined to the nearest 0.01 mm using a manual calliper, and the wet biomass per square metre (g m<sup>-2</sup>), estimated on the basis of the mean shell length, by length–weight relationship (according to <a href="https://doi.org/10.1080/24750263.2019.1668066">Petetta et al., 2019</a>), were provided. Depth, sediment grain size, and organic matter at each point are also provided. </p> <p>The dataset is provided in three formats: </p> <ul> <li>Microsoft Excel XLSX file, including 3 sheets (Dataset, Fields and units, Parameters) </li> <li>CSV files (UTF-8), 3 files corresponding to the 3 sheets of the Excel file </li> <li>ESRI Shapefile (UTF-8, geometry point, EPSG:4326 - WGS 84)</li> </ul> <p> </p> <p>The dataset includes 71 records, one for each sampling point, and 17 fields, which are described in the Excel sheet/CSV file “Fields and units” (see also Table 6). The Excel sheet/CSV file provides details and coefficients of the length–weight relationship (log W= log a + b log L; where: W=wet weight (g), L=length (mm), Log base=10) used to estimate the wet biomass from the mean lengths and abundances (the calculation formulas are present in the Excel sheet).</p> <p>Finally, ESRI Shapefile provides users with direct upload in any Geographic Information System (GIS). Nevertheless, due to this file format limitations, dataset field names have been truncated and/or renamed to fit 10 characters.</p> <p>Fields in the dataset (NA=not available).</p> <table> <thead> <tr> <th scope="col"> <p><strong>Field</strong></p> </th> <th scope="col"> <p><strong>Darwin Core term</strong></p> </th> <th scope="col"> <p><strong>Unit</strong></p> </th> <th scope="col"> <p><strong>Precision</strong></p> </th> <th scope="col"> <p><strong>Note</strong></p> </th> </tr> </thead> <tbody> <tr> <td> <p>locationID</p> </td> <td> <p>locationID</p> </td> <td> <p>NA</p> </td> <td> <p>NA</p> </td> <td> <p>Sampling location identifier (ID) specific to the data set</p> </td> </tr> <tr> <td> <p>samplingDate</p> </td> <td> <p>eventDate</p> </td> <td> <p>YYYY-MM-DD</p> </td> <td> <p>NA</p> </td> <td> <p>Conforms to ISO 8601-1:2019</p> </td> </tr> <tr> <td> <p>samplingTime</p> </td> <td> <p>eventTime</p> </td> <td> <p>HH:MM</p> </td> <td> <p>± 10 min</p> </td> <td> <p>Central European Summer Time CEST (UTC+2) conforms to ISO 8601-1:2019</p> </td> </tr> <tr> <td> <p>decimalLatitude</p> </td> <td> <p>decimalLatitude</p> </td> <td> <p>decimal degrees</p> </td> <td> <p>± 0.00001</p> </td> <td> <p>WGS84 (EPSG: 4326) - WAAS/EGNOS enabled GPS position</p> </td> </tr> <tr> <td> <p>decimalLongitude</p> </td> <td> <p>decimalLongitude</p> </td> <td> <p>decimal degrees</p> </td> <td> <p>± 0.00001</p> </td> <td> <p>WGS84 (EPSG: 4326) - WAAS/EGNOS enabled GPS position</p> </td> </tr> <tr> <td> <p>Depth</p> </td> <td> <p>maximumDepthInMeters</p> </td> <td> <p>m</p> </td> <td> <p>± 0.1</p> </td> <td> <p>Mean Lower Low Water - measured with echosounder or depth gauge corrected by tide gauge of Porto Corsini (RA)</p> </td> </tr> <tr> <td> <p>SamplingGear</p> </td> <td> <p>NA</p> </td> <td> <p>NA</p> </td> <td> <p>NA</p> </td> <td> <p>Van Veen grab operated from boat or bailer manually operated by diver inside a cylindrical frame</p> </td> </tr> <tr> <td> <p>SamplingArea</p> </td> <td> <p>NA</p> </td> <td> <p>m2</p> </td> <td> <p>± 0.001</p> </td> <td> <p>Sampler size</p> </td> </tr> <tr> <td> <p>Mud</p> </td> <td> <p>NA</p> </td> <td> <p>% dry mass</p> </td> <td> <p>± 0.1%</p> </td> <td> <p>Sediment particles <63 µ wet sieved recovered on Whatman filter paper and then dried at 80°C for 24 hours before weighing at ± 0.00001 g</p> </td> </tr> <tr> <td> <p>FineSand</p> </td> <td> <p>NA</p> </td> <td> <p>% dry mass</p> </td> <td> <p>± 0.1%</p> </td> <td> <p>Sediment particles 250-63 µ wet sieved recovered on Whatman filter paper and then dried at 80°C for 24 hours before weighing at ± 0.00001 g</p> </td> </tr> <tr> <td> <p>MediumSand</p> </td> <td> <p>NA</p> </td> <td> <p>% dry mass</p> </td> <td> <p>± 0.1%</p> </td> <td> <p>Sediment particles >250 µ wet sieved recovered on Whatman filter paper and then dried at 80°C for 24 hours before weighing at ± 0.00001 g</p> </td> </tr> <tr> <td> <p>OrganicMatter</p> </td> <td> <p>NA</p> </td> <td> <p>% dry mass</p> </td> <td> <p>± 0.1%</p> </td> <td> <p>Sediment organic matter content obtained by Loss of weight on Ignition (LOI%) at 450°C 8h and weighted at ± 0.00001 g</p> </td> </tr> <tr> <td> <p>Individuals</p> </td> <td> <p>NA</p> </td> <td> <p>ind. sample-1</p> </td> <td> <p>± 1</p> </td> <td> <p>Individuals of <em>Chamelea gallina </em>retrieved in each sample, preserved in alcohol sorted and classified under microscope</p> </td> </tr> <tr> <td> <p>Abundance</p> </td> <td> <p>NA</p> </td> <td> <p>ind. m-2</p> </td> <td> <p>± 10</p> </td> <td> <p>Abundance of <em>Chamelea gallina</em> per square meter estimated on the basis of the sampling area</p> </td> </tr> <tr> <td> <p>MeanLength</p> </td> <td> <p>NA</p> </td> <td> <p>mm</p> </td> <td> <p>± 0.01</p> </td> <td> <p>Mean shell length (i.e. the maximum distance between anterior and posterior margins) of <em>Chamelea gallina</em> determined to the nearest 0.01 mm using a manual calliper</p> </td> </tr> <tr> <td> <p>SDLength</p> </td> <td> <p>NA</p> </td> <td> <p>mm</p> </td> <td> <p>± 0.01</p> </td> <td> <p>Standar deviation of mean shell length of <em>Chamelea gallina</em></p> </td> </tr> <tr> <td> <p>WetMass</p> </td> <td> <p>NA</p> </td> <td> <p>g m-2</p> </td> <td> <p>± 1</p> </td> <td> <p>Wet biomass per square meter of <em>Chamelea gallina</em> estimated on the basis of the mean shell length, by length–weight relationship (according to <a href="https://doi.org/10.1080/24750263.2019.1668066">Petetta et al., 2019</a> DOI:10.1080/24750263.2019.1668066), and abundnce</p> </td> </tr> </tbody> </table> <p> </p> <p>This dataset comes from the project "Characterization of the mouth area of the Bevano River and identification of strategies for the conservation and enhancement of nursery areas for protected species of commercial interest", carried out by the Interdepartmental Research Center for Environmental Sciences (CIRSA) of the Alma Mater Studiorum University of Bologna. The project was financed by the Emilia-Romagna Region (call FLAG Costa dell'Emilia-Romagna 2018) with funds from the European Union (FEAMP 2014/2020, Action 2.A.a, "Marine and lagoon habitats - Studies and research"), and took place from January to August 2019 (<a href="https://doi.org/10.5281/zenodo.4016598">Abbiati et al., 2019</a>). Finally, this dataset has been revised and completed within the project “Ecosystem for Sustainable Transition in Emilia-Romagna” (ECOSISTER, Code: ECS_00000033 - CUP: B33D21019790006).</p> <p> </p>
Year 2007, 15 minute interval, water quality measurements of water column temperature, salinity, oxygen, and depth near the mouth of Plum Island Sound, Massachusetts
Year 2007, 15 minute measurements of water column temperature, salinity, oxygen and depth in Plum Island Sound at the Ipswich Bay Yacht Club, Ipswich, MA.
Year 2009, 15 minute interval, water quality measurements of water column temperature, salinity, oxygen, and depth near the mouth of Plum Island Sound, Massachusetts
Year 2009, 15 minute measurements of water column temperature, salinity, oxygen and depth in Plum Island Sound at the Ipswich Bay Yacht Club, Ipswich, MA.
Year 2008, 15 minute interval, water quality measurements of water column temperature, salinity, oxygen, and depth near the mouth of Plum Island Sound, Massachusetts
Year 2008, 15 minute measurements of water column temperature, salinity, oxygen and depth in Plum Island Sound at the Ipswich Bay Yacht Club, Ipswich, MA.
Year 2010, 15 minute interval, water quality measurements of water column temperature, salinity, oxygen, and depth near the mouth of Plum Island Sound, Massachusetts
Year 2010, 15 minute measurements of water column temperature, salinity, oxygen and depth in Plum Island Sound at the Ipswich Bay Yacht Club, Ipswich, MA.
Year 2011, 15 minute interval, water quality measurements of water column temperature, salinity, oxygen, and depth near the mouth of Plum Island Sound, Massachusetts
Year 2011, water quality sonde data. 15 minute measurements of water column temperature, salinity, oxygen and depth in Plum Island Sound at the Ipswich Bay Yacht Club pier in Ipswich, MA.
Year 2012, 15 minute interval, water quality measurements of water column temperature, salinity, oxygen, and depth near the mouth of Plum Island Sound, Massachusetts
Year 2012, 15 minute measurements of water column temperature, salinity, oxygen and depth in Plum Island Sound at the Ipswich Bay Yacht Club.
Year 2013, 15 minute interval, water quality measurements of water column temperature, salinity, oxygen, and depth near the mouth of Plum Island Sound, Massachusetts
Year 2013, 15 minute measurements of water column temperature, salinity, oxygen and depth in Plum Island Sound at the Ipswich Bay Yacht Club.
PIE LTER, Year 2019, 15 minute interval, water quality measurements of water column temperature, salinity, oxygen, and depth near the mouth of Plum Island Sound, Massachusetts
Year 2019, 15 minute measurements of water column temperature, salinity, oxygen and depth in Plum Island Sound at the Ipswich Bay Yacht Club, Ipswich, MA.
PIE LTER, Year 2020, 15 minute interval, water quality measurements of water column temperature, salinity, oxygen, and depth near the mouth of Plum Island Sound, Massachusetts
Year 2020, 15 minute measurements of water column temperature, salinity, oxygen and depth in Plum Island Sound at the Ipswich Bay Yacht Club, Ipswich, MA. There were sifgnificant datalogger power, radio telecommunication and sonde cabling corrosion issues during the Covid-19 Spring - Fall of 2020. There are many missing data time periods due to issues and some limited field work capabilities due to Covid working restrictions.
ScienceDex guides
Understand access before you commit
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.