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59 results for “depth profile”
Secchi depth data and discrete depth profiles of water temperature, dissolved oxygen, conductivity, specific conductance, photosynthetic active radiation, oxidation-reduction potential, and pH for Beaverdam Reservoir, Carvins Cove Reservoir, Falling Creek Reservoir, Gatewood Reservoir, and Spring Hollow Reservoir in southwestern Virginia, USA 2013-2025
Discrete depth profiles of water temperature, dissolved oxygen, oxidation-reduction potential, conductivity, specific conductance, and pH were collected with multiple handheld water quality probes and discrete depth profiles of photosynthetically active radiation (PAR) were collected with a LI-COR underwater light meter from 2013 to 2025 in five drinking water reservoirs in southwestern Virginia, USA. These reservoirs are: Beaverdam Reservoir (Vinton, Virginia), Carvins Cove Reservoir (Roanoke, Virginia), Falling Creek Reservoir (Vinton, Virginia), Gatewood Reservoir (Pulaski, Virginia), and Spring Hollow Reservoir (Salem, Virginia). Beaverdam, Carvins Cove, Falling Creek, and Spring Hollow Reservoirs are owned and operated by the Western Virginia Water Authority as primary or secondary drinking water sources for Roanoke, Virginia, and Gatewood Reservoir is a drinking water source for the Town of Pulaski, Virginia. All discrete depth profiles were collected on approximately 1-meter intervals. The data package consists of two datasets: 1) Secchi depth data; and 2) discrete depth profiles of multiple water quality variables measured by handheld sensors. The Secchi data and discrete depth profiles were measured at the deepest site of each reservoir adjacent to the dam, as well as other in-reservoir sites. Handheld sensor measurements were also collected at a gauged weir on the primary inflow tributary, other inflows, and outflows at Falling Creek Reservoir; inflows and outflows at Beaverdam Reservoir; and inflows at Carvins Cove Reservoir. In 2021, YSI handheld data were also collected from a littoral site in Beaverdam Reservoir. In 2025, YSI handheld data were collected monthly from June to October from nine littoral sites around the perimeter of Falling Creek Reservoir. From 2024 - 2025, additional within-reservoir depth profiles were collected in Carvins Cove Reservoir and multiple sites. Data were collected approximately fortnightly in the spring months (March - Ma
Time series of high-frequency profiles of depth, temperature, dissolved oxygen, conductivity, specific conductance, chlorophyll a, turbidity, pH, oxidation-reduction potential, photosynthetically active radiation, colored dissolved organic matter, phycocyanin, phycoerythrin, and descent rate for Beaverdam Reservoir, Carvins Cove Reservoir, Falling Creek Reservoir, Gatewood Reservoir, and Spring Hollow Reservoir in southwestern Virginia, USA 2013-2025
Depth profiles of water biogeochemical properties were collected with SeaBird Electronics (SBE) Conductivity, Temperature, and Depth (CTD) profilers from 2013-2025 at five drinking water reservoirs in southwestern Virginia, USA. The study reservoirs are: Beaverdam Reservoir (Vinton, Virginia), Carvins Cove Reservoir (Roanoke, Virginia), Falling Creek Reservoir (Vinton, Virginia), Gatewood Reservoir (Pulaski, Virginia), and Spring Hollow Reservoir (Salem, Virginia). Beaverdam, Carvins Cove, Falling Creek, and Spring Hollow Reservoirs are owned and operated by the Western Virginia Water Authority as primary or secondary drinking water sources for Roanoke, Virginia, and Gatewood Reservoir is a drinking water source for the town of Pulaski, Virginia. The dataset consists of CTD depth profiles measured at the deepest site of each reservoir adjacent to the dam as well as other upstream reservoir sites. The profiles were collected approximately fortnightly in the spring months, weekly in the summer and early autumn, and monthly in the late autumn and winter. Beaverdam Reservoir, Carvins Cove Reservoir, and Falling Creek Reservoir were sampled every year in the dataset (2013-2025); Spring Hollow Reservoir was only sampled 2013-2017 and 2019; and Gatewood Reservoir was only sampled in 2016. Data availability differs across years due to additional sensors that have been added or replaced over time. From 2013-2016, profiles were taken with a CTD equipped with an SBE 43 Dissolved Oxygen sensor and an ECO FLNTU sensor for turbidity and chlorophyll. From 2017-2025, profiles were taken with a CTD equipped with an SBE 43 Dissolved Oxygen sensor, an ECO FLNTU sensor for turbidity and chlorophyll, a PAR-LOG ICSW sensor for photosynthetically active radiation, and a SBE 27 pH and ORP (oxidation-reduction potential) sensor. In 2022 and 2023, profiles were also taken with an additional CTD equipped with an SBE 43 Dissolved Oxygen sensor; an ECO Triplet Scattering Fluorescence sensor for
GHG-depths: Greenhouse gas depth-profile data in 522 lakes worldwide
Lakes, ponds, and reservoirs (hereafter: “lakes”) are significant sources of the greenhouse gases carbon dioxide (CO2) and methane (CH4). Emissions of CO2 and CH4 from lakes are regulated in part by in-lake processes, including the production and storage of gases in the lower parts of the water column (bottom waters). However, while substantial efforts have been made to improve estimates of greenhouse gas emissions from lakes, limited data on gas concentrations along depth profiles have prevented the incorporation of bottom-water processes in global emission estimates. Here, we present GHG-depths: the largest existing dataset of depth-profile CO2 and CH4 measurements worldwide, including 522 lakes across 38 countries and all seven continents. These data include contributions from 45 research teams and 56 published studies, totaling 2558 discrete sampling events. As global change continues to alter biogeochemical cycling in lakes, these data can help improve mechanistic models to better predict greenhouse gas production and emission from lakes worldwide.
Shipboard Conductivity–Temperature–Depth (CTD) and dissolved oxygen profile data collected during hypoxia surveys along six hydrographic sampling lines within Olympic Coast National Marine Sanctuary, 2004–2015
<p>This data set includes Conductivity-Temperature-Depth (CTD) and dissolved oxygen profile data that were collected along Washington State’s outer coast within Olympic Coast National Marine Sanctuary (OCNMS). Measurements were made along six cross-shelf hydrographic sampling lines during a series of hypoxia survey cruises from 2004 – 2015. The 398 CTD profiles were acquired using Sea-Bird Scientific 19 SeaCAT or 19plus SeaCAT CTD profilers with associated SBE-43 (Sea-Bird Electronics) or Beckman or YSI-type (Yellow Springs Instruments) dissolved oxygen sensors. The data were processed via Sea-Bird Scientific’s SBE Data Processing application using six of the modules in the following order: Data Conversion, Filter, Align CTD, Loop Edit, Derive, and Bin Average. These processing steps and associated methods are the same as those used to process CTD data collected during OCNMS mooring maintenance cruises (<a href="https://www.sciencedirect.com/science/article/pii/S2352340924001422">Risien et al., 2024</a>) and along the Newport Hydrographic Line (<a href="https://www.sciencedirect.com/science/article/pii/S2352340922001342">Risien et al., 2022</a>) located off the central Oregon coast.</p> <table> <tbody> <tr> <td><strong>Station Name </strong></td> <td><strong>Latitude</strong></td> <td><strong>Longitude</strong></td> <td><strong>Water Depth (m, MLLW)</strong></td> </tr> <tr> <td><strong>Cape Alava (CA)</strong></td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>CA010</td> <td>48.1661oN</td> <td>124.7540oW</td> <td>10</td> </tr> <tr> <td>CA020</td> <td>48.1661oN</td> <td>124.7598oW</td> <td>20</td> </tr> <tr> <td>CA030</td> <td>48.1659oN</td> <td>124.7783oW</td> <td>30</td> </tr> <tr> <td>CA040</td> <td>48.1659oN</td> <td>124.7852oW</td> <td>40</td> </tr> <tr> <td>CA045</td> <td>48.1659oN</td> <td>124.8335oW</td> <td>45</td> </tr> <tr> <td>CA050</td> <td>48.1658oN</td> <td>124.8578oW</td> <td>50</td> </tr> <tr> <td>CA060</td> <td>48.1659oN</td> <td>124.8843oW</td> <td>60</td> </tr> <tr> <td>CA070</td> <td>48.1655oN</td> <td>124.9011oW</td> <td>70</td> </tr> <tr> <td>CA080</td> <td>48.1657oN</td> <td>124.9141oW</td> <td>80</td> </tr> <tr> <td>CA090</td> <td>48.1659oN</td> <td>124.9247oW</td> <td>90</td> </tr> <tr> <td>CA100</td> <td>48.1658oN</td> <td>124.9319oW</td> <td>100</td> </tr> <tr> <td><strong>Teahwhit Head (TH)</strong></td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>TH030</td> <td>47.8759oN</td> <td>124.6481oW</td> <td>30</td> </tr> <tr> <td>TH035</td> <td>47.8761oN</td> <td>124.7024oW</td> <td>35</td> </tr> <tr> <td>TH040</td> <td>47.8760oN</td> <td>124.7281oW</td> <td>40</td> </tr> <tr> <td>TH050</td> <td>47.8761oN</td> <td>124.7567oW</td> <td>50</td> </tr> <tr> <td>TH060</td> <td>47.8765oN</td> <td>124.7822oW</td> <td>60</td> </tr> <tr> <td>TH070</td> <td>47.8765oN</td> <td>124.8084oW</td> <td>70</td> </tr> <tr> <td>TH080</td> <td>47.8768oN</td> <td>124.8415oW</td> <td>80</td> </tr> <tr> <td>TH090</td> <td>47.8769oN</td> <td>124.8868oW</td> <td>90</td> </tr> <tr> <td>TH100</td> <td>47.8769oN</td> <td>124.9182oW</td> <td>100</td> </tr> <tr> <td><strong>Hoh Head (HH)</strong></td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>HH025</td> <td>47.7688oN</td> <td>124.5605oW</td> <td>25</td> </tr> <tr> <td>HH042</td> <td>47.7688oN</td> <td>124.6428oW</td> <td>42</td> </tr> <tr> <td>HH065</td> <td>47.7688oN</td> <td>124.7401oW</td> <td>65</td> </tr> <tr> <td><strong>Raft River (RR)</strong></td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>RR015</td> <td>47.4632oN</td> <td>124.3748oW</td> <td>15</td> </tr> <tr> <td>RR020</td> <td>47.4644oN</td> <td>124.4510oW</td> <td>20</td> </tr> <tr> <td>RR042</td> <td>47.4632oN</td> <td>124.5199oW</td> <td>42</td> </tr> <tr> <td>RR065</td> <td>47.4629oN</td> <td>124.6074oW</td> <td>65</td> </tr> <tr> <td><strong>Cape Elizabeth (CE)</strong></td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>CE010</td> <td>47.3541oN</td> <td>124.3347oW</td> <td>10</td> </tr> <tr> <td>CE020</td> <td>47.354oN</td> <td>124.3608oW</td> <td>20</td> </tr> <tr> <td>CE030</td> <td>47.3538oN</td> <td>124.3913oW</td> <td>30</td> </tr> <tr> <td>CE040</td> <td>47.3534oN</td> <td>124.4678oW</td> <td>40</td> </tr> <tr> <td>CE050</td> <td>47.3532oN</td> <td>124.5064oW</td> <td>50</td> </tr> <tr> <td>CE060</td> <td>47.3529oN</td> <td>124.5510oW</td> <td>60</td> </tr> <tr> <td>CE070</td> <td>47.3528oN</td> <td>124.5823oW</td> <td>70</td> </tr> <tr> <td>CE080</td> <td>47.3527oN</td> <td>124.6158oW</td> <td>80</td> </tr> <tr> <td>CE090</td> <td>47.3526oN</td> <td>124.6491oW</td> <td>90</td> </tr> <tr> <td>CE100</td> <td>47.3522oN</td> <td>124.6754oW</td> <td>100</td> </tr> <tr> <td><strong>Moclips (MO)</strong></td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>MO010</td> <td>47.2214oN</td> <td>124.2394oW</td> <td>10</td> </tr> <tr> <td>MO015</td> <td>47.2214oN</td> <td>124.2599oW</td> <td>15</td> </tr> <tr> <td>MO020</td> <td>47.2214oN</td> <td>124.2791oW</td> <td>20</td> </tr> <tr> <td>MO030</td> <td>47.2195oN</td> <td>124.3347oW</td> <td>30</td> </tr> <tr> <td>MO042</td> <td>47.2195oN</td> <td>124.3958oW</td> <td>42</td> </tr> </tbody> </table>
PITS Apparent Depth Profiles for Mars Global Cave Candidate Catalog (MGC3) Features
<p>Apparent depth profiles calculated by the Pit Topography from Shadows (PITS) tool for the majority of the features in the Mars Global Cave Candidate Catalog (MGC<sup>3</sup>). PITS is a Python framework for automatically calculating apparent depth profiles for Martian and Lunar pits from just a single cropped satellite image. These images can also be single- or multi-band, such as in the case of the Mars Reconnaissance Orbiter (MRO) HiRISE camera. You can learn more about PITS by reading its <a href="https://academic.oup.com/rasti/article/2/1/492/7241547">journal article</a> in RAS Techniques and Instruments, going to its <a href="https://github.com/dlecorre387/Pit-Topography-from-Shadows/">GitHub repository</a> or reading the following <a href="https://www.danlecorre.com/post/first-paper-published">post</a>.</p> <p>Since not all catalogued cave candidates on Mars will be pits, PITS has so far been applied to the following MGC<sup>3</sup> subcategories:</p> <ul> <li>Atypical Pit Craters (APCs).</li> </ul> <p>With plans to extend this to:</p> <ul> <li>Lava tube skylights,</li> <li>small rimless pits,</li> <li>generic, amorphous pits,</li> <li>and polar pits.</li> </ul> <p>This totals 123 apparent depth profiles in CSV format, which have been derived automatically by PITS for 88 APCs. Therefore, these profiles can be plotted as the user prefers, and/or used in combination with other data to reveal more about this particular APC on the surface of Mars.</p> <p>Each depth profile's CSV file is named according to the HiRISE Reduced Data Record Version 1.1. (RDRV11) that it was calculated upon (e.g. ESP_011386_2065_RED_profile.csv for the red-band version of the HiRISE image ESP_011386_2065). Where there are multiple MGC3 APCs contained within a single image, the file names are numbered generally from the most northern to southernmost, or most westerly to easterly. ESRI shapefiles for the location of all APCs in each HiRISE image have been provided in polygon (containing the extents used to crop the larger HiRISE product) and point format in order to give context in these intances. </p> <p>As the headers suggest, the first four columns represent the shadow length (<em><span class="math-tex">\(L\)</span></em>), apparent depth (<em><span class="math-tex">\(h\)</span></em>), and the upper/lower bounds of <span class="math-tex">\(\Delta h\)</span>, respectively, before they have been corrected for non-zero emission angles (<span class="math-tex">\(\varepsilon\)</span>) at the time of image acquisition. Whereas the latter four columns represent the same quantities after <span class="math-tex">\(\varepsilon\)</span>-correction. How this correction is derived and applied is explained in the PITS journal article linked above.</p>
Hourly time series of Ives Lake (Huron Mountains, Marquette County, MI) Water Temperature-Depth Profiles, 2013-2022 (continuing study)
Long-term measurements of lake temperatures are essential to providing insights into local and regional changes in climate since large, still water bodies effectively act as a high-frequency filter. Ives Lake is a 30.7 m deep water body in northern Marquette County, in Michigan's Upper Peninsula. Beginning in 2013, temperature readings have been collected hourly from a string of twelve sensors located near the deepest point of the lake (approximately 46.84874 N lat, 87.84895 W long; identified by sonar survey in 2010 by first author). Measurements are continuing. The purpose of the project is to collect a data record of sufficient duration to determine if water temperatures are warming, and if the dates of autumn lake turnover are shifting toward later in the year.
Missouri reservoir profile data including temperature, depth, and oxygen profiles (1989-2022)
This dataset of limnological profiles starts in 1989 and is from 250 reservoirs in the state of Missouri (MO) in the USA collected by the University of Missouri Limnology Lab. Physical parameters derived from sensors include temperature and oxygen with depth. After 2017, sondes were upgraded to Yellow Springs Instruments (YSI) EXO3s; profiles include a range of physical, chemical, and biological parameters including depth, conductivity, pH, oxidative-reductive potential (ORP), chlorophyll a, phycocyanin (PC), phycoerythrin (PE), and turbidity. Most of the profiles were collected during the summer months (May-September) when the reservoirs were thermally stratified, but a few were taken during the rest of the year (October-April). The majority of profiles were taken at the deepest point in the reservoir directly up-reservoir of the dam. Sampling was conducted from a boat most of the time, but a few profiles were taken from bridges and docks. The bulk of the data come from the Statewide Lake Assessment Project (SLAP), funded by the Missouri Department of Natural Resources. The profiles are divided into a single file for 1989-2016 and then annual compiled datasets for 2017 and beyond. This data has been quality controlled for basic errors and any data outside of normal factory issued sensor ranges.
Missouri reservoir profile data including depth, temperature, oxygen, photopigments, conductivity, pH, turbidity, and oxidative-reductive potential starting in 2023
This dataset of annual limnological profiles starts in 2023 and is from reservoirs in the state of Missouri (MO) in the USA collected by the University of Missouri Limnology Lab. Physical parameters derived from sensors include temperature and oxygen with depth. Sondes used were Yellow Springs Instruments (YSI) EXO3s; profiles include a range of physical, chemical, and biological parameters including depth, conductivity, pH, oxidative-reductive potential (ORP), chlorophyll a, phycocyanin (PC), and turbidity. After May 2024, the turbidity sensor was replaced with a phycoerythrin (PE) sensor. Most of the profiles were collected during the summer months (May-September) when the reservoirs were thermally stratified, but a few were taken during the rest of the year (October-April). The majority of profiles were taken at the deepest point in the reservoir directly up-reservoir of the dam. Sampling was conducted from a boat. The bulk of the data come from the Statewide Lake Assessment Project (SLAP), funded by the Missouri Department of Natural Resources. The profiles are divided into single files for each year. This data has been quality controlled for basic errors and any data outside of normal factory issued sensor ranges.
Conductivity, temperature, and depth (CTD) vertical profiles from Lake Joyce, McMurdo Dry Valleys, Antarctica, November 2014
Vertical profiles of conductivity, temperature, and depth (CTD) were collected from Lake Joyce, a perennially ice-covered lake in the McMurdo Dry Valleys of Antarctica. Water column observations were made in November 2014 using a YSI 6600 multiparameter probe in the deepest region of the lake, as identified by Mackey et al. (2018). The water column was accessed by drilling a 10-inch wide hole through the perennial ice cover using a Jiffy drill. This data package includes CTD profiles, as well as measurements of salinity, total dissolved solids (TDS), dissolved oxygen (DO), pH, and pressure.
Lake Fryxell under-ice conductivity, temperature, and depth (CTD) profiles, McMurdo Dry Valleys, Antarctica, January 2025
To characterize the upper ~2 m of the water column beneath the ~3 m ice cover in Lake Fryxell, located in the McMurdo Dry Valleys of Antarctica, 27 CTD (conductivity, temperature, depth) profiles were collected at ~5 m horizontal spacing along a transect spanning the dive hole to the shoreline. Measurements were made using a YSI Castaway CTD mounted on a 1 m mast atop a remotely operated vehicle (ROV), profiling upward from ~2 m below the ice-water interface. Using an ROV rather than drilling a hole through the ice was intended to minimize artifacts associated with ice openings. Sampling late in the austral summer targeted conditions during maximum seasonal ice melt.
Elevational Transects (ET): Soil temperature depth profiles from Garwood, Miers, and Taylor Valley, McMurdo Dry Valleys, Antarctica (2019-2024, ongoing)
As part of the McMurdo Dry Valleys Long Term Ecological Research (LTER) project, the Elevational Transects (ET) study was established in 1993 to investigate how elevation and topographic variation influence soil biotic communities and associated soil properties in the McMurdo Dry Valleys of Antarctica. Transects consisting of low-, mid-, and high-elevation sites were initially established in the Bonney, Hoare, and Fryxell basins of Taylor Valley, with additional transects added in Garwood and Miers Valleys during the 2012-2013 austral summer. This data package contains year-round soil temperature measurements recorded at four depths (0, 5, 10, and 20 cm) by HOBO dataloggers installed at the mid-elevation sites of each valley during the 2018–2019 austral summer.
Conductivity, temperature, and depth (CTD) vertical profiles collected from lakes in the McMurdo Dry Valleys, Antarctica (1993-2025, ongoing)
As part of the Long Term Ecological Research (LTER) project in the McMurdo Dry Valleys of Antarctica, a series of Taylor Valley lakes have been monitored for conductivity, temperature, and depth (CTD). A Seabird instrument was used to record CTD profiles in these perennial ice covered lakes.
Conductivity–Temperature–Depth (CTD) and dissolved oxygen profile data from shipboard surveys collected within Olympic Coast National Marine Sanctuary, 2005-2023
<p>This data set includes Conductivity-Temperature-Depth (CTD) and dissolved oxygen profile data that were collected along Washington State’s outer coast within Olympic Coast National Marine Sanctuary towards the northernmost extent of the California Current System. Measurements were made at fourteen hydrographic stations during mooring deployment, recovery, and maintenance cruises between the months of May and October from 2005–2023. The 792 CTD profiles were acquired using Sea-Bird Scientific 19 SeaCAT or 19plus SeaCAT CTD profilers with associated SBE-43 (Sea-Bird Electronics) or Beckman or YSI-type (Yellow Springs Instruments) dissolved oxygen sensors. The data were processed via Sea-Bird Scientific’s SBE Data Processing application using six of the modules in the following order: <em>Data Conversion, Filter, Align CTD, Loop Edit, Derive, and Bin Average</em>. These processing steps and associated methods are the same as those used to process CTD data that make up the <a href="../records/5814071">Newport Hydrographic Line time series</a> located off the central Oregon coast thus allowing for a direct comparison between the two regions.</p> <table> <tbody> <tr> <td><strong>Station Name </strong></td> <td><strong>Latitude</strong></td> <td><strong>Longitude</strong></td> <td><strong>Water Depth (m, MLLW)</strong></td> </tr> <tr> <td><strong>Makah Bay (MB)</strong></td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>MB015</td> <td>48.3254oN</td> <td>124.6768oW</td> <td>15</td> </tr> <tr> <td>MB042</td> <td>48.3240oN</td> <td>124.7354oW</td> <td>42</td> </tr> <tr> <td><strong>Cape Alava (CA)</strong></td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>CA015</td> <td>48.1663oN</td> <td>124.7568oW</td> <td>15</td> </tr> <tr> <td>CA042</td> <td>48.1660oN</td> <td>124.8234oW</td> <td>42</td> </tr> <tr> <td>CA065 </td> <td>48.1659oN</td> <td>124.8949oW</td> <td>65</td> </tr> <tr> <td><strong>Teahwhit Head (TH)</strong></td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>TH015</td> <td>47.8761oN</td> <td>124.6195oW</td> <td>15</td> </tr> <tr> <td>TH042</td> <td>47.8762oN</td> <td>124.7334oW</td> <td>42</td> </tr> <tr> <td>TH065 </td> <td>47.8767oN</td> <td>124.7967oW</td> <td>65</td> </tr> <tr> <td><strong>Kalaloch (KL)</strong></td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>KL015</td> <td>47.6008oN</td> <td>124.4284oW</td> <td>15</td> </tr> <tr> <td>KL027</td> <td>47.5946oN</td> <td>124.4971oW</td> <td>27</td> </tr> <tr> <td>KL050 </td> <td>47.5933oN</td> <td>124.6112oW</td> <td>50</td> </tr> <tr> <td><strong>Cape Elizabeth (CE)</strong></td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>CE015</td> <td>47.3568oN</td> <td>124.3481oW</td> <td>15</td> </tr> <tr> <td>CE042</td> <td>47.3531oN</td> <td>124.4887oW</td> <td>42</td> </tr> <tr> <td>CE065 </td> <td> 47.3528oN</td> <td>124.5669oW</td> <td>65</td> </tr> </tbody> </table>
Multi-channel seismic reflection profiles SALTFLU (Salt deformation and sub-salt fluid circulation in the Algero-Balearic abyssal plain) - Pre-Stack Kirchhoff Time & Depth Migration 2022
<p>This archive contains sections of reprocessed multi-channel seismic reflection profiles SALTFLU, acquired south of Ibiza (Spain) in 2012 with the OGS Explora (pre-stack Kirchhoff time and depth stacks, and migration velocities in SEG-Y format). It also contains the cruise report describing the survey acquisition in 2012. Connected articles describe the processing flow applied to this dataset and interpretations led by the first author. </p> <p>Field File Identification and Shot Numbers (FFID, SHOTNO) are linearly interpolated by matching the CMP numbers before and after migration. Bytes 73-76 and 77-80 are identical to bytes 181-184 and 185-188 and contain the CMP coordinates.</p> <p> </p> <p> </p> <p> </p>
Data for publication: A pipeline for in-depth analysis of DNA virus populations by profiling the low abundant virus variants and partial genomic components
<p>Raw and processed sequence data from Oxford Nanopore and BGI short read sequencing platforms used in the publication: "A pipeline for in-depth analysis of DNA virus populations by profiling the low abundant virus variants and partial genomic components".</p>
Discrete Flow Cytometry of Depth Profile Samples from the Gradients 5 (2023) Cruise Using a BD Influx Cell Sorter
<p>The dataset consists of BD Influx-based analysis of phytoplankton populations from discrete flow cytometry data collected during the Gradients 2023 (Gradients 5/TN412) oceanographic research cruise in the equatorial Pacific Ocean. The data consists of cell abundance, cell size (equivalent spherical diameter), carbon quota, and carbon biomass for heterotrophic bacteria, picophytoplankton populations, namely the cyanobacteria Prochlorococcus and Synechococcus, and small eukaryotic phytoplankton (<5 μm ESD). Time is in UTC format, latitude and longitude are in decimal degrees, and depth is in meters. Further information can be found here: https://github.com/fribalet/FCSplankton</p>
Discrete Flow Cytometry of Depth Profile Samples from TN413 (2023) Using a BD Influx Cell Sorter
<p>The dataset consists of BD Influx-based analysis of phytoplankton populations from discrete flow cytometry data collected underway during the University of Washington School of Oceanography 2023 undergraduate senior thesis cruise (TN413) oceanographic research cruise from Hawaii to Fiji. The data consists of cell abundance, cell size (equivalent spherical diameter), carbon quota, and carbon biomass for heterotrophic bacteria, picophytoplankton populations, namely the cyanobacteria Prochlorococcus and Synechococcus, and small eukaryotic phytoplankton (<5 μm ESD). Time is in UTC format, latitude and longitude are in decimal degrees, and depth is in meters. Further information can be found here: https://github.com/fribalet/FCSplankton</p>
The effect of the graded bilayer design on the strain depth profiles and microstructure of CuW nano-multilayers
<p>In this document we share:</p> <p>-the XRD in-plane scans acquired on Cu/W multilayers at different incidence angle,</p> <p>-the in-situ stress curvature data acquired during multilayer growth,</p> <p>-the in plane d-spacing derived at different incidence angle, used for the simulation of the strain gradient.</p>
Dissolved trace metal depth profile concentrations from the North Pacific Ocean Gradients 3 (KM1906) spring 2019 cruise
<p>This dataset contains dissolved trace metal depth profiles collected in the North Pacific Ocean in spring of 2019 on the KM1906 Gradients 3 cruise (Chief Scientist E. Virginia Armbrust). The project was funded by the Simons Collaboration on Ocean Processes and Ecology Gradients program (SCOPE award 426570SP to SGJ). The samples were collected by trace metal clean rosette. Data were produced at the University of Southern California Marine Trace Elements Lab run by Prof. Seth G. John. Briefly, the metals were preconcentrated using an Elemental Scientific Inc. SeaFast automated robot, detected by Element 2 ICP-MS and quantified using isotope dilution as described in Hawco et al. 2020. <em>GCA</em> <a href="https://doi.org/10.1016/j.gca.2020.05.005">https://doi.org/10.1016/j.gca.2020.05.005</a>. All concentrations are dissolved (<0.2um SUPOR filter) and reported as nmol/L. </p>
Discrete Flow Cytometry of Depth Profile Samples from the Gradients 4 (2021) Cruise Using a BD Influx Cell Sorter
<p>The dataset consists of BD Influx-based analysis of phytoplankton populations from discrete flow cytometry data collected during the Gradients 2021 (Gradients 4/TN397) oceanographic research cruise in the equatorial Pacific Ocean. The data consists of cell abundance, cell size (equivalent spherical diameter), carbon quota, and carbon biomass for heterotrophic bacteria, picophytoplankton populations, namely the cyanobacteria Prochlorococcus and Synechococcus, and small eukaryotic phytoplankton (<5 μm ESD). Time is in UTC format, latitude and longitude are in decimal degrees, and depth is in meters. Further information can be found here: https://github.com/fribalet/FCSplankton</p>
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.