Skip to main content
Powered by ShareScore

Find research datasets worth reusing

Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.

154

datasets available to search

ShareScore release 0.7.1

Reset

Dataset results

154 results for “Dissolved oxygen”

Learn how ShareScore rates datasets ↗
dryad36/100

Oxygen availability regulates the quality of soil dissolved organic matter by mediating microbial metabolism and iron oxidation

Open the record for dataset details and reuse information.

publicOct 2022View details →
edi36/100

Estimates of surface layer net community production based on underway Lagrangian measurements of the dissolved O2/Ar ratio using Equilibrator Inlet Mass Spectrometry (EIMS), based on both steady-state and non-steady-state assumptions of the mixed-layer biological oxygen budget. Also included are estimates of the potential contribution of vertical fluxes: advection, eddy diffusion, and entrainment.

The ratio of dissolved oxygen to argon in surface seawater is frequently employed to estimate rates of net community production (NCP) in the oceanic mixed layer. The in situ O2/Ar-based method accounts for many physical factors that influence oxygen concentrations in the surface ocean, permitting isolation of the biological oxygen signal produced by the balance of photosynthesis and respiration. However, this technique traditionally relies upon several assumptions when calculating the mixed layer O2/Ar budget, most notably the absence of vertical fluxes of O2/Ar and the existence of a steady-state balance between net productivity and the air-sea gas exchange of biological oxygen. Employing a Lagrangian study design and leveraging data outputs from a regional physical oceanographic model, we conducted in situ measurements of O2/Ar in the California Current Ecosystem in spring 2016 and summer 2017 to evaluate these assumptions within a ‘worst-case’ field environment. Quantifying the magnitude of vertical fluxes and comparing NCP estimates obtained using steady-state versus non-steady-state assumptions, we find the importance of the non-steady-state term to be considerable, also observing significant potential effects from vertical flux terms, particularly advection. Additionally, we observe strong diel variability in O2/Ar and calculated NCP rates at multiple stations. Our results reemphasize the importance of accounting for vertical fluxes when interpreting O2/Ar-derived NCP data as well as the potentially large effect of non-steady-state conditions, including diel cycles in surface O2/Ar that can bias interpretation of NCP data based on local productivity and the time of day at which measurements were made.

openCC0Oct 2021View details →
zenodo32/100

Supporting datasets used in the Geophysical Research - Oceans entitled "Variability of dissolved oxygen in the bottom layer of the southern Senegalese shelf"

<p>This archive contains text files corresponding to datasets used in the</p> <p>Geophysical Research-Oceans paper entitled &quot;Variability of dissolved oxygen in the bottom layer of the southern Senegalese shelf&quot;</p> <p>by Abdoul Wahab Tall, Eric Machu, Vincent Echevin, Xavier Capet, Alice Pietri, Khassoum Corr&eacute;a, Alban Lazar</p> <p>The data are in standard text file format, which are readily readable using standard text tools.</p> <p>Variables names/content/dimensions and units are described in the text metadata.</p>

opencc-by-4.0Oct 2020View details →
zenodo32/100

G4D-DOC: A global four-dimensional gridded dataset of ocean dissolved oxygen concentrations retrieval from Argo profiles

<p>Based on temperature and salinity observations from Argo floats, this dataset uses machine-learning methods to reconstruct global ocean dissolved oxygen (DO) concentrations.<br><strong>This version only provides monthly-scale netCDF format data for everyone's use. If you need other time scales, please check previous versions.</strong></p> <h2>Spatiotemporal Characteristics</h2> <ul> <li> <p><strong>Time range:</strong> 2005&ndash;2022, <strong>monthly</strong> fields.</p> </li> <li> <p><strong>Geographic range:</strong> Global oceans <strong>excluding the Arctic Ocean</strong>, from 90&deg;S to 84&deg;N and 180&deg;W to 180&deg;E.</p> </li> <li> <p><strong>Horizontal resolution:</strong> 1&deg; &times; 1&deg; (regular grid).</p> </li> <li> <p><strong>Vertical levels (26):</strong> 10, 20, 30, 40, 50, 75, 100, 125, 150, 200, 250, 300, 400, 500, 600, 700, 800, 900, 1000, 1100, 1200, 1300, 1400, 1500, 1750, 1995dbar .</p> </li> </ul> <h2>Data Format &amp; Conventions</h2> <ul> <li> <p><strong>Format:</strong> NetCDF4</p> </li> <li> <p><strong>Coordinate conventions:</strong></p> <ul> <li> <p><code>lat</code> (Y axis): 89.5 &rarr; &minus;89.5 (descending)</p> </li> <li> <p><code>lon</code> (X axis): converted to <strong>&minus;180 &rarr; 180</strong> (1&deg; centers)</p> </li> <li> <p><code>depth</code>: ascending (matching the 26 target levels)</p> </li> </ul> </li> <li> <p><strong>Units:</strong> DO in <strong>&mu;mol/kg</strong> (<code>umol kg-1</code>).</p> </li> </ul> <h2>Variables &amp; Dimensions</h2> <ul> <li> <p><strong>Variables kept:</strong> <code>DO</code>, <code>depth</code>, <code>lat</code>, <code>lon</code> (with a single-valued <code>time</code> coordinate).</p> </li> <li> <p><strong>DO dimensions:</strong> <code>(time, depth, lat, lon)</code>.</p> </li> </ul> <h2>Filenames</h2> <ul> <li> <p><strong>Pattern:</strong> <code>G4D_DOC_YYYY_MM.nc</code><br><em>Example:</em> <code>G4D_DOC_2005_07.nc</code> contains the field for <strong>July 2005</strong>.</p> </li> </ul> <h2>Citation &amp; Disclaimer</h2> <p>Please cite the dataset and relevant literature when using it in publications or products.<br>Recommended citation (example):</p> <blockquote> <p>Xue, C., &amp; Wang, Z. (2025). <em>A global four-dimensional gridded dataset of ocean dissolved oxygen concentrations retrieval from Argo profiles</em> (Monthly NetCDF version). Zenodo. <a target="_new" rel="noopener">https://doi.org/</a>10.5281/zenodo.13920233</p> </blockquote> <p>The data producers are not responsible for any losses arising from data use. Map boundaries or masks do not imply official positions.</p> <h2>Contacts</h2> <ul> <li> <p><strong>Cunjin Xue</strong> &mdash; <a rel="noopener">xuecj@aircas.ac.cn</a></p> </li> <li> <p><strong>Zhenguo Wang</strong> &mdash; <a rel="noopener">zgwang24@m.fudan.edu.cn</a></p> </li> </ul>

openJan 2024View details →
zenodo32/100

Surface-to-bottom data of total alkalinity, total inorganic carbon, pH and dissolved oxygen in the subpolar North Atlantic along the CLIVAR 59.5N hydrographic section during 2009-2019.

<p>Contact: magdalena.santana@ulpgc.es; melchor.gonzalez@ulpgc.es; david.curbelo@ulpgc.es</p><p>______________________________</p><p><strong>1. Introduction</strong></p><p>The dataset comprises physical and carbonate system data collected during eight summer cruises (2009-2019) along the meridional hydrographic CLIVAR 59.5N section. This repeated section covered the longitudinal span of the subpolar North Atlantic at 59.5ºN between Scotland and Greenland (4.5-43.0ºW), encompassing the Irminger and Iceland basins, and the Rockall Trough. Sampling stations were equidistantly spaced every 20 n.m. apart (~1/3º longitude) in most cruises, with exceptions in 2016 where station spacing was decreased to 10 n.m. over Reykjanes Ridge slopes. Notably, the distance between stations over the east Greenland slope and shelf decreased from 10 n.m. to about 2 n.m. The dataset provided here is the result of an international collaboration between researchers from the P. P. Shirshov Institute of Oceanology at the Russian Academy of Science and the QUIMA-IOCAG group from the ULPGC. The cruise ID, dates, research vessels and chief scientist of each cruise (2009, 2010, 2011, 2012, 2013, 2014, 2016 and 2019) are summarized as follows:</p><p><i><strong>Year&nbsp;&nbsp;&nbsp;&nbsp; Cruise ID&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Date&nbsp;&nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Research Vessel (R/V)&nbsp; &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Chief Scientist</strong></i></p><p>2009&nbsp;&nbsp;&nbsp;&nbsp; AI28&nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Aug 15-Sept 27&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Akademik Ioffe&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; A. Sokov</p><p>2010&nbsp;&nbsp;&nbsp;&nbsp; AI31&nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Sep 2-Sep 27&nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Akademik Ioffe&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; A. Sokov</p><p>2011&nbsp;&nbsp;&nbsp;&nbsp; SV33&nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Sep 9-Sep 28&nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Akademik Sergey Vavilov&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;A. Sokov</p><p>2012&nbsp;&nbsp;&nbsp;&nbsp; AI38&nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; May 25-Jul 1&nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Akademik Ioffe&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; S. Gladyshev</p><p>2013&nbsp;&nbsp;&nbsp;&nbsp; AI41&nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Jun 26-Jul 23&nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Akademik Ioffe&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; S. Gladyshev</p><p>2014&nbsp;&nbsp;&nbsp;&nbsp; AI44&nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Jun 27-Jul 20&nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Akademik Ioffe&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; S. Gladyshev</p><p>2016&nbsp;&nbsp;&nbsp;&nbsp; AI51&nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Jun 3-Jul 13&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Akademik Ioffe&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; S. Gladyshev</p><p>2019&nbsp;&nbsp;&nbsp;&nbsp; AMK77&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Aug 8-Sep 10&nbsp;&nbsp; &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Akademik Mstislav Keldysh&nbsp;&nbsp;&nbsp;&nbsp; S. Gladyshev</p><p><strong>2. Data collection: measurements and determination methodologies</strong></p><p>The surface-to-bottom sampling and in situ measurements were performed by using a SBE 911plus CTD with SBE32 Carousel containing 24 Niskin bottles (10 L) with additional sensors for pressure, temperature, salinity and dissolved oxygen (DO). The Chief Scientists (Alexey Sokov and Sergey Gladyshev,&nbsp;supported by FMWE-2023-0002) were&nbsp;responsible for the operational and maintenance procedures for the CTD and provided the physical variables (temperature, salinity, depth and bottom depth) for all the cruises and the sensor-measured DO for the cruise of 2019, all of them included in this dataset.&nbsp;The use of these data for scientific purposes is subject to request and granted only upon prior contact to A. Sokov and/or S. Gladyshev.</p><p>The dataset includes high-quality CO2 measurements obtained through a standardized analytical methodology applied across hydrographic cruises. The procedures adhere to the DOE method manual for CO2 analysis in seawater by Dickson et al., 2007. Seawater samples were onboard analysed for total alkalinity (AT), total inorganic carbon (CT), pH and dissolved oxygen (DO) determination. The QUIMA-IOCAG group from the ULPGC was responsible for the seawater sampling and chemical variables determination (CO2 system variables in all the cruises and WINKLER-measured dissolved oxygen from 2009 to 2016). &nbsp;The use of these data for scientific purposes is subject to request and granted only upon prior contact to any of the dataset authors.</p><p><strong>&nbsp; &nbsp; &nbsp;2.1. Total Alkalinity (AT) and Total Inorganic Carbon (CT)</strong></p><p>Total alkalinity (AT) and total inorganic carbon (CT) were determined onboard using a VINDTA 3C according to Mintrop et al., 2000. AT was analyzed via potentiometric titration with HCl, following the carbonic acid endpoint method (Millero et al., 1993; Dickson and Goyet, 1994), while CT was determined through coulometric titration (Johnson et al., 1993). In-situ calibration of the VINDTA 3C using Certified Reference Material (CRMs) by A. Dickson ensured accuracy of ±1.5 μmol kg-1 for AT and ±1.0 μmol kg-1 for CT.</p><p><strong>&nbsp; &nbsp; &nbsp;2.2. pH</strong></p><p>Spectrophotometric pH measurements were conducted between 2009 and 2016 at a constant temperature of 15ºC (pH15). The measurements utilized a spectrophotometric pH sensor (SP101-SM) developed by the QUIMA-IOCAG group at the ULPGC in collaboration with SensorLab (González-Dávila, 2014; González-Dávila et al., 2016). The method employs 4-wavelength analysis for m-cresol purple, incorporates auto-cleaning steps, and performs a blank for pH calculation post-dye injection. In-situ testing with a TRIS seawater buffer confirmed an accuracy of ±0.002 units, and a correction of +0.0047 units was applied to experimental pH values based on DelValls and Dickson, 1998, which reported an uncertainty associated with TRIS calibration.</p><p>The pH at in situ temperature (pH) was computed by using the CO2SYS programme developed by&nbsp;Lewis and Wallace, (1998) and run with the MATLAB software (van Heuven et al., 2011; Orr et al., 2018; Sharp et al., 2023) from the measured AT and pH15. The pH at in situ temperature for the cruise of 2019, in which direct pH measurements were not performed, was computed from the measured AT and CT.</p><p><strong>&nbsp; &nbsp; &nbsp;2.3. Dissolved Oxygen (DO)</strong></p><p>The WINKLER method, initially introduced by Winkler (1888) and subsequently optimized by Carpenter (1965) and Carrit and Carpenter (1966), was employed to analytically determine dissolved oxygen (DO) in seawater samples across all cruises from 2009 to 2016. During sample collection, seawater samples for DO determination were carefully collected in pre-calibrated glass wide-neck bottles to prevent bubble formation, and the water temperature was recorded at the time of sampling. Titration was performed using a Metrohm 888 Titrando and 794 Basic Titrino, operated with Tiamo software and a potentiometric electrode, as outlined by Culberson and Huang (1987). Thiosulfate standardization occurred every two days using a KIO3 0.01N solution. The reagents and solutions for DO determination were prepared following procedures by Dickson and Goyet (1994), with regular blank determinations every two days to control for possible impurities. As DO could not be analytically measured during the cruise of 2019 (due to limitations related with the oceanographic cruise plan), sensor-measured DO data were included in this dataset for this year.</p><p><strong>3. Dataset content</strong></p><p>The dataset includes the following variables:&nbsp;</p><ul><li>"cruise" (year of the cruise).</li><li>"cruise_ID" (ID of each cruise).</li><li>"date" (date of the day in which half of the cruise was completed).</li><li>"station" (ID of each sampling station).</li><li>"lon" (longitude in decimal degrees).</li><li>"lat" (latitude in decimal degrees).</li><li>"niskin" (number of each niskin bottle obtained from the bottle dataset).</li><li>"depth" (depth of each sample in meters, m).</li><li>"bottomdepth" (depth of the bottom in meters, m).</li><li>"temp" (temperature in ºC).</li><li>"sal" (salinity).</li><li>"pH15" (measured pH at a constant temperature of 15ºC, in total scale).</li><li>"pH" (pH at in situ temperature, in total scale).</li><li>"CT" (total inorganic carbon, in mmol m-3).</li><li>"AT" (total alkalinity, in mmol m-3).</li><li>"DO" (Dissolved Oxygen, in mmol m-3).</li></ul><p><strong>Acknowledgement</strong></p><p>The participation on the cruises for the Spanish Team from the ULPGC was funded by the Science Spanish Ministry under the Complimentary Actions CTM2008-05255, CTM2010-09514-E and CTM2011-12984-E (years 2009-2011), the FP7 European project CARBOCHANGE under grant agreement no. 264879 and by the Spanish Innovation and Science Ministry through the Projects EACFe (CTM2014-52342-P) and ATOPFe (CTM2017-83476-P).&nbsp;The participation of DCH was funded by the PhD grant PIFULPGC-2020-2 ARTHUM-2.&nbsp;Special thanks go to the technician and researchers Adrian Castro Álamo (2 cruises), Anna Barrera Galderique (3 cruises), Rayco Alvarado Medina (2 cruises) and Pilar Aparicio Rizzo (1 cruise) who helped with in situ analysis. We also thanks technicians at the P. P. Shirshov Institute of Oceanology from the Russian Academy of Science for their onboard help with sampling and analysis works. We are deeply grateful to A. Sokov and S. Gladyshev from the P. P. Shirshov Institute of Oceanology from the Russian Academy of Science for invite the QUIMA-IOCAG group (ULPGC) to participate in the 8 cruises between 2009 and 2019 and provide CTD data.</p>

opencc-by-sa-4.0Dec 2023View details →
zenodo32/100

Bottle-calibrated dissolved oxygen profiles from yearly turn-around cruises for the Ocean Observations Initiative (OOI) Irminger Sea Array 2014-2022

<p>This dataset contains bottle-calibrated dissolved oxygen (DO) profiles collected from Conductivity Temperature Depth (CTD) casts on turn-around cruises performed yearly to maintain the Ocean Observations Initiative (OOI) Global Irminger Sea Array (60.46&deg;N, 38.44&deg;W). DO profiles were used in conjunction with oxygen bottle measurements (Winklers) to produce a post-cruise oxygen-calibrated CTD product for scientific use. Bottle-calibrated CTD salinity products were used to produce post-cruise oxygen-calibrated CTD profiles starting in 2018 (Year 5). This document contains overviews of CTD data collection and processing and post-processing oxygen sensor calibration method. Reports for each cruise include a summary of relevant cruise events, oxygen sensor calibration results, and issues/problems associated with oxygen data collected on each cruise. This dataset has been created for end-users that require field-calibrated oxygen data products that are currently not provided by OOI through its standard data dissemination.</p>

opencc-by-4.0Aug 2023View details →
zenodo32/100

Observational data of temperature and oxygen for the study "High-frequency observations of temperature and dissolved oxygen reveal under-ice convection in a large lake"

<p>Matlab data for both temperature and oxygen time series between December 1, 2014, 0:00 (EST) and April 26, 2015, 0:00 (EST). Temperature profiles are sampled every 20 seconds. Dissolved oxygen are sampled every 30 minutes. The depth of each time series are written on the file name.</p>

opencc-by-4.0Oct 2017View details →
zenodo32/100

Surface dissolved oxygen taken at the Lehanagh Pool Salmon pens at IMTA lab Ireland

<p>Surface dissolved oxygen taken at the Lehanagh Pool Salmon pens at IMTA lab Ireland</p>

opencc-by-4.0Jun 2024View details →
zenodo32/100

Python analyses: Dissolved oxygen

<p>Contains the python scripts associated with (i) the development of the hybrid DynQual_Random Forest model; and (ii) the analyses of the dissolved oxygen output from the hybrid model.</p> <p>&nbsp;</p> <p>&nbsp;</p>

opencc-by-4.0Aug 2024View details →
zenodo32/100

《Effects of Typhoons on primary production and dissolved oxygen in the East China Sea》dataset

<p>Data used in the article《Effects&nbsp;of Typhoons on primary production and dissolved oxygen in the East China Sea》</p>

opencc-by-4.0May 2023View details →
dryad32/100

Data from: Geographic variation in phenotypic plasticity in response to dissolved oxygen in an African cichlid fish

Open the record for dataset details and reuse information.

publicJul 2010View details →
dryad32/100

Data from: Extreme diel dissolved oxygen and carbon cycles in shallow vegetated lakes

Open the record for dataset details and reuse information.

publicSep 2017View details →
edi32/100

Dissolved oxygen of discrete water column samples at selected depths collected aboard Palmer LTER annual cruises off the coast of the Western Antarctic Peninsula, 1993 - 2012.

Oxygen is produced by phytoplankton photosynthesis and consumed by respiration of phytoplankton, zooplankton and bacteria. Oxygen also enters and exits the ocean via physical exchange with the atmosphere. Oxygen concentrations in the surface ocean may be supersaturated by photosynthesis and turbulence enhancing air-sea exchange via bubble injection; or undersaturated due to excess respiration. In cases where exchange with the atmosphere is limited, and/or respiration exceeds photosynthesis, oxygen concentration can be reduced to very low levels (hypoxia) or entirely depleted (anoxia). This is uncommon in cold Antarctic Seas where respiration is depressed and oxygen solubility is enhanced by low temperature. Different water masses have characteristic oxygen concentrations which serve as tracers for diagnosing physical mixing and advection. Dissolved oxygen was analyzed by Winkler Titration (see Methods) in CTD-Rosette bottle samples at all depths sampled until 2012. This measurement was discontinued in 2013. The CTD has duplicate oxygen electrodes that provide continuous vertical profiles of oxygen concentration at all depths on all casts. The vessel also has continuous underway, Optode determination of dissolved oxygen in the surface (ship's intake at 6 meters depth) on all cruises. Finally we now routinely measure net community production by Equilibrator Inlet Mass Spectroscopy (EIMS) on LTER cruises

openCustomJul 2017View details →
zenodo28/100

Coastal plain stream carbon export and dissolved oxygen concentrations across a gradient of urbanization

<p>This dataset contains carbon quality data from ten coastal plain streams in North Carolina, USA spanning a gradient of urbanization and carbon export, stream discharge, and dissolved oxygen concentration&nbsp;data from a subset of five streams. See the spreadsheet &quot;metadata.csv&quot; for information about units. Methodology and site descriptions will be made available once the manuscript using these data is published (currently in press) or by request.</p>

opencc-by-4.0Jul 2020View details →
dryad28/100

Rapid range expansion of a marine ectotherm reveals the demographic and ecological consequences of short-term variability in seawater temperature and dissolved oxygen

<p>The distributions of marine ectotherms are governed by physiological sensitivities to long-term trends in seawater temperature and dissolved oxygen. Short-term variability in these parameters has the potential to facilitate rapid range expansions, and the resulting ecological and socioeconomic consequences may portend those of future marine communities. Here, we combine physiological experiments with ecological and demographic surveys to assess the causes and consequences of sudden but temporary poleward range expansions of a marine ectotherm with considerable life history plasticity (California market squid, <i>Doryteuthis opalescens</i>). We show that sequential factors related to resource accessibility in the core range may drive these expansions—the buildup of large populations due to competitive release, and climate-associated temperature increase and oxygen loss that constrain aerobic activity. We also reveal that poleward range expansion alters the body size—and therefore trophic role—of invading populations, with potential negative implications for socioeconomically valuable resident species. To help forecast rapid range expansions of marine ectotherms, we advocate that research efforts focus on factors impacting resource accessibility in core ranges. Determining how environmental conditions in receiving ecosystems affect body size, and how body size is related to trophic role, will help refine estimates of the impacts of future marine communities.</p>

opencc-zeroDec 2021View details →
dryad28/100

Coupled changes in pH, temperature and dissolved oxygen impact the physiology and ecology of herbivorous kelp forest grazers

<p>Understanding species' responses to upwelling may be especially important in light of ongoing environmental change. Upwelling frequency and intensity are expected to increase in the future, while ocean acidification and deoxygenation are expected to decrease the pH and dissolved oxygen of upwelled waters. However, the acute effects of a single upwelling event and the integrated effects of multiple upwelling events on marine organisms are poorly understood. Here, we use <em>in situ </em>measurements of pH, temperature, and dissolved oxygen to characterize the covariance of environmental conditions within upwelling-dominated kelp forest ecosystems. We then test the effects of acute (0-3 days) and chronic (1-3 month) upwelling on the performance of two species of kelp forest grazers, the echinoderm, <em>Mesocentrotus franciscanus, </em>and the gastropod, <em>Promartynia pulligo</em>. We exposed organisms to static conditions in a regression design to determine the shape of the relationship between upwelling and performance and provide insights into the potential effects in a variable environment. We found that respiration, grazing, growth, and net calcification decline linearly with increasing upwelling intensity for <em>M. francicanus </em>over both acute and chronic timescales. <em>Promartynia pulligo </em>exhibited decreased respiration, grazing, and net calcification with increased upwelling intensity after chronic exposure, but we did not detect an effect over acute timescales or on growth after chronic exposure. Given the highly correlated nature of pH, temperature, and dissolved oxygen in the California Current, our results suggest the relationship between upwelling intensity and growth in the 3-month trial could potentially be used to estimate growth integrated over long-term dynamic oceanographic conditions for <em>M. franciscanus</em>. Together, these results indicate current exposure to upwelling may reduce species performance and predicted future increases in upwelling frequency and intensity could affect ecosystem function by modifying the ecological roles of key species.</p>

opencc-zeroFeb 2022View details →
zenodo28/100

Fig. 2 in Artificially decreased dissolved oxygen increases the persistence of Trichomonas gallinae in water

Fig. 2. Persistence of two Trichomonas isolates (COHA, BWHA) in 500 mL distilled water in plastic containers with different concentrations (vol/vol) of Oxyraseª. Error bars = standard deviation from 3 replicates. Legend title: Concentration of Oxyrase ª (vol/vol).

opencc-by-4.0Aug 2019View details →
ClinicalTrials.gov28/100

Using A Dissolved Oxygen Enriched Dressing in Nipple-sparing Mastectomy

ClinicalTrials.gov study NCT01796977. IPD Sharing: Not stated. Countries: 1. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov28/100

OxyGenesys Dissolved Oxygen Dressing; Abdominoplasty at Northwestern University

ClinicalTrials.gov study NCT02591537. IPD Sharing: Not stated. Countries: 1. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov28/100

Dissolved Oxygen Dressing to Improve Chronic Wound Healing After Revascularization for Critical Limb Ischemia

ClinicalTrials.gov study NCT02046226. IPD Sharing: Not stated. Countries: 1. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View details →

ScienceDex guides

Understand access before you commit

These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated 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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record