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1,444 results for “ph”
North Temperate Lakes LTER High Frequency Water Temperature Data, Dissolved Oxygen, Chlorophyll, pH - Crystal Lake 2011 - 2014
Data from the instrumented buoy on Crystal Lake include micrometeorological parameters, relative humidity, air temperature, wind velocity, wind driection (2 m height),and water temperatures, pH, chlorophyll, and dissolved oxygen measured by a sonde that is moving through the water column. Measurements were taken before, during, and after lake mixing experiment
Lake Mendota Microbial Observatory Temperature, Dissolved Oxygen, pH, and conductivity data, 2006-present.
The Lake Mendota Microbial Observatory collects routine water physical and chemical measurements alongside their microbial samples. This dataset includes measurements of water temperature, dissolved oxygen, pH, and conductivity collected at the central Deep Hole, collocated with a weather buoy (43°05'58.2"N 89°24'16.2"W). All measurements were collected with handheld probes. Data from 2006-2014 was compiled from multiple sources and includes only water temperature and dissolved oxygen. Data from 2014-2019 is from the same probe, a YSI Pro Plus instrument, and also includes pH and specific conductance. Routine microbial observatory sampling continues into the present.
PIE LTER transects of the Parker River Plum Island Sound Estuary, Massachusetts conducted at dawn and dusk, containing dissolved oxygen, conductivity, temperature, percent saturation, pH, DIC and pCO2 data.
Multi-year transects, beginning in 1995, of the Parker River Plum Island Sound Estuary conducted at dawn and dusk, containing dissolved oxygen, conductivity, temperature, percent saturation, pH, salinity, DIC and pCO2 measurements. Differences between dawn and dusk measurements can be used to determine the water metabolism and corresponding estimates of gross primary production, total system respiration and net ecosystem production.
Transects of the Rowley River, Plum Island Sound Estuary, Massachusetts conducted at dawn and dusk, containing dissolved oxygen, conductivity, temperature, percent saturation, pH, DIC and pCO2 data, PIE LTER.
Multi-year transects, beginning in 2016, of the Rowley River Plum Island Sound Estuary, MA conducted at dawn and dusk, containing dissolved oxygen, conductivity, temperature, percent saturation, pH, DIC and pCO2 measurements. Differences between dawn and dusk measurements can be used to determine the water column metabolism and corresponding estimates of gross primary production, total system respiration and net ecosystem production.
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
Altering pH changes competition dynamics between two crayfish species for both food and shelter resources
As climate change continues, alterations in abiotic variables within habitats will also change. One of the key variables for aquatic systems is pH. We were interested in how lowered pH altered the behavioral characteristics of two keystone species: Faxonius rusticus, a non-native crayfish in the upper midwest and Faxonius virilis, the native crayfish. We dosed size-matched individuals in separate tanks for four days and than placed these individuals in a flow through mesocosm to allow them to compete over food and shelter resources. Behavior was recorded from midnight to 4 am. Pairs of animals were exposed to pH levels varying from ambient (8.4) to 6.4. The experiment took place at the University of Michigan's Biological Station in northern Michigan in the United States.
Stage height, discharge, water temperature, pH, conductivity, and dissolved oxygen at Cascade Brook in Black Rock Forest, Cornwall, NY 1998 - 2015
Black Rock Forest established a stream monitoring station in the Cascade Brook watershed in 1998. The station is equipped with a 120-degree sharp-crested v-notch weir and was built to continuously monitor the flow, temperature, pH, conductivity, and dissolved oxygen content of the stream water in Cascade Brook in New York. The Cascade Brook watershed encompasses 135 hectares (334 acres), is generally a southern aspect, and has been little affected by human activity in the last century. The forest is deciduous and dominated by oak species. The station records data hourly, and while water chemistry sensors have been used intermittently through the decades, stage height and discharge has been measured consistently from1998 - 2015.
Time series of water column pH from lagoon sites along the Alaska Beaufort Sea coast, 2018-ongoing
Beginning in August 2018, the Beaufort Lagoon Ecosystems Long Term Ecological Research (BLE LTER) program will record water column pH time series (hourly) from a benthic mooring containing a Seabird SeaFET V2 buoyed 10 cm from the lagoon seafloor. pH values are logged from the instrument’s internal sensor and reported on the total hydrogen ion scale. Site bottom water is collected and analyzed in the laboratory to employ a single point calibration to the data during post-processing. Another discrete water sample is collected months after instrument deployment to determine uncertainty (2018-2019 season: 0.002).
Little Rock Lake Experiment at North Temperate Lakes LTER: pH and Alkalinity 1983 - 2000
The Little Rock Acidification Experiment was a joint project involving the USEPA (Duluth Lab), University of Minnesota-Twin Cities, University of Wisconsin-Superior, University of Wisconsin-Madison, and the Wisconsin Department of Natural Resources. Little Rock Lake is a bi-lobed lake in Vilas County, Wisconsin, USA. In 1983 the lake was divided in half by an impermeable curtain and from 1984-1989 the northern basin of the lake was acidified with sulfuric acid in three two-year stages. The target pHs for 1984-5, 1986-7, and 1988-9 were 5.7, 5.2, and 4.7, respectively. Starting in 1990 the lake was allowed to recover naturally with the curtain still in place. Data were collected through 2000. The main objective was to understand the population, community, and ecosystem responses to whole-lake acidification. Funding for this project was provided by the USEPA and NSF. pH and alkalinity of the treatment and reference basins of Little Rock Lake are measured at one station in the deepest part of each basin at the top and bottom of the epilimnion, mid-thermocline, and top, middle, and bottom of the hypolimnion. During the course of the study, three different types of electrodes were used to measure pH. Sampling Frequency: varies - Number of sites: 2
Cascade Project at North Temperate Lakes LTER Phosphorus, Chlorophyll, DOC, Color, and pH for Twenty UNDERC Lakes 1995 - 2003
Data on total phosphorous, chlorophyll a, dissolved organic carbon, water color, and pH for a set of lakes located at the University of Notre Dame Environmental Research Center (UNDERC). Surface water samples were collected monthly from May through August either from shore with a telescoping pole or from a boat. Twenty lakes were sampled from 1995-2000. Fifteen of these lakes were sampled from 2001-2003.
SBC LTER: Ocean: Time-series: nearshore calibrated pH and temperature outside of reefs, ongoing since 2011
Calibrated pH (Total scale, SeaFET sensor) data was collected from 10 reefs in the Santa Barbara Channel along with in situ temperature. Most pH sensors are deployed together with SBC long-term mooring instruments. Data collection intervals and SeaFET sensor depths vary based on the site location.
Dataset of "High Entropy 2D Metals Sulfides: Fast Synthesis, Exfoliation and Electrochemical Activity in Overall Water Splitting at Alkaline pH"
<p>Novel simple and efficient method for synthesis of high entropy sulfides of iron group metals (Cr, Fe, Ni, Co, Zn) is describedThe created material was investigated as a catalyst for electrochemical water splitting in acidic, neutral and alkaline pH. Investigation of the electrocatalytic activity of the synthesized material shows its high efficiency for overall water splitting in alkaline media. </p>
Root Biomass, Fine Root Production, Soil Mass, and Soil pH in Limed and Control Plots at the Woods Lake Watershed, Adirondack Park, NY, USA, 2021-2022
In 1989, 6.89 Mg/ha of pelletized lime (CaCO3) was applied by helicopter to two subcatchments at the Woods Lake Watershed in Adirondack Park, New York, USA to ameliorate ecosystem acidification. Two unlimed (control) subcatchments were paired with limed subcatchments. In the same year, 99 permanent plots (20 m x 20 m) were established. Between 2008 and 2010, tree inventory and soil physicochemical measurements were made in five plots in each of the four subcatchments (20 plots total). This dataset contains soil physicochemical properties (dry mass, depth, and pH); root biomass (<1 mm, 1-2 mm, and >2 mm diameter); and annual fine root production (<1 mm and 1-2 mm) measurements made between 2021 and 2022 in 19 of these same plots (5 plots per control subcatchment and 4 or 5 plots per limed subcatchment). Data include measurements for all properties for Oe, Oa, and 0-10 cm mineral soil samples collected from 5 locations within each plot.
PIE LTER Year 2022 15-minute interval water quality measurements of water column temperature, salinity, oxygen, pH, and depth at four sites in the Plum Island Estuary.
Four YSI EXO2 water quality sondes were deployed from June 2022 to October 2022 at four sites in the Plum Island Estuary. One was at the mouth of the sound at the Ipswich Bay Yacht Club, one in the Rowley River, and two in the Parker River. The sondes measured water column temperature, salinity, oxygen, pH, and depth in 15-minute intervals.
SBC LTER: pH time series: Water-sample pH and CO2 system chemistry, ongoing since 2011
Data are a time-series of pH and carbonate chemistry in manually-collected sea water samples from sixteen near-shore locations and 20 locations along the Santa Barbara Channel, California, USA, and intended to benchmark data from moored pH instruments. Data collection began in June 2011 and is ongoing. Time-series for pH sensors deployed in the field (e.g., SeaFET) are available elsewhere. Discrete seawater samples were collected by hand or using a Niskin bottle. In the laboratory, samples were analyzed for pH (total scale) and total alkalinity. Two parameters were used to calculate the full suite of carbonate chemistry parameters using the CO2calc algorithms. Program outputs are included for laboratory conditions as input, and adjusted for situ temperature. See Methods for more information, e.g., Lunden, et al. Data were collected by a consortium of research groups with the intent to leverage their collective assets and expertise. These groups (and sponsors) include Santa Barbara Coastal LTER (NSF), OMEGAS Project (NSF), Passow Lab (Calif. State Water Board), Hofmann Lab (NSF, CINMS, US NPS).
iSDAsoil: soil pH for Africa predicted at 30 m resolution at 0-20 and 20-50 cm depths
<p>iSDAsoil dataset soil pH (1:1 Soil-Water Suspension) predicted at 30 m resolution for 0–20 and 20–50 cm depth intervals. Data has been projected in WGS84 coordinate system and compiled as <a href="https://gdal.org/drivers/raster/cog.html">COG</a>. Predictions have been generated using multi-scale Ensemble Machine Learning with 250 m (MODIS, PROBA-V, climatic variables and similar) and 30 m (DTM derivatives, Landsat, Sentinel-2 and similar) resolution covariates. For model training we use a pan-African compilations of soil samples and profiles (<a href="https://www.isda-africa.com/national-soil-services/">iSDA points</a>, <a href="https://www.isric.org/projects/africa-soil-profiles-database-afsp">AfSPDB</a>, and other national and regional soil datasets). Cite as:</p> <p>Hengl, T., Miller, M.A.E., Križan, J. <em>et al.</em> African soil properties and nutrients mapped at 30 m spatial resolution using two-scale ensemble machine learning. <em>Sci Rep</em> <strong>11, </strong>6130 (2021). <a href="https://doi.org/10.1038/s41598-021-85639-y">https://doi.org/10.1038/s41598-021-85639-y</a></p> <p>To open the maps in QGIS and/or directly compute with them, please use the <a href="https://gitlab.com/openlandmap/africa-soil-and-agronomy-data-cube"><strong>Cloud-Optimized GeoTIFF version</strong></a>.</p> <p>Layer description:</p> <ul> <li>sol_ph_h2o_m_30m_*..*cm_2001..2017_v0.13_wgs84.tif = predicted soil pH mean value,</li> <li>sol_ph_h2o_md_30m_*..*cm_2001..2017_v0.13_wgs84.tif = predicted soil pH model (prediction) errors,</li> </ul> <p>Model errors were derived using bootstrapping: md is derived as standard deviation of individual learners from 5-fold cross-validation (using spatial blocking). The model 5-fold cross-validation (<a href="https://mlr.mlr-org.com/reference/makeStackedLearner.html">mlr::makeStackedLearner</a>) for this variable indicates:</p> <pre><code>Variable: ph_h2o R-square: 0.818 Fitted values sd: 0.972 RMSE: 0.459 Random forest model: Call: stats::lm(formula = f, data = d) Residuals: Min 1Q Median 3Q Max -5.5939 -0.2328 -0.0066 0.2222 4.7477 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 1.113440 1.164473 0.956 0.338986 regr.ranger 1.032918 0.003138 329.116 < 2e-16 *** regr.xgboost -0.014201 0.004185 -3.393 0.000691 *** regr.cubist 0.049667 0.003709 13.392 < 2e-16 *** regr.nnet -0.188570 0.188214 -1.002 0.316398 regr.cvglmnet -0.059763 0.003636 -16.438 < 2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 0.4591 on 133378 degrees of freedom Multiple R-squared: 0.8176, Adjusted R-squared: 0.8176 F-statistic: 1.195e+05 on 5 and 133378 DF, p-value: < 2.2e-16</code></pre> <p>To back-transform values (y) to index use:</p> <pre><code>index = y / 10</code></pre> <p>To submit an issue or request support please visit <a href="https://isda-africa.com/isdasoil"><strong>https://isda-africa.com/isdasoil</strong></a></p>
Surface alkalinity, pH (total scale) and CO2 air-sea flux of the Mediterranean Sea under different alkalinisation scenarios.
<p>Surface maps and basin mean/total of annual mean surface alkalinity, pH (total scale) and CO2 air-sea flux of the Mediterranean Sea under different alkalinisation scenarios and for underlying the baseline projection (RCP4.5).</p> <p>Details on simulations and alkalinisation strategies are given in the reference article below.</p> <p> </p> <p>Reference:</p> <p>Butenschön, M., Lovato, T., Masina, S., Caserini, S., Grosso, M., 2021. Alkalinization Scenarios in the Mediterranean Sea for Efficient Removal of Atmospheric CO2 and the Mitigation of Ocean Acidification. Front. Clim. 3. <a href="https://doi.org/10.3389/fclim.2021.614537">https://doi.org/10.3389/fclim.2021.614537</a></p>
Soil pH in H2O [-] for continental Europe at 30 m spatial resolution for period 2000-2020: Open Soil Data Cube for Europe
<p>Predictions are based on the 3D Ensemble Machine Learning framework, as implemented in the R environment for statistical computing (Hengl & MacMillan, 2019; Hengl, et al., 2021). For each pixel we provide prediction errors as 1 standard deviation in either log or the original variable scale.</p> <p>The short description of currently available soil properties: soil pH in H2O;</p> <p>Soil properties were predicted at fixed depths:</p> <p> Surface soil = s0..0cm,<br> Subsoil 1 = s30..30cm,<br> Subsoil 2 = s60..60cm,<br> Subsoil 3 = s100..100cm.</p> <p>To produce estimates for depth intervals e.g. 0–30 cm, 0–100 cm best use the trapezoidal rule formula.</p> <p>Periods: 2000 (2000–2003), 2004 (2004–2007), 2008 (2008–2011), 2012 (2012–2015), 2016 (2016–2019), 2020;</p>
Soil pH in H2O at 6 standard depths (0, 10, 30, 60, 100 and 200 cm) at 250 m resolution
<p>Soil pH in H2O in × 10 at 6 standard depths (0, 10, 30, 60, 100 and 200 cm) at 250 m resolution. Processing steps are described in detail <strong><a href="https://gitlab.com/openlandmap/global-layers/tree/master/soil">here</a></strong>. Antarctica is not included.</p> <p>To access and visualize maps use: <a href="http://www.openlandmap.org/">OpenLandMap.org</a></p> <p>If you discover a bug, artifact or inconsistency in the maps, or if you have a question please use some of the following channels:</p> <ul> <li>Technical issues and questions about the code: <a href="https://gitlab.com/openlandmap/global-layers/issues">https://gitlab.com/openlandmap/global-layers/issues</a> </li> <li>General questions and comments: <a href="https://disqus.com/home/forums/landgis/">https://disqus.com/home/forums/landgis/</a></li> </ul> <p>All files internally compressed using "COMPRESS=DEFLATE" creation option in GDAL. File naming convention:</p> <ul> <li>sol = theme: soil,</li> <li>ph.h2o = variable: soil pH in H2O,</li> <li>usda.4c1a2a = determination method: laboratory method code,</li> <li>m = mean value,</li> <li>250m = spatial resolution / block support: 250 m,</li> <li>b10..10cm = vertical reference: 10 cm depth below surface,</li> <li>1950..2017 = time reference: period 1950-2017,</li> <li>v0.2 = version number: 0.2,</li> </ul>
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.