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Long-term water quality monitoring in the Altamaha, Doboy and Sapelo sounds and the Duplin River near Sapelo Island, Georgia from November 2013 to December 2022
Water samples were collected on Georgia Coastal Ecosystems LTER oceanographic monitoring cruises from November 2012 through December 2022. Monthly samples were collected from GCE 6 (high and low tide) and GCE 7 (high tide). Quarterly samples were collected from the remaining GCE sites and AL-02, the Altamaha River oceanic end-member station. Concentrations of the following were measured using standard analytical methods: dissolved nutrients (phosphate, nitrate+nitrite, ammonium, silicate), dissolved organics (carbon, nitrogen, phosphorus) and particulate carbon and nitrogen, chlorophyll, phaeopigments, total suspended solids and loss on ignition.
Long-term water quality monitoring in the Altamaha River near Doctortown, Georgia from January 2013 to December 2022.
Water samples were collected monthly on the Atlamaha River near Doctortown, Georgia. The samples were anlayzed for dissolved organics (carbon, nitrogen, phosphorus), dissolved nutrients (ammonium, nitrite, nitrate, phosphate, silicate) and particulate carbon and nitrogen. Concentrations of the following were measured using standard analytical methods: dissolved nutrients (phosphate, nitrate+nitrite, ammonium, silicate), dissolved organics (carbon, nitrogen, phosphorus) and particulate carbon and nitrogen
Daily average pCO2, dissolved oxygen, and water quality in Elson Lagoon: 2019, 2021, 2022
pCO2 (partial pressure of carbon dioxide) and other physicochemical parameters were measured during the open water season (July-August) in three years (2019, 2021, 2022) at five sites in Elson Lagoon, a coastal ecosystem near Utqiagvik, AK, as a supplement to the Beaufort Lagoons Ecosystems LTER core sampling program. Locations include three shallow sites (<1 m water depth) at a depth of 0.5 m and two deep sites (up 2 m depth) at a depth of ~1.7m. Data includes daily averages of sensor data for each site of pCO2 (uatm), water temperature (°C), absolute pressure (kPa), salinity (ppt), dissolved oxygen (DO, mg/L), light extinction (Kd; m-1), and water level difference from mean tidal level (m). Discrete laboratory data for dissolved organic carbon (C; umol/L) and turbidity (NTU) are also presented.
Long-term monitoring of stormwater runoff and water quality in urbanized watersheds of the greater Phoenix metropolitan area, ongoing since 2008
Urbanization alters dramatically watershed ecosystem processes. Land-use change and anthropogenic activities contribute to increased inputs of nutrients and other materials, while changes to land cover alter hydrology and the corresponding movement of materials. These changes have ramifications for both watershed processes and downstream systems. The impacts of urbanization on aquatic systems are well-studied, and frequently encapsulated in the ‘urban stream syndrome’ (Walsh et al. 2005) that describes, among others, increased nutrient loading and stream flashiness. However, there is some evidence that aridland cities behave differently (Grimm et al. 2004, 2005), and the complex dynamics among catchment characteristics, storm attributes, and runoff in highly urbanized settings of the arid Southwest remains poorly understood. To enhance our understanding of stormwater dynamics and watershed functioning in aridland, urban environments, the Central Arizona–Phoenix Long-Term Ecological Research (CAP LTER) program began monitoring stormwater runoff at the outflow of the Indian Bend Wash (IBW) in 2008. The IBW is a tributary to the Salt River in central Arizona, and is a major drainage within the greater Phoenix metropolitan area, encompassing much of the City of Scottsdale. A model of soft engineering, the IBW as it runs through much of the City of Scottsdale is comprised largely of a series of artificial lakes, parks, paths, golf courses, ball fields, and other non-structural elements designed with the dual roles of providing outdoor amenities to the City residents while serving as an effective flood water conveyance feature. A unique biogeochemistry of this novel system is detailed by Roach et al. (2008), and Roach and Grimm (2011). Stormwater sampling is conducted at numerous locations. The longest running sampling location is near the outflow of the IBW ~0.6 km above its confluence with the Salt River. The sampling location coincides with a permanent USGS gauging sta
Water Quality Data (Grab Samples) from the Taylor Slough, just outside Everglades National Park (FCE), for August 1998 to November 2006
Water quality samples are being collected using ISCO autosamplers at all wetland sites (that is, all sites except TS/Ph-9, 10, and 11). The autosamplers contain 24 1L bottles. Water is sampled by programming the autosamplers to take composite samples once every 3 days. These samples are a composite of four 250mL subsamples drawn every 18 hours (a sampling scheme that captures a dawn, noon, dusk, and midnight sample in every three day composite). The samples are collected every 3-4 weeks and analyzed for total phosphorus (TP), total nitrogen (TN), and salinity. When sites are visited to collect these samples, we also collect a grab sample that is immediately put on ice. A portion of these grab samples is filtered through a Whatman GF/F filter immediately upon return to the lab, and the filtered samples are analyzed for inorganic nutrients such as NO2-, NO3-, NH4+, SRP, and DOC. The unfiltered fraction of these grab samples is analyzed for TP, TN, and TOC. We use these montly grab samples to generate relationships between TP and SRP, and between TN and NO2- + NO3- + NH4+. Dissolved nutrients are measured using standard rapid flow analyzer (RFA) techniques. TP is analyzed with a modified Solorzano and Sharp (1980) technique. TN is measured with an Antec TN analyzer, TOC and DOC are quantified on a Shimadzu TOC Analyzer, and salinity is measured with a YSI conductivity meter. In addition to the regular water quality monitoring, we use the rain level actuators at all freshwater sites to trigger water sampling after rain events exceed a given threshold of duration and/or intensity. As currently programmed, when the threshold of = 2.5 cm of rain per hour is passed, the autosampler at that site collects a 1L sample every 15 minutes after the threshold has been reached and remains (previous to 2003- the autosampler was programmed to collect 500mL of water every 30 minutes while the threshold was being met). Rain event samples are collected, retrieved, and analyzed like out c
WSC 2007 - 2012 Yahara Watershed surface water quality policies and practices created and implemented by public agencies
This dataset was created June 2012 - August 2013 to contribute to research under the Water Sustainability and Climate project. Interventions collected are those land-based policies and practices written and implemented by public agencies. Policies were implemented in Wisconsin's Yahara Watershed the period 2007-2012. They aim to improve surface water quality through nutrient (phosphorus and nitrogen) and sediment reduction. Interventions included in the mapping must have spatially-explicit, publicly available data through personal communication or website.
Water quality data for Green Lakes Valley, 2000 - ongoing.
This dataset contains water quality measurements made on Green Lakes 1, 2, 3, 4, 5, and Lake Albion. Green Lake 4 was initially sampled in 2000 and is ongoing. Ongoing sampling of Green Lakes 1 was started in 2014 and ongoing sampling of Lake Albion was started in 2016. Water samples were collected for analysis of chlorophyll a and nutrient analysis (which is available in glvwatsolu.dm.data) and field measurements for pH, temperature, specific conductivity, dissolved oxygen (DO), % saturation, secchi depth, PAR. Secchi depth is recorded at the 0m row however it is a measurement of depth and so the units are meters. Most samples were collected between 0800 and 1200 MST. The first sampling date each summer occurs shortly after the ice had melted. Data are collected from an inflatable raft at the point of deepest depth or from the lake inlet and outlet when surface flow is present. The majority of chlorophyll-a the measurements were taken at the surface (0m), the metalimnion (3m), and the hypolimnion nine (usually 8-11m). However, additional measurements were taken for side projects of the long-term dataset during several of the years and are included in this dataset. Water samples from the metalimnion or hypolimnion were collected using a Van Dorne sampler, and surface samples were collected as grab samples from the water column surface, the inlet and outlet. Field measurements were conducted using a YSI either DO or multiple probe meter (2014-2017, YSI MPS 556)(2018-ongoing, YSI ProPlus) and a Li-Cor meter with a quantum sensor. Chlorophyll-a was extracted from filtered samples and absorbance was measured before and after acidification to quantify chlorophyll a concentration.
Anatoxin concentrations, algal assemblages, and water quality data for the South Fork Eel, Salmon, and Russian Rivers in northern California, 2022-2023
We collected this data to better understand the timing of peak benthic cyanobacterial mat occurrence (specifically taxa associated with anatoxin production, Microcoleus and Anabaena) and mat anatoxin concentrations in rivers. We sampled in northern California on the South Fork Eel, Salmon, and Russian Rivers biweekly in 2022, and the Salmon River biweekly and South Fork Eel weekly in 2023. During each sampling event, we conducted benthic cover surveys, measured in-situ water quality parameters (temperature, pH, dissolved oxygen, conductivity), and collected surface water samples and targeted cyanobacteria samples. In 2022 on all rivers and in 2023 at the Salmon River, we also collected distributed non-targeted periphyton samples to characterize full-reach community compositions. All sampling was completed in 150-m reaches upstream of sensors recording continuous dissolved oxygen, conductivity, and temperature data. We analyzed surface water samples for nitrate, ammonium, soluble reactive phosphate, total dissolved carbon, and dissolved organic carbon. We also analyzed surface water samples from 2022 for major anions (Cl, SO4, Br) and cations (Na, K, Mg, Ca). Targeted-cyanobacteria and non-target periphyton samples were analyzed for anatoxins (and two other classes of toxins, microcystins and cylindrospermopsins), relative abundance of algal taxa (via microscopy), ash-free dry mass, and chlorophyll-a. To estimate mean river depth within the dissolved oxygen footprint upstream of sensors, we kayaked portions of the river and collected river depth measurements. We also measured discharge at each river excluding the Salmon River (due to high discharge) and completed pebble counts at the South Fork Eel River to obtain sediment grain size distributions. Lastly, we estimated daily reach-scale river metabolism (gross primary productivity and ecosystem respiration) using data from dissolved oxygen sensors with the "streamMetabolizer" package in R at all sensor placements.
St. Louis River Estuary Phytoplankton and Water Quality, 2022 - 2024
This data package supports the project Building a Collaborative Water Quality Monitoring Strategy for a Changing St. Louis River Estuary, funded by the National Estuarine Research Reserve System Science Collaborative. Led by the Lake Superior National Estuarine Research Reserve (LSNERR) and University of Minnesota’s Natural Resources Research Institute (NRRI) datasets include 2023–2024 water quality, phytoplankton, and winter dissolved oxygen observations from eight estuary “hotspot” locations. Sampling captured seasonal variability and cyanobacteria bloom events. All samples were collected using standardized field and laboratory protocols. Project details and associated products are available at: https://nerrssciencecollaborative.org/project/Ramage22. This dataset can be used to evaluate spatial and temporal patterns in water quality and phytoplankton dynamics, assess predictors of cyanobacterial blooms, and monitor winter under-ice hypoxia in the St. Louis River Estuary. It is well-suited for research on nutrient-bloom relationships, seasonal ecological shifts, and long-term monitoring strategy development.
Lake Sunapee Instrumented Buoy: High Frequency Water Quality Data - 2007-2022
The Lake Sunapee (Global Lake Ecological Observatory Network—GLEON) instrumented buoy, operated by the Lake Sunapee Protective Association (LSPA www.lakesunapee.org), is equipped with a thermistor chain, one optical dissolved oxygen probe suspended at approximately 10 meters depth (installed in 2013), and a multi-parameter sonde (installed in 2021) at 1 meter depth. An optical dissolved oxygen (DO) probe was located at 1.5 meter prior to the 2021 deployment of the multi-parameter probe from the inception of the buoy and the deep DO sensor was at 10.5 meters depth prior to 2021 since deployment. The number of thermistors and below-surface depth of the thermistors has fluctuated throughout the years and the additional water quality sensors have changed over time. The Lake Sunapee buoy is located near Loon Island Lighthouse (43.391°N, 72.058°W) during the summer months and in the Lake Sunapee Harbor (43.386°N, 72.081°W) (2010-current). During the first few years of data collection (2007-2010), the buoy was located near Loon Island year-round. In two instances, HOBO units were deployed at the buoy's location when sensors failed. This occurred in 2015 (in place of the thermistors) and in 2018 (in place of the shallow DO sensor). All data in this data package have been QAQC'd to remove obviously errant readings, highly suspicious readings, and artifacts of buoy maintenance. Additionally, flags have been added per sensor, to indicate calibration and non-calibration of the optical DO probe, location of the buoy, and to document other potential confounding observations. Dissolved oxygen data and data from the multi-parameter probe are “raw”: they are have not been corrected for calibration issues, drift, or fouling. Additional documentation and data are provided including manual DO measurements, visual comparisons of buoy-recorded DO and manual DO measurements, and an overview of how and where DO offsets applied in the data logger program were removed.
Air Quality Index (AQI) data from PurpleAir sensor at H.J. Andrews Experimental Forest LTER
This dataset contains hourly air quality and meteorological measurements collected from a PurpleAir sensor deployed at the H.J. Andrews Experimental Forest Long Term Ecological Research (LTER) site. The data includes four variables: timestamp (in Pacific Time), relative humidity (%), temperature (°C), and particulate matter concentrations (PM2.5 in µg/m³ using the CF=1 correction factor). The sensor provides continuous monitoring of local air quality conditions, with particular focus on fine particulate matter that can impact ecosystem health and visibility. Data are recorded at hourly intervals and timestamped in ISO 8601 format with UTC offset. PM2.5 values are reported using PurpleAir's CF=1 (Correction Factor 1) algorithm, which is optimized for atmospheric particulate matter. This dataset supports long-term environmental monitoring objectives at the Andrews Forest LTER and provides baseline air quality data for research on atmospheric conditions, wildfire smoke impacts, and climate-ecosystem interactions in Pacific Northwest forest ecosystems.
High-frequency, long-term measurements of water quality and chlorophyll in the Tempe Town Lake, Tempe, Arizona, USA, ongoing since 2018
Constructed in 1997, the Tempe Town Lake is a small reservoir that transforms a section of the typically-dry Salt River bed into a 224-acre lake in the heart of Tempe, Arizona. To accommodate the river when it flows, the lake features hydraulically-operated steel gates that allow water to pass through the system unimpeded. The lake has been a remarkable success as a community amenity and as a driver of economic growth in the area around the lake. The lake provides an ideal model system for the many artificial lakes constructed in arid-land cities owing to management decisions, such as draining, that affect their operation and ecology. At the same time, dramatic shifts in hydrology and chemistry when the lake is transformed to a flowing river and back into a Lake during and after floods, provide opportunities to study the system's dynamic evolution to new limnological steady states. The CAP LTER began measuring water quality, including temperature, pH, conductivity, dissolved oxygen, dissolved organic carbon (DOC), and total dissolved nitrogen (TDN) in the lake starting 2005. Initially, these data were collected through a mix of hand-held meters and analyses of water samples collected during regular visits to the lake (e.g., see [knb-lter-cap.630](https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-cap&identifier=630)). In summer 2018, the CAP LTER installed a *in situ* datasonde to measure water quality, including optical dissolved organic carbon characteristics, at high temporal resolution (~ 30 minutes). After a brief period during which data were collected both with the datasonde, and by hand-held meters and analyses of water samples, the project transitioned to collecting data exclusively with the datasonde. The data presented here reflect readings captured by the datasone.
Cedar Bog Lake Water Quality Data
This dataset contains water quality data from multiple locations and dates collected from surface waters of Cedar Bog Lake (CBL) during summers of 2016 -2018. Sampling of biogeochemical and water quality parameters measured include dissolved inorganic and organic carbon, total dissolved nitrogen, total phosphorus, particulate particulate and total dissolved phosphorus, soluble reactive phosphorus, and algal biomass (as chlorophyll a). These data were collected to support research examining energy flow pathways in the lake using stable isotopes, and build long term water data records for the lake as a reference site, given that it is largely protected from direct human impacts. These water quality data enhance previous water quality data available for CBL. The food web analyses project was developed to compare energy flow in CBL food webs between the foundational original studies by Raymond Lindeman in the 1930s to those inferred from stable isotope analyses. The food web project also examined constraints on resource use by consumers imposed by chemical conditions, and explored the potential role of methane as an energy source for consumers. Stable isotope data for food web components, including fish and invertebrates, will be published separately.
Minneapolis-St. Paul Air Quality Sensor output 2024-2025
In the summers since field research at the MSP LTER began, wildfire smoke has led to record highs in Minnesota's Air Quality Index and there has been increasing public concern over the acute and long-term impacts of exposure to toxins in the air. In 2024, the MSP LTER acquired a small network of PurpleAir sensors to place in key areas alongside transplanted lichens that are also used in air quality research. In addition to Particulate Matter, the sensor models used here also are equipped with experimental VOC detection (Volatile Organic Compounds). PurpleAir sensors were collocated with lichens at two locations in St. Paul MN, one in Roseville MN, and one at Cedar Creek Ecosystem Reserve in Northern Anoka County, MN. After lichen material was collected, the sensors remained at the site to keep reporting to community air quality tracking maps. Data from the sensors is being regularly appended to a file on the MSP LTER GitHub page and is planned to be archived long-term.
LAGOS-NE v.1.054.1 - Lake water quality time series and geophysical data from a 17-state region of the United States
Time series of mean summer total nitrogen (TN), total phosphorus (TP), stoichiometry (TN:TP) and chlorophyll values from 2913 unique lakes in the Midwest and Northeast United States. Epilimnetic nutrient and chlorophyll observations were derived from the Lake Multi-Scaled Geospatial and Temporal Database LAGOS-NELIMNO version 1.054.1, and come from 54 disparate data sources. These data were used to assess long-term monotonic changes in water quality from 1990-2013, and the potential drivers of those trends (Oliver et al., submitted). Summer was used to approximate the stratified period, which was defined as June 15 to September 15. The median number of observations per summer for a given lake was 2, but ranged from 1 to 83. The rules for inclusion in the database were that, for a given water quality parameter, a lake must have an observation in each period of 1990-2000 and 2001-2011. Additionally, observations must span at least 5 years. Each unique lake with nutrient or chlorophyll data also has supporting geophysical data, including climate, atmospheric deposition, land use, hydrology, and topography derived at the lake watershed (variable prefix “iws”) and HUC 4 (variable prefix “hu4”) scale. Lake-specific characteristics, such as depth and area, are also reported. The geospatial data came from LAGOS-NEGEO version 1.03. For more specific information on how LAGOS-NE was created, see Soranno et al. 2015. Soranno P.A., Bissell E.G., Cheruvelil K.S., Christel S.T., Collins S.M., Fergus C.E., Filstrup C.T., Lapierre J.-F., Lottig N.R., Oliver S.K., Scott C.E., Smith N.J., Stopyak S., Yuan S., Bremigan M.T., Downing J.A., Gries C., Henry E.N., Skaff N.K., Stanley E.H., Stow C.A., Tan P.-N., Wagner T., and Webster K.E. 2015. Building a multi-scaled geospatial temporal ecology database from disparate data sources: fostering open science and data reuse. Gigascience 4: 28. doi: 10.1186/s13742-015-0067-4.
WSC - The Influence of Legacy P on Lake Water Quality
Using a suite of numerical models, we investigated the influence of legacy P on water quality in the Yahara Watershed of southern Wisconsin, USA. The suite included Agro-IBIS, a terrestrial ecosystem model; THMB, a hydrologic and nutrient routing model; and the Yahara Water Quality Model which estimates water quality indicators in the Yahara chain of lakes. Using five alternative scenarios of antecedent P storage (legacy P) in soils and channels under historical climate conditions, we simulated outcomes of P yield from the landscape, lake P loading, and three lake water quality indicators. Data and code may also be found in https://github.com/SRCarpen/Yahara2070LakeModel_Fits2data.git
Water quality, temperature, ash-free dry mass, photosynthetic activate radiation (PAR), and zooplankton data from a warming and DOC subsidy experiment, 2020 - 2021.
This dataset includes chlorophyll-a concentrations, periphyton biomass estimates, water quality measurements, and qualitative observations from a large-scale mesocosm experiment conducted in the Green Lakes Watershed, Colorado. The experiment was designed to test how earlier lake ice-off and increased dissolved organic material (DOM), associated with terrestrial plant encroachment in alpine watersheds, interactively influence aquatic food webs. In fall 2019, twenty 2600L “megacosms” were established at Sandy Corner (3300 m ASL; 40.042289, -105.584006), left to fill with snowmelt, and maintained throughout the 2020 open water season. The experiment followed a 2 × 2 randomized block design manipulating ice-off timing (via black vs. beige tank coloration) and DOM inputs (presence/absence of willow leaf packs), with five replicates per treatment. All tanks were seeded with sediments and zooplankton from both alpine and montane lakes (Green Lake 1 and Green Lake 4), and instrumented with thermistors recording surface and hypolimnion temperature every two hours year-round. Periphyton growth was monitored using clay tiles, sampled across five time points. Chlorophyll-a concentrations were extracted from filtered water samples and analyzed spectrophotometrically. Periphyton biomass was estimated via ash-free dry mass (AFDM) determinations, based on the mass lost on combustion of material scraped from tiles. Water quality was measured 1–2 times weekly using a YSI ProPlus multiprobe and Li-Cor quantum sensor, and snow/ice cover was qualitatively assessed monthly during winter.
Water Quality Sampling - integrated measurements for the Virginia Coast, 1992-2025
This dataset contains information about the aquatic environment along two transects that run from inlet to the mainland shore on the southern part of the Delmarva Peninsula since 1992. It has a large number of columns (111) that integrate information on water column and benthic measurements. Frequency of sampling varies from monthly to quarterly, and not all variables are necessarily measured on the same dates. However, all the data from a given date and location appears on a single line of the dataset.
Surface water quality from the Seagrass Recovery Experiment, South Bay, VA 2020-2022
To understand intra-meadow stability, the Seagrass Recovery Experiment was designed to ask 1) is recovery faster at sites with less thermal stress owing to greater exchange with cooler oceanic water at the meadow edge? 2) what is the shape of recovery? and 3) what are the recovery mechanisms? To conduct this experiment, aboveground seagrass biomass was removed from 28.3 m2 plots within the interior and along an edge of a restored seagrass meadow in South Bay, VA. Sites 1-3 correspond to the meadow interior while sites 4-6 correspond to the northern edge. Each site was comprised of a control (i.e., C) where no seagrass was disturbed and a treatment (i.e., T) where seagrass was removed (n = 12 sites total, e.g., 1C, 1T, 2C...). To further characterize differences between the meadow interior and edge, surface water quality samples were also collected and include turbidity, total suspended solids (TSS) concentration, TSS ash-free dry weight, TSS percent organic matter, pelagic chlorophyll concentration, dissolved oxygen saturation, dissolved oxygen concentration, salinity, water temperature, and specific conductivity. These discrete samples were collected monthly between June-October 2020, May-October 2021, and April-October 2022 using a 1-L Nalgene bottle and a handheld YSI Pro Plus Multiparameter meter.
MiRoR15-P1-Tools used to assess the quality of peer review reports: a methodological systematic review
<p>Database, data extraction form, R codes and protocol related to: Superchi C, González JA, Solà I, Cobo E, Hren D, Boutron I. <em>Tools used to assess the quality of peer review reports: a methodological systematic review</em>. BMC Med Res Methodol. 2019;19(48):1–14. DOI: <a href="https://doi.org/10.1186/s12874-019-0688-x">https://doi.org/10.1186/s12874-019-0688-x</a></p> <p> </p>
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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.