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12,237 results for “2019”
Stream Restoration and Flood Impacts in the Kickapoo River Watershed, Wisconsin, 2019
Data were collected from May to November 2019 at five sites on two stream reaches in the Kickapoo River Watershed. Sites include Billings Creek restoration site (BRES), Billings Creek reference site (BREF), Warner Creek upstream site (WUP), Warner Creek middle site (WMD), and Warner Creek downstream (WDN) site. Data were collected by Dr. Caroline Gottschalk Druschke as part of research into the impacts of stream restoration and flooding on Kickapoo River Watershed (WI, USA) streams. Data were collected on methane and carbon dioxide fluxes on all reaches, as well as cross sectional area and soft sediment depth on the restored reach on Billings Creek before and after restoration in July 2019.
Water properties of Arco Lake, Budd Lake, Deming Lake, and Josephine Lake in Itasca State Park from 2006-2009 and 2019-et seq.
Depth profiles of water column chemical and physical properties were assessed with seasonal-scale frequency from four lakes in the Itasca State Park from 2006-2009 and from 2019-et seq. The data was used to assess the mixing status and major geochemical constituents within the lakes. Several parameters were routinely measured with deployable probes at meter or sub-meter resolution at the deepest location in each lake. Water samples were also collected for laboratory analysis. Bathymetry data collected in 2022 is supplied as rasters.
The Jefferson Project 2019 hydrologic, water quality, and soil quality data from 12 Tributary Stations within the Lake George basin, NY, USA.
The Jefferson Project at Lake George -- a partnership between Rensselaer Polytechnic Institute, IBM Research, and Lake George Association -- combines Internet of Things technology and powerful analytics with science to create a new model for environmental monitoring and prediction. The project is building a computing platform that captures and analyzes data from a network of sensors tracking water quality and movement. These sensor data are combined with other monitoring and experimental data to create a thorough understanding of the factors that drive the lake's food web, hydrology, and water quality. More information about The Jefferson Project is available at https://jeffersonproject.rpi.edu/ In 2019, The Jefferson Project had twelve tributary monitoring stations around the lake collecting data on water quality, soil quality, and hydrology. These stations are TS_Finkle, TS_Hague, TS_Indian, TS_NorthwestBay, TS_Outlet, TS_PoleHill, TS_English, TS_Sunset, TS_Sucker, TS_ShelvingRock, TS_East, and TS_West. The stations have a sensor payload that may include some or all of the following sensors: YSI EXO2 Multi-parameter sonde, Campbell Scientific CS451 pressure transducer, SonTek-IQ+ multi-beam acoustic flow meter, Sontek-SL Doppler current meter, YSI WaterLOG® H-3123 submersible pressure transducer, and Stevens HydraProbe soil moisture sensor. The sensors collect data at high-frequency (~1 sample per minute) and the data is transferred in near real-time to off-site databases for monitoring and review by Jefferson Project researchers. Data provided is level 4 data which underwent data correction and downsampling to an hourly frequency.
The Jefferson Project 2019 weather data from ten surface weather stations on Lake George, NY, USA.
The Jefferson Project at Lake George – a partnership between Rensselaer Polytechnic Institute, IBM Research, and Lake George Association – combines Internet of Things technology and powerful analytics with science to create a new model for environmental monitoring and prediction. The project is building a computing platform that captures and analyzes data from a network of sensors tracking water quality and movement. These sensor data are combined with other monitoring and experimental data to create a thorough understanding of the factors that drive the lake's food web, hydrology, and water quality. More information about The Jefferson Project is available at https://jeffersonproject.rpi.edu/ In 2019, The Jefferson Project had seven weather monitoring stations around the lake collecting data on precipitation, temperature, wind speed, wind direction, barometric pressure, and relative humidiity. These stations are WX_CedarLane, WX_DFWI, WX_GullRock, WX_MossyPoint, WX_WhaleRock, WX_PilotKnob, and WX_Glenburnie. Weather data from three vertical profiler sites (VP_AnthonysNose, VP_CalvesPen, and VP_TeaIsland) are also included in this dataset. The stations have a sensor payload that include some combination of the following sensors: Rotronic HC2-S3 sensor, Campbell Scientific CS616 soil moisture sensor, Li-Cor LI-200R pyranometers, RM Young 85006 anemometer, Vaisala Weather Transmitter WXT series (520 & 530 models), HyQuest TB3 tipping bucket rain gauge, N-Con wet deposition sampler. The sensors collect data at high-frequency (~1 sample per minute) and the data is transferred in near real-time to off-site databases for monitoring and review by Jefferson Project researchers. Data provided is level 4 data which has undergone data correction and downsampling to an hourly frequency.
The Jefferson Project 2019 water quality data from three vertical profiler stations in Lake George, NY, USA.
The Jefferson Project at Lake George -- a partnership between Rensselaer Polytechnic Institute, IBM Research, and Lake George Association -- combines Internet of Things technology and powerful analytics with science to create a new model for environmental monitoring and prediction. The project is building a computing platform that captures and analyzes data from a network of sensors tracking water quality and movement. These sensor data are combined with other monitoring and experimental data to create a thorough understanding of the factors that drive the lake's food web, hydrology, and water quality. More information about The Jefferson Project is available at https://jeffersonproject.rpi.edu/ In 2019, The Jefferson Project deployed three vertical profiler stations on the lake, collecting data on water quality and weather. Meteorological data have been included with the Jefferson Project Weather Station dataset for 2019. These vertical profiler stations are named VP_AnthonysNose, VP_CalvesPen, and VP_TeaIsland. The water quality data are collected by a YSI EXO2 Multi-parameter sonde sensors. The sensors collect data at 1 meter depth increments, starting at 1 meter and proceeding to 2 meters off bottom. The data are transferred in near real-time to an off-site database for monitoring and review. The data provided here have undergone data correction by Jefferson Project researchers.
Environmental and biological data associated with captive-reared Delta Smelt Study, Sacramento-San Joaquin Delta, CA, January-March 2019
The endangered Delta Smelt Hypomesus transpacificus is an osmerid fish endemic to the upper San Francisco Estuary. A captive breeding program for the species led by the Fish Culture and Conservation Laboratory (FCCL), University of California, Davis, began in 1996 to create a refuge population. In order to better understand how captive Delta Smelt would fare in conditions outside of the hatchery, we placed captive-reared fish in enclosures in the Sacramento San-Joaquin Delta, and evaluated their ability to survive, feed, and maintain condition. Fish were acclimated in the hatchery at FCCL, tagged, swabbed, weighed, measured, and transferred to enclosures in the field. There were three types of enclosures (n=2 for each type), varying in mesh size and wrap condition. In January 2019, 384 adult Delta Smelt (243 days post hatch) were transferred to enclosures in Rio Vista. In February 2019, 360 adult Delta Smelt (278 days post hatch) were transferred to enclosures in the Deepwater Shipping Channel. For each deployment, fish remained in enclosures for approximately one month, then were retrieved from enclosures, euthanized, identified, weighed and measured. A subset were also analyzed for diet contents. During the one-month long deployments, cages were checked for biofouling, damage, and dead fish, and water quality measurements and zooplankton samples were collected.
Concentration of nutrients in water samples collected from the Upper Clark Fork River (Montana, USA) during water year 2019 (1 Oct 2018 - 30 Sept 2019)
The umbrella LTREB monitoring project generating these data is conducted separately and complementarily to the $200 million-dollar (USD) superfund project for ecological restoration of the Upper Clark Fork River (UCFR), associated tributaries, and head water streams including Silver Bow and Warm Springs Creeks. Restoration along the Upper Clark Fork River includes removal of metal-laden floodplain soils, lowering of the floodplain to its original elevation, and re-vegetation of over 70 km of the river's floodplain closest to contaminant sources. The UCFR Long Term Research in Environmental Biology (LTREB) project includes bi-weekly water quality monitoring across a 200-km gradient of heavy metal contamination associated with historic mining. Monitoring includes inorganic phosphorus and nitrogen concentrations, biotic standing stocks, and dissolved and whole-water heavy metal concentrations. The UCFR LTREB monitoring project is conducted within the first 200 km of the Upper Clark Fork River and associated tributaries located in western Montana. The current monitoring program began in 2017 and will be completed in the year 2023, with likely funding extension to 2028. Surface water samples represented in this data product are collected from fourteen sites along the mainstem of the UCFR, and one site representing a major tributary to the UCFR. Water samples are collected at each monitoring site in triplicate and filtered with a 0.7-µm glass fiber filter. Nutrient samples are analyzed using a spectrophotometric flow injection analyzer (AP2) for nitrate (NO3-N), soluble reactive phosphorus (SRP, as representative of PO4-P), and ammonium (NH4-N) concentrations reported in mg/L. The analysis-ready data of this dataset therefore represent Quality Assurance and Quality Control (QAQC) processed NH4-N, SRP, and NO3-N concentrations from fourteen sites along the mainstem of the UCFR and one tributary, collected in water year 2019 (1 Oct 2018 - 30 Sept 2019).
Shifts in Bacterioplankton During Cyanobacterial Blooms Reflect Bloom Toxicity and lake Trophic State, OR 2019-2020
Harmful cyanobacterial blooms (cyanoHABs) typically occur in human-impacted eutrophic lakes suffering from nutrient pollution, but they also occur in lakes spanning the trophic and disturbance gradients. CyanoHABs change the bacterioplankton community structure with increases in specific cyanobacteria strains, as well as shifts in heterotrophic taxa. Bacterioplankton community shifts during cyanoHABs can be somewhat predictable but have been only studied in a limited number of lakes, most highly productive and in developed watersheds. The Cascade Mountains (USA) offer an unique area to study cyanotoxin variation and shifts in bacterioplankton composition across a productivity gradient in lakes with documented cyanoHABs but removed from most development. We explored associations of bacterioplankton communities with cyanoHABs and toxins within a season, as well as across lakes and years via physicochemical metrics, passive toxin samplers and 16S rRNA gene sequencing. The data set is a compilation of physicochemical, meteorological, biological as well as physical lake characteristics and sampling information. Water temperature was tracked continuously within a season for the three lakes while single point measurements of water temperature were taken for the other lakes in the spatial (n= 29) and intra-annual subset (n =12). Daily air temperature, precipitation and aerosol optical depth were extracted from the PRISM Gridded Climate data. Nutrient concentrations were measured for all lakes and analyzed for nitrogen and phosphorus via colorimetry in a flow analyzer. Chlorophyll-a concentrations were measured from filter samples via fluorimetry. Microcystin concentrations from grab and SPATT samples were analyzed via an ELISA kit for Microcystin-LR. Bacterioplankton diversity metrics were calculated from the processed 16S rRNA sequences along with the relative abundance of potentially toxigenic cyanobacteria. Bacterioplankton composition was and can be derived from the raw
Data associated with the 2019 Freshwater Oil Spill Remediation Study (FOReSt) assessing the use of enhanced Monitored Natural Recovery (eMNR) and shoreline washing agent (SWA) of diluted bitumen spills conducted in shoreline enclosures at the IISD Experimental Lakes Area, ON, Canada from 2019 to 2020
The following package includes data from the 2019 Freshwater Oil spill Remediation Study (FOReSt) at the IISD Experimental Lakes Area studying the use of enhanced monitored natural recovery (eMNR) and shoreline washing agent (SWA) as a secondary remediation method for diluted bitumen spills in freshwater shoreline enclosures. This package includes data tables on polycyclic aromatic compound chemistry in water and sediments, basic water quality, nutrient chemistry, and tritium chemistry monitored in the experimental and reference enclosures, and lake reference sites over the duration of the study. Data included in this package was first collected and used in the paper by Palace et al., titled Polycyclic aromatic compounds in freshwater ecosystems following non-invasive remediation of controlled diluted bitumen spills: The Freshwater Oil Spill Remediation Study (FOReSt) at the Experimental Lakes Area, Canada.
Indicators of Contaminant Sources, PFAS, and Water Quality in Ellerbe Creek and New Hope Creek, NC (2019-2022)
Thousands of chemical contaminants are found in urban stream globally. This is a dataset of water quality measures of (1) compounds that are indicative of specific contaminant sources, (2) common water quality measures [trace metals, major ions, nutrients], and (3) PFAS. Sampling was conducted in Ellerbe Creek and New Hope Creek in the Durham and Orange counties of North Carolina. Biweekly and synoptic sampling was undertaken to explore spatial and temporal variation in water concentrations.
Time series of total metal and nutrient loads into Falling Creek Reservoir in southwestern Virginia, USA from 2019-2024
Metal and nutrient loads were calculated from 2019-2024 from the inflow stream to Falling Creek Reservoir (FCR), a drinking water reservoir located in Vinton, Virginia, USA. The reservoir is owned and operated by the Western Virginia Water Authority and is managed as a secondary drinking-water source for the city of Roanoke, VA. Only Fe, Mn, and nutrients (TN and TP) were analyzed and calculated in 2019. The full suite of metals (Li, Na, Mg, Al, K, Ca, Fe, Mn, Cu, Sr, Ba) and nutrients were analyzed from 2020-2024. The loads that were collected using an ISCO automated sampler located at the main inflow tributary to FCR. Sampling frequency was approximately fortnightly from spring to fall (March - November). Load calculations were performed using the calculated cumulative flow over the sampling period from the ISCO and the analyzed total metal and nutrient concentrations. Please note we are publishing this data package before the nutrient samples have been analyzed, but will be included in later versions.
Linking river metabolism time series and aquatic vegetation biomass at 11 sites along the Klamath River, California (summer 2019)
Algae blooms in rivers are difficult to quantify due to high heterogeneity, deep and swift conditions, seasonally rapid changes, and the high amount of surveyor effort needed to document river conditions. The data presented here were used to test the extent that summer time series of daily metabolism data reflected the quantity and type of vegetation biomass in a highly productive river with variable primary producer assemblages. Two categories of data are included in this data release: 1) Daily ecosystem metabolism estimates (gross primary production, GPP, ecosystem respiration, ER, and net ecosystem production, NEP), and 2) Reach scale biomass of 3 vegetation assemblages. In addition to these data products, we include the input data used to estimate metabolism, which includes high frequency measurements of dissolved oxygen, water temperature, and light. We also included the raw data used to estimate reach scale biomass, including measurements of filamentous algal and macrophyte percent cover and field samples analyzed for ash free dry mass, which were used to scale field observations of cover to reach scale biomass estimates. Metabolism and vegetation biomass data were collected at 11 reaches along the mid and lower Klamath River, California during summer 2019.
Clear Lake water quality monitoring data from 2019 to 2023 by the University of California, Davis
A major barrier to effective water quality restoration at Clear Lake is the absence of quantitative data on the anticipated response to restoration projects. In-lake monitoring (in-situ measurements) is needed to understand better the processes contributing to poor water quality. This data package contains the in-situ measurements collected by the University of California, Davis at Clear Lake between 2019 and 2023, which include: continous stream properties at three locations (Middle, Scott, and Kelsey Creeks); continuous meteorological variables at seven locations around the perimeter of the lake; continuous lake temperature and dissolved oxygen at multiple depths and locations across the lake (six permanent water quality stations); continuous lake surface temperature in the shoreline; and discreate samples to measure nutrient concentrations and phytoplankton biovolumes and species identification throughout the water column and across all three lake basins every 6-8 weeks.
Metabolism estimates from dissolved oxygen and inorganic carbon in the Judith River Watershed, MT, USA, 2019-2021.
This dataset provides necessary supporting data and models for the manuscript titled "Stream corridor structure drives patterns in lateral inorganic carbon inputs and CO2 emissions in agricultural headwaters". The entire dataset consists of sensor data, alkalinity and metabolism estimates from oxygen and carbon models, collected in three reaches located in the Judith River Watershed, MT. The sensor data include partial pressure of carbon dioxide in water, dissolved oxygen and temperature. At each reach, we established a two station approach, meaning two pairs of sensor suits were distributed upstream and downstream. In addition to data products, we also provide R packages for metabolism models.
Forage Resources in Warming and Removal Plots, Almont, CO, 2019
This is data collected to explore the impacts of warming and dominant species removal on the quantity and quality of plants for cattle foraging. The data were collected from the Colorado low elevation site (Almont) of the Warming and Removal in Mountains experiment which examines the direct and indirect impacts of climate change on plant and soil communities. Treatments include a control, warming (+1.5C), removal of the dominant species (Wyethia Amplexicalus), and both warming and dominant species removal. The dataset includes data that were collected in 2019 as well as historical data from the site. From 2019 we have in situ air temperature contained in and soil temperature data and an assessment of plant cover from every plot. We then have a compiled set of plant traits for each of the nine most common species including the leaf nitrogen, crude protein content, and forage quality class which are used for analysis on forage quality. The dataset also includes the annual plant cover data collected at peak season from 2013 to 2021 which was compared to daily temperature and precipitation data from the same date range collected by the National Oceanic and Atmospheric Administration. All reported figures and statistics published can be created from this data package.
Hourly water temperature from the San Francisco Estuary, 1986 - 2019
Projected temperature increases due to global climate change are likely to have localized impacts on the San Francisco Estuary (SFE). Increased water temperature in the SFE will lead to challenges for managing water resources. Many native species, such as salmon and smelt, rely on cooler water, and will be further stressed by increased water temperature. While real-time water temperature is collected by several state and federal agencies in the San Francisco Estuary, a landscape-scale synthesis of available water temperature data has not been conducted for the SFE. For this dataset, we compiled continuous water temperature data and associated metadata from the SFE to generate an integrated and usable dataset of known quality for climate and ecological analysis. Data were obtained from the California Data Exchange Center (CDEC; https://cdec.water.ca.gov/) for consistency (data are untreated) and efficiency (existing code to download data directly from CDEC). Data were integrated and standardized to hourly water temperature data in degrees Celsius. A series of quality control (QC) checks were then applied in a consistent manner to all stations. Datasets included in this package include raw hourly data, flagged data, and filtered data (where flagged data are removed). Additionally, information regarding current and historical sensors used for water temperature data collection was obtained from station managers for each station, and compiled in a metadata table.
Arctic LTER Streams Chemistry Toolik Field Station, Alaska 1978 to 2019.
Since 1983, the Streams Project at the Toolik Field Station has monitored physical, chemical, and biological parameters in a 5-km, fourth-order reach of the Kuparuk River near its intersection with the Dalton Highway and the Trans-Alaska Pipeline. In 1989, similar studies were begun on a 3.5-km, third-order reach of a second stream, Oksrukuyik Creek. In each river, physical conditions (such as discharge and temperature), nutrient levels, primary production, insects, and fishes are monitored throughout the summer. Also, we conduct experimental fertilization of the Kuparuk River and Oksrukuyik Creek to determine the effects of added phosphorus and nitrogen on primary productivity, insect communities, and fish growth in arctic rivers. The Oksrukuyik Creek has not been fertilized since 1996. The Kuparuk River received phosphorus additions from 1983 through 2016. Station sites are relative distance from the original nutrient drippers for both the Kuparuk and Oksrukuyik. Kuparuk stations include sites in a reference, recovery, and fertilized reach. Reaches were defined based on the location of nutrient addition (see methods).
Soil nutrient availability from the 2007 Anaktuvuk River, Alaska, USA fire scar during the 2019 growing season
This file contains plant-available nitrate (NO3), ammonium (NH4), phosphate (PO4), and total free primary amines (TFPA )in the upper 5-10cm of organic matter from a burned and unburned site in the southern section of the 2007 Anaktuvuk River fire in northern Alaska. Soil nutrients were assessed using buried resin bags which incubated for 1 month during the peak of the growing season in 2019.
Point-frame measurement of maximum canopy height for plant growth forms at the 2007 Anaktuvuk River Fire scar measured in 2019.
This file contains maximum plant heights from point frame measurements made in the southern section of the 2007 Anaktuvuk River fire scar, at a severely burned site and a nearby unburned site. Pin-vegetation contact was recorded using a 0.56 m2 frame with 41 evenly spaced sampling points. Data were collected during peak green in summer 2019. These data were used to examine the impact of post-fire changes in plant community composition and structure on habitat suitability and rodent herbivore activity in response to a large, severe, and unprecedented fire in northern Alaska moist acidic tussock tundra.
Eriophorum vaginatum tiller nitrogen content at the 2007 Anaktuvuk River fire scar and nearby unburned tundra measured in 2019.
Tillers from 24 Eriophorum vaginatum individuals were sampled in late July 2019 to examine differences in percent nitrogen between previously burned (Anaktuvuk River Fire) and unburned tussocks at a nearby unburned control site. At the burned site tussocks exhibiting evidence of rodent grazing were also sampled to separate herbivore effects from those of the fire. From each tussock, 3-4 new leaves were sampled (as indicated by lack of brown tips) and dried at 60°C for 24 hours, before being ground and analyzed for percent nitrogen. The goals of the project were to examine the impact of post-fire changes in plant community composition, nutrient quality and structure on habitat suitability and rodent herbivore activity in response to a large, severe, and unprecedented fire in northern Alaska moist acidic tundra.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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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.