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.
5,424
datasets available to search
ShareScore release 0.7.1
Dataset results
5,424 results for “USA”
Food-chain length in desert streams of central and southern Arizona, USA
## overview Food chain length (FCL) is a key measure of the vertical structure of food webs that determines energy flow through ecosystems, carbon exchange between freshwater ecosystems and the atmosphere, and rates of nutrient cycling. FCL also has a strong bearing on the biomass of green plants in ecosystems and hence on water quality in aquatic ecosystems. Broad-scale syntheses of controls on FCL in stream ecosystems indicate that FCL declines with discharge variation but, counter to theory, does not vary significantly with energy supply. The mechanisms linking discharge and energy to FCL are largely unresolved in streams. We propose that lack of a relationship between energy supply and FCL may be due to variation in efficiency of energy transfer caused by constraints of food quality, or to a temporal mismatch between measures of energy inputs and FCL. Alternatively, the effects of flow variation on FCL may simply be paramount to energy supply, but potential mechanisms linking flow to FCL remain untested. Regime shifts—punctuated change between strings of high- and low-flow events—may cause comprehensive faunal replacement across trophic levels and collapse of the vertical structure of food webs. FCL may change as a result of loss (or gain) of an apex predator, or as a result of changes in feeding relationships leading to apex predators that eat higher on the food chain. Finally, flow variation may indirectly influence FCL through inputs of limiting nutrients during floods. In desert streams, algae typically provide the primary source of energy, and algal production is limited by nitrogen (N). N loading from terrestrial ecosystems is strongly related to flow variation, particularly to the inter-flood interval (IFI) or duration of baseflow between floods. Long IFI leads to larger N pulses and potentially greater net ecosystem production (NEP), thereby providing an indirect effect of flow variation on FCL. Specific aims of the research include: 1) Quantify the effe
Cyanobacteria abundance, cyanotoxin concentration, and water quality data for the upper San Francisco Estuary, California, USA: 2014-2019
The goal of these measurements was to quantify Microcystis abundance and microcystin concentration and associated water quality conditions during summer blooms in the upper San Francisco Estuary in California, USA. Blooms of harmful algae are a major ecological concern in the area because harmful algae produce toxins and other metabolites, which deteriorate water quality and negatively impact the aquatic ecosystem. Our research team collected biological, physical, and chemical data at 2-week to 4-week intervals during the summer and fall from 2014 through 2019. Data included surface measurements of Microcystis volume (area-based diameter) by microscopy (flowCAM digital imaging flow cytometry) and subsurface (1 m depth) measurements of Microcystis, Aphanizomenon and Dolichospermum cell abundance measured by quantitative PCR, cyanotoxin concentration (total microcystins, anatoxin a and saxitoxin) measured by protein phosphatase inhibition assay or enzyme linked immunosorbent assay, and a suite of water quality parameters (water temperature, dissolved oxygen, nutrient concentration, water transparency, specific conductance, turbidity, pH, and chlorophyll a concentration). Details for the field sampling and analytical methods are available in Lehman et al. (2017). We also performed shotgun metagenomic analyses to investigate biodiversity of cyanobacteria and other aquatic microorganisms and all the DNA sequencing data are publicity available (www.ncbi.nlm.nih. gov/; BioProject ID: PRJNA434758, Kurobe et al. 2018, Lehman et al. 2021). During the study, we experienced critically dry (2014 and 2015), below normal (2016 and 2018), and wet years (2017 and 2019), therefore data obtained in this study provided a unique opportunity to assess impacts of extreme conditions on the aquatic ecosystem (Kurobe et al. 2018, Lehman et al. 2020).
General Lake Model-Aquatic EcoDynamics model parameter set for Falling Creek Reservoir, Vinton, Virginia, USA 2013-2019
The General Lake Model (GLM), an open-source, one-dimensional hydrodynamic model, was used to simulate physical, chemical, and biological variables in Falling Creek Reservoir, Vinton, Virginia, USA between 15 May 2013 and 31 December 2019. GLM (v.3.2.0a3) was coupled to the Aquatic EcoDynamics (AED) module library via the Framework for Aquatic Biogeochemical Modeling (FABM). GLM-AED requires three configuration files to run the model. First, the glm3.nml file configures lake metadata (including hypsometry), meteorological driver data, stream inflow and outflow driver data files, and physical response variables (mixing parameters and sediment heat zones). Second, the aed2_20220111_2DOCpools.nml file configures various biogeochemical modules for the simulation of oxygen, carbon, silica, nitrogen, phosphorus, organic matter, and phytoplankton. Third, the aed2_phyto_pars_4Jan2022.nml file configures all parameters pertaining to phytoplankton dynamics. Meteorological data, two surface stream inflow files, a submerged oxygenation inflow file, and outflow file used in this calibration are also included.
Ice Phenology for 58 Lakes in Maine, USA, 2002/2003-2017/2018
This dataset contains ice phenology for 58 lakes in Maine, USA between winter 2002/2003 and 2017/2018 from the Lake Stewards of Maine Volunteer Lake Monitoring Program, Maine Department of Environmental Protection, and the Auburn Water District/Lewiston Water Division. Ice-off data in this dataset are available for all 58 lakes, ice-on data are available for 13 lakes. These data are a subset of all ice phenology data available from each of the data sources. Lakes had at least four years of ice phenology data and each lake is at least 3 km2 to facilitate the pairing of MODIS temperature data.
Species and groundcover of understory herbaceous plants in a chronosequence of reforested urban sites, Lexington, KY USA
This dataset contains information on understory plant communities in across twenty urban reforestation sites planted as part of the Reforest the Bluegrass program in Lexington, KY. Urban reforested areas located in Lexington, Kentucky were evaluated over the course of summer 2020. At least three plots (and up to nine plots) were established in each site, with additional plots added if forested patches were sufficiently large. At each plot, we established a 0.008-ha (0.02-ac) circular sampling plot to survey understory plant species. Groundcover of all species, excepting tree- and shrub-forming species, was visually estimated in 10 grids, 0.6 m x 0.6 m. These data will contribute to understanding of understory plant community dynamics in developing urban forests.
Summer water chemistry, phytoplankton and zooplankton community composition, size structure, and biomass in a shallow, hypereutrophic reservoir in southwestern Iowa, USA (2019).
This data product contains data for Green Valley Lake, a hypereutrophic reservoir in southwest Iowa (USA) from the summer of 2019. We sampled and quantified zooplankton, phytoplankton, and nutrient concentrations (total N, total P, soluble reactive P, nitrate) in the lake weekly with the primary aim of assessing consumer nutrient cycling, specifically zooplankton nutrient cycling, in a hypereutrophic reservoir. Weekly plankton sampling included quantifying zooplankton and phytoplankton biomass, community composition, and size structure. Phytoplankton size was measured as the greatest axial linear distance which would be approached by a zooplankton grazer. Allometric equations from the literature were applied to the zooplankton size measurements to estimate zooplankton community excretion of N and P. We found that the estimated contribution of zooplankton excretion to the dissolved P pool was substantial in the spring. Further, we found evidence that zooplankton affected phytoplankton size distributions through selective grazing of smaller phytoplankton cells likely affecting nutrient uptake and storage by phytoplankton.
Long-term above- and belowground net primary production (NPP) measurements from a grassland-shrubland transition zone in the Sevilleta National Wildlife Refuge, New Mexico, USA
Drylands are key contributors to interannual variation in the terrestrial carbon sink, which has been attributed primarily to large-scale climatic anomalies that disproportionately affect net primary production (NPP) in these ecosystems. Current knowledge around the patterns and controls of NPP is based largely on measurements of aboveground NPP (ANPP), particularly in the context of altered precipitation regimes. Limited evidence suggests belowground NPP (BNPP), a major input to the terrestrial carbon pool, may respond differently than ANPP to precipitation, as well as other drivers of environmental change, such as nitrogen deposition and fire. This data package accompanies an associated manuscript in which we used sixteen years (2005-2020) of annual NPP measurements, derived from three ongoing long-term research sites, to investigate spatiotemporal responses of ANPP and BNPP to several environmental change drivers across a grassland-shrubland transition zone in the northern Chihuahuan Desert.
Long-term species-level measurements of fall season aboveground net primary production in the Monsoon Rainfall Manipulation Experiment (MRME), Sevilleta National Wildlife Refuge, New Mexico, USA
Anticipated intensification of the North American Monsoon in the southwestern United States is predicted to shift growing season rainfall patterns, historically characterized by frequent small rain events, to a more extreme precipitation regime consisting of fewer, but larger rain events. Atmospheric nitrogen deposition is also increasing throughout this dryland region as a result of anthropogenic activities. Alterations in rainfall size and frequency, along with changes in nitrogen availability, are likely to have significant consequences for aboveground net primary production (ANPP) and plant community dynamics in drylands, where ecological processes are limited by water and nitrogen availability. This data package accompanies an associated manuscript in which we used fourteen years (2007-2020) of growing season ANPP measurements from the long-term Monsoon Rainfall Manipulation Experiment (MRME), located in the Sevilleta National Wildlife Refuge, to investigate how changes in rainfall regimes, along with chronic nitrogen enrichment, impact ANPP in a northern Chihuahuan Desert grassland.
Hourly water chemistry measurements at the mouth of West Falmouth Harbor, MA, USA from 2005 to 2019 and 2023
West Falmouth Harbor (West Falmouth, MA, USA) has been experiencing a dramatic increase in nitrogen loading from an upgradient municipal wastewater treatment facility since the early 2000s. As part of a long-term study into the effects of this nitrogen enrichment, we have been measuring water chemistry at the mouth of the harbor to calculate exchange between the harbor and adjacent coastal waters of Buzzards Bay. Water samples were taken hourly over 24- to 48-hour periods during several periods in 2005-2009, 2014, 2017, 2019, and 2023. Data from 2005-2009 were collected year-round; samples from 2014 and later were collected during June through August. Samples were processed for ammonium, phosphate, nitrate + nitrite, total nitrogen, and total phosphorus unless otherwise notated. During some sampling years, additional samples were run for silicate, chlorophyll, total dissolved nitrogen, total dissolved phosphorus, dissolved organic carbon, particulate organic carbon, and particulate organic nitrogen. Salinity is reported for all samples. Samples were collected with an ISCO autosampler and stored on ice until analysis. Full analysis details and quality control methods are available in Hayn et al. 2014 (doi: 10.1007/s12237-013-9699-8) and Hayn 2025 (doi: 10.7298/btm6-ba76).
Time series of high-frequency sensors measuring water temperature and dissolved oxygen at discrete depths in Falling Creek Reservoir, Virginia, USA in 2012-2018
We measured water temperature and dissolved oxygen at multiple depths in Falling Creek Reservoir (Vinton, Virginia, USA) with high-frequency (10 to 15-minute) sensors for different durations during 2012 to 2018. Falling Creek Reservoir is owned and managed by the Western Virginia Water Authority as a primary drinking water source for Roanoke, Virginia. All measurements were collected at discrete depths at the deepest site of the reservoir adjacent to the dam. The sensors consisted of: 1) InsiteIG dissolved oxygen and water temperature sensors (Model 20 dissolved oxygen sensor) at both 1 m (November 2015 - December 2018) and 8 m (September 2012 - December 2018) and 2) HOBO (HOBO Pendant Temperature/Light 64K Data Logger) water temperature loggers deployed at 1, 2, 3, 4, 5, 6, 7, 8, and 9.3 m depths (September 2015 - January 2018).
Long-term (1993-2019) dynamics of tree populations on a mapped 3-ha permanent plot in old-growth northern hardwood forest, Huron Mts., Marquette Co., MI, USA
This data-set includes multiple remeasurements, over 25 years, of all woody stems >2 cm diameter (total of 2125 stems) on a 2.72-ha stem-mapped plot in old-growth northern hardwood forest in the Huron Mountains region of northern Marquette County, MI. The plot and surrounding forest is dominated by sugar maple (Acer saccharum) and eastern hemlock (Tsuga canadensis). Among secondary species, yellow birch (Betula alleghaniensis) and basswood (Tilia americana) are most common. Soils (identified as Kalkaska series) are developed on deep sandy glacial outwash. The plot is within a much larger region of old-growth forest, protected since ca. 1880, with only minimal disturbance associated with access tracks and trails. Numerous other forest community and dendrochronological studies support the interpretation that the area around the study plot has not experienced stand-initiating disturbance for at least 400 years. Initial mapping and measurements (1993-1995 for 2.52 ha; an additional 0.2 ha added in 1999) used a 20x20 m grid established in a near-level area of uniform substrate. All stems were identified to species, mapped on polar coordinates from the center of each grid cell (including, at first measurement, identifiable dead trees, standing and down), and diameter at breast height (dbh) measured to nearest 0.1 cm. All stems were remeasured on a five-year cycle 1999-2019, and new mortality was recorded at each remeasurement. New recruits > 2 cm dbh were added at each remeasurement.
Dreissenid mussel shell deposition, and benthic community data in the Rouge and Huron Rivers, Southeastern, MI., USA.
This data package was assembled and accompanies a project entitled "Investigating the effects of Dreissenid mussel shells in streams post-invasion," carried out in the Rouge and Huron Rivers in Southeastern, MI., USA in 2017. We assessed the impacts of Dreissenid shells on macroinvertebrates and fish communities. This package includes dreissenid shell density data, water quality data during macroinvertebrate sampling, macroinvertebrate data, water quality data during fish sampling in spring, fish data from spring, water quality data during fall sampling, and fish data from fall. All data tables feature rivers, identifiers, GPS coordinates, and sample dates.
Long-term (1993-2019) tree population measurements from a mapped 2.9-ha permanent plot in old-growth northern hardwood forest, Dukes Research Natural Area, Marquette Co., MI, USA
The Dukes Research Natural Area (Hiawatha National Forest, Marquette Co., MI) amounts to ca. 100 ha of minimally disturbed original forests, including a mix of mesic 'hemlock-northern hardwood' types and peaty wetlands dominated by several species of swamp conifers and black ash (Fraxinus nigra). The RNA hosts a regular grid of 250 permanent monitoring plots (data to be provided in a separate package). In 1993-95, a macroplot of 2.91 ha was established in a mixed mesic upland forest area within the RNA, in which all woody stems >2 cm diameter at breast height (DBH) were identified, measured, and mapped. In 1999 and again every five years subsequently through 2019, the macroplot was recensused; all stems were remeasured, stems newly recruited (>2 cm DBH) were measured and mapped, and any mortality since previous census was noted and described. A severe storm in 2002 resulted in extensive mortality throughout the RNA, particularly in the area in and around the macroplot.
High frequency limnological sensor data from three lakes in the Pocono Mountains region, Pennsylvania USA, 2016-2024
This dataset publication provides access to eight years of high-frequency sensor data from three lakes: Giles, Lacawac, and Waynewood. These lakes are located in the Pocono Mountains region of Pennsylvania, USA and have been the site of long-term monitoring and research. Lake Giles is a relatively clear-water low dissolved organic matter oligotrophic lake in a largely protected watershed. Lake Lacawac has higher dissolved organic matter concentrations and is considered a dystrophic brown-water system; it is also in a highly-protected watershed. Lake Waynewood is a relatively productive eutrophic lake with a larger watershed that is mixed agricultural, forested, and residential use. High-frequency sensors were deployed on sensor lines at the deepest point in each lake. Measurements included temperature and dissolved oxygen through the water column, fluorescent dissolved organic matter at the surface and bottom, and chlorophyll fluorescence at the surface of each lake. These data are collected at a frequency of 10 to 30 minutes and are available in the data packages GilesHighFrequencyData.csv, LacawacHighFrequencyData.csv, and WaynewoodHighFrequencyData.csv. Data from weather stations located adjacent to each lake can be found in the data package PoconosWeatherStationData.csv. Additional long-term limnological data (four decades) for Lakes Giles, Lacawac, and Waynewood are available in the data package edi.186.8.
Time series of stable water isotopes (d18O, d2H) from Carvins Cove Reservoir in Southwestern Virginia, USA 2024-2025
Samples of stable water isotopes (delta 18O and delta 2H) were collected from surface waters and depth profiles in Carvins Cove Reservoir (Roanoke, Virginia, USA). Carvins Cove Reservoir is owned operated by the Western Virginia Water Authority as a primary drinking water source for Roanoke, Virginia. Samples were collected approximately monthly at two sites along a primary tributary and depth profiles at multiple transects within Carvins Cove Reservoir from May 2024 - April 2025. Additional isotope samples were analyzed from precipitation collected at the Carvins Cove Reservoir dam in 2024. Samples were analyzed using cavity ringdown spectroscopy and reported as deviation of concentration from that of Vienna standard mean ocean water. An Rmarkdown file to visualize the dataset accompanies the package.
The Jefferson Project 2021 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 2021, 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 2021. These vertical profiler stations are named VP_AnthonysNose, VP_HarrisBay, and VP_TeaIsland. The water quality data are collected by a YSI EXO2 Multi-parameter sonde sensors. The sensors collect data at 1 meter or less 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.
The Jefferson Project 2021 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 2021, 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 are transferred in near real-time to off-site databases for monitoring and review by Jefferson Project researchers. The data provided here are level 4 data which underwent data correction and downsampling to an hourly frequency.
The Jefferson Project 2021 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 2021, The Jefferson Project had ten weather monitoring stations on and around the lake collecting data on precipitation, temperature, wind speed, wind direction, barometric pressure, and relative humidity. These stations are WX_CedarLane, WX_DFWI, WX_GullRock, WX_MossyPoint, WX_WhaleRock, WX_PilotKnob, WX_Glenburnie, VP_TeaIsland, VP_AnthonysNose, and VP_HarrisBay. 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, and N-Con wet deposition sampler. The sensors collect data at high-frequency (~1 sample per minute) and the data are transferred in near real-time to off-site databases for monitoring and review by Jefferson Project researchers. The data provided here are level 4 data which has undergone data correction and downsampling to an hourly frequency.
A database of published mangrove articles for coastal Louisiana, USA
Mangroves are being increasingly recognized as natural climate solutions for the range of ecosystem services they provide. In North America, one of the northern range limits of mangroves is found in coastal Louisiana, USA, where in recent decades, mangroves have been expanding into wetlands formerly dominated by salt marsh primarily due to decreases in the frequency and severity of winter freeze events. While reviews focused on mangrove ecology that include coastal Louisiana within a broader geographic scope have been conducted, no systematic review has focused on what is known about mangrove ecology across coastal Louisiana, a region that contains the expansive Mississippi River Delta. To fill this knowledge gap, we conducted a systematic review to highlight the breadth of mangrove research topics that have been studied in coastal Louisiana and identify emerging and future research opportunities. We identified four main research topics: (1) mangrove expansion, (2) freeze tolerance, (3) coastal restoration, and (4) disturbance. We also identified geographic biases in where mangrove research has been conducted, with a focus around the heavily industrialized Port Fourchon/Grand Isle area.
Continuous Climate Measurements from Highlands Biological Station, Highlands, North Carolina, USA, 2020-2025
The Highlands Biological Station (HBS) has been collecting rainfall and air temperature measurements since 1961. In October 2020 a new Campbell Scientific Instruments climate station was deployed on the north campus of HBS. Temperature, humidity, rainfall, wind speed, wind direction, and photosynthetically radiation (PAR) measurements are collected every 60 seconds and output as averages/total every hour.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.