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.
6,298
datasets available to search
ShareScore release 0.9.0
Dataset results
6,298 results for “2022”
Species-level estimated abundances and zero counts of nighttime collected female mosquitoes 2014 - 2022 (Derived from NEON Mosquitoes sampled from CO2 traps (DP1.10043.001, RELEASE-2024))
This Level 2 data package contains species level estimated abundances, including zero counts, and estimated mean number of female mosquitoes per trap derived from the NEON Mosquitoes sampled from CO2 traps (DP1.10043.001), RELEASE-2024 Level 0 data (https://doi.org/10.48443/3cyq-6v47). The data set includes mosquito records of traps collecting mosquito samples at night, for up to 24 trap hours, across a total of 20 terrestrial core and 27 terrestrial gradient sites from 2014 to 2022. To ensure high confidence in abundance estimates, records were only included when at least 90% of collected individuals were identified to sex, and 90% of female specimens were identified to species. Information across multiple QC/QA fields within the NEON mosquito data was evaluated to identify and exclude records where confidence in estimated abundances may have been compromised. Species level zero counts were added for all species collected at least once within the sampling year and trap location. Additionally, species level zero counts were included for trap events where only male mosquitoes had been collected or where QC/QA remarks indicated traps were inactive due to cold temperatures. The data set provides an analysis ready time series of estimated abundances across NEON sites and plots. An R Markdown file that contains descriptions of the QC/QA and data filtering steps along with annotated code, as well as data tables used to filter active and inactive trap events based on QC/QA fields, are published with the data package. Any questions about this data package should be directed to Amely Bauer listed under contacts.
Rates and controls of nitrogen fixation in post-fire lodgepole pine forests, Greater Yellowstone Ecosystem, 2022
This dataset contains all the contents needed to reproduce the calculations and analyses done in the original paper associated with this dataset (Heumann et al. 2025 Ecology). The primary method used in this study was the Acetylene Reduction Assay (ARA) which measures the rate at which acetylene is reduced to ethylene in nitrogen-fixing organisms as a proxy for nitrogen fixation activity. We measured acetylene reduction rates in multiple cryptic niches (i.e., lichen, moss, pine litter, dead wood and mineral soil) in 34-year-old lodgepole pine stands in the Greater Yellowstone Ecosystem to explore the rates, temporal patterns, and climate controls on cryptic N fixation. Thus the foundation of this dataset is ethylene production rate measurements. All the data tables in this dataset contain either measured ethylene production rates or estimates of N fixation scaled from those ethylene production rates. Included with this are various physical measurements (e.g. dry mass, moisture content, incubation temperatures) that we included in our analyses in order to either scale up rates of N fixation using biomass estimates from field sites or explore temperature and moisture relationships with nitrogen fixation activity under controlled conditions. Included with this dataset are three R studio scripts used to run the calculations and analyses reported in the manuscript publication from this study.
Endurance swimming performance and physiology of juvenile sturgeon at different temperatures, 2022-2024
Endurance swimming trials were conducted on both Green Sturgeon (Acipenser medirostris) and White Sturgeon (Acipenser transmontanus) across multiple size classes to assess the effects of temperature and velocity on swimming performance. Fish were exposed to various water temperatures for at least 14 days and swam at fixed-water velocities (cm/s) in controlled swim tunnels. Data were collected on parameters such as species, size class, trial temperature, velocity, recovery time, time-to-fatigue, swim type classifications, and whether the trials were completed. Additional metadata included fish morphometrics such as fork length, total length, weight, and trial dates, enabling comparisons across species, size, and treatment conditions. Physiological responses were measured post-swimming to evaluate the impacts of endurance trials on the smallest size class of Green Sturgeon (5cm fork length): - In 2022, whole-body cortisol, glucose, and lactate concentrations were measured immediately following endurance trials (0 min recovery). - In 2023, recovery dynamics were incorporated, with physiological responses assessed at multiple time points (0 min, 15 min, 30 min, and 60 min post-trial). - In 2022 and 2023 the baseline physiological metrics (whole-body cortisol, glucose, and lactate concentrations) of control fish (not subjected to swimming trials) were measured across all temperatures, years, species, and size classes. This dataset provides information on sturgeon swimming performance under varied temperature conditions, as well as the associated physiological stress responses, offering valuable insights into their endurance capabilities and recovery processes. The findings can inform conservation strategies, habitat management, and aquaculture practices for these ecologically and economically important species.
Field Evidence of Carbon and Nitrogen Stabilization through Mineral Associated Organic Matter Formation in Coastal Wetland Soils from Apalachicola, Florida, collected in June, 2022.
This data set was used to observe the role of Mineral Associated Organic Matter Formation (MAOM) on biogeochemical soil properties in three coastal wetlands in Apalachicola, Florida. One wetland was restored using beneficial dredged sediment, increasing the soil's inorganic matter content. Soil samples were collected in June 2022 from this wetland and two nearby reference wetlands: one with high organic matter and the other with higher inorganic matter content. The samples were analyzed at the University of Central Florida for biogeochemical properties to determine which properties were most related to MAOM pools.
Soil respiration rates, biogeochemical pools, and mineral-associated organic matter from high organic matter and high mineral content coastal wetland soils in Apalachicola, Florida, 2022
This data set was used to observe how the application of dredged sediment would impact soil respirations rates, biogeochemical pools, mineral associated organic matter of coastal wetland soils from Apalachicola, Florida. To achieve this, a combination of intact core and bottle incubations were used, comparing a high organic matter coastal wetland soil to a high mineral content wetland soil which were collected in June, 2022. All laboratory analysis was conducted at the University of Central Florida in Orlando, Florida.
Geochemical Characterizations for Identifying Fugitive Dust Deposition and Enrichment of Surface and Subsurface Subalpine Soils from Phosphorus Mining, Eastern Ashley National Forest, Utah, 2022-2023.
Phosphorus is a non-renewable resource essential for all life. Anthropogenic alterations to the phosphorus cycle have led to widespread phosphorus pollution, and the unsustainable management of P has led to the threat of global depletion of phosphorus resources. Thus, accounting for the natural and anthropogenic flow paths of phosphorus is essential for its conservation and pollution reduction. One such source of human alteration to the phosphorus-cycle is phosphate rock mining. Mining, however, has many adverse environmental effects, including widespread fugitive dust emissions. Dust collection in the Ashley National Forest of northeastern Utah, proximate to a surface phosphorus mine, has shown phosphorus concentrations in dust more than four times that of other regional samples. Elevated phosphorus in dust near active surface mining suggests that mining emissions may alter the natural phosphorus loading of the soils in the National Forest through dust deposition; however, no research has been done to identify the abundance and range of mine-attributable phosphorus enrichment in the soils surrounding phosphate mining activities. The combined geospatial and geochemical approach of this study shows that surface soil phosphorus concentrations were found to be enriched above naturally occurring levels up to 6.5 km from mining activity (enrichment factor > 1.5), with the most significant enrichment occurring within the first 3 km (enrichment factor > 2). On average, surface phosphorus concentrations were significantly enriched by 25% within 6.5 km of phosphorus mining activity. Observed phosphorus enrichment was positively correlated with the presence of fluorapatite in the soil, which is the primary phosphorus-mineral extracted from the nearby mine. Further, bioavailable phosphorus concentrations were also higher for the soils that were enriched in phosphorus. This study shows that fugitive emissions associated with the surface mining of phosphate rock are a significan
Longitudinal water quality sampling of King's Creek (KS) and Caribou Creek (AL), 2022 and 2023
We sampled Caribou Creek in July 2022 and King's Creek in August 2022 and May 2023 longitudinally for dissolved carbon dioxide using a headspace equilibrium method as well as other water quality parameters. The data was used to inform a stream network model to model carbon dioxide across the stream networks. The data package is complete.
Marsh vegetation data in Spartina alterniflora and Distichlis spicata marshes along the Texas coast, 2022 - 2024
We measured plant biomass and plant physiological metrics in two salt marshes in Bayside, Texas, and Port Aransas, Texas, from 2022 - 2024. Study plots (1-m2) were established in two Spartina alterniflora and Distichlis spicata-dominated salt marshes in the Texas Coastal Bend. At one site, S. alterniflora and D. spicata occurred in monoculture cover, and we established six study plots per species cover. Transects of plots encompassed two Landsat-8 and -9 pixel footprints, with a plot density of 3 plots per satellite pixel footprint. At the second site, both species occurred in intermixed stands. At this site we established seven study plots, and plots were not intentionally co-located with satellite pixel footprints. All plots were sampled once each during August and November of 2022, February, May, August, and November of 2023, and February and May of 2024. In each plot, measurements included plant biomass, plant species, stem density, and stem height. Aboveground biomass was calculated using allometric relationships between plant height and mass from plant clipping studies. During these surveys, destructive core sampling was also performed in the proximity of the plots (n = 1 per plot per species) to measure above- and belowground biomass. We measured plant physiological metrics as foliar chlorophyll, foliar N, and Leaf Area Index. Foliar chlorophyll and foliar N were assessed per species present, and Leaf Area Index was measured once per plot. These measurements were taken in the proximity of the plots. We also measured elevation once at each plot at the start of the study period. At each site, we measured water level with HOBO U20L pressure transducers. We installed a stilling well and placed one transducer above the marsh surface to measure ambient pressure, and one transducer at depth. We used the HOBOware software to calculate water level. Measurements were collected at 15 minute intervals. In instances of ambient pressure equipment failure, ambient pressure
Hydrochemical Data from a Tropical Andean Glacierized Catchment: δ18O, electrical conductivity, maximum fluorescence intensity, and dissolved organic carbon concentrations from short-term sampling campaigns, Ecuador (2022 and 2024)
Fluorescent dissolved organic matter (FDOM) quality, dissolved organic carbon (DOC) concentration, electrical conductivity (EC), and stable water isotopes (δ¹⁸O and δ2H) were determined in water, snow, and ice samples from a tropical glacierized catchment in the Ecuadorian Andes. The sampling locations were selected to capture the major hydrologic inputs to the main stream channel (glacial melt, tributaries, wetlands, and groundwater springs) and constrain the in-stream spatiotemporal variation in DOM quality and other hydrochemical characteristics. Two sets of high-resolution time series were collected on Oct 13, 2022 and Jun 14, 2024. Time series samples were collected at various upper catchment locations and the outlet simultaneously. DOM quality was characterized via fluorescence spectroscopy and processed using parallel factor analysis (PARAFAC). The DOM quality data are expressed as %FMax values obtained through a 4-component PARAFAC model, where %Fmax 1– 4 are interpreted as terrestrial humic-like, tyrosine-like, tryptophan-like, and microbial humic-like fluorescent components, respectively. DOC concentrations were quantified using high-temperature catalytic combustion, stable water isotopes were analyzed using laser-based spectroscopy, and EC was measured in situ with handheld multiparameter water quality probes.
California's Central Valley Project Improvement Act Predation Contact Point Study - 2022: Predator-prey interactions under low artificial lighting in a laboratory setting
The highest rates of piscivorous predation in the field have been recorded during crepuscular light levels associated with sunrise and sunset or artificial lighting at night (ALAN). We conducted a laboratory study where groups of predator-naïve, hatchery-raised juvenile rainbow trout (Oncorhynchus mykiss) were exposed to natural-origin piscivorous largemouth bass (Micropterus salmoides) under three light treatments representative of brighter crepuscular periods or direct ALAN illumination (“high” treatment), dimmer crepuscular periods or sky glow from ALAN (“medium” treatment), and night or no ALAN (“low” treatment). We then statistically evaluated potential associations between light treatment, prey group cohesion, and predator activity.
Infauna from the York River Estuary, Chesapeake Bay, Spring Fall 2022
Sediment macroinfauna were sampled at 7 sites in the York River Estuary in Spring and Fall, 2022, as part of a project relating infaunal community structure to physical properties of sediments.
Survey of Alarka Laurel and Rich Mountain Red Spruce (Picea rubens) Overstory, Saplings, and Seedlings in western North Carolina in 2007, 2022, and 2023
In the southern Appalachians, disjunct red spruce (Picea rubens) populations persist at low latitudes at elevations above 1,370 m. However, research on the condition of these disjunct red spruce populations is limited. This study compared baseline health, recruitment, and stand dynamics of two of the southern-most red spruce populations in eastern North America, the Rich Mountain and Alarka Laurel spruce bog basins in Nantahala National Forest, North Carolina. We collected data on overstory (DBH>10 cm), saplings (DBH< 10 cm, and height >2 m), and seedlings (height<10 cm) from Alarka Laurel in 2007 and 2022. Data from Rich Mountain were collected in 2023. We used 10-m wide belt transects noted the species and diameter at breast height (DBH) of overstory species, counted and noted the DBH of red spruce saplings, and counted and noted the height of red spruce seedlings. In 2022 and 2023, we gave a health score from 0-3 for all three categories of trees (overstory, saplings, and seedlings), with 0 being dead and 3 being healthy with little to no signs of disease or stress. Overall, both stands did not yet appear affected by climatic warming, despite the southern latitude and relatively low elevation. Our findings reveal that red spruce is the dominant overstory species, comprising an average of 25.6% of all measured overstory trees, with seedlings and saplings making up 72.8% of the red spruce population, indicating sustainable recruitment. Red spruce basal area declined by 13.9% from 2007 to 2022 in Alarka Laurel, with a concomitant increase in some hardwood species. However, both Alarka Laurel and Rich Mountain showed high levels of sapling and seedling recruitment. Overall, red spruce trees are healthy, particularly seedlings, representing the healthiest age category. Our results suggest the stands are relatively stable and provide essential baseline data for monitoring of forest conditions in the context of intensifying climate change. This research contributes to b
Data for: Techno-economic and environmental assessment of converting mixed prairie to renewable natural gas with co-product hydroxycinnamic acid, Iowa, USA, 2022-2023.
This dataset compiles model outputs, parameter sets, and documentation supporting a techno‑economic analysis (TEA) and life‑cycle assessment (LCA) of co‑digesting beef cattle manure with pretreated mixed prairie biomass to produce renewable natural gas (RNG), with hydroxycinnamic acids (HCA) and digestate‑derived biochar co‑products. It accompanies the study by Katherine Wild, Elmin Rahic, Lisa A Schulte Moore, and Mark Mba Wright "Techno-economic and environmental assessment of converting mixed prairie to renewable natural gas with co-product hydroxycinnamic acid," in Biofuels, Bioproducts, & Biorefining, 2024 (https://doi.org/10.1002/bbb.2710). The integrated simulation and assessment framework quantifies process performance, economics, and greenhouse‑gas intensity across five scenarios representing combinations of alkaline‑ethanol pretreatment for HCA extraction, liquid recirculation fractions, and biochar addition. This data collection includes: stream‑level mass flow/composition tables for each scenario; RNG, biochar, and HCA annual production summaries; literature‑based methane/biogas yield benchmarks; equipment‑level capital costs; TEA assumptions; emission‑factor inventories and displacement credits; and full sensitivity/uncertainty matrices for MFSP and GWP.
Removal of Aqueous Uranyl and Arsenate Mixtures by Natural Limestone and Hydroxyapatite Precipitates, Rio Paguate, NM, 2022-2023
This dataset documents a series of laboratory batch experiments investigating the removal of aqueous uranyl (U) and arsenate (As) mixtures using natural limestone and precipitated hydroxyapatite (HAp, Ca₁₀(PO₄)₆(OH)₂) as reactive materials. The main objective of the study was to address the challenge of simultaneous removal of uranyl cations and arsenate oxyanions by using mineral-based adsorbents, such as limestone. The precipitation of HAp enhanced As removal while maintaining high uranium immobilization efficiency.The archived data include measurements of aqueous U and As at trace-level concentrations under varying experimental conditions, including pH (ranging from 7 to 11), initial contaminant concentrations (0.05–1 mM), and the addition of calcium (Ca²⁺) and phosphate (PO₄³⁻) to promote HAp precipitation. Experiments were conducted in triplicate to ensure reproducibility, and solid-phase characterization data (from pXRD, SEM/EDX, and electron microprobe analysis) are also included to support the interpretation of removal mechanisms. A key finding revealed from the data is that near-complete removal of U (>97%) with As removal between 30 and 98% were achieved under pH conditions around 9. This dataset provides a comprehensive record of solution chemistry and treatment performance, serving as a fundamental resource for evaluating the effectiveness of natural mineral-based approaches for remediating co-contaminated waters.
Red Oak Root and Soil Environmental Gradient Study, Midwest U.S., 2022-2023.
Fine root trait and soils data for Quercus rubra L. (northern red oak) sampled along a Midwestern latitudinal gradient. Fourteen sites spanning 5-14 degrees C were sampled. Each sample represents 2 6 cm deep x 5 cm wide soil cores obtained from near the base of a Q. rubra individuals, with 6 sampled plots per site. Plots were located approximately 40 m apart along a linear transect to be at a cluster of Q. rubra individuals. All 14 sites were visited twice in the growing season of 2022: between June 1st and June 21st, and between July 5th and July 21st. Root traits sampled include average diameter, root tissue density, specific root length, branching intensity, and specific respiration rate. A 1 mm diameter limit cut-off was used. These traits were measured in the field (respiration rates) or from output from RhizoVision Explorer image analysis. Traits are associated with the smaller fine root sample used for respiration measurement in the field (~2 g dry weight). Fine root biomass was also obtained by removing all remaining fine roots in the core, drying, and weighing, and then was multiplied by weight-normalized respiration rates to obtain estimates of fine root ecosystem respiration. This data package is complete, but will be associated with data from 4 sites revisited in 2023 to obtain repeat fine root trait measurements and fungal community community metrics.
Microclimate data associated with green infrastructure in Lancaster Pennsylvania, 2022
Green stormwater infrastructure (GSI) is being increasingly implemented as a stormwater management practice. A key reason for its popularity is the potential for co-benefits, such as heat mitigation, in addition to stormwater management functions. This data is the result of field investigation of heat patterns around GSI in Lancaster, Pennsylvania, providing some of the first ever direct measurements of microclimate and thermal comfort near GSI. During summer 2022, we collected data along transects at 10 rain gardens. Microclimate variables were quantified using a Kestrel 5400 Heat Stress Tracker and were used to calculate metrics that represent heat stress experienced by a human such as wet bulb globe temperature (WBGT) and mean radiant temperature (MRT). Measurements were also made at nearby impervious surface and lawn reference sites.
The 2021 Freshwater Oil Spill Remediation Study (FOReSt), assessing the use of enhanced Monitored Natural Recovery (eMNR) of conventional heavy crude oil spills conducted in freshwater shoreline enclosures at the IISD Experimental Lakes Area, ON, Canada from 2021 to 2022.
The following package includes data from the 2021 Freshwater Oil spill Remediation Study (FOReSt) at the IISD Experimental Lakes Area studying the use of enhanced monitored natural recovery (eMNR) as a secondary remediation method for conventional heavy crude oil spills in freshwater shoreline enclosures. This package includes data tables on polycyclic aromatic compound chemistry in water and sediments, basic water quality, nutrient chemistry monitored in the experimental and reference enclosures, and lake reference sites over the duration of the study. As well as tables detailing enclosure metrics (depth), tritium chemistry, and a treatment key. Data included in this package was first collected and used in the paper by Stanley et al., titled Rapid Chemical Remediation of Freshwater Enclosures Treated with Conventional Heavy Crude Oil Spills Followed by Enhanced Monitored Natural Recovery
Survival, growth and biomass estimates of two dominant palmetto species of south-central Florida from 1981 - 2022, ongoing at 5-year intervals
This data package is comprised of three datasets all pertaining to two dominant palmetto species, Serenoa repens and Sabal etonia, at Archbold Biological Station in south-central Florida. The first dataset, palmetto_data, contains survival and growth data across multiple years, habitats and experimental treatments. The second dataset, seedlings_data, follows the fate of marked putative palmetto seedlings in the field to assess survivorship and growth. The final dataset, harvested_palmetto_data, contains size data and estimated dry mass (biomass in grams) of 33 destructively harvested palmetto plants (17 S. repens and 16 S. etonia) of varying sizes and across habitats. Thirty-two of these were used to calculate estimated biomass, using regression equations, for palmettos sampled in the palmetto_data. Below we summarize experimental setup and data collected for each dataset. Palmetto data Demographic data were collected as three separate components. The first component compared growth among habitats. Starting in 1981, equal numbers of both palmetto species were marked across scrubby flatwoods (oak scrub) and flatwoods habitats (3 sites per habitat) for a total of 240 marked plants. These habitats had not burned within the last decade, but historically had experienced a natural fire return interval of 5 - 20 years prior to this studies initiation. The second component added an additional 400 palmettos (200 of each species), which were marked in sand pine scrub (n = 200) in 1985 and sandhill habitat (n = 200) in 1989 on Archbold's Red Hill. At the time of this project's initiation, all Red Hill management units were last burned in 1927 and were considered long unburned. Part of Archbold's management plan included restoring fire into some management units while leaving others long unburned to serve as reference units. Therefore, for our second component, we were able to create a 2x2 factorial design using habitat types on Red Hill and fire management as factors, with 100
Model Simulations of The Effects of Shifts in High-frequency Weather Variability (No Long-term Weather Trend) Control Carbon Loss from Land to the Atmosphere, Toolik Lake, Alaska, 2022-2122
Climate change is increasing extreme weather events, but effects on high-frequency weather variability and the resultant impacts on ecosystem function are poorly understood. We assessed ecosystem responses of arctic tundra to changes in day-to-day weather variability using a biogeochemical model and stochastic simulations of daily temperature, precipitation, and light. Changes in weather variability altered ecosystem carbon, nitrogen, and phosphorus stocks and cycling rates. Some responses of processes (e.g., respiration) were inconsistent with expectations, indicating that whole-ecosystem interactions and feedbacks moderate or even reverse responses to weather variability. More weather variability led to greater carbon losses from land to atmosphere, and less variability led to higher carbon sequestration on land. The magnitude of response to weather variability was similar to that predicted from climate mean trend effects. This dataset consists of the MEL parameter file, driver files and output files for simulations without a long term weather trend.
Model Simulations of The Effects of Shifts in High-frequency Weather Variability (With a Long-term Trend) on Carbon Loss from Land to the Atmosphere, Toolik Lake, Alaska, 2022-2122
Climate change is increasing extreme weather events, but effects on high-frequency weather variability and the resultant impacts on ecosystem function are poorly understood. We assessed ecosystem responses of arctic tundra to changes in day-to-day weather variability using a biogeochemical model and stochastic simulations of daily temperature, precipitation, and light. Changes in weather variability altered ecosystem carbon, nitrogen, and phosphorus stocks and cycling rates. Some responses of processes (e.g., respiration) were inconsistent with expectations, indicating that whole-ecosystem interactions and feedbacks moderate or even reverse responses to weather variability. More weather variability led to greater carbon losses from land to atmosphere, and less variability led to higher carbon sequestration on land. The magnitude of response to weather variability was similar to that predicted from climate mean trend effects. This dataset consists of the MEL parameter file, driver files and output files for simulations with a long-term weather trend.
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.