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10,553 results for “measurements”
University of Kansas Field Station: Forest demography, 1980 – 2015. On ten study plots established on three management units all live trees with a dbh > 7.5 cm (3 in) were identified to species, measured, and tagged. Trees were initially measured in 1980/1981 and re-measured in three successive time periods: 1993/95; 2002/03; and 2014/15. Trees will be measured again in 2025/26.
In 1980 researchers at the University of Kansas initiated a long-term experiment monitoring the composition of oak-hickory forest communities at the University’s field station near Lawrence, Kansas. The purpose of the study was to determine how forest species composition varied temporally across distinct habitats that varied in topography, elevation, sun exposure, management history and successional stage. Ten permanent sites were sampled approximately each decade with data collection periods of 1980/81, 1993/95, 2002/03, and 2014/15. Trees with a minimum diameter at breast height (dbh) of ≥ 7.5 cm were tagged, identified to species and measured. Trees will be measured again in 2025/26.
Water quality measurements, stream order, channel slope and hydraulic equations of conterminous USGS sites: 1919-2009.
Streams and rivers emit petagrams of CO2 yet there is little known about how discharge (Q) variability impacts stream CO2 at broad scales. Herein, we compiled historical water quality (including pH, alkalinity and temperature) measurements for conterminous USGS sites and coupled them with daily Q for this analysis (the water_quality.csv dataset, 10,822 sites). Based on this dataset, NHDplus channel slopes (NHDplus_slopeSO.csv, 24,764 sites) and hydraulic geometry equations (lm_vQ.csv, 12,854 sites), we calculated partial pressure of dissolved CO2 (pCO2), gas transfer velocity (k) and CO2 effluxes (F) for a total of 813 USGS sites across conterminous US. We derived hydrologic responses (log-linear regressions) for pCO2, k and F versus Q at each site and explored how these responses varied across stream order and different regions. Ancillary datasets provided coordinates (coor_sites.xls), hydrologic unit code (HUC.csv), and watershed area of conterminous USGS sites (watersheds_area.csv).
Temperature Measurements of Southern California Deserts 2022.
The following data was recorded at various desert field sites within Southern California. Data was collected between May 2022 and June 2022. 3 different deserts; Carrizo, Cuyama, and Mojave, were tested. Temperature pendants were deployed for 30 days and recorded local temperature at 1 hour intervals.
LAGOS-NE – Lake nutrient chemistry and geospatial data to measure spatial structure of ecosystem properties in a 17-state region of the U.S.
This dataset includes data for the lake water quality and geospatial variables that describe climate, hydrology, land use land cover, and lake characteristics that were used to study spatial structure in lake properties at the sub-continental scales (Lapierre et al. Quantifying spatial structure to improve understanding of the relationships between climate, landscape, and lake ecosystem properties, to be submitted to Ecology). All observations came from LAGOS-NELIMNO v. 1.054.1 and LAGOS-NEGEO v. 1.03 (LAke multi-scaled GeOSpatial and temporal database), an integrated database of lake ecosystems (Soranno et al. 2015). LAGOS-NE contains a complete census of lakes great than or equal to 4 ha with corresponding geospatial information for a 17-state region of the U.S., and a subset of the lakes has observational data on morphometry and chemistry. Approximately 54 different sources of data were compiled for the LAGOS-NELIMNO v. 1.054.1 dataset and were mostly generated by government agencies (state, federal, tribal) and universities. In this analysis, we compiled lake water quality data from the summer stratified season (June 15-September 15) in the most recent 10 years of data included in LAGOS-NELIMNO v. 1.054.1 (2002-2011). We report the median total nitrogen, total phosphorus, secchi depth, and chlorophyll values for each lake, which was calculated as the grand median of each yearly median value. We also include data for lake and landscape characteristics including variables related to lake morphometry, climate, hydrology, atmospheric deposition, land use and land cover.
Nutrient and stoichiometric time series measurements of decomposing coarse detritus in freshwaters worldwide from literature published between 1976-2020.
This data publication is a database of published estimates of nitrogen, phosphorus, and carbon content of decomposing coarse detritus though time in freshwater ecosystems worldwide. Nutrient content measurements are paired with estimates of detrital mass loss within decomposition time series (i.e., defined cohorts of decomposing material through time) with the goal of understanding patterns and drivers of temporal elemental dynamics of freshwater detritus. A systematic literature search for aquatic decomposition experiments conducted on 29 April 2020 generated 580 records (after trimming for duplicates and obvious relevance). From this literature pool, we extracted 810 decomposition time series and associated environmental data (e.g., temperature, water quality, detrital characteristics). Time series included in this synthesis include a range of detritus types (including terrestrial and aquatic plant material, carcasses, dung, and veneers), ecosystems (including streams, lakes, rivers, and wetlands), and settings (including natural ecosystems, field mesocosms, and laboratory microcosms).
Measurements of ethylene production (using the acetylene reduction assay) as a proxy for nitrogen fixation of epiphytes on seagrass in West Falmouth Harbor during July from 2005 through 2019.
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 2000’s. As part of a long-term study into the effects of this nitrogen enrichment, we have measured nitrogen fixation rates of seagrass-associated epiphytes using the acetylene reduction technique. Samples were taken annually in July at two sites, one in the well-flushed outer basin (OH) and one in the inner basin closer to the dominant groundwater N source (Snug Harbor, SH). Additional data are presented in 2019 at 18 sites spatially distributed through the seagrass bed to assess spatial heterogeneity. Individual replicate data are presented. These data are in support of a manuscript submitted to the journal Biogeochemistry by Marino et al, submitted for publication (12/2022).
Measurements of water column chemistry taken hourly over 24-hour periods at three sites in West Falmouth Harbor from 2006 to 2019
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 2000’s. As part of a long-term study into the effects of this nitrogen enrichment, we have been measuring water chemistry at stations throughout the harbor to examine nutrient concentrations along the gradient from the highest loaded areas of the site to the most well-flushed. Water samples were taken hourly over 24-hour periods at 3 stations between 2006 and 2019. Due to covid restrictions on field and laboratory work, samples were not collected in 2020-2021; sample collection resumed in 2022 and data will be added after analysis. One station is in the well-flushed outer basin (OH) and one in the inner basin closer to the dominant groundwater N source (Snug Harbor, SH). These two were sampled at least once per year between 2006 and 2019. In two years, samples in the OH were taken at a location approximately 140m from the long-term site from this dataset. Those data can be accessed at doi:10.6073/pasta/73408abf801827966041c219f4222c1f. A third station is in the middle between the two, and was sampled in 2016 and 2018. Samples were processed for ammonium, phosphate, nitrate + nitrite, total nitrogen, and total phosphorus. On some dates, additional samples were run for silicate and chlorophyll. 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).
Measurements of soil nutrient leaching from agricultural depressions and uplands in Iowa, USA
We measured the leaching of nitrate, ammonium, and phosphorus in resin lysimeters installed along topographic transects from depressions to uplands within agricultural fields in Iowa, USA. Lysimeters were each installed for approximately one year. Crops included conventional corn and soybean, corn and soybean with a winter rye cover crop, and corn and soybean fields where depressions were planted with miscanthus. Measurements were made during 2018, 2019, and 2020, although not all transects could be measured each year. There were a total of 28 transect-years that included data from 734 individual resin lysimeters.
Meteorological Field Measurements in Yahara River Watershed
These data are collected to support the Water Sustainability and Climate of the Yahara River Watershed Project. Meteorological measurements include air temperature, relative humidity, wind speed, gust wind speed, solar radiation, dew point temperature, and rainfall. Weather stations were installed at 3 locations across the Yahara Watershed at the UW Arboretum, the City of Madisons Cherokee Park, and Waunakee Marsh State Wildlife Area. These data are being collected to observe differences in how water and energy are processed under different land cover types and to create calibration datasets for a separate project goal of creating an agro-biophysical model of the entire Yahara River watershed.
Leaf angle measurements for temperate tree species in northeastern USA
Leaf angle distribution (LAD) measurements were made during the growing season in 2021 at the Harvard Forest in Petersham, MA, USA, and in 2022 at the Thompson Farm Earth Systems Observatory in Durham, NH, USA. At both sites, a level-calibrated digital angle tool was used to measure LAD in upper canopy foliage of common northeastern temperate tree species accessed using a mobile canopy lift. Additionally, at Thompson Farm, measurements were made at multiple heights to characterize differences of LAD in high, middle, and low canopy positions. Here, we have published those measurements, including a summary table of species average leaf angles and calculated parameters for fitted beta distributions. Processing scripts can be made available upon request to the authors. Additionally, leaf chemical, physical, structure, optical and physiological traits have been measured at these site as well as canopy scale measures of structure and UAV-based spectral, thermal, and lidar imagery.
High-frequency light attenuation measurements in 35 lakes: companion data from "Coefficients in Taylor’s Law increase with the time scale of water clarity measurements in a global suite of lakes"
Identifying the scaling rules describing ecological patterns across time and space is a central challenge in ecology. Taylor’s Law of fluctuation scaling, which states that the variance of a population is proportional to a positive power of the mean, has been widely observed in population dynamics and characterizes variability in multiple scientific domains. However, it is unclear if this phenomenon accurately describes ecological patterns across many orders of magnitude in time, and therefore links otherwise disparate observations. This dataset uses light attenuation observations from 10,531 days of high-frequency measurements in 35 globally distributed lakes to test this unknown. We focus on water clarity as an integrative ecological characteristic that responds to both biotic and abiotic drivers. We provide documentation that variations in ecological measurements across diverse sites and temporal scales exhibit variance patterns consistent with Taylor’s Law, and that model coefficients increase in a predictable yet non-linear manner with decreasing observation frequency.
Extreme Drought in Grasslands Experiment (EDGE): High frequency measurements from the northern Chihuahuan Desert site, Sevilleta National Wildlife Refuge, NM, USA (2013-2023)
The Extreme Drought in Grasslands Experiment (EDGE) is distributed across six representative grassland ecosystems of the central United States. EDGE serves as an important research platform for understanding the resistance and resilience of these grassland ecosystems to extreme prolonged drought as well as to changes in precipitation seasonality. This data package contains high-frequency environmental sensor measurements from the northern Chihuahuan Desert site, dominated by black grama (Bouteloua eriopoda), located in the Sevilleta National Wildlife Refuge in central New Mexico.
Extreme Drought in Grasslands Experiment (EDGE): High frequency measurements from the southern Great Plains site, Sevilleta National Wildlife Refuge, NM, USA (2013-2023)
The Extreme Drought in Grasslands Experiment (EDGE) is distributed across six representative grassland ecosystems of the central United States. EDGE serves as an important research platform for understanding the resistance and resilience of these grassland ecosystems to extreme prolonged drought as well as to changes in precipitation seasonality. This data package contains high-frequency environmental sensor measurements from the southern Great Plains site, dominated by blue grama (Bouteloua gracilis), located in the Sevilleta National Wildlife Refuge in central New Mexico.
Tree species identity, diameter and qualitative canopy health measurements (full, partial or dead) from 2005 to 2023 on 12 experimental oak loss plots in Black Rock Forest, NY.
Black Rock Forest established a series of 12, 0.56 ha plots in 2005 to assess impacts of the loss of tree in the genus Quercus on the forest ecosystem (entitled the Future of Oak Forests experiment). Three trunk girdling treatments, with control plots were instituted in 2008. Each plot also contained an ~10m by ~15m deer exclosure to assess the impact of herbivory post-disturbance. Trees were measured twice per year from 2008 to 2013 (except 2009 when trees were measured once) and once per year from 2014 to 2023. Data include tree species identity, diameter at breast height (DBH), canopy health (a qualitative assessment of approximate cover as full, partial or dead), presence/absence of sprouts, and location within the plot. All live trees equal to or larger than 2.5 cm DBH are included in the dataset.
Sevilleta Field Station Meteorological Network (SevMET): High frequency measurements from the Black Butte Meteorological Station (BLBT), Sevilleta National Wildlife Refuge, NM, USA, 2024-ongoing.
The Sevilleta Field Station Meteorological Network (SevMET) is a spatially distributed, long-term climate monitoring network established to enhance and expand climate monitoring across a variety of dryland ecosystems (e.g., grasslands, shrublands, woodlands) within the Sevilleta National Wildlife Refuge in central New Mexico. Ecosystem processes in drylands are strongly regulated by climatic drivers that are highly variable in space and time, both within and among years. Therefore, accurate measurement of environmental variables at high spatial and temporal resolution is fundamental to understanding biophysical processes in these ecosystems. SevMET consists of fifteen standardized research-grade weather stations located across multiple dryland ecosystem types (e.g., grasslands, shrublands, woodlands) representative of the southwestern US. Stations continuously measure a standard suite of meteorological variables at five-minute intervals, including air temperature, relative humidity, precipitation, photosynthetically active radiation, incoming shortwave radiation, wind speed and direction, dew point, vapor pressure, and, at a subset of stations, barometric pressure. Stations also measure a suite of soil parameters (bulk electrical conductivity, dielectric permittivity, temperature, and volumetric water content) at six depths (5, 10, 20, 30, 40, and 50 cm) below the ground surface using 1-2 integrated soil profilers. Additionally, phenocams at each station capture images at thirty-minute intervals during daylight hours. This data package contains high-frequency meteorological measurements from the Black Butte Meteorological Station (BLBT). Phenocam images can be accessed through the PhenoCam Network at: https://phenocam.nau.edu/webcam/sites/sevmetblbt/. These data complement and extend meteorological data recorded by an adjacent station (Met54), accessible at: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sev&identifier=1.
Sevilleta Field Station Meteorological Network (SevMET): High frequency measurements from the Bronco Well Meteorological Station (BRWL), Sevilleta National Wildlife Refuge, NM, USA, 2024-ongoing.
The Sevilleta Field Station Meteorological Network (SevMET) is a spatially distributed, long-term climate monitoring network established to enhance and expand climate monitoring across a variety of dryland ecosystems (e.g., grasslands, shrublands, woodlands) within the Sevilleta National Wildlife Refuge in central New Mexico. Ecosystem processes in drylands are strongly regulated by climatic drivers that are highly variable in space and time, both within and among years. Therefore, accurate measurement of environmental variables at high spatial and temporal resolution is fundamental to understanding biophysical processes in these ecosystems. SevMET consists of fifteen standardized research-grade weather stations located across multiple dryland ecosystem types (e.g., grasslands, shrublands, woodlands) representative of the southwestern US. Stations continuously measure a standard suite of meteorological variables at five-minute intervals, including air temperature, relative humidity, precipitation, photosynthetically active radiation, incoming shortwave radiation, wind speed and direction, dew point, vapor pressure, and, at a subset of stations, barometric pressure. Stations also measure a suite of soil parameters (bulk electrical conductivity, dielectric permittivity, temperature, and volumetric water content) at six depths (5, 10, 20, 30, 40, and 50 cm) below the ground surface using 1-2 integrated soil profilers. Additionally, phenocams at each station capture images at thirty-minute intervals during daylight hours. This data package contains high-frequency meteorological measurements from the Bronco Well Meteorological Station (BRWL). Phenocam images can be accessed through the PhenoCam Network at: https://phenocam.nau.edu/webcam/sites/sevmetbrwl/. These data complement and extend meteorological data recorded by an adjacent station (Met45), accessible at: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sev&identifier=1.
Sevilleta Field Station Meteorological Network (SevMET): High frequency measurements from the Burris Well Meteorological Station (BUWL), Sevilleta National Wildlife Refuge, NM, USA, 2024-ongoing.
The Sevilleta Field Station Meteorological Network (SevMET) is a spatially distributed, long-term climate monitoring network established to enhance and expand climate monitoring across a variety of dryland ecosystems (e.g., grasslands, shrublands, woodlands) within the Sevilleta National Wildlife Refuge in central New Mexico. Ecosystem processes in drylands are strongly regulated by climatic drivers that are highly variable in space and time, both within and among years. Therefore, accurate measurement of environmental variables at high spatial and temporal resolution is fundamental to understanding biophysical processes in these ecosystems. SevMET consists of fifteen standardized research-grade weather stations located across multiple dryland ecosystem types (e.g., grasslands, shrublands, woodlands) representative of the southwestern US. Stations continuously measure a standard suite of meteorological variables at five-minute intervals, including air temperature, relative humidity, precipitation, photosynthetically active radiation, incoming shortwave radiation, wind speed and direction, dew point, vapor pressure, and, at a subset of stations, barometric pressure. Stations also measure a suite of soil parameters (bulk electrical conductivity, dielectric permittivity, temperature, and volumetric water content) at six depths (5, 10, 20, 30, 40, and 50 cm) below the ground surface using 1-2 integrated soil profilers. Additionally, phenocams at each station capture images at thirty-minute intervals during daylight hours. This data package contains high-frequency meteorological measurements from the Burris Well Meteorological Station (BUWL). Phenocam images can be accessed through the PhenoCam Network at: https://phenocam.nau.edu/webcam/sites/sevmetbuwl/. These data complement and extend meteorological data recorded by an adjacent station (Met50), accessible at: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sev&identifier=1.
Sevilleta Field Station Meteorological Network (SevMET): High frequency measurements from the Contreras Meteorological Station (CONT), Sevilleta National Wildlife Refuge, NM, USA, 2024-ongoing.
The Sevilleta Field Station Meteorological Network (SevMET) is a spatially distributed, long-term climate monitoring network established to enhance and expand climate monitoring across a variety of dryland ecosystems (e.g., grasslands, shrublands, woodlands) within the Sevilleta National Wildlife Refuge in central New Mexico. Ecosystem processes in drylands are strongly regulated by climatic drivers that are highly variable in space and time, both within and among years. Therefore, accurate measurement of environmental variables at high spatial and temporal resolution is fundamental to understanding biophysical processes in these ecosystems. SevMET consists of fifteen standardized research-grade weather stations located across multiple dryland ecosystem types (e.g., grasslands, shrublands, woodlands) representative of the southwestern US. Stations continuously measure a standard suite of meteorological variables at five-minute intervals, including air temperature, relative humidity, precipitation, photosynthetically active radiation, incoming shortwave radiation, wind speed and direction, dew point, vapor pressure, and, at a subset of stations, barometric pressure. Stations also measure a suite of soil parameters (bulk electrical conductivity, dielectric permittivity, temperature, and volumetric water content) at six depths (5, 10, 20, 30, 40, and 50 cm) below the ground surface using 1-2 integrated soil profilers. Additionally, phenocams at each station capture images at thirty-minute intervals during daylight hours. This data package contains high-frequency meteorological measurements from the Burris Well Meteorological Station (BUWL). Phenocam images can be accessed through the PhenoCam Network at: https://phenocam.nau.edu/webcam/sites/sevmetcont/.
Sevilleta Field Station Meteorological Network (SevMET): High frequency measurements from the Cerro Montoso Meteorological Station (CRMT), Sevilleta National Wildlife Refuge, NM, USA, 2024-ongoing.
The Sevilleta Field Station Meteorological Network (SevMET) is a spatially distributed, long-term climate monitoring network established to enhance and expand climate monitoring across a variety of dryland ecosystems (e.g., grasslands, shrublands, woodlands) within the Sevilleta National Wildlife Refuge in central New Mexico. Ecosystem processes in drylands are strongly regulated by climatic drivers that are highly variable in space and time, both within and among years. Therefore, accurate measurement of environmental variables at high spatial and temporal resolution is fundamental to understanding biophysical processes in these ecosystems. SevMET consists of fifteen standardized research-grade weather stations located across multiple dryland ecosystem types (e.g., grasslands, shrublands, woodlands) representative of the southwestern US. Stations continuously measure a standard suite of meteorological variables at five-minute intervals, including air temperature, relative humidity, precipitation, photosynthetically active radiation, incoming shortwave radiation, wind speed and direction, dew point, vapor pressure, and, at a subset of stations, barometric pressure. Stations also measure a suite of soil parameters (bulk electrical conductivity, dielectric permittivity, temperature, and volumetric water content) at six depths (5, 10, 20, 30, 40, and 50 cm) below the ground surface using 1-2 integrated soil profilers. Additionally, phenocams at each station capture images at thirty-minute intervals during daylight hours. This data package contains high-frequency meteorological measurements from the Cerro Montoso Meteorological Station (CRMT). Phenocam images can be accessed through the PhenoCam Network at: https://phenocam.nau.edu/webcam/sites/sevmetcrmt/. These data complement and extend meteorological data recorded by an adjacent station (Met42), accessible at: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sev&identifier=1.
Sevilleta Field Station Meteorological Network (SevMET): High frequency measurements from the Deep Well Meteorological Station (DPWL), Sevilleta National Wildlife Refuge, NM, USA, 2024-ongoing.
The Sevilleta Field Station Meteorological Network (SevMET) is a spatially distributed, long-term climate monitoring network established to enhance and expand climate monitoring across a variety of dryland ecosystems (e.g., grasslands, shrublands, woodlands) within the Sevilleta National Wildlife Refuge in central New Mexico. Ecosystem processes in drylands are strongly regulated by climatic drivers that are highly variable in space and time, both within and among years. Therefore, accurate measurement of environmental variables at high spatial and temporal resolution is fundamental to understanding biophysical processes in these ecosystems. SevMET consists of fifteen standardized research-grade weather stations located across multiple dryland ecosystem types (e.g., grasslands, shrublands, woodlands) representative of the southwestern US. Stations continuously measure a standard suite of meteorological variables at five-minute intervals, including air temperature, relative humidity, precipitation, photosynthetically active radiation, incoming shortwave radiation, wind speed and direction, dew point, vapor pressure, and, at a subset of stations, barometric pressure. Stations also measure a suite of soil parameters (bulk electrical conductivity, dielectric permittivity, temperature, and volumetric water content) at six depths (5, 10, 20, 30, 40, and 50 cm) below the ground surface using 1-2 integrated soil profilers. Additionally, phenocams at each station capture images at thirty-minute intervals during daylight hours. This data package contains high-frequency meteorological measurements from the Deep Well Meteorological Station (DPWL). Phenocam images can be accessed through the PhenoCam Network at: https://phenocam.nau.edu/webcam/sites/sevmetdpwl/. These data complement and extend meteorological data recorded by an adjacent station (Met40), accessible at: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sev&identifier=1.
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.