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6,175 results for “Composition”
Data from: Analysing small insect glands with UV-LDI MS: high-resolution spatial analysis reveals the chemical composition and use of the osmeterium secretion in Themira superba (Sepsidae: Diptera)
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Data from: Independent sources of condition dependency and multiple pathways determine a composite trait: lessons from carotenoid-based plumage colouration
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Data for: Causes and consequences of variation in diet composition of nestling Canada jays
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Compiled trace element compositions for magmatic zircons from I-type granitoids, S-type granitoids and TTGs, and detrital zircons
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How climate impacts the composition of wolf killed-elk in northern Yellowstone National Park
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Arthropod Trophic Group Composition Data
*We conducted a field study to test the hypothesis that creosotebush (Larrea tridentata) shrubs growing in naturally nutrient-rich sites had better quality foliage and supported greater populations of foliage arthropods than shrubs growing in nutrient-poor sites. This is data for foliage arthropods sampled from LVAR creosotebush shrubs. Sampling was done in April of 1985 and 1986. Shrubs were sampled from 5 separate sites designated A-E. 10 shrubs of 3 different types, R=random, H=high quality, L=low quality were sampled at each site. Total numbers of taxa and individuals of each major trophic group, herbivores, predators, omnivores, from each of the 30 shrubs/site are listed.
Sources of oceanic freshwater content along the western Antarctic Peninsula (PAL-LTER Study Region) determined by the stable isotope composition (d18O) of seawater.
The oceanic distribution of d18O is determined largely by the same processes that control salinity. Surface d18O reflects the magnitude and spatial distribution of freshwater inputs, and it is a conservative tracer in the ocean interior. The great benefit of d18O is obtained from the circumstances under which it exhibits behavior different to that of salinity. One such circumstance derives from the salinity and d18O values in precipitation, with salinity being constant with latitude (typically zero), while in general d18O in precipitation becomes progressively isotopically lighter toward the poles. This results in glacial ice (which derives from high-latitude precipitation) being very isotopically light, enabling d18O to be a useful tracer of glacial discharge to the ocean (e.g., Schlosser et al. 1990; Weiss et al. 1979). Another difference occurs in regions influenced by sea ice, which greatly affects salinity during its formation/melt cycle but has only minimal impact on d18O. This decoupling of the two tracers allows them to be used in tandem to quantitatively separate freshwater inputs from sea ice melt and those from meteoric sources (precipitation plus glacial discharge). For this, a simple three-endmember mass balance can be used. For details please see Meredith, M. P., H. J. Venables, A. Clarke, H. W. Ducklow, M. Erickson, M. J. Leng, J. T. M. Lenaerts, and M. R. van den Broeke. 2013. The freshwater system west of the Antarctic Peninsula: Spatial and temporal changes. Journal of Climate 26:1669-1684.
Conifer Needle Pigment Composition, Niwot Ridge, Colorado, USA, 2017-2018
This dataset provides concentrations of pigments in pine and spruce needle tissues collected at the Niwot Ridge AmeriFlux Core site (US-NR1) near Nederland, Colorado, USA, during the summers of 2017 and 2018. Pigments measured included Chlorophyll A and B, Violaxanthin, Antheraxanthin, Zeaxanthin, Neoxanthin, Lutein, and beta-Carotene. Measurements were made on sun foliage from two canopy-access towers near the main flux tower, and in the laboratory on branches collected from those towers, every 4-8 weeks over the annual cycle. Due to canopy structure, a limited number of trees were accessible from the towers, preventing extensive replication. Pigments were extracted in acetone and analyzed by HPLC. The measurements were made to evaluate seasonal changes associated with the down-regulation of photosynthesis.
ISLSCP II UNH/GRDC Composite Monthly Runoff
The University of New Hampshire (UNH)/Global Runoff Data Centre (GRDC) composite runoff data combines simulated water balance model runoff estimates derived from climate forcing with monitored river discharge. It can be viewed as a data assimilation applied in a water balance model context (conceptually similar to the commonly used 4DDA techniques used in meteorological modeling). Such a data assimilation scheme preserves the spatial specificity of the water balance calculations while constrained by the more accurate discharge measurement. There are 11 data files in this data set and 1 changemap file which shows the differences between the ISLSCP II land/water mask and the original data set.
NASA Web-Enabled Landsat Data Alaska 30m Composite Pixel Center Lat/Longs V001
WELDAKLL.015 was decommissioned on December 2, 2019. Users are encouraged to use the improved monthly Global Web-Enabled Landsat Data (GWELD) [Version 3](https://doi.org/10.5067/MEaSUREs/GWELD/GWELDMO.003), [3.1](https://doi.org/10.5067/MEaSUREs/GWELD/GWELDMO.031), and [3.2](https://doi.org/10.5067/MEaSUREs/GWELD/GWELDMO.032) datasets.The NASA Web-Enabled Landsat Data (WELD) Alaska Latitude Longitude (LL) products are defined with 30 meter (m) composite pixel of the center latitude/longitude point. The NASA WELD data contain a range of values for the minimum/maximum latitude and longitude points. The LL products were created to account for the actual center pixel latitude and longitude points.WELD systematically generated 30 m composited Landsat Enhanced Thematic Mapper Plus (ETM+) mosaics of the United States and Alaska from 2002 to 2012 to provide consistent data for deriving land cover as well as geophysical and biophysical products for regional assessments of surface dynamics for effective study of Earth system function. WELDAKLL is distributed in Hierarchical Data Format 4 (HDF4).The WELD project is funded by the National Aeronautics and Space Administration (NASA) and is a collaboration between the United States Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center and the South Dakota State University (SDSU) Geospatial Sciences Center of Excellence (GSCE). Known Issues* WELD Version 1.5 known issues can be found in the WELD Version 1.5 User Guide.Improvements/Changes from Previous Version* Version 1.5 is the original version.
NASA Web-Enabled Landsat Data CONUS 30m Composites over Annual Periods V001
WELDUSYR.015 was decommissioned on December 2, 2019. Users are encouraged to use the improved yearly Global Web-Enabled Landsat Data (GWELD) [Version 3](https://doi.org/10.5067/MEaSUREs/GWELD/GWELDYR.003), [3.1](https://doi.org/10.5067/MEaSUREs/GWELD/GWELDYR.031), and [3.2](https://doi.org/10.5067/MEaSUREs/GWELD/GWELDYR.032) datasets.NASA’s Web-Enabled Landsat Data (WELD) are generated from composited 30 meter (m) Landsat Enhanced Thematic Mapper Plus (ETM+) mosaics of the United States and Alaska from 2002 to 2012. These products provide consistent data to derive land cover, geophysical, and biophysical products for regional assessments of surface dynamics for effective study of Earth system function. The WELD Conterminous (CONUS) United States Annual (WELDUSYR) products include Top of Atmosphere (TOA) Reflectance and Brightness Temperature, along with the Normalized Difference Vegetation Index (NDVI) generated from Band 3 and Band 4 TOA Reflectance. WELDUSYR is distributed in Hierarchical Data Format 4 (HDF4).The WELDUSYR products include the preceding year’s December through the current year’s November. For example, for the year 2007, the product includes data from December 1, 2006, through November 30, 2007.The WELD project is funded by the National Aeronautics and Space Administration (NASA) and is a collaboration between the United States Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center and the South Dakota State University (SDSU) Geospatial Sciences Center of Excellence (GSCE). Known Issues* WELD Version 1.5 known issues can be found in the WELD Version 1.5 User Guide.Improvements/Changes from Previous Version* Version 1.5 is the original version.
BOREAS RSS-07 Regional LAI and FPAR Images From Ten-Day AVHRR-LAC Composites
The BOREAS RSS-07 team focused their efforts on developing and validating procedures and algorithms that would allow the retrieval of LAI from remotely sensed vegetation indices. This data set contains images of LAI and FPAR that were produced from the AVHRR Level-4c ten-day composite NDVI images produced at CCRS for the three summer IFCs in 1994. The algorithms were developed based on ground measurements and Landsat TM images (Chen and Cihlar, 1996; Chen, 1996b). The data are provided in binary image format files. Companion files include example thumbnail images that may be viewed and the image data files downloaded using a convenient viewer utility.
BASIN TCP Stable Isotope Composition of CO2 in Terrestrial Ecosystems
This data set reports stable isotope ratio data of CO2 (13C/12C and 18O/16O) associated with photosynthetic and respiratory exchanges across the biosphere-atmosphere boundary. Measurements were made at selected AmeriFlux sites including Harvard Forest, Howland Forest, Rannells Flint Hills Prairie, Niwot Ridge Forest, and the Wind River Canopy Crane Site, which span the dominant ecosystem types of the United States. These data were collected periodically from 2001 through 2004 and are available as an ASCII comma separated file.The goal of this Terrestrial Carbon Processes (TCP) project is to better capture isotopic effects of ecosystem-atmosphere interaction at diurnal, seasonal and interannual time scales by long-term monitoring 13C of CO2 exchange with the atmosphere at weekly intervals. Photosynthesis and respiration in terrestrial ecosystems have opposite effects on diurnal and seasonal patterns on atmospheric CO2 concentration and isotope ratios. This isotopic variation contains information about the functioning of different terrestrial ecosystems.
BOREAS Level-4b AVHRR-LAC Ten-Day Composite Images: At-Sensor Radiance
The BOREAS Staff Science Satellite Data Acquisition Program focused on providing the research teams with the remotely sensed satellite data products they needed to compare and spatially extend point results. MRSC and BORIS personnel acquired, processed, and archived data from the AVHRR instruments on the NOAA-11 and -14 satellites. The AVHRR data were acquired by CCRS and were provided to BORIS for use by BOREAS researchers. These AVHRR level-4b data are gridded, 10-day composites of at-sensor radiance values produced from sets of single-day images. Temporally, the 10-day compositing periods begin 11-Apr-1994 and end 10-Sep-1994. Spatially, the data cover the entire BOREAS region. The data are stored in binary image format files. Companion files include example thumbnail images that may be viewed and the image data files downloaded using a convenient viewer utility.
VIIRS/JPSS1+JPSS2 Hourly Cumulative L3 Global Flood Composite 250m Linear Lat Lon Grid - NRT
The VIIRS/JPSS1+JPSS2 Hourly Cumulative L3 Global Flood Composite 250m Linear Lat Lon Grid Near Real Time (NRT) Product, short-name VCDWDG_L3_NRT provides hourly updated maps of flooding globally. The VCDWDG_L3_NRT product is generated using VIIRS Surface Reflectance (VJ109/VJ209) products as inputs from NOAA-20 and NOAA-21 satellites. The product files are in EOS-HDF5 file format. The VIIRS Near Real-Time Global Flood Product (Collection 2) is processed by NASA's Land, Atmosphere Near real-time Capability for Earth observation (LANCE). The VCDWDG_L3_NRT is currently at Beta 1, under VIIRS collection 2. For more information, visit product page at:https://www.earthdata.nasa.gov/global-flood-product
LBA-ECO LC-15 NDVI Composite Images of the Amazon Basin: 1999-2000
This data set provides Normalized Difference Vegetation Index (NDVI) composite images of the Amazon Basin for the years 1999-2000 at approximately1-km spatial resolution. The images were from the VEGETATION 1 sensor, aboard the SPOT 4 satellite.Ten day composite images were reprocessed through several filters for cloud removal. Monthly NDVI data were used to create five metrics: maximum NDVI, minimum of 6 greenest months, range of NDVI between min and max, mean NDVI dry months, and mean NDVI wet months. There are five GeoTIFF (.tif) files with this data set.
Daytime Earth radiation budget determined from NISTAR and EPIC composites Version 1
Deep Space Climate Observatory (DSCOVR) DSCOVR National Institute of Standards and Technology Advanced Radiometer (NISTAR) was explicitly designed to measure the global daytime radiation budget for an entire hemisphere using active cavity radiometers for three channels: total (0.2 - 100 um), SW (0.2 - 4.0 um), and near-infrared (0.7 - 4.0 um). To derive the Earth Radiation Budget (ERB) from NISTAR measurements, the Short Wave (SW) radiances need to be unfiltered first before they can be subtracted from the total to yield the Long Wave (LW) (4 - 100 um) radiances. Additionally, the Earth's surface and atmosphere are anisotropic reflectors and emitters, resulting in a relatively complex variation of radiance leaving the Earth as a function of viewing and illumination. Converting radiance to flux requires using angular distribution models (ADMs) to account for the emittance and reflectance anisotropies. The anisotropies are characterized for all Earth Polychromatic Imaging Camera (EPIC) pixels by using the Clouds and the Earth's Radiant Energy System (CERES) empirical angular distribution models (ADMs), which are functions of scene types which are defined using many variables including surface type, cloud amount, cloud phase, and optical depth, and water vapor. EPIC composite product is used to provide accurate scene-type information. The EPIC composites are generated from cloud property retrievals from Low Earth Orbit/Geostationary Equatorial Orbit (LEO/GEO) imagers mapped into the EPIC pixels. The EPIC composite also includes ancillary data (i.e., surface type, snow and ice map, skin temperature, precipitable water, etc.) needed for anisotropic factor selections. The anisotropies at the EPIC-pixel are then used to calculate the global mean SW and LW anisotropic factors, then convert the NISTAR SW and LW radiances to fluxes. This product contains the time series of the daytime Earth radiation budget derived from the NISTAR measurements.
NASA Web-Enabled Landsat Data CONUS 30m Composites over Seasonal Periods V001
WELDUSSE.015 was decommissioned on December 2, 2019. Users are encouraged to use the improved monthly Global Web-Enabled Landsat Data (GWELD) [Version 3](https://doi.org/10.5067/MEaSUREs/GWELD/GWELDMO.003), [3.1](https://doi.org/10.5067/MEaSUREs/GWELD/GWELDMO.031), and [3.2](https://doi.org/10.5067/MEaSUREs/GWELD/GWELDMO.032) datasets.NASA’s Web-Enabled Landsat Data (WELD) are generated from composited 30 meter (m) Landsat Enhanced Thematic Mapper Plus (ETM+) mosaics of the United States and Alaska from 2002 to 2012. The mosaics provide consistent data to derive land cover, geophysical, and biophysical products for regional assessments of surface dynamics for effective study of Earth system function. The Conterminous (CONUS) United States Seasonal (WELDUSSE) product include Top of Atmosphere (TOA) Reflectance and Brightness Temperature, along with the Normalized Difference Vegetation Index (NDVI) generated from Band 3 and Band 4 TOA Reflectance. WELDUSSE is distributed in Hierarchical Data Format 4 (HDF4).In the WELDUSSE products, seasons are defined as follows: Winter: December, January, February Spring: March, April, May Summer: June, July, August Autumn: September, October, NovemberThe WELD project is funded by the National Aeronautics and Space Administration (NASA) and is a collaboration between the United States Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center and the South Dakota State University (SDSU) Geospatial Sciences Center of Excellence (GSCE). Known Issues* WELD Version 1.5 known issues can be found in the WELD Version 1.5 User Guide.Improvements/Changes from Previous Version* Version 1.5 is the original version.
NASA Web-Enabled Landsat Data Alaska 30m Composites over Weekly Periods V001
WELDAKWK.015 was decommissioned on December 2, 2019. Users are encouraged to use the improved monthly Global Web-Enabled Landsat Data (GWELD) [Version 3](https://doi.org/10.5067/MEaSUREs/GWELD/GWELDMO.003), [3.1](https://doi.org/10.5067/MEaSUREs/GWELD/GWELDMO.031), and [3.2](https://doi.org/10.5067/MEaSUREs/GWELD/GWELDMO.032) datasets.NASA’s Web-Enabled Landsat Data (WELD) are generated from composited 30 meter (m) Landsat Enhanced Thematic Mapper Plus (ETM+) mosaics of the United States and Alaska from 2003 to 2012. These mosaics provide consistent data to derive land cover, geophysical, and biophysical products for regional assessments of surface dynamics for effective study of Earth system function. This product includes Top of Atmosphere (TOA) Reflectance and Brightness Temperature, along with the Normalized Difference Vegetation Index (NDVI) generated from Band 3 and Band 4 TOA Reflectance. WELDAKWK is distributed in Hierarchical Data Format 4 (HDF4).The WELD weekly products are defined with respect to each calendar year and as consecutive 7 day products with the following examples defined for the weeks: Week01: January 1 to January 7 Week02: January 8 to January 14 Week52: December 24 to December 30 (non-leap years) Week52: December 23 to December 29 (leap years) Week53: December 31 (non-leap years) Week53: December 30 to December 31 (leap years) The WELD project is funded by the National Aeronautics and Space Administration (NASA) and is a collaboration between the United States Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center and the South Dakota State University (SDSU) Geospatial Sciences Center of Excellence (GSCE). Known Issues* WELD Version 1.5 known issues can be found in the WELD Version 1.5 User Guide.Improvements/Changes from Previous Version* Version 1.5 is the original version.
Oceansat-2 Scatterometer Level 2B Ocean Wind Vectors in 12.5km Slice Composites Version 2
This dataset consists of the version 2 Level 2B science-quality ocean surface wind vector retrievals from the Oceansat-2 scatterometer (OSCAT), which was designed and launched by the Indian Space Research Organization (ISRO) 23 September 2009. This Level 2B dataset is produced by the Jet Propulsion Laboratory (JPL) QuikSCAT Project in cooperation with ISRO. The retrievals are provided on a non-uniform grid within the swath at 12.5 km pixel resolution. This resolution is achieved through a slice composite technique in which high resolution slice measurements from L1B data are composited into a 12.5 km wind vector cell. This newest version contains an improved geophysical model function (GMF), known as QSCAT12, consistent with the Remote Sensing Systems Ku2011 GMF, and an improved rain detection and flagging algorithm; these algorithms are consistent with the latest reprocessed version 3 QuikSCAT L2B dataset. Each L2B file corresponds to a specific orbital revolution (rev) number, which begins at the southernmost point of the ascending orbit. As a Ku-band dual pencil-beam rotating scatterometer, OSCAT design specs bear a strong resemblence of the Ku-band SeaWinds scatterometers on QuikSCAT and Midori-II (ADEOS-II). The primary difference between OSCAT and SeaWinds is the ~4 degree increase in the OSCAT incidence angle, which acts as an offset to the relatively lower altitude of Oceansat-2 to help provide a nearly identical swath width to SeaWinds. In the early phase of cal/val, the JPL QuikSCAT Project identified several problems, most of which have been corrected in this latest L2B version. This dataset release is expected to have an accuracy similar to that of the version 3 L2B QuikSCAT product, with minor caveats, all of which are described by Jaruwatanadilok et al. (2014) and summarized in the User Guide document which is made available in PO.DAAC Drive at https://podaac-tools.jpl.nasa.gov/drive/files/allData/oceansat2/L2B/oscat/jpl/docs/ . Read software is made available in MATLAB, Python, R, and IDL and is accessible in PO.DAAC Drive at https://podaac-tools.jpl.nasa.gov/drive/files/allData/oceansat2/L2B/oscat/jpl/sw/ .
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.