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1,940 results for “data sample”
Field data for seasonal synoptic sampling of 100 urban streams in Salt Lake City, Utah (USA), 2023-2024
This dataset contains field measurements taken during water sampling from 100 urban stream locations in the greater Salt Lake City, Utah (USA) metropolitan area. Field collection took place during four synoptic sampling events (July 2022, October 2022, February 2023, and May 2023) to capture spatial and seasonal variation in stream conditions (specific conductivity, water temperature, dissolved oxygen, pH, ORP). Filtered stream samples were analyzed for dissolved organic carbon concentration and characteristics, available in a separate dataset. These data were collected as part of the Carbon in Urban Rivers Biogeochemistry (CURB) Project. Detailed field data and site data are published separately and can be linked using the “curbid” and “synoptic_event” columns in each dataset.
Field data for seasonal synoptic sampling of 93 urban streams in Atlanta, Georgia (USA), 2021-2022
This dataset contains field measurements taken during water sampling from 93 first- to fifth-order streams in the Altamaha, Chattahoochee, and Flint Watersheds draining a gradient of urban land use in the greater Atlanta, Georgia metropolitan area. Field collection took place during four synoptic sampling events(September 2021, December 2021, March 2022, and July 2022) to capture spatial and seasonal variation in stream conditions (specific conductivity, water temperature, dissolved oxygen, pH, ORP). Filtered stream samples were analyzed for dissolved organic carbon concentration and characteristics, available in separate datasets. These data were collected as part of the Carbon in Urban Rivers Biogeochemistry (CURB) Project. Detailed field data and site data are published separately and can be linked using the “curbid” and “synoptic_event” columns in each dataset.
Macrobenthos Sampling data for the North Inlet Estuary, Georgetown,South Carolina, from 1981 to 1992 North Inlet LTER (Reformatted to the ecocomDP Design Pattern)
This data package is formatted as an ecocomDP (Ecological Community Data Pattern). For more information on ecocomDP see https://github.com/EDIorg/ecocomDP. This Level 1 data package was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-nin/9/1. The abstract below was extracted from the Level 0 data package and is included for context: This data package consists of Macrobenthos Sampling Data for North Inlet Stations Bread and Butter Creek from 1981 to 1992, and Debidue Creek from 1981 to 1984, North Inlet LTER. The purpose of this study was to document the composition and abundance of macrobenthic subtidal populations over time at one mud and one sand site. Macrobenthos was defined here as those animals retained on a 0.5 mm mesh screen.
LTER Epibenthos Sampling Data for North Inlet Estuary, Georgetown, South Carolina from 1981 to 1992, North Inlet LTER (Reformatted to the ecocomDP Design Pattern)
This data package is formatted as an ecocomDP (Ecological Community Data Pattern). For more information on ecocomDP see https://github.com/EDIorg/ecocomDP. This Level 1 data package was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-nin/7/1. The abstract below was extracted from the Level 0 data package and is included for context: This data package consists of Epibenthos Sampling for North Inlet Stations Bread and Butter Creek, from 1981 to 1992, and Debidue Creek from 1981 to 1984, The purpose of the long term monitoring of Epibenthos was to determine seasonal and inter-annual changes in the taxonomic/life stage composition and abundance of small motile epibenthic invertebrates and fishes (1-20 mm in length) in the major sub- tidal habitats of North Inlet estuary.
Plot descriptions and location data from datalogger, 1m x 1m chamber flux and point frame plots sampled near Toolik Field Station in Alaska the summer of 2012.
"2012_GS_PFandCH_GPS" contains GPS locations of all datalogger, 1m x 1m chamber flux and point frame plots sampled IVO Toolik Field Station in Alaska during the summer of 2012. The sorting variables (YEAR, DATE, SITE, GROUP, PLOT, TREAT, PLOT SIZE) are identical to those in other files with data collected that season. The main purpose of this file is for reference and as an aid in interpretation of data analyses and among-site comparisons.
Raw pin-hit data from 19 1m x 1m point frame plots sampled near the LTER Shrub plots at Toolik Field Station in AK the summer of 2012.
This dataset includes every pin-hit recorded from 19 1m x 1m point frame plots of tall Betula nana and Salix pulchra canopies sampled at the Toolik Field Station, AK the summer of 2012. Twenty-five evenly spaced holes within the plot were sampled for each point frame for which the height and species was recorded for each leaf, stem, or plant that intersected the pin when lowered perpendicular to the ground. Non-woody species were grouped into functional groups (e.g. forb, graminoid, moss) and not identified to species. Stem diameter and the length of gramminoid blades were also recorded.
Coweeta LTER Synoptic Data from 49 sampling sites in the Upper Little Tennessee River Basin from 2009 to 2010 (Chemistry Data)
Coweeta LTER researchers sampled fifty-eight stream sites in the Upper Little Tennessee River Basin in February and June of 2009. Sites were selected to represent the range of land cover and land use within the basin. This datasets includes stream chemistry data from both the winter and summer sampling events. A whitepaper on the Synoptic field sampling activites can be found at: http://coweeta.uga.edu/publications/white%20paper%20summary%20of%20synoptic%20sampling.pdf
Coweeta LTER Synoptic Data from 56 sampling sites located in the Upper Little Tennessee River Basin from 2009 (geomorphological)
Coweeta LTER researchers sampled fifty-eight stream sites in the Upper Little Tennessee River Basin in February and June of 2009. Sites were selected to represent the range of land cover and land use within the basin. Samples were taken over three days of stable weather and discharge during periods of baseflow. They were used to characterize conditions across the basin during the growing and the non-growing seasons without the influence of elevated discharge. Each entity represents a table found in the downloadable relational database. NOTE: There is only 1 database to download regardless of which entity you choose. A whitepaper on the Synoptic field sampling activites can be found at: http://coweeta.uga.edu/publications/white%20paper%20summary%20of%20synoptic%20sampling.pdf
Coweeta Synoptic Data from 49 sampling sites in the Upper Little Tennessee River Basin from 2009 to 2010 (drainage area, slope, particle size data)
This data was generated as part of synoptic sampling conducted at the Coweeta LTER between June 2009 and May 2010. 49 wadeable streams with low levels of development were sampled throughout the Upper Little Tennessee River Basin in the Southern Appalachians. This dataset contains the location code (visually categorized basin landcover), drainage area, slope, riparian code (visually categorized riparian conditions), percent fines (<2mm), and median particle size (D50) calculated from a Wolman pebble count. The purpose of this study was to investigate the effects of riparian vegetative conditions on a suite of channel morphological variables. At each site, a uniform 150 meter section of stream was surveyed. Within each reach, the active and bankfull channel widths were measured every 5 meters, where active channel width was defined as the vegetationless channel bed from left vegetation break to right vegetation break. All wood exceeding 10 cm diameter and 1.0 m length were tallied. A Wolman pebble count (N = 100) was conducted on the coarsest riffle in each stream reach. Slopes were measured from the upstream end of riffles over three riffle-to-riffle sequences with a level rod and tape. Riparian conditions at each reach were visually categorized. Drainage area was determined from 2006 Landsat imagery. A whitepaper on the Synoptic field sampling activites can be found at: http://coweeta.uga.edu/publications/white%20paper%20summary%20of%20synoptic%20sampling.pdf
Coweeta Synoptic Data from 49 sampling sites in the Upper Little Tennessee River Basin from 2009 to 2010 (active channel width, bankfull width, and channel depth data)
This data was generated as part of synoptic sampling conducted at the Coweeta LTER between June 2009 and May 2010. 49 wadeable streams with low levels of development were sampled throughout the Upper Little Tennessee River Basin in the Southern Appalachians. Active channel width, bankfull width, and channel depth were measured every 5 meters for 150 meters at synoptic stream sites. Effects of riparian vegetative conditions on a suite of channel morphological variables were investigated: active channel width, variability of width within a reach, large wood frequency, mesoscale habitat distributions, median particle size, and percent fines. At each site, a uniform 150 meter section of stream was surveyed. Within each reach active channel width, bankfull channel width, and channel depth were measured every 5 meters. Active channel width was defined as the vegetationless channel bed from left vegetation break to right vegetation break. A whitepaper on the Synoptic field sampling activites can be found at: http://coweeta.uga.edu/publications/white%20paper%20summary%20of%20synoptic%20sampling.pdf
Coweeta Synoptic Data from 49 sampling sites in the Upper Little Tennessee River Basin from 2009 to 2010 (diameter of LWD data)
This data was generated as part of synoptic sampling conducted at the Coweeta LTER between June 2009 and May 2010. 49 wadeable streams with low levels of development were sampled throughout the Upper Little Tennessee River Basin in the Southern Appalachians. Effects of riparian vegetative conditions on a suite of channel morphological variables were investigated: active channel width, variability of width within a reach, large wood frequency, mesoscale habitat distributions, median particle size, and percent fines. Diameter of large woody debris (LWD) in each stream reach were tallied in this specific dataset. At each site, a uniform 150 meter section of stream was surveyed. All wood in a reach exceeding 10cm diameter and 1.0m length were tallied. Observers kept a tally of the function, if any, of the large woody debris within the channel (e.g. pool formation, jam formation, bank protection, etc.). A whitepaper on the Synoptic field sampling activites can be found at: http://coweeta.uga.edu/publications/white%20paper%20summary%20of%20synoptic%20sampling.pdf
Optimizing sampling across methods improves the power of ecological monitoring data
Transect-based monitoring has long been a valuable tool in ecosystem monitoring. These transects are often used to measure multiple ecosystem attributes. The line-point intercept (LPI), vegetation height, and canopy gap intercept methods comprise a set of core methods, which provide indicators of ecosystem condition. However, users struggle to design a sampling strategy that optimizes the ability to detect ecological change using transect-based methods. We assessed the sensitivity of these core methods on a one-hectare plot to transect length, number, and sampling interval to determine: 1) minimum sampling required to describe ecosystem characteristics and detect change for each method and 2) optimal transect length and number for all three methods to make recommendations for future analyses and monitoring efforts. We used data from 13 National Wind Erosion Research Network locations spanning the western US, which included 151 measurements over time across five biomes. We found that longer and increased numbers of transects were more important for reducing sampling error than increased sample intensity along transects. For all methods and indicators across plots, three 100-m transects reduced sampling error so that indicator estimates fall within an 95% confidence interval of +/- 5% for canopy gap intercept and LPI-total foliar cover, +/- 5 cm for height and +/- two species for LPI-species counts. For the same criteria at 80% confidence intervals, two 100-m transects are needed. Site-scale inference was strongly affected by sample design, consequently our understanding of ecological dynamics may be influenced by sampling decisions.
CSM09 Small mammal host-parasite sampling data associated with the Consume herbivore exclusion plots across two burned and native-grazed watersheds at Konza Prairie
Data set contains summaries of the number of individuals of each species of small mammal captured (relative abundance) on each trapping grid. Each record contains date, treatment, grid, trap station, species, specimen number, recapture status, specimen disposition, external body measurements (where applicable), reproductive information, and miscellaneous associated comments. These sampling records are based on nightly captures during one 4-night trapping period in fall (October concurrent with annual bison roundup activites) for each of 4 permanent trapping grids established on two fire/grazing treatments (two grids per treatment). These treatments are both grazed by native grazers (bison) and include one treatment burned annually (N1A) and one treatment burned every 4 years (N4B). In each treatment, sampling grids are arranged as 5 x 10 permanent stakes spaced 10m apart and labeled numerically between 1-50 for grid A and 51-100 for grid B. One grid per treatment (grid A) is sampled using capture-mark-release methods and the other grid in each treatment (grid B) is sampled using specimen removal and subsequent whole body processing and curation.
Biogeochemical rate data and sediment properties of samples used for a controlled flow through experiment testing the effect of nitrate on organic matter decomposition, PIE LTER, Plum Island Sound estuary, Massachusetts.
In this dataset, we used a controlled flow-through reactor (FTR) experiment to test the role of nitrate as an electron acceptor, and its effect on organic matter decomposition and the associated microbial community in salt marsh sediments. Organic matter decomposition significantly increased in response to nitrate, even at sediment depths typically considered resistant to decomposition. The use of isotope tracers suggests this pattern was largely driven by stimulated denitrification. Nitrate addition also significantly altered the microbial community and decreased alpha diversity, selecting for taxa belonging to groups known to reduce nitrate and oxidize more complex forms of organic matter. Fourier Transform-Infrared Spectroscopy further supported these results, suggesting that nitrate facilitated decomposition of complex organic matter compounds into more bioavailable forms. Taken together, these results suggest the existence of organic matter pools that only become accessible with nitrate and would otherwise remain stabilized in the sediment. The existence of such pools could have important implications for carbon storage, since greater decomposition rates as N loading increases may result in less overall burial of organic-rich sediment. Given the extent of nitrogen loading along our coastlines, it is imperative that we better understand the resilience of salt marsh systems to nutrient enrichment, especially if we hope to rely on salt marshes, and other blue carbon systems, for long-term carbon storage.
Mega-Monsoon Experiment (MegaME) Vegetation Sampling Data from the Sevilleta National Wildlife Refuge, New Mexico
Shrub encroachment is a global phenomenon. Both the causes and consequences of shrub encroachment vary regionally and globally. In the southwestern US a common native C3 shrub species, creosotebush, has invaded millions of hectares of arid and semi-arid C4-dominated grassland. At the Sevilleta LTER site, it appears that the grassland-shrubland ecotone is relatively stable, but infill by creosotebush continues to occur. The consequences of shrub encroachment have been and continue to be carefully documented, but the ecological drivers of shrub encroachment in the southwestern US are not well known. One key factor that may promote shrub encroachment is grazing by domestic livestock. However, multiple environmental drivers have changed over the 150 years during which shrub expansion has occurred through the southwestern US. Temperatures are warmer, atmospheric CO2 has increased, drought and rainy cycles have occurred, and grazing pressure has decreased. From our prior research we know that prolonged drought greatly reduces the abundance of native grasses while having limited impact on the abundance of creosotebush in the grass-shrub ecotone. So once established, creosotebush populations are persistent and resistant to climate cycles. We also know that creosotebush seedlings tend to appear primarily when rainfall during the summer monsoon is well above average. However, high rainfall years also stimulate the growth of the dominant grasses creating a competitive environment that may not favor seedling establishment and survival. The purpose of the Mega-Monsoon Experiment (MegaME) is twofold. First, this experiment will determine if high rainfall years coupled with (simulated) grazing promote the establishment and growth of creosotebush seedlings in the grassland-shrubland ecotone at Sevilleta, thus promoting infill and expansion of creosotebush into native grassland. Second, MegaME will determine if a sequence of wet summer monsoons will promote the establishment and gro
Table S3. List of Locustella sound recordings included in bioacoustic analysis surrounding description of the Taliabu Grasshopper-Warbler. The table provides information on sound library sources and sampling localities of recordings as well as raw data on all 11 bioacoustic parameters measured (see Supplementary Materials section SM3 for more details on parameters). Recordings whose source is labeled as "private recording" were obtained by colleagues and are available upon demand from the corresponding author.
<p>supplement to Rheindt, Frank E., Prawiradilaga, Dewi M., Ashari, Hidayat, Suparno, Gwee, Chyi Yin, Lee, Geraldine W. X., Wu, Meng Yue, Ng, Nathaniel S. R. (2020): A lost world in Wallacea: Description of a montane archipelagic avifauna. Science 367: 167-170, DOI: 10.1126/science.aax2146</p>
TIPP 2.0.0 taxonomic profiling of the CAMI 2 Mouse Gut Toy data set, samples 0-63
<strong>Software: </strong>TIPP<br><strong>SoftwareVersion: </strong>2.0.0<br><strong>DataURL: </strong> https://data.cami-challenge.org/participate<br><strong>SoftwareURL:</strong> https://github.com/smirarab/sepp<br><strong>DockerImage:</strong> stefanjanssen/docker_profiling_tools:tipp<br><strong>IsBiobox:</strong> True<br><strong>BioboxYAMLFile:</strong> https://zenodo.org/record/3629567/files/biobox.yaml?download=1<br><strong>ReferenceDatabase:</strong> 2015<br><strong>ShortReadsUsed:</strong> True<br><strong>LongReadsUsed:</strong> False<br><strong>CommandsUsed:</strong> docker run \<br>--volume="/path/to/19122017_mousegut_scaffolds_yaml:/bbx/mnt/yaml:ro" \<br>--volume="/path/to/19122017_mousegut_scaffolds:/bbx/mnt/input:ro" \<br>--volume="/path/to/output:/bbx/mnt/output:rw" \<br>--volume="/path/to/output/metadata:/bbx/metadata:rw" \<br>--volume="/path/to/output/cache:/cache:rw" \<br>stefanjanssen/docker_profiling_tools:tipp
Bracken 2.5 taxonomic profiling of the CAMI 2 Mouse Gut Toy data set, samples 0-63
<strong>Software: </strong>Bracken<br><strong>SoftwareVersion: </strong>2.5<br><strong>DataURL: </strong> https://data.cami-challenge.org/participate<br><strong>SoftwareURL:</strong> https://github.com/jenniferlu717/Bracken<br><strong>DockerImage:</strong> cami/bracken:2.5<br><strong>IsBiobox:</strong> True<br><strong>BioboxYAMLFile:</strong> https://zenodo.org/record/3629567/files/biobox.yaml?download=1<br><strong>ReferenceDatabase:</strong> Kraken standard db built May 2019<br><strong>ShortReadsUsed:</strong> True<br><strong>LongReadsUsed:</strong> False<br><strong>CommandsUsed:</strong> docker run \<br>--volume="/path/to/19122017_mousegut_scaffolds_yaml:/bbx/mnt/yaml:ro" \<br>--volume="/path/to/19122017_mousegut_scaffolds:/bbx/mnt/input:ro" \<br>--volume="/path/to/output:/bbx/mnt/output:rw" \<br>--volume="/path/to/output/metadata:/bbx/metadata:rw" \<br>--volume="/path/to/output/cache:/cache:rw" \<br>cami/bracken:2.5
MetaPalette 1.0.0 taxonomic profiling of the CAMI 2 Mouse Gut Toy data set, samples 0-63
<strong>Software: </strong>MetaPalette<br><strong>SoftwareVersion: </strong>1.0.0<br><strong>DataURL: </strong> https://data.cami-challenge.org/participate<br><strong>SoftwareURL:</strong> https://doi.org/10.5281/zenodo.1730624<br><strong>DockerImage:</strong> stefanjanssen/docker_profiling_tools:commonkmers<br><strong>IsBiobox:</strong> True<br><strong>BioboxYAMLFile:</strong> https://zenodo.org/record/3629567/files/biobox.yaml?download=1<br><strong>ReferenceDatabase:</strong> https://zenodo.org/record/1749272<br><strong>ShortReadsUsed:</strong> True<br><strong>LongReadsUsed:</strong> False<br><strong>CommandsUsed:</strong> docker run \<br>--volume="/path/to/19122017_mousegut_scaffolds_yaml:/bbx/mnt/yaml:ro" \<br>--volume="/path/to/19122017_mousegut_scaffolds:/bbx/mnt/input:ro" \<br>--volume="/path/to/output:/bbx/mnt/output:rw" \<br>--volume="/path/to/output/metadata:/bbx/metadata:rw" \<br>--volume="/path/to/output/cache:/cache:rw" \<br>--volume="/path/to/reference_database:/exchange/db:rw" \<br>stefanjanssen/docker_profiling_tools:commonkmers
MetaBAT 2.12.1 genome binning of the CAMI 2 Mouse Gut Toy data set, samples 0-63, gold standard pooled assembly
Genome binning of the gold standard pooled assembly <br><strong>Software: </strong>MetaBAT<br><strong>SoftwareVersion: </strong>2.12.1<br><strong>DataURL: </strong> https://data.cami-challenge.org/participate<br><strong>SoftwareURL:</strong> https://bitbucket.org/berkeleylab/metabat<br><strong>ShortReadsUsed:</strong> True<br><strong>LongReadsUsed:</strong> False<br><strong>CommandUsed:</strong> bowtie2-build anonymous_gsa_pooled.fasta anonymous_gsa_pooled.fasta<br>for i in {0..63}; do bowtie2 -q --threads 30 --fr -x anonymous_gsa_pooled.fasta --interleaved sample_${i}/anonymous_reads.fq -S anonymous_reads_sample_${i}.sam ; done<br>for i in {0..63}; do samtools view -b sample_${i}.sam -o anonymous_reads_sample_${i}.bam & done<br>for i in {0..63}; do samtools sort anonymous_reads_sample_${i}.bam -o anonymous_reads_sample_${i}.sorted.bam ; done<br>for i in {0..63}; do samtools index anonymous_reads_sample_${i}.sorted.bam ; done<br>runMetaBat.sh -l anonymous_gsa_pooled.fasta anonymous_reads_sample_*.sorted.bam
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.