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Bald cypress radiocarbon and dendrochronological data from trees located in the Altamaha Wildlife Management Area and on Sapelo Island, Georgia, USA
Ancient bald cypress trees buried under anoxic mud on the Altamaha Wildlife Management Area islands were sampled, prepared, radiocarbon dated, and the ringwidths measured for crossdating. Modern bald cypress samples were also obtained from Sapelo Island. Tree rings were measured using a Velmex and Measure J2X software and/or the ObjectJ extension of ImageJ. Measured radii were crossdated using visual dendrochronological methods and Cofecha software. Tree rings anchored to the present date back to 3161 B.C.E. and extend to 2016 C.E. In addition, the oldest two trees provide another 529 years of ringwidth data. This work was conducted under the National Science Foundation Doctoral Dissertation Improvement Award: Human Adaptation to Long Term Environmental Change (Award #1834682). All samples are part of the accessioned collections of the University of Georgia Laboratory's of Archaeology.
Soil volumetric water content calculated from neutron hydroprobe data at 15 NPP study locations at the Jornada Basin LTER site, 1989-ongoing
This data package contains soil water content data calculated from monthly neutron hydroprobe count measurements made at 15 net primary production (NPP) study locations on Jornada Experimental Range (JER) and Chihuahuan Desert Rangeland Research Center (CDRRC) lands. Once a month, neutron probe measurements are made at 10 depths (where possible) at each of 10 access tubes at each of the 15 NPP sites using a neutron probe (CPN Model 503DR Hydroprobe and CPN Model 503 Elite Hydroprobe). The raw dataset, also on EDI (knb-lter-jrn.210013001), consists of the count of thermalized neutrons at 30 cm depth intervals to a maximum depth of 300 cm. In this data package, the raw neutron counts have been adjusted for radioactive decay of the neutron source, then converted to volumetric water content (VWC) to a maximum depth of 270 cm using calibration equations (deepest probe depths are excluded from VWC calculations). The NPP sites these measurements are made at represent the 5 dominant vegetation types of the Jornada Basin, which consist of 3 shrub (creosotebush, mesquite dune, and tarbush) and 2 grass (upland grassland and playa) types. Three NPP sites are located in each of the types. This data collection is ongoing with new data collected monthly (updates to the EDI package may occur less frequently). NOTE: This version of the dataset includes calibrated data from a new hydroprobe unit that has recently been put into service. Repair parts were no longer available for the older unit.
Temperature, Salinity, Sound Velocity, Location, Depth, Heading, and Velocity measured aboard the R/V Nanuq for the Northern Gulf of Alaska LTER site, 2020-2021
This dataset describes measurements from a thermosalinograph and navigation device used aboard the R/V Nanuq during cruises in Resurrection Bay and the Gulf of Alaska. Thermosalinograph data includes temperature, salinity, conductivity, and sound speed measurements every five seconds while the instrument was in use. Navigation data describes latitude, longitude, depth, heading, course over ground, and speed over ground. Data are collected on R/V Nanuq using the ship's GPS devices and a Seabird Electronics SBE-45 thermosalinograph (TSG) that samples uncontaminated pumped seawater. Temperature and conductivity data are sampled every 5 seconds and salinity and sound velocity are derived parameters. No data quality control has been applied to this data, so users should be cautious that conductivity, salinity and sound speed dropouts to due bubbles are common when the ship is plowing through large waves. Data are collected by a variety of projects, including from the NSF-funded Northern Gulf of Alaska Long Term Ecological Research (NGA LTER) program, the Exxon Valdez Oil Spill Trustee Council (EVOSTC) Gulf Watch Alaska GAK1 project, the UAF Sub-Arctic Oceanography Field Course, the Alaska Ocean Observing System (AOOS) glider program, and others.
North Temperate Lakes LTER Processed eddy covariance time series fluxes from tower located on roof of the CFL building oriented toward Lake Mendota 2012 - current
We calculated eddy covariance based fluxes of CO2, H2O, heat, and momentum to study lake-atmosphere exchanges since 2012. These data were collected by Ankur Desai from 2012 to present using a CSAT-3 sonic anemometer and LI-7500 gas analyzer located on the roof of the CFL building. A footprint model (Kljun) was used to screen for lake only data.
Weather station data from three locations at Lake Sunapee (NH, USA), July 2019 – December 2023
Davis weather stations, owned and operated by the Lake Sunapee Protective Association (LSPA), were installed at three locations near the shoreline of Lake Sunapee (NH, USA) in July 2019. These stations collect data at 30-minute intervals for a number of weather and meteorological variables continuously throughout the year. In addition to the measured variables, a number of derived variables are also recorded at the same time intervals. Data are manually downloaded from Davis’s WeatherLink website every quarter, then collated and QAQC’d to remove any obvious outliers or recording errors in the R programming language.
GPS Locations of Seagrass Sites in Hog Island Bay and South Bay, VA 2010-2021
This dataset contains the GPS coordinates for plots within the Z. marina restoration in the Hog Island Bay and South Bay, VA that are sampled annually as part of the long-term restoration experiment. Plots were seeded between 2001-2008; 64 plots in Hog Island Bay (58 seagrass plots and 6 bare plots) and 12 plots in South Bay (6 seagrass plots and 6 bare plots) were sampled beginning in 2010. The bare sites in South Bay were no longer sampled after 2013 due to colonization by seagrass. Additional sites were identified in 2017 in areas of natural seagrass expansion - 6 in Hog Island Bay and 6 in South Bay.
OLVSL_ Object-location visual statistical learning
Open the record for dataset details and reuse information.
Point locations for spatial and morphological analyses of barchans in swarms
<div>This dataset contains the long-lat coordinates of seven points on ~6000 barchans located in six swarms.</div> <div> </div> <div>Four of the locations are on Earth (three in the Tarfaya region of the Western Sahara, one in Mauritania).</div> <div>The other two swarms are from high latitudes of the northern hemisphere of Mars.</div> <div> </div> <div>In each location between 850 and 1112 barchans were measured.</div> <div> </div> <div>The measurements were carried out manually by Dominic T Robson and Andreas CW Baas according to the method described in</div> <div>Robson, D. T., Annibale, A., & Baas, A. C.W. (2022). Reproducing size distributions of swarms of barchan dunes on Mars and Earth using a mean-field model. Physica A: Statistical Mechanics and its Applications, 606, 128042.</div> <div> </div> <div>The included metadata file lists the copyrights and dates (DD/MM/YYYY) for the imagery used, all imagery was accessed through Google Earth. </div> <div> </div> <div>The metadata file also includes descriptions of the format of the data. The data themselves are provided in separate comma delimited files for each location. Only the bedforms identified as barchans are included although other bedforms in the locations were also measured (see Robson et al. Physica A (2022)).</div> <div> </div> <div>Using the seven points recorded for each dune it is possible to calculate:</div> <div>Body length</div> <div>Total length</div> <div>Horn lengths</div> <div>Total width</div> <div>Horn-to-horn width</div> <div>Port flank width</div> <div>Starboard flank width</div> <div>Slipface length</div> <div>Dune orientation</div> <div> </div> <div>The area of the polygons formed by the points also provides an estimate for the basal area of the dune though it is not a perfect match.</div> <div> </div> <div>We hope that these data will be of use to those seeking to study the morphology, size, asymmetry, and spatial distribution of barchans in swarms.</div> <div> </div> <div>Dominic T Robson and Andreas CW Baas.</div>
Invasion Biology WikiProject Scientific Papers: Text Data Mining and LLM-based Information Extraction of Species, Locations, Habitats, and Ecosystems
<p>This dataset contains the abstract and full-text for publication DOIs from the Invasion Biology WikiProject (DOI: <a href="https://www.doi.org/10.5281/zenodo.12518036">10.5281/zenodo.12518036</a>). The data was retrieved using the <a href="https://ask.orkg.org/">ask.orkg.org</a> <a href="https://api.ask.orkg.org/docs#tag/Semantic-Neural-Search/operation/explore_documents_index_explore_get">API</a>. For the <a href="https://github.com/jd-coderepos/invasion-biology-IE/blob/main/scripts/ask-doi-list-fulltext-search.py">script</a> used to obtain the data, refer to the accompanying GitHub repository: <a href="https://github.com/jd-coderepos/invasion-biology-IE/" target="_blank" rel="noopener">https://github.com/jd-coderepos/invasion-biology-IE/</a>.</p> <p>The resulting CSV file includes the following fields: <code>"ASK ID"</code>, <code>"DOI"</code>, <code>"Title"</code>, <code>"Abstract"</code>, and <code>"Full-text"</code>.</p> <p>Of the 49,438 queried DOIs, the ASK database provided:</p> <ul> <li><strong>Total DOIs processed:</strong> 12,636</li> <li><strong>DOIs with neither abstract nor full-text:</strong> 36 (abstract token count was less than 10)</li> <li><strong>DOIs with abstracts but no full-text:</strong> 12,636</li> <li><strong>DOIs with both abstract and full-text:</strong> 2,834</li> </ul> <p>The second part of the dataset contains structured information extracted from the publications using the GPT-4o Large Language Model. This structured data is included in the zipped folder <code>structured-publications.zip</code>.</p> <p>The accompanying GitHub repository provides access to the code and scripts used at various stages of the information extraction (IE) process.</p> <p><strong>Theme of the Study:</strong><br>"Mining for Species, Locations, Habitats, and Ecosystems from Scientific Papers in Invasion Biology: A Large-Scale Exploratory Study with Large Language Models."</p>
Steady-state operation dataset of an experimental Wet Cooling Tower pilot plant located at Plataforma Solar de Almería
<p>Repository that contains experimental data obtained from a Wet Cooling Tower (WCT) plant located at <a href="https://www.psa.es/es/index.php">Plataforma Solar de Almería</a>.</p> <p>For the article "Wet cooling tower performance prediction in CSP plants: A comparison between artificial neural networks and Poppe’s model", three experimental campaigns were used, quoting from the article:</p> <blockquote> <p>A total of 132 steady-state experimental points have been obtained thanks to the thorough experimentation conducted. These data cover a large variety of ambient conditions (different seasons, days and nights) and thermal loads (from 27 kW to 207 kW). </p> </blockquote> <p> </p> <p>See <code>README.md</code> for a more detailed description and instructions on how to use the data.</p> <h2><br>License</h2> <p><a href="https://creativecommons.org/licenses/by/4.0/">CC BY 4.0. Attribution 4.0 International</a></p> <p>If the data is used as part of a scientific publication, please cite the source publication:</p> <div> <div>Serrano, Juan Miguel, Pedro Navarro, Javier Ruiz, Patricia Palenzuela, Manuel Lucas, and Lidia Roca. “Wet Cooling Tower Performance Prediction in CSP Plants: A Comparison between Artificial Neural Networks and Poppe’s Model.” <em>Energy</em> 303 (September 15, 2024): 131844. <a href="https://doi.org/10.1016/j.energy.2024.131844">https://doi.org/10.1016/j.energy.2024.131844</a>.</div> </div>
6C dataset for Mw 7.4 Hualien earthquake on 2024-04-02 at station locations MDSA0 and NA01.
<p>This repository contains the 6-component data set recording the Hualien Mw 7.4 earthquake on 2024-04-02. It contains the data for two station locations MDSA0 and NA01. For both locations there are 3 component rotation rates and 3 component accelerations. The instrument type and the coresponding response is in the file instrument_response.txt. It also includes the coordinates of both stations.</p> <p>After removing the response the acceleration data will be in units 'm/s/s' and the rotation data will be in 'rad/s'. </p> <p>The MDSA0 station is situated in Hualien, Taiwan. One blueSeis-3A rotational sensor is collocated with a Nanometrics Titan accelerometer at depth of 0.5 m in a vault structure.</p> <p>The NA01 station is situated in Nanao, Taiwan. One blueSeis-3A rotational sensor is collocated with a Kinemetrics EpiSensor accelerometer at depth of 2 m in a vault structure.</p>
Soil moisture sensor network, design, location attributes and soil properties, Hainich, Germany, project AquaDiva
<p>This dataset contains information of the small scale highly resolved soil moisture measurement network that is part of the of the AquaDiva Critical Zone exploratory, Hainich National Park, Germany. The dataset contains information on soil measurement locations, as well as attributes to the location, the design type (random locations vs transects), as well as locations attributes like distance to the next tree and soil properties. Measurement design was first introduced by Metzger et al., (2017), and used in Fischer et al., 2023. See there for more information.</p> <p><strong>References</strong></p> <p>Fischer-Bedtke, C., Metzger, J. C., Demir, G., Wutzler, T., and Hildebrandt, A.: Throughfall spatial patterns translate into spatial patterns of soil moisture dynamics – empirical evidence, Hydrology and Earth System Sciences, https://doi.org/10.5194/hess-2022-418, 2023.</p> <p>Metzger, J. C., Wutzler, T., Dalla Valle, N., Filipzik, J., Grauer, C., Lehmann, R., Roggenbuck, M., Schelhorn, D., Weckmüller, J., Küsel, K., Totsche, K. U., Trumbore, S., and Hildebrandt, A.: Vegetation impacts soil water content patterns by shaping canopy water fluxes and soil properties, Hydrological Processes, 31, 3783–3795, https://doi.org/10.1002/hyp.11274, 2017.</p>
Near-surface, soil, and air temperature data acquired across multiple locations on the San Joaquin Experimental Range, California, 2011-2017
These temperature records were collected as part of a larger study relating microclimates to tree seedling survival in southern California mountains. These temperature records are for studies at the San Joaquin Experimental Range (Lat 37.083, Long -119.716, elevation 210-520 m, www.fs.fed.us/psw/ef/san_joaquin/). Temperature sensors were located at 23 sites across the landscape. Sites were selected to sample topographic variation in surface and air temperatures within a narrow range of elevations on northeast to southwest-facing slopes, ridges, and valleys. To characterize surface temperature variation within a site, 21 sensors were arranged in an identical pattern around and in six, 5x5 m experimental gardens. An additional 18 sensors were placed along three transects over the landscape running E-W. They were placed strategically to sample topographic inflection points (hill tops and valley bottoms) as well as north and south facing slopes. Temperatures were recorded on a 10 or 20-minute interval, depending on the sensor, using HOBO (Onset, www.onsetcomp.com) devices.
Weather station data acquired across multiple locations on the San Joaquin Experimental Range, California, 2011-2017
These weather station records were collected as part of a larger study relating microclimates to tree seedling survival in southern California mountains. These weather station records are for studies at the San Joaquin Experimental Range (Lat 37.083, Long -119.716, elevation 210-520 m, www.fs.fed.us/psw/ef/san_joaquin/). Weather stations were located at six sites across the landscape. Sites were selected to sample topographic variation in surface and air temperatures within a narrow range of elevations on northeast to southwest-facing slopes, ridges, and valleys. Three full weather stations (north slope, south slope, and valley floor) monitored precipitation, wind, insolation, temperature, relative humidity, and soil moisture. Three micro stations (west slope, east slope, and ridge) measured soil moisture at -20 cm. Data was recorded on a 10-minute interval using HOBO (Onset, www.onsetcomp.com) devices.
Near-surface, soil, and air temperature data acquired across multiple locations in the Teakettle Experimental Forest, California, 2011-2017
These temperature records were collected as part of a larger study relating microclimates to tree seedling survival in southern California mountains. These temperature records are for studies at the Teakettle Experimental Forest (Lat 36.967, Long -119.017, elevation 2000-2800 m, www.fs.fed.us/psw/ef/teakettle/). Temperature sensors were located at 44 sites across the landscape. Sites were selected to sample topographic variation in surface and air temperatures within a narrow range of elevations on northeast to southwest-facing slopes, ridges and valleys. To characterize surface temperature variation within select sites, 21 sensors were arranged in an identical pattern around and in six, 5x5 m experimental gardens (see garden schematic for details). An additional 33 sites were located across the site by way of a stratified sampling scheme which targeted low, medium, and high elevation areas, low, medium, and high radiation areas, and cold air pooling areas. In June 2012, in order to concentrate sensors in a smaller study area (ease of access and to make this more similar to other sites, 22 sites were "retired," and 7 new sites were installed, for a total of 18 during the remainder of the study. Temperatures were recorded on a 10 or 20-minute interval, depending on the sensor. using HOBO (Onset, www.onsetcomp.com) devices.
Ovenbird song recordings from Alberta (Canada) with individual labels and spatial locations, 2015-2016
This dataset includes spatially localized and individually identified Ovenbird songs. We used automated species detection and acoustic localization to localize Ovenbird singing events from microphone arrays in Alberta, Canada (2015-2016). We then hand-annotated songs to individuals based on acoustic characteristics. This dataset includes the manual annotations and annotations from automated individual identification approaches. This data publication pertains to the manuscript [in prep] by Lapp et al on Ovenbird individual identification and provides further details on the study and the individual identification approach.
A unified dataset of co-located sewage pollution, periphyton, and benthic macroinvertebrate community and food web structure from Lake Baikal (Siberia)
Sewage released from lakeside development can introduce nutrients and micropollutants that can restructure aquatic ecosystems. Lake Baikal, the world's most ancient, biodiverse, and voluminous lake, has been experiencing localized sewage pollution from lakeside settlements. Increasing filamentous algal abundance suggests benthic communities are responding to this localized pollution. We surveyed 40-km of Lake Baikal's southwestern shoreline 19-23 August 2015 for sewage indicators, including pharmaceuticals, personal care products, and microplastics with co-located periphyton, macroinvertebrate, stable isotope, and fatty acid sampling. Unique identifiers corresponding to sampling locations are retained throughout all data files to facilitate interoperability among the dataset's 150+ variables. The data are structured in a tidy format (a tabular arrangement familiar to limnologists) to encourage future reuse. For Lake Baikal studies, these data can support continued monitoring and research efforts. For global studies of lakes, these data can help characterize sewage prevalence and ecological consequences of anthropogenic disturbance across spatial scales.
Site Location and Environmental Characteristics for 83 Locations of 6-163 Years Old Black Spruce, Alaska Paper Birch, and Aspen Stands Accoss Interior Alaska. Sampled in 2008-2010 and 2013-2015.
This dataset contains the GPS location, slope, orientation, elevation, forest type based on dominant tree biomass, Age, sampling year, total vascular cover, total lchen cover, deciduous index (Alexander et al. 2012, Ecosphere), basal area of black spruce, Alaska paper birch, trembling aspen, large deciduous shrubs and trembling aspen, organic layer depth, pH, heatload, approximated moisture class for all sites (Johnstone et al. 2008), gravimetric moisture content, and volumetric moisture content. This dataset was part of the site-level covariates used in a study of bryophyte post-fire succession in deciduous and coniferous successional trajectories. NOTE: there is some overlap between the >20 years old sites that were sampled by Heather Alexander with some of the data she submitted in relation to her 2012 Ecosphere paper.
Vegetation Data Collected with Point Frame for 83 Locations of 6-163 Years Old Black Spruce, Alaska Paper Birch, and Aspen Stands Across Interior Alaska. Sampled in 2008-2010 and 2013-2015.
This dataset contains point frame data for vegetation less than 1.3 m, including vascular plants, bryophytes, lichens, leaf litter and bare ground, as well as species codes used, as described in Jean et al. 2017 Canadian Journal of Forest Research. Samples of all encountered unknown species were collected for identification in the lab. Bryophyte nomenclature followed Anderson et al. (1990).
Bryophyte Cover Summary Data for 83 Locations of 6-163 Years Old Black Spruce, Alaska Paper Birch, and Aspen Stands Across Interior Alaska. Sampled in 2008-2010 and 2013-2015.
This dataset contains the summarized bryophyte (percent cover) data obtained from point frame measurements, as used in Jean et al. 2017 Canadian Journal of Forest Research. ?Samples of all encountered unknown species were collected for identification in the lab. Bryophyte nomenclature followed Anderson et al. (1990).
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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.