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27 results for “running waters”
Background data: Untangling the effects of multiple human stressors and their impacts on fish assemblages in European running waters
<p>This dataset presents some backkground data from the EFI+ database. Related work addresses human stressors and their impacts on fish assemblages at pan-European scale by analysing single and multiple stressors and their interactions. Based on an extensive dataset with 3105 fish sampling sites, patterns of stressors, their combination and nature of interactions, i.e. synergistic, antagonistic and additive were investigated. </p> <p>Data were derived within the EU-project "Improvement and Spatial extension of the European Fish Index (EFI+)". EFI+, an EU FP6 research project from 2007-2009 was designed to gain new knowledge and to further develop and improve new biological assessment methods to meet needs of the Water Framework Directive (WFD). </p> <p>Background data are available for boxplots and barplots shown in the related research article in STOTEN.</p>
Large Ensemble Dataset for Discovering Global Peak Water Limit of Future Groundwater Withdrawals Using 900 GCAM Runs
<h2><strong>Global Groundwater Withdrawals Peak Over the 21st Century </strong></h2> <p>The large ensemble dataset contains groundwater related model outputs from 900 scenarios modeled using <a href="http://jgcri.github.io/gcam-doc/toc.html">Global Change Analysis Model (GCAM)</a>. The scenario ensemble members include five Shared Socioeconomic Pathways (SSPs), four Representative Concentration Pathways (RCPs), five global climate model outputs, three groundwater depletion limits, two surface water storage expansion regimes, and two historical groundwater depletion trends.</p> <h3><strong>Journal Article</strong></h3> <p>Niazi, H., Wild, T.B., Turner, S.W.D., Graham, N.T., Hejazi, M., Msangi, S., Kim, S., Lamontagne, J.R., & Zhao, M. (2024). <a href="https://rdcu.be/dFpb5">Global peak water limit of future groundwater withdrawals</a>. <em>Nature Sustainability, 7</em>(4), 413–422. <a href="https://doi.org/10.1038/s41893-024-01306-w" rel="nofollow">https://doi.org/10.1038/s41893-024-01306-w</a></p> <p>Read full-text here: <a href="https://rdcu.be/dFpb5">https://rdcu.be/dFpb5</a> </p> <h3><strong>Data Repository </strong></h3> <p>This <em><strong>data</strong></em> repository is to be used in combination with the <em><strong>main</strong></em> <a href="https://github.com/JGCRI/niazi-etal_2024_nature-sustainability">meta-repository</a> containing all scripts and files for reproducing the experiment as well as the analysis and post-processing of the model outputs.</p> <p>Scripts and smaller files are provided in the <a href="https://github.com/JGCRI/niazi-etal_202X_xyz">GitHub meta-repository</a> whereas larger files are provided in this data repository. Please complete the repository by placing the files as described hereunder. Please find the GitHub meta-repository here: <a href="https://github.com/JGCRI/niazi-etal_2024_nature-sustainability">https://github.com/JGCRI/niazi-etal_2024_nature-sustainability</a></p> <p>Descriptions of files:</p> <ol> <li><em><strong>gcam-5.7z</strong></em> contains the GCAM version used to simulate 900 scenarios of plausible futures. The model folder contains all necessary input files to reproduce the simulations. <ul> <li>The model is to be used in combination with the <a href="https://github.com/JGCRI/niazi-etal_2024_nature-sustainability">meta-repository</a> to setup batch runs on cluster.</li> <li>Please navigate to <a href="https://github.com/JGCRI/niazi-etal_202X_xyz/tree/main/model">model/</a> folder for other scenario-specific and model setup folders and files. <em><strong>gcam-5</strong></em> is to be extracted in the same directory (./<em>model/gcam-5/</em>). </li> <li>For the first-time users of GCAM, please follow guidance on <a href="http://jgcri.github.io/gcam-doc/toc.html">GCAM wiki</a> to setup GCAM or for background knowledge. </li> </ul> </li> <li><em><strong>crop_yeild.7z</strong></em>: This file contains inputs related to climate impacts on crop yields. This is to be downloaded and extracted in the <a href="https://github.com/JGCRI/niazi-etal_202X_xyz/tree/main/model/combined_impacts">model/combined_impacts/</a> folder. </li> <li><em><strong>outputs-all.7z: </strong></em>Key model outputs queried and collated from 900 GCAM runs are explained hereunder. The files could be downloaded individually (.csv files) or all at once in .7z format (<a href="../api/files/80b237d3-b22f-499f-8b8e-76c3846720a0/outputs-all.7z">outputs-all.7z</a>). These files are to be placed in the <a href="https://github.com/JGCRI/niazi-etal_202X_xyz/tree/main/model/outputs">model/outputs</a> folder of the <a href="https://github.com/JGCRI/niazi-etal_2024_nature-sustainability">meta-repository</a>. <ul> <li><em><strong>ag_prod_all_GW_scenarios.csv</strong></em> - Agricultural production across all scenario for 2050 and 2100 (tonnes)</li> <li><em><strong>prices_water_withdrawal_all.csv</strong> - </em>Water prices across all scenarios and years ($/km<sup>3</sup>)</li> <li><em><strong>global_irrigated_prod_by_crop.csv</strong></em> - All irrigated agricultural production for each crop across and scenarios all years (tonnes)</li> <li><em><strong>surface_water_production_all.csv</strong></em> - Runoff across all scenarios and years (km<sup>3</sup>)</li> <li><em><strong>groundwater_production_FINAL.csv</strong></em> - Groundwater withdrawals across all scenarios and years (km<sup>3</sup>)</li> <li><em><strong>water_withdrawals_desal_all.csv</strong></em> - Water withdrawals from desalination plants across all scenarios and years (km<sup>3</sup>)</li> </ul> </li> </ol> <h3><strong>Short introduction to the study</strong></h3> <p>Using 900 GCAM runs, this study finds that global groundwater withdrawals are expected to peak around mid-century, followed by a decline through 21st century, exposing about half of the population living in one-third of basins to groundwater stress, with cost and availability of surface water storage being the most significant driver of future groundwater withdrawals. This first-ever robust, quantitative confirmation of the peak-and-decline pattern for groundwater, previously only known for fossil fuels and minerals, raises concerns for basins heavily dependent on groundwater.</p> <p>Niazi, H., Wild, T.B., Turner, S.W.D., Graham, N.T., Hejazi, M., Msangi, S., Kim, S., Lamontagne, J.R., & Zhao, M. (2024). <a href="https://rdcu.be/dFpb5">Global peak water limit of future groundwater withdrawals</a>. <em>Nature Sustainability, 7</em>(4), 413–422. <a href="https://doi.org/10.1038/s41893-024-01306-w" rel="nofollow">https://doi.org/10.1038/s41893-024-01306-w</a></p> <p>Read full-text here: <a href="https://rdcu.be/dFpb5">https://rdcu.be/dFpb5</a></p> <h3><strong>Contact </strong></h3> <p>Please reach out to Hassan Niazi at <a href="mailto:hassan.niazi@pnnl.gov">hassan.niazi@pnnl.gov</a> for any questions. </p>
Figure 11 in A quantitative method for collecting water mites in lotic, riffle-run habitats for water quality biomonitoring
Figure 11 An example of how water mites appear under a stereoscope. a – water mites of mixed taxa in a single sample ready to be sorted through and identified; b – water mites belonging to the genusTestudacarus and their easily observable characteristic dorsal plates; c – water mites belonging to the genusKongsbergia and their easily distinguishable posterior body shape.
Figure 6 in A quantitative method for collecting water mites in lotic, riffle-run habitats for water quality biomonitoring
Figure 6 The sieving process proposed in this manuscript. a – collector fills the composited sample container with water and shakes the container for approximately 10 seconds; b – immediately after shaking the collector removes the lid and pours the water through the 3mm and 250 μm sieves; c and d – the 3mm will be placed on top of the 250 μm sieve so it can filter out larger sized substrate and debris. This process is repeated 10x.
Figure 5 in A quantitative method for collecting water mites in lotic, riffle-run habitats for water quality biomonitoring
Figure 5 An example of the collector emptying the net contents from the first of four site collections into sample container; the next three site
Figure 2 in A quantitative method for collecting water mites in lotic, riffle-run habitats for water quality biomonitoring
Figure 2 Collection nets discussed in this manuscript. a – a standard, commercially available, truncated D-frame net with 500 μm mesh; b – our custom made, non-truncated D-frame net with 250 μm mesh.
Figure 1 in A quantitative method for collecting water mites in lotic, riffle-run habitats for water quality biomonitoring
Figure 1 Examples of impaired and attaining riffle-run stream habitats in central Pennsylvania. a – Warriors Mark Run, impaired stream; b – Muddy Run, impaired stream; c – Spruce Run, attaining stream; d – Laurel Run, attaining stream.
Figure 3 What a in A quantitative method for collecting water mites in lotic, riffle-run habitats for water quality biomonitoring
Figure 3 What a single collection site should look like after the proposed three-minute collection effort. The blue arrows indicate stacked rocks that were stacked upstream of the net to better direct flow into the net. Large rocks were moved before digging into the substrate, while medium-sized and smaller rocks were placed as the substrate was dug up.
Figure 10 A in A quantitative method for collecting water mites in lotic, riffle-run habitats for water quality biomonitoring
Figure 10 A final, picked water mite sample preserved in 80% ethanol ready for identification and enumeration.
Figure 7 After sieving, the collector removes the contents from the 250 in A quantitative method for collecting water mites in lotic, riffle-run habitats for water quality biomonitoring
Figure 7 After sieving, the collector removes the contents from the 250 μm sieve and places them into the final sample jar. a – fine sediment
Figure 4 in A quantitative method for collecting water mites in lotic, riffle-run habitats for water quality biomonitoring
Figure 4 An example of the collection process proposed in this manuscript. a – the collector stands upstream of the net and disturbs the substrate; b – a typical collection setup that includes one person shoveling and another holding the net; c – water mites become suspended in the water column and flow downstream into the net.
Figure 9 in A quantitative method for collecting water mites in lotic, riffle-run habitats for water quality biomonitoring
Figure 9 The picking process proposed in this manuscript. a – the picker empties the contents of the sample container into the white photographic
Μονή Θάρρι Moni Thari, Ρόδος Rodos. Spring and water channel running east of the church.
<p>Μονή Θάρρι Moni Thari, Ρόδος Rodos. Spring and water channel running east of the church.</p>
Evaluating rapid water excitation techniques for 5D whole-heart fat-suppressed free-running cardiac MRI at 1.5T scanner
<p>Volunteer dataset of the paper: <em>"Evaluating Rapid Water Excitation Techniques for 5D Whole-Heart Fat-Suppressed Free-Running Cardiac MRI at 1.5T Scanner"</em></p> <p>The folder "InVivo" contains raw data from five different volunteers, with each volunteer having undergone 5 different acquisitions: bSSFP, FISS, BORR, LIBRE, and LIBOR. </p>
Figure 8 in A quantitative method for collecting water mites in lotic, riffle-run habitats for water quality biomonitoring
Figure 8 The final composite, sieved water mite sample ready for the picking process.
Data from: Running in the rain: Impact of water droplets on tandem running recruitment in a tropical ant
Open the record for dataset details and reuse information.
An evidence map of research assessing the effects of timber harvesting on water quality, biotic and biodiversity indicators in running waters: Data and R code
<p>These are the data and R code that accompany the Forest Ecology and Management publication titled "An evidence map of research assessing the effects of timber harvesting on water quality, biotic and biodiversity indicators in running waters". </p>
Figure 2 in Tyrannosaurus rex runs again: a theoretical analysis of the hypothesis that full-grown large theropods had a locomotory advantage to hunt in a shallow-water environment
Figure 2. Depiction of the measurements (a, b, h) taken from figures in the paper by Bates et al. (2009) and the methods to estimate wetted areas and volumes from cylindrical slices. A representative example of the methods (best reconstruction of Tyrannosaurus rex BHI 3033) is shown. The silhouettes were modified from fig. 5 in the paper by Bates et al. (2009). A, cranial view and lateromedial measurements. B, right lateral view and anteroposterior measurements. C, a generic cylindrical slice and the equations to estimate the contribution to the total areas and volumes.
Figure 1 in Tyrannosaurus rex runs again: a theoretical analysis of the hypothesis that full-grown large theropods had a locomotory advantage to hunt in a shallow-water environment
Figure 1. Schematic representation of the hunting scenario. Tyrannosaurus rex is wading in mode II, while Edmontosaurus annectens and Struthiomimus sedens are already engaged in mode IV, corresponding to surface swimming.
Figure 3. A in Tyrannosaurus rex runs again: a theoretical analysis of the hypothesis that full-grown large theropods had a locomotory advantage to hunt in a shallow-water environment
Figure 3. A comparative plot of maximum speed in water as a function of water depth for the three species studied here.
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.