Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
3,101
datasets available to search
ShareScore release 0.9.0
Dataset results
3,101 results for “tables”
Supplementary Table S27.1: Animal species native to South Africa that have invasive populations elsewhere.
<p>Animal species native to South Africa that have invasive populations elsewhere. Sorted by expected chronological appearance in the first place they were recorded as alien species. Notes are made on whether the introduction is known to be (Y) or not (N) from South Africa (or unknown U). Pathways are according to the CBD pathway classification scheme (Harrower et al. 2017), along with an indication of whether the introduction was intentional or accidental. Species that have multi-continental distributions, and which may in addition have some introduced populations are shown at the end of the table.</p>
Radar and Lidar scattering lookup tables for atmospheric hydrometeors using a T-Matrix method and a Mie theory
<h2>Overview</h2> <p>The database includes text files containing the scattering amplitude matrices for single spherical/nonspherical particles for radar and lidar. They are the lookup tables used for calculating radar and lidar observables in the Cloud-Resolving Radar Simulator (Oue et al. 2020). The radar scattering properties were calculated for several hydrometeor categories using a T-matrix method proposed by Mishchenko (2000) accounting for incident angles, scattering direction (forward and backward), polarimetry (horizontally (H) and vertically (V) polarized waves), particle aspect ratio, phase (liquid or ice), bulk density, temperature, particle size, and radar frequency. The lidar scattering properties at a vertical incidence were calculated for spherical liquid or ice particles using the BHMIE Mie code (Bohrean and Hyffman,1998) accounting for lidar wavelength, temperature, and bulk density. The hydrometeor categories are commonly used for cloud resolving models employing bulk microphysical schemes (e.g., cloud, rain, ice cloud, snow aggregates, and graupel). Detailed descriptions are also available in the CR-SIM user guide (https://github.com/marikooue/CR-SIM/releases/tag/crsim-v3.34).</p> <h2>Data structure</h2> <p>The data files are arranged and zipped every hydrometeor types. The names of the tar-zipped directories under the top directory LLUT3 represents the hydrometer type.<br>For lidar scattering, the following directories are included:<br>ceilo: Ceilometer lidar backscatter properties at a wavelength of 905 nm<br>mpl: Micropulse lidar (MPL) backscatter properties at wavelengths of 353 and 532 nm</p> <p>For radar scattering, the following hydrometer types are included:<br>cloud: Radar scattering for liquid cloud droplets (spherical shape)<br>raina: Radar scattering for raindrops with the aspect ratio model proposed by Andsager et al. (1999)<br>rainb: Radar scattering for raindrops with the aspect ratio model proposed by Brandes et al (2002)<br>ice_ar0.90: Radar scattering for cloud ice with an aspect ratio of 0.9<br>ice_ar0.20: Radar scattering for cloud ice with an aspect ratio of 0.2<br>smallice: Radar scattering for spherical cloud ice particles<br>snow_ar0.60: Radar scattering for snowflakes with an aspect ratio of 0.6<br>graupel_ar0.60: Radar scattering for graupel particles with an aspect ratio of 0.6<br>graupel_ar0.80: Radar scattering for graupel particles with an aspect ratio of 0.8<br>graupel: Radar scattering for spherical graupel particles<br>gh_ryzh: Radar scattering for graupel particles with the graupel aspect ratio model proposed by Ryzhkov et al (2011)<br>unrimedice_ar0.40: Radar scattering for unrimed ice particles with an aspect ratio of 0.4<br>unrimedice_ar0.60: Radar scattering for unrimed ice particles with an aspect ratio of 0.6<br>unrimedice_ar0.80: Radar scattering for unrimed ice particles with an aspect ratio of 0.8<br>unrimedice: Radar scattering for spherical unrimed ice particles<br>partrimedice_ar0.40: Radar scattering for partially rimed ice particles with an aspect ratio of 0.4<br>partrimedice_ar0.60: Radar scattering for partially rimed ice particles with an aspect ratio of 0.6<br>partrimedice_ar0.80: Radar scattering for partially rimed ice particles with an aspect ratio of 0.8<br>partrimedice: Radar scattering for partially rimed spherical ice particles </p> <h2>The file name convention </h2> <p>For lidar scattering data, each file name has the following format:<br>[hydrometeor type]_[instrument name]_ [wavelength in nm]_[phase ID]_d[bulk density in kg m-3].dat<br>The hydrometeor type shows: 1) ‘cld’ for liquid cloud droplets, and 2) ‘ice’ for ice particles. The phase ID shows: 1) ‘p25’ for ceilometer liquid cloud, 2) ‘p20’ for MPL lidar liquid cloud, and 3) ‘m30’ for MPL lidar ice. </p> <p>For radar scattering data, each file name has the following format.<br>[hydrometeor type]_fr[frequency in GHz]GHz_t[temperature in K]_rho[bulk density in kg m-3]_el[elevation angle in degree].dat<br>The hydrometeor type follows the directory name presented above.</p> <h2>Format of the data files</h2> <p>Line 1: Wavelength in mm<br>Line 2: Temperature in K<br>Line 3: Refractive index (real and imaginary)<br>Line 4: Number of radii calculated and number of elevation angles<br>Line 6: Incident angle and scattered angle in degrees<br>Line 7: Radius in mm and aspect ratio<br>Line 8: Forward scattering amplitude for co-polarization VV and HH (complex number)<br>Line 9: Backward scattering amplitude for co- and cross polarizations VV, VH, HV, HH (complex number) <br>Line 10 to the end of file: Repeat Line 7 to Line 9 with different radii until the maximum radius.</p>
New Zealand Wide model 2.3 seismic velocity, Qs and Qp Tables
<p><span>This record contains uncompressed files of the tables of the </span>New Zealand Wide 2.3 velocity model, <a href="https://doi.org/10.5281/zenodo.6568301" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.6568301</a>, and New Zealand Wide 2.3 Qs and Qp models, <a href="https://doi.org/10.5281/zenodo.5098356" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.5098356</a>.</p> <p><span>The files in those previous zenodo records were compressed gz files. Some people reported that they were unable to extract the text tables from the gz files.<span> </span>This record has the same tables in full uncompressed format.</span></p>
HI line observations of 290 evolved stars made with the Nancay Radio Telescope - I. Data: online Tables
<p>--- Table B.1: Clear NRT HI detections - basic data </p> <p>Description of the columns:</p> <p>(1) Name: common catalogue name of the target. <br> An ^n after a name indicates that it is clearly not an AGB star, <br> a ^d that we consider its classification as an AGB to be dubious, <br> and a ^* indicates that notes on the object can be found in Appendix A;<br>(2,3) RA,DEC: literature right ascension and declination of the target from Gaia EDR 3, <br> for epoch J2000.0;<br>(4) Type: target type. <br> Primarily the variability type as listed in Version 5.1 of the General Catalogue of Variable Stars, <br> GCVS (A description of GCVS types is given in https://cdsarc.u-strasbg.fr/ftp/cats/B/gcvs/vartype.txt),<br> but if an object is not included in the GCVS, other identifiers are listed in brackets: <br> HPM = high proper motion star, (OH/IR) = OH/IR maser, LPVc = long-period variable candidate, <br> PN = planetary nebula, pPN = proto-planetary nebula, and post-AGB star;<br>(5,6) Spec & ref: spectral type of the star, followed by its literature reference, <br> as retrieved from the SIMBAD database. If none was listed there, the reference is noted as 'SIMBAD';<br>(7,8) Teff & ref: effective temperature of the star, in K, followed by its literature reference; <br>(9) d: distance of the target, based on its parallax (mainly from the Gaia EDR3), in pc.<br> If no Gaia parallax was available a reference to the distance we adopted is given in Appendix A<br> (for RAFGL 3099, mu Cep, and V Peg);<br>(10) Vlit: published radial velocity of the target in the LSR reference frame, in km/s;<br>(11) Vexp: literature expansion velocity measured from CO or OH 1612 MHz line observations, in km/s. <br> If a pair of values was published for a two-velocity component CO line fit, the largest value is listed here;<br>(12) ref: literature references to the published Vlit and Vexp values; <br>(13) line: spectral line on which the published radial velocity measurement (Vlit) was based;<br>(14,15) Mdot & ref: literature mass loss rates, in solar masses per year, <br> followed by its literature reference.</p> <p>Notes to Table B.1:</p> <p>References: see Table B.1 in the Astronomy & Astrophysics paper.</p> <p><br>--- Table B.2: Clear NRT HI detections - HI data </p> <p>Description of the columns:</p> <p>(1) Name: common catalogue name of the target. <br> A ^T after a name indicates that HI line parameters are based on a 'total' spectrum, whereas <br> a ^P indicates that a 'peak' spectrum was used. <br> An ^n indicates that it is clearly not an AGB star, <br> a ^d that we consider its classification as an AGB to be dubious, <br> and a ^* indicates that notes on the object can be found in Appendix A;<br>(2) VHI: our central radial velocity in the LSR reference frame of the Gaussian fitted <br> to the HI profile, in km/s.<br>(3) FWHM: our full width half maximum of the Gaussian fitted to the HI line profile, in km/s;<br>(4) Speak: our peak flux density of the HI line profile, in Jy;<br>(5) diam: our estimated angular size of the HI CSE in the east-west direction, in arcmin;<br>(6) FHI: our integrated line flux of the HI profile, in Jy km/s;<br>(7) MHI: our total HI mass, in Msun;<br>(8) HI ref: references to previously published HI studies,<br> see Table B.2 in the Astronomy & Astrophysics paper.</p> <p><br>--- Table B.3: Possible NRT HI detections - basic data</p> <p>Description of the columns:</p> <p>(1) Name: common catalogue name of the target. <br> An ^n after a name indicates that it is clearly not an AGB star, <br> a ^d that we consider its classification as an AGB to be dubious, <br> and a ^* indicates that notes on the object can be found in Appendix A;<br>(2,3) RA,DEC: literature right ascension and declination of the target from Gaia EDR 3, <br> for epoch J2000.0;<br>(4) Type: target type. <br> Primarily the variability type as listed in Version 5.1 of the General Catalogue of Variable Stars, <br> GCVS (A description of GCVS types is given in https://cdsarc.u-strasbg.fr/ftp/cats/B/gcvs/vartype.txt),<br> but if an object is not included in the GCVS, other identifiers are listed in brackets: <br> HPM = high proper motion star, (OH/IR) = OH/IR maser, LPVc = long-period variable candidate, <br> PN = planetary nebula, pPN = proto-planetary nebula, and post-AGB star;<br>(5,6) Spec & ref: spectral type of the star, followed by its literature reference, <br> as retrieved from the SIMBAD database. If none was listed there, the reference is noted as 'SIMBAD';<br>(7,8) Teff & ref: effective temperature of the star, in K, followed by its literature reference; <br>(9) d: distance of the target, based on its parallax (mainly from the Gaia ED33), in pc.<br> If no Gaia parallax was available a reference to the distance we adopted is given in Appendix A<br> (for RAFGL 3099, mu Cep, and V Peg);<br>(10) Vlit: published radial velocity of the target in the LSR reference frame, in km/s;<br>(11) Vexp: literature expansion velocity measured from CO or OH 1612 MHz line observations, in km/s. <br> If a pair of values was published for a two-velocity component CO line fit, the largest value is listed here;<br>(12) Mdot : literature mass loss rates, in solar masses per year, <br>(13) line: spectral line on which the published radial velocity measurement (Vlit) was based;<br>(14) ref: literature references to the published Vlit, Vexp and Mdot values; </p> <p>Notes to Table B.3:</p> <p>References: see Table B.1 in the Astronomy & Astrophysics paper.</p> <p><br>--- Table B.4: Possible NRT HI detections - HI data</p> <p>Description of the columns:</p> <p>See the description of the columns of Table B.2.</p> <p><br>--- Online only Table 5: Upper limits to NRT HI lines </p> <p>Description of the columns:</p> <p>(1) Name: common catalogue name of the target. <br> An ^n after a name indicates that it is clearly not an AGB star, <br> a ^d that we consider its classification as an AGB to be dubious, <br> and a ^* indicates that notes on the object can be found in Appendix A;<br>(2,3) RA,DEC: literature right ascension and declination of the target from Gaia EDR 3, <br> for epoch J2000.0;<br>(4) Type: target type. <br> Primarily the variability type as listed in Version 5.1 of the General Catalogue of Variable Stars, <br> GCVS (A description of GCVS types is given in https://cdsarc.u-strasbg.fr/ftp/cats/B/gcvs/vartype.txt),<br> but if an object is not included in the GCVS, other identifiers are listed in brackets: <br> HPM = high proper motion star, (OH/IR) = OH/IR maser, LPVc = long-period variable candidate, <br> PN = planetary nebula, pPN = proto-planetary nebula, and post-AGB star;<br>(5,6) spec & ref: spectral type of the star, followed by its literature reference, <br> as retrieved from the SIMBAD database. If none was listed there, the reference is noted as 'SIMBAD';<br>(7,8) Teff & ref: effective temperature of the star, in K, followed by its literature reference; <br>(9) d: distance of the target, based on its parallax (mainly from the Gaia EDR3, in pc.<br> If no Gaia parallax was available a reference to the distance we adopted is given in Appendix A<br> (for RAFGL 3099, mu Cep, and V Peg);<br>(10) Vlit: published radial velocity of the target in the LSR reference frame, in km/s;<br>(11) Vexp: literature expansion velocity measured from CO or OH 1612 MHz line observations, in km/s. <br> If a pair of values was published for a two-velocity component CO line fit, the largest value is listed here;<br>(12) Mdot : literature mass loss rates, in solar masses per year, <br>(13) ref: literature references for Vlit, Vexp and Mdot, as applicable;<br>(14) line: spectral line on which the published radial velocity measurement (Vlit) was based;<br>(15) Speak: peak flux density of our HI line profile, in Jy;<br>(16) notes: 'old data' indicates objects observed only in 1992/1993, before the renovation of the NRT; <br> 'blue/red side' indicates that either the blue or red side of the HI profile could be used to measure <br> an upper limit to the line flux;<br>(17) HI ref: references to previously published HI studies;</p> <p>Notes to online only Table 5: </p> <p>HI references: see Table B.2 in the Astronomy & Astrophysics paper.<br>Other references: see Table B.1 in the Astronomy & Astrophysics paper.</p> <p><br>--- Online only Table 6: Confused NRT HI spectra</p> <p>Description of the columns:</p> <p>(1) Name: common catalogue name of the target. <br>(2,3) RA, DEC: literature right ascension and declination of the target from Gaia EDR3, <br> for epoch J2000.0; <br>(4) type: target type. Primarily the variability type as listed in Version 5.1 of the <br> General Catalogue of Variable Stars, GCVS; but if an object is not included in the GCVS, <br> other identifiers are listed in brackets: HPM = high proper motion star, (OH/IR) = OH/IR maser, <br> LPVc = long-period variable candidate, PN = planetary nebula, pPN = proto-planetary nebula, <br> and post-AGB star; <br>(5,6) spec & ref spectral type of the star, followed by its literature reference, <br> as retrieved from the SIMBAD database. If none was listed there, the reference is noted as 'SIMBAD'; <br>(7,8) Vlit & ref: published radial velocity of the target in the LSR reference frame, in km/s; <br>(9) line: spectral line on which the published radial velocity measurement (Vlit) was based; <br>(10) notes: 'old data' denotes objects observed only in 1992/1993, before the renovation of the NRT<br> (see Section 3), for which no observations in digital form are available; <br>(11) HI ref: references to previously published HI studies.</p> <p>Notes to online only Table 6:</p> <p>HI references: see Table B.2 in the Astronomy & Astrophysics paper.<br>Other references: see Table B.1 in the Astronomy & Astrophysics paper.</p>
Metagenome-Assembled Genomes Abundance & Activity Tables. Environmental Parameters Associated with the dataset.
<p>Lake Mendota, WI, USA, is a temperate lake subject to annual temperature and oxygen fluctuations. Each summer, the water column becomes anoxic (no-oxygen). In 2020, we sampled the lake at weekly intervals, at different depths (5, 10, 15, 20 and 23.5m). For each time+depth sample, we collected metagenomes, viromes and metatranscriptomes. Environmental data profiles were collected on-site for each sampling day. </p> <p>Following standard metagenomic binning best practices, we obtained 431 metagenomes-assembled-genomes (MAGs).</p> <p>This record comprises the microbial abundance and expression table for these MAGs, and the environmental profiles collected each day.</p>
Arabidopsis thaliana circadian mRNA-seq gene expression processed tables from Romanowski et al., TPJ 2020.
<p>This dataset is an add-on for Romanowski et al., TPJ 2020 (https://doi.org/10.1111/tpj.14776) containing processed files for the circadian RNAseq data in tab delimited txt format.</p> <p><br> Here, you can the raw counts file, the normalized CPM values, and the full JTK result (without recalculated circadian phases, just the original ones). All genes with a read density > 0.05 in at least one timepoint were considered expressed. The read density is calculated as the amount of reads divided by the effective length of a gene (total reads / length). Genes rd file is also included.</p> <p>Some useful notes:<br> 1) Counts were assigned using ASpli and the AtRTDv2 annotation (34,212 genes).<br> 2) After filtering by rd we had a total of 18,503 expressed genes.<br> 3) 13,256 genes passed the QL F-tests.<br> 4) 9,127 genes were rhythmic according to JTK_cycle. </p> <p>For detailed protocols, please see Romanowski et al., TPJ 2020 (https://doi.org/10.1111/tpj.14776)</p> <p>The RNA-seq raw data supporting the conclusions of this article have been deposited in ArrayExpress (Kolesnikov et al., 2015) at EMBL-EBI (www.ebi.ac.uk/arrayexpress), under accession numbers E-MTAB-7933.</p> <p>All relevant custom r scripts are available at https://github.com/aromanowski/Circadian_rhythms_and_alternative_splicing</p>
Catalog of synthetic seismic records from mineral physics and travel-time tables from Waszek et al., 2021, Nature Geoscience
<p>This release is associated with the accepted publication in Nature Geoscience:</p> <p>Waszek L., Tauzin B., Schmerr N., Ballmer M. and Afonso J.C. A poorly mixed mantle transition zone and its thermal state inferred from seismic waves. Nature Geoscience, 2021.</p> <p>This dataset must be used in conjunction with the NoLimit software package (https://zenodo.org/record/5512805).</p> <p>Both the software and dataset allow the prediction of synthetic seismic waveforms for SS and PP-precursors from mineral physics models, as well as their processing for reconstructing the surface of seismic boundaries associated with major mineralogical phase transitions in the Earth’s mantle (namely, the 410-km and 660-km depth discontinuities).</p> <p>For technical reasons (storage and quick access), the catalog is downsampled with respect to the one in Waszek et al. (2021), and it is provided with the HDF5 format. For more advanced applications such as changing mantle composition, or generating waveforms for deeper earthquakes, please contact Benoit Tauzin (benoit.tauzin@univ-lyon1.fr) and Lauren Waszek (lauren.waszek@jcu.edu.au).</p> <p>The dataset includes:</p> <p>* A fixed mantle composition, which is a mechanical mixture of basalt and harzburgite with a fraction of basalt f=0.2.<br> * A downsampled catalog of synthetic waveforms for event depths between 0 and 80 km by step of 10 km (enough for reproducing the processing of observed SS and PP precursors waveforms).<br> * Adiabatic temperature gradients with potential temperature Tpot between 1200 and 2100 K by step of 100 K.</p> <p>This catalog and associated travel-time tables will allow any user to generate synthetic waveforms for any moment tensor, and events within the pre-defined depth interval.<br> </p> <p><strong>How to cite this material?</strong></p> <p>Any use of the datasets or software must refer to:</p> <p>The reference paper: Waszek L., Tauzin B., Schmerr N., Ballmer M., Afonso J.C. A poorly mixed mantle transition zone and its thermal state inferred from seismic waves. Nature Geoscience. 2021.<br> <br> Software: Tauzin, Benoit, & Waszek, Lauren. (2021). NoLiMit MATLAB package v1.0. Non-Linear Bayesian partition Modeling of the Earth's Mantle Transition zone (Version 1). Zenodo. https://doi.org/10.5281/zenodo.5512805<br> <br> Datasets: Tauzin, Benoit, Waszek, Lauren, & Afonso, Juan Carlos. (2021). Catalog of synthetic seismic records from mineral physics and travel-time tables from Waszek et al., 2021, Nature Geoscience (Version 1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.5512035</p>
QST - open data of the article Vanwindekens & Hardy (2022) - table 1 soil properties
<p>Soil properties of the long term fields trials linked to the paper "The QuantiSlakeTest, dynamic weighting of soil under water to measure soil structural stability" submitted to the SOIL journal by Vanwindekens & Hardy (2022).</p>
MICrONS Layer 2/3 Data Tables
<p>These are data tables released as part of the MICrONS project, and contain annotations on the EM data and reconstructions. You can find more information about the dataset and the project at microns-explorer.org. </p>
Blind Prediction Competition - Sera.ta - Seismic Response of Masonry Cross Vaults: Shaking table tests and numerical validations
<p>Masonry vaults play a much relevant role in the seismic response of heritage masonry buildings, ranging from housing to the greatest cathedrals. Acting as both a ceiling and a structural horizontal diaphragm with significant mass, their mechanical behaviour affects the overall seismic response of buildings, in terms of strength, stiffness, and ductility. Moreover, local damage and collapse of vaults may produce significant losses in terms of cultural assets and casualties. In spite of the importance of this topic, the evaluation of the complex three-dimensional behaviour of vaults is still an important challenge for researchers. The main objectives of the present research project are:<br> 1) to better understand the seismic behaviour of masonry cross vaults by means of shaking table tests on both full-scale and small-scale models;<br> 2) to assess the capability of different modelling/analysis approaches to predict the seismic response of these masonry structures.</p> <p>In particular, three sets of shaking table tests are planned:<br> a. Tests on a 1:1 scale model of a brick unreinforced masonry cross vault: to investigate the behaviour of brick masonry cross vaults under different seismic inputs, in terms of damage, displacement capacity and peak acceleration.<br> b. Tests on a 1:1 scale model of a brick reinforced masonry cross vault: to evaluate the effectiveness of reinforcing techniques to repair the vaults tested in a).</p> <p>In addition to the experimental tests, a blind prediction competition is performed to assess the efficacy of different modelling strategies and analysis techniques. The final aims are to improve the safety assessment procedures proposed for historic masonry buildings in Eurocode 8.3 and to provide better seismic assessment techniques and strengthening measures.</p>
15000 Ellipsoidal Binary Candidates in TESS: Associated Tables
<p>A catalogue of 15779 candidate ellipsoidal binary systems, identified from the first two years of TESS full-frame images.</p> <p>Table 2 contains the 'BEER' score applied to approximately 8,000,000 input TESS targets.</p> <p>Table 3 contains the details of the 15779 selected candidates.</p> <p>Full details of both tables, and the selection process, can be found in the associated paper.</p> <p>https://arxiv.org/abs/2211.06194</p>
Table 2 (JAS - Wendt and Peters 2023)
<p>Source-related biomarker ratios and predicted families of fourteen oil/seep and artifact samples, Table 2 in "Ancient Olmec tar trade revealed by combined biomarker and chemometric analysis" by Carl J. Wendt and Kenneth E. Peters</p> <p>Table 2. Predicted families of fourteen oil/seep and artifact samples from the study area based on a two-tier SIMCA (soft independent modeling of class analogy) model constructed from the 97-sample training set in Table E1. The five samples from Rancho Orel, Salinas, Bat 2 Ogarrio, PO-22*, PO:23*, and SA:61A* have zero values for predicted family because they lack affinity to the families established by chemometric study of the training set. Asterisks identify archaeological artifacts. Plus signs ‘+’ in the description column identifies samples published previously (Wendt and Lu, 2006).</p>
Table E1 (JAS - Wendt and Peters 2023)
<p><strong>Source-related Biomarker Ratios, </strong><strong>Table E.1 </strong>in <strong>"</strong>Ancient Olmec tar trade revealed by combined biomarker and chemometric analysis" by Carl J. Wendt and Kenneth E. Peters</p> <p>From <strong>Supplementary Materials: Appendix E. </strong></p> <p><strong>Table E1.</strong> Source-related biomarker ratios and locations for ninety-seven produced oil, seep, modern use items (oil/seep) and Olmec artifacts (asterisks) arranged by genetic family based on hierarchical cluster analysis. Four samples omitted from the analysis (designated as Family 0) violated sample residual and/or Mahalanobis distance outlier diagnostics. Asterisks identify archaeological artifacts. Plus signs ‘+’ in the description column identifies samples published previously in Wendt and Lu (2006).</p>
Data for Figures 4, A-F and Table J of Publication "Blue skies over China: The effect of pollution-control on solar power generation and revenues"
<p>This repository contains the data to produce Figures 4, A-F and Table J and emission data in the paper:</p> <p>"Labordena M, Neubauer D, Folini D, Patt A, Lilliestam J (2018) Blue skies over China: The effect of pollution-control on solar power generation and revenues. PLoS ONE 13(11): e0207028. https://doi.org/10.1371/journal.pone.0207028"</p> <p>Note that the scripts are to be found in the accompanying package (https://doi.org/10.5281/zenodo.8130726)</p>
Table 1. Lithostratigraphy of the middle Eocene in Paris basin (Brachert et al., 2023, Paleoceanography and Paleoclimatology)
<p>Lithostratigraphy of the middle Eocene in Paris basin (Blondeau, 1965; Gély, 1996). Coordinates for the neostratotype Saint-Vaast-lès-Mello (49.267778°, 2.393056°). Elementary sequences according to Gély (Gély and Leroux, 2019; Merle, 2008), modified for Bartonian parasequences (Briais, 2015). Thickness from Cavelier and Le Calvez (1965), Mégnien and Mégnien (1980) and Merle (2008); decompaction number according to Goldhammer (1997).</p>
Marcell Experimental Forest monthly upland water table elevation, 1962 - ongoing
This data publication contains monthly upland ground water table elevation data collected from 1962-ongoing at the Marcell Experimental Forest (MEF) in Itasca County, Minnesota, which is operated and maintained by the USDA Forest Service, Northern Research Station. The data come from upland monitoring wells in six watersheds (with peatlands) that are instrumented for hydrologic monitoring.
Baltimore Ecosystem Study: Long-Term Monitoring of Riparian Water Table Depth and Groundwater Chemistry
Long-term monitoring of riparian water tables and groundwater chemistry began in 2000 along four first or second order steams in and around the Gwynns Falls watershed in Baltimore City and County, MD. One site (Oregon Ridge) is in the completely forested Pond Branch catchment that serves as a ""reference"" study area for the Baltimore LTER (BES). Two sites (Glyndon, Gwynbrook) were in suburban areas of the watershed; one just upstream from the Glyndon BES long-term stream monitoring site in the headwaters of the Gwynns Falls, and one along a tributary that enters the Gwynns Falls just above the Gwynnbrook BES long-term stream monitoring site farther downstream. The final, urban site (Cahill) was along a tributary to the Gwynns Falls in Leakin Park in the urban core of the watershed. Water table data and more detailed descriptions of soils, vegetation, stream channel properties and microbial processes at these sites can be found in Groffman et al. (2002, Environmental Science and Technology 36:4547-4552) and Gift et al. (2010, Restoration Ecology 18:113-120).
Eight Mile Lake Research Watershed, Carbon in Permafrost Experimental Heating and Drying Research (DryPEHR): Seasonal water table depth data, 2011-2022
This drying and warming experiment addresses the following questions: 1) Does ecosystem drying, warming and permafrost thaw cause a net release or uptake of C from the ecosystem to the atmosphere?, 2) Does the decomposition of old C that comprises the bulk of the soil C pool influence ecosystem C loss? 3) How do drying and warming affect plant communities and ecosystem properties? We are answering these questions using a combined warming and drying experiment (DryPEHR), which is situated with the Carbon in Permafrost Experimental Heating Research (CiPEHR) project and located in an upland tundra field site near Healy, Alaska in the foothills of the Alaska Range. Warming treatment here refers to growing season air temperature warming (~1C) using open top chambers (OTC) combined with soil 'warming' using snow fences during the snow covered months. Drying is achieved using an automated pumping system that lowers the water table in the dry plots. Soil warming began in 2008; OTCs and drying in 2011. This data includes water table depth measurements collected from the drying experiment (dry and control) at DryPEHR and winter warming and control treatment plots at CiPEHR for the ice-free period of 2011-2020.
Eight Mile Lake Research Watershed, Thaw Gradient: Seasonal water table depth from 2004-2024
In this larger study, we are asking the question: Is old carbon that comprises the bulk of the soil organic matter pool released in response to thawing of permafrost? We are answering this question by using a combination of field and laboratory experiments to measure radiocarbon isotope ratios in soil organic matter, soil respiration, and dissolved organic carbon, in tundra ecosystems. The objective of these proposed measurements is to develop a mechanistic understanding of the SOM sources contributing to C losses following permafrost thawing. We are making these measurements at an established tundra field site near Healy, Alaska in the foothills of the Alaska Range. Field measurements center on a natural experiment where permafrost has been observed to warm and thaw over the past several decades. This area represents a gradient of sites each with a different degree of change due to permafrost thawing. As such, this area is unique for addressing questions at the time and spatial scales relevant for change in arctic ecosystems.
PIE LTER, marsh surface marker horizon measurements at each Surface Elevation Table (SET) site, Rowley, MA.
Marker horizon depth measurements at each Surface Elevation Table (SET) site. Marker horizons are commonly used in conjunction with the SET. Marker horizons measure vertical accretion which predominantly incorporates surface processes.
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.