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Figure 1 in Assessing high compositional differences of beetle assemblages across vertical woodland strata in the New Forest, Hampshire, England
Figure 1. Correspondence analysis ordination of subfamily/family level showing separation between the sampling methods. Eigenvalue axis 1: 0.4953, variation 45.14; axis 2: 0.2668, variation 69.47. Key to subfamily/family abbreviations – Carabida: Carabidae, Hydrophl: Hydrophilidae, Leiodida: Leiodidae, Omaliina: Omaliinae, Pselaphn: Pselaphinae, Phloeocr: Phloeocharinae, Tachypor: Tachyporinae, Habrocer: Habrocerinae, Aleochar: Aleocharinae, Oxytelin: Oxytelinae, Scaphidi: Scaphidiinae, Scydmaen: Scydmaeninae, Paederin: Paederinae, Staphyln: Staphylininae, Geotrupd: Geotrupidae, Scirtida: Scirtidae, Throscid: Throscidae, Elaterid: Elateridae, Canthard: Cantharidae, Ptiliida: Ptiliidae, Anobiida: Anobiinae, Malachii: Malachiidae, Sphindid: Sphindidae, Nitiduld: Nitidulidae, Cryptoph: Cryptophagidae, Coccinel: Coccinellidae, Coryloph: Corylophidae, Latridii: Latridiidae, Melandry: Melandryidae, Tenebrio: Tenebrionidae, Salpingd: Salpingidae, Scraptii: Scraptiidae, Cerambyc: Cerambycidae, Crytocp: Cryptocephalinae, Chrysoml: Chrysomelinae, Galerucn: Galerucinae, Rhynchit: Rhynchitidae, Apionida: Apionidae, Curculio: Curculioninae, Cossonin: Cossninae, Entimina: Entiminae, Molytina: Molytinae, Scolytin: Scolytinae.
Illuminating the impact of diel vertical migration on visual gene expression in deep-sea shrimp
<p>Diel vertical migration (DVM) of marine animals represents one of the largest migrations on our planet. Migrating fauna are subjected to a variety of light fields and environmental conditions that can have notable impacts on sensory mechanisms, including an organism's visual capabilities. Among deep-sea migrators are oplophorid shrimp, that vertically migrate hundreds of meters to feed in shallow waters at night. These species also have bioluminescent light organs that emit light during migrations to aid in camouflage. The organs have recently been shown to contain visual proteins (opsins) and genes that infer light sensitivity. Knowledge regarding the impacts of vertical migratory behavior, and fluctuating environmental conditions, on sensory system evolution is unknown. In this study, the oplophorid <i>Systellaspis debilis</i> was either collected during the day from deep waters or at night from relatively shallow waters to ensure sampling across the vertical distributional range. <i>De novo </i>transcriptomes of light sensitive tissues (eyes/photophores) from the <i>Day/Night </i>specimens were sequenced and analyzed to characterize opsin diversity and visual/light interaction genes. Gene expression analyses were also conducted to quantify expression differences associated with DVM. Our results revealed an expanded opsin repertoire among the shrimp and differential opsin expression that may be linked to spectral tuning during the migratory process. This study sheds light on the sensory systems of a bioluminescent invertebrate and provides additional evidence for extraocular light sensitivity. Our findings further suggest opsin coexpression and subsequent fluctuations in opsin expression may play an important role in diversifying the visual responses of vertical migrators.</p>
Figure 4 in Inter-oceanic comparison of planktonic copepod ecology (vertical distribution, abundance, community structure, population structure and body size) between the Okhotsk Sea and Oyashio region in autumn
Figure 4. Copepod species composition (centre) and copepodid stage structures of the dominant species (left: Oyashio region, right: Okhotsk Sea). All data are integrated means of a 0– 500 m water column based on the IONESS samples in the Oyashio region (St. 19) and Okhotsk Sea (St. OK24) from October to November 1996. Error bars for the copepodid stage indicate standard deviations of each daily duplicate.
Figure 3 in Inter-oceanic comparison of planktonic copepod ecology (vertical distribution, abundance, community structure, population structure and body size) between the Okhotsk Sea and Oyashio region in autumn
Figure 3. Vertical distribution of zooplankton biovolume in the Oyashio region (upper panels) and Okhotsk Sea (lower panels) from September to December in 1996–1998. Note that the biovolume axes are not the same between panels. Tc: thermocline.
CONUS crustal vertical velocities 2007-2017
<p>This dataset includes vertical velocity fields derived from Global Positioning System (GPS) daily positions from 2007-2017, in the IGS08 reference frame. Residual velocities after removing glacial isostatic adjustment model (ICE6GD), elastic deformation due to GRACE-derived hydrologic loading, and Earth's geocenter motion are also presented. Description of data, methods, and results are documented in the following peer-reviewed publication:</p> <p>Lau, N., Borsa, A.A., & Becker, T.W. (2020). Present-day crustal vertical velocity field for the contiguous United States. Journal of Geophysical Research: Solid Earth, 125, e2020JB020066. https://doi.org/10.1029/2020JB020066</p> <p>This NETCDF file contains the following nine subsets:</p> <ol> <li>'lat', latitude, centerd in 0.25-degree grid cell.</li> <li>'lon', longitude, centered in 0.25-degree grid cell.</li> <li>'gps_vu', gps derived vertical velocities, in millimeters.</li> <li>'gps_vu_smooth', gps derived vertical velocities smoothed by 300-km Gaussian filter; in millimeters.</li> <li>'gps_uncertainties', one-sigma uncertainty estimates for 'gps_vu'; in millimeters.</li> <li>'gps_vu_poro', gps derived vertical velocities, including stations strongly affected by poroelastic effect; in millimeters.</li> <li>'grace_vu', velocities due to hydrologic elastic loading estimated by GRACE; in millimeters.</li> <li>'net_vu', velocities after removing GRACE hydrolog, ICE6GD glacial isostatic adjustment model, and Earth's geocenter motion from 'gps_vu'; in millimeters.</li> <li>'net_vu_smooth',velocities after removing GRACE hydrolog, ICE6GD glacial isostatic adjustment model, and Earth's geocenter motion from 'gps_vu_smooth'; in millimeters.</li> </ol> <p> </p>
Vertical Wind and Temperature Gravity Wave Perturbations Derived from Na Lidar Observations
<p>The gravity wave perturbations associated with vertical wind and temperature in the mesopause region for heat flux calculations. </p>
Vertical Compositional Variations of liquid hydrocarbons in Titan's Alkanofers
<p>This data set is composed of six archives (.TAR) which collect input and output files from GROMACS (2018 version) simulations on binary and ternary mixtures representative of liquids in Titan's alkanofers:<br> 3000CH4+1000C2H6+1000N2_90K.tar<br> 3000CH4+1000C2H6+1000N2_95K.tar<br> 4000CH4+1000C2H6_90K.tar<br> 4000CH4+1000C2H6_95K.tar<br> 4000CH4+1000N2_90K.tar<br> 4000CH4+1000N2_95K.tar</p> <p>The system under study is always composed of 5000 molecules. Simulations at 90 K correspond to a pressure of 1.5 bar while those at 95K correspond to a pressure of 120 bar.</p> <p>Each archive contains 5 directories:</p> <p>1)<strong> INPUTS:</strong> It contains all the GROMACS input files (.GRO, .ITP, .TOP) needed to build the simulation box as well as the files required to prepare the molecular dynamics (MD) simulations (.MDP and .TPR). More details about the content of these files is available in the GROMACS manual (https://www.gromacs.org/).<br> 2 README files are added to inform the reader on useful GROMACS commands used here:<br> - README_box.txt: commands to build the simulation box.<br> - README_NVT+NPT-runs.dat: commands to run MD simulations and treat some data.</p> <p>2) <strong>NVTOUT_EQ</strong>: It contains all the files related to the 1-ns NVT equilibration phase, namely, the script for job submission (.SH) together with the related standard ouput files (.OUT and .ERR), and typical GROMACS output files (.GRO, .LOG, .EDR, .TRR, .CPT).<br> Post-treatment data are collected in 2 files:<br> - stats_nvt-eq.dat: Average potential energy, kinetic energy, total energy, temperature and pressure.<br> - energy_nvt-eq.xvg: Potential energy (col. 2), kinetic energy (col. 3), total energy (col. 4), temperature (col. 5), and pressure (col. 6) as a function of time (col.1).</p> <p>3) <strong>NPTOUT_EQ</strong>: It contains the same kind of files as NVTOUT_EQ but for the first 9 ns of the 19-ns NPT equilibration phase.<br> Post-treatment data are collected in 2 files:<br> - stats_npt-eq.dat: Average potential energy, kinetic energy, total energy, temperature, pressure, volume, density, and enthalpy.<br> - energy_npt-eq.xvg: Potential energy (col. 2), kinetic energy (col. 3), total energy (col. 4), temperature (col. 5), and pressure (col. 6), volume (col.7), density (col.8), and enthalpy (col. 9) as a function of time (col. 1).</p> <p>4) <strong>NPTOUT_EQ-RERUN1</strong>: It contains the same kind of files as NPTOUT_EQ but for the last 10 ns of the 19-ns NPT equilibration phase.</p> <p>5) <strong>NPTOUT_ACC</strong>: It contains the same kind of files as NPTOUT_EQ but for the 10-ns NPT accumulation phase. Additional data files also provide diffusion coefficients and shear viscosities depending on the mixture under consideration (see below).</p> <p><em>For binary mixtures</em>, the mean squared displacements (MSD) of species and the corresponding diffusion coefficients are estimated with the "gmx msd" GROMACS command.<br> Data are collected in two files:<br> - msd-CH4.xvg / msd-C2H6.xvg / msd-N2.xvg: MSD (col. 2) as a function of time (col. 1). The value of the corresponding diffusion coefficient (in cm<sup>2 </sup>s<sup>-1</sup>) is indicated as a comment in the preamble of these files.<br> - DCH4.dat / DC2H6.dat / DN2.dat: Estimated diffusion coefficient (in cm<sup>2 </sup>s<sup>-1</sup>) for the three moelcules under study.</p> <p><em>For ternary mixtures</em>, transverse current autocorrelation functions (TCAF) are computed with the "gmx tcaf" GROMACS command to get values of the shear viscosity:<br> - tcaf-slurm.sh, tcaf.out tcaf.xvg. tcaf_all.xvg, tcaf_cub.xvg, tcaf_fit.xvg: script (.SH) and several output files with transverse current autocorrelation functions (.XVG).<br> - visc_k.xvg: shear viscosity (col.2) as a function of the wave number (col.1). The last four viscosities can be fitted to get the shear viscosity at infinite wavelength (see GROMACS manual).</p>
Supplementary Material: A Large-Eddy Simulation Study of Vertical Axis Wind Turbine Wakes in the Atmospheric Boundary Layer
<p>Supplementary material for <em>Energies</em> <strong>2016</strong>, <em>9</em>, 366; doi:10.3390/en9050366:</p> <p><strong>Video S1:</strong> Normalized instantaneous streamwise velocity field both on a vertical plane (<em>x</em>-<em>z</em>) going through the center of the turbine and on a horizontal plane at the equator height of the turbine (Note: the physical time corresponding to this video is 1 minute and 17 seconds, and the size of the blades is magnified for illustration purposes).</p> <p><strong>Video S2:</strong> Normalized instantaneous streamwise velocity field on a horizontal plane at the equator height of the turbine for two cases: when the turbine starts to operate (top) and when the flow has reached statistically steady condition (bottom) (Note: the physical time corresponding to both videos is 1 minute and 17 seconds, and the size of the blades is magnified for illustration purposes).</p>
EAST-WEST and VERTICAL deformation maps of Alto Tiberina Fault supersite: The Post-Proc service in Geohazard Exploitation Platform applied to Sentinel-1 dataset
<p>In the framework of the ESA funded project “MEMpHIS - Multi Scale and Multi Hazard Mapping Space based Solutions ”, the Istituto Nazionale di Geofisica e Vulcanologia (INGV) together with TRE-ALTAMIRA, generated the EAST-WEST and VERTICAL deformation maps of Alto Tiberina Fault supersite. The two maps of ground velocity were derived thanks to the adoption of a specific tool named "Post-Proc", implemented in MEMPHIS and with the support of Terradue, that is able to automatically re-project on the east-west and vertical directions the ascending and descending InSAR time series. In particular, the output refers to the deformation maps calculated by processing with SqueeSAR (TM) method, a large dataset acquired by the ESA Sentinel-1 mission.</p> <p>The Post-Proc tool also calculates the mean accelerations associated to each persistent scatterer in the scenes. Some additional features are also available from this tool:</p> <p>- Change the coherence threshold for selecting a subset of persistent scatterers</p> <p>- Activate a geometrical distortion filter to take into account the layover and foreshortening effects</p> <p>- Change the reference point (position and coherence)</p> <p>- Choose between two types of accelerations: 2<sup>nd</sup> order model or velocity derivative</p> <p>- Choose among three different projection: east-west, vertical, and downslope.</p> <p>The present dataset is composed of the EAST-WEST and VERTICAL acceleration maps. The data are in shapefile format: for each record (PS) the topography, velocity, acceleration, and InSAR coherence is reported.</p>
Model output and figure code for "Tradeoffs Between Vertical and Lateral Resilience in a Salt Marsh Restoration Model"
<p>Simulation output data from COLT_Restorations model stored on the Community Surface Dynamics Modeling System public model repository at <a href="https://csdms.colorado.edu/wiki/Model:COLT_Restorations">https://csdms.colorado.edu/wiki/Model:COLT_Restorations</a> and on a GitHub public repository at<a href="https://github.com/mbbarksdale/CoLT_Restorations"> https://github.com/mbbarksdale/CoLT_Restorations</a>.</p> <p>These data were processed and graphed with model code that can also be found in a GitHub public repository at <a href="https://github.com/mbbarksdale/COLTRestorationsPaper_dataANDfigures">https://github.com/mbbarksdale/COLTRestorationsPaper_dataANDfigures</a>. </p>
Vertical profiles of stable water isotopes and thermodynamic properties from research flights during the L-WAIVE field campaign in June 2019
<p>This datasets contains the measurements of stable water isotopes conducted during the Lacustrine-Water vApor Isotope inVentory Experiment (L-WAIVE) field campaign taking place in June 2019 in the Annecy valley in the French Alps (Chazette et al. 2021). The measurements were conducted using a Picarro laser spectrometer L2130-i that was installed on an ultralight aircraft. The Picarro measurements of atmospheric humidity are merged measurements of thermodynamic properties by a fast-response temperature and humidity probe (iMet XQ-2; see also Chazette et al. 2021) interpolated on 10s temporal resolution.</p> <p>The data is provided on a one file per flight. All variables are described in README.</p> <p>This dataset has been used in Thurnherr et al. (submitted) for a comparison study of stable water isotopes measurements from various platforms and COSMOiso model simulations.</p>
Numerical simulation of the equatorial plasma bubble: the effect of seeding by the vertical winds and random background noise perturbations.
<p>A wide variety of small-amplitude waves widely exist in the ionosphere and have significant effects on the evolution of equatorial plasma bubbles. In this paper, we simulated equatorial plasma bubbles (EPB) seeded by vertical neutral wind perturbations with wavelengths of 125 km and 250 km, and compared the morphology characteristics of plasma bubble structures with those under random noise perturbations in the background density. The numerical results showed that both vertical winds and random background noise perturbations can contribute to the growth of plasma bubbles, and the perturbations under additional random background noise can promote the growth of the plasma bubble structures faster. Additionally, several processes of the nonlinear behavior of bifurcated EPB structures, including bifurcation, pinching, and small-scale turbulent structures, were successfully obtained. Our simulation captured supersonic flows within the low-density plasma structures characterized by vertical velocities of about 1.5 km/s, which is consistent with experimental studies found in the literature.</p>
Vertical profiles of air temperature, relative humidity, wind speed and direction observed using UAV over the Mukhrino peatland in June 2022
<p>Vertical profiles of air temperature and relative humidity were measured using the iMetXQ2 sensor onboard DJI Phantom 4 quad-copter; vertical profiles of wind speed and direction were obtained from the Phantom 4 flight logs as produced by the DJI proprietary algorithm. </p>
Rates of species turnover across elevation vary with vertical stratum in rainforest ant assemblages
<p>Climatic variation at local scales can influence both exposure and sensitivity of organisms and thereby scale up to influence population persistence and community composition across broader geographic extents. Tropical forest canopies are more climatically dynamic than the understorey. Consequently, the niche space of forest canopies has higher overlap in thermal conditions along elevation gradients, which imposes less of a climatic barrier to arboreal species than their ground-dwelling counterparts. We use ant communities of the Australian Wet Tropics to test the prediction that ground communities should have higher rates of species turnover over elevation compared to arboreal communities. We sampled ground and arboreal ants along elevation gradients at a bioregional scale that includes four mountain sub-regions. We assessed community composition at three spatial resolutions (regional, elevation, vertical) and then calculated beta diversity (species turnover) over elevation for ground and arboreal communities using null modelling procedures to compare different-sized species pools. Vertical niche affinity was a strong contributor to overall biogeographic patterns; indicated by a strong interaction between vertical niche and elevation in beta diversity models. On average, the ground community exhibited a pronounced elevational distance-decay pattern while the arboreal community showed no pattern. Mean species turnover was 36% higher in ground than arboreal communities. Our findings suggest that the vertical niche has a pronounced effect on biogeographic patterns which has important implications for understanding the role of local scale climate conditions in shaping communities and for potential responses to future climate change.</p>
Radar high resolution vertical velocity
<p>High temporal resolution vertical velocity profiles from 205 MHz wind profiler radar at Cochin university of science and technology</p>
Dataset and R code used in "Environmental filtering governs consistent vertical zonation in sedimentary microbial communities across disconnected mountain lakes"
<p>Dataset and R code used for the manuscript:</p> <p>Von Eggers, J. M., Wisnoski, N. I., Calder, J. W., Capo, E., Groff, D. V., Krist, A. C., & Shuman, B. (2024). Environmental filtering governs consistent vertical zonation in sedimentary microbial communities across disconnected mountain lakes. <em>Environmental Microbiology</em>, 26(3), e16607.</p> <p>This dataset and code are also available on GitHub (<a href="https://github.com/jvoneggers/WYLakeSedMicrobes">https://github.com/jvoneggers/WYLakeSedMicrobes</a>).</p>
Codes and Data for "Vertically resolved analysis of the Madden-Julian Oscillation highlights the role of convective transport of moist static energy"
<p>This file contains the analysis code and a condensed version of data to reproduce figures in the paper "Vertically resolved analysis of the Madden-Julian Oscillation highlights the role of convective transport of moist static energy". </p>
Figure 6 in Evaluation of vertical and horizontal changes in community structure of zooplankton in a deep dam lake
Figure 6. CCA triplots for zooplankton abundance and environmental variables (variables are represented by arrows. Species are depicted by points; the numbers indicate sampling stations). Abbreviations: K.coch: K. cochlearis; K.quad: K. quadrata; K.trop: K. tropica; K.long: K. longispina; P.vulg: P. vulgaris; P.doli: P. dolichoptera; S.oblo: S. oblonga; A.prio: A. priodonta; A.brig: A. brightwelli; L.pate: L. patella; L.rhom: L. rhomboides; L.quad: L. quadridentata; Habro.: Habrotrocha sp.; F.long: F. longiseta; D.cucu: D. cucullata; D.long: D. longispina; B.long: B. longirostris; C.spha: C. sphaericus; C.rect: C. rectangula; Cyc sp: Cyclops sp.; Naup: nauplius.
Figure 4 in Evaluation of vertical and horizontal changes in community structure of zooplankton in a deep dam lake
Figure 4. The Shannon–Weaver species diversity index (Hʹ) based on numbers of individuals during the study period.
Figure 1 in Evaluation of vertical and horizontal changes in community structure of zooplankton in a deep dam lake
Figure 1. Map of Karakaya Dam Lake on the Euphrates River in eastern Anatolia. Sampling stations surveyed in this study are indicated.
ScienceDex guides
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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.