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4,681 results for “light”
Atomic spin-controlled non-reciprocal Raman amplification of fibre-guided light
<p>This repository contains the data used in an experiment that demonstrates atomic spin-controlled non-reciprocal Raman amplification of fibre-guided light. For more information, see the following publication:</p> <ul> <li><a href="https://doi.org/10.1038/s41566-022-00987-z">10.1038/s41566-022-00987-z</a></li> <li><a href="https://doi.org/10.48550/arXiv.2107.07272">10.48550/arXiv.2107.07272</a></li> </ul> <p>We provide the data in text files encoded in the Unicode standard UTF-8. In the following, we describe the files in more detail.</p> <p>The measured evolution of the signal transmission presented in Fig. 2<strong>b</strong> is provided in the file “source_data_fig2b.txt”. The file has five columns that are separated by the delimiter “, ”:</p> <ul> <li>the time in microseconds,</li> <li>the signal transmission in the 1→2 direction,</li> <li>the error of the signal transmission in the 1→2 direction,</li> <li>the signal transmission in the 1→2 direction,</li> <li>and the error of the signal transmission in the 1→2 direction.</li> </ul> <p>We provide the theory data in the additional file “theory_fig2b.txt”. It contains three columns that are separated by the delimiter “, ” :</p> <ul> <li>the time in microseconds,</li> <li>the calculated signal transmission in the 1→2 direction,</li> <li>the calculated signal transmission in the 2→1 direction.</li> </ul> <p>In the files “source_data_fig2c.txt”, “source_data_fig2d.txt”, and “source_data_fig3b.txt”, we provide the data of the bar plots in Fig. 2<strong>c</strong>, 2<strong>d</strong>, and 3<strong>b</strong>, respectively. In every file, the first column indicates the measurement direction. The following columns contain the detected mean signal transmission with the corresponding errors for various initial atomic spin states defined by the magnetic quantum number <em>m<sub>F</sub></em>.</p>
Movies of mouse oocyte maturation in transmitted light
<p>This dataset has been presented in our paper "An interpretable and versatile machine learning approach for oocyte phenotyping", in bioRxiv.</p> <p>It contains 466 movies of mouse oocytes maturation acquired in transmitted light every 3 min. Spatial resolution is 0.227 µm/pixel.</p>
A Consistent and Corrected Nighttime Light dataset (CCNL 1992-2013) from DMSP-OLS data
<p>DMSP-OLS provides the longest observations of NTL information, from 1992 to 2013, an unparalleled dataset for studying historical artificial lights. Version 4 of the DMSP-OLS Nighttime Lights Time Series is widely used ( Image and data processing by NOAA's National Geophysical Data Center. DMSP data collected by US Air Force Weather Agency ). However, it suffers from three main problems: inter-annual inconsistency, saturation, and blooming effect.</p> <p>We used a series of methods to mitigate the impact and improve data quality. After processing, we get consistent and corrected nighttime light dataset (CCNL).</p> <p>The version 1 products span the globe from 75N latitude to 65S. The products are produced in 30 arc resolution and are made available in GeoTIFF format. Pixel Unit: 'DN'(Digital Number).</p> <p>Each GeoTIFF filename has 4 filename fields that are separated by an underscore "_". A filename extension follows these fields. The fields are described below using this example filename:</p> <p>CCNL_DMSP_1992_V1</p> <p>Field 1: CCNL(Consistent and Corrected Nighttime Light dataset)</p> <p>Field 2: Platform "DMSP"</p> <p>Field 3: Year “1992”</p> <p>Field 4: version “V1”</p>
5D-NP-FABTECH_ALD - Open Dataset for: "Shedding light on the initial growth of ZnO during plasma-enhanced atomic layer deposition on vapor-deposited polymer thin films"
<p>This is the open dataset for the paper: "Demelius, L. <em>et al.</em> Shedding light on the initial growth of ZnO during plasma-enhanced atomic layer deposition on vapor-deposited polymer thin films. <em>Applied Surface Science</em> <strong>604</strong>, (2022)."</p> <p>This includes the supplementary information and all the source material that was used for the paper preparation.</p> <p>For each folder (sub-dataset), there exists a corresponding readme file describing the content and including material.</p>
Dataset: Using light and X-ray scattering to untangle complex neuronal orientations and validate diffusion MRI
<p>This dataset supplements the research article <a href="https://doi.org/10.1101/2022.10.04.509781">"Using light and X-ray scattering to untangle complex neuronal orientations and validate diffusion MRI"</a>. It contains images and parameter maps obtained from measurements with Scattered Light Imaging (SLI), small-angle X-ray scattering (SAXS), and diffusion magnetic resonance imaging (dMRI) of a vervet monkey and a human brain sample (containing parts of the corona radiata, the cingulum, and the corpus callosum). Please refer to the research article for more information about the sample preparation, the measurement settings, and the generation of the different parameter maps - as well as for a more detailed analysis of the data.</p> <p>While SLI and SAXS were performed on two sections per sample (vervet monkey brain: sections no. 501 and 511; human brain: anterior section no. 20, posterior section no. 18), dMRI was performed on the entire human brain sample (3.5 x 3.5 x 1 cm³), and evaluated in the corresponding section plane of the anterior and posterior section, respectively. Pixel sizes in SLI are 3 µm, and in SAXS 100 µm (vervet) and 150 µm (human). Voxels in dMRI are 200 µm isotropic.</p> <p>All files are in tif-format and can be opened with standard image processing tools like ImageJ. The files labeled with "dMRI_ODF" contain a set of spherical harmonics for each voxel, describing the orientation distribution of the nerve fibers in the respective section plane obtained from the dMRI measurement, and can be visualized with MRtrix3, using the command 'mrview [filename] -odf.load_sh [filename]'.</p> <p>In addition to the ODFs, the dataset contains the b0-values and the dMRI-based metrics for the whole human brain sample in form of image stacks: fractional anisotropy (FA), axonal water fraction (AWF), axial/mean/radial diffusivity (AD/MD/RD), and axial/mean/radial kurtosis (AK/MK/RK).</p> <p>For the evaluated human brain sections (anterior/posterior), the 3D-orientations of the nerve fibers were derived from the dMRI and SAXS measurements, respectively: The files labeled with "3D-vectors" contain the unit vectors as X-Y-Z stack; the files labeled with "inclination" contain the (absolute) out-of-plane inclination of the fibers with respect to the section plane.</p> <p>All measurements were further evaluated with the software SLIX (https://github.com/3d-pli/SLIX) in order to derive the in-plane fiber directions (up to three fiber directions per pixel). The dataset contains the image stacks used as input (Stack) as well as the resulting parameter maps: average/maximum/minimum of the signal (avg/max/min), distance/prominence/width of peaks in the signal (peakdistance/peakprominence/peakwidth), the computed in-plane fiber directions (direction1,2,3), the fiber orientation map encoding the fiber directions in different colors (fom), as well as the vector maps (vectors) where fiber orientations of several pixels are displayed on top of each other. For the vervet brain section no. 511, the dataset also contains the parameter maps registered onto the SLI parameter maps.</p>
Kodaikanal Solar Observatory (KoSO) White-Light Sunspot Regions Masks (1904-2017)
<p>Regular observations at the Kodaikanal Solar Observatory (KoSO) began in 1904 using a white-light telescope with a 10-cm aperture lens and an f/15 light beam. Between 1912 and 1917, the objective lens was changed several times. In 1918, a 15-cm achromatic lens was installed. This new configuration produced a 20.4 cm size image of the Sun in the image plane. Photographic plates were used to capture the image. The same telescope has been used since 1918 up until 2017 to take regular white-light observations of the Sun. This data set provides the sunspot mask in HDF5 format for all the White Light Observations acquired at KoSO. Each HDF5 file contains the sunspot mask for all the observations for that year. The sunspot masks are provided in two different coordinate systems: (i) Full Disk as observed and (ii) Carrington heliographic coordinate, which is transformed from full disk using near point interpolation. Each data set also contains metadata in the form of HDF5 attributes. The Carrington co-ordinate data if full Sun map, hence the near-side of the Sun is the region where values in the mask in non-zero, where as sunspot regions are filled with value 2. </p> <p>A <strong>Python package (KoSOpy), which can be located on <a href="https://github.com/Kodaikanal-Solar-Observatory/kosopy" target="_blank" rel="noopener">GitHub</a>,</strong> is being developed which can be used to navigate through these data sets.</p>
Nighttime Lights PC1-4 based on the Version 4 DMSP-OLS Nighttime Lights Time Series 1997–2014
<p>Nighttime Lights PC1-4 based on the Version 4 <a href="https://ngdc.noaa.gov/eog/dmsp/downloadV4composites.html">DMSP-OLS Nighttime Lights Time Series</a> 1997–2014. Derived using SAGA GIS Principal Component analysis. Image and data processing by NOAA's National Geophysical Data Center. DMSP data collected by US Air Force Weather Agency.</p> <p>To access and visualize maps use: <a href="http://www.openlandmap.org/">OpenLandMap.org</a></p> <p>If you discover a bug, artifact or inconsistency in the maps, or if you have a question please use some of the following channels:</p> <ul> <li>Technical issues and questions about the code: <a href="https://gitlab.com/openlandmap/global-layers/issues">https://gitlab.com/openlandmap/global-layers/issues</a> </li> <li>General questions and comments: <a href="https://disqus.com/home/forums/landgis/">https://disqus.com/home/forums/landgis/</a></li> </ul>
Data for manuscript Marmet, Studer, Lemoine, Grazioli, Bertholet & Gmel (2019). Reconsidering the associations between self-reported alcohol use disorder and mental health problems in the light of co-occurring addictions in young Swiss men. Plos One. DOI: 10.1371/journal.pone.0222806.
<p>Dataset for the manuscript Marmet, Studer, Lemoine, Grazioli, Bertholet & Gmel (2019). Reconsidering the associations between self-reported alcohol use disorder and mental health problems in the light of co-occurring addictions in young Swiss men. Plos One. DOI: 10.1371/journal.pone.0222806.</p> <p>The dataset contains all data needed to reproduce the results in the above cited manuscript. Variable description and labels can be found in the codebook. For further information on the instruments used please refer to the manuscript.</p> <p>The data was collected between April 2016 and March 2018 in Switzerland by the C-SURF study (<a href="http://www.c-surf.ch">www.c-surf.ch</a>). Participants were on average 25 years old when they answered the questionnaires. The final sample size used in the manuscript is 5516. Please note that the dataset contains 25 datasets created with multiple imputation, therefore there are no missing values in the dataset.</p> <p>The research protocol for this study was approved by the Human Research Ethics Committee of the Canton Vaud (Protocol No. 15/07). Data collection was funded by the Swiss National Science Foundation (FN 33CSC0-122679, FN 33CS30_139467, FN 33CS30_148493)</p>
A European aerosol phenomenology – 9: LIGHT ABSORPTION PROPERTIES OF CARBONACEOUS AEROSOL PARTICLES ACROSS SURFACE EUROPE
<p>Carbonaceous aerosols (CA), composed of black carbon (BC) and organic aerosols (OA), exert an important role on the climate system through their interaction with solar radiation. Light absorption properties of CA particles are of special interest due to their important contribution to global and regional warming. Among atmospheric particulate matter (PM), BC and the absorbing components of OA (or brown carbon, BrC) are characterized by the highest absorption efficiency but their role in the current climate change, especially that of BrC, is still uncertain. Here we present the absorption properties of BC and BrC PM at 44 sites across Europe using aethalometer data collected at different types of environment (6 traffic (TR), 16 urban (UB), 7 suburban (SUB), 10 regional background (RB) and 5 mountain (M) sites). The absorption Ångström exponent (AAE) method was used to assign total measured absorption to the contributions of BC (bAbs,BC) and BrC (bAbs,BrC) to total absorption (bAbs). The results showed a clear dependence of the absorption coefficients bAbs, bAbs,BC and bAbs,BrC on station settings as follows: TR > UB > SUB > RB > M, even if significant exceptions were observed. The relative contribution of bAbs,BrC to bAbs (%AbsBrC) at 370 nm was on average lower at traffic sites (11-20%) reaching at some SUB and RB sites median annual values that accounted for more than 30% and 10% of the absorption at 370 and 660 nm, respectively. The median AAE of CA particles was correspondingly low at TR sites (1.1-1.2) where internal combustion engines dominated the CA mass concentration. Low AAE were also observed at some remote RB and M sites, likely due to the lack of proximity from BrC sources or lack of sufficiently strong secondary processes resulting in BrC. On average, AAE was lower in Western Europe (<1.3) compared to Eastern Europe (>1.3), likely due to a more extensive use of coal and biomass burning in eastern countries. The median AAE of BrC PM (AAEBrC) showed a wide range of values, from 2.5 to 6, with no clear relationship with station background or region. Assessing the seasonal variability revealed, overall, an increase of bAbs, bAbs,BC, bAbs,BrC in winter, which was attributed to meteorological conditions and more heating related emissions. Accordingly, bAbs,BrC exhibited a stronger increase than bAbs,BC, resulting in higher AAE and %AbsBrC during the winter season. The diel cycles differed between bAbs,BC and bAbs,BrC, with bAbs,BC showing the bimodal peaks during the morning and evening rush hours, whereas bAbs,BrC, together with %AbsBrC, AAE and AAEBrC, peaked at night. Decade-long trend analysis performed for a subset of stations across Europe revealed a decrease of bAbs, driven by declining bAbs,BC, whereas, overall, bAbs,BrC, %AbsBrC and AAE increased with time. This strongly implies an efficient reduction of BC mass concentrations from traffic sources in Europe and a less effective reduction of emissions from BrC sources. The observed increasing trends of AAE reflected a progressive change in the chemical composition of CA particles driven by a relative increase/decrease of BrC/BC content in CA with time.</p>
A Fully-Parameterized Object-Side Light Field Dataset and Theory for Using Entrance and Exit Pupils as Natural Light Field Reference Planes for an Unfocused Plenoptic Camera
<p>We describe a dataset of light fields with full object-side parameterizations. The dataset contains PNG and ESLF files for all 32 images. 12 of them additionally contain depth maps and point clouds.</p>
Dataset for "Light Scalar Meson and Decay Constant in SU(3) Gauge Theory with Eight Dynamical Flavors"
<p><strong>Decoding File Names</strong>: Consider the file name f8l24t48b48m00889_S0.csv. We will break down the meaning of the various pieces of the filename</p> <ul> <li>"f8" means 8 Dirac flavors.</li> <li>"l24t48" means 24<sup>3</sup>×48 lattice.</li> <li>"b48" means beta=4.8, related to the inverse bare gauge coupling.</li> <li>"m00889" means fermion mass m=0.00889.</li> <li>"S" means flavor-singlet scalar meson. Other options are "P" for flavor non-singlet pseudoscalar meson and "C" for flavor non-singlet scalar meson.</li> <li>"0" an integer from 0 to 4 proportional to the squared length of the spatial momentum vector of the correlation function.</li> </ul> <p><strong>Columns of the CSV files</strong>: Each line of the CSV file should contain 41 entries, separated by commas. Refer to the Eq. (8) which defines model A in the accompanying paper to understand the physical interpretation of these parameters.</p> <ol> <li>Model number: 1 is model A, 2 is model B, 3 is model C.</li> <li>n<sub>max</sub>: the number of non-oscillating states in the fit.</li> <li>j<sub>max</sub>: the number of oscillating states in the fit.</li> <li>t<sub>min</sub>: the minimum t value used in the fit.</li> <li>t<sub>max</sub>: the maximum t value used in the fit.</li> <li>𝜒<sup>2</sup> of the fit.</li> <li><span class="math-tex">\(\log\ p\left(\left.M\right|D\right)\)</span>: log of model probability used in Bayesian model averaging.</li> <li>fit value for c<sub>0</sub> (model A) or <span class="math-tex">\(\overline{c}_0\)</span> (model B).</li> <li>fit error for c<sub>0</sub> (model A) or <span class="math-tex">\(\overline{c}_0\)</span> (model B).</li> <li>fit value for c<sub>1</sub>.</li> <li>fit error for c<sub>1</sub>.</li> <li>fit value for c<sub>2</sub>.</li> <li>fit error for c<sub>2</sub>.</li> <li>fit value for c<sub>3</sub>.</li> <li>fit error for c<sub>3</sub>.</li> <li>fit value for c<sub>4</sub>.</li> <li>fit error for c<sub>4</sub>.</li> <li>fit value for <span class="math-tex">\(c_1^\prime\)</span>.</li> <li>fit error for <span class="math-tex">\(c_1^\prime\)</span></li> <li>fit value for <span class="math-tex">\(c_2^\prime\)</span>.</li> <li>fit error for <span class="math-tex">\(c_2^\prime\)</span>.</li> <li>fit value for <span class="math-tex">\(c_3^\prime\)</span>.</li> <li>fit error for <span class="math-tex">\(c_3^\prime\)</span>.</li> <li>fit value for <span class="math-tex">\(c_4^\prime\)</span>.</li> <li>fit error for <span class="math-tex">\(c_4^\prime\)</span>.</li> <li>fit value for <span class="math-tex">\(\log(E_2 - E_1)\)</span>.</li> <li>fit error for <span class="math-tex">\(\log(E_2-E_1)\)</span>.</li> <li>fit value for <span class="math-tex">\(\log(E_3-E_2)\)</span>.</li> <li>fit error for <span class="math-tex">\(\log(E_3-E_2)\)</span>.</li> <li>fit value for <span class="math-tex">\(\log(E_4-E_3)\)</span>.</li> <li>fit error for <span class="math-tex">\(\log(E_4-E_3)\)</span>.</li> <li>fit value for <span class="math-tex">\(\log(E_2^\prime - E_1^\prime)\)</span>.</li> <li>fit error for <span class="math-tex">\(\log(E_2^\prime - E_1^\prime)\)</span>.</li> <li>fit value for <span class="math-tex">\(\log(E_3^\prime - E_2^\prime)\)</span>.</li> <li>fit error for <span class="math-tex">\(\log(E_3^\prime - E_2^\prime)\)</span>.</li> <li>fit value for <span class="math-tex">\(\log(E_4^\prime - E_3^\prime)\)</span>.</li> <li>fit error for <span class="math-tex">\(\log(E_4^\prime - E_3^\prime)\)</span>.</li> <li>fit value for <span class="math-tex">\(\log(E_1)\)</span>.</li> <li>fit error for <span class="math-tex">\(\log(E_1)\)</span>.</li> <li>fit value for <span class="math-tex">\(\log(E_1^\prime)\)</span>.</li> <li>fit error for <span class="math-tex">\(\log(E_1^\prime)\)</span>.</li> </ol>
Supplementary CIF files for "Shedding Light on the Enigmatic TcO2 ⋅ xH2O Structure with Density Functional Theory and EXAFS Spectroscopy"
<p>Optimized geometries from the paper "Shedding Light on the Enigmatic TcO2 ⋅ <em>x</em>H2O Structure with Density Functional Theory and EXAFS Spectroscopy" (<a href="https://doi.org/10.1002/chem.202202235">https://doi.org/10.1002/chem.202202235</a>), provided in CIF format.</p> <p>All structures were fully optimized (lattice vectors and atomic coordinates) using AMS/BAND (<a href="https://www.scm.com/">https://www.scm.com/</a>) with the PBE density functional, scalar relativistic effects (ZORA), and numerical atomic orbitals (NAOs) augmented with a triple-zeta polarized (TZP) set of Slater-type basis functions. For the chains, D3 dispersion corrections were also included.</p> <p> </p>
Datasets for: A global review of pyrosomes: Shedding light on the ocean’s elusive gelatinous ‘fire-bodies’
These are the datasets used to create all figures included in: "Lilly, L.E., Suthers, I.M., Everett, J.D., Richardson, A.J. (2023). A Global Review of Pyrosomes: Shedding light on the ocean’s elusive gelatinous ‘fire-bodies’. Limnology & Oceanography Letters." The review presents a comprehensive global description of the body of current knowledge on pyrosomes, a zooplanktonic tunicate taxon closely related to salps, doliolids, and appendicularians. For review analyses, we used pyrosome observations and associated information from literature-published studies and four databases: NOAA COPEPOD Urochordates database (NOAA, 2022; https://www.st.nmfs.noaa.gov/copepod/atlas/html/taxatlas_4350000.html), BCO-DMO Jellyfish Database Initiative (JeDI; Condon et al., 2014; https://www.bco-dmo.org/dataset/526852), Global Biodiversity Information Facility (GBIF; https://doi.org/10.15468/dl.a8phvp), and Ocean Biodiversity Information System (OBIS; https://obis.org/taxon/137216). We matched pyrosome observations to corresponding satellite-measured sea surface temperature (NOAA Optimum Interpolation Sea Surface Temperature, V2, high-resolution, https://psl.noaa.gov/data/gridded/data.noaa.oisst.v2.highres.html) and chlorophyll-a (MODIS-AQUA, 4 km^2 resolution, Melin, 2013; http://data.europa.eu/89h/10161412-a76c-42b0-b4e1-5fcccdc412b2). The files included in this metadata record have been subsetted from all original file sources. Our subsetted files are designed to run with the associated MATLAB scripts to recreate all manuscript files. We include seven MATLAB scripts: 1) A four-part script to clean up all pyrosome observations, divide to species level, and remove duplicate records from multiple databases and within each database, and 2) Three standalone scripts to plot Figs. 1, 2, and 3.
CVPIA Predation Contact Point Study - 2020: Impacts of Artificial Light At Night in the Upper Sacramento River
The Central Valley Project Improvement Act (CVPIA) has led to the implementation of a Decision Support Model (DSM) to assist in the prioritization of CVPIA restoration actions. The fall-run Chinook salmon DSM depends on a coarse-resolution salmon life-cycle model to predict the population benefits of different restoration actions and scenarios. One critical element of the life-cycle model is how to incorporate predation mortality during the juvenile rearing and outmigration portion of the salmon life-cycle in the Sacramento-San Joaquin Delta. Of particular importance to potential restoration activities, is the predation mortality that occurs in proximity to, and as a result of contact points between predator and prey fishes. Sacramento River winter-run Chinook salmon (Oncorhynchus tshawytscha) are a genetically distinct Evolutionary Significant Unit (ESU) with a unique life history and are listed as endangered at both state and federal levels. Predation of juvenile winter-run by piscivorous fishes is considered to be an important stressor that may reduce the population size of this ESU. Notably, the presence of artificial illumination at night (ALAN) has been shown to aggregate and slow out-migrating salmonids and increase predation by piscivores, and may be an important contact point affecting winter-run Chinook salmon, especially given the vast majority of winter-run Chinook salmon are born and rear within the city limits of Redding, CA. Perhaps the most significant source of ALAN in this region of the Sacramento River is the iconic Sundial Bridge. This bridge is illuminated at night and regional biologists have long been concerned on its potential impacts on winter-run Chinook salmon, as mediated through predation by Rainbow Trout. We therefore performed a field-based experiment to better inform this management concern. To assess the impacts of Sundial Bridge ALAN on fishes, our first objective was to determine whether variable ALAN intensities altered the relati
Underwater temperature, light, and dissolved oxygen data from 3 mini-buoys in Lake Sunapee, NH, USA from June to October 2018
Three mini-buoys were deployed during a portion of the ice-off period of 2018 in Lake Sunapee, NH, USA with HOBO temperature sensors at various depths below the water’s surface. Temperature data were collected using HOBO pendant temperature and HOBO pendant temperature/light sensors at descending depths between 0.1m and the nearest whole and/or half meter increments below the water surface and above the sediment/water interface at 10 minute intervals. Two buoys (Georges Mills and Herrick Cove) also had miniDOT (PME) dissolved oxygen and temperature sensors placed 1.75 meters below the surface. The buoys were located in cove areas of the lake in the north east arm of the lake (Herrick Cove, 0.1m – 6.5m), the west side of the southern area of the lake near Lake Sunapee State Beach (State Beach, 0.1m – 2.5m) and the northwest arm of the lake (George’s Mills, 0.1m -7m). This data has been QAQC’d to remove obviously errant data and artifacts of buoy maintenance visits.
Riparian controls on light availability, primary producers, invertebrates, fish and salamanders in streams in and near the Andrews Experimental Forest, 2014-2018
The goal of this data collection effort was to determine how the age, stage, and structure of the riparian forest relates to stream primary producers and stream biota. Data were collected on stream habitat, benthic algal, biota (fish, salamanders and macroinvertebrates), and riparian forest cover across a total of 9 streams: 7 streams in the HJ Andrews basin/Lookout Creek stream network; one stream in the westward adjacent Blue River basin, and one stream in the eastward adjacent Deer Creek river basin. In each stream there were 2 study reaches – one bordered by old-growth riparian forest and the other bordered by regenerated second-growth riparian forest on at least one bank (with a stand ages that generally ranged between 30 and 60 years). In each study reach (80 – 150 m), we collected the following data: pool habitat, wetted and bankfull widths, large wood abundance and volume, riparian forest canopy cover, benthic algae accrual on tiles, stream macroinvertebrate abundances (from 6 replicate surber samplers, which were pooled and then sub-sampled, identified and measured), age 1+ cutthroat trout (Oncorhynchus clarkii clarkii) abundance and biomass, age 0+ (young-of-year) trout abundance and biomass, coastal giant salamander (Dicamptodon tenebrosus) abundance and biomass. Fish and salamander abundances were calculated by either mark-recapture or multiple pass depletion methods.
Field survey of mangrove regeneration, porewater variables, and light in mangrove forests in Everglades National Park, Florida, USA, July 2020 - August 2022
This dataset package encompasses measurements from field surveys of mangrove regeneration, porewater variables, and light conditions across six mangrove sites in the coastal Everglades. The goal of this project was to quantify mangrove regeneration of seedlings and saplings in mid- and downstream locations within three estuaries in Everglades National Park, Florida, USA. We assessed the effects of porewater variables and light conditions on the observed regeneration patterns. The package includes seven datasets: FCE1268_Porewater: Contains measurements of porewater salinity, sulfide, ammonia, nitrite, orthophosphate, and nitrate at a 30 cm depth. Porewater surveys were conducted biannually from 09-10-2020 to 05-17-2022. See also similar porewater data for Florida Coastal Everglades (FCE) long-term sites in data packages knb-lter-fce.1169 and knb-lter-fce.1171, which contain data for SRS-5 and SRS-6, available in the FCE LTER website's data catalog or the EDI repository. FCE1268_Foliar_Nutrient_Content dataset, collected in August 2022, includes measurements of foliar nutrient content (total carbon, total nitrogen, and total phosphorus) for three mangrove species (A. germinans, L. racemosa, R. mangle) of two life stages—seedlings (height < 1 m) and saplings (height ≥ 1 m and Diameter at Breast Height (DBH) < 2.5 cm). FCE1268_Light contains light intensity (foot-candle) measurements taken at 1-hour intervals from 09-18-2020 to 08-29-2022 at mangrove sites and converted photosynthetic active radiation values from an outdoor mesocosm experiment. FCE1268_Sapling_Density provides biannual count measurements of individuals at the sapling plot level (4 m^-2) within each site from 07-09-2020 to 08-29-2022. FCE1268_Seedling_Density contains biannual count measurements of individuals at the seedling plot level (m^-2) within each site from 07-07-2020 to 08-29-2022. FCE1268_Sapling_Regeneration contains height, crown area, and stem elongation measurements of tagged sapling indiv
The Hubbard Brook Stream Ecology Record: Light, 2018 - ongoing
The Hubbard Brook Stream Ecology record is a companion dataset to the Hubbard Brook Watershed Stream and Precipitation Chemistry record. The Stream Ecology record started in 2018 and HBWatER collects ecological samples from seven gauged watersheds: Watersheds 1 through 6 and Watershed 9. HBWatER measures algal biomass, aquatic invertebrate emergence, and stream decomposition by measuring (1) chlorophyll-a on tiles and artificial moss, which approximate algal biomass growth on bare rock and bryophyte mats, (2) preserved algal biomass on artificial moss substrates in Lugol’s Iodine solution, (3) aquatic invertebrate emergence on replicate sticky traps placed above the stream, and (4) stream decomposition through leaf litter pack and cotton strip decay. To complement these ecological records, HBWaTER installed light sensors and field cameras to obtain better information about the light and stream environment daily. Three replicate light sensors that take sub-daily measurements of light level intensity are placed at each watershed at the weir pond (full-sun), and two under the canopy (partial shade). Field cameras take daily photos at noon of the stream canopy and the stream channel. While many studies at Hubbard Brook have measured algal biomass, aquatic invertebrates, and stream decomposition, they are scattered in locations across the valley, were performed at non-continuous times, and use various semi-comparable methods. The HBWatER Stream Ecology record was created to address this gap and systematically measure any long-term changes in the organisms living in the stream. The collection of HBWatER samples is currently sustained by Tammy Wooster (Cary IES) and analyses of these samples has been performed by Heather Malcom (Cary IES), Audrey Thellman (Duke), and Geoff Wilson (Cary IES). The dataset is curated and maintained by a team of researchers: Chris Solomon (Cary IES), Emma Rosi (Cary IES), and Emily Bernhardt (Duke). Current Financial Support for HBWatER is pro
Effect of plant density and light availability on leaf damage in Manilkara bidentata
Variation in herbivory is often associated with plant density and light environment. To determine the effect of these variables on herbivory we studied leaf production and herbivory on saplings, juveniles and adults of Manilkara bidentata (Sapotaceae) in the Luquillo Experimental Forest (LEF), Puerto Rico. The major herbivore of M. bidentata is microlepidoptera leaf miner (Acrocercopssp.; Gracillariidae). To determine the effect of plant density on herbivory, 24 - 20 x 20 m plots were established and the density of saplings, juveniles and adults were determined. Leaf production, herbivory and growth were measured on all saplings in the plots. In addition, plant density was determined in 8-20 x 20 m plots surrounding the 24 focal plots. The effect of light environment was determined by comparing leaf phenology, leaf quality and herbivory in the vertical and horizontal profile. Sapling density in 60 x 60 m plots was associated with increased levels of herbivory. In the vertical profile, leaf production was continuous in the canopy and synchronous for juveniles and saplings and herbivory increased from the canopy (1.3%) towards the understory (35.6%). In the horizontal profile leaf production was related with the light environmen. Saplings in low light environment produced leaves in June, while plants in gaps had a broader peak of leaf production. Differences in leaf phenology did not result in differences in herbivory possibly because there was high variation in herbivory among leaves. Although many saplings lost more than 80% of new leaf area, there was no detectable effect on plant growth. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International
Germination in three R/FR light environments (El Verde)
Experiments were conducted in the Tabonuco forest at Luquillo Experimental Forest to determine the germination success of a number of species in different light environments. Species tested included: Byrsonima spicata, Calophyllum brasiliense, Carapa sp., Choven venosa, Guarea guidonia, Manilkara bidentata, Ochroma pyramidale and an unidentified species known locally as Jobo. Seeds were collected as they fell and placed on moist towling in horticulture trays at four sites. Seeds were kept moist and germination was recorded daily for 81 days and three times weekly for an additional 75 days. Light environments included a site exposed to full sun (FS) and sites with 55%, 75% and 80% cover. Instantaneous light measurements were made with a Licor 1800 spectroradiometer to determine the Red (660 nm) to Far-red (730 nm) ratio (R/FR) (Lee, 1987). Analysis of light data indicated that the four sites chosen provided three significantly different R/FR ratio environments, and that germination of some species was affected by the light environment (Smith, H. & Whitelam, G.C. 1990). Three species failed to germinate in any of the four light environments. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.
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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.