Find research datasets worth reusing

opencc-by-4.0Nov 2023View details →

North Carolina Outer Banks, USA Coastal Foredune Sediment Cores - Grain Size Data & Core Log Descriptions

This repository includes sediment core data collected at seven sites along the northern Outer Banks, North Carolina, USA. From north to south, the sites include Pine Island, Corolla Reserve, Duck, the US Army Corps of Engineers Field Research Facility (FRF) North, FRF South, Southern Shores (i.e., Hillcrest Beach Access), and Nags Head (Bonnett St. Beach Access).At each site, internal dune sedimentology and stratigraphy were characterized using sediment vibracores, each 1.5–2.2 m long, collected along a cross-shore transect from the dune toe to the dune heel. Coring locations were selected based on dune morphology to capture the stratigraphy of the dune toe, stoss slope, primary dune crest, lee slope, swale, and secondary dune crest, as applicable. Sediment core locations were documented using RTK-GPS and are included in the .kmz file.All sediment cores were split, photographed, described for sedimentary structures, texture (as compared to standards), mineralogy, and color (Munsell, 2012). Sediment cores were described using the Modified Burmister System in 10-cm intervals, with additional intervals added as needed to capture stratigraphic units with thicknesses less than 10 cm but greater than 1 cm. Sediment core log descriptions are included in the NOAA_NCDunes_Vibracore_CoreLogs.xlsx data file.Sediment size and shape were analyzed from oven-dried samples using a CAMSIZERX2Ⓡ. These data are included in the Dune_Grain_Size_camsizer_outputs.csv data file. Metrics reported for each sample include the following: Site, Core ID, Sample Number, Depth (cm below ground surface), Elevation (m, NAVD88), D2 (mm), D5 (mm), D10 (mm), D16 (mm), D25 (mm), D50 (mm), D75 (mm), D84 (mm), D90 (mm), D95 (mm), D98 (mm), average grain symmetry, average grain sphericity, average grain aspect ratio, percent pebble, percent granule, percent very coarse sand, percent coarse sand, percent medium sand, percent fine sand, percent very fine sand, and percent silt.More details regarding these measurements can be found in the following manuscript:Davis, E.H., Hein, C.J., Cohn, N., White, A.E., Zinnert, J.C. Differences in internal sedimentologic and biotic structure between natural, managed, and constructed coastal foredunes (in review).

opencc-by-4.0Nov 2023View details →

Core collapse supernova yield from the post-processing of a long-term 3D simulation

This dataset accompanies the publication "Production of 44Ti and Iron-group Nuclei in the Ejecta of 3D Neutrino-driven Supernovae" published in the Astrophysical Journal Letters Volume 957, Issue 2, id.L25.The dataset consists of an ACII text file that contains the isotopic yields from the post-processing of a 3D long-term supernova simulation for a 18.88 solar mass progenitor model. The yields are given in units of solar masses. Important: The dataset does not include the full stellar yield. It only represents the inner 0.142 solar masses. The total ejecta mass is expected to be larger. The dataset is also available on the websites of the Max-Planck Institute for Astrophysics in Garching, Germany: https://wwwmpa.mpa-garching.mpg.de/ccsnarchive/data/Sieverding2023/The results have been obtained using the open source nuclear reaction network code <a href="https://github.com/starkiller-astro/XNet">XNet.</a>Calculations have been performed on the supercomputing cluster Cobra the Max-Planck Computing and Data Facility (MPCDF) in Garching, Germany.

opencc-by-4.0Aug 2019View details →

Computation-Ready Experimental Metal-Organic Framework (CoRE MOF) 2019 Dataset

High-throughput computational screening of metal-organic frameworks rely on the availability of atomic coordinate files which can be used as input to simulation software packages. CoRE MOF Datasets are derived from Cambridge Structural Database (CSD) and also from the World Wide Web. Nomenclatures: LCD (Largest Cavity Diameter), PLD (pore limiting diameter), LFPD (Largest Sphere along the Free Path), ASA (Accessible Surface Area), NASA (Non-accessible surface area), AV_VF (Void Fraction, 0 - 1), NAV (Non Accessible Volume) Dataset Directory Organization CoREMOF2019_public_v2.zip: dataset with CR and NCR classifications 1.  CR dataset: computaion-ready (N = 10,367) <ul> <li>    ASR: all solvent removed (N = 6,603)</li> <li>    FSR: free solvent removed (N = 3,764)</li> </ul> 2.  NCR: not computaion-ready (N = 8,714) <ul> <li>    ASR: all solvent removed (N = 5,417) <ul> <li>Both: NCR determined by Chen_Manz and mofchecker (N = 2,597)</li> <li>Chen_Manz: NCR determined by Chen_Manz (N = 958)</li> <li>mofchecker: NCR determined by mofchecker (N = 1,859)</li> <li>PACMAN_fail: NCR determined by Chen_Manz and mofchecker, and fail to predict PACMAN charges (N = 3)</li> </ul> </li> <li>    FSR: free solvent removed (N = 3,297) <ul> <li>Both: NCR determined by Chen_Manz and mofchecker (N = 1,646)</li> <li>Chen_Manz: NCR determined by Chen_Manz (N = 463)</li> <li>mofchecker: NCR determined by mofchecker (N = 1,185)</li> <li>PACMAN_fail: NCR determined by Chen_Manz and mofchecker, and fail to predict PACMAN charges (N = 3)</li> </ul> </li> </ul> 2. NCR_detail.xlsx: details of all structures by mofchecker and Chen_Manz for each NCR cases November, 24 2024 <ul> <li>Re-ordering of folders such that top level directory is based on computation-ready and not-computation ready classification.</li> </ul> November, 13 2024 <ul> <li>Classification of Computation-Ready (CR) and Not Computation-Ready (NCR) Structures based on <a href="https://pubs.rsc.org/en/content/articlelanding/2020/ra/d0ra02498h">Chen & Manz</a> (RSC Adv., 2020,10, <a>26944-26951</a>) and <a href="https://github.com/kjappelbaum/mofchecker">MOFChecker </a>program by <a href="https://github.com/kjappelbaum">Kevin M. Jablonka</a>)</li> <li>ML-predicted DDEC6 partial atomic charges based on <a href="https://github.com/mtap-research/PACMAN-charge">PACMAN</a></li> </ul> Acknowledgements <ul> <li>This reserach is supported by the National Research Foundation of Korea (No. 2016R1D1A1B3934484, NRF-2020R1C1C1010373, RS-2024-00449431)</li> <li>This research is supported by the U.S. Department of Energy, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences and Biosciences under Award DE-FG02-17ER16362 (Predictive Hierarchical Modeling of Chemical Separations and Transformations in Functional Nanoporous Materials: Synergy of Electronic Structure Theory, Molecular Simulations, Machine Learning, and Experiment)</li> </ul>

opencc-by-4.0Jan 2022View details →

Example Microscopy Metadata JSON files produced using Micro-Meta App to document example microscopy experiments performed at individual core facilities

Example Microscopy Metadata (Microscope.JSON and Settings.JSON) files produced using <a href="https://wu-bimac.github.io/MicroMetaApp.github.io/">Micro-Meta App</a> to document the Hardware Specifications of example Microscopes and the Image Acquisition Settings utilized to acquire example images as listed in the table below. <blockquote> For each facility, the dataset contains two JSON files: <ol> <li>Microscope.JSON file (e.g., 01_marcello_uliverpool_cci_zeiss_axioobserz1_lsm710.json)</li> <li>Settings.JSON file (indicated with the name of the image and with the _AS suffix)</li> </ol> </blockquote> Micro-Meta App was developed as part of a global community initiative including the <a href="http://www.4dnucleome.org/">4D Nucleome (4DN) </a>Imaging Working Group, BioImaging North America (BINA) <a href="https://www.bioimagingna.org/qc-dm-wg">Quality Control and Data Management Working Group</a>, and QUAlity and REProducibility for Instrument and Images in Light Microscopy (<a href="https://quarep.org/">QUAREP-LiMi</a>), to extend the Open Microscopy Environment (OME) <a href="https://www.openmicroscopy.org/Schemas/Documentation/Generated/OME-2016-06/ome.html">data model</a>. <blockquote> The works of this global community effort resulted in multiple publications featured on a recent Nature Methods FOCUS ISSUE dedicated to <a href="https://www.nature.com/collections/djiciihhjh">Reporting and reproducibility in microscopy</a>. </blockquote> <blockquote> Learn More! For a thorough description of Micro-Meta App consult our recent <a href="https://doi.org/10.1038/s41592-021-01315-z">Nature Methods</a> and <a href="https://doi.org/10.1101/2021.05.31.446382">BioRxiv.org</a> publications! </blockquote>   <table> <tbody> <tr> <td>Nr.</td> <td>Manufacturer</td> <td>Model</td> <td>Tier</td> <td>Εxperiment Type</td> <td>Facility Name</td> <td>Department and Institution</td> <td>URL</td> <td>References</td> </tr> <tr> <td>1</td> <td>Carl Zeiss Microscopy</td> <td>Axio Observer Z1 (with LSM 710 scan head)</td> <td>1</td> <td>3D visualization of superhydrophobic polymer-nanoparticles</td> <td>Centre for Cell Imaging (CCI)</td> <td>University of Liverpool</td> <td>https://cci.liv.ac.uk/equipment_710.html</td> <td>Upton et al., 2020</td> </tr> <tr> <td>2</td> <td>Carl Zeiss Microscopy</td> <td>Axio Observer (Axiovert 200M)</td> <td>2</td> <td>Μeasurement of illumination stability on Chinese Hamster Ovary cells expressing Paxillin-EGFP</td> <td>Advanced BioImaging Facility (ABIF).</td> <td>McGill University</td> <td>https://www.mcgill.ca/abif/equipment/axiovert-1</td> <td>Kiepas et al., 2020</td> </tr> <tr> <td>3</td> <td>Carl Zeiss Microscopy</td> <td>Axio Observer Z1 (with Spinning Disk)</td> <td>2</td> <td>Immunofluorescence imaging of cryosection of Mouse kidney</td> <td>Imagerie Cellulaire; Quality Control managed by Miacellavie (https://miacellavie.com/)</td> <td>Centre de recherche du Centre Hospitalier Université de Montréal (CR CHUM), University of Montreal</td> <td>https://www.chumontreal.qc.ca/crchum/plateformes-et-services  (the web site is for all core facilities, not specifically for the core facility hosting this microscope)</td> <td>Pilliod et al., 2020</td> </tr> <tr> <td>4</td> <td>Carl Zeiss Microscopy</td> <td>Axio Imager Z2 (with Apotome)</td> <td>2</td> <td>Immunofluorescence imaging of mitotic division in Hela cells using  </td> <td>Bioimaging Unit</td> <td>Newcastle University</td> <td>https://www.ncl.ac.uk/bioimaging/</td> <td>Watson et al., 2020</td> </tr> <tr> <td>5</td> <td>Carl Zeiss Microscopy</td> <td>Axio Observer Z1</td> <td>2</td> <td>Fluorescence microscopy of human skin fibroblasts from Glycogen Storage Disease patients.</td> <td>Life Imaging Center (LIC)</td> <td>Centre for Integrative Signalling Analysis (CISA), University of Freiburg</td> <td>https://miap.eu/equipments/sd-i-abl/</td> <td>Hannibal et al., 2020</td> </tr> <tr> <td>6</td> <td>Leica Microsystems</td> <td>DMI6000B</td> <td>2</td> <td>3D immunofluorescence imaging  rhinovirus infected macrophages </td> <td>IMAG'IC Confocal Microscopy Facility</td> <td>Institut Cochin, CNRS, INSERM, Université de Paris</td> <td>https://www.institutcochin.fr/core_facilities/confocal-microscopy/cochin-imaging-photonic-microscopy/organigram_team/10054/view</td> <td>Jubrail et al., 2020</td> </tr> <tr> <td>7</td> <td>Leica Microsystems</td> <td>DM5500B</td> <td>2</td> <td>Immunofluorescence analysis of the colocalization of PML bodies with DNA double-strand breaks</td> <td>Bioimaging Unit</td> <td>Edwardson Building on the Campus for Ageing and Vitality, Newcastle University</td> <td>https://www.ncl.ac.uk/bioimaging/equipment/leica-dm5500/#overview</td> <td>da Silva et al., 2019; Nelson et al., 2012   </td> </tr> <tr> <td>8</td> <td>Leica Microsystems</td> <td>DMI8-CS (with TCS SP8 STED 3X)</td> <td>2</td> <td>Live-cell imaging of N. benthamiana leaves cells-derived protoplasts</td> <td>Center for Advanced Imaging (CAi)</td> <td>School of Mathematics/Natural Sciences, Heinrich-Heine-Universität Düsseldorf</td> <td>https://www.cai.hhu.de/en/equipment/super-resolution-microscopy/leica-tcs-sp8-sted-3x</td> <td>Singer et al., 2017; Hänsch et al., 2020</td> </tr> <tr> <td>9</td> <td>Nikon Instruments</td> <td>Eclipse Ti</td> <td>2</td> <td>Immunofluorescence analysis of the cytoskeleton structure in COS cells</td> <td>Advanced Imaging Center (AIC)</td> <td>Janelia Research Campus, Howard Hughes Medical Institute</td> <td>https://www.janelia.org/support-team/light-microscopy/equipment</td> <td>Abdelfattah et al., 2019; Qian et al., 2019; Grimm et al., 2020</td> </tr> <tr> <td>10</td> <td>Nikon Instruments</td> <td>Eclipse Ti-E (HCA)</td> <td>2</td> <td>Τime-lapse analysis of the bursting behavior of amine-functionalized vesicular assemblies</td> <td>Light Microscopy Facility (IALS-LIF)</td> <td>Institute for Applied Life Sciences, University of Massachusetts at Amherst</td> <td>https://www.umass.edu/ials/light-microscopy</td> <td>Fernandez et al., 2020</td> </tr> <tr> <td>11</td> <td>Nikon Instruments/Coleman laboratory (customized)</td> <td>TIRF HILO Epifluorescence light Microscope (THEM)/ Eclipse Ti</td> <td>2</td> <td>Single-particle tracking of Halo-tagged PCNA in Lox cells</td> <td>Coleman laboratory</td> <td>Anatomy and Structural Biology Department, The Albert Einstein College of Medicine</td> <td>https://einsteinmed.org/faculty/12252/robert-coleman/</td> <td>Drosopoulos et al., 2020</td> </tr> <tr> <td>12</td> <td>Nikon Instruments</td> <td>Eclipse Ti (with Andor Dragon Fly Spinning Disk)</td> <td>2</td> <td>Investigation of the 3D structure of cerebral organoids</td> <td>Montpellier Resources Imagerie</td> <td>Centre de Recherche de Biologie cellulaire de Montpellier (MRI-CRBM), CNRS, Univerity of Montpellier</td> <td>https://www.mri.cnrs.fr/en/optical-imaging/our-facilities/mri-crbm.html</td> <td>Ayala-Nunez et al., 2019</td> </tr> <tr> <td>13</td> <td>Nikon Instruments</td> <td>Eclipse Ti2</td> <td>2</td> <td>Ιmmunofluorescence imaging of cryosections of mouse hearth myocardium </td> <td>Neuroscience Center Microscopy Core</td> <td>Neuroscience Center, University of North Carolina</td> <td>https://www.med.unc.edu/neuroscience/core-facilities/neuro-microscopy/</td> <td>Aghajanian et al., 2021</td> </tr> <tr> <td>14</td> <td>Nikon Instruments</td> <td>Eclipse Ti2</td> <td>2</td> <td>Live-cell imaging of bacterial cells expressing GFP-PopZ</td> <td>Microscopy Resources on the North Quad (MicRoN)</td> <td>Harvard Medical School </td> <td>https://micron.hms.harvard.edu/</td> <td>Lim and Bernhardt 2019; Lim et al., 2019</td> </tr> <tr> <td>15</td> <td>Olympus/Biomedical Imaging Group (customized)</td> <td>TIRF Epifluorescence Structured light Microscope (TESM)/IX71</td> <td>3</td> <td>3D distribution of HIV-1 in the nucleus of human cells</td> <td>Biomedical Imaging Group</td> <td>Program in Molecular Medicine, University of Massachusetts Medical School</td> <td>https://trello.com/b/BQ8zCcQC/tirf-epi-fluorescence-structured-light-microscope</td> <td>Navaroli et al., 2012</td> </tr> <tr> <td>16</td> <td>Olympus/Computer Vision Laboratory (customized)</td> <td>3D BrightField Scanner/IX71</td> <td>3</td> <td>Transmitted light brightfield visualization of swimming spermatocytes</td> <td>Laboratorio Nacional de Microscopia Avanzada (LNMA) and Computer Vision Laboratory of the Institute of Biotechnology</td> <td>Universidad Nacional Autonoma de Mexico (UNAM)</td> <td>https://lnma.unam.mx/wp/</td> <td>Pimentel et al., 2012; Silva-Villalobos et al., 2014</td> </tr> </tbody> </table> Getting started Use these videos to get started with using Micro-Meta App after installation into OMERO and downloading the example data files: <ol> <li><a href="https://vimeo.com/562022222">Video 1</a></li> <li><a href="https://vimeo.com/562022281">Video 2</a></li> </ol> More information <blockquote> For full information on how to use Micro-Meta App please utilize the following resources: <ol> <li>Micro-Meta App <a href="https://wu-bimac.github.io/MicroMetaApp.github.io/">website</a></li> <li><a href="https://micrometaapp-docs.readthedocs.io/en/latest/index.html">Full documentation</a></li> <li><a href="https://micrometaapp-docs.readthedocs.io/en/latest/docs/intro/installation.html">Installation</a> instructions</li> <li><a href="https://micrometaapp-docs.readthedocs.io/en/latest/docs/tutorials/index.html#step-by-step-instructions">Step-by-Step Instructions</a></li> <li><a href="https://micrometaapp-docs.readthedocs.io/en/latest/docs/tutorials/VideoTutorials.html#micro-meta-app-video-tutorials">Tutorial Videos</a></li> </ol> </blockquote> Background If you want to learn more about the importance of metadata and quality control to ensure full reproducibility, quality and scientific value in light microscopy, please take a look at our recent publications describing the development of community-driven light 4DN-BINA-OME Microscopy Metadata specifications <a href="https://doi.org/10.1038/s41592-021-01327-9">Nature Methods</a> and <a href="https://doi.org/10.1101/2021.04.25.441198">BioRxiv.org</a> and our <a href="https://arxiv.org/abs/1910.11370">overview manuscript</a> entitled A perspective on Microscopy Metadata: data provenance and quality control.

opencc-by-4.0Dec 2023View details →

COgnitive intervention to Restore attention using nature Environment (CORE) study data

The COgnitive intervention to Restore attention using nature Environment (CORE) study is single-blinded, two-group randomized-controlled pilot trial among patients with heart failure. The aims to test the preliminary efficacy of the newly developed Nature-VR, a virtual reality-based cognitive intervention that is based on the restorative effects of nature. The Nature-VR intervention group viewed 3-dimensional nature pictures using a virtual reality headset for 10 minutes per day, 5 days per week for 4 weeks (a total of 200 minutes). The active comparison group, Urban-VR, viewed 3-dimensional urban pictures using a virtual reality headset to match the Nature-VR intervention in intervention dose and delivery mode, but not in content. In this study, 73 participants with heart failure completed the baseline and randomized to either Nature-VR or Urban-VR. The target outcomes were attention, self-care of heart failure, and health-related quality of life (HRQoL). After baseline data collection, 4 follow-up data were collected at 4, 8, 26, and 52 weeks.

opencc-by-4.0Oct 2023View details →

Simulated galaxy cluster data at z=0 demonstrating the entropy core problem with the SWIFT-EAGLE galaxy formation model

Cluster simulated with the SWIFT hydrodynamic code with the Ref SWIFT-EAGLE model. This dataset contains the redshift 0 snapshot and the VELOCIraptor halo catalogue. Paper reference: https://arxiv.org/abs/2210.09978

openCC0Jul 2021View details →

Long-term monitoring of ground-dwelling arthropods in the McDowell Sonoran Preserve, Scottsdale, Arizona, ongoing since 2012 (Reformatted to a Darwin Core Archive)

openCC0Jul 2021View details →

Long-term monitoring of ground-dwelling arthropods in central Arizona-Phoenix, ongoing since 1998 (Reformatted to a Darwin Core Archive)

This data package is formatted as a Darwin Core Archive (DwC-A, event core). For more information on Darwin Core see https://www.tdwg.org/standards/dwc/. This Level 2 data package was derived from the Level 1 data package found here: https://pasta.lternet.edu/package/metadata/eml/edi/254/2, which was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-cap/41/16. The abstract below was extracted from the Level 0 data package and is included for context: The Central Arizona–Phoenix Long-Term Ecological Research (CAP LTER) program has been monitoring ground-dwelling arthropods (e.g., insects, ararchnids) at locations throughout the greater Phoenix metropolitan area (GPMA) and surrounding Sonoran desert region since 1998. Monitoring locations span a diversity of habitat types, including mesic and xeric residential yards, commercial areas, agricultural fields, desert locations within the GPMA (desert remnant), and undisturbed desert locations. Organisms are collected quarterly using unbaited pitfall traps, typically ten per location but with some variation, exposed for approximately seventy-two hours. Organisms are identified to the lowest practical taxonomic level and enumerated. Many of the sampling locations established at the beginning of the monitoring project were relocated in 2001-2002 to overlap with the CAP LTER’s Ecological Survey of Central Arizona (ESCA; formerly named Survey200) long-term monitoring sites, although within the same general landscape categories.

openCC (other)Jul 2021View details →

Forest-wide bird survey at 183 sample sites the Andrews Experimental Forest from 2009-2019 (Reformatted to a Darwin Core Archive)

This data package is formatted as a Darwin Core Archive (DwC-A, event core). For more information on Darwin Core see https://www.tdwg.org/standards/dwc/. This Level 2 data package was derived from the Level 1 data package found here: https://pasta.lternet.edu/package/metadata/eml/edi/359/2, which was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-and/4781/3. The abstract below was extracted from the Level 0 data package and is included for context: Bird occurrence data collected at 183 sample locations within the H. J. Andrews Experimental Forest (HJA) from 2009-present. We used a stratified, systematic, random design to select sample locations. We stratified across elevation, distance to road, and habitat type (plantation or mature/old-growth forest). We conduct point counts on six separate occasions from May – July, which corresponded to spring arrival and subsequent breeding period for the majority of bird species at HJA. Surveys occur between 05:15h and 10:30h and each consists of a 10-min point count where we record all birds seen or heard. The species of all birds seen and heard are recorded as well as all individual squirrels, chipmunks and pikas seen and heard. Survey-level information is also collected at each point count and includes: weather and wind conditions, stream noise, snow cover on the ground, phenology of vine maple and rhododendron. Data collection is ongoing. The H.J. Andrews Experimental Forest is a living laboratory that provides unparalleled opportunities for the study of forest and stream ecosystems in the central Cascade Range of Oregon. Since 1980, as a part of the National Science Foundation Long Term Ecological Research (NSF-LTER) program, the Andrews Experimental Forest has become a leader in the analysis of forest and stream ecosystem dynamics. Long-term field experiments and measurement programs have focused on climate dynamics, streamflow, water quality, and vegetation succe

openCC (other)Jul 2021View details →

Moss point transect data for the Kuparuk River near Toolik Field Station, Alaska 1993-current. (Reformatted to a Darwin Core Archive)

This data package is formatted as a Darwin Core Archive (DwC-A, event core). For more information on Darwin Core see https://www.tdwg.org/standards/dwc/. This Level 2 data package was derived from the Level 1 data package found here: https://pasta.lternet.edu/package/metadata/eml/edi/280/2, which was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-arc/10317/8. The abstract below was extracted from the Level 0 data package and is included for context: This file contains the consolidated data for percent cover of dominant bryophytes and other easily identifiable macro-algae in the experimental reaches of the Kuparuk River beginning in 1993 and updated annually. In some years percent cover was recorded more than one time per season. In all years percent cover was recorded in riffle habitats and in some (early) years percent cover was recorded for pool habitats. Moss point transects have been done on the Kuparuk since 1993. The Arctic is one of the most rapidly warming regions on Earth. Responses to this warming involve acceleration of processes common to other ecosystems around the world (e.g., shifts in plant community composition) and changes to processes unique to the Arctic (e.g., carbon loss from permafrost thaw). The objectives of the Arctic Long-Term Ecological Research (LTER) Project for 2017-2023 are to use the concepts of biogeochemical and community “openness” and “connectivity” to understand the responses of arctic terrestrial and freshwater ecosystems to climate change and disturbance. These objectives will be met through continued long-term monitoring of changes in undisturbed terrestrial, stream, and lake ecosystems in the vicinity of Toolik Lake, Alaska, observations of the recovery of these ecosystems from natural and imposed disturbances, maintenance of existing long-term experiments, and initiation of new experimental manipulations. Based on these data, carbon and nutrient budgets and indices

MCR LTER: Coral Reef: Long-term Population and Community Dynamics: Fishes, ongoing since 2005 (Reformatted to a Darwin Core Archive)

This data package is formatted as a Darwin Core Archive (DwC-A, event core). For more information on Darwin Core see https://www.tdwg.org/standards/dwc/. This Level 2 data package was derived from the Level 1 data package found here: https://pasta.lternet.edu/package/metadata/eml/edi/125/2, which was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-mcr/6/58. The abstract below was extracted from the Level 0 data package and is included for context: These data describe the species abundance and size distributions of fishes surveyed as part of MCR LTER's annual reef fish monitoring program. This study began in 2005 and the dataset is updated annually. The abundances of all mobile taxa of fishes (Scarids, Labrids, Acanthurids, Serranids, etc.) observed on a five by fifty meter transect which extends from the bottom to the surface of the water column are recorded by a diver using SCUBA. The diver then swims back along a one by fifty meter section of the original transect line and records the abundances of all non-mobile or cryptic taxa of fishes (Pomacentids, Gobiids, Cirrhitids, Holocentrids etc). Surveys are conducted between 0900 and 1600 hours (Moorea time) during late July or early August each year. In 2006, divers also began to estimate the size (length) of each fish observed to the nearest half cm. Four replicate transects are surveyed in each of six locations on the forereef (two on each of Moorea's three sides), six locations on the backreef (two on each of Moorea's three sides) and on six locations on the fringing reef (two on each of Moorea's three sides) for a total of 72 individual transects. Transects are permanently marked using a series of small, stainless steel posts affixed to the reef. Transects on the forereef are located at a depth of approximately 12m, those on the backreef are located at a depth of approximately 1.5m and those on the fringing reef are located at a depth of approximately 10m.

MCR LTER: Coral Reef: Long-term Population and Community Dynamics: Corals, ongoing since 2005 (Reformatted to a Darwin Core Archive)

This data package is formatted as a Darwin Core Archive (DwC-A, event core). For more information on Darwin Core see https://www.tdwg.org/standards/dwc/. This Level 2 data package was derived from the Level 1 data package found here: https://pasta.lternet.edu/package/metadata/eml/edi/277/3, which was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-mcr/4/38. The abstract below was extracted from the Level 0 data package and is included for context: This dataset contains the percentage cover of the stony corals (Scleractinia) and other major groups analyzed from 0.5 x 0.5 m photographic quadrats in several reef habitats at the Moorea Coral Reef LTER, French Polynesia. This survey has been repeated annually in April since 2005. There are two tables available, providing different views of the same data: a long table having all values in one column and a wide table having a separate column for each dependent variable. Functional groups (i.e., dependent variables) counted are: Scleractinian Corals (by genus where appropriate, see methods), Macroalgae, Crustose Coralline Algae / Bare Space, Soft Corals, Hydrocorals (Millepora), Algal Turf and Sand. The coral community was sampled photographically in all habitats surrounding the island: Fringing Reef, Lagoon (Backreef), and Outer Reef (Forereef.) The sampling regime consists of a repeated-measures protocol in each habitat, and is structured by habitat to allow a statistical contrast of sites, shores, times, and in the case of the outer reef, depths. Detailed methods are available in the protocols section. This material is based upon work supported by the U.S. National Science Foundation under Grant No. OCE 16-37396 (and earlier awards) as well as a generous gift from the Gordon and Betty Moore Foundation. Research was completed under permits issued by the French Polynesian Government (Délégation à la Recherche) and the Haut-commissariat de la République en Polynésie

MCR LTER: Coral Reef: Long-term Population and Community Dynamics: Benthic Algae and Other Community Components, ongoing since 2005 (Reformatted to a Darwin Core Archive)

This data package is formatted as a Darwin Core Archive (DwC-A, event core). For more information on Darwin Core see https://www.tdwg.org/standards/dwc/. This Level 2 data package was derived from the Level 1 data package found here: https://pasta.lternet.edu/package/metadata/eml/edi/279/2, which was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-mcr/8/32. The abstract below was extracted from the Level 0 data package and is included for context: Coral reefs are comprised of scleractinian corals and many other benthic organims. The sampling described here quantifies the relative abundances of corals (aggregate abundance) and the other major benthic components including algal turfs, macroalgae, crustose corallines, and other sessile invertebrates. Abundance is estimated yearly at each of 6 sites (2 per shore) around the island. At each site, and in each of 4 habitats (fringing reef, backreef, forereef 10-m depth, forereef 17-m depth), 5 permanent 10-m long transects have been established and abundance estimates are made at fixed positions along each transect (n=10, 0.25 m2 quadrats per transect) allowing a repeated measures statistical analysis for the detection of temporal trends. This material is based upon work supported by the U.S. National Science Foundation under Grant No. OCE 16-37396 (and earlier awards) as well as a generous gift from the Gordon and Betty Moore Foundation. Research was completed under permits issued by the French Polynesian Government (Délégation à la Recherche) and the Haut-commissariat de la République en Polynésie Francaise (DTRT) (Protocole d'Accueil 2005-2020). This work represents a contribution of the Moorea Coral Reef (MCR) LTER Site.

MCR LTER: Coral Reef: Long-term Community Dynamics: Backreef (Lagoon) Corals Annual Survey, ongoing since 2005 (Reformatted to a Darwin Core Archive)

This data package is formatted as a Darwin Core Archive (DwC-A, event core). For more information on Darwin Core see https://www.tdwg.org/standards/dwc/. This Level 2 data package was derived from the Level 1 data package found here: https://pasta.lternet.edu/package/metadata/eml/edi/321/3, which was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-mcr/1038/10. The abstract below was extracted from the Level 0 data package and is included for context: This dataset contains the percentage cover of all stony corals (Scleractinia, pooled among genera) and other major groups analyzed from 0.5 x 0.5 m photographic quadrats at the Backreef habitat at the Moorea Coral Reef LTER, French Polynesia. This survey time series began in 2005 and is repeated each year in April. Functional groups counted are: Scleractinian corals, Macroalgae, Crustose Coralline Algae / Bare Space, Soft Corals, Hydrocorals (Millepora), Algal Turf and Sand. The coral community was sampled photographically in all represented habitats surrounding the island: Fringing Reef, Lagoon, and Outer Reef. This dataset contains only Lagoon (Backreef) data (see knb-lter-mcr.4 for the other habitats) and is structured in a repeated-measures protocol to allow a statistical contrast of sites, shores and times. Community structure was determined through a coarse analysis of the benthic community, initially completed in situ (2005), but using photoquadrats from 2006. There are quadrats analyzed at each of five areas within each site, and the areas are revisited (but not the quadrats) each year to support the repeated measures design. There are two tables available, providing different views of the same data: a long table having all values in one column and a wide table having a separate column for each observed object. Detailed methods are available in the protocols section. This material is based upon work supported by the U.S. National Science Foundation under

PIE LTER zooplankton surveys using plankton tows along transects in the Plum Island Sound estuary, Massachusetts (Reformatted to a Darwin Core Archive)

This data package is formatted as a Darwin Core Archive (DwC-A, event core). For more information on Darwin Core see https://www.tdwg.org/standards/dwc/. This Level 2 data package was derived from the Level 1 data package found here: https://pasta.lternet.edu/package/metadata/eml/edi/337/2, which was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-pie/405/2. The abstract below was extracted from the Level 0 data package and is included for context: Zooplankton were collected in spring and late summer/fall at four stations representing the salinity gradient in the Parker River-Plum Island Sound estuary. Two size classes, greater than 335 micron and greater than 150 micron, were collected by net tows. Conductivity or salinty and temperature were recorded for each sample. Samples were concentrated to less than 250 mls and preserved in 70 percent EtOH. For taxonomy, sample splits were taken such that a minimum of 250 individuals were present, and counted under a dissecting microscope. Individuals were identified to the lowest taxonomic level possible, generally to species. Adult copepods were additionally characterized by sex. The Plum Island Ecosystems (PIE) LTER has, since its inception in 1998, been working towards a predictive understanding of the long-term response of coupled land-estuary-ocean ecosystems to changes in three drivers: climate, sea level, and human activities. The Plum Island Estuary-LTER includes the coupled Parker, Rowley, and Ipswich River watersheds, estuarine areas including a shallow open sound, and extensive tidal marshes. PIE is connected to the Gulf of Maine in the Acadian biogeographic province, which is a cold water, macrotidal environment that is geographically and biologically distinct from coastal ecosystems to the south of Cape Cod, Massachusetts. Over the next four years the LTER will build upon the progress they have made in understanding the importance of spatial patterns and

Plum Island LTER phytoplankton identification using HPLC and Chem Taxonomy along transects in the Plum Island Sound estuary, Massachusetts. (Reformatted to a Darwin Core Archive)

This data package is formatted as a Darwin Core Archive (DwC-A, event core). For more information on Darwin Core see https://www.tdwg.org/standards/dwc/. This Level 2 data package was derived from the Level 1 data package found here: https://pasta.lternet.edu/package/metadata/eml/edi/338/2, which was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-pie/404/4. The abstract below was extracted from the Level 0 data package and is included for context: Water column samples are collected along an estuarine salinity gradient as part of our monitoring surveys of the Parker River estuary each spring and late summer (typically high vs low freshwater input). Samples are filtered, and stored frozen for later pigment analyses by HPLC. Pigment data are then analyzed by CHEMTAX, calibrated to a matrix of pigment ratios based on taxonomy and enumeration of selected subsamples by microspcopy. Data are presented in terms of chlorophyll a concentrations partitionaed among the major phytoplankton groups as determined by CHEMTAX. For 2003-2006, sampling stations along the Plum Island Sound-Parker River were at fixed geographic locations at specific "Bends" in the river. In 2008, we began sampling the water column in salinity space rather than at specific geographic locations along the river. This sampling approach was adopted in order to follow particular water masses in this macrotidal estuary. In practical terms, it means that sampling locations, or stations, are not static. Therefore, we have mapped the 11 sampling locations (latitude and longitude are logged at each station) from each transect along the mainstem of the estuary, so each station may be placed along the river (to the nearest 0.5km) as well as in salinity space. We have also used the km marker to assign the sampling locations from each survey to one of four bounding boxes : the Sound (Plum Island Sound; EST-PR-SoundBND) which encompasses approximatly the first 9

Florida Bay Braun Blanquet, Everglades National Park (FCE), South Florida from October 2000 to Present (Reformatted to a Darwin Core Archive)

This data package is formatted as a Darwin Core Archive (DwC-A, event core). For more information on Darwin Core see https://www.tdwg.org/standards/dwc/. This Level 2 data package was derived from the Level 1 data package found here: https://pasta.lternet.edu/package/metadata/eml/edi/345/2, which was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-fce/1129/8. The abstract below was extracted from the Level 0 data package and is included for context: Braun Blanquet surveys determining frequency, abundance, and density for seagrass and macroalgae made during visits to TS/Ph 7a, 8-11. Our long term research program focuses on the following central objective: Regional processes mediated by water flow control population and ecosystem level dynamics at any location within the coastal Everglades landscape. This phenomenon is best exemplified in the dynamics of an estuarine oligohaline zone where fresh water draining phosphorus-limited Everglades marshes mixes with water from the more nitrogen-limited coastal ocean. Graphic representation of data can be located at http://serc.fiu.edu/seagrass/!CDreport/DataHome.htm We are investigating how variability in regional climate, freshwater inputs, disturbance, and perturbations affect the coastal Everglades ecosystem. Our long term research program focuses on testing the following central idea and hypotheses: Regional processes mediated by water flow control population and ecosystem level dynamics at any location within the coastal Everglades landscape. This phenomenon is best exemplified in the dynamics of an estuarine oligohaline zone where fresh water draining phosphorus-limited Everglades marshes mixes with water from the more nitrogen-limited coastal ocean. Hypothesis 1: In nutrient-poor coastal systems, long-term changes in the quantity or quality of organic matter inputs will exert strong and direct controls on estuarine productivity, because inorganic nutrients are

Cross Bank Benthic Aboveground Biomass, Everglades National Park (FCE LTER), South Florida from 1983 to 2014 (Reformatted to a Darwin Core Archive)

This data package is formatted as a Darwin Core Archive (DwC-A, event core). For more information on Darwin Core see https://www.tdwg.org/standards/dwc/. This Level 2 data package was derived from the Level 1 data package found here: https://pasta.lternet.edu/package/metadata/eml/edi/346/2, which was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-fce/1203/2. The abstract below was extracted from the Level 0 data package and is included for context: Aboveground biomass surveys of benthos on cross bank, a site of experimental fetilization via bird defecation since 1983. Dataset includes species specific biomass at five sites, each with both control and experimental treatments We are investigating how variability in regional climate, freshwater inputs, disturbance, and perturbations affect the coastal Everglades ecosystem. Our long term research program focuses on testing the following central idea and hypotheses: Regional processes mediated by water flow control population and ecosystem level dynamics at any location within the coastal Everglades landscape. This phenomenon is best exemplified in the dynamics of an estuarine oligohaline zone where fresh water draining phosphorus-limited Everglades marshes mixes with water from the more nitrogen-limited coastal ocean. Hypothesis 1: In nutrient-poor coastal systems, long-term changes in the quantity or quality of organic matter inputs will exert strong and direct controls on estuarine productivity, because inorganic nutrients are at such low levels. Hypothesis 2: Interannual and long-term changes in freshwater flow controls the magnitude of nutrients and organic matter inputs to the estuarine zone, while ecological processes in the freshwater marsh and coastal ocean control the quality and characteristics of those inputs. Hypothesis 3: Long-term changes in freshwater flow (primarily manifest through management and Everglades restoration) will interact with long-t

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Bonanza Creek LTER: Annual Active Layer Depths at Core Floodplain Sites from 1990 to Present in the Bonanza Creek Experimental Forest near Fairbanks, Alaska

Annual thaw depths are measured at the time of maximum thaw at any of the 35 BCEF-LTER sites that have permafrost or intermittent seasonal frost. 1. Wildfire in the black spruce permafrost sites will cause an increase in the active layer thickness and subsidence of the surface layers that may last for up to 25 years. The active layer thickness should return to the pre-fire depths between 25 and 30 years after the fire. 2. Climate warming in interior Alaska may result in an increase in the active layer thickness in black spruce permafrost sites. 3. Fire and climate warming together may result in the elimination of permafrost from some black spruce permafrost sites in interior Alaska. 4. Forest succession on the floodplain of the Tanana River results in a gradual decrease in soil temperature as the organic layer increases with time. The development of a thick feathermoss layer in later stages of succession is especially important in the development of permafrost. Permanent or intermittent permafrost should develop in the older white spruce stages. Black spruce stands on the older terraces should be underlain by permafrost with a shallow active layer. 5. Climate warming will delay the formation of permafrost until the latest stages of forest succession and may eliminate it completely from floodplain stands.