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2,852 results for “preservation”
An ensemble of trend preserving statistically downscaled projections for key marine variables under three different future scenarios for the North Sea
<p>The ensemble provides future projections of key marine variables under climate change for the North Sea region. The datasets were produced for three different future scenarios (SSP1-2.6, SSP2-4.5 and SSP5-8.5) and five different variables (potential temperature, salinity, dissolved oxygen, pH and chlorophyll) at three different depth levels (5m, 25m and seafloor with the exception of chlorophyll) at monthly frequency for the years 1993 - 2099. The statistical metrics provided are the mean, standard deviation, minimum, maximum median, 2.5 and 97.5 percentile. The ensemble is computed over 3-7 different CMIP6 model realisations (depending on variable), the bias corrections and statistical downscaling was trained on the GLORYS12V1 reanalysis provided by the Copernicus Marine Environment Monitoring Service (CMEMS).</p> <p>The following Earth System Models were used in building the ensemble:</p> <ul> <li>CMCC-ESM2 (Lovato et al. 2022)</li> <li>CMCC-CM2-SR5 (Cherchi et al. 2019)</li> <li>GFDL-ESM4 (Dunne et al., 2020)</li> <li>MPI-ESM1-2-LR (Mauritsen et al., 2020)</li> <li>IPSL-CM6A-LR (Boucher et al. 2020)</li> </ul> <p>A description of the downscaling approach and evaluation of the datasets over the European regions is published in <a href="https://doi.org/10.1038/s41598-024-51160-1">Kristiansen et al. 2024</a>.</p> <p> <br>Analogue datasets are provided in separate zenodo entries for the regions of the Mediterranean Sea, the Baltic Sea, the Bay of Biscay, the Chilean coast and the area around the Yucatán Peninsula, see “Related identifiers”.</p> <p> </p> <p>We acknowledge the World Climate Research Programme's Working Group on Coupled Modelling, which is responsible for CMIP. Generated using E.U. Copernicus Marine Service Information; <a href="https://doi.org/10.48670/moi-00021">https://doi.org/10.48670/moi-00021</a>, <a href="https://doi.org/10.48670/moi-00019">https://doi.org/10.48670/moi-00019</a>.</p> <p><br><strong>This data is distributed under <a href="https://creativecommons.org/licenses/by-nc-sa/4.0/">Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License</a>.</strong></p>
An ensemble of trend preserving statistically downscaled projections for key marine variables under three different future scenarios for the Mediterranean Sea
<p>The ensemble provides future projections of key marine variables under climate change for the Mediterranean region. The datasets were produced for three different future scenarios (SSP1-2.6, SSP2-4.5 and SSP5-8.5) and five different variables (potential temperature, salinity, dissolved oxygen, pH and chlorophyll) at three different depth levels (5m, 25m and seafloor with the exception of chlorophyll) at monthly frequency for the years 1993 - 2099. The statistical metrics provided are the mean, standard deviation, minimum, maximum median, 2.5 and 97.5 percentile. The ensemble is computed over 3-7 different CMIP6 model realisations (depending on variable), the bias corrections and statistical downscaling was trained on the GLORYS12V1 reanalysis provided by the Copernicus Marine Environment Monitoring Service (CMEMS).</p> <p>The following Earth System Models were used in building the ensemble:</p> <ul> <li>CMCC-ESM2 (Lovato et al. 2022)</li> <li>CMCC-CM2-SR5 (Cherchi et al. 2019)</li> <li>GFDL-ESM4 (Dunne et al., 2020)</li> <li>MPI-ESM1-2-LR (Mauritsen et al., 2020)</li> <li>IPSL-CM6A-LR (Boucher et al. 2020)</li> </ul> <p>A description of the downscaling approach and evaluation of the datasets over the European regions is published in <a href="https://doi.org/10.1038/s41598-024-51160-1">Kristiansen et al. 2024</a>.</p> <p> <br>Analogue datasets are provided in separate zenodo entries for the regions of the North Sea, the Baltic Sea, the Bay of Biscay, the Chilean coast and the area around the Yucatán Peninsula, see “Related identifiers”.</p> <p>We acknowledge the World Climate Research Programme's Working Group on Coupled Modelling, which is responsible for CMIP. Generated using E.U. Copernicus Marine Service Information; <a href="https://doi.org/10.48670/moi-00021">https://doi.org/10.48670/moi-00021</a>, <a href="https://doi.org/10.48670/moi-00019">https://doi.org/10.48670/moi-00019</a>.</p> <p><br><strong>This data is distributed under <a href="https://creativecommons.org/licenses/by-nc-sa/4.0/">Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License</a>.</strong></p> <p> </p>
An ensemble of trend preserving statistically downscaled projections for key marine variables under three different future scenarios for the Baltic Sea
<p>The ensemble provides future projections of key marine variables under climate change for the Baltci Sea region. The datasets were produced for three different future scenarios (SSP1-2.6, SSP2-4.5 and SSP5-8.5) and five different variables (potential temperature, salinity, dissolved oxygen, pH and chlorophyll) at three different depth levels (5m, 25m and seafloor with the exception of chlorophyll) at monthly frequency for the years 1993 - 2099. The statistical metrics provided are the mean, standard deviation, minimum, maximum median, 2.5 and 97.5 percentile. The ensemble is computed over 3-7 different CMIP6 model realisations (depending on variable), the bias corrections and statistical downscaling was trained on the GLORYS12V1 reanalysis provided by the Copernicus Marine Environment Monitoring Service (CMEMS).</p> <p>The following Earth System Models were used in building the ensemble:</p> <ul> <li>CMCC-ESM2 (Lovato et al. 2022)</li> <li>CMCC-CM2-SR5 (Cherchi et al. 2019)</li> <li>GFDL-ESM4 (Dunne et al., 2020)</li> <li>MPI-ESM1-2-LR (Mauritsen et al., 2020)</li> <li>IPSL-CM6A-LR (Boucher et al. 2020)</li> </ul> <p>A description of the downscaling approach and evaluation of the datasets over the European regions is published in <a href="https://doi.org/10.1038/s41598-024-51160-1">Kristiansen et al. 2024</a>.</p> <p>Analogue datasets are provided in separate zenodo entries for the regions of the Mediterranean Sea, the North Sea, the Bay of Biscay, the Chilean coast and the area around the Yucatán Peninsula, see “Related identifiers”.</p> <p>We acknowledge the World Climate Research Programme's Working Group on Coupled Modelling, which is responsible for CMIP. Generated using E.U. Copernicus Marine Service Information; <a href="https://doi.org/10.48670/moi-00021">https://doi.org/10.48670/moi-00021</a>, <a href="https://doi.org/10.48670/moi-00019">https://doi.org/10.48670/moi-00019</a>.</p> <p><br><strong>This data is distributed under <a href="https://creativecommons.org/licenses/by-nc-sa/4.0/">Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License</a>.</strong></p>
Questionnaire for the self-assessment of digital preservation activities in institutional research repositories
<p>This dataset includes a questionnaire designed to enable institutional repository managers to conduct a self-assessment of their digital preservation strategies and activities. It consists of 46 evaluation criteria extracted and modified from the NDSA Levels of Digital Preservation and ISO 16363:2017 standards. The questionnaire is provided in queXML format, facilitating its import into various survey applications</p> <p> </p>
Sutra to DNA : An interdisciplinary approach to cultural heritage preservation
<p>Materials pertaining to the project Sutra2DNA. We have chosen the Diamond Sūtra as the first Buddhist text to be encoded in DNA. The DNA is encased in metal capsule, which in turn are housed in specially designed, 3D printed miniature stūpas.</p> <p>A QR code with the DOI of this archive will be printed on the miniature stūpas. Interested finders who have arrived here because of the QR code should first read the final report of the project.</p> <p>The upload contains the following files:</p> <p>* Sutra2DNA_finalReport.odt<br> Explains the project and outcome.</p> <p>* diamondSutraT235_textOnly.txt<br> The Chinese text of the Diamond Sūtra as provided to the encoder.</p> <p>* Twist-Decoding Instructions-DS14.pdf<br> Contains some of the decoding options available in 2022.</p> <p>* twist_bioscience_codec_v2_external.tar.gz<br> Docker file with the decoder for the DNA sequence as provided by TwistBioscience. </p> <p>* miniatureStupa_STLfiles/*.stl<br> Three files to 3D print the three parts of the miniature stūpa that houses the capsule with the DNA.</p> <p>* dna-fountain-master.zip<br> Justin Brody's porting of Erlich's fountain code algorithm (2017) to Python 3. (2022-06 code from https://github.com/jdbrody/dna-fountain)</p>
Age-related proteostatic imbalance exacerbates heart failure with preserved ejection fraction pathogenesis in old mice
<p>Heart failure with preserved ejection fraction (HFpEF) is a leading cause of hospitalization and death in the elderly. While aging strongly increases the incidence of HFpEF, the specific influences of aging on HFpEF at molecular and pathophysiological levels remain unclear. Here, we show that aged mice, when subjected to chronic metabolic and hypertensive stress (2-hit stress), develop an aggravated cardiometabolic HFpEF phenotype compared to younger counterparts. Aged HFpEF mice also display unique pathological characteristics reminiscent of those found in HFpEF patients. We demonstrate that age-related dysfunction in protein quality control (PQC) exacerbates proteostatic stress in HFpEF. Specifically, we demonstrate that increased protein synthesis induced by 2-hit stress combines with age-related impairment in protein degradation in aged HFpEF hearts, culminating in the accumulation of protein aggregates. These findings underscore the importance of incorporating aging into preclinical HFpEF models and support the therapeutic potentials of targeting PQC mechanisms to ameliorate disease outcomes.</p> <p>The deposited data are lc-ms data acquired on the Thermo QEx-Plus system. For any questions, please contact mike kinter mike-kinter at omrf.org</p> <p>This upload contains the bulk of the LC-MS data. But, due to file sizes, and addition group of files can be found at doi 10.5281/zenodo.11094720</p>
The BEV*ARV Project; the Preservation Conditions of Museum Collection Storages in Denmark.
<p>A national survey on the preservation condition in Danish state subsidised museums’ storages was conducted in 2022-23. The collected data has been anonymized and is open for further study and research.</p> <p>The survey consisted of 25 questions (<em>BEV.ARV_Spørgeskema</em>) responded during physical inspections of the storages. 103 museums participated in the survey, 350 buildings and more than 850 storage rooms were physically inspected, and the results recorded. Upon inspection, the preservation/degradation risks addressed in each question were rated according to an A-B-C-D scale. Character A is the best (no degradation risk), D is the lowest (high degradation risk). A guideline (<em>BEV.ARV_Svarvejledning</em>) was used to assist uniform evaluations of the storage conditions.</p> <p>The survey covered museums with art collections, cultural history collections and natural history collections. The indoor climate over one calendar year was recorded in around five hundred of the storage rooms.</p> <p>The collected and uploaded data contain information on the condition of the buildings used for storages, the condition of the storage rooms and the objects stored therein, and how the museums manage and control their collection storage rooms. The survey method has been developed for future inspections and comparative reports of the storage conditions of museum collections.</p> <p>The files included in the datasets have been used in the report to the Ministry of Culture. Furthermore, the data has been applied for making individual museum storage reports with scores and characters for each storage facility. The data is available in Danish only.</p> <p>Content of the folder <strong>Klimadata</strong>:</p> <ul> <li>The file BEV.ARV_2024.04_Dataoversigt provides information regarding type of museum and whether climate data from the storages have been collected or not. </li> <li>The Excel files (<em>M00X-files</em>), one per museum, provides the climate data (Relative Humidity, RH % and Temperature, T °C) from the individual storages, naming corresponding to those applied in the file BEV.ARV_2024.04_Anonymiseret_Raadata.csv</li> </ul> <p>Content of the folder<strong> Rapporter_Supp.Info</strong>:</p> <ul> <li>The file BEV.ARV_2024.04_Anonymiseret_Raadata.csv holds the complete inspection results for all museum storages (the buildings and their rooms).</li> <li>The file BEV.ARV_2024.04_Karaktermodel+Analyse contains analyses carried out and used in the overall report to the Ministry of Culture.</li> <li>For completeness, the report to the Ministry of Culture<em> (BEV.ARV_Slutrapport)</em>, an example of an individual museum storage report ( BEV.ARV_<em>Magasinrapport_Museum_X</em>) the 25 survey questions (<em>BEV.ARV_Spoergeskema</em>) and the response guidelines (<em>BEV.ARV_Svarvejledning</em>), all in Danish, are included. </li> </ul>
Experimental data, analysis scripts and simulations for "Emittance preservation in a plasma-wakefield accelerator"
<p>This dataset presents the experimental data, the analysis scripts and the accompanying simulations for the article <em>"Emittance preservation in a plasma-wakefield accelerator"</em> by C. A. Lindstrøm <em>et al</em>. [<a href="https://doi.org/10.1038/s41467-024-50320-1">Nat. Commun. 15, 6097 (2024)</a>].</p> <p>The data was collected at the FLASHForward facility at DESY (Hamburg, Germany). Simulations were performed using <a href="https://doi.org/10.5281/zenodo.5639467" target="_blank" rel="noopener">HiPACE++ v23.11</a>.</p> <p><strong>Folder structure:</strong></p> <ul> <li>Folders containing experimental data: <ul> <li>Folder <code>1A_DATA__OBJECT_PLANE_SCANS</code> contains all data from object-plane scans (emittance measurements).</li> <li>Folder <code>1B_DATA__SPECTRUM_MEASUREMENT</code> contains all data from energy-spectrum measurements.</li> <li>Folder <code>1C_DATA__TWO_BPM_TOMOGRAPHY</code> contains all data from two-BPM tomography measurements.</li> <li>Folder <code>1D_DATA__BEAM_RECONSTRUCTION</code> contains all data from beam-reconstruction measurements (including longitudinal-phase-space measurements).</li> <li>Folder <code>1E_DATA__PLASMA_DENSITY</code> contains all data from plasma-density measurements (spectral-line broadening).</li> </ul> </li> <li>Folder <code>2_ANALYSIS</code> contains all the data-analysis scripts, required for plotting experimental figures.</li> <li>Folder <code>3_SIMULATION</code> contains all simulation scripts, required for generating 6D beam phase spaces and plotting simulation figures.</li> <li>Folder <code>4_FIGURES</code> contains all figure-plotting scripts (17 figures total).</li> </ul> <p><br><strong>Dataset structure:</strong></p> <ul> <li>Each dataset is identified by a 5-digit number (e.g., <code>14275</code>)</li> <li>Metadata and beam-synchronous scalar values are contained in a <code>.mat</code> dataset file (e.g., <code>14275.mat</code>).</li> <li>The dataset file has the following fields: <ul> <li><code>.metadata</code> containing all the generic metadata</li> <li><code>.state</code> containing all the <em>non-beam-synchronous</em> data (once per dataset; magnet settings etc.)</li> <li><code>.scalars</code> containing all the <em>beam-synchronous scalar</em> data (once per shot; BPM readings etc.)</li> <li><code>.vectors</code> containing all the <em>beam-synchronous vector</em> data (once per shot; scope traces etc.)</li> <li><code>.images</code> containing all the <em>beam-synchronous image</em> data, with relative URLs (once per shot; spectrometer images etc.)</li> </ul> </li> <li>The corresponding images (linked from the <code>.mat</code> file) are contained in the <code>images</code> folder, sorted by scan step.</li> </ul> <p><br><strong>Instructions for plotting all figures*:</strong></p> <ol> <li>Change directory to <code>4_FIGURES/</code></li> <li>In MATLAB, run <code>plot_all_figures();</code></li> <li>The 4 main figures and 13 supplementary figures will be plotted</li> </ol> <p><strong>Instructions for generating the 6D phase space for simulations*:</strong></p> <ol> <li>Change directory to<code> 3_SIMULATION/input_beam_generation/</code></li> <li>In MATLAB, run <code>generate_beam_and_plasma();</code></li> <li>The full analysis will up to several minutes (the files are stored in the <code>_files</code> folder)</li> </ol> <p><strong>Instructions for performing HiPACE++ simulations*:</strong></p> <ol> <li>Change directory to e.g. <code>3_SIMULATION/simulations/experimental_cell_50mm/</code></li> <li>The HiPACE++ input file is called <code>input_file</code></li> <li>This file refers to the plasma profile (<code>plasma_short.csv</code>) and beam files (<code>beam.h5</code> and <code>driver.h5</code>) found in <code>3_SIMULATION/run_notebooks/inputs/</code></li> </ol> <p><strong>Instructions for re-performing all the analysis*:</strong></p> <ol> <li>Change directory to <code>2_ANALYSIS/</code></li> <li>In MATLAB, run <code>run_all_analyses();</code></li> <li>The full analysis will up to several hours (the files are stored in various <code>_files</code> folders)</li> </ol> <p><em>* The scripts use UNIX system calls and are only compatible with Linux and Mac, but not Windows.</em></p>
Myocardial ultrastructure of human heart failure with preserved ejection fraction
<p>These transmission electron micrographs were obtained from endocardial biopsies of patients with heart failure and preserved ejection fraction, or from non-failling control myocardium. The myocardium is from the right side of the ventricular septum. Images are shown at various magnification levels indicated in the title of the image. Images with titles: HH_DM+ or HH_DM-; Mixed_DM+ or Mixed_DM-; OB_DM+ or OB_DM-; or NF_DM+ or NF_DM- show examples from the primary groups, HH represents HFpEF patients with primarily hypertensive hypertrophic heart disease and the least obesity; OB represents HFpEF patients with primarily severe obesity and the least hypertensive hypertrophic disease; Mixed matches obesity and hypertensive hypertrophic heart disease in HFpEF patients to levels obsserved in the HH and OB groups, and NF is non-failing controls. </p> <p>Additional images are shown for NF, HH, OB, and Mixed from the remaining patients in this study are provided at two magnification levels. These are provided as individual pictures as well. </p> <p> </p>
Supplementary dataset to the publication "Ultraviolet C inactivation of Coxiella burnetii for production of a structurally preserved whole cell vaccine antigen"
<p>The dataset supplements the journal article "Ultraviolet C inactivation of <em>Coxiella burnetii </em>for production of a structurally preserved whole cell vaccine antigen" published by Katja Mertens-Scholz, Amira A. Moawad, Elisabeth M. Liebler-Tenorio, Andrea Helming, Jennifer Andrack, Peter Miethe, Heinrich Neubauer, Mathias W. Pletz and Ina-Gabriele Richter in the journal BMC Microbiology (https://doi.org/10.1186/s12866-024-03246-z). The file "NMII 100µW" contains all data regarding inactivation of <em>C. burnetii</em> Nine Mile phase II with 100µW in a time dependent manner. The file "NMI 100 and 250µW" contains all data regarding inactivation of <em>C. burnetii</em> Nine Mile phase I with 100µW and 250µW in a time dependent manner. The file "surviving fraction" contains all data regarding inactivation of <em>C. burnetii </em>Nine Mile phase I and II after UVC treatment. The file "serology" contains all data obtained from ELISA experiments. The file "diameter" contains all data regarding the bacterial diameter after UVC treatment.</p>
Supplementary data: Geometry-preserving Expansion Microscopy microplates enable high fidelity nanoscale distortion mapping
<p>--- Data supplement---</p> <p>--- Title: Geometry-preserving Expansion Microscopy microplates enable high fidelity nanoscale distortion mapping</p> <p>The zip file contains the following directories and subdirectories. The files, recommended software, calling code and relevance to the main manuscript (preprint found at https://doi.org/10.1101/2023.02.20.529230) are included in the notes below:</p> <p>(i) “STL files” – Includes .stl file formats of the Expansion Microscopy microplate components. These files can be opened with any CAD software (e.g. Fusion 360) or any opensource 3D printer slicer programme (e.g. Chitubox v1.9.5)</p> <p>(ii) “Image alignment & distortion analysis code” – Directory containing the ImageJ macros and custom-written Python scripts for the analysis pipeline described in the main manuscript, from image scaling and alignment to for distortion plotting and RMS Error analysis and plotting. Subdirectories include:</p> <ul> <li>a.“Distortion analysis and RMSE plotting code” – Directory contains custom-written Python scripts for updated distortion analysis, plotting, RMS error calculation, and code for combining the plots. Each .py file can be run with any Python distribution. Dependency libraries and modules (all opensource) include numpy, os, cv2, skimage, and tifffile</li> <li>b.“Basic Align Macro.ijm” – ImageJ macro for basic image alignment of pre- and post-Expansion Microscopy images. Refer to <a href="https://imagej.nih.gov/ij/developer/macro/macros.html#tools">https://imagej.nih.gov/ij/developer/macro/macros.html#tools</a> on how to install and run ImageJ macros.</li> </ul> <p> </p> <p>(iii)“Example data and analysis scripts” – Directory containing example datasets and worked examples of analysis. Subdirectories include:</p> <ul> <li>a.“Single-channel_HeLa_cells”. Worked example of single-colour dataset of a cluster of HeLa cells stained with NHS-AZ488. Folder includes pre-Expansion and post-Expansion images (.tif format), overlays of the pre- and post-Expansion images along with distortion vector maps, and plots of normalised RMS error (in % values) against measurement length scale (in micrometers) saved as numpy arrays (.npy format). This can be called in using a Python code similar to: numpy.load("file name")</li> <li>b.“Multiplexed_Drosophila_wing”. Worked example of two-colour dataset of Drosophila fly wing tissue images stained with NHS-Alexa647 and anti-E-cad-GFP/Alexa488. Folder includes pre-Expansion and post-Expansion images (.tif format), overlays of the pre- and post-Expansion images along with distortion vector maps, and plots of normalised RMS error (in % values) against measurement length scale (in micrometers) saved as numpy arrays (.npy format).</li> <li>c.“Multiplexed_HeLa_cells”. Worked example of two-colour dataset of cultured HeLa cell images stained with NHS-AZ488 and antibodies. Each folder includes pre-Expansion and post-Expansion images (.tif format), overlays of the pre- and post-Expansion images along with distortion vector maps, and plots of normalised RMS error (in % values) against measurement length scale (in micrometers) saved as numpy arrays (.npy format): <ul> <li>I.“KDELAlexa594_NHSAZ488” – antibody staining against KDEL</li> <li>II.“NUP98Alexa594_NHSAZ488” – antibody staining against Nups98</li> </ul> </li> </ul> <p> </p> <ul> <li>d.“Distortion Correction”. Folder contains two subfolders of output images from distortion corrections using the Linear Stack Alignment with SIFT plugin in ImageJ v1.54f. Each example consists of a pre- and post-Expansion image file, and the ‘corrected’ image file generated with 5, 10, and 50 voxel B-spline sampling.</li> </ul> <p> </p> <p>These files are placed in public domain under Creative Commons license CC BY-ND 4.0</p>
Mohonk Preserve Grassland Field Monitoring 2017-2021
Between 2017-2021, Mohonk Preserve inventoried vegetation in its old-fields and grasslands. The goal was to increase understanding and knowledge of the Preserve’s vegetation communities so informed management strategies could be developed. This data provides information on species composition; occurrence frequency; vegetation type (woody, forb, grass, sedge, etc.); species percent cover (dominance); and species listed, invasive, and pollinator importance status. Five fields have been sampled thus far: Spring Farm (SF, plots [n]= 96); Glory Hill (GF, n= 45); Testimonial Gateway (TG, n= 66); Brook Farm (BF, n= 36); and Pine Farm (PF, n= 27). Soil samples were taken from three sites in 2018: Spring Farm, Glory Hill, and Testimonial Gateway. All data collection occurred between the months of May and August. There are plans to add more plots to sites Brook Farm, Pine Farm, and a field that has not yet been sampled, Klein kill Farm. There are no immediate plans to resample Spring Farm, Glory Hill, or Testimonial Gateway.
Mohonk Preserve Phenology Monitoring 1912-present
Phenology records around Mohonk Lake date back to the early 1900s, when Daniel and Keith Smiley started noting the date of spring bird arrivals. The Preserve’s Daniel Smiley Research Center continues this tradition of natural history observation and has expanded the scope of the Smileys’ phenology records to monitor seasonal changes in plants and other fauna at Mohonk Preserve on local, regional, and national levels. Alongside our long-term weather data, these data provide insight into the changing communities in the Mohonk Preserve in response to changing climate. These data include first occurrence dates for each of the taxa and associated life stages in the vicinity of Mohonk Preserve and were collected by staff at the Daniel Smiley Research Center.
Climate data for Mojave National Preserve Granite Mountains 2019
Basic climate data derived from a local weather station. Mean and max temp with humidity relevant to avian abundance surveys conducted at that location during those specific time blocks.
NEON Biorepository Aquatic Microalgae Collection (Chemical Preservation) (repackaging of occurrences published by the NEON Biorepository Data Portal)
This collection contains subsamples of aquatic microalgae preserved in either glutaraldehyde or a high-iodine Lugol's solution (NEON sample class: ptx_taxonomy_in.preserved). Periphyton and phytoplankton samples are collected three times per year at wadeable stream, river, and lake sites during aquatic biology bout windows, roughly in spring, summer, and fall. Benthic samples are collected using the most appropriate sampler for the habitat and substratum type, including rock scrubs, grab samples, and epiphyton. In wadeable streams, periphyton samples are collected in the two most dominant benthic habitat types (e.g. riffles, runs, pools, step pools), and seston samples were collected from the water column near the S2 sensor (seston samples were discontinued in 2018). In lakes, water-column phytoplankton samples are collected near the buoy and littoral sensors using a Kemmerer sampler, and in littoral areas using the best benthic sampling method for the dominant substratum type. In rivers, phytoplankton samples are collected near the buoy and two other deep-water locations using a Kemmerer or Van Dorn sampler, and in littoral areas using the best benthic sampling method for the dominant substratum type. All field-collected samples are split into subsamples in the domain support facility, preserved, and shipped to a contracting taxonomy laboratory where samples are further subsampled for analysis and archiving. All samples are archived in 20 mL glass scintillation vials and stored in a temperature (17-18°C) and humidity controlled environment. Phytoplankton and seston samples are preserved in a 2% high-iodine Lugol's solution from 2014-2020 and 0.5% glutaraldehyde starting in 2021. Periphyton samples are preserved in 0.5% glutaraldehyde. See related links below for protocols and NEON related data products.
Leaf litter quality induces morphological changes in wood frog (Lithobates sylvaticus) metamorphs, Oakland University Biological Preserve (MI, USA) 2010.
For organisms that exhibit complex life cycles, resource conditions experienced by individuals before metamorphosis can strongly affect phenotypes later in life. Such resource-induced effects are known to arise from variation in resource quantity, yet little is known regarding effects stemming from variation in resource quality (e.g., chemistry). For larval anurans, we hypothesized that variation in resource quality will induce a gradient of effects on metamorph morphology. We conducted an outdoor mesocosm experiment in which we manipulated resource quality by rearing larval wood frogs (Lithobates sylvaticus) under 11 leaf litter treatments. The litter species represented plant species found in open- and closed-canopy wetlands and included many plant species of current conservation concern (e.g., green ash, common reed). Consistent with our hypothesis, we found a gradient of responses for nearly all mass-adjusted morphological dimensions. Hindlimb dimensions and gut mass were positively associated with litter nutrient content and decomposition rate. In contrast, forelimb length and head width were positively associated with concentrations of phenolic acids and dissolved organic carbon. Limb lengths and widths were positively related with the duration of larval period, and we discuss possible hormonal mechanisms underlying this relationship. There were very few, broad differences in morphological traits of metamorphs between open- and closed-canopy litter species or between litter and no-litter treatments. This suggests that the effects of litter on metamorph morphology are litter species-specific, indicating that the effects of changing plant community structure in and around wetlands will largely depend on plant species composition.
History of Acid Precipitation on the Shawangunk Ridge: Mohonk Preserve Precipitation Depths and pH, 1976 to Present
We, the staff, volunteers and associates of the Mohonk Preserve, have been collecting precipitation data at Mohonk Lake since January 1976. The Level1_MohonkPrecipData includes precipitation depths recorded either during or at the conclusion of every precipitation event. This dataset additionally includes pH measurements for most precipitation collections.The Level2_MohonkPrecipData summarizes data collections into precipitation events where the precipitation depth is cumulative and the pH is averaged for all data collections in that event. We measured precipitation via a National Weather Service Rain Gauge and the pH was measured at a Cooperative Weather Service Station at Mohonk Lake.
Mohonk Preserve Amphibian and Water Quality Monitoring Dataset at 11 Vernal Pools from 1931-Present
"The Mohonk Preserve's Daniel Smiley Research Center has been monitoring species occupancy, reproductive success, and water quality of 11 vernal pools (Ski Loop, Bonticou, Terrace, Long Woodland Pool, Long Woodland Swamp, Oakwood, Sleepy Hollow, Hermits, North Mud Pond, Canaan, and Talus) on the Preserve each spring from April 1931 to May 2019 (present). This project aims to document changes in the reproductive behavior and phenology of amphibians and allow research access to historical, longitudinal records. The dataset is a paired record of amphibian occurence with environmental indicators spanning nearly 90 years of data collection. The dataset includes environmental conditions for the 730 sampling events associated with the species occurences with complete coverage air temperature and precipitation records and partial coverage for a variety of other weather and water quality measures. Species occurence data collection has included species identification and counts of live and dead adults, mated pairs, spermatophores, egg masses, juveniles, and tadpoles counts as well as a record of the level of frog calling. Weather conditions including precipitation, sky and wind codes; and water quality measurements including water temperature, pH, and depth. Collection of data was sporadic from 1931 - 1991 but has been collected consistently from 1991 to present. We also began monitoring dissolved oxygen, nitrate concentrations, and conductivity of the vernal pools using a YSI Sonde Professional Plus Instrument and turbidity using a turbidity tube in February 2018. The data collection is ongoing, as are digitization efforts, and the data package will receive periodic updates."
Annual Point Count Breeding Bird Survey at Pepperwood Preserve in the California Coast Ranges 2007-2019
The Dwight Center for Conservation Science at Pepperwood is an ecological institute dedicated to educating, engaging, and inspiring our community through habitat preservation, science-based conservation, leading-edge research, and interdisciplinary educational programs. Our mission is to steward the life and landscapes of the 3,200-acre Pepperwood Preserve and to advance science-based conservation of ecosystems throughout our region and beyond. The Pepperwood Breeding Bird Survey was initiated in the spring of 2007 with the goal of establishing a set of baseline bird community data that would be built upon for years to come. Four transects (totaling 38 points) are surveyed annually using standardized five-minute point count protocols outlined by the Point Reyes Bird Observatory (now called Point Blue Conservation Science; Ballard et al. 2003) and the Handbook of Field Methods for Monitoring Landbirds (Ralph et al. 1993). Surveys are conducted by experienced volunteers during the breeding season starting in late April and ending in June, with each transect surveyed a total of three times. The Rogers Creek and Martin Creek transects were established in 2007. The Weimar Flat and Pepperwood Road transects were established in 2008 and 2012, respectively, to ensure comprehensive coverage across the various habitats that occur at the preserve including Douglas-fir forest, mixed hardwood forest, oak woodland/forest, chaparral, and open grasslands. This dataset includes data collected between 2007-2019.
Post-Tubbs Fire Chaparral Floristic Survey at Pepperwood Preserve in the California Coast Ranges 2018-2019
The Dwight Center for Conservation Science at Pepperwood is an ecological institute dedicated to educating, engaging, and inspiring our community through habitat preservation, science-based conservation, leading-edge research, and interdisciplinary educational programs. Our mission is to steward the life and landscapes of the 3,200-acre Pepperwood Preserve and to advance science-based conservation of ecosystems throughout our region and beyond. Following the October 2017 Tubbs Fire, Pepperwood hired Nomad Ecology, LLC, to implement Nomad Ecology's post-fire research program at Pepperwood. Specifically, Nomad Ecology conducted a two-year study of post-fire plant diversity and succession in chaparral at the preserve. Species richness and ecological dynamics are not well understood in these post-fire areas (especially in northern California) despite high interest from land managers, ecologists, and botanists. Documentation of the post-fire flora and the sensitive species that are part of this fleeting diversity is essential to understanding the full range of natural resources associated with chaparral ecosystems, and thus key to developing conservation goals specific to Pepperwood. This study documented the burn severity and diversity and abundance of the fleeting post-Tubbs Fire flora in spring 2018 and 2019 using species ocular cover estimates across ten 50-meter belt transects in four different soil types: rhyolite, fluvial and lacustrine deposits, andesite, and serpentinite.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.