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Members and Destinations of Spain's Judiciary (2005-2023)
<p>This document contains the documentation of the dataset <em>Members and Destinations of Spain’s Judiciary (2005-2023)</em>, created at the University of Barcelona. The work is part of the I+D+i project PREFJUDIPOL: <em>Preferences, career, and territory. The politics of judicial inequality in Spain</em> (PID-2020-113871RB-I00), funded by MICIU/AEI/10.13039/501100011033/.</p> <p>The data have been used to produce the following paper:</p> <ul> <li>Vallbé, Joan-Josep and Ramírez-Folch, Carmen and Lozano, Luis Mario, Glass ceiling or merit? The politics of judicial promotion in a civil law system (July 26, 2024). Pre-print version available at <a href="https://ssrn.com/abstract=">SSRN</a>.</li> </ul>
2005-2099 High resolution bioclimatic variables for the surface and bottom of the Mediterranean Sea.
<p><em><span>This dataset provides annual statistical descriptors (mean, minimum, maximum, range and standard deviation) of key biogeochemical and physical variables for the Mediterranean Sea. It covers the period 2005-2099 under the RCP8.5 scenario, with a spatial resolution of 1/24 degree (~4km²). Variables include temperature, salinity, pH, water velocity, nutrients (NO3, PO4, NH4), dissolved inorganic carbon, oxygen, and net primary production. Data are available for both surface and at bathymetry level. The original projections were generated using OGSTM-BFM and MFS16 models at daily time and 1/16 degree grid resolution. We downscaled these to 1/24 degree and applied Quantile Delta Mapping bias correction using CMEMS reanalysis products for 2005-2020. The dataset is provided in a user-friendly format, making it accessible for various ecological and environmental modelling applications.</span></em></p>
Monthly aggregated GLASS FAPAR V6 (250 m): 5th percentile monthly time-series (2005)
<p><strong>List of Subdatasets:</strong></p> <ul> <li>Long-term data: <a href="https://doi.org/10.5281/zenodo.8381409">2000-2021</a></li> <li>5th percentile (p05) monthly time-series: <a href="https://doi.org/10.5281/zenodo.8408654">2000</a>, <a href="https://doi.org/10.5281/zenodo.8411611">2001</a>, <a href="https://doi.org/10.5281/zenodo.8412712">2002</a>, <a href="https://doi.org/10.5281/zenodo.8413021">2003</a>, <a href="https://doi.org/10.5281/zenodo.8413689">2004</a>, <a href="https://doi.org/10.5281/zenodo.8414639">2005</a>, <a href="https://doi.org/10.5281/zenodo.8411609">2006</a>, <a href="https://doi.org/10.5281/zenodo.8414085">2007</a>, <a href="https://doi.org/10.5281/zenodo.8414960">2008</a>, <a href="https://doi.org/10.5281/zenodo.8415476">2009</a>, <a href="https://doi.org/10.5281/zenodo.8415686">2010</a>, <a href="https://doi.org/10.5281/zenodo.8412154">2011</a>, <a href="https://doi.org/10.5281/zenodo.8414082">2012</a>, <a href="https://doi.org/10.5281/zenodo.8411364">2013</a>, <a href="https://doi.org/10.5281/zenodo.8414933">2014</a>, <a href="https://doi.org/10.5281/zenodo.8415414">2015</a>, <a href="https://doi.org/10.5281/zenodo.8412246">2016</a>, <a href="https://doi.org/10.5281/zenodo.8414083">2017</a>, <a href="https://doi.org/10.5281/zenodo.8411366">2018</a>, <a href="https://doi.org/10.5281/zenodo.8415203">2019</a>, <a href="https://doi.org/10.5281/zenodo.8415549">2020</a>, <a href="https://doi.org/10.5281/zenodo.8387608">2021</a></li> <li>50th percentile (p50) monthly time-series: <a href="https://doi.org/10.5281/zenodo.8408710">2000</a>, <a href="https://doi.org/10.5281/zenodo.8408798">2001</a>, <a href="https://doi.org/10.5281/zenodo.8408866">2002</a>, <a href="https://doi.org/10.5281/zenodo.8415319">2003</a>, <a href="https://doi.org/10.5281/zenodo.8415619">2004</a>, <a href="https://doi.org/10.5281/zenodo.8415878">2005</a>, <a href="https://doi.org/10.5281/zenodo.8416080">2006</a>, <a href="https://doi.org/10.5281/zenodo.8416619">2007</a>, <a href="https://doi.org/10.5281/zenodo.8417164">2008</a>, <a href="https://doi.org/10.5281/zenodo.8417513">2009</a>, <a href="https://doi.org/10.5281/zenodo.8417708">2010</a>, <a href="https://doi.org/10.5281/zenodo.8415669">2011</a>, <a href="https://doi.org/10.5281/zenodo.8416000">2012</a>, <a href="https://doi.org/10.5281/zenodo.8416542">2013</a>, <a href="https://doi.org/10.5281/zenodo.8417055">2014</a>, <a href="https://doi.org/10.5281/zenodo.8417467">2015</a>, <a href="https://doi.org/10.5281/zenodo.8415747">2016</a>, <a href="https://doi.org/10.5281/zenodo.8416333">2017</a>, <a href="https://doi.org/10.5281/zenodo.8416835">2018</a>, <a href="https://doi.org/10.5281/zenodo.8417326">2019</a>, <a href="https://doi.org/10.5281/zenodo.8417589">2020</a>, <a href="https://doi.org/10.5281/zenodo.8388078">2021</a></li> <li>95th percentile (p95) monthly time-series: <a href="https://doi.org/10.5281/zenodo.8408949">2000</a>, <a href="https://doi.org/10.5281/zenodo.8409059">2001</a>, <a href="https://doi.org/10.5281/zenodo.8409154">2002</a>, <a href="https://doi.org/10.5281/zenodo.8409362">2003</a>, <a href="https://doi.org/10.5281/zenodo.8416487">2004</a>, <a href="https://doi.org/10.5281/zenodo.8417029">2005</a>, <a href="https://doi.org/10.5281/zenodo.8417833">2006</a>, <a href="https://doi.org/10.5281/zenodo.8417996">2007</a>, <a href="https://doi.org/10.5281/zenodo.8418308">2008</a>, <a href="https://doi.org/10.5281/zenodo.8418669">2009</a>, <a href="https://doi.org/10.5281/zenodo.8418986">2010</a>, <a href="https://doi.org/10.5281/zenodo.8417649">2011</a>, <a href="https://doi.org/10.5281/zenodo.8417816">2012</a>, <a href="https://doi.org/10.5281/zenodo.8417959">2013</a>, <a href="https://doi.org/10.5281/zenodo.8418253">2014</a>, <a href="https://doi.org/10.5281/zenodo.8418625">2015</a>, <a href="https://doi.org/10.5281/zenodo.8417759">2016</a>, <a href="https://doi.org/10.5281/zenodo.8417898">2017</a>, <a href="https://doi.org/10.5281/zenodo.8418076">2018</a>, <a href="https://doi.org/10.5281/zenodo.8418442">2019</a>, <a href="https://doi.org/10.5281/zenodo.8418751">2020</a>, <a href="https://doi.org/10.5281/zenodo.8392976">2021</a></li> </ul> <p><strong>General Description</strong></p> <p>The <i>monthly aggregated Fraction of Absorbed Photosynthetically Active Radiation (FAPAR)</i> dataset is derived from <abbr title="glass.umd.edu/FAPAR/MODIS/250m/">250m 8d GLASS V6 FAPAR</abbr>. The data set is derived from Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance and LAI data using several other FAPAR products (MODIS Collection 6, GLASS FAPAR V5, and PROBA-V1 FAPAR) to generate a bidirectional long-short-term memory (Bi-LSTM) model to estimate FAPAR. The dataset time spans from March 2000 to December 2021 and provides data that covers the entire globe. The dataset can be used in many applications like land degradation modeling, land productivity mapping, and land potential mapping. The dataset includes:</p> <ul> <li><strong>Long-term:</strong></li> </ul> <p>Derived from monthly time-series. This dataset provides linear trend model for the p95 variable: (1) slope beta mean (p95.beta_m), p-value for beta (p95.beta_pv), intercept alpha mean (p95.alpha_m), p-value for alpha (p95.alpha_pv), and coefficient of determination R<sup>2</sup> (p95.r2_m).</p> <ul> <li><strong>Monthly time-series:</strong></li> </ul> <p>Monthly aggregation with three standard statistics: (1) 5th percentile (p05), median (p50), and 95th percentile (p95). For each month, we aggregate all composites within that month plus one composite each before and after, ending up with 5 to 6 composites for a single month depending on the number of images within that month.</p> <p><strong>Data Details</strong></p> <ul> <li><strong>Time period:</strong> March 2000 – December 2021</li> <li><strong>Type of data:</strong> Fraction of Absorbed Photosynthetically Active Radiation (FAPAR)</li> <li><strong>How the data was collected or derived:</strong> Derived from 250m 8 d GLASS V6 FAPAR using Python running in a local HPC. The time-series analysis were computed using the <a href="https://github.com/scikit-map/scikit-map">Scikit-map</a> Python package.</li> <li><strong>Statistical methods used:</strong> for the long-term, Ordinary Least Square (OLS) of p95 monthly variable; for the monthly time-series, percentiles 05, 50, and 95.</li> <li><strong>Limitations or exclusions in the data:</strong> The dataset does not include data for Antarctica.</li> <li><strong>Coordinate reference system:</strong> EPSG:4326</li> <li><strong>Bounding box (Xmin, Ymin, Xmax, Ymax):</strong> (-180.00000, -62.0008094, 179.9999424, 87.37000)</li> <li><strong>Spatial resolution:</strong> 1/480 d.d. = 0.00208333 (250m)</li> <li><strong>Image size:</strong> 172,800 x 71,698</li> <li><strong>File format:</strong> Cloud Optimized Geotiff (COG) format.</li> </ul> <p><strong>Support</strong></p> <p>If you discover a bug, artifact, or inconsistency, or if you have a question please raise a GitHub issue: <a href="https://github.com/Open-Earth-Monitor/Global_FAPAR_250m/issues">https://github.com/Open-Earth-Monitor/Global_FAPAR_250m/issues</a></p> <p><strong>Reference</strong></p> <p>Hackländer, J., Parente, L., Ho, Y.-F., Hengl, T., Simoes, R., Consoli, D., Şahin, M., Tian, X., Herold, M., Jung, M., Duveiller, G., Weynants, M., Wheeler, I., (2023?) "Land potential assessment and trend-analysis using 2000–2021 FAPAR monthly time-series at 250 m spatial resolution", submitted to PeerJ, preprint available at: <a href="https://doi.org/10.21203/rs.3.rs-3415685/v1">https://doi.org/10.21203/rs.3.rs-3415685/v1</a></p> <p><strong>Name convention</strong></p> <p>To ensure consistency and ease of use across and within the projects, we follow the standard Open-Earth-Monitor file-naming convention. The convention works with 10 fields that describes important properties of the data. In this way users can search files, prepare data analysis etc, without needing to open files. The fields are:</p> <ol> <li><strong>generic variable name:</strong> fapar = Fraction of Absorbed Photosynthetically Active Radiation</li> <li><strong>variable procedure combination:</strong> essd.lstm = Earth System Science Data with bidirectional long short-term memory (Bi–LSTM)</li> <li><strong>Position in the probability distribution / variable type:</strong> p05/p50/p95 = 5th/50th/95th percentile</li> <li><strong>Spatial support:</strong> 250m</li> <li><strong>Depth reference:</strong> s = surface</li> <li><strong>Time reference begin time:</strong> 20000301 = 2000-03-01</li> <li><strong>Time reference end time:</strong> 20211231 = 2022-12-31</li> <li><strong>Bounding box:</strong> go = global (without Antarctica)</li> <li><strong>EPSG code:</strong> epsg.4326 = EPSG:4326</li> <li><strong>Version code:</strong> v20230628 = 2023-06-28 (creation date)</li> </ol>
City of Seattle, Seattle Public Utilities, Restoration Thinning Trial, 2005 - 2017, Cedar River Municipal Watershed, King County, WA
The Restoration Thinning (RT) Program in the Cedar River Municipal Watershed (CRMW) was one of three forest restoration programs (the others being Ecological Thinning and Planting) defined and funded through the Cedar River Watershed Habitat Conservation Plan (HCP) that was signed and initiated in April of 2000. Restoration thinning and ecological thinning projects were combined into the 'Upland Forest Thinning' project and are ongoing today to meet objectives outlined in the Habitat Conservation Plan and Forest Managment Plan. The primary goal of the RT program, which is analogous to pre-commercial thinning, was to actively thin dense young second-growth forest stands (generally less than 30 years old) to facilitate ecological development towards old-growth forest habitat conditions. Objectives of RT include: Reduce competition among trees. Stimulate tree growth. Increase light penetration under the top tree canopy. Increase tree and understory plant species diversity. Accelerate forest development beyond the competitive exclusion stage towards a more biologically diverse stage. Extend the forest development stand initiation stage such that diverse species become established and diverse stand structures develop. Provide multiple development pathways for variable forest stand structures. Reduce long-term fire hazard. Increase resilience to catastrophic windthrow, insect, or disease outbreak. Increase habitat connectivity and structural variability of riparian areas. This data package describes a forest restoration trial in young conifer forests of the western central Cascade Range in Washington State, USA. Young second-growth forests often regenerate as very dense, homogeneous stands following harvesting. These forests have low species diversity and trees often experience strong competition for resources. To increase tree vigor and growth and stimulate development of diverse understory, shrub species stands are thinned with the long-term goal to restore diverse func
[DEPRECATED] MCR LTER: Coral Reef: Long-term Population Dynamics of Acanthaster planci, ongoing since 2005 (Reformatted to ecocomDP Design Pattern)
This ecocomDP formatted dataset is deprecated due to the fact that the focus of the original L0 dataset is population ecology, not community ecology. This data package is formatted according to the "ecocomDP", a data package design pattern for ecological community surveys, and data from studies of composition and biodiversity. For more information on the ecocomDP project see https://github.com/EDIorg/ecocomDP/tree/master, or contact EDI https://environmentaldatainitiative.org. This Level 1 data package was derived from the Level 0 data package found here: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-mcr&identifier=1039&revision=9 The abstract below was extracted from the Level 0 data package and is included for context: These data describe the abundance of Acanthaster planci, Crown of Thorns Sea stars, 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 A. planci observed on a five by fifty meter transect are recorded by a diver using SCUBA. Surveys are conducted between 0900 and 1600 hours (Moorea time) during late July or early August each year. Four replicate transects are surveyed in each of three habitats (forereef, backreef and fringing reef) at six locations, two on each of Moorea's three sides, on the forereef, six locations on the backreef (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. This monitoring program is consistent with the protocols adopted by the Global Coral Reef Monitoring Network and the Australian Institute of Marine Science for use with the Great Barrier Reef Long-term Monitoring Program. Thes
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
Eddy Flux Measurements, Tussock Station, Imnavait Creek, Alaska - 2005
The Biocomplexity Station was established in 2005 to measure landscape-level carbon, water and energy balances at Imnavait Creek, Alaska. The station is now contributing valuable data to the Arctic Observing Network that was established at two nearby stations. These will form part of a network of observatories with Abisko (Sweden), Zackenburg (Greenland) and a location in the Canadian High Arctic which will provide further data points as part of the International Polar Year. This particular part of the project focuses on simultaneous measurements of carbon, water and energy fluxes of the terrestrial landscape at hourly, daily, seasonal and multi-year time scales. These are the major regulatory drivers of the Arctic climate system and form key linkages and feedbacks between the land surface, the atmosphere and the oceans. We will provide a comprehensive description of the state of the regional Arctic system with respect to these variables, its overall regulation and controlling features and its interaction with the global system.
Large consumer isotope values, Shark River Slough, Everglades National Park (FCE LTER), Florida, USA, May 2005 - ongoing
This dataset provides information on the stable isotope values from multiple tissues from various consumers (especially bull sharks and American alligators) sampled within the Shark River Slough.
Consumer Stocks: Fish, Vegetation, and other Non-physical Data from Everglades National Park (FCE LTER), South Florida, USA from February 2000 to April 2005
We hypothesize that standing crops of consumers reflect patterns of allochthonous nutrient transport along the estuarine interface at the Florida Coastal Everglades (FCE) LTER. Our goal is to investigate how variation in hydrology, water quality, and disturbance influence secondary production. This data set represents the numeric count data of fish, plants, and other fauna.
Consumer Stocks: Fish Biomass from Everglades National Park (FCE), South Florida from February 2000 to April 2005
We hypothesize that standing crops of consumers reflect patterns of allochthonous nutrient transport along the estuarine interface at the Florida Coastal Everglades (FCE) LTER. Our goal is to investigate how variation in hydrology, water quality, and disturbance influence secondary production. This data set represents the numeric count data of fish, plants, and other fauna.
Physical Characteristics and Stratigraphy of Deep Soil Sediments from Shark River Slough, Everglades National Park (FCE) from 2005 and 2006
These data represent the results of piston-coring deep (around 1m) soil cores from Shark Slough sites, including FCE LTER site SRS3 and FCE related site NE-SRS1 from November 18, 2005 to February 26, 2006. Soils from 1-cm depth increments were analyzed for bulk density and stratigraphy. These analyses contribute to a paleoecological study to quantify past changes in vegetation and soil accumulation in relation to past climate variation, fire occurrences and water management.
Radiometric Characteristics of Soil Sediments from Shark River Slough, Everglades National Park (FCE) from 2005 and 2006
These data represent the results of radiometric dating of soil cores from Shark Slough sites, including FCE LTER sites SRS3 and SRS4 and FCE related site NE-SRS1 from November 18, 2005 to February 26, 2006. Soils from 1-cm depth increments were analyzed for bulk density and stratigraphy. These analyses contribute to a paleoecological study to quantify past changes in vegetation and soil accumulation in relation to past climate variation, fire occurrences and water management.
Flux measurements from the SRS-6 Tower, Shark River Slough, Everglades National Park, South Florida (FCE) from January 2004 to August 2005
Above canopy measurements of carbon dioxide fluxes and sensible and latent heating were obtained with an open path eddy covariance system positioned on the tower at 26-m. Additionally, measurements of solar irradiance, wind speed, air temperature and humidity were made every half hour.
Bull shark catches, water temperatures, salinities, and dissolved oxygen levels in the Shark River Slough, Everglades National Park (FCE) , from May 2005 to May 2009
This dataset provides information on the catches of bull sharks in the Shark River Slough in relation to physical factors including dissolved oxygen, water temperature, salinity, and distance upstream. Analysis of data collected from 2005-2007 indicate that distance from the Gulf of Mexico and dissolved oxygen concentrations have the largest effects on bull shark catch rates. Data are presented for both young of the year sharks, which are concentrated in areas away from the main channel approximately 20km upstream, and older juvenile sharks which are found along the main channel at similar distances upstream. Salinity has a surprisingly weak impact on catches over the time frame initially investigated.
Shark catches (longline), water temperatures, salinities, and dissolved oxygen levels, and stable isotope values in the Shark River Slough, Everglades National Park (FCE LTER), Florida, USA, May 2005 - ongoing
This dataset provides information on the catches of sharks in the Shark River Slough in relation to physical factors including dissolved oxygen, water temperature, salinity, and distance upstream. Analysis of data collected suggest that distance from the Gulf of Mexico and dissolved have the largest effects on shark catch rates, with most juvenile bull sharks being caught in Tarpon Bay. This dataset includes all sharks caught on longline gear, their morphometric data, and CNS stable isotope analysis for selected individuals.
Periphyton and Associated Environmental Data Relative from Samples Collected from the Greater Everglades, Florida, USA from September 2005 to November 2014
This data package contains peripihyton and environmental data collected annually during the wet season between 2005 and 2014 from sites distributed throughout the greater Everglades ecosystem. This project is part of the Comprehensive Everglades Restoration Program's Monitoring and Assessment Plan intended to document baseline variability in periphyton attributes for assessing the effectiveness of restoration projects. A total of 200 primary sampling units (PSU) of 800 m x 800 m are nested in 32 landscape units and each year, random coordinates are 'drawn' within each PSU and one sampleable draw is visited in each. Sampled periphyton is processed for diatoms, slides are prepared, and 500 frustules are enumerated and identified to the lowest possible taxonomic resolution per slide. Taxon abundances are then relativized to the total count. These data accompany environmental, periphyton biomass, and soft algal abundance datasets.
Relative Abundance Diatom Data from Periphyton Samples Collected from the Greater Everglades, Florida USA from September 2005 to November 2014
This data package contains relative diatom taxon abundances collected annually during the wet season between 2005 and 2014 from sites distributed throughout the greater Everglades ecosystem. This project is part of the Comprehensive Everglades Restoration Program's Monitoring and Assessment Plan intended to document baseline variability in periphyton attributes for assessing the effectiveness of restoration projects. A total of 200 primary sampling units (PSU) of 800 m x 800 m are nested in 32 landscape units and each year, random coordinates are 'drawn' within each PSU and one sampleable draw is visited in each. Sampled periphyton is processed for diatoms, slides are prepared, and 500 frustules are enumerated and identified to the lowest possible taxonomic resolution per slide. Taxon abundances are then relativized to the total count. These data accompany environmental, periphyton biomass, and soft algal abundance datasets. Post-2014 data are available upon request to the project PI, Evelyn Gaiser.
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.