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84 results for “national level”
National Park Service - South Florida/Caribbean Inventory & Monitoring Network - BISC1 SET Surface Water level data from in Biscayne National Park, Florida, USA (2016-2025)
Surface water level data (m) was collected in Biscayne National Park (BISC) by the South Florida/Caribbean Inventory and Monitoring Network (SFCN) as part of the Soil Elevation Table (SET) vital sign monitoring program. Water level data collected from 2016 to 2025 is included in this dataset. The water level data was collected using HOBOware Onset Water Level Data Loggers. This dataset belongs to Site 1, known as BISC-SET-1 or BISC1. This data-package is complete.
National Park Service - South Florida/Caribbean Inventory & Monitoring Network - BISC2 SET Surface Water level data from in Biscayne National Park, Florida, USA (2017-2025)
Water level data (m) was collected in Biscayne National Park (BISC) by the National Park Service - South Florida/Caribbean Inventory and Monitoring Network (SFCN) as part of the Soil Elevation Table (SET) vital sign monitoring program. Water level data collected from 2017-2025 is included in this dataset. The water level data was collected using HOBOware Onset Water Level Data Loggers. This dataset belongs to Site 2, known as BISC-SET-2 or BISC2. This data-package is complete.
National Park Service - South Florida/Caribbean Inventory & Monitoring Network - SARI SET Surface Water level data from Salt River Bay National Historical Park and Ecological Preserve, St. Croix, US Virgin Islands.
Surface water level data (m) was collected in Salt River Bay National Historic Park and Ecological Preserve (SARI) by the South Florida/Caribbean Inventory and Monitoring Network (SFCN) as part of the Soil Elevation Table (SET) vital sign monitoring program. Water level data collected from 2017 to 2024 is included in this dataset. The water level data was collected using HOBOware Onset Water Level Data Loggers. This data-package is complete.
National Park Service - South Florida/Caribbean Inventory & Monitoring Network - Mary's Point SET Surface Water level data from Virgin Islands National Park, St. John, US Virgin Islands
Surface water level data (m) was collected in Virgin Islands National Park, Mary's Point (MARY) by the South Florida/Caribbean Inventory and Monitoring Network (SFCN) as part of the Soil Elevation Table (SET) vital sign monitoring program. Water level data collected from 2017 to 2024 is included in this dataset. The water level data was collected using HOBOware Onset Water Level Data Loggers. This data-package is complete.
National Park Service - South Florida/Caribbean Inventory & Monitoring Network - Water Creek SET Surface Water level data from Virgin Islands National Park, St. John, US Virgin Islands
Surface water level data (m) was collected in Virgin Islands National Park, Water Creek (WACR) by the South Florida/Caribbean Inventory and Monitoring Network (SFCN) as part of the Soil Elevation Table (SET) vital sign monitoring program. Water level data collected from 2017 to 2024 is included in this dataset. The water level data was collected using HOBOware Onset Water Level Data Loggers. This data-package is complete.
Toklat River Fire in Denali National Park and Preserve: Site level environmental, soil, tree, vegetation, and fire characteristics measured in 2016
This dataset contains site-level average estimated of environmental, soil, tree, vegetation, and fire characteristics measured in 2016, three years after the Toklat River Fire in Denali National Park and Preserve. Measured parameters include latitude, longitude, slope, aspect, elevation, moisture classification, bulk density of the surface soil, residual organic soil depth, thaw depth, burn depth, density and basal area of all tree species pre-fire, the density of all tree species post-fire, estimates of above- and below-ground carbon combustion, and understory vegetation turnover from pre-fire to post-fire. There is also data on seed trap collection and experimental regeneration of seedlings collected in 2017 and 2018 at a subset of sites.
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.
Water Levels and Porewater Temperature data from the Shark River and Taylor River Slough mangrove sites, Everglades National Park (FCE LTER), South Florida, USA: May 2001 - ongoing
Water levels for SRS4 are recorded at 1h intervals. Water level recorder is located in the mangrove forest approximately 80 m inland at Tarpon Bay. Water levels for SRS5 are recorded at 1h intervals. Water level recorder is located in the mangrove forest approximately 80 m at the Shark River Slough. Water levels for SRS6 are recorded at 1h intervals. Water level recorder is located in the mangrove forest approximately 80 m at the Shark River Slough. Water levels for SRS7 are recorded at 1h intervals. Water level recorder is located in the mangrove forest approximately 80 m at the Shark River Slough. Water levels for TS/Ph6a are recorded at 1h intervals. Water level recorder is located in the mangrove forest approximately 80 m inland at the Taylor River Slough. Water level recorder is located in between of two 20 by 20 m permanent monitoring plots. Water levels for TS/Ph7a are recorded at 1h intervals. Water level recorder is located in the mangrove forest approximately 60 m inland at the Taylor River Slough. Water level recorder is located in between of two 20 by 20 m permanent monitoring plots. Water levels for TS/Ph8 are recorded at 1h intervals. Water level recorder is located in the mangrove forests 40 m inland at the Joe Bay area. Water level recorder is located in between of two 20 by 20 m permanent monitoring plots. All water level data are measured by Florida International University.
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.
Long-term species-level measurements of fall season aboveground net primary production in the Monsoon Rainfall Manipulation Experiment (MRME), Sevilleta National Wildlife Refuge, New Mexico, USA
Anticipated intensification of the North American Monsoon in the southwestern United States is predicted to shift growing season rainfall patterns, historically characterized by frequent small rain events, to a more extreme precipitation regime consisting of fewer, but larger rain events. Atmospheric nitrogen deposition is also increasing throughout this dryland region as a result of anthropogenic activities. Alterations in rainfall size and frequency, along with changes in nitrogen availability, are likely to have significant consequences for aboveground net primary production (ANPP) and plant community dynamics in drylands, where ecological processes are limited by water and nitrogen availability. This data package accompanies an associated manuscript in which we used fourteen years (2007-2020) of growing season ANPP measurements from the long-term Monsoon Rainfall Manipulation Experiment (MRME), located in the Sevilleta National Wildlife Refuge, to investigate how changes in rainfall regimes, along with chronic nitrogen enrichment, impact ANPP in a northern Chihuahuan Desert grassland.
Temperatures,salinities, and dissolved oxygen levels in the Shark River Slough, Everglades National Park (FCE LTER) , from May 2005 to May 2014
This dataset provides information on the environmental conditions in the Shark River Slough including dissolved oxygen, water temperature, and salinity. Data suggest that environmental parameters vary spatially and temporally within the system, especially during transition periods between the wet and dry seasons.
Water Levels from the Taylor Slough, Everglades National Park (FCE LTER), South Florida from April 1996 to 2012
Data is a compilation of 15 minute data into daily averages for use with other FCE-LTER datasets. For original dataset Meta-data and other information please visit the South Florida Information Access (SOFIA) website at https://archive.usgs.gov/archive/sites/sofia.usgs.gov/index.html (the current URL as of March 2020)
Large shark catches (Drumline), water temperatures, salinities, dissolved oxygen levels, and stable isotope values in the Shark River Slough, Everglades National Park (FCE LTER) from May 2009 to May 2011
This dataset provides information on the catches of large 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 salinity have the largest effects on shark catch rates, with most large sharks being caught at the mouth of the estuary in high salinity waters. This dataset includes all sharks caught on drumline gear, including large coastal species such as bull sharks and lemon sharks, as well as smaller coastal species such as Atlantic sharpnose sharks and blacknose sharks.
Fecal glucocorticoid metabolite levels of American pika (Ochotona princeps) and habitat characteristics of their associated territories found in rock glaciers adjacent to Niwot Ridge and within Rocky Mountain National Park, 2018 - 2019.
To understand whether stress-associated hormones vary with metrics of habitat quality, we measured fecal glucocorticoid metabolite (FGM) levels in the American pika (Ochotona princeps), a small mammal with well-defined habitat (talus), that can vary in quality depending on the presence of rock ice features (RIFs). In 2018, we sampled pika scat from two types of RIFs: “active” rock glaciers thought to harbor subsurface ice recently, and “fossil” rock glaciers considered long devoid of subsurface ice (as classified by Janke 2005, 2007). Specifically, fecal pellets were collected from pika territories located in rock glaciers within eight sites along the Front Range of Colorado: four in Rocky Mountain National Park (2 active, 2 fossil) and four adjacent to Niwot Ridge (2 active, 2 fossil) (pika_fecal_glu_rg.aw.csv). To account for possible seasonal variation in pika FGM, scat samples were collected in the alpine spring and fall. To understand other influences of habitat quality on FGMs, we also measured fine-scale habitat differences between rock glaciers in 2019, including talus depth, clast size, and land cover metrics related to forage (pika_fecal_habitat_rg.aw.csv).
H2020 PrimeFish National Level Competitiveness Iceland Norway Spain Vietnam Newfoundland
<p>The data set contains data on individual indicators of national seafood competitiveness. Data are collected as part of the EU H2020 project PrimeFish (grant no 635761). The analysis follows the general framework of the annual World Economic Forum Competitiveness Report. Indicators are taken from three sources; directly from the World Economic Forum report, survey among national experts and hard data such as stock sizes and wages. All data are numeric, and on a 1-7 scale. Data were collected from the World Economic Forum 2017 competitiveness report and surveys and hard data collected in 2017.</p> <p> </p> <p>Indicators are grouped in several catergories, that again are grouped in higher level categories, ultimately yielding a single competitiveness indicator for the seafood sector.</p>
Water Levels from the Taylor Slough, just outside the Everglades National Park (FCE), South Florida from October 1997 to December 2006
Water level is recorded at least hourly at TS/Ph4 and TS/Ph5. Water level is measured with acoustic water level gages that digitally record relative water height relative to the local soil surface.
Output dataset for the SIM4NEXUS Sweden national level case study
<p>Complete baseline system dynamics model output for the national level Sweden case study of the SIM4NEXUS project. The data are provided split into three regions in Sweden. Aggregating across the regions gives national totals.</p>
Data for "Random forest-based modeling of stream nutrients at national level in a data-scarce region"
<p>The aim of the study was to model annual total nitrogen (TN) and total phosphorus (TP) concentrations at national level using an ML approach. We used water quality data originating from the Environmental Monitoring Database KESE to train RF models for nutrient concentration prediction in 242 catchments across Estonia. A total of 82 environmental variables were used as predictors in the models. In order to yield the best results, a feature selection strategy along with hyperparameter optimization was performed when building the models. The models are applicable for predicting nutrient loads on an annual level, e.g. for the purpose of reporting national level water quality statistics in regional projects, such as HELCOM. The results showed that this relatively basic RF modeling approach can have a performance similar to process-based models. Moreover, these models are easier to reuse and apply on a larger scale, since the required inputs can be derived from freely available datasets (e.g. satellite imagery)</p> <p>This repository contains the input data used for building the RF models and the files describing the modeling results.</p> <p>The description of the files is given in the README.txt file.</p> <p>Virro, H., Kmoch, A., Vainu, M. and Uuemaa, E., 2022. Random forest-based modeling of stream nutrients at national level in a data-scarce region. Science of The Total Environment, 840, p.156613.</p> <p><a href="https://doi.org/10.1016/j.scitotenv.2022.156613">https://doi.org/10.1016/j.scitotenv.2022.156613</a></p>
Fig. 3 in The correlations between certain features of the journal Neotropical Ichthyology and its impact factor: a comparative analysis at the thematic and national levels
Fig. 3. Correlation between average IF and uncitedness rate of journals on zoology in Sample 1 between 2006 and 2010. The highlighted represents the data for Neotropical Ichthyology.
gellum black. Femora all black or forefemur ferruginous in apicoventral half; foretibia brown or ferruginous, midtibia brown ferruginous, hindtibia brown; tarsi varying from brown to ferruginous. ♂.– Unknown. GEOGRAPHIC DISTRIBUTION.– Known only from higher elevations (1020-1130 m above sea level) of Ranomafana National Park, Madagascar. RECORDS (Fig. 29).— All specimens were collected in Ranomafana National Park, Fianarantsoa Province. Holotype: ♀, Belle Vue at Talatakely at 21º15.99'S 47º25.21'E, alt. 1020 m, 14-21 Jan 2002, M. Irwin and R. Harin 'Hala (CAS). Paratypes: Radio tower at forest edge at 21º15.05'S 47º24.43'E, alt. 1130 m, 23 Aug – 7 Sept 2006 and 1-11 Nov 2006, M. Irwin and R. Harin 'Hala (2 ♀, CAS); same data as holotype except 22-28 Nov 2001 and R. Harin 'Hala alone (1 ♀, CAS); Vohiparara at 21º13.57'S 47º22.19'E, alt. 1110 m, 22-28 Nov 2001, R. Harin 'Hala (1 ♀, CAS). FIGURE 29. Collecting localities of Tachytes melanogaster sp. nov. in A Review of the Wasp Genus Tachytes Panzer, 1806 of Madagascar (Hymenoptera: Crabronidae)
gellum black. Femora all black or forefemur ferruginous in apicoventral half; foretibia brown or ferruginous, midtibia brown ferruginous, hindtibia brown; tarsi varying from brown to ferruginous. ♂.– Unknown. GEOGRAPHIC DISTRIBUTION.– Known only from higher elevations (1020-1130 m above sea level) of Ranomafana National Park, Madagascar. RECORDS (Fig. 29).— All specimens were collected in Ranomafana National Park, Fianarantsoa Province. Holotype: ♀, Belle Vue at Talatakely at 21º15.99'S 47º25.21'E, alt. 1020 m, 14-21 Jan 2002, M. Irwin and R. Harin 'Hala (CAS). Paratypes: Radio tower at forest edge at 21º15.05'S 47º24.43'E, alt. 1130 m, 23 Aug – 7 Sept 2006 and 1-11 Nov 2006, M. Irwin and R. Harin 'Hala (2 ♀, CAS); same data as holotype except 22-28 Nov 2001 and R. Harin 'Hala alone (1 ♀, CAS); Vohiparara at 21º13.57'S 47º22.19'E, alt. 1110 m, 22-28 Nov 2001, R. Harin 'Hala (1 ♀, CAS). FIGURE 29. Collecting localities of Tachytes melanogaster sp. nov.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.