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28 results for “2010–2014”
Interpolated N2O fluxes on the GLBRC Scaleup Sites at the Kellogg Biological Station, Hickory Corners, MI (2010 to 2014)
Dataset AbstractTo create a complete time series of N2O fluxes from the GLBRC Scaleup fields the fluxes were interpolated from 2010 to 2014.original data source http://lter.kbs.msu.edu/datasets/168
Daily time series of spatially enhanced relative humidity for Europe at 30 arc seconds resolution (Set 3: 2010 - 2014) derived from ERA5-Land data
<p>Overview:<br> ERA5-Land is a reanalysis dataset providing a consistent view of the evolution of land variables over several decades at an enhanced resolution compared to ERA5. ERA5-Land has been produced by replaying the land component of the ECMWF ERA5 climate reanalysis. Reanalysis combines model data with observations from across the world into a globally complete and consistent dataset using the laws of physics. Reanalysis produces data that goes several decades back in time, providing an accurate description of the climate of the past.</p> <p>Processing steps:<br> The original hourly ERA5-Land air temperature 2 m above ground and dewpoint temperature 2 m data has been spatially enhanced from 0.1 degree to 30 arc seconds (approx. 1000 m) spatial resolution by image fusion with CHELSA data (V1.2) (<a href="https://chelsa-climate.org/">https://chelsa-climate.org/</a>). For each day we used the corresponding monthly long-term average of CHELSA. The aim was to use the fine spatial detail of CHELSA and at the same time preserve the general regional pattern and fine temporal detail of ERA5-Land. The steps included aggregation and enhancement, specifically:<br> 1. spatially aggregate CHELSA to the resolution of ERA5-Land<br> 2. calculate difference of ERA5-Land - aggregated CHELSA<br> 3. interpolate differences with a Gaussian filter to 30 arc seconds<br> 4. add the interpolated differences to CHELSA</p> <p>Subsequently, the temperature time series have been aggregated on a daily basis. From these, daily relative humidity has been calculated for the time period 01/2000 - 07/2021.</p> <p>Relative humidity (rh2m) has been calculated from air temperature 2 m above ground (Ta) and dewpoint temperature 2 m above ground (Td) using the formula for saturated water pressure from Wright (1997):</p> <p><code>maximum water pressure = 611.21 * exp(17.502 * Ta / (240.97 + Ta))</code></p> <p><code>actual water pressure = 611.21 * exp(17.502 * Td / (240.97 + Td))</code></p> <p><code>relative humidity = actual water pressure / maximum water pressure</code></p> <p>Data provided is the daily averages of relative humidity. This set provides data for the years 2000 - 2004. For other time periods, please see further linked data sets.</p> <p>Resultant values have been converted to represent percent * 10, thus covering a theoretical range of [0, 1000].</p> <p>File naming scheme (YYYY = year; MM = month; DD = day):<br> <code>ERA5_land_rh2m_avg_daily_YYYYMMDD.tif</code></p> <p>Projection + EPSG code:<br> Latitude-Longitude/WGS84 (EPSG: 4326)</p> <p>Spatial extent:<br> north: 82:00:30N<br> south: 18N<br> west: 32:00:30W<br> east: 70E</p> <p>Spatial resolution:<br> 30 arc seconds (approx. 1000 m)</p> <p>Temporal resolution:<br> Daily</p> <p>Pixel values:<br> Percent * 10 (scaled to Integer; example: value 738 = 73.8 %)</p> <p>Software used:<br> GDAL 3.2.2 and GRASS GIS 8.0.0</p> <p>Original ERA5-Land dataset license:<br> <a href="https://apps.ecmwf.int/datasets/licences/copernicus/">https://apps.ecmwf.int/datasets/licences/copernicus/</a></p> <p>CHELSA climatologies (V1.2):<br> Data used: Karger D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E, Linder, H.P., Kessler, M. (2018): Data from: Climatologies at high resolution for the earth's land surface areas. Dryad digital repository. <a href="http://dx.doi.org/doi:10.5061/dryad.kd1d4">http://dx.doi.org/doi:10.5061/dryad.kd1d4</a><br> Original peer-reviewed publication: Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, P., Kessler, M. (2017): Climatologies at high resolution for the Earth land surface areas. Scientific Data. 4 170122. <a href="https://doi.org/10.1038/sdata.2017.122">https://doi.org/10.1038/sdata.2017.122</a></p> <p>Processed by:<br> mundialis GmbH & Co. KG, Germany (<a href="https://www.mundialis.de/">https://www.mundialis.de/</a>)</p> <p>Reference: Wright, J.M. (1997): Federal meteorological handbook no. 3 (FCM-H3-1997). Office of Federal Coordinator for Meteorological Services and Supporting Research. Washington, DC</p> <p>Data is also available in EU LAEA (EPSG: 3035) projection: <a href="https://zenodo.org/record/7432432">https://zenodo.org/record/7432432</a></p>
Daily time series of spatially enhanced relative humidity for Europe at 1000 m resolution (Set 3: 2010 - 2014) derived from ERA5-Land data
<p>Overview:<br> ERA5-Land is a reanalysis dataset providing a consistent view of the evolution of land variables over several decades at an enhanced resolution compared to ERA5. ERA5-Land has been produced by replaying the land component of the ECMWF ERA5 climate reanalysis. Reanalysis combines model data with observations from across the world into a globally complete and consistent dataset using the laws of physics. Reanalysis produces data that goes several decades back in time, providing an accurate description of the climate of the past.</p> <p>Processing steps:<br> The original hourly ERA5-Land air temperature 2 m above ground and dewpoint temperature 2 m data has been spatially enhanced from 0.1 degree to 30 arc seconds (approx. 1000 m) spatial resolution by image fusion with CHELSA data (V1.2) (<a href="https://chelsa-climate.org/">https://chelsa-climate.org/</a>). For each day we used the corresponding monthly long-term average of CHELSA. The aim was to use the fine spatial detail of CHELSA and at the same time preserve the general regional pattern and fine temporal detail of ERA5-Land. The steps included aggregation and enhancement, specifically:<br> 1. spatially aggregate CHELSA to the resolution of ERA5-Land<br> 2. calculate difference of ERA5-Land - aggregated CHELSA<br> 3. interpolate differences with a Gaussian filter to 30 arc seconds<br> 4. add the interpolated differences to CHELSA</p> <p>Subsequently, the temperature time series have been aggregated on a daily basis. From these, daily relative humidity has been calculated for the time period 01/2000 - 07/2021.</p> <p>Relative humidity (rh2m) has been calculated from air temperature 2 m above ground (Ta) and dewpoint temperature 2 m above ground (Td) using the formula for saturated water pressure from Wright (1997):</p> <p><code>maximum water pressure = 611.21 * exp(17.502 * Ta / (240.97 + Ta))</code></p> <p><code>actual water pressure = 611.21 * exp(17.502 * Td / (240.97 + Td))</code></p> <p><code>relative humidity = actual water pressure / maximum water pressure</code></p> <p>Data provided is the daily averages of relative humidity. This set provides data for the years 2010 - 2014. For other time periods, please see further linked data sets.</p> <p>Resultant values have been converted to represent percent * 10, thus covering a theoretical range of [0, 1000].</p> <p>The data have been reprojected to EU LAEA.</p> <p>File naming scheme (YYYY = year; MM = month; DD = day):<br> <code>ERA5_land_rh2m_avg_daily_YYYYMMDD.tif</code></p> <p>Projection + EPSG code:<br> EU LAEA (EPSG: 3035)</p> <p>Spatial extent:<br> north: 6874000<br> south: -485000<br> west: 869000<br> east: 8712000</p> <p>Spatial resolution:<br> 1000 m</p> <p>Temporal resolution:<br> Daily</p> <p>Pixel values:<br> Percent * 10 (scaled to Integer; example: value 738 = 73.8 %)</p> <p>Software used:<br> GDAL 3.2.2 and GRASS GIS 8.0.0</p> <p>Original ERA5-Land dataset license:<br> <a href="https://apps.ecmwf.int/datasets/licences/copernicus/">https://apps.ecmwf.int/datasets/licences/copernicus/</a></p> <p>CHELSA climatologies (V1.2):<br> Data used: Karger D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E, Linder, H.P., Kessler, M. (2018): Data from: Climatologies at high resolution for the earth's land surface areas. Dryad digital repository. <a href="http://dx.doi.org/doi:10.5061/dryad.kd1d4">http://dx.doi.org/doi:10.5061/dryad.kd1d4</a><br> Original peer-reviewed publication: Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, P., Kessler, M. (2017): Climatologies at high resolution for the Earth land surface areas. Scientific Data. 4 170122. <a href="https://doi.org/10.1038/sdata.2017.122">https://doi.org/10.1038/sdata.2017.122</a></p> <p>Processed by:<br> mundialis GmbH & Co. KG, Germany (<a href="https://www.mundialis.de/">https://www.mundialis.de/</a>)</p> <p>Reference: Wright, J.M. (1997): Federal meteorological handbook no. 3 (FCM-H3-1997). Office of Federal Coordinator for Meteorological Services and Supporting Research. Washington, DC</p> <p>Data is also available in Latitude-Longitude/WGS84 (EPSG: 4326) projection: <a href="http://https://doi.org/10.5281/zenodo.6344012">https://doi.org/10.5281/zenodo.6344012</a></p>
Water Temperature, Salinity and other physical measurements taken at Shark River, Everglades National Park (FCE LTER) from February 2010 to March 2014
In early 2010 we established three new permanent water quality monitoring stations in the Shark River Estuary. These stations expanded FCE's spatial coverage in terms of salinity and also established the first continuous dissolved oxygen monitoring in the estuary.
Solar and meteorological data collected from the Bras Panon Moreau station (La Réunion) by the ENERGY-lab at the University of La Reunion between November 2010 and September 2014
<p>Scientific data provided by ENERGY-lab located at the University of La Reunion. These data come from solar and meteorological stations present in the following territories: La Reunion, Comoros, Madagascar, Mauritius, Seychelles and South Africa. A THREDDS Data Server was created as part of the IOS-net (Indian Ocean Solar Network, https://galilee.univ-reunion.fr) project which aims to study the solar field and the optimisation of intelligent solar energy systems in the countries of the IOC (Indian Ocean Commission). These data are served by Unidata's Thematic Realtime Environmental Distributed Data Services (THREDDS) Data Server (TDS) in a variety of interoperable data services and output formats.</p> <p>Dataset is available from the THREDDS Data Server to this url: <a href="https://galilee.univ-reunion.fr/thredds/catalog/dataStations/catalog.html"> https://galilee.univ-reunion.fr/thredds/catalog/dataStations/catalog.html</a>.</p> <p>Data are also viewable and exploitable on the mobile application of the IOS-net project. The SolarIO app is downloadable in all stores.</p> <p><strong><em>ENERGY-lab data may be reused, provided that related metadata explaining the data has been reviewed by the user, and that the data are appropriately acknowledged.</em></strong></p>
COMMENTS.— Although not breeding in the Mediterranean, the species forages in Libyan waters (van Dijk et al. 2014). In addition to the single beached record, an individual was pulled from nearshore waters of the Tajura coast in 1996 and died in the rehabilitation facility of the Marine Biology Research Centre (MBRC) at Tajura, where it was subsequently taxidermied at the MBRC Museum (Hamza 2010). Capra's (1949) records were based on a report in "L'Idea Coloniale" for 2 May 1927 (Mongàr) and an unspecified specimen in the Museo Civico di Storia Naturale di Trieste (Sella). IUCN THREAT STATUS.— Vulnerable A2bd. MAP 3. Distribution of Dermochelys coriacea in Libya showing stranding site records. in Atlas of the Reptiles of Libya
COMMENTS.— Although not breeding in the Mediterranean, the species forages in Libyan waters (van Dijk et al. 2014). In addition to the single beached record, an individual was pulled from nearshore waters of the Tajura coast in 1996 and died in the rehabilitation facility of the Marine Biology Research Centre (MBRC) at Tajura, where it was subsequently taxidermied at the MBRC Museum (Hamza 2010). Capra's (1949) records were based on a report in "L'Idea Coloniale" for 2 May 1927 (Mongàr) and an unspecified specimen in the Museo Civico di Storia Naturale di Trieste (Sella). IUCN THREAT STATUS.— Vulnerable A2bd. MAP 3. Distribution of Dermochelys coriacea in Libya showing stranding site records.
Text-fig. 9. Biostratigraphy of African Miocene localities, with the temporal ranges of the diverse species of hyaenodonts found therein. See Pickford (1986a), Pickford and Senut (2003), Reynoso (2014) and Werdelin (2010). in New Hyaenodonts (Ferae, Mammalia) From The Early Miocene Of Napak (Uganda), Koru (Kenya) And Grillental (Namibia)
Text-fig. 9. Biostratigraphy of African Miocene localities, with the temporal ranges of the diverse species of hyaenodonts found therein. See Pickford (1986a), Pickford and Senut (2003), Reynoso (2014) and Werdelin (2010).
FIFA World Cups 2010, 2014 and 2018 matches' information datasets
<p>Data from FIFA World Cups 2010 (South Africa), 2014 (Brazil) and 2018 (Russia) collected from the FIFA website from the section of each match's facts. The original data were pdf files, which were cleaned and organized.</p> <p>The data was collected for the analysis of competition networks in soccer matches, where the high and low performance teams were studied.</p> <p>The zip file contains 3 folders of each world cup. Each folder contains the following files:</p> <p>- Players performance measures: input_worldcup.csv. This file contains information from 'fulltime statistics' and 'teams statistics' original files, complete for each match played in the world cup. More detailed player statistics is only complete for the teams that were champion, runner-up, and the teams that accumulated the less points and goals-against in their respective world cup.</p> <p>- The description of each column can be found in data_dictionary_worldcup.csv.</p> <p>- The list of countries that participated in the world cup with its abbreviation is found in countries_abbreviations_worldcup.csv.</p> <p>- The result of each match is found in tags_worldcup.csv</p> <p>- The players position information is the tactical line-up for World Cup 2010 and initial actual formation for World Cups 2014 and 2018. This information was manually set as a best approximation of position for the starting 11 players and a receiving shots nodes 'XS' - special for the visualization developed. The x-axis is between 0.5 and 6 and y-axis is flipped and between 0 and 6.</p> <p>- Folder of ball passing distributions for each match and team. The name of each file contains the match number and the team's ball passing distribution. The column names are the players numbers who received the ball. Rows represent 'from' and the columns 'to'. Each value are the number of passes between players.</p>
Personality, space use, network, and tick infestation data from a field study of sleepy lizards, 2010 and 2014 - 2017
Open the record for dataset details and reuse information.
Dodd Frank financial reform at the Commodity Futures Trading Commission (CFTC): Public comments, January 14th, 2010 – July 16th, 2014
Open the record for dataset details and reuse information.
Detection history of 175 adult Plain-crested Elaenia (Elaenia cristata) throughout nine sessions between 2010 and 2014 in the northeastern Brazil.
<p>The input file for analysing the detection history of 175 adult Plain-crested Elaenia (<em>Elaenia cristata</em>) throughout nine sessions between 2010 and 2014 in the northeastern Brazil.</p>
Colombia. Justicia. Policia Nacional. Contravenciones 2010 a 2014
<p>Compilado de registros de Contravenciones de Policía basado en el Decreto 1355 de 1970 y reemplazado por la Ley 1801 de 2016. para los años 2010 a 2014 e incluido del DIVIPOLA o número asignado a cada Muncipio referenciados a la División Político Administrativa.</p>
Figures 6-11 from: Theron P, Fernandez N, Rollard C, Castillo E (2014) Revision of the family Carabodidae (Acari, Oribatida) VII. Redefinition of the genus Malgasodes; redescription of M. curvisetus Mahunka, 2000; and complementary description of M. hungarorum Mahunka, 2010. Phylogenetic relationships between Malgasodes, Bovicarabodes, Afticarabodes, Congocepheus and Cavaecarabodes are discussed. ZooKeys 435: 25-48. https://doi.org/10.3897/zookeys.435.8071
Figures 6-11 - Malgasodes curvisetus Mahunka, 2000, adult. SEM observations. 6 lateral view 7 prodorsum, anterior part, lateral view 8 sensillus and anterior zone humeral apophysis 9 tarsus I, (u) seta, lateral view 10 rostrum and subcapitulum, frontal view 11 leg 1, segment l, genu. Notes: Abbreviations: see "Material and methods". Scale bar: 6 = 100 μm; 7, 8, 10 = 10 μm; 10, 9, 11 = 1 μm.
Figures 20-23 from: Theron P, Fernandez N, Rollard C, Castillo E (2014) Revision of the family Carabodidae (Acari, Oribatida) VII. Redefinition of the genus Malgasodes; redescription of M. curvisetus Mahunka, 2000; and complementary description of M. hungarorum Mahunka, 2010. Phylogenetic relationships between Malgasodes, Bovicarabodes, Afticarabodes, Congocepheus and Cavaecarabodes are discussed. ZooKeys 435: 25-48. https://doi.org/10.3897/zookeys.435.8071
Figures 20-23 - Malgasodes curvisetus Mahunka, 2000, adult. Legs. Optic observations 20 leg I antiaxial view 21 leg IV, antiaxial view 22 leg III, view 23 leg II, antiaxial view. Notes: Abbreviations: see "Material and methods". Scale bar: 20–23 = 100 μm.
Figures 4-5 from: Theron P, Fernandez N, Rollard C, Castillo E (2014) Revision of the family Carabodidae (Acari, Oribatida) VII. Redefinition of the genus Malgasodes; redescription of M. curvisetus Mahunka, 2000; and complementary description of M. hungarorum Mahunka, 2010. Phylogenetic relationships between Malgasodes, Bovicarabodes, Afticarabodes, Congocepheus and Cavaecarabodes are discussed. ZooKeys 435: 25-48. https://doi.org/10.3897/zookeys.435.8071
Figures 4-5 - Malgasodes curvisetus Mahunka, 2000, adult. Optic observations. 4 dorsal view 5 ventral view. Notes: Abbreviations: see "Material and methods". Scale bar 4, 5 = 250 μm.
Figures 1-3 from: Theron P, Fernandez N, Rollard C, Castillo E (2014) Revision of the family Carabodidae (Acari, Oribatida) VII. Redefinition of the genus Malgasodes; redescription of M. curvisetus Mahunka, 2000; and complementary description of M. hungarorum Mahunka, 2010. Phylogenetic relationships between Malgasodes, Bovicarabodes, Afticarabodes, Congocepheus and Cavaecarabodes are discussed. ZooKeys 435: 25-48. https://doi.org/10.3897/zookeys.435.8071
Figures 1-3 - Malgasodes curvisetus Mahunka, 2000, adult. SEM observations. 1 dorsal view 2 frontal view 3 posterior view. Notes: Abbreviations: see "Material and methods". Scale bar: 1–3 = 100 μm.
Figures 24-27 from: Theron P, Fernandez N, Rollard C, Castillo E (2014) Revision of the family Carabodidae (Acari, Oribatida) VII. Redefinition of the genus Malgasodes; redescription of M. curvisetus Mahunka, 2000; and complementary description of M. hungarorum Mahunka, 2010. Phylogenetic relationships between Malgasodes, Bovicarabodes, Afticarabodes, Congocepheus and Cavaecarabodes are discussed. ZooKeys 435: 25-48. https://doi.org/10.3897/zookeys.435.8071
Figures 24-27 - Malgasodes hungarorum Mahunka, 2000, adult. Optic observations. 24 lateral, slightly inclined view 25 dorsal view 26 prodorsum anterior part, dorsal view, inclined anteroposterior 27 prodorsum dorsal, inclined laterally. Abbreviations: see "Material and methods". Scale bar: 24–25 = 60 μm; 26, 27 = 55 μm.
Figures 16-19 from: Theron P, Fernandez N, Rollard C, Castillo E (2014) Revision of the family Carabodidae (Acari, Oribatida) VII. Redefinition of the genus Malgasodes; redescription of M. curvisetus Mahunka, 2000; and complementary description of M. hungarorum Mahunka, 2010. Phylogenetic relationships between Malgasodes, Bovicarabodes, Afticarabodes, Congocepheus and Cavaecarabodes are discussed. ZooKeys 435: 25-48. https://doi.org/10.3897/zookeys.435.8071
Figures 16-19 - Malgasodes curvisetus Mahunka, 2000, adult. SEM observations. 16 ventral view 17 lamellae and lamellar tip 18 subcapitulum 19 lateral view, rotated. Abbreviations: see "Material and methods". Scale bar: 16, 19 = 100 μm; 17, 18 = 10 μm.
Figure 28-34 from: Theron P, Fernandez N, Rollard C, Castillo E (2014) Revision of the family Carabodidae (Acari, Oribatida) VII. Redefinition of the genus Malgasodes; redescription of M. curvisetus Mahunka, 2000; and complementary description of M. hungarorum Mahunka, 2010. Phylogenetic relationships between Malgasodes, Bovicarabodes, Afticarabodes, Congocepheus and Cavaecarabodes are discussed. ZooKeys 435: 25-48. https://doi.org/10.3897/zookeys.435.8071
Figure 28-34 - Setal distribution. 28 Cavaecarabodes, Bovicarabodes, Afticarabodes, Congocepheus 29 Congocepheus germani 30 Malgasodes curvisetus 31 Congocepheus anouchkae 32 neotrichal zone Congocepheus germani 33 regression area of setae Congocepheus anouchkae 34 migration process (with arrows) and area of marginal setae h3, p1, p2, p3 of Malgasodes curvisetus and Malgasodes hungarorum.
Figures 12-15 from: Theron P, Fernandez N, Rollard C, Castillo E (2014) Revision of the family Carabodidae (Acari, Oribatida) VII. Redefinition of the genus Malgasodes; redescription of M. curvisetus Mahunka, 2000; and complementary description of M. hungarorum Mahunka, 2010. Phylogenetic relationships between Malgasodes, Bovicarabodes, Afticarabodes, Congocepheus and Cavaecarabodes are discussed. ZooKeys 435: 25-48. https://doi.org/10.3897/zookeys.435.8071
Figures 12-15 - Malgasodes curvisetus Mahunka, 2000, adult. Optic observations. 1 dorsal view 2 ventral view 3 frontal view. Notes: Abbreviations: see "Material and methods". Scale bar: 12 = 250 μm; 13 = 2 μm; 14 = 200 μm; 15 = 4 μm.
ScienceDex guides
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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.