cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.1594/pangaea.922846
title: Teaser - Manovo-Gounda-St Floris-Bamingui Key Landscape for Conservation Land Cover and Validation Datasets (2015)

description: The teaser dataset of Manovo-Gounda-St Floris-Bamingui KLC covers an area of 10328km2 and mapped with both dichotomous (8 land cover classes) and modular (up to 32 land cover classes) levels based on FAO's Land Cover Classification System (LCCS). High-resolution optical satellite imagery were used to generate dense time-series data from which the thematic land cover map was derived (2015). The map was fully verified and validated by an independent team to achieve the Copernicus Global Land Monitoring Programme's strict data quality requirements. An independent validation dataset was also collected and it is shared here. The validation dataset contains 578 verified land cover points based on the [up to] 32 modular level land cover classes. Furthermore, two predefined symbology (QGIS legend files) for the land cover and validation datasets based on FAO's LCCS is also shared here to ease the visualization of them (Dichotomous and Modular levels). Further details regarding the sites selection, mapping and validation procedures are described in the corresponding publication: Szantoi, Z., Brink, A., Lupi, A., Mannone, C., and Jaffrain, G.: Key Landscapes for Conservation Land Cover and Change Monitoring Thematic and Validation Datasets for Sub-Saharan Africa, Earth Syst. Sci. Data, 12-3001-2020, https://doi.org/10.5194/essd-12-3001-2020.
description: Three datasets are shared here.Data format: vector (shapefile, polygon - LC datasets), vector (shapefile, point - validation dataset),Geographic Coordinate System (LC/LCC dataset): World Geodetic System 1984 (EPSG:4326) and its datum (EPSG:6326), Projected coordinate system (validation data): Africa Albers Equal Area Conic (EPSG:102022),Minimum mapping unit: 0.5-5ha.Land cover dataset attributes:[mapcode_A] - dichotomous level,[mapcode_B] - modular level (Mapcode),[name_B] - corresponding modular class name.Validation dataset attributes:[plaus2015] - modular level (Mapcode),The naming of all attributes follow the same structure in all shapefiles - see Table 2 Dichotomous and Modular thematic land cover/use classes in the corresponding publication.
DOI: 10.15468/dl.poscyv
title: Occurrence Download

description: A dataset containing 144 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is CardObs : Observations naturalistes issues de l'outil CardObs-Données naturalistes de Xavier BONNET"
 ]
}

 The dataset includes 144 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024872-200221144449610/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.1594/pangaea.923721
title: Metabolomes in sympatric populations of closely related species of the genus Littorina (Neritrema) in two sites in the Norwegian and Barents Sea

description: This zip file contains metabolomic data from gas chromatography mass-spectrometry analysis. Metabolites identification was done using fragmented spectra NIST (National Institute of Standards and Technology) database and standard chromatograms of single amino acids, monosaccharides, fatty acids manually and their mixtures.
description: - metabolome.csv [comma separated] - log2-transformed and normalized by sample weight detection intensities form GC-MS/MS analysis:= "ID" [text] - metabolome sample id= "Site" [text] - the name of the sampling site ("Saltstraumen", "Varangerfjord"); = "Level" [text] - level of the intertidal zone ("upper" or "lower"); = "Species" [text] - species of Littorina (L.arcana, L.saxatilis, L.compressa, L.obtusata, L.fabalis) ;= "Cpd_1"-"Cpd_91" [relative units] - log-transformed and normalized by sample weight detection intensities of compounds form GC-MS/MS analysis.- metabolites.csv [comma separated] - list of identified/unidentified chemical compounds and their characteristics:= "Compound" [text] - compound identifiers numbered according to order of elution;= "Identification" [text] - compound name according to identification results; unk[principal ion mass] code for compounds not identified based on available NIST database and standards, TMS code for trimethylsilyl groups number, P code for monosaccharide in pyranose form, F code for monosaccharide in furanose form, MAG code for monoacylglycerol;= "Retention_time" [minutes] - retention time;= "Retention_index" [dimensionless] - retention index.
DOI: 10.15468/dl.ry9f2c
title: Occurrence Download

description: A dataset containing 25 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Milviscutulus mangiferae (Green, 1889)",
 {
 "not" : {
 "DatasetKey" : [
 "is Global database of alien macrofungi"
 ]
 }
 },
 {
 "or" : [
 "Country is United States of America",
 "Country is United States",
 "Country is United States of America",
 "Country is Canada",
 "Continent is North America"
 ]
 }
 ]
}

 The dataset includes 25 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0367893-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.1594/pangaea.923728
title: Shell morphometry in sympatric populations of closely related species of the genus Littorina (Neritrema) in two sites in the Norwegian and Barents Sea

description: Folder Morphometry contains geometric morphometric data. The shell shape was described by 11 landmarks and 56 semilandmarks. In total, the analysis included: 126 individuals of L. saxatilis (50-141 mm), 32 individuals of L. arcana (81-130 mm), 47 individuals of L. compressa (61-113 mm), 128 individuals of L. obtusata (55-167 mm) and 41 individuals of L. fabalis (50-147 mm).
description: - TPS.tps - the coordinates of landmarks and semilandmarks describing the shape of the shells of mollusks in .tps format.- curveslide.csv [semicolon separated] - semilandmark relative positions for import to geomorph package of R in specific geomorph format:= "before" [landmark id number] - id of landmark before the semilandmark;= "slide" [landmark id number] - semilandmark id;= "after" [landmark id number] - id of landmark after the semilandmark.- links.csv [semicolon separated] - positions of links between landmarks for graphical representation of shapes for import to geomorph package of R in specific geomorph format:= "start" [landmark id number] - landmark id at the link beginning;= "stop" [landmark id number] - landmark id at the link end.morphometry_metadata.csv - metadata on molluscs:= "ID" [text] - image id;= "Site" [text] - the name of the sampling site ("Saltstraumen", "Varangerfjord"); = "Level" [text] - level of the intertidal zone ("upper" or "lower"); = "Species" [text] - species of Littorina (L.arcana, L.saxatilis, L.compressa, L.obtusata, L.fabalis) ;= "Sex" [text] - sex ("f" - female; "m" - male);= "SpeciesGroup" - name of the species group ("'saxatilis'" - "saxatilis", "'obtusata'" -"obtusata");= "SpeciesSubpopulation" [text] - species name and subpopulation.- TPS_measurement_error.tps - the coordinates of landmarks and semilandmarks describing the shape of the shells of molluscs in .tps format. The dataset for calculation of measurement error related to digitization. measurement_error_metadata.csv- metadata on molluscs in TPS_measurement_error.tps (for variable description see morphometry_metadata.csv).
DOI: 10.1594/pangaea.924003
title: Multibeam bathymetry raw data (Kongsberg EM710 entire dataset) of RV HEINCKE during cruise HE508

description: Multibeam data were collected during R/V Heincke cruise HE508 with echo sounder system Kongsberg Simrad EM710. Data recording was executed in North Sea around island Helgoland. Data are unprocessed and may contain outliers and blunders. Therefore the data should not directly be used for grid calculations and charting projects but need to be edited furthermore. One file typically contains a measurement period of ten minutes. The dataset consists of 446 files in Simrad Multibeam Processing Format (*.all) which are compressed with GZIP to size of 21.4 GB (33.2 GB uncompressed). Simrad data files can be processed using the software packages CARIS HIPS/SIPS or with the open source software package MB-System (https://www.mbari.org/products/research-software/mb-system/).
DOI: 10.15468/dl.epdzjb
title: Occurrence Download

description: A dataset containing 1517 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Bauhinia tomentosa L."
 ]
}

 The dataset includes 1517 records from 132 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034158-230810091245214/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.1594/pangaea.922848
title: Teaser - Tai-Sapo Key Landscape for Conservation Land Cover and Validation Datasets (2016)

description: The teaser dataset of Tai-Sapo KLC covers an area of 9100km2 and mapped with both dichotomous (8 land cover classes) and modular (up to 32 land cover classes) levels based on FAO's Land Cover Classification System (LCCS). High-resolution optical satellite imagery were used to generate dense time-series data from which the thematic land cover map was derived (2016). The map was fully verified and validated by an independent team to achieve the Copernicus Global Land Monitoring Programme's strict data quality requirements. An independent validation dataset was also collected and it is shared here. The validation dataset contains 1283 verified land cover points based on the [up to] 32 modular level land cover classes. Furthermore, two predefined symbology (QGIS legend files) for the land cover and validation datasets based on FAO's LCCS is also shared here to ease the visualization of them (Dichotomous and Modular levels). Further details regarding the sites selection, mapping and validation procedures are described in the corresponding publication: Szantoi, Z., Brink, A., Lupi, A., Mannone, C., and Jaffrain, G.: Key Landscapes for Conservation Land Cover and Change Monitoring Thematic and Validation Datasets for Sub-Saharan Africa, Earth Syst. Sci. Data, 12-3001-2020, https://doi.org/10.5194/essd-12-3001-2020.
description: Three datasets are shared here.Data format: vector (shapefile, polygon - LC datasets), vector (shapefile, point - validation dataset),Geographic Coordinate System (LC/LCC dataset): World Geodetic System 1984 (EPSG:4326) and its datum (EPSG:6326),Projected coordinate system (validation data): Africa Albers Equal Area Conic (EPSG:102022),Minimum mapping unit: 0.5-5ha.Land cover dataset attributes:[mapcode_A] - dichotomous level,[mapcode_B] - modular level (Mapcode),[name_B] - corresponding modular class name.Validation dataset attributes:[plaus2016] - modular level (Mapcode),The naming of all attributes follow the same structure in all shapefiles - see Table 2 Dichotomous and Modular thematic land cover/use classes in the corresponding publication.
DOI: 10.1594/pangaea.922849
title: Teaser - Takamanda Key Landscape for Conservation Land Cover and Validation Datasets (2016)

description: The teaser dataset of Takamanda KLC covers an area of 239km2 and mapped with both dichotomous (8 land cover classes) and modular (up to 32 land cover classes) levels based on FAO's Land Cover Classification System (LCCS). High-resolution optical satellite imagery were used to generate dense time-series data from which the thematic land cover map was derived (2016). The map was fully verified and validated by an independent team to achieve the Copernicus Global Land Monitoring Programme's strict data quality requirements. An independent validation dataset was also collected and it is shared here. The validation dataset contains 232 verified land cover points based on the [up to] 32 modular level land cover classes. Furthermore, two predefined symbology (QGIS legend files) for the land cover and validation datasets based on FAO's LCCS is also shared here to ease the visualization of them (Dichotomous and Modular levels). Further details regarding the sites selection, mapping and validation procedures are described in the corresponding publication: Szantoi, Z., Brink, A., Lupi, A., Mannone, C., and Jaffrain, G.: Key Landscapes for Conservation Land Cover and Change Monitoring Thematic and Validation Datasets for Sub-Saharan Africa, Earth Syst. Sci. Data, 12-3001-2020, https://doi.org/10.5194/essd-12-3001-2020.
description: Three datasets are shared here.Data format: vector (shapefile, polygon - LC datasets), vector (shapefile, point - validation dataset),Geographic Coordinate System (LC/LCC dataset): World Geodetic System 1984 (EPSG:4326) and its datum (EPSG:6326),Projected coordinate system (validation data): Africa Albers Equal Area Conic (EPSG:102022),Minimum mapping unit: 0.5-5ha.Land cover dataset attributes:[mapcode_A] - dichotomous level,[mapcode_B] - modular level (Mapcode),[name_B] - corresponding modular class name.Validation dataset attributes:[plaus2016] - modular level (Mapcode),The naming of all attributes follow the same structure in all shapefiles - see Table 2 Dichotomous and Modular thematic land cover/use classes in the corresponding publication.
DOI: 10.15468/dl.qaggx2
title: Occurrence Download

description: A dataset containing 189767 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Anthyllis montana L., Anthyllis vulneraria L.)",
 "Geometry POLYGON((-9.36035 44.71551,-10.59082 42.81152,-11.82129 36.80928,-7.69043 36.17336,-3.38379 35.88905,3.12012 38.13456,9.18457 38.20366,11.7334 37.16032,12.78809 34.74161,17.09473 33.79741, 23.15918 34.23451,30.10254 32.62087,33.2666 32.99024,35.72754 35.03,33.00293 35.53223,28.69629 35.17381,28.34473 36.31513,25.7959 37.50973,24.91699 39.90974,28.78418 40.6473,30.71777 41.17865,36.87012 45.213,38.18848 46.98025,38.71582 47.7541,39.94629 47.93107,40.20996 49.61071,37.0459 50.34546,35.72754 50.40152,33.79395 52.26816,31.68457 51.94426,31.4209 53.27835,32.56348 53.43572,30.98145 54.77535,30.89355 55.52863,28.43262 56.02295,27.20215 57.65716,27.37793 58.30949,27.90527 59.17593,29.66309 59.88894,27.6416 60.58697,31.50879 62.75473,28.78418 69.83962,30.89355 70.28912,29.22363 71.55274,21.75293 71.30079,14.28223 70.14036,11.38184 67.47492,4.87793 63.66576,-5.53711 71.52491,-10.63477 71.69129,-21.5332 67.74276,-28.56445 65.36684,-24.3457 61.35461,-9.36035 44.71551))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2021"
 ]
}

 The dataset includes 189767 records from 534 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0230924-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.1594/pangaea.922851
title: Teaser - The Great Limpopo Key Landscape for Conservation Land Cover and Validation Datasets (2016)

description: The teaser dataset of the Great Limpopo KLC covers an area of 3888km2 and mapped with both dichotomous (8 land cover classes) and modular (up to 32 land cover classes) levels based on FAO's Land Cover Classification System (LCCS). High-resolution optical satellite imagery were used to generate dense time-series data from which the thematic land cover map was derived (2016). The map was fully verified and validated by an independent team to achieve the Copernicus Global Land Monitoring Programme's strict data quality requirements. An independent validation dataset was also collected and it is shared here. The validation dataset contains 398 verified land cover points based on the [up to] 32 modular level land cover classes. Furthermore, two predefined symbology (QGIS legend files) for the land cover and validation datasets based on FAO's LCCS is also shared here to ease the visualization of them (Dichotomous and Modular levels). Further details regarding the sites selection, mapping and validation procedures are described in the corresponding publication: Szantoi, Z., Brink, A., Lupi, A., Mannone, C., and Jaffrain, G.: Key Landscapes for Conservation Land Cover and Change Monitoring Thematic and Validation Datasets for Sub-Saharan Africa, Earth Syst. Sci. Data, 12-3001-2020, https://doi.org/10.5194/essd-12-3001-2020.
description: Three datasets are shared here.Data format: vector (shapefile, polygon - LC datasets), vector (shapefile, point - validation dataset),Geographic Coordinate System (LC/LCC dataset): World Geodetic System 1984 (EPSG:4326) and its datum (EPSG:6326),Projected coordinate system (validation data): Africa Albers Equal Area Conic (EPSG:102022),Minimum mapping unit: 0.5-5ha.Land cover dataset attributes:[mapcode_A] - dichotomous level,[mapcode_B] - modular level (Mapcode),[name_B] - corresponding modular class name.Validation dataset attributes:[plaus2016] - modular level (Mapcode),The naming of all attributes follow the same structure in all shapefiles - see Table 2 Dichotomous and Modular thematic land cover/use classes in the corresponding publication.
DOI: 10.1594/pangaea.922856
title: Teaser - Upemba Key Landscape for Conservation Land Cover and Validation Datasets (2016)

description: The teaser dataset of Upemba KLC covers an area of 6067km2 and mapped with both dichotomous (8 land cover classes) and modular (up to 32 land cover classes) levels based on FAO's Land Cover Classification System (LCCS). High-resolution optical satellite imagery were used to generate dense time-series data from which the thematic land cover map was derived (2016). The map was fully verified and validated by an independent team to achieve the Copernicus Global Land Monitoring Programme's strict data quality requirements. An independent validation dataset was also collected and it is shared here. The validation dataset contains 440 verified land cover points based on the [up to] 32 modular level land cover classes. Furthermore, two predefined symbology (QGIS legend files) for the land cover and validation datasets based on FAO's LCCS is also shared here to ease the visualization of them (Dichotomous and Modular levels). Further details regarding the sites selection, mapping and validation procedures are described in the corresponding publication: Szantoi, Z., Brink, A., Lupi, A., Mannone, C., and Jaffrain, G.: Key Landscapes for Conservation Land Cover and Change Monitoring Thematic and Validation Datasets for Sub-Saharan Africa, Earth Syst. Sci. Data, 12-3001-2020, https://doi.org/10.5194/essd-12-3001-2020.
description: Three datasets are shared here.Data format: vector (shapefile, polygon - LC datasets), vector (shapefile, point - validation dataset),Geographic Coordinate System (LC/LCC dataset): World Geodetic System 1984 (EPSG:4326) and its datum (EPSG:6326),Projected coordinate system (validation data): Africa Albers Equal Area Conic (EPSG:102022),Minimum mapping unit: 0.5-5ha.Land cover dataset attributes:[mapcode_A] - dichotomous level,[mapcode_B] - modular level (Mapcode),[name_B] - corresponding modular class name.Validation dataset attributes:[plaus2016] - modular level (Mapcode),The naming of all attributes follow the same structure in all shapefiles - see Table 2 Dichotomous and Modular thematic land cover/use classes in the corresponding publication.
DOI: 10.1594/pangaea.922864
title: δ18O and Model data for enhanced Greenland surface-temperature variability during the Last Glacial Maximum

description: Stable oxygen isotope records from central Greenland suggest disproportionally large long-term surface-air temperature (SAT) variability during the last glacial maximum (LGM) relative to preindustrial times. Large perturbations in mean atmospheric circulation and its variability forced by extensive Northern Hemisphere ice sheet coverage has been suggested as cause for the enhanced Greenland SAT variability. Here, we assess the factors driving Greenland SAT variability during the LGM by means of dedicated climate model simulations and find remote forcing from the Pacific of critical importance. Atmospheric teleconnections from the Interdecadal Pacific Oscillation (IPO), a multidecadal oscillation of sea-surface temperature in the Pacific Ocean, strongly intensify under LGM conditions, driving enhanced surface wind variability over Greenland, which in turn amplifies SAT variability by anomalous atmospheric heat transport. A major role of the IPO in forcing Greenland SAT variability also is supported by a number of models from the Paleoclimate Modelling Intercomparison Project Phase III.
DOI: 10.15468/dl.222km6
title: Occurrence Download

description: A dataset containing 442 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-8.19862 36.69677,-5.98289 36.69677,-5.98289 37.67874,-8.19862 37.67874,-8.19862 36.69677))",
 "HasCoordinate is true",
 "TaxonKey is Ulex argenteus Welw. ex Webb",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 442 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000421-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.1594/pangaea.923820
title: Geophysical survey at Wabar meteoroid, Saudi Arabia recorded in November 2019

description: The data is composed of 2 parts, a seismic data set, and a ground-penetrating data set. The seismic data set consists of 87 shot gathers each one has 48 receivers. The shot interval is 2.5 m while the receiver interval is 5 m. The ground-penetrating radar data set consists of 12 parallel profiles, each one is 120 m long. All profiles run from south to north. The data are recorded at the Wabar meteoroid site at the Empty Quarter area on the eastern side of Saudi Arabia. The data were recorded in Nov. 2019. To record this data we used a Geometrics system with 14-Hz receivers and a sledgehammer as the seismic source. while the ground-penetrating radar data set is recorded using an unshielded 35 Hz antennas. The data is recorded to explore the subsurface setting at the area and search for any hidden meteoroid.
DOI: 10.1594/pangaea.924669
title: Master track of POLARSTERN cruise PS122/1 in 1 sec resolution (zipped, 43.3 MB)

description: Raw data acquired by position sensors on board RV Polarstern during expedition PS122_1 was processed to receive a validated master track which can be used as reference of further expedition data. During PS122_1 two Trimble Marine SPS461 GPS receivers and the iXBlue HYDRINS hydrographic survey inertial navigation system were used as navigation sensors. Data were downloaded from DAVIS SHIP data base (https://dship.awi.de) with a resolution of 1 sec. Processing and evaluation of the data is outlined in the data processing report found at EPIC repository https://hdl.handle.net/10013/epic.14eb801d-744f-4467-9c6a-3bd72ef41fd3. Processed data are provided as a master track with 1 sec resolution derived from the position sensors' data selected by priority and a generalized track with a reduced set of the most significant positions of the master track.
DOI: 10.15468/dl.yrfd77
title: Occurrence Download

description: A dataset containing 46 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Calanthe ceciliae Rchb.f."
 ]
}

 The dataset includes 46 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0113624-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.