cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.34930/5d47abfc-0fef-4f54-9c69-68b75068fb3f
title: JULIO - TIMESERIE #3: Etude long terme de la variabilité du Courant Nord 

description: JULIO (Judicious Location for Intrusions Observations) mooring is located close to the 100 m-deep isobath (around 5.25°E and 43.13°N), offshore Marseille. With its bottom-moored (300kHz) ADCP, it enables measuring horizontal currents (every 4 m and every ½ h) through the water column, and among others, identifying periods of exchange between the Northern Current and the continental shelf. It is one crucial component in the study of the coastal-offshore gradient from Marseille to the MOOSE 42°N5°E station, and potential covariances with the MIO radar and other MIO or international observing systems, as well as with the SOMLIT site (including also an ADCP) in the bay of Marseille. Moreover, with a bottom CTD, it can detect environmental anomalies in classical hydrographic data, useful for oceanographers. As one of the rare station at the interface between the continental shelf and offshore, it will allow to observe the long-term evolution of the Northern Current in the context of climate change and anthropogenic pressure, and its potential varying impact on the Gulf of Lion. The data are of course also crucial for modellers. Moreover they show a great potential when supplementing other MOOSE data (glider and radar). Timeserie #3 : - JULIO 3 - 17/07/2014 to 10/04/2015; JULIO (Judicious Location for Intrusions Observations) est situé à proximité de l'isobathe de 100 m de profondeur (environ 5,25°E et 43,13°N), au large de Marseille. Grâce à son ADCP (300 kHz), il permet de mesurer les courants horizontaux (tous les 4 m et toutes les ½ h) à travers la colonne d'eau et, entre autres, d'identifier les périodes d'échange entre le courant du Nord et le plateau continental. Il s'agit d'un élément crucial dans l'étude du gradient littoral-offshore de Marseille à la station MOOSE 42°N5°E, et des covariances potentielles avec le radar MIO et autres systèmes d'observation MIO ou internationaux, ainsi qu'avec le site SOMLIT (incluant également un ADCP) dans la baie de Marseille. De plus, avec un CTD de fond, il peut détecter les anomalies environnementales dans les données hydrographiques classiques, utiles aux océanographes. En tant qu'une des rares stations à l'interface entre le plateau continental et le large, elle permettra d'observer l'évolution à long terme du courant du Nord dans le contexte du changement climatique et de la pression anthropique, et son impact potentiel variable sur le Golfe du Lion. Les données sont bien sûr également cruciales pour les modélisateurs. De plus, ils présentent un grand potentiel en complément d'autres données MOOSE (planeur et radar). Série temporelle #3 : - JULIO 3 - 17/07/2014 to 10/04/2015;
DOI: 10.34930/6da3237c-4732-4c71-b7f1-140c7b2dcdaa
title: Zooplankton timeseries Marseille bay

description: This series is part of the long-term planktonic monitoring of Marseille Oceanographic Laborarories (successively Centre Océanographique de Marseille, Laboratoire d’Océanographie Biologique, Laboratoire d’Océanographie Physique et Biogéochimique, and presently Mediterranean Institute of oceanography / OSU Pytheas ). It aims at describing the dynamics of the mesozooplankton community both in term of biomass and taxonomic groups. This dataset contains the planktonic organisms collected by a WP2 net (Diameter 55 cm; Length : 3 m; Mesh size: 200μm mesh) and therefore covering zooplanktonic organisms from 200µm to ~2cm. The sampling is carried out twice a month at a fixed station in the center of the bay of Marseille (43.2417°N; 5.29167°E) with a depth of 60m (see https://www.somlit.fr/marseille/ ). The WP2 net (200μm mesh) is hauled vertically from 55 to the surface. Sample preserved in 4% buffered formalin and stored over the long term at the MIO. Sample have bee scanned on a ZooScan, images processed with ZooProcess and sorted taxonomically on Particle Trieur, within the Plateforme Microscopie et IMagerie (MIM). The data collection and processing has been funded by several projects over its lifetime. It is currently supported directly by the Mediterranean Institute of oceanography (MIO), as part of its long-term monitoring effort associated with SOMLIT. (https://www.somlit.fr/marseille/)
DOI: 10.34930/79c421c5-9335-4957-88fa-804fb4ae4b43
title: Panache du Rhône : Suivi des eaux du Rhône en zone côtière par mesure haute fréquence de la salinité de surface

description: Suivi des eaux du Rhône en zone côtière par mesure haute fréquence de la température et de la salinité de surface - Bouee OMEGA: 43°11,952' N, 5°01,789' E - Balise DE LA BALANCELLE: 43°20,443' N, 4°55,464' E - CARRO/Couronne: 43°18,716' N, 5°02,676' E - CARRY LE ROUET: 43°19,146' N, 5°09,641' E
DOI: 10.34930/9263c4df-4f55-4c5a-b183-c40ee1d844b1
title: HF RADAR - French Riviera (Mediterranean Institute of Oceanography) - daily surface currents filled with DINEOF

description: Daily High Frequency Radar (HFR) surface current data (radial velocity files and total velocity file) from 2 different stations located on the French Mediterranean coast (Toulon), spanning from January 2012 to December 2019. The radial datasets have been processed to remove outliers. Then, the gaps in the data have been filled using the DINEOF algorithm. The total velocity is then reconstructed from the filled radial velocity files, and projected onto a cartesian grid of 1km x 1km. The HFR data comes from two systems, one monostatic radar PEY (located at Fort Peyras, La Seyne sur mer), and one bistatic POB (emitter located at Cap Bénat - Bormes les Mimosas, and transmitter on Porquerolles Island). The HFR data is initially hourly sampled. To remove the outliers of the data, for each timestep, a Probability Density Function (PDF) is computed on the spatial gradient of each radial map. Pixels with a spatial gradient with a probability under 3% are removed. Additionnally, for each pixel, a PDF is computed on the temporal gradient of its whole timeseries. Timesteps with a temporal gradient that have a probability under 1% are then removed. Then we proceed to a preliminary temporal and spatial hole filling of the missing data. For the timeseries of each pixel, timesteps that are surrounded by valid values within 3 hours (i.e. 3 timesteps) are filled by a weighted linear interpolation. For each timestep, pixels of the map surrounded by values within 1 grid point are filled in the same way. The radial data is then daily averaged. The DINEOF algorithm (http://modb.oce.ulg.ac.be/mediawiki/index.php/DINEOF) is run in a multivariate way (2 radial velocity files) using 50 EOF modes for the reconstruction. At some timesteps (shown by the flag variable of the file), the filling has not been possible, and the missing maps have been replaced by the temporal average radial map. The filled radial velocities are then locally interpolated onto a cartesian grid of 1km spatial resolution using a Weighted Least Square method. HF radar sites : - Peyras : 43°03'47.4"N, 5°51'40.3"E - Porquerolles (transmitter only): 42°58'59.0"N, 6°12'15.3"E - Bénat (receiver only): 43°05'31.5"N, 6°21'26.5"E EUROPEAN DIRECTORY OF MARINE ENVIRONMENTAL RESEARCH PROJECTS (EDMERP) : - SICOMAR PLUS(12402), IMPACT(12271), MOOSE(11574), and JERICHO NEXT(12227) EQUIPEMENTS: - High Frequency Surface Wave radar WERA from HELZEL MESSTECHNIK PARAMETERS: - sea surface current
DOI: 10.34930/9db3bec4-0bbf-4531-8864-f100c4b8eced
title: Maupiti Hoe 2018

description: The scientific objectives of the project MAUPITI HOE are to understand the hydrodynamics of an archetypal reef-lagoon system of a high volcanic reef island. The physical functioning of the hydrosystem involves a fine coupling between water levels, waves (including wind, infragravity and VLF waves), currents and seabed structure (reef roughness). The present data focuses on the reef barrier dynamics.
DOI: 10.34930/ap_mio_20231114
title: JULIO - TIMESERIE #6 : Etude long terme de la variabilité du Courant Nord

description: JULIO (Judicious Location for Intrusions Observations) mooring is located close to the 100 m-deep isobath (around 5.25°E and 43.13°N), offshore Marseille. With its bottom-moored (300kHz) ADCP, it enables measuring horizontal currents (every 4 m and every ½ h) through the water column, and among others, identifying periods of exchange between the Northern Current and the continental shelf. It is one crucial component in the study of the coastal-offshore gradient from Marseille to the MOOSE 42°N5°E station, and potential covariances with the MIO radar and other MIO or international observing systems, as well as with the SOMLIT site (including also an ADCP) in the bay of Marseille. Moreover, with a bottom CTD, it can detect environmental anomalies in classical hydrographic data, useful for oceanographers. As one of the rare station at the interface between the continental shelf and offshore, it will allow to observe the long-term evolution of the Northern Current in the context of climate change and anthropogenic pressure, and its potential varying impact on the Gulf of Lion. The data are of course also crucial for modellers. Moreover they show a great potential when supplementing other MOOSE data (glider and radar). Timeserie #6 : - JULIO 6 - 24/06/2022 to 22/06/2023; JULIO (Judicious Location for Intrusions Observations) est situé à proximité de l'isobathe de 100 m de profondeur (environ 5,25°E et 43,13°N), au large de Marseille. Grâce à son ADCP (300 kHz), il permet de mesurer les courants horizontaux (tous les 4 m et toutes les ½ h) à travers la colonne d'eau et, entre autres, d'identifier les périodes d'échange entre le courant du Nord et le plateau continental. Il s'agit d'un élément crucial dans l'étude du gradient littoral-offshore de Marseille à la station MOOSE 42°N5°E, et des covariances potentielles avec le radar MIO et autres systèmes d'observation MIO ou internationaux, ainsi qu'avec le site SOMLIT (incluant également un ADCP) dans la baie de Marseille. De plus, avec un CTD de fond, il peut détecter les anomalies environnementales dans les données hydrographiques classiques, utiles aux océanographes. En tant qu'une des rares stations à l'interface entre le plateau continental et le large, elle permettra d'observer l'évolution à long terme du courant du Nord dans le contexte du changement climatique et de la pression anthropique, et son impact potentiel variable sur le Golfe du Lion. Les données sont bien sûr également cruciales pour les modélisateurs. De plus, ils présentent un grand potentiel en complément d'autres données MOOSE (planeur et radar). Série temporelle #6 : - JULIO 6 - 24/06/2022 to 22/06/2023;
DOI: 10.34930/dc1daf1c-09e3-4829-8878-91d0bf0e643e
title: R-shiny-microorganisms v2 : A ready-to-use logistic regression implemented in R shiny to estimate growth parameters of microorganisms

description: Environmental conditions are a set of physical and biological variables that define an ecosystem. Microorganisms with higher generation times than more complex multicellular organisms are more sensitive to changing environmental conditions. Therefore, microbial growth curves are an important and simple way to understand how environmental conditions affect microorganisms. Growth curves are used in a variety of biological applications. Traditionally in microbiology, the maximum growth rate (µmax) is calculated by fitting a linear model on data of the exponential growth phase. This method is simple to implement, and robust if the exponential phase contains many points. However, this method is very limiting when the curve is described with few points, as we have seen with experiments under high pressure conditions. In order to overcome this limit, recurrent in biology, we propose to use models to estimate growths parameters. Modeling has existed for many years to describe the growth behavior of microorganisms under variable physical and chemical conditions (Zwietering et al., 1990). Here we propose a ready-to-use application that do not require any special coding skills and allow retrieving several essential parameters describing microbial growth. his app aims at estimating the growth rate and maximum cells density using non-linear regression. The method is detailled in Martini et al. (2013). A demo dataset is available in "Download a demo dataset", you can save it in your computer and load it using "Browse", or you can also browse your own dataset. On Plot panel, it is possible to set axes labels, axes range and Smooth. Smooth parameter can compute theorical (downloadable) for to use with other activities. In order to run this application, you have to format your dataset with tabulation separators. Also, remove all spaces in the dataset header (prefer to use "_" when needed). Organise your dataset so that there is only two arrays. The first one being the time and the second one, the cells density (e. g. optic density, cell number, biomass). This application proposes a method to perform a logistic regression to estimate growth rate as well as maximum cells density . Authors : Garel, M., Lloyd, I., Vienne, M., David, N., Tamburini, C., Martini, S.,
DOI: 10.34930/yq-crg-20230926
title: VelingaraData : geophysical and zircon data acquired in the Velingara circular depression (Senegal)

description: The Velingara dataset gathers geophysical and zircon data acquired in the Velingara circular depression (Senegal). In March 2022, a field campaign was performed in this depression, since it is thought to be an impact structure. Magnetic and gravity field observations were done, as well as sampling. Several zircon grains of sample VEL29A were analysed by LA-ICP-MS, given an age of 550 Ma.
DOI: 10.15468/dl.ayy336
title: Occurrence Download

description: A dataset containing 107 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Croatia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Castor fiber Linnaeus, 1758"
 ]
}

 The dataset includes 107 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015663-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9vtupz
title: Occurrence Download

description: A dataset containing 3299 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Tessaratoma papillosa, Tessaratoma papillosa (Drury, 1770), Tessaratoma papillosa, Tessaratoma papillosa (Drury, 1770), Tessaratoma papillosa (Drury, 1770), Tessaratoma papillosa, Tessaratoma papillosa (Drury, 1770), Tessaratoma papillosa (Drury, 1770), Anastatus (Anastatus) shichengensis Sheng and Wang 1997, Anastatus shichengensis Sheng & Wang, 1997, Anastatus formosanus Crawford, 1913, Anastatus (Anastatus) formosanus Crawford 1913, Anastatus (Anastatus) fulloi Sheng and Wang 1997, Anastatus (Anastatus) dexingensis Sheng and Wang 1997, Anastatus fulloi Sheng & Wang, 1997, Anastatus dexingensis Sheng & Wang, 1997, Anastatus shichengensis Sheng & Wang 1997, Anastatus (Anastatus) japonicus Ashmead 1904, Anastatus japonicus Ashmead, 1904)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "Geometry POLYGON((-180 -90,180 -90,180 90,-180 90,-180 -90))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 3299 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015665-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dwtn68
title: Occurrence Download

description: A dataset containing 1753 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Macropsis remota Tishechkin, 1998, Kybos purus (Stål, 1858), Kybos livingstonii (Gillette, 1898), Macropsis leporina Tishechkin, 1997, Kybos clinatus (Ross, 1963), Edwardsiana geriosi Lahoud, 1995, Edwardsiana euphrante (McAtee, 1926), Macropsis ochotonaria Tishechkin, 1994, Kybos crystola (Ross, 1963), Omalophora costalis (Matsumura, 1903), Metidiocerus crassipes (Sahlberg, 1871), Eratoneura macra (Beamer, 1932), Idiocerus albolinea Hamilton, 1985, Populicerus duzeei (Provancher, 1889), Kybos rufescens rufescens, Macropsis microcerea Vilbaste, 1980, Kybos dentifer (Logvinenko, 1980), Kybos tereholli Vilbaste, 1980, Kybos dworakowskii Mitjaev, 1980, Kybos isotoma (Logvinenko, 1980), Idiocerus lucidae Hamilton, 1980, Podulmorinus consimilis (Vilbaste, 1968), Nabicerus fuscescens (Anufriev, 1971), Podulmorinus opacus (Anufriev, 1978), Kybos candelabricus Dlabola, 1958, Idiocerus ramentosus (Uhler, 1877), Macropsis rufocephalus Osborn, 1932, Idiocerus snowi Gillette & Baker, 1895, Kybos alberta (Ross, 1963), Idiocerus heptapotamicus Mitjaev, 1970, Macropsis sordida (Van Duzee, 1894), Kybos montanus Mitjaev, 1971, Macropsis feminis Hamilton, 1972, Koreocerus koreanus (Matsumura, 1915), Kybos chadchalicus Dlabola, 1967, Podulmorinus latistylus (Vilbaste, 1968), Elymana pallidipennis (Lindberg, 1929), Athysanopsis salicis Matsumura, 1905, Cedusa turkestanica (Dubovskiy, 1965), Macropsis asiatica Dubovsky, 1966, Platymetopius tortuosus Dlabola, 1963, Podulmorinus vitticollis (Matsumura, 1905), Hebata serrata (Vilbaste, 1965), Kybos annella (Hartzell, 1923), Kybos chapingo (Ross, 1963), Kybos ziona (DeLong & Davidson, 1936), Macropsis glandacea (Fieber, 1868), Macropsis viridans (Turton, 1802), Macropsis impura (Boheman, 1847), Colladonus atropunctatus (Van Duzee, 1890))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 1753 records from 73 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015667-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5066/p1vf3zx4
title: Current and future hydrology and occupancy predictions for boreal toads (Anaxyrus boreas boreas) in the Southern Rocky Mountains

description: These data consist of three primary types of products for managers of boreal toads in the Southern Rocky Mountains: 1) Re-constructed hydroperiods for historical breeding sites from LANDSAT imagery from 1985-2022 (SMA_hydroperiod_reconstruction.csv). This dataset was developed using a Spectral Mixture Analysis (SMA). 2) Current (1985-2022) and future (2040-2069) predictions of probability of drying and surface area estimates for historical breeding sites (Current_hydrology_predictions.csv, Future_hydrology_predictions.csv). These datasets were developed using a Bayesian hurdle model with the surface water area estimate from the SMA as the response variable. 3) Current (1985-2020) and future (1955-1969) predictions of occupancy for boreal toads (Anaxyrus boreas boreas) and the amphibian chytrid fungus (Batrachochytrium dendrobatidis) at three spatial scales; breeding site (Current_future_occ_prob_ind_site.csv), mountain range (Current_future_occ_prob_mtn_range.csv) and Southern Rocky Mountain Region (Current_future_occ_prob_SRM.csv). These datasets were developed from a Bayesian dynamic state-space community model.
DOI: 10.15468/dl.p3nsr8
title: Occurrence Download

description: A dataset containing 588353 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Polygonatum Mill."
 ]
}

 The dataset includes 588353 records from 2248 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015664-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.f2tk8f
title: Occurrence Download

description: A dataset containing 60049 species occurrences available in GBIF matching the query:
{
 "PublishingOrg" : [
 "is 4f3d98d3-f69a-4929-9291-6c35340b6711"
 ]
}

 The dataset includes 60049 records from 34 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0090717-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.436pbb
title: Occurrence Download

description: A dataset containing 78 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Liasis olivaceus olivaceus)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 78 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0090751-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.60600/yu/clawet/onv9yq
title: 0336.wav

description: :unav
DOI: 10.15468/dl.ykewqq
title: Occurrence Download

description: A dataset containing 411 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Spain",
 {
 "or" : [
 "Geometry POLYGON((-17.68957 30.13963,18.6049 30.13963,18.6049 44.6512,-17.68957 44.6512,-17.68957 30.13963))",
 "Geometry POLYGON((-2.14945 38.0813,0.78155 38.0813,0.78155 39.29815,-2.14945 39.29815,-2.14945 38.0813))"
 ]
 },
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Genista longipes Rouy"
 ]
}

 The dataset includes 411 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0090752-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ay4g7p
title: Occurrence Download

description: A dataset containing 68 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Morella adenophora (Hance) J.Herb.",
 "Year 1812-2024"
 ]
}

 The dataset includes 68 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0090753-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.60600/yu/clawet/jrqndk
title: 0478.TextGrid

description: :unav
DOI: 10.60600/yu/clawet/fh32js
title: 0366.TextGrid

description: :unav
DOI: 10.15468/dl.ye769f
title: Occurrence Download

description: A dataset containing 1451 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Salix taraikensis Kimura)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Machine Observation)",
 "Country is Russian Federation",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 1451 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0090754-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.f3g2ha
title: Occurrence Download

description: A dataset containing 285 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "OccurrenceStatus is Present",
 "TaxonKey is Bactris guineensis (L.) H.E.Moore"
 ]
}

 The dataset includes 285 records from 42 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0090755-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.60600/yu/clawet/l9gfon
title: 0354.wav

description: :unav