cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.nzx88j
title: Occurrence Download

description: A dataset containing 165 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "BasisOfRecord is Specimen",
 "BasisOfRecord is Fossil",
 "BasisOfRecord is Material sample"
 ]
 },
 "Geometry POLYGON((-251.52353 29.38235,-138.97059 29.38235,-138.97059 74.38235,-251.52353 74.38235,-251.52353 29.38235))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Selaginella selaginoides (L.) Schrank & C.F.P.Mart."
 ]
}

 The dataset includes 165 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0292528-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7uzw5h
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Saussurea taraxacifolia Wall.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0321313-200613084148143/datasets/export for details.
DOI: 10.15468/dl.xm7dhm
title: Occurrence Download

description: A dataset containing 6654 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Symphytum asperum Lepech."
 ]
}

 The dataset includes 6654 records from 221 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0269934-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ps8ny2
title: Occurrence Download

description: A dataset containing 51576 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "BasisOfRecord is Observation",
 "BasisOfRecord is Machine Observation",
 "BasisOfRecord is Human Observation",
 "BasisOfRecord is Material sample",
 "BasisOfRecord is Literature Occurrence",
 "BasisOfRecord is Specimen",
 "BasisOfRecord is Living Specimen",
 "BasisOfRecord is Unknown evidence"
 ]
 },
 "Country is Spain",
 "HasCoordinate is true",
 "TaxonKey is Pinus halepensis Mill.",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 51576 records from 46 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009441-180412121330197/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wzmc6v
title: Occurrence Download

description: A dataset containing 73 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Endecous Saussure, 1878"
 ]
}

 The dataset includes 73 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0314989-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ykmskn
title: Occurrence Download

description: A dataset containing 117 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-60.39843 -58.88672,-42.11718 -25.98047,-63.21093 -15.85549,-81.77343 -17.54297,-83.17968 -58.32423,-60.39843 -58.88672))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Saxegothaea Lindl."
 ]
}

 The dataset includes 117 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0317585-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xfkt2r
title: Occurrence Download

description: A dataset containing 860 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "OccurrenceStatus is Present",
 "TaxonKey is Origanum vulgare L."
 ]
}

 The dataset includes 860 records from 39 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0276914-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dcv7a9
title: Occurrence Download

description: A dataset containing 24 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Physostigma mesoponticum Taub.",
 "HasCoordinate is TRUE"
 ]
}

 The dataset includes 24 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009441-180730143533302/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.38zvy5
title: Occurrence Download

description: A dataset containing 73654 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Aquila fasciata Vieillot, 1822",
 "HasCoordinate is true",
 "Year is greater than or equal to 2011",
 "Year is less than or equal to 2024"
 ]
}

 The dataset includes 73654 records from 156 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0051259-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh0162728.10fu
title: SH0162728.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0162729.10fu
title: SH0162729.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0162730.10fu
title: SH0162730.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0162731.10fu
title: SH0162731.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0162732.10fu
title: SH0162732.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0162733.10fu
title: SH0162733.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0162734.10fu
title: SH0162734.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.5285/3f0820a7-a8c8-4dd7-a058-8db79ba9c7fe
title: Five year record of aquatic carbon and greenhouse gas concentrations from Auchencorth Moss

description: Dataset contains concentrations of particulate and dissolved organic carbon, inorganic carbon, CO2, CH4 and N2O in the Black Burn stream which drains Auchencorth Moss peatland in South East Scotland. Auchencorth Moss is part of the UK Centre for Ecology & Hydrology's UK Carbon Catchment project. 

Concentrations have been measured approximately weekly from January 2007 to December 2011 
description: Water and headspace (for gas analsyis) samples were collected approximately weekly primarily by Dr Kerry Dinsmore. Analysis was carried out at CEH Edinburgh, again primarily by Dr Kerry Dinsmore. The samples were collected from a single sampling site over the 5 year period. A detailed description of the datasets, including methodology and discussion of the findings can be found in the following peer-reviewed article: Dinsmore, K.J.; Billett, M.F.; Dyson, K.E.. 2013 Temperature and precipitation drive temporal variability in aquatic carbon and GHG concentrations and fluxes in a peatland catchment. Global Change Biology. 10.1111/gcb.12209
DOI: 10.15156/bio/sh0162735.10fu
title: SH0162735.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15468/dl.65fcez
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Cypripedium fargesii",
 "Year 1950-2026"
 ]
}

 The dataset includes 5 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001082-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5285/37a503da-d75c-4d72-8e8b-b11c2fdc7d92
title: Farm scale evaluations of herbicide tolerant genetically modified crops - winter oilseed rape

description: This dataset consists of a range of ecological measurements collected from a set of arable fields, each sown with a combination of genetically modified and conventional winter-sown oilseed rape crops. Measurements include species counts in the following areas: weed seedbank, vegetation in the crop, field edge vegetation, invertebrates. The data were collected as part of the Farm Scale Evaluations (FSEs), a four-year programme of research by independent researchers aimed at studying the effect that the management practices associated with Genetically Modified Herbicide Tolerant (GMHT) crops might have on farmland wildlife, when compared with weed control used with non-GM crops. Data were collected by a consortium of: the Institute of Terrestrial Ecology (now the Centre for Ecology & Hydrology), the Institute of Arable Crops Research (now Rothamsted Research) and the Scottish Crop Research Institute (now the James Hutton Institute). Data were collected for four crops overall (Beet, Maize, Spring-sown Oilseed Rape and Winter-sown oilseed Rape).
description: Data were collected by a consortium of: the Institute of Terrestrial Ecology, ITE (now the Centre for Ecology & Hydrology, CEH), the Institute of Arable Crops Research (now Rothamsted Research, IACR) and the Scottish Crop Research Institute,SCRI. Data were collected for the four crops (Beet, Maize, Spring-sown Oilseed Rape and Winter-sown oilseed Rape) in the following areas: seedbank, vegetation in the crop, field edge vegetation, invertebrates.  Strict data entry and storage controls, data management controls and data analysis protocols were in place during the project. Key reference: Effects on weed and invertebrate abundance and diversity of herbicide management in genetically modified herbicide-tolerant winter-sown oilseed rape, Bohan et al., Proc. R. Soc. B March 7, 2005 272:463-474
DOI: 10.5285/f6cac471-7d92-4e6d-be8a-9f7887143058
title: Grid-to-Grid model estimates of daily mean river flow for gauged catchments in Great Britain: weather@home2 (climate model) driving data [MaRIUS-G2G-WAH2-daily]

description: This dataset is a model output, from the Grid-to-Grid hydrological model driven by weather@home2 climate model data. It provides a 100-member ensemble of daily mean river flow (m3/s) for 260 catchments, for the following time periods: historical baseline (HISTBS: 1900-2006), near-future (NF: 2020-2049) and far-future (FF: 2070-2099). It also includes a baseline period (BS: 1975-2005). The catchments correspond to locations of NRFA gauging stations (http://nrfa.ceh.ac.uk/). 

The data were produced as part of MaRIUS (Managing the Risks, Impacts and Uncertainties of drought and water Scarcity), which was a UK NERC-funded research project (2014-2017) that developed a risk-based approach to drought and water scarcity.
description: The flow estimates are output from the Grid-to-Grid hydrological model (Bell et al. 2009; https://doi.org/10.1016/j.jhydrol.2009.08.031). The meteorological inputs to the model were the weather@home2 bias-corrected precipitation and potential evaportation (Guillod et al. 2018; http://dx.doi.org/10.5285/0cea8d7aca57427fae92241348ae9b03). See Supporting Information for more details.
DOI: 10.15156/bio/sh0162736.10fu
title: SH0162736.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0162737.10fu
title: SH0162737.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.5285/0ceb4f85-0bbf-49f0-ab70-cfc137ab7d4d
title: Grid-to-Grid model estimates of daily mean river flow for gauged catchments in Great Britain (1891 to 2015): observed driving data [MaRIUS-G2G-Oudin-daily]

description: This dataset is a model output, from the Grid-to-Grid hydrological model driven by observed climate data (CEH-GEAR rainfall and Oudin temperature-based potential evaporation). It provides daily mean river flow (m3/s) for 260 catchments, for the period 1891 to 2015. The catchments correspond to locations of NRFA gauging stations (http://nrfa.ceh.ac.uk/).

The data were produced as part of MaRIUS (Managing the Risks, Impacts and Uncertainties of drought and water Scarcity), which was a UK NERC-funded research project (2014-2017) that developed a risk-based approach to drought and water scarcity (http://www.mariusdroughtproject.org/).
description: The river flow estimates are output from the Grid-to-Grid hydrological model (Bell et al. 2009; doi:10.1016/j.jhydrol.2009.08.031). The meteorological inputs to the model were rainfall from CEH-GEAR (Tanguy et al. 2016; doi:10.5285/33604ea0-c238-4488-813d-0ad9ab7c51ca) and potential evaporation derived from 5km temperature data (Perry and Hollis, 2005, doi:10.1002/joc.1161) using the method of Oudin et al. (2005; https://doi.org/10.1016/j.jhydrol.2004.08.026). See Supporting Information for more details.