cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh0193207.10fu
title: SH0193207.10FU

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/sh0193208.10fu
title: SH0193208.10FU

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/sh0193209.10fu
title: SH0193209.10FU

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/sh0193210.10fu
title: SH0193210.10FU

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/sh0193211.10fu
title: SH0193211.10FU

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/sh0193212.10fu
title: SH0193212.10FU

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/sh0193213.10fu
title: SH0193213.10FU

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/sh0193214.10fu
title: SH0193214.10FU

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/sh0193215.10fu
title: SH0193215.10FU

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/sh0193216.10fu
title: SH0193216.10FU

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.jbyc48
title: Occurrence Download

description: A dataset containing 834 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Mesobuthus Vachon, 1950"
 ]
}

 The dataset includes 834 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004907-250415084134356/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/11451532
title: Vietnam SARS-CoV-2 | COVID-19 Data
DOI: 10.15468/dl.nyj2w2
title: Occurrence Download

description: A dataset containing 117 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Occurrence evidence, Human Observation)",
 "TaxonKey is Stryphnodendron adstringens (Mart.) Coville"
 ]
}

 The dataset includes 117 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024101-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mh2742
title: Occurrence Download

description: A dataset containing 858 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Astragalus angustifolius Lam."
 ]
}

 The dataset includes 858 records from 76 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024104-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7st3mp
title: Occurrence Download

description: A dataset containing 4316 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Flora del Parque Nacional Cumbres de Monterrey, Nuevo León, México"
 ]
}

 The dataset includes 4316 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024102-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nqqrar
title: Occurrence Download

description: A dataset containing 858 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Astragalus angustifolius Lam."
 ]
}

 The dataset includes 858 records from 76 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024105-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14853280
title: ACORN (Accumulated Carbon on Range and Natural lands), a resource for carbon estimation in California oak woodlands

description: A draft version of a resource for estimation of carbon sequestration in California oak woodlands. Data sources include USDA Forest Inventory Analysis (FIA) plots, published peer-reviewed papers, and the grey literature, including unpublished reports and undergraduate theses. Plots met criteria for Manual of California Vegetation classification in one of eight types of oak-dominated habitat. Plots were area-based censuses of all woody individuals measured for diameter at breast height, permitting the calculation of biomass and carbon according to standard allometric equations. The dataset consists of data summed by plot as well as a comprehensive listing of all individual trees, both presented in the style of an FIA database. Pending publication of a peer-reviewed journal article summarizing these data, the dataset should be considered as being in draft (unfinished) form; please contact author Virginia Matzek vmatzek@scu.edu for permission to use the database and to answer any questions about its application to carbon accounting.
DOI: 10.5281/zenodo.14853281
title: ACORN (Accumulated Carbon on Range and Natural lands), a resource for carbon estimation in California oak woodlands

description: A draft version of a resource for estimation of carbon sequestration in California oak woodlands. Data sources include USDA Forest Inventory Analysis (FIA) plots, published peer-reviewed papers, and the grey literature, including unpublished reports and undergraduate theses. Plots met criteria for Manual of California Vegetation classification in one of eight types of oak-dominated habitat. Plots were area-based censuses of all woody individuals measured for diameter at breast height, permitting the calculation of biomass and carbon according to standard allometric equations. The dataset consists of data summed by plot as well as a comprehensive listing of all individual trees, both presented in the style of an FIA database. Pending publication of a peer-reviewed journal article summarizing these data, the dataset should be considered as being in draft (unfinished) form; please contact author Virginia Matzek vmatzek@scu.edu for permission to use the database and to answer any questions about its application to carbon accounting.
DOI: 10.15468/dl.b996rw
title: Occurrence Download

description: A dataset containing 833964 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is one of (North America, South America)",
 "Country is Mexico",
 "GadmGid is MEX.19_1",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 833964 records from 604 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024001-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14853271
title: data for karinorman/monitoringSim

description: These are the raw and interim data products required for reproducing the analysis outlined in karinorman/monitoringSim.
DOI: 10.5281/zenodo.14853272
title: data for karinorman/monitoringSim

description: These are the raw and interim data products required for reproducing the analysis outlined in karinorman/monitoringSim.
DOI: 10.5281/zenodo.14049886
title: Increased transparency in accounting conventions could benefit climate policy

description: Datasets of emissions from 1750-2020 and spreadsheet of calculations supporting the manuscript: Wedderburn-Bisshop, G. 2025 Increased transparency in accounting conventions could benefit climate policy

 

Abstract

Greenhouse gas accounting conventions were first devised in the 1990’s to assess and compare emissions. Several assumptions were made when devising these conventions that remain in practice, however recent advances offer potentially more consistent and inclusive accounting of greenhouse gases. We apply these advances, namely: gross accounting of CO2 sources; linking land use emissions with sectors; using Effective Radiative Forcing (ERF) rather than Global Warming Potentials (GWPs) to compare emissions; including both heating and cooling emissions, and including loss of additional sink capacity (LASC). We compare these results with conventional accounting and find that this approach boosts perceived carbon emissions from deforestation, and finds agriculture, the most extensive land user, to be the leading emissions sector and to have caused 60% (32%-87%) of ERF change since 1750. We also find that fossil fuels are responsible for 17% of ERF, a reduced contribution due to masking from cooling co-emissions. We test the validity of this accounting and find it useful for determining sector responsibility for present-day warming and for framing policy responses, while recognising the dangers of assigning value to cooling emissions, due to health impacts and future warming.
DOI: 10.5281/zenodo.14049887
title: Consistent, inclusive emissions accounting identifies agriculture as the leading cause of climate change

description: Datasets of emissions from 1750-2020 and spreadsheet of calculations supporting the manuscript: Wedderburn-Bisshop, G. 2024 Consistent, inclusive emissions accounting identifies agriculture as the leading cause of climate change 

 

Abstract

Recent advances in emissions accounting enable an improved assessment of sector responsibility for present day climate change. We apply these advances, namely: consistent gross accounting of CO2 sources; linking land use emissions with sectors; using Effective Radiative Forcing (ERF) rather than Global Warming Potentials (GWPs) to compare emissions; and inclusive accounting of heating and cooling emissions. This assessment finds agriculture, the most extensive land user, to be the leading emissions sector and to have caused 60% (44%-86%) of global surface air temperature (GSAT) change from 1750 to 2020, due in large part to past and present deforestation, with 87% of this (52% of total warming) attributable to animal agriculture. We also find that fossil fuels have been responsible for 23% of warming, a reduced contribution due to the masking impact of cooling co-emissions. We test the validity of this accounting and find it useful for determining sector responsibility for present-day warming and for framing policy response, while recognising the dangers of assigning value to cooling emissions, due to health impacts and future warming.
DOI: 10.5281/zenodo.14624823
title: Increased transparency in accounting conventions could benefit climate policy

description: Datasets of emissions from 1750-2020 and spreadsheet of calculations supporting the manuscript: Wedderburn-Bisshop, G. 2025 Increased transparency in accounting conventions could benefit climate policy

 

Abstract

Greenhouse gas accounting conventions were first devised in the 1990’s to assess and compare emissions. Several assumptions were made when devising these conventions that remain in practice, however recent advances offer potentially more consistent and inclusive accounting of greenhouse gases. We apply these advances, namely: gross accounting of CO2 sources; linking land use emissions with sectors; using Effective Radiative Forcing (ERF) rather than Global Warming Potentials (GWPs) to compare emissions; including both heating and cooling emissions, and including loss of additional sink capacity (LASC). We compare these results with conventional accounting and find that this approach boosts perceived carbon emissions from deforestation, and finds agriculture, the most extensive land user, to be the leading emissions sector and to have caused 60% (32%-87%) of ERF change since 1750. We also find that fossil fuels are responsible for 17% of ERF, a reduced contribution due to masking from cooling co-emissions. We test the validity of this accounting and find it useful for determining sector responsibility for present-day warming and for framing policy responses, while recognising the dangers of assigning value to cooling emissions, due to health impacts and future warming.
DOI: 10.5281/zenodo.14838263
title: Increased transparency in accounting conventions could benefit climate policy

description: Datasets of emissions from 1750-2020 and spreadsheet of calculations supporting the manuscript: Wedderburn-Bisshop, G. 2025 Increased transparency in accounting conventions could benefit climate policy

 

Abstract

Greenhouse gas accounting conventions were first devised in the 1990’s to assess and compare emissions. Several assumptions were made when devising these conventions that remain in practice, however recent advances offer potentially more consistent and inclusive accounting of greenhouse gases. We apply these advances, namely: gross accounting of CO2 sources; linking land use emissions with sectors; using Effective Radiative Forcing (ERF) rather than Global Warming Potentials (GWPs) to compare emissions; including both heating and cooling emissions, and including loss of additional sink capacity (LASC). We compare these results with conventional accounting and find that this approach boosts perceived carbon emissions from deforestation, and finds agriculture, the most extensive land user, to be the leading emissions sector and to have caused 60% (32%-87%) of ERF change since 1750. We also find that fossil fuels are responsible for 17% of ERF, a reduced contribution due to masking from cooling co-emissions. We test the validity of this accounting and find it useful for determining sector responsibility for present-day warming and for framing policy responses, while recognising the dangers of assigning value to cooling emissions, due to health impacts and future warming.