cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh1407954.10fu
title: SH1407954.10FU

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/sh1407955.10fu
title: SH1407955.10FU

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/sh1407957.10fu
title: SH1407957.10FU

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/sh1407962.10fu
title: SH1407962.10FU

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/sh1407963.10fu
title: SH1407963.10FU

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/sh1407966.10fu
title: SH1407966.10FU

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/sh1407972.10fu
title: SH1407972.10FU

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/sh1407973.10fu
title: SH1407973.10FU

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.cw7df7
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"GADM_LEVEL_2_GID","value":"BRA.13.211_2","matchCase":false},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006244-260108223611665/datasets/export for details.
DOI: 10.15156/bio/sh1407975.10fu
title: SH1407975.10FU

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.bc6yk3
title: Occurrence Download

description: A dataset containing 537 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Spermolepis echinata (Nutt.) A.Heller)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 537 records from 61 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0078909-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ns36k4
title: Occurrence Download

description: A dataset containing 14472 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Silphium perfoliatum L.)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 14472 records from 132 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0078910-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25919/xzrs-f758
title: Account-ready data: ecosystem services in the Flinders, Norman and Gilbert river catchments. A data collection from the Regional Ecosystem Accounting Pilot projects

description: This collection comprises account-ready data for the Flinders, Norman and Gilbert river catchments for the following ecosystem services: (1) terrestrial carbon storage, sequestration and emissions and (2) biomass provisioning. It includes annual time-series provided as spatial data (.GPKG and .TIFF) and Excel spreadsheets. (3) Supplementary socio-economic data are also provided.

Terrestrial carbon storage, sequestration and emissions: Spatial emulation of the Full Carbon Accounting Model (FullCAM) is used to develop an annual time-series (1988-2020) of terrestrial carbon storage, sequestration, and emissions across the Flinders, Norman and Gilbert (FNG) river catchments at a spatial resolution of 100 m. Both stocks (carbon mass of crops, pastures, forests, woodlands, shrublands, debris and soil) and fluxes (emissions of CO2, N2O and CH4 due to fire, heterotrophic respiration, net primary productivity, net ecosystem carbon balance) of carbon are provided in units of tCO2e ha-1 and tCO2e ha-1 yr-1, respectively. Emission factors and other quantities used to convert CH4 and N2O fire emissions to CO2e are provided in Section 6.4.5.1 of DISER (2022) 
(https://www.dcceew.gov.au/sites/default/files/documents/national-inventory-report-2020-volume-2.pdf). 

Biomass provisioning: This collection comprises an annual time-series from 2000-01 to 2019-20 (where possible) of physical and monetary measures of agricultural production and estimates of biomass provisioning ecosystem services across the Flinders, Norman, and Gilbert (FNG) river catchments. The agricultural production data covers livestock (milk, sheep and lambs slaughtered, cattle and calves slaughtered, pigs, poultry). The ecosystem service data provides estimates of the final ecosystem services of grazed biomass provisioning. The data was sourced from the Australian Bureau of Statistics (ABS) DataLab environment using the Farm-level Longitudinal Agricultural Dataset (FLAD) and the Business Longitudinal Analysis Data Environment (BLADE). 

This collection comprises a time series (2011, 2016 and 2021) of selected socio-economic variables across the Flinders, Norman, and Gilbert (FNG) river catchments. The variables provide estimates of the number of people employed and gross value added (GVA) in selected industries. The data was sourced from the Australian Bureau of Statistics (ABS).
DOI: 10.15468/dl.bqbcmr
title: Occurrence Download

description: A dataset containing 2330 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Cicuta bulbifera L.)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2330 records from 79 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0078911-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25919/zg7g-3113
title: Account-ready data: ecosystem condition in the Flinders, Norman and Gilbert river catchments in Queensland. A data collection from the Regional Ecosystem Accounting Pilot projects

description: This collection comprises ecosystem condition account-ready data for the Flinders, Norman and Gilbert river catchments in Queensland, which is one of two case studies of the Ecosystem Accounting Pilots for Agricultural and Mixed-Use Landscapes project, delivering ecosystem accounts at sub-national scales. Dataset values (index) vary continuously from a theoretical minimum of 0.0 (ecosystem integrity extinguished) to a maximum of 1.0 (ecosystem integrity in reference condition). The index represents the contribution that a given site (grid cell) makes to the effective area of ecosystem integrity remaining within any given spatial reporting unit, expressed as a proportion of the contribution made by a site in reference condition. Ecosystem condition data are provided for 18 annual epochs (between 2001 and 2018) derived by combining data developed through applications of the Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensing-based Habitat Condition Assessment System (HCAS) and the expert opinion-based Australian Ecosystem Models (AusEcoModels) Framework. The HCAS application version 2.3 (v2.3) is a modification of the original HCAS version 2.1 and further incorporates landscape context effects through inferred local pressures, resulting in the ecosystem site condition subindex. The AusEcoModels application uses expert elicitation to derive conceptual models of ecosystem reference and modified condition states and associated condition scores. Rule sets relate these condition states to remote sensing variables representing ecosystem characteristics to map the ecosystem state condition subindex. These subindex datasets are included in this collection.

The supplementary metadata report summarises how the ecosystem condition index was derived, and describes the datasets in this collection. Supplementary data are provided in this collection to support interpretation and use. These include the overall HCAS v2.3 best estimate of ecosystem condition for the 2001 to 2018 long-term remote sensing epoch and associated subindex datasets; the significant trend in ecosystem condition from the 18 annual epochs; an analysis of how ‘nearby’ and relevant the 20 reference sites used as benchmarks were to the estimate of HCAS habitat condition for each site of interest; and a spatial mask for use when aggregating ecosystem condition data into accounts and tables for reporting to exclude areas identified as potentially erroneous.

All raster data in this collection are provided as 100 m spatially-registered GeoTiff files, mostly in floating point format (Spatial extent in GDA2020, Australian Albers, EPSG:9473: xmin: 802000, xmax: 1350000, ymin: -2383000, ymax: -1792000). These were used as a basis for developing a set of ecosystem condition stock accounts and supplementary data tables for the Flinders, Norman and Gilbert river catchments in Queensland (see Richards et al. 2023, https://data.csiro.au/collection/csiro:57810).
DOI: 10.15468/dl.bdygw7
title: Occurrence Download

description: A dataset containing 1857 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Silphium asteriscus L.)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1857 records from 73 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0078912-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25919/145e-rm35
title: Ecosystem classification and conceptual models for the Flinders, Norman and Gilbert river catchments. A data collection from the Regional Ecosystem Accounting Pilot projects

description: This is a collection that describes conceptual ecosystem models for the Flinders, Norman and Gilbert river catchments pilot region. These are supplementary information used for interpretation of ecosystem accounts developed in the ‘Ecosystem Accounting Pilots for Agricultural and Mixed-Use Landscapes’ project, one of two Regional Ecosystem Accounting Pilot (REAP) projects delivering ecosystem accounts at sub-national scales. A second data collection describes conceptual ecosystem models for the WA Wheatbelt, the other pilot region in Project 1 (Prober et al. 2023, https://data.csiro.au/collection/csiro:57829).

This data collection comprises the following elements: a methods report (which includes a description of methods used to generate conceptual models and expert-derived condition scores, a text summary of the models (including ecosystem states and transitions), a table of expert-derived condition scores and a summary of limitations and lessons learned)); PowerPoint files containing diagrams and photographs of each model; Excel files containing descriptions and quantities for attributes related to structure, function and composition of each conceptual model; an Excel file of transitions between ecosystem states; an Excel file of individual expert condition scores.
DOI: 10.48597/5n3f-pede
title: Measurement of Nitrogen oxides at Monte Cimone

description: Measurement of Nitrogen oxides at Monte Cimone
DOI: 10.5281/zenodo.11231501
title: Dataset of 4D conserved tracers for convection simulated by large eddy model and cloud resolving model

description: There are conserved tracers and active flag for convection used for diagnosis of bulk entrainment rate for four convection cases in this dataset. Total water and moist static energy are selected as tracer for shallow convection (BOMEX and RICO) and deep convection (GATE and KWAJEX), respectively. The two variables simulated by large eddy model for shallow convection and cloud resolving model for deep convection are four-dimension variables with horizontal scales, vertical altitude, and time. 

The size of domain simulated for BOMEX and RICO is 6.4 km with horizontal grid spacing of 100 m, and that GATE and KWAJEX is 256 km with horizontal grid spacing of 1 km. Besides, vertical layers in the simulation are 75 levels with spacing of 40m for BOMEX and 100 levels with spacing of 40m for RICO. For KWAJEX and GATE, the model was set up with 64 levels vertically, which gradually increases from 75 m at the surface to a spacing of 400 m through the troposphere and a larger spacing of 1 km in the Newtonian damping region. The model is integrated for 6 hours for BOMEX, 24 hours for RICO, 52.25 days for KWAJEX, and 20 days for GATE. Here, the range of time in these variables  The four-dimension variables are saved every 3 seconds for shallow convection, and every 6 minutes for deep convection for two consecutive days.
DOI: 10.5281/zenodo.11231502
title: Diagnostic entrainment rate for convection with varying horizontal resolution

description: There are diagnostic entrainment rate for four cases in this dataset. Two of them are for shallow convection (BOMEX and RICO), while the other two cases are for deep convection (GATE and KWAJEX). Each folder is for one convective case. For shallow convection, there are six files containing diagnostic entrainment rate coarse grained by large eddy simulation outcomes with whole domain of 6.4km at horizontal resolution for 6.4km, 3.2km, 1.6km, 0.8km, 0.4km, and 0.2km, respectively. And for deep convection cases, the horizontal resolution for eight files of diagnostic entraiment rate varies from 256km to 2km, with whole domain area of 256km.

Every file is a 3D matrix for entrainment rate with dimension of altitude, time, and coarse grained parts. 75 levels with spacing of 40m for BOMEX and 100 levels with spacing of 40m for RICO are set for shallow convection cases. For KWAJEX and GATE, the model was set up with 64 levels in the vertical, which gradually increases from 75 m at the surface to a spacing of 400 m through the troposphere and a larger spacing of 1 km in the Newtonian damping region. The three-dimensional variables are saved every 1 minute for shallow convection, and every 10 minutes for deep convection for two consecutive days.
DOI: 10.15468/dl.aua66c
title: Occurrence Download

description: A dataset containing 46 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lasiognathus Regan, 1925"
 ]
}

 The dataset includes 46 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0078914-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.