cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.p6zx6q
title: Occurrence Download

description: A dataset containing 843 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((-72.908 5.016153, -72.978531 5.010583, -73.047321 4.994009, -73.112675 4.966842, -73.17298 4.92975, -73.22675 4.883649, -73.272661 4.829675, -73.309583 4.76916, -73.336608 4.703594, -73.35307299999999 4.634594, -73.358577 4.563859, -73.352986 4.49313, -73.33644200000001 4.424149, -73.309355 4.358614, -73.27239299999999 4.298138, -73.226468 4.244207, -73.172712 4.198149, -73.112447 4.161096, -73.047156 4.133959, -72.978444 4.117405, -72.908 4.111841, -72.83755600000001 4.117405, -72.768844 4.133959, -72.703553 4.161096, -72.643288 4.198149, -72.58953200000001 4.244207, -72.54360699999999 4.298138, -72.50664500000001 4.358614, -72.479558 4.424149, -72.463014 4.49313, -72.45742300000001 4.563859, -72.46292699999999 4.634594, -72.479392 4.703594, -72.506417 4.76916, -72.543339 4.829675, -72.58925000000001 4.883649, -72.64302000000001 4.92975, -72.70332500000001 4.966842, -72.76867900000001 4.994009, -72.837469 5.010583, -72.908 5.016153))"},{"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 843 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003068-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.31116280
title: Dataset for SDG 3 Questionnaire Development

description: This dataset was used for the development of SDG 3 questionnaire.
DOI: 10.6084/m9.figshare.31116280.v1
title: Dataset for SDG 3 Questionnaire Development

description: This dataset was used for the development of SDG 3 questionnaire.
DOI: 10.15468/dl.zmhvf6
title: Occurrence Download

description: A dataset containing 7768830 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Vespertilionidae"
 ]
}

 The dataset includes 7768830 records from 6926 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003007-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.60503/d3/zgigv0
title: Blue Chip Economic Indicators

description: Forecasts from 50-plus economists employed by US manufacturers, banks, insurance companies, and brokerage firms, plus an average or consensus, of their forecasts. Data is historical, annual and quarterly from 1976. Access the data by visiting: Blue Chip Economic Indicators
DOI: 10.5281/zenodo.15577849
title: DNL343v2
DOI: 10.5281/zenodo.15577850
title: DNL343v2
DOI: 10.15468/dl.x7bkad
title: Occurrence Download

description: A dataset containing 43622 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Nocardioides Prauser, 1976"
 ]
}

 The dataset includes 43622 records from 475 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015690-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ub8ss9
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Deutzia scabra",
 "Country is Georgia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049193-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3w4wg9
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Deutzia scabra",
 "Country is India",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049194-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.27969351.v4
title: The Role of Threatened Species in Food Web Structure Across Europe

description: Dataset for the manuscript entitled "The Role of Threatened Species in Food Web Structure Across Europe".<br><b>Aim</b>Assess the relevance of threatened and non-threatened species to local food web network structures across Europe.<b>Location</b>Europe (extending eastward to include Turkey, Georgia, Armenia, Azerbaijan and Russia west of the Urals).<b>Time-period</b>We derived our interactions from a metaweb of potential tetrapod interactions across Europe, using data spanning the past 50 years.<b>Major taxa studied</b>Terrestrial tetrapods (birds, mammals, amphibians and reptiles).<b>Methods</b>We used a dataset of local European potential food webs, obtained from Galiana et al. (2021). The local food webs were inferred to Europe by combining a species-level metaweb of trophic interactions of European tetrapods, the Tetra-EU 1.0 (Maiorano et al. 2020), with the distribution of these species (Maiorano et al. 2013).Next, we added information about the threat statuses across Europe and measured the importance of species through node-level network structural metrics, including in-degree (number of prey species), out-degree (number of predator species), trophic level, betweenness centrality (how often a species lies on the shortest paths between all other species), closeness centrality (how close to all other species is the focal species), and the integrated Value of Influence (a species' overall impact on a food web, combining both direct and indirect effects).<b>Results</b>While threatened species occasionally hold key roles in specific regions (e.g. the Iberian Peninsula), non-threatened species often demonstrate a higher Integrated Value of Influence and betweenness centrality, underscoring their significant contributions to network integrity.<b>Main conclusions</b>We highlight the importance of integrating threatened and non-threatened species into conservation strategies, recognising their complementary roles in maintaining food web stability at multiple spatial scales.
DOI: 10.15468/dl.n9dycm
title: Occurrence Download

description: A dataset containing 17719 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Cabomba caroliniana A.Gray, Lagarosiphon major (Ridl.) Moss, Myriophyllum heterophyllum Michx., Salvinia minima Baker, Salvinia ×molesta D.S.Mitch.)",
 "BasisOfRecord is one of (Human Observation)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 17719 records from 293 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013014-250415084134356/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25948/d1j3-aw85
title: HEVAE Vegetation Groundwater Dependent Ecosystems Value - Hawkesbury Nepean

description: NSW DoI Water has adopted the Guidelines for Identifying High Ecological Value Aquatic Ecosystems (HEVAE) framework developed by the Australian Commonwealth Government. In the current assessment for NSW, the HEVAE consists of four key criteria which include diversity, distinctiveness, naturalness and vital habitat. Therefore, the HEVAE vegetation GDE value layer is a combination of four individual criterion layers. The final or overall HEVAE score was determined for vegetation PCT polygons which has a high probability of being groundwater dependent. This was calculated by adding together the final scores for each criterion (Naturalness, Diversity, Distinctiveness and Vital Habitat). This score was then standardised by dividing by the maximum combined HEVAE score for a whole catchment’s vegetation GDE polygons to provide an even spread of score outcomes between 0 (lowest) and 1 (highest). For ease of data modelling and management, the dataset was divided into the following catchment management areas; Border Rivers-Gwydir, Central Tablelands, Central West, Hawkesbury-Nepean, Hunter-Central Rivers, Lachlan, Lower Murray Darling, Murray, Murrumbidgee, Namoi, Northern Rivers, Southern Rivers, Southern Tablelands, Sydney Metro and Western Division (subdivided further into the IBRA Sub regions). *Currently only the MDBA and Hunter Central River Catchments have been completed.
DOI: 10.15468/dl.u4qyxe
title: Occurrence Download

description: A dataset containing 368 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-111.47658 25.34857,-106.1901 25.34857,-106.1901 31.34918,-111.47658 31.34918,-111.47658 25.34857))",
 "HasGeospatialIssue is false",
 "TaxonKey is Coleonyx"
 ]
}

 The dataset includes 368 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029898-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25948/ryyh-0r48
title: HEVAE Vegetation Groundwater Dependent Ecosystems Value - Namoi

description: NSW DoI Water has adopted the Guidelines for Identifying High Ecological Value Aquatic Ecosystems (HEVAE) framework developed by the Australian Commonwealth Government. In the current assessment for NSW, the HEVAE consists of four key criteria which include diversity, distinctiveness, naturalness and vital habitat. Therefore, the HEVAE vegetation GDE value layer is a combination of four individual criterion layers. The final or overall HEVAE score was determined for vegetation PCT polygons which has a high probability of being groundwater dependent. This was calculated by adding together the final scores for each criterion (Naturalness, Diversity, Distinctiveness and Vital Habitat). This score was then standardised by dividing by the maximum combined HEVAE score for a whole catchment’s vegetation GDE polygons to provide an even spread of score outcomes between 0 (lowest) and 1 (highest). For ease of data modelling and management, the dataset was divided into the following catchment management areas; Border Rivers-Gwydir, Central Tablelands, Central West, Hawkesbury-Nepean, Hunter-Central Rivers, Lachlan, Lower Murray Darling, Murray, Murrumbidgee, Namoi, Northern Rivers, Southern Rivers, Southern Tablelands, Sydney Metro and Western Division (MDB and far west subdivided further into the IBRA Sub regions).
DOI: 10.25948/41t1-kv23
title: HEVAE Vegetation Groundwater Dependent Ecosystems Value - Lachlan

description: NSW DoI Water has adopted the Guidelines for Identifying High Ecological Value Aquatic Ecosystems (HEVAE) framework developed by the Australian Commonwealth Government. In the current assessment for NSW, the HEVAE consists of four key criteria which include diversity, distinctiveness, naturalness and vital habitat. Therefore, the HEVAE vegetation GDE value layer is a combination of four individual criterion layers. The final or overall HEVAE score was determined for vegetation PCT polygons which has a high probability of being groundwater dependent. This was calculated by adding together the final scores for each criterion (Naturalness, Diversity, Distinctiveness and Vital Habitat). This score was then standardised by dividing by the maximum combined HEVAE score for a whole catchment’s vegetation GDE polygons to provide an even spread of score outcomes between 0 (lowest) and 1 (highest). For ease of data modelling and management, the dataset was divided into the following catchment management areas; Border Rivers-Gwydir, Central Tablelands, Central West, Hawkesbury-Nepean, Hunter-Central Rivers, Lachlan, Lower Murray Darling, Murray, Murrumbidgee, Namoi, Northern Rivers, Southern Rivers, Southern Tablelands, Sydney Metro and Western Division (MDB and far west subdivided further into the IBRA Sub regions).
DOI: 10.25948/zvpw-1f92
title: HEVAE Vegetation Groundwater Dependent Ecosystems Value - Macquarie / Castlereagh

description: NSW DoI Water has adopted the Guidelines for Identifying High Ecological Value Aquatic Ecosystems (HEVAE) framework developed by the Australian Commonwealth Government. In the current assessment for NSW, the HEVAE consists of four key criteria which include diversity, distinctiveness, naturalness and vital habitat. Therefore, the HEVAE vegetation GDE value layer is a combination of four individual criterion layers. The final or overall HEVAE score was determined for vegetation PCT polygons which has a high probability of being groundwater dependent. This was calculated by adding together the final scores for each criterion (Naturalness, Diversity, Distinctiveness and Vital Habitat). This score was then standardised by dividing by the maximum combined HEVAE score for a whole catchment’s vegetation GDE polygons to provide an even spread of score outcomes between 0 (lowest) and 1 (highest). For ease of data modelling and management, the dataset was divided into the following catchment management areas; Border Rivers-Gwydir, Central Tablelands, Central West, Hawkesbury-Nepean, Hunter-Central Rivers, Lachlan, Lower Murray Darling, Murray, Murrumbidgee, Namoi, Northern Rivers, Southern Rivers, Southern Tablelands, Sydney Metro and Western Division (MDB and far west subdivided further into the IBRA Sub regions).
DOI: 10.25948/fn5c-1853
title: HEVAE Vegetation Groundwater Dependent Ecosystems Value - Murray

description: NSW DoI Water has adopted the Guidelines for Identifying High Ecological Value Aquatic Ecosystems (HEVAE) framework developed by the Australian Commonwealth Government. In the current assessment for NSW, the HEVAE consists of four key criteria which include diversity, distinctiveness, naturalness and vital habitat. Therefore, the HEVAE vegetation GDE value layer is a combination of four individual criterion layers. The final or overall HEVAE score was determined for vegetation PCT polygons which has a high probability of being groundwater dependent. This was calculated by adding together the final scores for each criterion (Naturalness, Diversity, Distinctiveness and Vital Habitat). This score was then standardised by dividing by the maximum combined HEVAE score for a whole catchment’s vegetation GDE polygons to provide an even spread of score outcomes between 0 (lowest) and 1 (highest). For ease of data modelling and management, the dataset was divided into the following catchment management areas; Border Rivers-Gwydir, Central Tablelands, Central West, Hawkesbury-Nepean, Hunter-Central Rivers, Lachlan, Lower Murray Darling, Murray, Murrumbidgee, Namoi, Northern Rivers, Southern Rivers, Southern Tablelands, Sydney Metro and Western Division (MDB and far west subdivided further into the IBRA Sub regions).
DOI: 10.25345/c57m04d1d
title: MassIVE MSV000099881 - Neiswender eLife_2025 protoemics dataset
title: Interactome of BICD2 wild-type and SMALED mutants N188T, R694C and R747C
DOI: 10.15468/dl.z23ery
title: Occurrence Download

description: A dataset containing 131723 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Batrachoidiformes"
 ]
}

 The dataset includes 131723 records from 337 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029864-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.75rr27
title: Occurrence Download

description: A dataset containing 31 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Heliaster canopus"
 ]
}

 The dataset includes 31 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029899-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sk6sev
title: Occurrence Download

description: A dataset containing 144466 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Kazakhstan",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 144466 records from 171 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029869-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25948/1xm6-hz02
title: Spatial Layer of Probable Vegetation Groundwater Dependent Ecosystems in NSW

description: The purpose of this project is to create a data set that identifies vegetation communities that have a probability of being a groundwater dependent ecosystem within NSW. Probability categories are high, medium, low and non GDE. The data is required to meet legislative requirements for water sharing plans and water resource plans. This is a base data layer that can be used to aid research projects, assessment of state significant development applications, licence applications and compliance issues. For ease of data modelling and management, the dataset was divided into the following catchment management areas; Border Rivers-Gwydir, Central Tablelands, Central West, Hawkesbury-Nepean, Hunter-Central Rivers, Lachlan, Lower Murray Darling, Murray-Murrumbidgee, Namoi, Northern Rivers, Southern Rivers, Sydney Metro and Western Division (Far West and Western MDBA). 

Please note: Groundwater Dependent Ecosystem mapping used the NSW DPE Environment and Heritage vegetation mapping product as the underlying data source. NSW DPE Water activities such as bore applications that are examined at a site specific scale may need subsequent verification to confirm.

Method report is available via the DoI Water website - https://water.dpie.nsw.gov.au/__data/assets/pdf_file/0010/151894/High-Probability-GDE-method-report.pdf
DOI: 10.60521/332488
title: ROV-mounted high-resolution laser scan data acquired at vertical deep-sea habitats, Galapagos Islands, 2023 (FKt230918)

description: ROV SuBastian-mounted laser scanner data for high-resolution mapping of steep, vertical and overhanging cold water coral reefs in the Galápagos, Ecuador, was collected during Falkor (too) cruise FKt230918 in 2023. The Voyis Insight Micro laser scanner system was mounted on the vehicle porch using an adjustable bracket to set the pitch during three ROV SuBastian dives (S0578, S0584, S0597). Mapping was done by vertically moving the vehicle from the base of a cliff to the top, then shifting slightly over for another line. Navigation data from the SprintNav system were combined in the Voyis ViewLS software to provide georeferenced 3D point clouds data. All mounting offsets are outlined in the associated cruise report (https://doi.org/10.48336/7sjp-t131), but this represents the data prior to the inclusion of patch test offsets. The data files are in ASCII XYZ comma-separated format with the following six columns: Column 1: Scalar Field 1, ZDA timestamp. Column 2: X Position Value (relative). Column 3: Y Position Value (relative). Column 4: Z Position Value (depth). Column 5: Scalar Field 2, Intensity. Column 6: Scalar Field 3, Quality. Funding for the project was provided through Schmidt Ocean Institute; processing of this data was supported through a Canada Research Chair in Ocean Mapping award.
DOI: 10.15468/dl.3tzj59
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Dicranostigma iliensis"
 ]
}

 The dataset includes 4 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029901-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cbqu4z
title: Occurrence Download

description: A dataset containing 17478 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Oman",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 17478 records from 71 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029902-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tmtcd6
title: Occurrence Download

description: A dataset containing 75 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Chimonobambusa utilis"
 ]
}

 The dataset includes 75 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029903-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cr8exb
title: Occurrence Download

description: A dataset containing 168 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((125.8697 -4.0839,131.06453 -4.0839,130.99053 -2.39261,125.83261 -2.62523,125.8697 -4.0839))",
 "HasGeospatialIssue is false",
 "IucnRedListCategory is CR",
 "OccurrenceStatus is Present",
 "Year 2015-2025"
 ]
}

 The dataset includes 168 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029904-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25955/29369264
title: Data analyses Files for Quantitative Study

description: Excel sheet and SPSS file from Quantitative Study. Please contact me for further access at:s.alikhan@federation.edu.au, shariqalikhan1@gmail.com
DOI: 10.25955/29369264.v1
title: Data analyses Files for Quantitative Study

description: Excel sheet and SPSS file from Quantitative Study. Please contact me for further access at:s.alikhan@federation.edu.au, shariqalikhan1@gmail.com
DOI: 10.5281/zenodo.17585751
title: Water and Carbon Use Efficiency and Bioclimatic Zone Distribution in Cross-Border Watersheds of Northeast Asia

description: The transboundary watersheds of Northeast Asia form a connecting unit for ecological and economic activities among China, Russia, North Korea, and Mongolia. In recent years, issues such as water scarcity and fluctuating carbon sink capacity have become increasingly prominent in these basins. This study combines MODIS remote sensing datasets with environmental data to analyze the spatial distribution patterns of water and carbon use efficiency in 2020. The Structure K-means clustering algorithm was employed to delineate bioclimatic zones. The coordinate system for this study's data is WGS_1984_UTM_Zone_52N, with a spatial resolution of 1 km.
DOI: 10.5281/zenodo.17585750
title: Water and Carbon Use Efficiency and Bioclimatic Zone Distribution in Cross-Border Watersheds of Northeast Asia

description: The transboundary watersheds of Northeast Asia form a connecting unit for ecological and economic activities among China, Russia, North Korea, and Mongolia. In recent years, issues such as water scarcity and fluctuating carbon sink capacity have become increasingly prominent in these basins. This study combines MODIS remote sensing datasets with environmental data to analyze the spatial distribution patterns of water and carbon use efficiency in 2020. The Structure K-means clustering algorithm was employed to delineate bioclimatic zones. The coordinate system for this study's data is WGS_1984_UTM_Zone_52N, with a spatial resolution of 1 km.