cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.exuq2p
title: Occurrence Download

description: A dataset containing 5149 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Jurinea humilis"
 ]
}

 The dataset includes 5149 records from 148 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031269-250717081556266/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.29590625
title: Supporting information_Soil carbon isotopes in global coastal wetlands

description: In this study, we synthesized date from global coastal wetland studies to reveal this scientific issue. The results indicated that soil δ¹³C exhibits significant spatial heterogeneity across global coastal wetlands, with values ranging from -21.20‰ to -9.00‰ and decreasing with increasing latitude. Within the soil profile (0-100 cm), δ¹³C values increased with depth. Significant variations in soil δ¹³C values were also observed among different vegetation types, with seagrass meadows and mudflats exhibiting significantly higher δ¹³C values compared to salt marshes and mangroves (p &lt; 0.05). Climatic factors, such as mean annual precipitation (MAP) and mean annual temperature (MAT), were found to directly and indirectly regulate soil δ¹³C values. Specifically, MAP exhibited a significant negative correlation with soil δ¹³C values, while MAT showed a positive effect. Soil physicochemical properties were identified as the primary factors influencing soil δ¹³C values, with soil pH indirectly affecting the δ¹³C distribution by controlling clay content and total organic carbon (TOC). These results showed that the interactions of soil physicochemical properties, climate factors and vegetation types significantly influenced the spatial distribution of soil δ¹³C in coastal wetland ecosystems. This study will provide valuable scientific references for a deeper understanding of C biogeochemical cycles in coastal wetland ecosystems.
DOI: 10.6084/m9.figshare.29590625.v1
title: Supporting information_Soil carbon isotopes in global coastal wetlands

description: In this study, we synthesized date from global coastal wetland studies to reveal this scientific issue. The results indicated that soil δ¹³C exhibits significant spatial heterogeneity across global coastal wetlands, with values ranging from -21.20‰ to -9.00‰ and decreasing with increasing latitude. Within the soil profile (0-100 cm), δ¹³C values increased with depth. Significant variations in soil δ¹³C values were also observed among different vegetation types, with seagrass meadows and mudflats exhibiting significantly higher δ¹³C values compared to salt marshes and mangroves (p &lt; 0.05). Climatic factors, such as mean annual precipitation (MAP) and mean annual temperature (MAT), were found to directly and indirectly regulate soil δ¹³C values. Specifically, MAP exhibited a significant negative correlation with soil δ¹³C values, while MAT showed a positive effect. Soil physicochemical properties were identified as the primary factors influencing soil δ¹³C values, with soil pH indirectly affecting the δ¹³C distribution by controlling clay content and total organic carbon (TOC). These results showed that the interactions of soil physicochemical properties, climate factors and vegetation types significantly influenced the spatial distribution of soil δ¹³C in coastal wetland ecosystems. This study will provide valuable scientific references for a deeper understanding of C biogeochemical cycles in coastal wetland ecosystems.
DOI: 10.15468/dl.hsgxqw
title: Occurrence Download

description: A dataset containing 50443 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Calidris ferruginea)",
 "Country is one of (Afghanistan, Armenia, Azerbaijan, Bahrain, Bangladesh, Bhutan, Brunei Darussalam, Cambodia, China, Cyprus, Georgia, Hong Kong, India, Indonesia, Iran (Islamic Republic of), Iraq, Israel, Japan, Jordan, Kazakhstan, Korea (Democratic People’s Republic of), Korea, Republic of, Kuwait, Kyrgyzstan, Lao People’s Democratic Republic, Lebanon, Macao, Malaysia, Maldives, Mongolia, Myanmar, Nepal, Oman, Pakistan, Palestine, State of, Philippines, Qatar, Saudi Arabia, Singapore, Sri Lanka, Syrian Arab Republic, Tajikistan, Thailand, Timor-Leste, Türkiye, Turkmenistan, United Arab Emirates, Uzbekistan, Viet Nam, Yemen)"
 ]
}

 The dataset includes 50443 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031241-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mz45zc
title: Occurrence Download

description: A dataset containing 972 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hemerocallis lilioasphodelus",
 "Country is Sweden",
 "HasCoordinate is true"
 ]
}

 The dataset includes 972 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031271-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.c24rp7
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hemerocallis lilioasphodelus",
 "Country is Ukraine",
 "HasCoordinate is true"
 ]
}

 The dataset includes 4 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031272-250717081556266/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.29622217
title: Code S1 from Diffusion-controlled growth of a planar chemical garden wall before osmotic fracture

description: A sample MATLAB code for quantifying chemical garden growth in this work. A photograph obtained from the experiment is binarised. The area of the pattern at the middle of the image is computed as A(t). Treating the pattern to be circular, an equivalent radius of the pattern, r(t), can be obtained. Since the boundary between the precipitate layer and the inner solution containing undissolved pellet corresponds well to the perimeter of the original circular pellet, an equivalent width of the precipitate layer, w(t), can be calculated.
DOI: 10.6084/m9.figshare.29622217.v1
title: Code S1 from Diffusion-controlled growth of a planar chemical garden wall before osmotic fracture

description: A sample MATLAB code for quantifying chemical garden growth in this work. A photograph obtained from the experiment is binarised. The area of the pattern at the middle of the image is computed as A(t). Treating the pattern to be circular, an equivalent radius of the pattern, r(t), can be obtained. Since the boundary between the precipitate layer and the inner solution containing undissolved pellet corresponds well to the perimeter of the original circular pellet, an equivalent width of the precipitate layer, w(t), can be calculated.
DOI: 10.15468/dl.xa5kh9
title: Occurrence Download

description: A dataset containing 29318 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Circus cyaneus)",
 "Country is one of (Afghanistan, Armenia, Azerbaijan, Bahrain, Bangladesh, Bhutan, Brunei Darussalam, Cambodia, China, Cyprus, Georgia, Hong Kong, India, Indonesia, Iran (Islamic Republic of), Iraq, Israel, Japan, Jordan, Kazakhstan, Korea (Democratic People’s Republic of), Korea, Republic of, Kuwait, Kyrgyzstan, Lao People’s Democratic Republic, Lebanon, Macao, Malaysia, Maldives, Mongolia, Myanmar, Nepal, Oman, Pakistan, Palestine, State of, Philippines, Qatar, Saudi Arabia, Singapore, Sri Lanka, Syrian Arab Republic, Tajikistan, Thailand, Timor-Leste, Türkiye, Turkmenistan, United Arab Emirates, Uzbekistan, Viet Nam, Yemen)"
 ]
}

 The dataset includes 29318 records from 31 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031274-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57760/sciencedb.j00001.01567
title: An eddy covariance dataset of ecosystem carbon fluxes in a salt marsh in the Yellow River Delta (2012–2020)
title: 2012–2020年黄河三角洲盐沼湿地生态系统碳通量观测数据集

description: Salt marshes are a representative type of "blue carbon" ecosystem, playing a vital role in mitigating global climate change through their carbon sink capacity. Long-term and continuous carbon flux observations are crucial for accurately assessing the carbon sink potential of salt marshes and predicting their responses under climate change conditions. However, the current lack of long-term monitoring data for these ecosystems limits comprehensive investigations into their carbon sink function, highlighting the urgent need for high-quality, long-term datasets. Since 2011, the Yellow River Delta Ecological Research Station of Coastal Wetland, Chinese Academy of Sciences, has conducted continuous monitoring of carbon exchange processes in the salt marsh using the eddy covariance technique. Over the years, a substantial amount of high-quality carbon flux data has been collected. This dataset compiles observations from 2012 to 2020 and provides data products at both half-hourly and daily temporal resolutions. It includes net ecosystem exchange of CO2 (NEE), gross primary productivity (GPP), and ecosystem respiration (ER). The dataset offers reliable support for related research and contributes to a deeper understanding of carbon exchange processes in salt marshes.
description: Salt marshes are a representative type of "blue carbon" ecosystem, playing a vital role in mitigating global climate change through their carbon sink capacity. Long-term and continuous carbon flux observations are crucial for accurately assessing the carbon sink potential of salt marshes and predicting their responses under climate change conditions. However, the current lack of long-term monitoring data for these ecosystems limits comprehensive investigations into their carbon sink function, highlighting the urgent need for high-quality, long-term datasets. Since 2011, the Yellow River Delta Ecological Research Station of Coastal Wetland, Chinese Academy of Sciences, has conducted continuous monitoring of carbon exchange processes in the salt marsh using the eddy covariance technique. Over the years, a substantial amount of high-quality carbon flux data has been collected. This dataset compiles observations from 2012 to 2020 and provides data products at both half-hourly and daily temporal resolutions. It includes net ecosystem exchange of CO2 (NEE), gross primary productivity (GPP), and ecosystem respiration (ER). The dataset offers reliable support for related research and contributes to a deeper understanding of carbon exchange processes in salt marshes.
DOI: 10.15468/dl.e2jxvc
title: Occurrence Download

description: A dataset containing 33256 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Circus cyaneus)",
 "Country is one of (Anguilla, Antigua and Barbuda, Argentina, Aruba, Bahamas, Barbados, Belize, Bolivia (Plurinational State of), Bonaire, Sint Eustatius and Saba, Bouvet Island, Brazil, Cayman Islands, Chile, Colombia, Costa Rica, Cuba, Curaçao, Dominica, Dominican Republic, Ecuador, El Salvador, Falkland Islands (Malvinas), French Guiana, Grenada, Guadeloupe, Guatemala, Guyana, Haiti, Honduras, Jamaica, Martinique, Mexico, Montserrat, Nicaragua, Panama, Paraguay, Peru, Puerto Rico, Saint Barthélemy, Saint Kitts and Nevis, Saint Lucia, Saint Martin (French part), Saint Vincent and the Grenadines, Sint Maarten (Dutch part), South Georgia and the South Sandwich Islands, Suriname, Trinidad and Tobago, Turks and Caicos Islands, Uruguay, Venezuela (Bolivarian Republic of), Virgin Islands (British), Virgin Islands (U.S.))"
 ]
}

 The dataset includes 33256 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031275-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.t42w4y
title: Occurrence Download

description: A dataset containing 32977 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Mammalia",
 "Country is China",
 "HasCoordinate is true"
 ]
}

 The dataset includes 32977 records from 98 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031276-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.u8t95g
title: Occurrence Download

description: A dataset containing 10677 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Rumex obtusifolius",
 "Country is United States of America",
 "HasCoordinate is true"
 ]
}

 The dataset includes 10677 records from 151 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031277-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7uxsc5
title: Occurrence Download

description: A dataset containing 131489 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Olea europaea",
 "HasCoordinate is true",
 "Geometry POLYGON ((-17.66889 -35.11691, 51.34702 -35.11691, 51.34702 37.62, -17.66889 37.62, -17.66889 -35.11691))"
 ]
}

 The dataset includes 131489 records from 129 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031248-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2a23y5
title: Occurrence Download

description: A dataset containing 66 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hemerocallis lilioasphodelus",
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "HasCoordinate is true"
 ]
}

 The dataset includes 66 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031278-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yeuqfq
title: Occurrence Download

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

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031279-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fu5syy
title: Occurrence Download

description: A dataset containing 330707 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Calidris ferruginea)",
 "Country is one of (Åland Islands, Albania, Andorra, Austria, Belarus, Belgium, Bosnia and Herzegovina, Bulgaria, Croatia, Czechia, Denmark, Estonia, Faroe Islands, Finland, France, Germany, Gibraltar, Greece, Guernsey, Holy See, Hungary, Iceland, Ireland, Isle of Man, Italy, Jersey, Latvia, Liechtenstein, Lithuania, Luxembourg, Malta, Moldova, Republic of, Monaco, Montenegro, Netherlands, North Macedonia, Norway, Poland, Portugal, Romania, Russian Federation, San Marino, Serbia, Slovakia, Slovenia, Spain, Svalbard and Jan Mayen, Sweden, Switzerland, Ukraine, United Kingdom of Great Britain and Northern Ireland)"
 ]
}

 The dataset includes 330707 records from 417 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031251-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh0168904.10fu
title: SH0168904.10FU

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/sh0168905.10fu
title: SH0168905.10FU

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/sh0168906.10fu
title: SH0168906.10FU

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/sh0168907.10fu
title: SH0168907.10FU

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/sh0168908.10fu
title: SH0168908.10FU

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/sh0168909.10fu
title: SH0168909.10FU

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.