cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25921/e18c-h512
title: NOAA/WDS Paleoclimatology - Iniguez fire data from Catalina Butterfly Peak Plot 26 - IMPD USCBP_26

description: Fire histories contribute important information to contemporary fire planning, however, our knowledge is not comprehensive geographically. We evaluated the influence of topography on fire history patterns in two contrasting landscapes within the Santa Catalina Mountains of southeastern Arizona. Multiple fire-scarred trees from randomly selected 2-ha plots were used to develop plot composite mean fire intervals (PCMFIs) within the Butterfly Peak (BP) and Rose Canyon (RC) landscapes. BP is dominated by steep, northerly aspects and presence of potential fire spread barriers (exposed rock bluffs and scree slopes). RC is dominated by more gentle and southerly aspects with relatively few fire barriers. Within each landscape, PCMFIs did not differ significantly between aspect classes from A.D. 1748 to 1910 (BP: p = 0.73 and RC: p = 0.57). Pooled PCMFIs in the gentler RC landscape were, however, significantly shorter (p < 0.001) than in the steeper BP landscape. The frequency of relatively widespread fires (i.e., number of fire years when ≥2 plots scarred) was similar between landscapes, but fires in the gentler RC landscape were significantly larger (p = 0.033). The higher frequency of large fires (i.e., fires that burned >75% of the landscape) in RC resulted in more area burned over time and shorter fire intervals at individual plots. Conversely, smaller fires in the dissected BP landscape resulted in less area burned and longer periods between fires at individual plots. The different topographies in the two landscapes likely result in different wind intensities, fuel moistures, and fuel/vegetation types—and consequently, different historical fire spread patterns. Our conclusion is that fire history patterns are not influenced primarily by stand-scale topography, but rather by the topographic characteristics of the broader, surrounding landscape.
description: 
This dataset was contributed as part of the North American Tree-ring Fire Scar Synthesis (NAFSS) project (https://www.ncei.noaa.gov/access/paleo-search/study/34853). Data were contributed to the project from the original data generators.

Sample Storage Location: Laboratory of Tree-Ring, University of Arizona
Dating Method: Dated
Related ITRDB_Chronology: Not Applicable

Fire scar data from this site are available in FHX2 format at:
  https://www.ncei.noaa.gov/pub/data/paleo/firehistory/firescar/northamerica/uscbp_26.fhx
along with associated metadata at:
  https://www.ncei.noaa.gov/pub/data/paleo/firehistory/firescar/northamerica/uscbp_26-noaa.txt
DOI: 10.25921/etrp-p863
title: NOAA/WDS Paleoclimatology - Iniguez fire data from Catalina Butterfly Peak Plot 28 - IMPD USCBP_28

description: Fire histories contribute important information to contemporary fire planning, however, our knowledge is not comprehensive geographically. We evaluated the influence of topography on fire history patterns in two contrasting landscapes within the Santa Catalina Mountains of southeastern Arizona. Multiple fire-scarred trees from randomly selected 2-ha plots were used to develop plot composite mean fire intervals (PCMFIs) within the Butterfly Peak (BP) and Rose Canyon (RC) landscapes. BP is dominated by steep, northerly aspects and presence of potential fire spread barriers (exposed rock bluffs and scree slopes). RC is dominated by more gentle and southerly aspects with relatively few fire barriers. Within each landscape, PCMFIs did not differ significantly between aspect classes from A.D. 1748 to 1910 (BP: p = 0.73 and RC: p = 0.57). Pooled PCMFIs in the gentler RC landscape were, however, significantly shorter (p < 0.001) than in the steeper BP landscape. The frequency of relatively widespread fires (i.e., number of fire years when ≥2 plots scarred) was similar between landscapes, but fires in the gentler RC landscape were significantly larger (p = 0.033). The higher frequency of large fires (i.e., fires that burned >75% of the landscape) in RC resulted in more area burned over time and shorter fire intervals at individual plots. Conversely, smaller fires in the dissected BP landscape resulted in less area burned and longer periods between fires at individual plots. The different topographies in the two landscapes likely result in different wind intensities, fuel moistures, and fuel/vegetation types—and consequently, different historical fire spread patterns. Our conclusion is that fire history patterns are not influenced primarily by stand-scale topography, but rather by the topographic characteristics of the broader, surrounding landscape.
description: 
This dataset was contributed as part of the North American Tree-ring Fire Scar Synthesis (NAFSS) project (https://www.ncei.noaa.gov/access/paleo-search/study/34853). Data were contributed to the project from the original data generators.

Sample Storage Location: Laboratory of Tree-Ring, University of Arizona
Dating Method: Dated
Related ITRDB_Chronology: Not Applicable

Fire scar data from this site are available in FHX2 format at:
  https://www.ncei.noaa.gov/pub/data/paleo/firehistory/firescar/northamerica/uscbp_28.fhx
along with associated metadata at:
  https://www.ncei.noaa.gov/pub/data/paleo/firehistory/firescar/northamerica/uscbp_28-noaa.txt
DOI: 10.15468/dl.iufeyi
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 32 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012412-190415153152247/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.trf28c
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Syrphidae)",
 "BasisOfRecord is one of (Specimen, Human Observation)",
 "StateProvince is USA.5_1",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0125152-220831081235567/datasets/export for details.
DOI: 10.15468/dl.2qzwbs
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 8 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007074-171124123535762/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5bcnqm
title: Occurrence Download

description: A dataset listing the 1 species recorded in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation, Material sample, Material citation, Specimen, Occurrence evidence)",
 "Country is Greece",
 "OccurrenceStatus is Present",
 "TaxonKey is Alopochen aegyptiaca (Linnaeus, 1766)",
 "Year 1990-2022"
 ]
}

 The dataset's 1 records were derived from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0235444-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.oxznwn
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 32 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012227-190415153152247/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vrwovj
title: Occurrence Download

description: A dataset containing 1941748277 species occurrences available in GBIF matching the query:
{ }

 The dataset includes 1941748277 records from 18403 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004926-171124123535762/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.f6q92w
title: Occurrence Download

description: A dataset containing 2593837 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is 2023 Contributions of Plant Specimen Data inside China"
 ]
}

 The dataset includes 2593837 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0051517-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.s6f4j5
title: Occurrence Download

description: A dataset containing 57873 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Bidens pilosa L."
 ]
}

 The dataset includes 57873 records from 956 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0051520-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tu2wjc
title: Occurrence Download

description: A dataset containing 1995 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "TaxonKey is Hedylidae"
 ]
}

 The dataset includes 1995 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0051522-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.urnsyf
title: Occurrence Download

description: A dataset containing 36 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Coenocyathus anthophyllites Milne Edwards & Haime, 1848"
 ]
}

 The dataset includes 36 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0051523-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.h9rj57
title: Occurrence Download

description: A dataset containing 11383 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Tithonia diversifolia (Hemsl.) A.Gray"
 ]
}

 The dataset includes 11383 records from 408 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0051525-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vrpn2t
title: Occurrence Download

description: A dataset containing 30960 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Parthenium hysterophorus L."
 ]
}

 The dataset includes 30960 records from 448 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0051524-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh1187531.10fu
title: SH1187531.10FU

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/sh1187532.10fu
title: SH1187532.10FU

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/sh1187533.10fu
title: SH1187533.10FU

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/sh1187536.10fu
title: SH1187536.10FU

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: 10.3886/e243174
title: College of Nursing Sciences, Amachara, Abia State 2026/2027 Admission Form is Out Call ☎️(08039478772) DR MERCY ☎️(+23408039478772), Midwifery Form, Post basic nursing form ,Post basic midwifery Form

description: College of Nursing Sciences, Amachara, Abia State 2026/2027 Admission Form is Out Call ☎️(08039478772) DR MERCY ☎️(+23408039478772), Midwifery Form, Post basic nursing form ,Post basic midwifery Form, Transfer form are all out Call on ☎️(08039478772) on how to purchase the form and register online, For Admission Process on how to be admitted and mode of payment of School Fee And Acceptances Fee Contact Office of the registrar on ☎️(+23408039478772) more Inquiry On AND ADMISSION ASSISTANCE CALL DR. MRS MERCY ON ☎️(08039478772)
DOI: 10.15156/bio/sh1187539.10fu
title: SH1187539.10FU

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/sh1187541.10fu
title: SH1187541.10FU

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/sh1187543.10fu
title: SH1187543.10FU

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/sh1187544.10fu
title: SH1187544.10FU

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/sh1187546.10fu
title: SH1187546.10FU

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/sh1187547.10fu
title: SH1187547.10FU

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.