cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.aa874v
title: Occurrence Download

description: A dataset containing 81908 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Dataset of occurrence and incidence of pine processionary moth in Andalusia (South Spain)"
 ]
}

 The dataset includes 81908 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0268980-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.utykqj
title: Occurrence Download

description: A dataset containing 281 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Australia)",
 "BasisOfRecord is one of (Specimen)",
 "Year is greater than or equal to 1900",
 "TaxonKey is Nassella trichotoma (Nees) Hack. & Arechav.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 281 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0435708-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rmde4f
title: Occurrence Download

description: A dataset containing 18600557 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is one of (Mexico, United States of America, Canada)",
 "DatasetKey is one of (DFO Pacific: Herring Biosample Database, Maritimes Summer Research Vessel Surveys, Multistate Aquatic Resources Information System - MARIS - Fish, Maritimes Spring Research Vessel Surveys, SEFSC CAGES Alabama Fish Length Data with CPUE, USGS GAP - Alaska - Vertebrates - 1867-2009, ECNASAP - East Coast North America Strategic Assessment, iNaturalist Research-grade Observations)",
 "Geometry POLYGON((-151.79849 65.01744,-200.59087 39.44024,-172.70951 -5.02767,-106.87853 -5.02767,-46.46893 20.09844,-30.97928 50.36213,-72.02684 65.98087,-123.91714 67.50925,-151.79849 65.01744))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Chordata"
 ]
}

 The dataset includes 18600557 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015886-230828120925497/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.adpe8h
title: Occurrence Download

description: A dataset listing the 1 species recorded in GBIF matching the query:
{
 "TaxonKey" : [
 "is Litopenaeus occidentalis (Streets, 1871)"
 ]
}

 The dataset's 1 records were derived from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0267731-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kg9eat
title: Occurrence Download

description: A dataset containing 82 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Musonycteris harrisoni Schaldach & McLaughlin, 1960"
 ]
}

 The dataset includes 82 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002572-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.upgny3
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Thalamita platypedis Dai & Chen, 1986",
 "HasCoordinate is true",
 "Year is greater than or equal to 1970",
 "HasGeospatialIssue is false",
 "Geometry POLYGON((108.080642 16.439832, 121.84182 16.084389, 123.975906 41.313386, 108.669355 40.867975, 108.080642 16.439832))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012983-230828120925497/datasets/export for details.
DOI: 10.15468/dl.p7kghy
title: Occurrence Download

description: A dataset containing 11981 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Crypsirina temia (Daudin, 1800)"
 ]
}

 The dataset includes 11981 records from 50 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0384594-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.n6k32y
title: Occurrence Download

description: A dataset containing 1233027 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Botanical Database of Southern Africa (BODATSA): Botanical Collections"
 ]
}

 The dataset includes 1233027 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002114-230918134249559/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4j368t
title: Occurrence Download

description: A dataset containing 169 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Micrurus nigrocinctus (Girard, 1854)"
 ]
}

 The dataset includes 169 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002547-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5nzw7q
title: Occurrence Download

description: A dataset containing 86911 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Aythya nyroca (Güldenstädt, 1770)"
 ]
}

 The dataset includes 86911 records from 310 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0426707-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jgjtkn
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Leskea rotulata Hedw."
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002115-230918134249559/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.48wmer
title: Occurrence Download

description: A dataset containing 1285014 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Setophaga magnolia (A.Wilson, 1811)"
 ]
}

 The dataset includes 1285014 records from 183 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002581-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5j6xw3
title: Occurrence Download

description: A dataset containing 23522041 species occurrences available in GBIF matching the query:
{
 "or" : [
 "PublishingCountry is Colombia",
 {
 "and" : [
 "Country is Colombia",
 {
 "not" : {
 "Issue" : [
 "is Country coordinate mismatch"
 ]
 }
 }
 ]
 }
 ]
}

 The dataset includes 23522041 records from 3766 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010787-220831081235567/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.22094565
title: Heterogeneous mass balance of selected Glaciers in the Hindu Kush, Karakoram, and Himalaya between 2000 and 2018

description: Glaciers in the Hindu Kush-Karakoram-Himalayas (HKH) are a major source of freshwater in the agriculture-dependent economy of Pakistan. In recent decades, mountain glaciers have been threatened by global warming. In this study, we estimated the Equilibrium Line Altitude (ELA) and geodetic mass balance of fifteen representative glaciers from Hunza (Karakoram), Chitral (Hindu Kush), and Astore (Himalaya) using Landsat satellite images and Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) DEMs between 2000 and 2018. The climatic trends (temperature and precipitation) in the 19 years (1995–2013) time series of the three regions were assessed using the non-parametric Mann-Kendall test and Sen’s Slope. The ELA of the observed glaciers except for two Atrak (Chitral) and Gulkin (Hunza) is shifted upward, while the mass balance indicates a heterogeneous pattern ranging from −0.23 ± 0.05 to −0.01 ± 0.015 m w.e a<sup>−1</sup>, −0.13 ± 0.05 to+0.17 ± 0.11 m w.e a<sup>−1</sup> and −0.03 ± 0.02 to+0.23 ± 0.09 m w.e a<sup>−1</sup> in Chitral, Hunza, and Astore basin, respectively. A significant or slight increasing or decreasing trend was found in the mean annual temperature, mean total precipitation, and mean discharge of the studied basins. This study will be a good contribution to understanding snow and glacier dynamics in HKH, the factors that influence them, and their interaction with the environment.
DOI: 10.6084/m9.figshare.22094565.v1
title: Heterogeneous mass balance of selected Glaciers in the Hindu Kush, Karakoram, and Himalaya between 2000 and 2018

description: Glaciers in the Hindu Kush-Karakoram-Himalayas (HKH) are a major source of freshwater in the agriculture-dependent economy of Pakistan. In recent decades, mountain glaciers have been threatened by global warming. In this study, we estimated the Equilibrium Line Altitude (ELA) and geodetic mass balance of fifteen representative glaciers from Hunza (Karakoram), Chitral (Hindu Kush), and Astore (Himalaya) using Landsat satellite images and Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) DEMs between 2000 and 2018. The climatic trends (temperature and precipitation) in the 19 years (1995–2013) time series of the three regions were assessed using the non-parametric Mann-Kendall test and Sen’s Slope. The ELA of the observed glaciers except for two Atrak (Chitral) and Gulkin (Hunza) is shifted upward, while the mass balance indicates a heterogeneous pattern ranging from −0.23 ± 0.05 to −0.01 ± 0.015 m w.e a<sup>−1</sup>, −0.13 ± 0.05 to+0.17 ± 0.11 m w.e a<sup>−1</sup> and −0.03 ± 0.02 to+0.23 ± 0.09 m w.e a<sup>−1</sup> in Chitral, Hunza, and Astore basin, respectively. A significant or slight increasing or decreasing trend was found in the mean annual temperature, mean total precipitation, and mean discharge of the studied basins. This study will be a good contribution to understanding snow and glacier dynamics in HKH, the factors that influence them, and their interaction with the environment.
DOI: 10.6084/m9.figshare.22348807
title: Assessing the effectiveness of UAV data for accurate coastal dune habitat mapping

description: Coastal dunes are considered some of the most threatened and vulnerable habitats in the European Union. Mapping the spatial distribution of these habitats is an essential task for their conservation. Advances in Unoccupied Aerial Vehicles (UAVs) facilitate the flexible acquisition of high-resolution imagery for identifying detailed spatial distributions of habitats within dune systems. This study aimed to assess the effectiveness of UAV remote sensing for mapping these habitat types. Specifically, we determined the impact of temporally acquired UAV-derived spectral and topographic information on classification accuracy. The work combined the multi-temporal UAV imagery with field observation data and used the Random Forest machine learning algorithm to classify dune habitats. Results showed that using multi-temporal UAV imagery increased classification accuracy compared to using uni-temporal UAV imagery (92.37% vs. 84.09%, respectively). Also, including topographic information consistently improved accuracy, regardless of the number of image sets used (the highest accuracy increased from 84.81% to 92.57% for a uni-temporal model). Temporal analyses showed that the data acquired in the middle period of the growing season were better than those acquired in the early or late periods. The methodology presented here demonstrates the potential of using UAV data for detailed mapping and monitoring of habitat types.
DOI: 10.6084/m9.figshare.22348807.v1
title: Assessing the effectiveness of UAV data for accurate coastal dune habitat mapping

description: Coastal dunes are considered some of the most threatened and vulnerable habitats in the European Union. Mapping the spatial distribution of these habitats is an essential task for their conservation. Advances in Unoccupied Aerial Vehicles (UAVs) facilitate the flexible acquisition of high-resolution imagery for identifying detailed spatial distributions of habitats within dune systems. This study aimed to assess the effectiveness of UAV remote sensing for mapping these habitat types. Specifically, we determined the impact of temporally acquired UAV-derived spectral and topographic information on classification accuracy. The work combined the multi-temporal UAV imagery with field observation data and used the Random Forest machine learning algorithm to classify dune habitats. Results showed that using multi-temporal UAV imagery increased classification accuracy compared to using uni-temporal UAV imagery (92.37% vs. 84.09%, respectively). Also, including topographic information consistently improved accuracy, regardless of the number of image sets used (the highest accuracy increased from 84.81% to 92.57% for a uni-temporal model). Temporal analyses showed that the data acquired in the middle period of the growing season were better than those acquired in the early or late periods. The methodology presented here demonstrates the potential of using UAV data for detailed mapping and monitoring of habitat types.
DOI: 10.6084/m9.figshare.24517336
title: Modelling in-ground wood decay using time-series retrievals from the 5<sup>th</sup> European climate reanalysis (ERA5-Land)

description: This article presents models to predict the time until mechanical failure of in-ground wooden test specimens resulting from fungal decay. Historical records of decay ratings were modelled by remotely sensed data from ERA5-Land. In total, 2,570 test specimens of 16 different wood species were exposed at 21 different test sites, representing three continents and climatic conditions from sub-polar to tropical, spanning a period from 1980 until 2022. To obtain specimen decay ratings over their exposure time, inspections were conducted in mostly annual and sometimes bi-annual intervals. For each specimen’s exposure period, a laboratory developed dose–response model was populated using remotely sensed soil moisture and temperature data retrieved from ERA5-Land. Wood specimens were grouped according to natural durability rankings to reduce the variability of in-ground wood decay rate between wood species. Non-linear, sigmoid-shaped models were then constructed to describe wood decay progression as a function of daily accumulated exposure to soil moisture and temperature conditions (dose). Dose, a mechanistic weighting of daily exposure conditions over time, generally performed better than exposure time alone as a predictor of in-ground wood decay progression. The open-access availability of remotely sensed soil-state data in combination with wood specimen data proved promising for in-ground wood decay predictions.
DOI: 10.15468/dl.ajg4c3
title: Occurrence Download

description: A dataset containing 155 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lynx lynx (Linnaeus, 1758)",
 "HasCoordinate is true",
 "Year is greater than or equal to 2013",
 "Year is less than or equal to 2018",
 "CoordinateUncertaintyInMeters is less than or equal to 1000"
 ]
}

 The dataset includes 155 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000067-250121130708018/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.24517336.v1
title: Modelling in-ground wood decay using time-series retrievals from the 5<sup>th</sup> European climate reanalysis (ERA5-Land)

description: This article presents models to predict the time until mechanical failure of in-ground wooden test specimens resulting from fungal decay. Historical records of decay ratings were modelled by remotely sensed data from ERA5-Land. In total, 2,570 test specimens of 16 different wood species were exposed at 21 different test sites, representing three continents and climatic conditions from sub-polar to tropical, spanning a period from 1980 until 2022. To obtain specimen decay ratings over their exposure time, inspections were conducted in mostly annual and sometimes bi-annual intervals. For each specimen’s exposure period, a laboratory developed dose–response model was populated using remotely sensed soil moisture and temperature data retrieved from ERA5-Land. Wood specimens were grouped according to natural durability rankings to reduce the variability of in-ground wood decay rate between wood species. Non-linear, sigmoid-shaped models were then constructed to describe wood decay progression as a function of daily accumulated exposure to soil moisture and temperature conditions (dose). Dose, a mechanistic weighting of daily exposure conditions over time, generally performed better than exposure time alone as a predictor of in-ground wood decay progression. The open-access availability of remotely sensed soil-state data in combination with wood specimen data proved promising for in-ground wood decay predictions.
DOI: 10.6084/m9.figshare.24517336.v2
title: Modelling in-ground wood decay using time-series retrievals from the 5<sup>th</sup> European climate reanalysis (ERA5-Land)

description: This article presents models to predict the time until mechanical failure of in-ground wooden test specimens resulting from fungal decay. Historical records of decay ratings were modelled by remotely sensed data from ERA5-Land. In total, 2,570 test specimens of 16 different wood species were exposed at 21 different test sites, representing three continents and climatic conditions from sub-polar to tropical, spanning a period from 1980 until 2022. To obtain specimen decay ratings over their exposure time, inspections were conducted in mostly annual and sometimes bi-annual intervals. For each specimen’s exposure period, a laboratory developed dose–response model was populated using remotely sensed soil moisture and temperature data retrieved from ERA5-Land. Wood specimens were grouped according to natural durability rankings to reduce the variability of in-ground wood decay rate between wood species. Non-linear, sigmoid-shaped models were then constructed to describe wood decay progression as a function of daily accumulated exposure to soil moisture and temperature conditions (dose). Dose, a mechanistic weighting of daily exposure conditions over time, generally performed better than exposure time alone as a predictor of in-ground wood decay progression. The open-access availability of remotely sensed soil-state data in combination with wood specimen data proved promising for in-ground wood decay predictions.
DOI: 10.15468/dl.gcrxju
title: Occurrence Download

description: A dataset containing 106387 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "Geometry POLYGON((-64.62858 60.51462,-63.65433 55.4183,-63.11841 52.61485,-63.65568 52.30489,-63.63502 51.72629,-58.75826 51.6643,-58.71693 51.10636,-55.69995 52.16024,-55.7254 53.55816,-57.57234 54.71478,-59.32096 55.28645,-56.56351 56.26164,-57.57234 58.51468,-61.51835 57.50693,-64.62858 60.51462))",
 "Geometry POLYGON((-63.11841 52.61485,-64.62858 60.51462,-64.71778 58.6004,-64.88453 55.02216,-65.44581 55.04767,-66.03259 55.35382,-66.64489 55.5069,-67.61436 54.40986,-67.18065 52.87911,-65.93054 51.98618,-63.73647 51.65452,-63.68545 52.49643,-63.11841 52.61485))"
 ]
 },
 "License is one of (CC0 1.0, CC-BY 4.0)",
 "OccurrenceStatus is Present",
 "Year 2010-2025"
 ]
}

 The dataset includes 106387 records from 48 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000047-250121130708018/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ryfby7
title: Occurrence Download

description: A dataset containing 16172 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Rupicapra rupicapra (Linnaeus, 1758)",
 "HasCoordinate is true",
 "Year is greater than or equal to 2013",
 "Year is less than or equal to 2018",
 "CoordinateUncertaintyInMeters is less than or equal to 1000"
 ]
}

 The dataset includes 16172 records from 88 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000068-250121130708018/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9qsc82
title: Occurrence Download

description: A dataset containing 72 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-75.2497 -18.15104,-69.14899 -18.15104,-69.14899 -14.98307,-75.2497 -14.98307,-75.2497 -18.15104))",
 "HasGeospatialIssue is false",
 "TaxonKey is Phegornis mitchellii (Fraser, 1845)",
 "Year 2021-2025"
 ]
}

 The dataset includes 72 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000069-250121130708018/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.a566ry
title: Occurrence Download

description: A dataset containing 6226 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Elegia L.)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 6226 records from 39 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000071-250121130708018/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uqntv9
title: Occurrence Download

description: A dataset containing 2755 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Encephalartos Lehm.)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 2755 records from 71 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000072-250121130708018/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9c4vc4
title: Occurrence Download

description: A dataset containing 2522 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-76.15627 -18.60837,-68.88829 -18.60837,-68.88829 -13.94364,-76.15627 -13.94364,-76.15627 -18.60837))",
 "HasGeospatialIssue is false",
 "TaxonKey is Haematopus palliatus Temminck, 1820",
 "Year 2021-2025"
 ]
}

 The dataset includes 2522 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000073-250121130708018/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.