cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7284/156932
title: INS (Inertial Navigation System) data collected during research cruise TN417 using a Applanix POS/MV-320 V5 instrument system onboard the platform RV Thomas G. Thompson

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/156926
title: Radiometer data collected during research cruise TN417 using a Biospherical QSR-2150 instrument system onboard the platform RV Thomas G. Thompson

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/156928
title: Radiometer data collected during research cruise TN417 using a Eppley RAD instrument system onboard the platform RV Thomas G. Thompson

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/156934
title: Singlebeam Echosounder data collected during research cruise TN417 using a Knudsen 3260 instrument system onboard the platform RV Thomas G. Thompson

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/156944
title: SSV (Sound Speed Velocimeter) data collected during research cruise TN417 using a AML SV&T instrument system onboard the platform RV Thomas G. Thompson

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/156942
title: Water Temperature data collected during research cruise TN417 using a SeaBird SBE-38 instrument system onboard the platform RV Thomas G. Thompson

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/156927
title: Transmissometer data collected during research cruise TN417 using a WETLabs C-Star instrument system onboard the platform RV Thomas G. Thompson

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/156929
title: TSG (Thermosalinograph) data collected during research cruise TN417 using a SeaBird SBE-45 instrument system onboard the platform RV Thomas G. Thompson

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/156943
title: Wave Radar data collected during research cruise TN417 using a OceanWaveS WaMoS instrument system onboard the platform RV Thomas G. Thompson

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.15468/dl.kqbqaz
title: Occurrence Download

description: A dataset containing 154 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Türkiye",
 "TaxonKey is Cyprinus carpio Linnaeus, 1758"
 ]
}

 The dataset includes 154 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029111-241107131044228/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.27165192
title: Spatial Modeling and Future Projection of Extreme Precipitation Extents

description: Extreme precipitation events with large spatial extents may have more severe impacts than localized events as they can lead to widespread flooding. It is debated how climate change may affect the spatial extent of precipitation extremes, whose investigation often directly relies on simulations of precipitation from climate models. Here, we use a different strategy to investigate how future changes in spatial extents of precipitation extremes differ across climate zones and seasons in two river basins (Danube and Mississippi). We rely on observed precipitation extremes while exploiting a physics-based average-temperature covariate, enabling us to project future precipitation extents based on projected temperatures. We include the covariate into newly developed time-varying <i>r</i>-Pareto processes using suitably chosen spatial risk functionals <i>r</i>. This model captures temporal non-stationarity in the spatial dependence structure of precipitation extremes by linking it to the temperature covariate, derived from reanalysis data (ERA5-Land) for model calibration and from bias-corrected climate simulations (CMIP6) for projections. Our results show an increasing trend in the margins, with both significantly positive or negative trend coefficients depending on season and river (sub-)basin. During major rainy seasons, the significant trends indicate that future spatial extreme events will become relatively more intense and localized in several sub-basins. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
DOI: 10.6084/m9.figshare.27165192.v2
title: Spatial Modeling and Future Projection of Extreme Precipitation Extents

description: Extreme precipitation events with large spatial extents may have more severe impacts than localized events as they can lead to widespread flooding. It is debated how climate change may affect the spatial extent of precipitation extremes, whose investigation often directly relies on simulations of precipitation from climate models. Here, we use a different strategy to investigate how future changes in spatial extents of precipitation extremes differ across climate zones and seasons in two river basins (Danube and Mississippi). We rely on observed precipitation extremes while exploiting a physics-based average-temperature covariate, enabling us to project future precipitation extents based on projected temperatures. We include the covariate into newly developed time-varying <i>r</i>-Pareto processes using suitably chosen spatial risk functionals <i>r</i>. This model captures temporal non-stationarity in the spatial dependence structure of precipitation extremes by linking it to the temperature covariate, derived from reanalysis data (ERA5-Land) for model calibration and from bias-corrected climate simulations (CMIP6) for projections. Our results show an increasing trend in the margins, with both significantly positive or negative trend coefficients depending on season and river (sub-)basin. During major rainy seasons, the significant trends indicate that future spatial extreme events will become relatively more intense and localized in several sub-basins. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
DOI: 10.6084/m9.figshare.27165192.v1
title: Spatial modeling and future projection of extreme precipitation extents

description: Extreme precipitation events with large spatial extents may have more severe impacts than localized events as they can lead to widespread flooding. It is debated how climate change may affect the spatial extent of precipitation extremes, whose investigation often directly relies on simulations of precipitation from climate models. Here, we use a different strategy to investigate how future changes in spatial extents of precipitation extremes differ across climate zones and seasons in two river basins (Danube and Mississippi). We rely on observed precipitation extremes while exploiting a physics-based average-temperature covariate, enabling us to project future precipitation extents based on projected temperatures. We include the covariate into newly developed time-varying r-Pareto processes using suitably chosen spatial risk functionals r. This model captures temporal non-stationarity in the spatial dependence structure of precipitation extremes by linking it to the temperature covariate, derived from reanalysis data (ERA5-Land) for model calibration and from bias-corrected climate simulations (CMIP6) for projections. Our results show an increasing trend in the margins, with both significantly positive or negative trend coefficients depending on season and river (sub-)basin. During major rainy seasons, the significant trends indicate that future spatial extreme events will become relatively more intense and localized in several sub-basins.
DOI: 10.6084/m9.figshare.27260895
title: Matrix GARCH Model: Inference and Application

description: Matrix-variate time series data are largely available in applications. However, no attempt has been made to study their conditional heteroscedasticity that is often observed in economic and financial data. To address this gap, we propose a novel matrix generalized autoregressive conditional heteroscedasticity (GARCH) model to capture the dynamics of conditional row and column covariance matrices of matrix time series. The key innovation of the matrix GARCH model is the use of a univariate GARCH specification for the trace of conditional row or column covariance matrix, which allows for the model identification. Moreover, we introduce a quasi-maximum likelihood estimator (QMLE) for model estimation and develop a portmanteau test for model diagnostic checking. Simulation studies are conducted to assess the finite-sample performance of the QMLE and portmanteau test. To handle large dimensional matrix time series, we also propose a matrix factor GARCH model, and establish its theoretical properties. Finally, we demonstrate the superiority of the matrix GARCH and matrix factor GARCH models over existing multivariate GARCH-type models in volatility forecasting and portfolio allocations using three applications on credit default swap prices, global stock sector indices, and future prices. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
DOI: 10.6084/m9.figshare.27260895.v1
title: Matrix GARCH model: Inference and application*

description: Matrix-variate time series data are largely available in applications. However, no attempt has been made to study their conditional heteroskedasticity that is often observed in economic and financial data. To address this gap, we propose a novel matrix generalized autoregressive conditional heteroskedasticity (GARCH) model to capture the dynamics of conditional row and column covariance matrices of matrix time series. The key innovation of the matrix GARCH model is the use of a univariate GARCH specification for the trace of conditional row or column covariance matrix, which allows for the model identification. Moreover, we introduce a quasi-maximum likelihood estimator (QMLE) for model estimation and develop a portmanteau test for model diagnostic checking. Simulation studies are conducted to assess the finite-sample performance of the QMLE and portmanteau test. To handle large dimensional matrix time series, we also propose a matrix factor GARCH model, and establish its theoretical properties. Finally, we demonstrate the superiority of the matrix GARCH and matrix factor GARCH models over existing multivariate GARCH-type models in volatility forecasting and portfolio allocations using three applications on credit default swap prices, global stock sector indices, and future prices.
DOI: 10.15468/dl.zmptyu
title: Occurrence Download

description: A dataset containing 630 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Euderma maculatum (J.A.Allen, 1891)"
 ]
}

 The dataset includes 630 records from 43 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029114-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kpey9x
title: Occurrence Download

description: A dataset containing 37 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-140.92778 69.19244,-141.28154 59.50339,-140.33819 58.77622,-131.71041 60.64328,-139.84685 69.78204,-140.92778 69.19244))",
 "OccurrenceStatus is Present",
 "TaxonKey is Asynarchus mutatus (Hagen, 1861)"
 ]
}

 The dataset includes 37 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029115-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.skwwy6
title: Occurrence Download

description: A dataset containing 18607 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Masaridae"
 ]
}

 The dataset includes 18607 records from 105 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029113-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3n597v
title: Occurrence Download

description: A dataset containing 630 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Euderma maculatum (J.A.Allen, 1891)"
 ]
}

 The dataset includes 630 records from 43 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029119-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ty5a23
title: Occurrence Download

description: A dataset containing 14963 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is Peru",
 "TaxonKey is Phrygilus punensis Ridgway, 1887"
 ]
}

 The dataset includes 14963 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029117-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bj9jh7
title: Occurrence Download

description: A dataset containing 13 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-70.18099 -15.25759,-70.75196 -15.61051,-70.76406 -16.19823,-70.68097 -16.67473,-70.23766 -16.66251,-69.31565 -16.70665,-69.22855 -15.72477,-69.84437 -15.39478,-70.18099 -15.25759))",
 "HasGeospatialIssue is false",
 "TaxonKey is Asthenes dorbignyi (Reichenbach, 1853)"
 ]
}

 The dataset includes 13 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029121-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21966/fbv4-th96
title: MusselSeg: Semantic Segmentation for Rocky Intertidal Mussel Habitat
title: MusselSeg : segmentation sémantique pour l'habitat des moules dans la zone intertidale rocheuse

description: MusselSeg is a large-scale dataset for semantic segmentation of mussel habitat using high resolution drone imagery. It covers coastal mussel habitat located on the central coast of British Columbia, Canada, as well as areas in California, USA and provides pixel-wise annotation for mussel beds.
description: MusselSeg est un ensemble de données à grande échelle pour la segmentation sémantique de l'habitat des moules à l'aide d'images haute résolution prises par drone. Il couvre l'habitat côtier des moules situé sur la côte centrale de la Colombie-Britannique, au Canada, ainsi que des régions de Californie, aux États-Unis, et fournit des annotations au pixel près pour les herbiers de moules.
DOI: 10.6084/m9.figshare.23068370
title: A probabilistic approach to estimating timber harvest location

description: Code and data for the paper "A probabilistic approach to estimating timber harvest location". The data consists of 87 trees from 7 oak species in the USA. The code implements a Bayesian model for estimating timber harvest location using Gaussian Process regression.
DOI: 10.15468/dl.gj5w3c
title: Occurrence Download

description: A dataset containing 205599 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is CABI Bioscience Fungus Collection"
 ]
}

 The dataset includes 205599 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020028-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zp9mzh
title: Occurrence Download

description: A dataset containing 207564 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Vascular plant collections of the Botanical Museum, University of Oulu (OULU)"
 ]
}

 The dataset includes 207564 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020027-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yf2wfa
title: Occurrence Download

description: A dataset containing 205967 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is CM Birds Collection"
 ]
}

 The dataset includes 205967 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020026-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.djfplu
title: Occurrence Download

description: A dataset containing 15 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Imperata brasiliensis Trin.",
 "DatasetKey is Museo Argentino de Ciencias Naturales \"Bernardino Rivadavia\" (MACN). Vascular Plants National Collection (BAv)"
 ]
}

 The dataset includes 15 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006417-160910150852091/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sfj9um
title: Occurrence Download

description: A dataset containing 24487 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "BasisOfRecord is Observation",
 "BasisOfRecord is Machine Observation",
 "BasisOfRecord is Human Observation",
 "BasisOfRecord is Material sample",
 "BasisOfRecord is Living Specimen",
 "BasisOfRecord is Literature Occurrence"
 ]
 },
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Ptilogonys cinereus Swainson, 1827",
 "Year 1980-2020"
 ]
}

 The dataset includes 24487 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0116636-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wa9erv
title: Occurrence Download

description: A dataset containing 117 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Rhododendron sanguineum var. haemaleum (Balf.fil. & Forrest) D.F.Chamb."
 ]
}

 The dataset includes 117 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010924-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ehday7
title: Occurrence Download

description: A dataset containing 12204 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is one of (Abutilon theophrasti Medik.)"
 ]
}

 The dataset includes 12204 records from 274 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0098489-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7lj3xx
title: Occurrence Download

description: A dataset containing 299 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lactuca capensis Thunb."
 ]
}

 The dataset includes 299 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006417-170714134226665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9jpp6k
title: Occurrence Download

description: A dataset containing 232 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Aphaerema spicata Miers"
 ]
}

 The dataset includes 232 records from 40 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004144-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hvczbc
title: Occurrence Download

description: A dataset containing 173856 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Seasearch Marine Surveys in Scotland"
 ]
}

 The dataset includes 173856 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0121082-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.abpzjd
title: Occurrence Download

description: A dataset containing 18 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "Geometry POLYGON ((21.9287109375 39.87601941962116, 21.9287109375 42.74701217318067, 26.4990234375 42.74701217318067, 26.4990234375 39.87601941962116, 21.9287109375 39.87601941962116))",
 "Geometry POLYGON ((18.45703125 33.358061612778876, 18.45703125 44.402391829093915, 30.937499999999996 44.402391829093915, 30.937499999999996 33.358061612778876, 18.45703125 33.358061612778876))"
 ]
 },
 "HasCoordinate is true",
 "TaxonKey is Tetrao urogallus Linnaeus, 1758",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 18 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006417-170826194755519/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.brxmc4
title: Occurrence Download

description: A dataset containing 1028 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Plantae",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Country is Germany",
 "DecimalLongitude is greater than or equal to 12.0527465388463",
 "DecimalLongitude is less than 12.0558060920307",
 "DecimalLatitude is greater than or equal to 47.27011",
 "DecimalLatitude is less than or equal to 55.05864"
 ]
}

 The dataset includes 1028 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013758-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fx57pd
title: Occurrence Download

description: A dataset containing 31539 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Argentina",
 "OccurrenceStatus is Present",
 "TaxonKey is Insecta",
 "Year 2017-2020"
 ]
}

 The dataset includes 31539 records from 33 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0106241-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7fmffc
title: Occurrence Download

description: A dataset containing 53 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Arnebia obovata Bunge"
 ]
}

 The dataset includes 53 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013750-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.