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

description: A dataset containing 53 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Harpagoxenus canadensis Smith, 1939",
 "Country is Canada",
 {
 "not" : {
 "InstitutionCode" : [
 "is one of (iNaturalist)"
 ]
 }
 }
 ]
}

 The dataset includes 53 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0074528-240626123714530/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.23709072
title: Data and code for: <em>Understanding the chemodiversity of plants: Quantification, variation and ecological function</em>

description: Data and R-code for: <em>Understanding the chemodiversity of plants: Quantification, variation and ecological function.</em>
<br>
Two main files are associated with this. PetrenEtalData.csv is a csv-file that contains the dataset from the from the systematic literature review part of the paper. PetrenEtalScript.R is an R-script with code for producing figures of the dataset.
<br>
The third file, README.txt, contains more details of the data and code.
DOI: 10.15468/dl.uqygvf
title: Occurrence Download

description: A dataset containing 72 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "MULTIPOLYGON (((146.927699 -35.877171, 146.93219 -35.877171, 146.93219 -35.881663, 146.934436 -35.881663, 146.934436 -35.877171, 146.941174 -35.877171, 146.941174 -35.886154, 146.938928 -35.886154, 146.938928 -35.8884, 146.927699 -35.8884, 146.927699 -35.892892, 146.925453 -35.892892, 146.925453 -35.8884, 146.920961 -35.8884, 146.920961 -35.892892, 146.918716 -35.892892, 146.918716 -35.895137, 146.911978 -35.895137, 146.911978 -35.897383, 146.91647 -35.897383, 146.91647 -35.901875, 146.918716 -35.901875, 146.918716 -35.897383, 146.920961 -35.897383, 146.920961 -35.901875, 146.925453 -35.901875, 146.925453 -35.904121, 146.93219 -35.904121, 146.93219 -35.901875, 146.934436 -35.901875, 146.934436 -35.904121, 146.95914 -35.904121, 146.95914 -35.901875, 146.954648 -35.901875, 146.954648 -35.899629, 146.950157 -35.899629, 146.950157 -35.886154, 146.945665 -35.886154, 146.945665 -35.870434, 146.941174 -35.870434, 146.941174 -35.863696, 146.934436 -35.863696, 146.934436 -35.872679, 146.927699 -35.872679, 146.927699 -35.877171), (146.941174 -35.870434, 146.941174 -35.872679, 146.938928 -35.872679, 146.938928 -35.870434, 146.941174 -35.870434)), ((146.927699 -35.877171, 146.925453 -35.877171, 146.925453 -35.879417, 146.927699 -35.879417, 146.927699 -35.877171)))"
 ]
}

 The dataset includes 72 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0074529-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fxg8tt
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((146.833375 -35.901875, 146.833375 -35.91535, 146.84685 -35.91535, 146.84685 -35.910858, 146.842358 -35.910858, 146.842358 -35.904121, 146.840113 -35.904121, 146.840113 -35.901875, 146.833375 -35.901875))"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0074531-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.z3qcnw
title: Occurrence Download

description: A dataset containing 20 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Leptothorax athabasca",
 "Country is Canada",
 {
 "not" : {
 "InstitutionCode" : [
 "is one of (iNaturalist)"
 ]
 }
 }
 ]
}

 The dataset includes 20 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0074532-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8vdnfb
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "MULTIPOLYGON (((146.840113 -35.919841, 146.840113 -35.924333, 146.842358 -35.924333, 146.842358 -35.919841, 146.840113 -35.919841)), ((146.842358 -35.924333, 146.842358 -35.933316, 146.84685 -35.933316, 146.84685 -35.935562, 146.851342 -35.935562, 146.851342 -35.933316, 146.849096 -35.933316, 146.849096 -35.93107, 146.84685 -35.93107, 146.84685 -35.924333, 146.842358 -35.924333)))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0074533-240626123714530/datasets/export for details.
DOI: 10.15468/dl.y4x5am
title: Occurrence Download

description: A dataset containing 26895 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Brazil",
 "TaxonKey is Aspidosperma Mart. & Zucc."
 ]
}

 The dataset includes 26895 records from 273 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0074534-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cs9yfg
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((146.862571 -35.93107, 146.862571 -35.935562, 146.867062 -35.935562, 146.867062 -35.93107, 146.862571 -35.93107))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0074535-240626123714530/datasets/export for details.
DOI: 10.15468/dl.9chufq
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((146.871554 -35.93107, 146.871554 -35.933316, 146.878291 -35.933316, 146.878291 -35.93107, 146.871554 -35.93107))"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0074536-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pqtg6a
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((146.894012 -35.933316, 146.894012 -35.935562, 146.900749 -35.935562, 146.900749 -35.933316, 146.894012 -35.933316))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0074537-240626123714530/datasets/export for details.
DOI: 10.15468/dl.raqme6
title: Occurrence Download

description: A dataset containing 11 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Leptothorax calderoni Creighton",
 "Country is Canada",
 {
 "not" : {
 "InstitutionCode" : [
 "is one of (iNaturalist)"
 ]
 }
 }
 ]
}

 The dataset includes 11 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0074538-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.5784704
title: TELL weather forcing sample data

description: This dataset contains three years of sample data generated by the sequence of processing scripts that convert the meteorology from IM3's climate simulations using the Weather Research and Forecasting (WRF) model into input files ready for use in the Total ELectricity Load (TELL) model. The first step in the processing chain spatially averages the gridded meteorology output from WRF into county mean values. The output of that processing step is a series of .csv files (one for every hour processed) with the county-mean value of six meteorological variables: T2, Q2, U10, V10, SWDOWN, and GLW. The second step then takes these county-level hourly values and population-weights them into an annual time-series for each of the balancing authorities (BAs) used in the TELL model. The sample dataset includes three years of output for both processing steps: 2019, 2059, and 2099. The 2019 data is based on observed historical meteorology simulated by WRF. In contrast, the 2059 and 2099 sample data comes from IM3's future WRF runs under the RCP 8.5 climate scenario with SSP5 population forcing. The code used to generate this sample dataset and more information about the wrf_to_tell processing pipeline can be found at: https://github.com/IMMM-SFA/im3components. More information about the TELL model can be found at: https://immm-sfa.github.io/tell/user_guide.html.
DOI: 10.5281/zenodo.5912022
title: TELL weather forcing sample data

description: This dataset contains three years of sample data generated by the sequence of processing scripts that convert the meteorology from IM3's climate simulations using the Weather Research and Forecasting (WRF) model into input files ready for use in the Total ELectricity Load (TELL) model. The first step in the processing chain spatially averages the gridded meteorology output from WRF into county mean values. The output of that processing step is a series of .csv files (one for every hour processed) with the county-mean value of six meteorological variables: T2, Q2, U10, V10, SWDOWN, and GLW. The second step then takes these county-level hourly values and population-weights them into an annual time-series for each of the balancing authorities (BAs) used in the TELL model. The sample dataset includes three years of output for both processing steps: 2019, 2059, and 2099. The 2019 data is based on observed historical meteorology simulated by WRF. In contrast, the 2059 and 2099 sample data comes from IM3's future WRF runs under the RCP 8.5 climate scenario with SSP5 population forcing. Additionally, we include the full historical meteorology for a single BA (California Independent System Operator; CISO) in case you want to explore retraining the TELL machine-learning models using a longer historical record. The code used to generate this sample dataset and more information about the wrf_to_tell processing pipeline can be found at: https://github.com/IMMM-SFA/im3components. More information about the TELL model can be found at: https://immm-sfa.github.io/tell/user_guide.html.
DOI: 10.5281/zenodo.6147143
title: TELL weather forcing sample data

description: This dataset contains three years of sample data generated by the sequence of processing scripts that convert the meteorology from IM3's climate simulations using the Weather Research and Forecasting (WRF) model into input files ready for use in the Total ELectricity Load (TELL) model. The first step in the processing chain spatially averages the gridded meteorology output from WRF into county mean values. The output of that processing step is a series of .csv files (one for every hour processed) with the county-mean value of six meteorological variables: T2, Q2, U10, V10, SWDOWN, and GLW. The second step then takes these county-level hourly values and population-weights them into an annual time-series for each of the balancing authorities (BAs) used in the TELL model. The sample dataset includes three years of output for both processing steps: 2019, 2059, and 2099. The 2019 data is based on observed historical meteorology simulated by WRF. In contrast, the 2059 and 2099 sample data comes from IM3's future WRF runs under the RCP 8.5 climate scenario with SSP5 population forcing. Additionally, we include the full historical meteorology for a single BA (California Independent System Operator; CISO) in case you want to explore retraining the TELL machine-learning models using a longer historical record. Finally, we include a sample output dataset from the United States version of the Global Change Analysis Model (GCAM-USA) that can be used in the TELL quickstarter notebook. The code used to generate this sample dataset and more information about the wrf_to_tell processing pipeline can be found at: https://github.com/IMMM-SFA/im3components. More information about the TELL model can be found at: https://immm-sfa.github.io/tell/user_guide.html.
DOI: 10.5281/zenodo.6326507
title: TELL sample weather data

description: This dataset contains sample data generated by the sequence of processing scripts that convert the meteorology from IM3's climate simulations using the Weather Research and Forecasting (WRF) model into input files ready for use in the Total ELectricity Load (TELL) model. The first step in the processing chain spatially averages the gridded meteorology output from WRF into county mean values. The output of that processing step is a series of .csv files (one for every hour processed) with the county-mean value of six meteorological variables: T2, Q2, U10, V10, SWDOWN, and GLW. The second step then takes these county-level hourly values and population-weights them into an annual time-series for each of the balancing authorities (BAs) used in the TELL model. The sample dataset includes five years of historical data (2015-2019) and four years of sample future data (2039, 2059, 2079, and 2099). The 2015-2019 data is based on historical meteorology simulated by WRF. In contrast, the sample future data comes from IM3's future WRF runs under the RCP 8.5 climate scenario with SSP5 population forcing. Finally, we include a sample output dataset from the United States version of the Global Change Analysis Model (GCAM-USA) that can be used in the TELL quickstarter notebook. The code used to generate this sample dataset and more information about the wrf_to_tell processing pipeline can be found at: https://github.com/IMMM-SFA/im3components. More information about the TELL model can be found at: https://immm-sfa.github.io/tell/user_guide.html.
DOI: 10.5281/zenodo.13344803
title: TELL sample forcing data

description: This dataset contains sample data forcing data for the Total Electricity Loads (TELL) model developed by the IM3 project. More information about the TELL model can be found at: https://immm-sfa.github.io/tell/user_guide.html.


The sample dataset includes five years of historical weather data (2015-2019) and four years of sample future data (2039, 2059, 2079, and 2099). The 2015-2019 data is based on historical meteorology simulated by WRF. In contrast, the sample future data comes from IM3's future WRF runs under the RCP 8.5 climate scenario with SSP5 population forcing. The weather data was generated by the sequence of processing scripts that convert the meteorology from IM3's climate simulations using the Weather Research and Forecasting (WRF) model into input files ready for use in TELL. The first step in the processing chain spatially averages the gridded meteorology output from WRF into county mean values. The output of that processing step is a series of .csv files (one for every hour processed) with the county-mean value of six meteorological variables: T2, Q2, U10, V10, SWDOWN, and GLW. The second step then takes these county-level hourly values and population-weights them into an annual time-series for each of the balancing authorities (BAs) used in the TELL model. The code used to generate this sample weather data and more information about the wrf_to_tell processing pipeline can be found at: https://github.com/IMMM-SFA/im3components.


The dataset also contains a sample output file from the United States version of the Global Change Analysis Model (GCAM-USA) and two future county-level population projections that can be used in the TELL quickstarter notebook.
DOI: 10.5281/zenodo.5784703
title: TELL sample forcing data

description: This dataset contains sample data forcing data for the Total Electricity Loads (TELL) model developed by the IM3 project. More information about the TELL model can be found at: https://immm-sfa.github.io/tell/user_guide.html.


The sample dataset includes five years of historical weather data (2015-2019) and four years of sample future data (2039, 2059, 2079, and 2099). The 2015-2019 data is based on historical meteorology simulated by WRF. In contrast, the sample future data comes from IM3's future WRF runs under the RCP 8.5 climate scenario with SSP5 population forcing. The weather data was generated by the sequence of processing scripts that convert the meteorology from IM3's climate simulations using the Weather Research and Forecasting (WRF) model into input files ready for use in TELL. The first step in the processing chain spatially averages the gridded meteorology output from WRF into county mean values. The output of that processing step is a series of .csv files (one for every hour processed) with the county-mean value of six meteorological variables: T2, Q2, U10, V10, SWDOWN, and GLW. The second step then takes these county-level hourly values and population-weights them into an annual time-series for each of the balancing authorities (BAs) used in the TELL model. The code used to generate this sample weather data and more information about the wrf_to_tell processing pipeline can be found at: https://github.com/IMMM-SFA/im3components.


The dataset also contains a sample output file from the United States version of the Global Change Analysis Model (GCAM-USA) and two future county-level population projections that can be used in the TELL quickstarter notebook.
DOI: 10.5281/zenodo.6354665
title: TELL sample forcing data

description: This dataset contains sample data forcing data for the Total Electricity Loads (TELL) model developed by the IM3 project. More information about the TELL model can be found at: https://immm-sfa.github.io/tell/user_guide.html. The sample dataset includes five years of historical weather data (2015-2019) and four years of sample future data (2039, 2059, 2079, and 2099). The 2015-2019 data is based on historical meteorology simulated by WRF. In contrast, the sample future data comes from IM3's future WRF runs under the RCP 8.5 climate scenario with SSP5 population forcing. The weather data was generated by the sequence of processing scripts that convert the meteorology from IM3's climate simulations using the Weather Research and Forecasting (WRF) model into input files ready for use in TELL. The first step in the processing chain spatially averages the gridded meteorology output from WRF into county mean values. The output of that processing step is a series of .csv files (one for every hour processed) with the county-mean value of six meteorological variables: T2, Q2, U10, V10, SWDOWN, and GLW. The second step then takes these county-level hourly values and population-weights them into an annual time-series for each of the balancing authorities (BAs) used in the TELL model. The code used to generate this sample weather data and more information about the wrf_to_tell processing pipeline can be found at: https://github.com/IMMM-SFA/im3components. The dataset also contains a sample output file from the United States version of the Global Change Analysis Model (GCAM-USA) and two future county-level population projections that can be used in the TELL quickstarter notebook.
DOI: 10.15468/dl.26ztju
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((146.902995 -35.935562, 146.902995 -35.937808, 146.905241 -35.937808, 146.905241 -35.935562, 146.902995 -35.935562))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0074539-240626123714530/datasets/export for details.
DOI: 10.15468/dl.r2jfbc
title: Occurrence Download

description: A dataset containing 16 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Thelypodium howellii subsp. spectabilis (M.Peck) Al-Shehbaz",
 "Year 1994-2024"
 ]
}

 The dataset includes 16 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0074540-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kw8szr
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((146.837867 -35.940053, 146.837867 -35.942299, 146.84685 -35.942299, 146.84685 -35.940053, 146.837867 -35.940053))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0074542-240626123714530/datasets/export for details.
DOI: 10.5066/p9zl6gk6
title: Electron Microprobe and 40Ar/39Ar data from the East Derby Shear Zone, Connecticut

description: This data release includes electron microprobe and 40Ar/39Ar measurements collected at the U.S. Geological Survey for samples from the East Derby Shear Zone (EDSZ) in Connecticut, USA. Rock samples were collected by Bryan Wathen, now at the University of Wisconsin. Muscovite, biotite, chlorite, plagioclase, and K-feldspar were analyzed by electron probe microanalysis at the U.S. Geological Survey, Reston Electron Microbeam Laboratory. Aliquots of muscovite from several samples were analyzed by argon geochronology at the U.S. Geological Survey Bascom ARgon Dating (BARD) Laboratory in Reston, Virginia. The 40Ar/39Ar data constrain the cooling history of the rocks around the EDSZ as well as the time(s) of deformation in the EDSZ.
DOI: 10.15468/dl.xuy22j
title: Occurrence Download

description: A dataset containing 929 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Brazil",
 "TaxonKey is Aspidosperma polyneuron Müll.Arg."
 ]
}

 The dataset includes 929 records from 125 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0074543-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xvzn9r
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((146.862571 -35.940053, 146.862571 -35.942299, 146.864816 -35.942299, 146.864816 -35.940053, 146.862571 -35.940053))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0074544-240626123714530/datasets/export for details.
DOI: 10.15468/dl.ew5tf5
title: Occurrence Download

description: A dataset containing 34 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Epidendrum pittieri Ames"
 ]
}

 The dataset includes 34 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0074545-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8bmny5
title: Occurrence Download

description: A dataset containing 6169 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Caracterización de flora y fauna en Área de perforación exploratoria LLANOS 87, departamento de Casanare, Colombia"
 ]
}

 The dataset includes 6169 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0074546-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2x4hhb
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Colombia",
 "TaxonKey is Epidendrum physopus Kraenzl."
 ]
}

 The dataset includes 12 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0074547-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.