cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.swkt8j
title: Occurrence Download

description: A dataset listing the 61033 species recorded in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "Country is Colombia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year 2013-2023"
 ]
}

 The dataset's 61033 records were derived from 2116 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0238367-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15048706
title: Stordalen Mire mire-wide survey: Plot-level vegetation greenness, porewater pH, and methane production data (from porewater measurements, models, and microbial analyses)

description: Plot-level data from all mire-wide plots in Stordalen Mire (northern Sweden) sampled in July 2015, including vegetation greenness area (VGA); porewater pH and methane (CH4) concentrations and δ13C at 20cm; Wetland-DNDC-modeled hydrogenotrophic & acetoclastic CH4 production, oxidation, net emission, and δ13C values; microbial hydrogenotroph:acetoclast ratios; and methanogen relative abundances.

More details of the plots, including latitude, longitude, and species-specific vegetation cover, are in the dataset "Stordalen Mire mire-wide survey: Vegetation cover" (https://doi.org/10.5281/zenodo.15048198). Metadata for the microbial samples, including the numeric depths for shallow (S), mid (M), and deep (D) samples, are defined in "Stordalen Mire mire-wide survey: Microbial sample metadata" (https://doi.org/10.5281/zenodo.15047156). For "methanogen relative abundance summed across depths", methanogen ASVs' relative abundances were summed across depths, and CLR-transformed consistent with other Methods; and site 13 was excluded because that site did not have data for all 3 depths. NA indicates no data available for that sampling site. Blank cells indicate a value of 0 for VGA columns, and NA for all other columns.

FUNDING:



National Aeronautics and Space Administration, Interdisciplinary Science program: From Archaea to the Atmosphere (award # NNX17AK10G).

National Science Foundation, Biology Integration Institutes Program: EMERGE Biology Integration Institute (award # 2022070).

United States Department of Energy Office of Biological and Environmental Research, Genomic Science Program: The IsoGenie Project (grant #s DE-SC0004632, DE-SC0010580, and DE-SC0016440).

National Science Foundation, MacroSystems program (grant # EF-1241037).

Sequencing was performed using startup funding from the University of Arizona to Virginia Rich.

We thank the Swedish Polar Research Secretariat and SITES for the support of the work done at the Abisko Scientific Research Station. SITES is supported by the Swedish Research Council's grant 4.3-2021-00164
DOI: 10.5281/zenodo.15048707
title: Stordalen Mire mire-wide survey: Plot-level vegetation greenness, porewater pH, and methane production data (from porewater measurements, models, and microbial analyses)

description: Plot-level data from all mire-wide plots in Stordalen Mire (northern Sweden) sampled in July 2015, including vegetation greenness area (VGA); porewater pH and methane (CH4) concentrations and δ13C at 20cm; Wetland-DNDC-modeled hydrogenotrophic & acetoclastic CH4 production, oxidation, net emission, and δ13C values; microbial hydrogenotroph:acetoclast ratios; and methanogen relative abundances.

More details of the plots, including latitude, longitude, and species-specific vegetation cover, are in the dataset "Stordalen Mire mire-wide survey: Vegetation cover" (https://doi.org/10.5281/zenodo.15048198). Metadata for the microbial samples, including the numeric depths for shallow (S), mid (M), and deep (D) samples, are defined in "Stordalen Mire mire-wide survey: Microbial sample metadata" (https://doi.org/10.5281/zenodo.15047156). For "methanogen relative abundance summed across depths", methanogen ASVs' relative abundances were summed across depths, and CLR-transformed consistent with other Methods; and site 13 was excluded because that site did not have data for all 3 depths. NA indicates no data available for that sampling site. Blank cells indicate a value of 0 for VGA columns, and NA for all other columns.

FUNDING:



National Aeronautics and Space Administration, Interdisciplinary Science program: From Archaea to the Atmosphere (award # NNX17AK10G).

National Science Foundation, Biology Integration Institutes Program: EMERGE Biology Integration Institute (award # 2022070).

United States Department of Energy Office of Biological and Environmental Research, Genomic Science Program: The IsoGenie Project (grant #s DE-SC0004632, DE-SC0010580, and DE-SC0016440).

National Science Foundation, MacroSystems program (grant # EF-1241037).

Sequencing was performed using startup funding from the University of Arizona to Virginia Rich.

We thank the Swedish Polar Research Secretariat and SITES for the support of the work done at the Abisko Scientific Research Station. SITES is supported by the Swedish Research Council's grant 4.3-2021-00164
DOI: 10.15468/dl.md7wyq
title: Occurrence Download

description: A dataset containing 30653 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "PublishingCountry is Canada",
 "Country is Canada"
 ]
 },
 "TaxonKey is one of (Alosa pseudoharengus (Wilson, 1811))"
 ]
}

 The dataset includes 30653 records from 38 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014123-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dn4ddq
title: Occurrence Download

description: A dataset containing 3896 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Desmanthus virgatus (L.) Willd.)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "Geometry POLYGON((-180 -90,180 -90,180 90,-180 90,-180 -90))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1945"
 ]
}

 The dataset includes 3896 records from 255 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014124-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15066280
title: HDMA ChromBPNet contribution scores - Part 3

description: Base-resolution contribution scores from ChromBPNet models (in the form of h5 files containing mean scores across folds per cell type), for HDMA (Liu*, Jessa*, Kim*, Ng* et al, bioRxiv 2025). A detailed description of the main data types deposited on Zenodo can be found here.
DOI: 10.5281/zenodo.15066281
title: HDMA ChromBPNet contribution scores - Part 3

description: Base-resolution contribution scores from ChromBPNet models (in the form of h5 files containing mean scores across folds per cell type), for HDMA (Liu*, Jessa*, Kim*, Ng* et al, bioRxiv 2025). A detailed description of the main data types deposited on Zenodo can be found here.
DOI: 10.5281/zenodo.15048823
title: HDMA ChromBPNet contribution scores - Part 2

description: Base-resolution contribution scores from ChromBPNet models (in the form of h5 files containing mean scores across folds per cell type), for HDMA (Liu*, Jessa*, Kim*, Ng* et al, bioRxiv 2025). A detailed description of the main data types deposited on Zenodo can be found here.
DOI: 10.5281/zenodo.15048827
title: HDMA ChromBPNet contribution scores - Part 2

description: Base-resolution contribution scores from ChromBPNet models (in the form of h5 files containing mean scores across folds per cell type), for HDMA (Liu*, Jessa*, Kim*, Ng* et al, bioRxiv 2025). A detailed description of the main data types deposited on Zenodo can be found here.
DOI: 10.15468/dl.shyogv
title: Occurrence Download

description: A dataset containing 27098953 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "Continent is South America",
 "Continent is North America"
 ]
 },
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 27098953 records from 1345 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018356-200221144449610/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.11582455
title: Storage and Transit Time Data and Code

description: Author: Andrew J. FeltonDate: 5/5/2024

This R project contains the primary code and data (following pre-processing in python) used for data production, manipulation, visualization, and analysis and figure production for the study entitled:

"Global estimates of the storage and transit time of water through vegetation"

Please note that 'turnover' and 'transit' are used interchangeably in this project.

Data information:

The data folder contains key data sets used for analysis. In particular:

"data/turnover_from_python/updated/annual/multi_year_average/average_annual_turnover.nc" contains a global array summarizing five year (2016-2020) averages of annual transit, storage, canopy transpiration, and number of months of data. This is the core dataset for the analysis; however, each folder has much more data, including a dataset for each year of the analysis. Data are also available is separate .csv files for each land cover type. Oterh data can be found for the minimum, monthly, and seasonal transit time found in their respective folders. These data were produced using the python code found in the "supporting_code" folder given the ease of working with .nc and EASE grid in the xarray python module. R was used  primarily for data visualization purposes. The remaining files in the "data" and "data/supporting_data"" folder primarily contain ground-based estimates of storage and transit found in public databases or through a literature search, but have been extensively processed and filtered here. 

#Code information

Python scripts can be found in the "supporting_code" folder.

Each R script in this project has a particular function:

01_start.R: This script loads the R packages used in the analysis, sets thedirectory, and imports custom functions for the project. You can also load in the main transit time (turnover) datasets here using the `source()` function.

02_functions.R: This script contains the custom function for this analysis, primarily to work with importing the seasonal transit data. Load this using the  `source()` function in the 01_start.R script. 

03_generate_data.R: This script is not necessary to run and is primarilyfor documentation. The main role of this code was to import and wranglethe data needed to calculate ground-based estimates of aboveground water storage.

04_annual_turnover_storage_import.R: This script imports the annual turnover andstorage data for each landcover type. You load in these data from the 01_start.R scriptusing the `source()` function.

05_minimum_turnover_storage_import.R: This script imports the minimum turnover andstorage data for each landcover type. Minimum is defined as the lowest monthlyestimate.You load in these data from the 01_start.R scriptusing the `source()` function.

06_figures_tables.R: This is the main workhouse for figure/table production and supporting analyses. This script generates the key figures and summary statistics used in the study that then get saved in the  manuscript_figures folder. Note that allmaps were produced using Python code found in the "supporting_code"" folder.
DOI: 10.5281/zenodo.8136816
title: Storage and Transit Time Data and Code

description: Author: Andrew J. FeltonDate: 5/5/2024

This R project contains the primary code and data (following pre-processing in python) used for data production, manipulation, visualization, and analysis and figure production for the study entitled:

"Global estimates of the storage and transit time of water through vegetation"

Please note that 'turnover' and 'transit' are used interchangeably in this project.

Data information:

The data folder contains key data sets used for analysis. In particular:

"data/turnover_from_python/updated/annual/multi_year_average/average_annual_turnover.nc" contains a global array summarizing five year (2016-2020) averages of annual transit, storage, canopy transpiration, and number of months of data. This is the core dataset for the analysis; however, each folder has much more data, including a dataset for each year of the analysis. Data are also available is separate .csv files for each land cover type. Oterh data can be found for the minimum, monthly, and seasonal transit time found in their respective folders. These data were produced using the python code found in the "supporting_code" folder given the ease of working with .nc and EASE grid in the xarray python module. R was used  primarily for data visualization purposes. The remaining files in the "data" and "data/supporting_data"" folder primarily contain ground-based estimates of storage and transit found in public databases or through a literature search, but have been extensively processed and filtered here. 

#Code information

Python scripts can be found in the "supporting_code" folder.

Each R script in this project has a particular function:

01_start.R: This script loads the R packages used in the analysis, sets thedirectory, and imports custom functions for the project. You can also load in the main transit time (turnover) datasets here using the `source()` function.

02_functions.R: This script contains the custom function for this analysis, primarily to work with importing the seasonal transit data. Load this using the  `source()` function in the 01_start.R script. 

03_generate_data.R: This script is not necessary to run and is primarilyfor documentation. The main role of this code was to import and wranglethe data needed to calculate ground-based estimates of aboveground water storage.

04_annual_turnover_storage_import.R: This script imports the annual turnover andstorage data for each landcover type. You load in these data from the 01_start.R scriptusing the `source()` function.

05_minimum_turnover_storage_import.R: This script imports the minimum turnover andstorage data for each landcover type. Minimum is defined as the lowest monthlyestimate.You load in these data from the 01_start.R scriptusing the `source()` function.

06_figures_tables.R: This is the main workhouse for figure/table production and supporting analyses. This script generates the key figures and summary statistics used in the study that then get saved in the  manuscript_figures folder. Note that allmaps were produced using Python code found in the "supporting_code"" folder.
DOI: 10.15468/dl.5nluu7
title: Occurrence Download

description: A dataset containing 788235635 species occurrences available in GBIF matching the query:
{ }

 The dataset includes 788235635 records from 17086 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002125-170714134226665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5517/cc3tccm
title: CCDC 113750: Experimental Crystal Structure Determination

description: Related Article: S.Kabashima, S.Kuwata, M.Hidai|1999|J.Am.Chem.Soc.|121|7837|doi:10.1021/ja990034a
description: Related Article: S.Kuwata, M.Hidai|1998|Chem.Lett.|27|885|doi:10.1246/cl.1998.885
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/cc3ts0p
title: CCDC 114142: Experimental Crystal Structure Determination

description: Related Article: J.Huhmann-Vincent, B.L.Scott, G.J.Kubas|1999|Inorg.Chem.|38|115|doi:10.1021/ic980912q
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/cc3ts1q
title: CCDC 114143: Experimental Crystal Structure Determination

description: Related Article: J.Huhmann-Vincent, B.L.Scott, G.J.Kubas|1999|Inorg.Chem.|38|115|doi:10.1021/ic980912q
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/cc3tryl
title: CCDC 114140: Experimental Crystal Structure Determination

description: Related Article: J.Huhmann-Vincent, B.L.Scott, G.J.Kubas|1999|Inorg.Chem.|38|115|doi:10.1021/ic980912q
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/cc3ts2r
title: CCDC 114144: Experimental Crystal Structure Determination

description: Related Article: J.Huhmann-Vincent, B.L.Scott, G.J.Kubas|1999|Inorg.Chem.|38|115|doi:10.1021/ic980912q
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/cc3trzm
title: CCDC 114141: Experimental Crystal Structure Determination

description: Related Article: J.Huhmann-Vincent, B.L.Scott, G.J.Kubas|1999|Inorg.Chem.|38|115|doi:10.1021/ic980912q
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/cc3ts3s
title: CCDC 114145: Experimental Crystal Structure Determination

description: Related Article: J.Huhmann-Vincent, B.L.Scott, G.J.Kubas|1999|Inorg.Chem.|38|115|doi:10.1021/ic980912q
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/cc3ts5v
title: CCDC 114147: Experimental Crystal Structure Determination

description: Related Article: R.T.Stibrany, S.Knapp, J.A.Potenza, H.J.Schugar|1999|Inorg.Chem.|38|132|doi:10.1021/ic980903h
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/cc3ts6w
title: CCDC 114148: Experimental Crystal Structure Determination

description: Related Article: Wa-Hung Leung, E.Y.Y.Chan, Wing-Tak Wong|1999|Inorg.Chem.|38|136|doi:10.1021/ic980196s
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/cc3ts7x
title: CCDC 114149: Experimental Crystal Structure Determination

description: Related Article: Wa-Hung Leung, E.Y.Y.Chan, Wing-Tak Wong|1999|Inorg.Chem.|38|136|doi:10.1021/ic980196s
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/cc3ts8y
title: CCDC 114150: Experimental Crystal Structure Determination

description: Related Article: Wa-Hung Leung, E.Y.Y.Chan, Wing-Tak Wong|1999|Inorg.Chem.|38|136|doi:10.1021/ic980196s
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/cc3ts9z
title: CCDC 114151: Experimental Crystal Structure Determination

description: Related Article: Wa-Hung Leung, E.Y.Y.Chan, Wing-Tak Wong|1999|Inorg.Chem.|38|136|doi:10.1021/ic980196s
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.