cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.fyhg73
title: Occurrence Download

description: A dataset containing 61 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Nematalosa nasus)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 61 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0089203-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qf5qe7
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acmella uliginosa",
 "Country is Fiji",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0089205-250717081556266/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.29652065
title: Soil Nutrient Availability Data for Perpetuo Socorro Property, Paraná, Brazil (2022/2023 Harvest)

description: This zipped data file contains comprehensive geospatial information on <b>soil nutrient availability</b> collected from the <b>Perpetuo Socorro Property in Paraná, Brazil</b>, during the <b>2022/2023 harvest season</b>. This dataset is part of a larger study investigating environmental sustainability and carbon balance in rural properties, contributing to the understanding of carbon credit potential.The file is organized into subfolders, each representing an individual plot/section (talhão) within the Perpetuo Socorro property (e.g., 'T10', 'T01', 'T02eT03', 'T04e08', 'T05', 'T06eT07', 'T09', 'T11'). Inside each plot's folder, separate shapefiles are provided for each analyzed nutrient element.The included nutrient elements are: <b>Aluminum (Al), Boron (Br), Calcium (Ca), Potassium (K), Magnesium (Mg), Nitrogen (N), Phosphorus (P), Sulfur (S), and Zinc (Zn)</b>. The units for each nutrient represent their <b>actual availability</b> in the soil and are provided within the internal metadata of their respective shapefiles.All geospatial data uses the <b>WGS 84 (EPSG: 4326) Geodetic Coordinate Reference System (CRS)</b>.
DOI: 10.6084/m9.figshare.29652065.v2
title: Soil Nutrient Availability Data for Perpetuo Socorro Property, Paraná, Brazil (2022/2023 Harvest)

description: This zipped data file contains comprehensive geospatial information on <b>soil nutrient availability</b> collected from the <b>Perpetuo Socorro Property in Paraná, Brazil</b>, during the <b>2022/2023 harvest season</b>. This dataset is part of a larger study investigating environmental sustainability and carbon balance in rural properties, contributing to the understanding of carbon credit potential.The file is organized into subfolders, each representing an individual plot/section (talhão) within the Perpetuo Socorro property (e.g., 'T10', 'T01', 'T02eT03', 'T04e08', 'T05', 'T06eT07', 'T09', 'T11'). Inside each plot's folder, separate shapefiles are provided for each analyzed nutrient element.The included nutrient elements are: <b>Aluminum (Al), Boron (Br), Calcium (Ca), Potassium (K), Magnesium (Mg), Nitrogen (N), Phosphorus (P), Sulfur (S), and Zinc (Zn)</b>. The units for each nutrient represent their <b>actual availability</b> in the soil and are provided within the internal metadata of their respective shapefiles.All geospatial data uses the <b>WGS 84 (EPSG: 4326) Geodetic Coordinate Reference System (CRS)</b>.
DOI: 10.6084/m9.figshare.29652065.v1
title: <b>Soil Nutrient Availability Data for Perpetuo Socorro Property, Paraná, Brazil (2022/2023 Harvest)</b>

description: This zipped data file contains comprehensive geospatial information on <b>soil nutrient availability</b> collected from the <b>Perpetuo Socorro Property in Paraná, Brazil</b>, during the <b>2022/2023 harvest season</b>. This dataset is part of a larger study investigating environmental sustainability and carbon balance in rural properties, contributing to the understanding of carbon credit potential.The file is organized into subfolders, each representing an individual plot/section (talhão) within the Perpetuo Socorro property (e.g., 'T10', 'T01', 'T02eT03', 'T04e08', 'T05', 'T06eT07', 'T09', 'T11'). Inside each plot's folder, separate shapefiles are provided for each analyzed nutrient element.The included nutrient elements are: <b>Aluminum (Al), Boron (Br), Calcium (Ca), Potassium (K), Magnesium (Mg), Nitrogen (N), Phosphorus (P), Sulfur (S), and Zinc (Zn)</b>. The units for each nutrient represent their <b>actual availability</b> in the soil and are provided within the internal metadata of their respective shapefiles.All geospatial data uses the <b>WGS 84 (EPSG: 4326) Geodetic Coordinate Reference System (CRS)</b>.
DOI: 10.6084/m9.figshare.29652074
title: Soil Nutrient Availability Data for Smart Farm Property, Paraná, Brazil (2022/2023 Harvest)

description: This zipped data file contains comprehensive geospatial information on <b>soil nutrient availability</b> collected from the <b>Smart Farm Property in Paraná, Brazil</b>, during the <b>2022/2023 harvest season</b>. This dataset is part of a larger study investigating environmental sustainability and carbon balance in rural properties, contributing to the understanding of carbon credit potential.The file is organized into subfolders, for each analyzed nutrient element.The included nutrient elements are: <b>Aluminum (Al), Boron (Br), Calcium (Ca), Potassium (K), Magnesium (Mg), Nitrogen (N), Phosphorus (P), Sulfur (S), and Zinc (Zn)</b>. The units for each nutrient represent their <b>actual availability</b> in the soil and are provided within the internal metadata of their respective shapefiles.All geospatial data uses the <b>WGS 84 (EPSG: 4326) Geodetic Coordinate Reference System (CRS)</b>.
DOI: 10.6084/m9.figshare.29652074.v2
title: Soil Nutrient Availability Data for Smart Farm Property, Paraná, Brazil (2022/2023 Harvest)

description: This zipped data file contains comprehensive geospatial information on <b>soil nutrient availability</b> collected from the <b>Smart Farm Property in Paraná, Brazil</b>, during the <b>2022/2023 harvest season</b>. This dataset is part of a larger study investigating environmental sustainability and carbon balance in rural properties, contributing to the understanding of carbon credit potential.The file is organized into subfolders, for each analyzed nutrient element.The included nutrient elements are: <b>Aluminum (Al), Boron (Br), Calcium (Ca), Potassium (K), Magnesium (Mg), Nitrogen (N), Phosphorus (P), Sulfur (S), and Zinc (Zn)</b>. The units for each nutrient represent their <b>actual availability</b> in the soil and are provided within the internal metadata of their respective shapefiles.All geospatial data uses the <b>WGS 84 (EPSG: 4326) Geodetic Coordinate Reference System (CRS)</b>.
DOI: 10.6084/m9.figshare.29652074.v1
title: <b>Soil Nutrient Availability Data for Smart Farm Property, Paraná, Brazil (2022/2023 Harvest)</b>

description: This zipped data file contains comprehensive geospatial information on <b>soil nutrient availability</b> collected from the <b>Smart Farm Property in Paraná, Brazil</b>, during the <b>2022/2023 harvest season</b>. This dataset is part of a larger study investigating environmental sustainability and carbon balance in rural properties, contributing to the understanding of carbon credit potential.The file is organized into subfolders, for each analyzed nutrient element.The included nutrient elements are: <b>Aluminum (Al), Boron (Br), Calcium (Ca), Potassium (K), Magnesium (Mg), Nitrogen (N), Phosphorus (P), Sulfur (S), and Zinc (Zn)</b>. The units for each nutrient represent their <b>actual availability</b> in the soil and are provided within the internal metadata of their respective shapefiles.All geospatial data uses the <b>WGS 84 (EPSG: 4326) Geodetic Coordinate Reference System (CRS)</b>.
DOI: 10.6084/m9.figshare.29652080
title: Soil Nutrient Availability Data for Agropecuária Vanguarda Property, Paraná, Brazil (2022/2023 Harvest)

description: This zipped data file contains comprehensive geospatial information on <b>soil nutrient availability</b> collected from the <b>Vanguarda Property in Paraná, Brazil</b>, during the <b>2022/2023 harvest season</b>. This dataset is part of a larger study investigating environmental sustainability and carbon balance in rural properties, contributing to the understanding of carbon credit potential.The file is organized into subfolders, each representing an individual plot/section (talhão) within the Vanguarda property. Inside each plot's folder, separate shapefiles are provided for each analyzed nutrient element.The included nutrient elements are: <b>Aluminum (Al), Boron (Br), Calcium (Ca), Potassium (K), Magnesium (Mg), Nitrogen (N), Phosphorus (P), Sulfur (S), and Zinc (Zn)</b>. The units for each nutrient represent their <b>actual availability</b> in the soil and are provided within the internal metadata of their respective shapefiles.All geospatial data uses the <b>WGS 84 (EPSG: 4326) Geodetic Coordinate Reference System (CRS)</b>.
DOI: 10.6084/m9.figshare.29652080.v2
title: Soil Nutrient Availability Data for Agropecuária Vanguarda Property, Paraná, Brazil (2022/2023 Harvest)

description: This zipped data file contains comprehensive geospatial information on <b>soil nutrient availability</b> collected from the <b>Vanguarda Property in Paraná, Brazil</b>, during the <b>2022/2023 harvest season</b>. This dataset is part of a larger study investigating environmental sustainability and carbon balance in rural properties, contributing to the understanding of carbon credit potential.The file is organized into subfolders, each representing an individual plot/section (talhão) within the Vanguarda property. Inside each plot's folder, separate shapefiles are provided for each analyzed nutrient element.The included nutrient elements are: <b>Aluminum (Al), Boron (Br), Calcium (Ca), Potassium (K), Magnesium (Mg), Nitrogen (N), Phosphorus (P), Sulfur (S), and Zinc (Zn)</b>. The units for each nutrient represent their <b>actual availability</b> in the soil and are provided within the internal metadata of their respective shapefiles.All geospatial data uses the <b>WGS 84 (EPSG: 4326) Geodetic Coordinate Reference System (CRS)</b>.
DOI: 10.6084/m9.figshare.29652080.v1
title: <b>Soil Nutrient Availability Data for Agropecuária Vanguarda Property, Paraná, Brazil (2022/2023 Harvest)</b>

description: This zipped data file contains comprehensive geospatial information on <b>soil nutrient availability</b> collected from the <b>Vanguarda Property in Paraná, Brazil</b>, during the <b>2022/2023 harvest season</b>. This dataset is part of a larger study investigating environmental sustainability and carbon balance in rural properties, contributing to the understanding of carbon credit potential.The file is organized into subfolders, each representing an individual plot/section (talhão) within the Vanguarda property. Inside each plot's folder, separate shapefiles are provided for each analyzed nutrient element.The included nutrient elements are: <b>Aluminum (Al), Boron (Br), Calcium (Ca), Potassium (K), Magnesium (Mg), Nitrogen (N), Phosphorus (P), Sulfur (S), and Zinc (Zn)</b>. The units for each nutrient represent their <b>actual availability</b> in the soil and are provided within the internal metadata of their respective shapefiles.All geospatial data uses the <b>WGS 84 (EPSG: 4326) Geodetic Coordinate Reference System (CRS)</b>.
DOI: 10.6084/m9.figshare.29652722
title: Carbon Emission and Retention Data for Bela Vista Property, Paraná, Brazil (2022/2023 Harvest)

description: This zipped data file contains comprehensive geospatial information on carbon emission and retention collected from the Bela Vista Property in Paraná, Brazil, during the 2022/2023 harvest season. This dataset is part of a larger study investigating how rural properties can become positive climate assets through innovative technological integration, including portable sensors, satellite imagery, blockchain, and AI.The file is organized into subfolders, each representing a distinct land use type and its associated carbon dynamic at the Bela Vista Property. Inside each of these folders, you'll find the corresponding shapefiles:<b>Consolidated_Area_Emission:</b> Carbon emission estimates (in tons) for consolidated agricultural areas.<b>Consolidated_Area_Crop_Retention:</b> Carbon retention estimates (in tons) specifically from crop cultivation within consolidated agricultural areas.<b>Consolidated_Area_Soil_Retention:</b> Soil organic carbon retention estimates (in tons) within consolidated agricultural areas.<b>Legal_Reserve_Forest_Retention:</b> Carbon retention estimates (in tons) for native forest areas designated as Legal Reserves.<b>Legal_Reserve_Soil_Retention:</b> Soil organic carbon retention estimates (in tons) within Legal Reserve areas.All geospatial data uses the WGS 84 (EPSG: 4326) Geodetic Coordinate Reference System (CRS).
DOI: 10.6084/m9.figshare.29652722.v2
title: Carbon Emission and Retention Data for Bela Vista Property, Paraná, Brazil (2022/2023 Harvest)

description: This zipped data file contains comprehensive geospatial information on carbon emission and retention collected from the Bela Vista Property in Paraná, Brazil, during the 2022/2023 harvest season. This dataset is part of a larger study investigating how rural properties can become positive climate assets through innovative technological integration, including portable sensors, satellite imagery, blockchain, and AI.The file is organized into subfolders, each representing a distinct land use type and its associated carbon dynamic at the Bela Vista Property. Inside each of these folders, you'll find the corresponding shapefiles:<b>Consolidated_Area_Emission:</b> Carbon emission estimates (in tons) for consolidated agricultural areas.<b>Consolidated_Area_Crop_Retention:</b> Carbon retention estimates (in tons) specifically from crop cultivation within consolidated agricultural areas.<b>Consolidated_Area_Soil_Retention:</b> Soil organic carbon retention estimates (in tons) within consolidated agricultural areas.<b>Legal_Reserve_Forest_Retention:</b> Carbon retention estimates (in tons) for native forest areas designated as Legal Reserves.<b>Legal_Reserve_Soil_Retention:</b> Soil organic carbon retention estimates (in tons) within Legal Reserve areas.All geospatial data uses the WGS 84 (EPSG: 4326) Geodetic Coordinate Reference System (CRS).
DOI: 10.6084/m9.figshare.29652722.v1
title: <b>Carbon Emission and Retention Data for Bela Vista Property, Paraná, Brazil (2022/2023 Harvest)</b>

description: This zipped data file contains comprehensive geospatial information on carbon emission and retention collected from the Bela Vista Property in Paraná, Brazil, during the 2022/2023 harvest season. This dataset is part of a larger study investigating how rural properties can become positive climate assets through innovative technological integration, including portable sensors, satellite imagery, blockchain, and AI.The file is organized into subfolders, each representing a distinct land use type and its associated carbon dynamic at the Bela Vista Property. Inside each of these folders, you'll find the corresponding shapefiles:<b>Consolidated_Area_Emission:</b> Carbon emission estimates (in tons) for consolidated agricultural areas.<b>Consolidated_Area_Crop_Retention:</b> Carbon retention estimates (in tons) specifically from crop cultivation within consolidated agricultural areas.<b>Consolidated_Area_Soil_Retention:</b> Soil organic carbon retention estimates (in tons) within consolidated agricultural areas.<b>Legal_Reserve_Forest_Retention:</b> Carbon retention estimates (in tons) for native forest areas designated as Legal Reserves.<b>Legal_Reserve_Soil_Retention:</b> Soil organic carbon retention estimates (in tons) within Legal Reserve areas.All geospatial data uses the WGS 84 (EPSG: 4326) Geodetic Coordinate Reference System (CRS).
DOI: 10.6084/m9.figshare.29652752
title: Carbon Emission and Retention Data for Perpetuo Socorro Property, Paraná, Brazil (2022/2023 Harvest)

description: This zipped data file contains comprehensive geospatial information on carbon emission and retention collected from the Perpetuo Socorro Property in Paraná, Brazil, during the 2022/2023 harvest season. This dataset is part of a larger study investigating how rural properties can become positive climate assets through innovative technological integration, including portable sensors, satellite imagery, blockchain, and AI.The file is organized into subfolders, each representing a distinct land use type and its associated carbon dynamic at the Bela Vista Property. Inside each of these folders, you'll find the corresponding shapefiles:<b>Consolidated_Area_Emission:</b> Carbon emission estimates (in tons) for consolidated agricultural areas.<b>Consolidated_Area_Crop_Retention:</b> Carbon retention estimates (in tons) specifically from crop cultivation within consolidated agricultural areas.<b>Consolidated_Area_Soil_Retention:</b> Soil organic carbon retention estimates (in tons) within consolidated agricultural areas.<b>Legal_Reserve_Forest_Retention:</b> Carbon retention estimates (in tons) for native forest areas designated as Legal Reserves.<b>Legal_Reserve_Soil_Retention:</b> Soil organic carbon retention estimates (in tons) within Legal Reserve areas.All geospatial data uses the WGS 84 (EPSG: 4326) Geodetic Coordinate Reference System (CRS).
DOI: 10.6084/m9.figshare.29652752.v2
title: Carbon Emission and Retention Data for Perpetuo Socorro Property, Paraná, Brazil (2022/2023 Harvest)

description: This zipped data file contains comprehensive geospatial information on carbon emission and retention collected from the Perpetuo Socorro Property in Paraná, Brazil, during the 2022/2023 harvest season. This dataset is part of a larger study investigating how rural properties can become positive climate assets through innovative technological integration, including portable sensors, satellite imagery, blockchain, and AI.The file is organized into subfolders, each representing a distinct land use type and its associated carbon dynamic at the Bela Vista Property. Inside each of these folders, you'll find the corresponding shapefiles:<b>Consolidated_Area_Emission:</b> Carbon emission estimates (in tons) for consolidated agricultural areas.<b>Consolidated_Area_Crop_Retention:</b> Carbon retention estimates (in tons) specifically from crop cultivation within consolidated agricultural areas.<b>Consolidated_Area_Soil_Retention:</b> Soil organic carbon retention estimates (in tons) within consolidated agricultural areas.<b>Legal_Reserve_Forest_Retention:</b> Carbon retention estimates (in tons) for native forest areas designated as Legal Reserves.<b>Legal_Reserve_Soil_Retention:</b> Soil organic carbon retention estimates (in tons) within Legal Reserve areas.All geospatial data uses the WGS 84 (EPSG: 4326) Geodetic Coordinate Reference System (CRS).
DOI: 10.15468/dl.ankwp5
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acmella uliginosa",
 "Country is Micronesia (Federated States of)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0089204-250717081556266/datasets/export for details.
DOI: 10.6084/m9.figshare.29652752.v1
title: Carbon Emission and Retention Data for Perpetuo Socorro Property, Paraná, Brazil (2022/2023 Harvest)

description: This zipped data file contains comprehensive geospatial information on carbon emission and retention collected from the Perpetuo Socorro Property in Paraná, Brazil, during the 2022/2023 harvest season. This dataset is part of a larger study investigating how rural properties can become positive climate assets through innovative technological integration, including portable sensors, satellite imagery, blockchain, and AI.The file is organized into subfolders, each representing a distinct land use type and its associated carbon dynamic at the Bela Vista Property. Inside each of these folders, you'll find the corresponding shapefiles:<b>Consolidated_Area_Emission:</b> Carbon emission estimates (in tons) for consolidated agricultural areas.<b>Consolidated_Area_Crop_Retention:</b> Carbon retention estimates (in tons) specifically from crop cultivation within consolidated agricultural areas.<b>Consolidated_Area_Soil_Retention:</b> Soil organic carbon retention estimates (in tons) within consolidated agricultural areas.<b>Legal_Reserve_Forest_Retention:</b> Carbon retention estimates (in tons) for native forest areas designated as Legal Reserves.<b>Legal_Reserve_Soil_Retention:</b> Soil organic carbon retention estimates (in tons) within Legal Reserve areas.All geospatial data uses the WGS 84 (EPSG: 4326) Geodetic Coordinate Reference System (CRS).
DOI: 10.15468/dl.98tdx8
title: Occurrence Download

description: A dataset containing 23 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Catharanthus roseus",
 "Country is Fiji",
 "HasCoordinate is true"
 ]
}

 The dataset includes 23 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0089208-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.styhf6
title: Occurrence Download

description: A dataset containing 724 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Coccyzus rufigularis)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "License is one of (CC-BY 4.0, CC0 1.0)"
 ]
}

 The dataset includes 724 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0089207-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tz5qn3
title: Occurrence Download

description: A dataset containing 31017 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Symphoricarpos albus",
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "HasCoordinate is true"
 ]
}

 The dataset includes 31017 records from 106 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0089206-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5n7qx2
title: Occurrence Download

description: A dataset containing 2396 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Coccyzus vetula)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "License is one of (CC-BY 4.0, CC0 1.0)"
 ]
}

 The dataset includes 2396 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0089209-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.669xwa
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Paspalum urvillei",
 "Country is Malaysia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0089210-250717081556266/datasets/export for details.