cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.12742210
title: CFATD: The First High-Spatiotemporal-Resolution Mapping of Forest Aboveground Biomass in China from 1985 to 2023 (Part Ⅴ: 2016-2021)

description: The China Annual Forest Aboveground Biomass Time-Series Dataset (CFATD) is the first comprehensive, high-resolution annual dataset specifically developed for monitoring forest aboveground biomass (AGB) across China. Covering the period from 1985 to 2023, this dataset was generated using a combination of multi-source remote sensing data and deep learning techniques, including residual neural networks. CFATD provides 30-meter resolution annual AGB density (AGBD) estimates, enabling a detailed assessment of spatiotemporal biomass dynamics in China’s forests.

CFATD is publicly available on the Google Earth Engine (GEE) platform, with updates planned annually. The dataset can be accessed via the following link:👉 https://code.earthengine.google.com/4f8ad8d32ddb84e826e941a95f31f9be

Users can explore both AGBD estimates and the corresponding uncertainty layers (available only via GEE), supporting in-depth analysis of forest biomass trends and dynamics. Please note that uncertainty estimates are not included in the Zenodo repository.

The unit of CFATD is megagrams per hectare (Mg/ha). This is a density value, already normalized per hectare, so no further conversion based on pixel area (900 m²) is required when interpreting per-pixel values. Each pixel represents the AGBD of the forest within that 30 m × 30 m grid cell. However, to compute total biomass or carbon stock, AGBD values should be multiplied by the corresponding forest area (e.g., pixel area × tree cover fraction), following the approach outlined in our related publication (Cai et al., essdd, 2025).

The tree cover dataset used in these calculations, the China Annual Tree Cover Dataset (CATCD), is available from our peer-reviewed article:👉 https://doi.org/10.1016/j.isprsjprs.2024.08.001This article provides both GEE access and offline download links for CATCD.

Important note: The dataset may contain a small number of unusually high AGB values in certain regions (e.g., >1500 Mg/ha), which may reflect outliers or model artifacts rather than actual forest conditions. While these values occur only in a very limited portion of the dataset, users are advised to apply appropriate filters or quality control procedures when conducting sensitive analyses. These issues will be addressed in future dataset updates.

Citation:Cai, Y., Zhu, P., Li, X., Liu, X., Chen, Y., Shen, Q., Xu, X., Zhang, H., Nie, S., Wang, C., Wang, J., Li, B., Wu, C., and Zhuang, H.: Dynamics of China’s Forest Carbon Storage: The First 30 m Annual Aboveground Biomass Mapping from 1985 to 2023, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2025-96, in review, 2025.

For data-related inquiries, please contact:Dr. Yaotong Cai (caiyt33@mail2.sysu.edu.cn)
DOI: 10.5281/zenodo.12747328
title: CFATD: The First High-Spatiotemporal-Resolution Mapping of Forest Aboveground Biomass in China from 1985 to 2023 (Part Ⅵ: 2022-2023)

description: The China Annual Forest Aboveground Biomass Time-Series Dataset (CFATD) is the first comprehensive, high-resolution annual dataset specifically developed for monitoring forest aboveground biomass (AGB) across China. Covering the period from 1985 to 2023, this dataset was generated using a combination of multi-source remote sensing data and deep learning techniques, including residual neural networks. CFATD provides 30-meter resolution annual AGB density (AGBD) estimates, enabling a detailed assessment of spatiotemporal biomass dynamics in China’s forests.

CFATD is publicly available on the Google Earth Engine (GEE) platform, with updates planned annually. The dataset can be accessed via the following link:👉 https://code.earthengine.google.com/4f8ad8d32ddb84e826e941a95f31f9be

Users can explore both AGBD estimates and the corresponding uncertainty layers (available only via GEE), supporting in-depth analysis of forest biomass trends and dynamics. Please note that uncertainty estimates are not included in the Zenodo repository.

The unit of CFATD is megagrams per hectare (Mg/ha). This is a density value, already normalized per hectare, so no further conversion based on pixel area (900 m²) is required when interpreting per-pixel values. Each pixel represents the AGBD of the forest within that 30 m × 30 m grid cell. However, to compute total biomass or carbon stock, AGBD values should be multiplied by the corresponding forest area (e.g., pixel area × tree cover fraction), following the approach outlined in our related publication (Cai et al., essdd, 2025).

The tree cover dataset used in these calculations, the China Annual Tree Cover Dataset (CATCD), is available from our peer-reviewed article:👉 https://doi.org/10.1016/j.isprsjprs.2024.08.001This article provides both GEE access and offline download links for CATCD.

Important note: The dataset may contain a small number of unusually high AGB values in certain regions (e.g., >1500 Mg/ha), which may reflect outliers or model artifacts rather than actual forest conditions. While these values occur only in a very limited portion of the dataset, users are advised to apply appropriate filters or quality control procedures when conducting sensitive analyses. These issues will be addressed in future dataset updates.

Citation:Cai, Y., Zhu, P., Li, X., Liu, X., Chen, Y., Shen, Q., Xu, X., Zhang, H., Nie, S., Wang, C., Wang, J., Li, B., Wu, C., and Zhuang, H.: Dynamics of China’s Forest Carbon Storage: The First 30 m Annual Aboveground Biomass Mapping from 1985 to 2023, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2025-96, in review, 2025.

For data-related inquiries, please contact:Dr. Yaotong Cai (caiyt33@mail2.sysu.edu.cn)
DOI: 10.5281/zenodo.12747329
title: CFATD: The First High-Spatiotemporal-Resolution Mapping of Forest Aboveground Biomass in China from 1985 to 2023 (Part Ⅵ: 2022-2023)

description: The China Annual Forest Aboveground Biomass Time-Series Dataset (CFATD) is the first comprehensive, high-resolution annual dataset specifically developed for monitoring forest aboveground biomass (AGB) across China. Covering the period from 1985 to 2023, this dataset was generated using a combination of multi-source remote sensing data and deep learning techniques, including residual neural networks. CFATD provides 30-meter resolution annual AGB density (AGBD) estimates, enabling a detailed assessment of spatiotemporal biomass dynamics in China’s forests.

CFATD is publicly available on the Google Earth Engine (GEE) platform, with updates planned annually. The dataset can be accessed via the following link:👉 https://code.earthengine.google.com/4f8ad8d32ddb84e826e941a95f31f9be

Users can explore both AGBD estimates and the corresponding uncertainty layers (available only via GEE), supporting in-depth analysis of forest biomass trends and dynamics. Please note that uncertainty estimates are not included in the Zenodo repository.

The unit of CFATD is megagrams per hectare (Mg/ha). This is a density value, already normalized per hectare, so no further conversion based on pixel area (900 m²) is required when interpreting per-pixel values. Each pixel represents the AGBD of the forest within that 30 m × 30 m grid cell. However, to compute total biomass or carbon stock, AGBD values should be multiplied by the corresponding forest area (e.g., pixel area × tree cover fraction), following the approach outlined in our related publication (Cai et al., essdd, 2025).

The tree cover dataset used in these calculations, the China Annual Tree Cover Dataset (CATCD), is available from our peer-reviewed article:👉 https://doi.org/10.1016/j.isprsjprs.2024.08.001This article provides both GEE access and offline download links for CATCD.

Important note: The dataset may contain a small number of unusually high AGB values in certain regions (e.g., >1500 Mg/ha), which may reflect outliers or model artifacts rather than actual forest conditions. While these values occur only in a very limited portion of the dataset, users are advised to apply appropriate filters or quality control procedures when conducting sensitive analyses. These issues will be addressed in future dataset updates.

Citation:Cai, Y., Zhu, P., Li, X., Liu, X., Chen, Y., Shen, Q., Xu, X., Zhang, H., Nie, S., Wang, C., Wang, J., Li, B., Wu, C., and Zhuang, H.: Dynamics of China’s Forest Carbon Storage: The First 30 m Annual Aboveground Biomass Mapping from 1985 to 2023, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2025-96, in review, 2025.

For data-related inquiries, please contact:Dr. Yaotong Cai (caiyt33@mail2.sysu.edu.cn)
DOI: 10.15468/dl.zjkx9c
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Mammalia",
 "Year is greater than or equal to 1900",
 "Year is less than or equal to 1990",
 "HasCoordinate is true",
 "Geometry POLYGON ((130 31, 130 32, 131 32, 131 31, 130 31))"
 ]
}

 The dataset includes 6 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080172-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.f8w3ty
title: Occurrence Download

description: A dataset containing 24967 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Mammal records for Europe via the iMammalia app"
 ]
}

 The dataset includes 24967 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080171-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.c3cjaw
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acacia melanoxylon R.Br.",
 "Country is Eswatini",
 "HasCoordinate is true"
 ]
}

 The dataset includes 12 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080173-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rfgd43
title: Occurrence Download

description: A dataset containing 31 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acacia melanoxylon R.Br.",
 "Country is India",
 "HasCoordinate is true"
 ]
}

 The dataset includes 31 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080174-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.65svyp
title: Occurrence Download

description: A dataset containing 300 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "GadmGid is one of (CHN.31_1, CHN.24_1, CHN.15_1, CHN.1_1)",
 "OccurrenceStatus is Present",
 "TaxonKey is Tadorna tadorna (Linnaeus, 1758)"
 ]
}

 The dataset includes 300 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080175-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k8w48n
title: Occurrence Download

description: A dataset containing 50 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is one of (Mosses (S), INSDC Sequences, CSIC-Real Jardín Botánico-Colección de Musgos (MA-Musci), The New York Botanical Garden Herbarium (NY), iNaturalist Research-grade Observations, Inventario Español de Especies Terrestres (MAGRAMA), Natural History Museum (London) Collection Specimens, The MOVECLIM – AZORES project: Bryophytes from Pico Island (2012), Botany (UPS), Biological Collection of the National Taiwan Museum, Taipei, Taiwan, Naturalis Biodiversity Center (NL) - Botany, Herbarium Senckenbergianum (FR), The MOVECLIM – AZORES project: Bryophytes from Terceira Island (2012))",
 "Geometry POLYGON((-34.51833 35.5778,-9.0587 21.31578,8.00287 42.47212,-22.10446 42.83084,-34.51833 42.83084,-34.51833 35.5778))",
 "TaxonKey is Tetrastichium fontanum (Mitt.) Cardot"
 ]
}

 The dataset includes 50 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080177-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.658wjc
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acacia melanoxylon R.Br.",
 "Country is Japan",
 "HasCoordinate is true"
 ]
}

 The dataset includes 4 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080179-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15735548
title: A High-Resolution, Long-Term Global Radar-Based Above-Ground Biomass Dataset from 1993 to 2020

description: This dataset provides a new global annual above-ground biomass carbon (AGC) record at an 8 km spatial resolution, covering the years 1993 to 2020. It is derived from satellite radar backscatter data and incorporates vegetation and climate information, including tree cover, tree density, and background climate data, to improve the accuracy of global AGC mapping.
DOI: 10.5281/zenodo.15735549
title: A High-Resolution, Long-Term Global Radar-Based Above-Ground Biomass Dataset from 1993 to 2020

description: This dataset provides a new global annual above-ground biomass carbon (AGC) record at an 8 km spatial resolution, covering the years 1993 to 2020. It is derived from satellite radar backscatter data and incorporates vegetation and climate information, including tree cover, tree density, and background climate data, to improve the accuracy of global AGC mapping.
DOI: 10.6084/m9.figshare.28347353.v1
title: Code for the paper "The productivity gradient explains global bird specialization better than climate stability"

description: We investigated the relative contributions of species richness, evolutionary age, long-term climate stability, and current climatic conditions (i.e., using aridity as a proxy of environmental harshness and the stress-productivity gradient), in shaping the degree of climatic, dietary, and habitat specialization in bird assemblages at a global scale. This project contains all the information necessary to replicate all the data processing and analysis performed in this study. <br>
DOI: 10.15468/dl.jfd7ve
title: Occurrence Download

description: A dataset containing 34 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acacia melanoxylon R.Br.",
 "Country is Kenya",
 "HasCoordinate is true"
 ]
}

 The dataset includes 34 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080180-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.m4r3zs
title: Occurrence Download

description: A dataset containing 19 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acacia melanoxylon R.Br.",
 "Country is Mexico",
 "HasCoordinate is true"
 ]
}

 The dataset includes 19 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080181-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/12328003
title: World Weather Repository ( Daily Updating )
DOI: 10.15468/dl.vztnm2
title: Occurrence Download

description: A dataset containing 125153 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Australia",
 "TaxonKey is Macrotis lagotis (Reid, 1837)"
 ]
}

 The dataset includes 125153 records from 38 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080157-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wgvpgv
title: Occurrence Download

description: A dataset containing 21088 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Euphorbia nicaeensis All.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 21088 records from 252 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080182-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ek9per
title: Occurrence Download

description: A dataset containing 119103 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Ligustrum pricei Hayata, Ligustrum stenophyllum Quisumb. & Merr., Ligustrum ibota Siebold, Ligustrum salicinum Nakai, Ligustrum robustum (Roxb.) Blume, Ligustrum sempervirens (Franch.) Lingelsh., Ligustrum confusum Decne., Ligustrum japonicum Thunb., Ligustrum cumingianum Decne., Ligustrum compactum (Wall. ex G.Don) Hook.f. & Thomson ex Brandis, Ligustrum sinense Lour., Ligustrum lucidum W.T.Aiton, Ligustrum lianum P.S.Hsu, Ligustrum nepalense Wall., Ligustrum liukiuense Koidz., Ligustrum expansum Rehder, Ligustrum glomeratum Blume, Ligustrum minii Raizada, Ligustrum ovalifolium Hassk., Ligustrum leucanthum (S.Moore) P.S.Green)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 119103 records from 785 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080158-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pb3c9h
title: Occurrence Download

description: A dataset containing 457 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acacia melanoxylon R.Br.",
 "Country is New Zealand",
 "HasCoordinate is true"
 ]
}

 The dataset includes 457 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080185-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cq3xh6
title: Occurrence Download

description: A dataset containing 1878 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acacia melanoxylon R.Br.",
 "Country is South Africa",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1878 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080188-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.t8am6u
title: Occurrence Download

description: A dataset containing 5297 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acacia melanoxylon R.Br.",
 "Country is Portugal",
 "HasCoordinate is true"
 ]
}

 The dataset includes 5297 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080187-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.szkgmb
title: Occurrence Download

description: A dataset containing 37 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "OccurrenceStatus is Present",
 "TaxonKey is Phoebe hui Cheng ex Yen C.Yang"
 ]
}

 The dataset includes 37 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080190-250525065834625/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.29436095
title: Table 2. The data set was obtained in Sapporo Maruyama Zoo and used for this study's analysis.

description: The data set was obtained in Sapporo Maruyama Zoo and used for this study's analysis.
DOI: 10.6084/m9.figshare.29436095.v1
title: Table 2. The data set was obtained in Sapporo Maruyama Zoo and used for this study's analysis.

description: The data set was obtained in Sapporo Maruyama Zoo and used for this study's analysis.
DOI: 10.21947/1775531
title: NREL - GE 1.5MW SLE Wind Turbine / Reviewed Data

description: This dataset is intended to be a public resource for anyone conducting wind turbine noise research. It contains noise spectra and equivalent sound pressure levels at 11 measurement stations. The dataset also contains wind turbine operational data and meteorological data from a met mast directly upstream of the wind turbine.
DOI: 10.6084/m9.figshare.29436260
title: database figshare.xlsx

description: <b>Fibromyalgia (FM) is a chronic, female-predominant condition characterized by widespread musculoskeletal pain and frequent gastrointestinal (GI) symptoms. Its overlap with irritable bowel syndrome (IBS) suggests shared pathophysiological mechanisms. Yet, few studies have explored the relationship between GI symptoms and psychological features across FM-only, IBS-only, and FM+IBS groups. </b><b>This cross-sectional study included 53 adults, categorized as FM-only, IBS-only, or FM+IBS. Participants underwent a comprehensive assessment.</b>
DOI: 10.6084/m9.figshare.29436260.v1
title: database figshare.xlsx

description: <b>Fibromyalgia (FM) is a chronic, female-predominant condition characterized by widespread musculoskeletal pain and frequent gastrointestinal (GI) symptoms. Its overlap with irritable bowel syndrome (IBS) suggests shared pathophysiological mechanisms. Yet, few studies have explored the relationship between GI symptoms and psychological features across FM-only, IBS-only, and FM+IBS groups. </b><b>This cross-sectional study included 53 adults, categorized as FM-only, IBS-only, or FM+IBS. Participants underwent a comprehensive assessment.</b>
DOI: 10.15468/dl.y9d7gj
title: Occurrence Download

description: A dataset containing 1172 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acacia melanoxylon R.Br.",
 "Country is Spain",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1172 records from 37 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080192-250525065834625/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.29436281
title: Supplementary_table.xlsx

description: Extrachromosomal circular DNA (ecDNA) is a predominant driver of oncogenic copy-number amplifications across diverse tumor types, however, there is currently no clinically validated non-invasive method for its detection. In this study, we present a cfDNA fragmentation profiling approach that leverages the increased abundance of short DNA fragments within amplified genomic regions as a biomarker for gene amplification events. We utilized metrics, such as fragment size entropy, motif diversity score, and weighted fragment size as features to develop gene-specific machine learning classifiers and validated their performance using somatic panel sequencing data from liquid-biopsy samples of cancer patients. This approach circumvents dependence on conventional read-depth analyses while achieving robust performance. Collectively, our results establish cfDNA fragmentation profiling as a powerful, reliable, and minimally invasive method for detecting amplifications.