cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.gu8n99
title: Occurrence Download

description: A dataset containing 273211 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Calopteryx splendens Harris, 1780"
 ]
}

 The dataset includes 273211 records from 1174 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0174222-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.38wsh4
title: Occurrence Download

description: A dataset containing 207 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acacia melanoxylon R.Br.",
 "Country is Bolivia (Plurinational State of)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 207 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080166-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.12637100
title: CFATD: The First High-Spatiotemporal-Resolution Mapping of Forest Aboveground Biomass in China from 1985 to 2023 (Part Ⅱ: 1994-2001)

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.12637101
title: CFATD: The First High-Spatiotemporal-Resolution Mapping of Forest Aboveground Biomass in China from 1985 to 2023 (Part Ⅱ: 1994-2001)

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: 10.7910/dvn/grbqh4
title: Replication Data for: Countering Online Abuse of Politicians Through Information About Consequences and Norms

description: In recent years, a growing body of research has documented how both local and national politi-cians experience insults, sexism, and even threats on social media platforms. Studies show that such online abuse can have serious democratic consequences and negatively impact politicians’ mental health and wellbeing. We investigate whether online abuse directed at politicians can be countered by providing citizens with information regarding such abuse. Specifically, we examine whether information about how abusive comments (1) hurt individual politicians, (2) violate social norms, and (3) undermine democratic quality can influence citizens’ abuse tolerance and their willingness to engage in behaviours that counter online abuse on social media. We test our preregistered hypotheses in a survey experiment using a sample of 2,000 Danish citizens. Our results show that information about consequences and norms regarding online abuse does not significantly affect citizens’ tolerance of abusive online behaviour. However, it can increase citizens’ willingness to engage in behaviours that counter instances of online abuse, such as writing a comment to support the targeted politician or reporting the abusive comment to the social media site.
DOI: 10.5281/zenodo.12655491
title: CFATD: The First High-Spatiotemporal-Resolution Mapping of Forest Aboveground Biomass in China from 1985 to 2023 (Part Ⅲ: 2002-2008)

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.12655492
title: CFATD: The First High-Spatiotemporal-Resolution Mapping of Forest Aboveground Biomass in China from 1985 to 2023 (Part Ⅲ: 2002-2008)

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: 10.34740/kaggle/dsv/12327954
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.ghx5rf
title: Occurrence Download

description: A dataset containing 10 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acacia melanoxylon R.Br.",
 "Country is Brazil",
 "HasCoordinate is true"
 ]
}

 The dataset includes 10 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080167-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4zdp2f
title: Occurrence Download

description: A dataset containing 404 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Regroupement d'études et d'inventaires-Données opportunistes faune"
 ]
}

 The dataset includes 404 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080168-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.12658254
title: CFATD: The First High-Spatiotemporal-Resolution Mapping of Forest Aboveground Biomass in China from 1985 to 2023 (Part Ⅳ: 2009-2015)

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.12658255
title: CFATD: The First High-Spatiotemporal-Resolution Mapping of Forest Aboveground Biomass in China from 1985 to 2023 (Part Ⅳ: 2009-2015)

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.12742209
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)