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A long-term gridded dataset of aboveground net primary productivity for global natural grasslands
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  • Published: 27 February 2026

A long-term gridded dataset of aboveground net primary productivity for global natural grasslands

  • Ziwei Chen1,2,
  • Dongsheng Zhao2,
  • Zhiyuan Zhang1,
  • Liming Zhang1 &
  • …
  • Du Zheng2 

Scientific Data , Article number:  (2026) Cite this article

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We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Agroecology
  • Carbon cycle
  • Grassland ecology

Abstract

A long-term dataset of aboveground net primary productivity (ANPP) for global natural grasslands is essential for carbon dynamics modeling and sustainable land management. However, existing datasets are limited: they often fail to separate above- and below-ground productivity or reflect only post-disturbance conditions. To address these gaps, we developed a gridded annual ANPP dataset using machine learning, spanning historical (1958–2023) and future (2015–2100) periods. Historical ANPP data were derived from TerraClimate at 1/24° spatial resolution, while future projections came from CMIP6 models under SSP245 and SSP585 scenarios at 1/2° resolution. Our model performed robustly (R2 = 0.675 ± 0.009), showing temporal and spatial reliability through cross-validation with published products. Notably, systematic ANPP underestimation occurs in high-productivity regions (>700 g m−2) due to sparse field observations, so values in these areas should be interpreted with caution. Our dataset provides a spatially explicit baseline of climate-driven productivity, supporting precise evaluation of human impacts on grasslands and informing adaptive management under climate change.

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Data availability

The data supporting this study and the ANPP dataset generated in this study are publicly available at https://doi.org/10.5281/zenodo.18171957.

Code availability

The R code supporting this study is available at https://doi.org/10.5281/zenodo.18171957.

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Acknowledgements

The research presented in this paper were funded by the National Natural Science Foundation of China (42207477 & 42271489), the Natural Science Foundation Program of Fujian Province, China (2024J01412), and the Science and Technology Innovation Fund Project of Fujian Agriculture and Forestry University (KFB24131A).

Author information

Authors and Affiliations

  1. University Key Lab of Soil Ecosystem Health and Regulation in Fujian, College of Resources and Environment, Fujian Agriculture and Forestry University, Fuzhou, 350002, China

    Ziwei Chen, Zhiyuan Zhang & Liming Zhang

  2. Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China

    Ziwei Chen, Dongsheng Zhao & Du Zheng

Authors
  1. Ziwei Chen
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  2. Dongsheng Zhao
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  3. Zhiyuan Zhang
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  4. Liming Zhang
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  5. Du Zheng
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Contributions

Dongsheng Zhao and Ziwei Chen conceptualized the study. Ziwei Chen generated the dataset and drafted the work. Zhiyuan Zhang conducted quality control on the dataset. All authors contributed to preparing the manuscript and approved the submission.

Corresponding authors

Correspondence to Dongsheng Zhao or Zhiyuan Zhang.

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Chen, Z., Zhao, D., Zhang, Z. et al. A long-term gridded dataset of aboveground net primary productivity for global natural grasslands. Sci Data (2026). https://doi.org/10.1038/s41597-026-06944-7

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  • Received: 25 September 2025

  • Accepted: 19 February 2026

  • Published: 27 February 2026

  • DOI: https://doi.org/10.1038/s41597-026-06944-7

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