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Cited by 24Plant Water Relations and Carbon DynamicsRemote Sensing in AgricultureAtmospheric and Environmental Gas Dynamics

The DOI matches its Crossref record; 293 of the 293 references it cites were found in a registry or an index.

CEDAR-GPP: spatiotemporally upscaled estimates of gross primary productivity incorporating CO 2 fertilization

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Kang, Yanghui, Bassiouni, Maoya, Gaber, Max, Lu, Xinchen, Keenan, Trevor F.·2025·Earth System Science Data
DOI 10.5194/essd-17-3009-2025

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Abstract

Gross primary productivity (GPP) is the largest carbon flux in the Earth system, playing a crucial role in removing atmospheric carbon dioxide and providing carbohydrates needed for ecosystem metabolism. Despite the importance of GPP, however, existing estimates present significant uncertainties and discrepancies. A key issue is the underrepresentation of the CO 2 fertilization effect, a major factor contributing to the increased terrestrial carbon sink over recent decades. This omission could potentially bias our understanding of ecosystem responses to climate change. Here, we introduce CEDAR-GPP, the first global machine-learning-upscaled GPP product that incorporates the direct CO 2 fertilization effect on photosynthesis. Our product is comprised of monthly GPP estimates and their uncertainty at 0.05° resolution from 1982 to 2020, generated using a comprehensive set of eddy covariance measurements, multi-source satellite observations, climate variables, and machine learning models. Importantly, we used both theoretical and data-driven approaches to incorporate the direct CO 2 effects. Our machine learning models effectively predict monthly GPP ( R 2 ∼ 0.72), the mean seasonal cycles ( R 2 ∼ 0.77), and spatial variabilities ( R 2 ∼ 0.63) based on cross-validation at flux sites. After incorporating the direct CO 2 effects, the predicted long-term GPP trend across global flux towers substantially increases from 3.1 to 4.5–5.4 gC m −2 yr −1 , which aligns more closely with the 7.7 gC m −2 yr −1 trend detected from eddy covariance data. While the global patterns of annual mean GPP, seasonality, and interannual variability generally align with existing satellite-based products, CEDAR-GPP demonstrates higher long-term trends globally after incorporating CO 2 fertilization and reflected a strong temperature control on direct CO 2 effects. The estimated global GPP trend is 0.57–0.76 PgC yr −1 from 2001 to 2018 and 0.32–0.34 PgC yr −1 from 1982 to 2018. Estimating and validating GPP trends in data-scarce regions, such as the tropics, remains challenging, underscoring the importance of ongoing ground-based monitoring and advancements in modeling techniques. CEDAR-GPP offers a comprehensive representation of GPP temporal and spatial dynamics, providing valuable insights into ecosystem–climate interactions. The CEDAR-GPP product is available at https://doi.org/10.5281/zenodo.8212706 (Kang et al., 2024).

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Items 201–293 of 293

Research works printed but not linked: 2

  1. Lundberg, S. M. and Lee, S.-I.: A Unified Approach to Interpreting Model Predictions, in: Proceedings of the 31st International Conference on Neural Information Processing Systems (NIPS 2017), Long Beach, California, USA, 4768–4777, https://dl.acm.org/doi/10.5555/3295222.3295230 (last access: 31 March 2025), 2017. · DOI
  2. Zhang, Y.: A global spatially contiguous solar-induced fluorescence (CSIF) dataset using neural networks (2000–2020), National Tibetan Plateau Data Center [data set], 10.11888/Ecolo.tpdc.271751., 2021. · DOI

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Metadata

Authors
Kang, Y., Bassiouni, M., Gaber, M., Lu, X., & Keenan, T. F.
Affiliations
  • Lawrence Berkeley National Laboratory (US)
  • University of Copenhagen (DK)
ORCID
Venue
Earth System Science Data
Publisher
Copernicus GmbH
Published
2025-06-30
Volume
17
Issue
6
Pages
3009-3046
ISSN
  • 1866-3508 (ISSN-L)
  • 1866-3516
DOI
10.5194/essd-17-3009-2025
OpenAlex
W4411792583
Cited by
22
References
292
Citations by year
2026: 11 · 2025: 8
FWCI
7.80
Type
journal article
Language
en
Open access
Licence
Locations
  • Earth system science data (publishedVersion, cc-by)
  • Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, cc-by)
  • EarthArXiv (California Digital Library) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • U.S. Department of Energy (DE-SC0021023)
  • National Aeronautics and Space Administration (80NSSC21K1705, 80NSSC24K1562, 80NSSC20K1801, 80NSSC25K7327)
  • U.S. Department of Agriculture (2023-67012-40086)
Topics
  • Physical Sciences › Environmental Science › Global and Planetary Change › Plant Water Relations and Carbon Dynamics
  • Physical Sciences › Environmental Science › Ecology › Remote Sensing in Agriculture
  • Physical Sciences › Environmental Science › Global and Planetary Change › Atmospheric and Environmental Gas Dynamics
Keywords
gross primary productivity, CO2 fertilization, terrestrial carbon sink, eddy covariance flux towers, seasonal cycle, interannual variability, temperature effects on photosynthesis, satellite observations, data-scarce regions, climate-ecosystem interactions, uncertainty estimation

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