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CEDAR-GPP: spatiotemporally upscaled estimates of gross primary productivity incorporating CO2 fertilization

CEDAR-GPP: spatiotemporally upscaled estimates of gross primary productivity incorporating CO2 fertilization

This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.5194/essd-17-3009-2025. This is version 1 of this Preprint.

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Authors

Yanghui Kang, Max Gaber, Maoya Bassiouni, Xinchen Lu, Trevor Keenan

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 the sugars and starches 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 CO2 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 upscaled GPP pr...  more

DOI

https://doi.org/10.31223/X5R957

Subjects

Earth Sciences, Physical Sciences and Mathematics

Keywords

gross primary productivity, CO2 fertilization, remote sensing, machine learning

Dates

Published: 2023-08-09 17:38

Last Updated: 2023-08-10 00:38

License

CC BY Attribution 4.0 International

Additional Metadata

Data Availability (Reason not available):
https://doi.org/10.5281/zenodo.8212707