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CEDAR-GPP: spatiotemporally upscaled estimates of global photosynthesis incorporating CO2 fertilization

Presentation Date
Thursday, December 14, 2023 at 8:30am - Thursday, December 14, 2023 at 12:50pm
Location
MC - Poster Hall A-C - South
Authors

Author

Abstract

Gross primary productivity (GPP) is the largest carbon flux in the Earth system, playing a crucial role in supporting ecosystem metabolism and sequestering atmospheric carbon dioxide (CO2). However, existing GPP estimates present significant uncertainties and discrepancies, partly due to the underrepresentation of the CO2 fertilization effect, which has enhanced the terrestrial carbon sink over recent decades. We introduce CEDAR (sCaling Ecosystem Dynamics with ARtifical intelligence) -GPP, the first global upscaled GPP dataset integrating the direct CO2 fertilization effect on photosynthesis. CEDAR-GPP was generated by synthesizing globally distributed eddy covariance measurements of carbon fluxes, multi-source satellite observations, and climate variables using machine learning models. Our models effectively predicted monthly GPP (R2 ~ 0.74), the mean seasonal cycles (R2 ~ 0.79), and spatial variabilities (R2 ~ 0.67). Importantly, incorporating direct CO2 effects substantially improved the models’ capability to reproduce long-term GPP trends across global flux sites. While aligning with existing satellite-based products on the global patterns of annual mean GPP, seasonality, and interannual variability, CEDAR-GPP shows elevated long-term trends, particularly in the tropics. This reflects a strong temperature control on the response of light use efficiency to CO2. Available at a 0.05º monthly resolution from 1982 to 2020, CEDAR-GPP offers a comprehensive representation of global GPP spatiotemporal dynamics, providing valuable insights into ecosystem-climate interactions.

Category
Biogeosciences
Funding Program Area(s)