Partitioning Net Ecosystem Exchange (NEE) of CO2 Using Solar-Induced Chlorophyll Fluorescence (SIF)

  • O. Kira
  • , C. Y-Y. Chang
  • , L. Gu
  • , J. Wen
  • , Z. Hong
  • , Y. Sun

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

Accurate partitioning of net ecosystem exchange (NEE) of CO2 to gross primary production (GPP) and ecosystem respiration (Reco) is crucial for understanding carbon cycle dynamics under changing climate. However, it remains as a long-standing problem in global ecology due to lack of independent constraining information for the two offsetting component fluxes. solar-induced chlorophyll fluorescence (SIF), a mechanistic proxy for photosynthesis, holds great promise to improve NEE partitioning by constraining GPP. We developed a parsimonious SIF-based approach for NEE partitioning and examined its performance using synthetic simulations and field measurements. This approach outperforms conventional approaches in reproducing simulated GPP and Reco, especially under high vapor pressure deficit. For field measurements, it results in lower daytime GPP and Reco than conventional approaches. This study made the first attempt to demonstrate SIF's potential for improving NEE partitioning accuracy and sets the stage for future efforts to examine its robustness and scalability under real-world environmental conditions.

Original languageEnglish
Article numbere2020GL091247
JournalGeophysical Research Letters
Volume48
Issue number4
DOIs
StatePublished - Feb 28 2021

Funding

The authors acknowledge the support from the United States‐Israel Binational Agricultural Research and Development Fund, Vaadia‐BARD Postdoctoral Fellowship (FI‐576‐18), NSF Macrosystem Biology (Award 1926488), the NASA Earth Science Division MEaSUREs program, USDA‐NIFA postdoctoral fellowship (2018‐67012‐27985), USDA‐NIFA Hatch Project Award 1014740. L. Gu was supported by the U.S. Department of Energy (DOE), Office of Science, Biological and Environmental Research Program. ORNL is managed by UT‐Battelle, LLC, for DOE under contract DE‐AC05‐00OR22725.

Keywords

  • GPP
  • NEE partitioning
  • R
  • SIF

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