Multi-site evaluation of an improved SIF-based model for estimating canopy GPP
Abstract
Sun-induced chlorophyll fluorescence (SIF) offers a promising path to quantify gross primary productivity (GPP) across spatiotemporal scales. Recent studies have demonstrated the applicability of the SIF-based mechanistic light response (qMLR-SIF) model for estimating canopy GPP. However, the inadequate simulation of the key parameter qL (the fraction of open photosystem II reaction centers) restricts the applicability of the qMLR-SIF model. Therefore, we developed a SIF-based qL function to improve the simulation of qL, and thereby to enhance the performance of the qMLR-SIF model. Tower-based datasets collected from 16 sites were utilized to evaluate the improved qMLR-SIF model. Multi-site validation indicated that the improved qMLR-SIF model enhanced the accuracy of canopy GPP estimation for different plant functional types, photosynthetic pathways, and temporal scales. In particular, the improved qMLR-SIF model significantly reduced the underestimation and overestimation of GPP (y-slope = 0.94 to 1.05; y-intercept = -0.94 to 0.74 μmol CO2 m-2 s-1). Threshold analysis showed that environmental stresses decreased model performance, while even in this situation, the improved qMLR-SIF model still outperformed the original model (except for the boreal evergreen needleleaf forests). The advantages of the SIF-based qL function stem from the mechanistic link between SIF and qL and several unique features of SIF. Our findings demonstrate the enhanced applicability of the improved qMLR-SIF model, highlighting its potential for estimating photosynthesis at regional and global scales.
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BibTeX
@misc{liu2026multisite,
title = {{Multi-site evaluation of an improved SIF-based model for estimating canopy GPP}},
author = {Yanping Liu and Genxu Wang and Zhaoyong Hu and Arthur Gessler and Shouqin Sun},
howpublished = {EarthArXiv},
year = {2026},
month = oct,
doi = {10.31223/x5m80r},
url = {https://eartharxiv.org/repository/view/15313/},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Multi-site evaluation of an improved SIF-based model for estimating canopy GPP
AU - Yanping Liu
AU - Genxu Wang
AU - Zhaoyong Hu
AU - Arthur Gessler
AU - Shouqin Sun
PY - 2026
DA - 2026/10/01
PB - EarthArXiv
DO - 10.31223/x5m80r
UR - https://eartharxiv.org/repository/view/15313/
AB - Sun-induced chlorophyll fluorescence (SIF) offers a promising path to quantify gross primary productivity (GPP) across spatiotemporal scales. Recent studies have demonstrated the applicability of the SIF-based mechanistic light response (qMLR-SIF) model for estimating canopy GPP. However, the inadequate simulation of the key parameter qL (the fraction of open photosystem II reaction centers) restricts the applicability of the qMLR-SIF model. Therefore, we developed a SIF-based qL function to improve the simulation of qL, and thereby to enhance the performance of the qMLR-SIF model. Tower-based datasets collected from 16 sites were utilized to evaluate the improved qMLR-SIF model. Multi-site validation indicated that the improved qMLR-SIF model enhanced the accuracy of canopy GPP estimation for different plant functional types, photosynthetic pathways, and temporal scales. In particular, the improved qMLR-SIF model significantly reduced the underestimation and overestimation of GPP (y-slope = 0.94 to 1.05; y-intercept = -0.94 to 0.74 μmol CO2 m-2 s-1). Threshold analysis showed that environmental stresses decreased model performance, while even in this situation, the improved qMLR-SIF model still outperformed the original model (except for the boreal evergreen needleleaf forests). The advantages of the SIF-based qL function stem from the mechanistic link between SIF and qL and several unique features of SIF. Our findings demonstrate the enhanced applicability of the improved qMLR-SIF model, highlighting its potential for estimating photosynthesis at regional and global scales.
ER -