Phenology-Based Maximum Light Use Efficiency for Modeling Gross Primary Production across Typical Terrestrial Ecosystems

The maximum light use efficiency (LUE) (e(0)) is a key essential parameter of the LUE model, and its accurate estimation is crucial for quantifying gross primary production (GPP) and better understanding the global carbon budget. Currently, a comprehensive understanding of the potential of seasonal variations of e(0) in GPP estimation across different plant functional types (PFTs) is still lacking. In this study, we used a phenology-based strategy for the estimation of e(0) to find the optimal photosynthetic responses of the parameter in different phenological stages. The start and end of growing season (SOS and EOS) from time series vegetation indices and the camera-derived greenness index were extracted across seven PFT flux sites using the methods of the hybrid generalized additive model (HGAM) and double logistic function (DLF). Optimal extractions of SOS and EOS were evaluated, and the e0 was estimated from flux site observations during the optimal phenological stages with the light response equation. Coupled with other obligatory parameters of the LUE model, phenology-based GPP (GPP(phe-based)) was estimated over 21 site-years and compared with vegetation photosynthesis model (VPM)-based GPP (GPP(VPM)) and eddy covariance-measured GPP (GPP(EC)). Generally, GPP(phe-based) basically tracked both the seasonal dynamics and inter-annual variation of GPP(EC )well, especially at forest, cropland, and wetland flux sites. The R-2 between GPP(phe-based) and GPP(EC) was stable between 0.85 and 0.95 in forest ecosystems, between 0.75 and 0.85 in cropland ecosystems, and around 0.9 in wetland ecosystems. Furthermore, we found that GPP(phe-based) was significantly improved compared to GPPVPM in cropland, grassland, and wetland ecosystems, implying that phenology-based e(0 )is more appropriate in the GPP estimation of herbaceous plants. In addition, we found that GPP(phe-based) was significantly improved over GPP(VPM) in cropland, grassland, and wetland ecosystems, and the R-2 between GPP(phe-based) and GPP(EC) was improved by up to 0.11 in cropland ecosystems and 0.05 in wetland ecosystems compared to GPPVPM, and RMSE was reduced by up to 5.90 and 2.11 g C m(-2) 8 day(-1), respectively, implying that phenology-based e(0) in herbaceous plants is more appropriate for GPP estimation. This work highlights the potential of phenology-based e0 in understanding the seasonal variation of vegetation photosynthesis and production.