## 4 Discussion  
The \(\mathrm{LUE_{max}}\) and FPAR are important parameters in the LUE model. We found that the \(\mathrm{LUE_{max}}\) was 1.5056 g C MJ\({}^{-1}\) on cloudy days and 1.2367 g C MJ\({}^{-1}\) on sunny days, and the fitted equations of FPAR and LAI, NDVI were: FPAR = \(1-\mathrm{e}^{-0.5052^{\mathrm{t}}\mathrm{LAI}}\), FPAR = \(1.2018^{\mathrm{s}}\mathrm{NDVI}-0.2583\) (Figure 2 andFigure 3). [PERSON] and [PERSON] [46] stated in the user guide of the MOD17 product that the \(\mathrm{LUE_{max}}\) for a deciduous broad-leaf forest was 1.1165 g C MJ\({}^{-1}\). [PERSON] et al. [47] considered that the extinction coefficient of multiple vegetation types could be set to 0.50, and [PERSON] et al. [48] found that the slope and intercept of the fitted curve of FPAR and NDVI for deciduous broad-leaf forests were 1.24 and \(-0.168\), respectively. Further, [PERSON] et al. [29] pointed out that as the CI decreases, the LUE gradually increases. These results are in agreement with ours. At present, some studies suggest that \(\mathrm{LUE_{max}}\) varies with the model structure, resulting in a large difference in \(\mathrm{LUE_{max}}\) for the same species in different LUE models. For example, in the Wang model, the \(\mathrm{LUE_{max}}\) was set to 2.97 g C MJ\({}^{-1}\)[40], and in the Carbon Fix model (C-Fix), it was only 1.10 g C MJ\({}^{-1}\)[49]. Through model parameter optimization, [PERSON] et al. [10] found that the variation range of \(\mathrm{LUE_{max}}\) in different model structures of the same grassland site was  
Figure 8: Comparison of daily gross primary production (GPP) simulated by MOD17 (**a**), MODTEM (**b**), EC-LUE (**c**), ECM-LUE (**d**), SM-LUE (**e**), GLO-PEM (**f**), Wang (**g**), and ECM-LUE+GLO-PEM\({}_{\mathrm{p}\mathrm{p}\mathrm{s}}\) (**h**) models versus observed GPP. ECM-LUE+GLO-PEM\({}_{\mathrm{p}\mathrm{s}\mathrm{i}}\) means the combination of ECM-LUE model on cloudy days and the GLO-PEM\({}_{\mathrm{p}\mathrm{s}\mathrm{i}}\) model on sunny days. Solid dots represent cloudy days, and the open circle dots represent sunny days. The subscript plant water stress index (PWSI) indicates that PWSI was used to modify the water stress scalar in the LUE model. Data from July–September 2021 and May–June 2022. The red line is the fitting curve. 0.70-1.94 g C MJ\({}^{-1}\). However, LUE\({}_{\text{max}}\) is a characteristic parameter of plants, which is related to the plant species and leaf nitrogen content, among other factors [50]. The initial quantum efficiency is an important parameter to characterize the maximum light energy conversion efficiency in photosynthesis; when determining this parameter, photosynthesis is mainly limited by light intensity. Therefore, in the present study, LUE\({}_{\text{max}}\) was determined using the photosynthesis light-response curve of the plantation. The same method was adopted by [PERSON] et al. [13]. Model structural differences are considered the most important source of uncertainty in estimating GPP based on LUE models [9; 10]. Different quantification methods for FPAR, Ws, and Ts have been used in LUE models to estimate regional and even global GPP [5; 14]. In this study, the daily GPP simulated by the seven LUE models on sunny days was poorly matched with the measured GPP, and all models explained only 23-52% of the daily GPP variation in the cork oak plantation (Figure 6). [PERSON] et al. [9] also found that the Carnegie-Ames-Stanford approach (CASA), C-Fix, Carbon Flux (CFlux), EC-LUE, MOD17, Vegetation Photosynthesis model (VPM), and Vegetation Photosynthesis and Respiration model (VPRM) could only explain 41-57% of the GPP variation of different types of vegetation. [PERSON] et al. [51] compared 17 models against observations from 36 North American flux towers and showed that none of the models consistently reproduced the variability of the GPP measure from eddy covariance. These models performed poorly in terms of the magnitude and temporal variations of GPP [52]. This indicates that the LUE model still has a significant uncertainty.