## 4 Discussion
Comparing the differences between GPP\({}_{\text{wat}}\)/PGPP and GPP\({}_{\text{tem}}\)/PGPP, we found that the water stress scalar had a greater impact on the performance of the LUE model in our study area, whereas the temperature stress scalar had a relatively small effect (Figure 5). This finding is consistent with the results of [PERSON] et al. [53] and [PERSON] [54]. In our study area, due to the influence of the monsoon climate, the seasonal distribution of precipitation is uneven; the mean precipitation in summer accounts for 68% of the entire year [55]. Continuous rainy days reduced the impact of high temperatures on the productivity of plantations. Furthermore, the soil layer of this site is thin, and the soil layer contains high rock fractions [24]. The thin soil layer limits the water-holding capacity, resulting in drought events easily occurring in spring and autumn with less precipitation. [PERSON] et al. [9] and [PERSON] et al. [12] also argued that different methods of quantification of water stress scalars was the main source of the performance divergence of the LUE models in multiple study regions around the world. However, defining the limiting function of water availability in plant photosynthesis has long been a serious challenge [6; 9]. [PERSON] et al. [15] pointed out that different LUE models do not accurately represent the complex relationship between water availability and LUE, resulting in large errors in the LUE model. This is consistent with the results of our study (Figures 6 and 7). Currently, indicators commonly used to quantify the limitation of water availability for plant photosynthesis include atmospheric drought indicators, soil moisture indicators, and plant moisture indicators [7], yet there are contrasting opinions regarding which one is optimal [56; 57]. Soil water couples the water vapor demand of the atmosphere with the water supply from the soil to the leaves via roots. Soil moisture indicators are always used in the Terrestrial Carbon Flux model (TCF) and the Physiological Principles in Predicting Growth model (3-PG). Some studies have reported that water stress scalars based on soil moisture indicators better explain LUE variations in grasslands than in forests and shrubs [11; 58]. This is because woody plants have a higher water availability through deep roots and store more water in stems [58; 59; 60], thereby reducing the sensitivity of LUE to changes in shallow soil moisture. This was also the main reason for the poor performance of the SM-LUE model in this study on both cloudy and sunny days (Figure 6 ij, and Figure 8e). Since the study area is a lithoid mountain region, the soil layer thickness in most areas is only 20 cm, and plant roots will grow in the rock cracks. The water stress scalar defined by soil moisture indicates that it cannot accurately indicate the limitation of water availability for photosynthesis. Atmospheric drought indicators, such as VPD and SHD, represent the impact of atmospheric dryness on stomatal conductance and thus on plant transpiration and photosynthesis. Such indicators are often used in the MOD17 and GLO-PEM models. [PERSON] et al. [24] found that atmospheric drought is the main factor causing plant water stress in cork oak plantations. [PERSON] et al. [61] also reported that VPD and LUE were significantly negatively correlated in sub-humid areas and that the correlation was stronger in humid areas. These results are consistent with our findings. The LUE models established based on the atmospheric drought indicator had a relatively high explanatory power of GPP variation, especially on cloudy days, reaching 52%. However, the GPP values simulated by the MOD17 and MODTEM models were generally larger than the measured GPP values on cloudy days (Figures 6a-d and 8a,b), which is consistent with the results of [PERSON] and [PERSON] [62]. This is because the water stress scalar defined by VPD indicates that the degree of water stress on photosynthesis limitation is relatively weak on cloudy days (Figure 5).