## 4 Discussion  
### Feasibility of PRI to Indicate LUE  
During this study period (Figure 2), GPP roughly varied with temperature in the rainy season, but was limited by the water condition in the dry season. Differently, PRI and LUE showed quite complicated seasonal variations due to polytropic meteorological conditions. According to diurnal (Figure 4), monthly (Figure 6), and six-month results (Figure 5), PRI showed the potential to be a proxy of LUE in this sub-tropic evergreen coniferous forest, but the best correlations between PRI and LUE are found only under certain meteorological conditions. Significant positive correlations between PRI and LUE were found on some days (Figure 4), months (Figure 6), as well as throughout the study period (Figure 5). These results are consistent with previous studies at canopy scales and different temporal scales [3; 26; 32; 44; 66]. LUE is mostly determined by environmental stress factors that reduce photosynthetic rates, such as photoinhibition in short terms and water deficit in long terms. This reduction inversely increases the proportion of absorbed energy dissipated as heat, which can be detected by the decrease of R\({}_{531}\), forming the basis of PRI [33; 37; 55; 67]. Thus, PRI could track LUE at different temporal scales. [PERSON] _et al._[44] indicated different types of relationships between PRI and LUE. In this study, PRI was mostly linearly correlated to LUE at the diurnal scale and logarithmically correlated to LUE for longer periods, which was possibly due to the complicated canopy structure of conifer forest. PRI was announced as a short-term variable index [32; 34], which allowed it to track the variation of LUE at short temporal scales. However, even though PRI could track LUE variations to some extent (Figure 2c), some distinctive variations among bioclimatic factors, PRI and LUE were observed, which indicated that PRI and LUE were driven by different factors (Figures 3 and 7-9) during such a long period [30]. Additionally, the difference in meteorological conditions between the rainy and dry seasons further magnified this gap. variations of both half-hourly PRI and LUE (Figure 3). When the study period was separated to six months, radiation became a 'double-edged sword', although the most important determinant of the correlation between PRI and LUE was always the relationship of PRI with PAR (Figure 7). Under rainy or severely overcast sky conditions, since canopy reflectance observations were contaminated by rain or low illumination, abnormal PRI might be observed that induced inconsistent, even negative correlations of PRI with LUE (Figure 4). In May, because of frequent alternations between sunny and rainy conditions, the relationship between PRI and LUE was very scattered. Even if only data on clear and slightly overcast days in this month were used, this relationship was still poor, which was consistent with the findings reported by [PERSON] _et al._[32]. In the dry season, both PRI and LUE were more sensitive to VPD and Ta than to PAR, especially during the summer depression period. However, as illustrated in Table 1, the strongest correlation between PRI and LUE was not found at the highest level of VPD, indicating that the ability of PRI to track LUE is compromised under high atmospheric water stress. At the diurnal scale, the findings here were slightly different from the conclusion declared by [PERSON] and [PERSON] [27]. In this sub-tropic conifer forest, both radiation (_i.e._, PAR and CI) and VPD (Figure 8a,b,d) are dominant factors regulating the correlation between PRI and LUE. Under conditions of moderate to high PAR, CI, VPD, and Ta, the correlation coefficients between PRI and LUE were high (Figures 8a-d and 9), indicating the ability of PRI to act as a proxy of LUE under climatic stress. A paired factors analysis illustrated the complexity of correlation between PRI and LUE under different weather conditions (Figure 9).