## 3 Results
### Effects of Bioclimatic Factors on the Ability of PRI as a Proxy of LUE  
Light, water and temperature are the most essential factors regulating photosynthesis. The effects of these bioclimatic factors on PRI and LUE and on the ability of PRI to indicate LUE were investigated. In April, when Ta was low, both LUE and PRI were less sensitive to Ta, but were more sensitive to PAR, leading to a moderate correlation between LUE and PRI (Figure 7). PRI was decoupled with LUE in May, as LUE was significantly correlated to the three bioclimatic factors while the PRI variation was irrelevant to any of them, due to the abundance of rainfall which might induce uncertainties in spectral observations. The correlation between LUE and Ta was much stronger than all other five correlations in June, while the correlation between PRI and LUE was not strong. In July, all six correlations were at a high level which made the best correlation between PRI and LUE among all six months. In this month, there were many sunny or slightly cloudy days (CI > 0.5). Since then, in August and September, PRI was much more correlated to VPD while LUE was more correlated to PAR, which apparently caused the decline of the correlation between PRI and LUE. Figure 8 illustrated variations of diurnal correlation coefficients (\(R\)) of half-hourly PRI with LUE binned according to different daily means of bioclimatic factors and GPP. With increases of VPD, PAR and CI, the \(R\) increased obviously (Figure 8a-c). The \(R\) of half-hourly PRI with LUE changed marginally with daily mean air temperatures when the daily mean air temperatures was below 30 \({}^{\circ}\)C and then increased considerably with the further increase of daily mean air temperatures. The \(R\) of half-hourly PRI with LUE slightly decreased with the increase of soil moisture (Figure 8d). Overall, PRI performed better in tracking diurnal variations of LUE on clear and dry days than on overcast and wet days. In addition, the ability of PRI to track LUE became weaker on days with low and high daily GPP (Figure 7f). Figure 9 showed the variations of diurnal correlation coefficients (\(R\)) between half-hourly PRI and LUE in the two-dimensional space of two bioclimatic parameters. High values of \(R\) between PRI and LUE were mostly under conditions when VPD was above 20 hPa. If VPD was above 30 hPa, PRI was able to track LUE well regardless of the values of the other bioclimatic factors (Figure 9a-c). As to same given values of Ta, SM, PAR and CI, the ability of PRI to act as a proxy of LUE increased with VPD. The effects of CI and PAR on the relationship of PRI with LUE were not synchronous (Figure 9e). When PAR was less than 4 MJ-m-2.d-1, \(R\) was low, but decreased with the increase of CI when PAR varied from 4 to 8 MJ-m-2.d-1. Additionally, the values of \(R\) were generally high when PAR was above 8 MJ-m-2.d-1. For different levels of SM (Figure 9f), high values of \(R\) were mostly found on sunny or slightly cloudy days (CI > 0.5). Figure 7: Variations of linear coefficients of determination (\(R^{2}\)) between PRI or LUE and the three bioclimatic parameters (_i.e._, VPD, PAR, and Ta) observed from 9 a.m. to 16:30 each day at monthly interval. Figure 8: Average diurnal correlation coefficients (\(R\)) of half-hourly PRI with LUE in relation to (**a**–**e**) individual bioclimatic factors or (**f**) GPP throughout the whole season. Error bars indicated one standard deviation. Figure 9: _Cont._  
The ability of PRI to track LUE changed with different combinations of bioclimatic factors (Table 1). There are 2223 paired samples of PRI and LUE in total between 9 a.m. and 16:30 throughout the entire study period. When these samples were binned according to VPD in conjunction with Ta, PRI was correlated with LUE at the significance levels of 0.05, 0.01 and 0.001 for 1712, 1703, and 1680 samples. Classifying samples according to the configuration of VPD and Ta could greatly improve the ability of PRI to track LUE.