## 3 Results
### Temporal Variation of the Relationship between PRI and LUE  
Figure 4 shows the correlation coefficients (\(R\)) of half-hourly PRI with LUE on individual days with more than five good-quality observations between 9 a.m. and 16:30 with high solar elevation angles. Generally, PRI is positively correlated with LUE. Among 163 days, PRI was significantly correlated with LUE on 58 days (\(p\) < 0.05).  
The correlations of PRI with LUE changed with weather conditions. PRI was significantly correlated with LUE on 40.6% of the days in the dry season. The corresponding ratio decreased to 22.4% in the rainy season. On days when PRI was significantly correlated with LUE, PRI was affected by both CI and VPD before day 206. On the following days, VPD was a more important factor for regulating PRI than CI. During the period of consecutively high temperature in August, VPD was high and acted as the dominant controller of GPP. It increased continuously after sunrise, resulting in a corresponding decrease of GPP due to the closure of leaf stomata. As a consequence, LUE continuously decreased. Meanwhile, a continuous decrease of PRI was observed since the fraction of radiation used for carbon fixation continuously decreased during daytime. PRI was positively correlated with both LUE and GPP. Similar phenomena were also found on some other clear days with high VPD (>20 hPa). Some unexpected significantly negative relationships between PRI and LUE were observed on or shortly after some heavily raining days. At this site, fluxes were measured  
Figure 4: Correlation coefficients (\(R\)) of half-hourly PRI with LUE on individual days, with data acquired from 9 a.m. to 16:30. The length of error-bars represents the \(p\)-value of each linear regression. PR: positive correlation, NR: negative correlation.  
Figure 3: Relationships of half-hourly bioclimatic parameters (_i.e._, VPD, PAR, and Ta) with LUE (**a–c**); and with PRI (**d–f**) observed from 9 a.m. to 16:30 each day across the season.  
using an open path EC system. When the sensor is wet, the accuracy of the measured flux is low. Water accumulated on leaves also impacts the measurements of the optical spectra. Uncertainties in estimated GPP and measured spectra resulted in an unexpected relationship between PRI and LUE.  
Figure 5a,b show the relationships between LUE and PRI at half-hourly and daily temporal scales, respectively, throughout the study period. Significant logarithmic correlations were found at both half-hourly and daily temporal scales, even though the coefficients of determination (\(R^{2}\)) were not very high. The difference in dominant regulators of PRI and LUE variations appeared to be the reason for the low correlation coefficients between PRI and LUE throughout the entire growing season (Figure 3). The difference in the correlations between these two temporal steps indicates that the temporal scale can have some effects on the correlation of PRI with LUE.  
For individual months, logarithmic relationships between daily average PRI and LUE were presented in Figure 6. The relationship varied dramatically throughout the growing season. The worst regression between PRI and LUE was observed in May due to the abundance of rainy days. PRI can act as a good indicator of LUE in July and August, in which severe drought and consecutive high temperature occurred.  
Figure 5: Relationships between (**a**) half-hourly and (**b**) daily average PRI and LUE calculated using data observed from 9 a.m. to 16:30 each day throughout the study period.  
Figure 6: Logarithmic relationships between daily average PRI and LUE calculated using data observed from 9 a.m, to 16:30 each day for six months (**Apr.–Sep.**).