## 3 Results
### Correlation Analysis between SIF and Environmental Factors in Growing Season  
Environmental factors can affect SIF by affecting the amount of light energy absorbed by leaves or the allocation of the light energy by the chlorophyll molecules. To clarify the similarities and differences in the SIF responses to the environmental factors in the different seasons, five factors were selected to calculate the correlation coefficients between SIF and the environmental factors at both daily and half-hour scales (Figure 5). The results of a Pearson correlation analysis of the whole growing season showed that the PAR, Ta, Ws, SM and VPD had extremely significant relationships with SIF in the half-hour scale; the sequence of the correlation coefficient was PAR \(>\) VPD \(>\) Ta \(>\) Ws \(>\) SM. Except for the SM, all of the factors were also significantly correlated with SIF on the daily scale, and the order of the correlation coefficients was the same as on the half-hour scale. Unlike SIF, the SM had no diurnal variation. Although there was a significant correlation between SM and SIF on the half-hour scale, the correlation disappeared when the temporal aggregated to the daily scale. All the factors significantly affected the daily and half-hour scale of SIF in the spring; however, the effects of SM and Ws on SIF disappeared in the summer. SM was  
Figure 3: Diurnal dynamics of SIF (yellow line) and PAR (blue line) in spring (sunny (**a**), cloudy (**d**) and rainy (**g**)); summer (sunny (**b**), cloudy (**e**) and rainy (**h**)); and autumn (sunny (**c**), cloudy (**f**) and rainy (**i**)). correlated with the half-hour scale of SIF in the autumn, but this relationship was covered up at the daily scale. Figure 4: Diurnal dynamics of APAR (brown line); \(\mathrm{\Phi F}\) (purple line); and \(\mathrm{f_{esc}}\) (green line) in spring (sunny (**a**), cloudy (**d**), rainy (**g**)); summer (sunny (**b**), cloudy (**e**), rainy (**h**)); and autumn (sunny (**c**), cloudy (**f**) and rainy (**i**)). Each subgraph was dated in the upper right corner. Figure 5: Pearson correlation coefficients between SIF and different environmental factors, in different seasons (whole, spring, summer and autumn). Environmental variations included PAR, Ta, wind speed (Ws), SM and VPD at daily scale (the lower part of each figure) and half-hour scale (the upper part of each figure). Blue means positive correlation; red means negative correlation; and the flatter the ellipse, the stronger the correlation. Note: *—significant correlation at \(p<0.05\) and **—**–significant correlation at \(p<0.01\). PAR was a necessary condition for the emission of SIF, which was significantly correlated with SIF and APAR on both the daily and half-hour scales. It should be noted that the Ta and VPD were also significantly correlated with PAR at different temporal scales, and the correlation coefficients were larger than those between these environmental factors with SIF and APAR. In other words, the Ta, VPD, SIF and APAR had a covariant relationship with PAR, which would affect the relationship between the environmental factors and the fluorescence parameters. To eliminate this effect, we chose a partial correlation analysis to analyze the links between the fluorescence parameters with the Ta and VPD, and we took PAR as the control variable (Figure 6). After removing the effect of PAR, the VPD still significantly affected SIF, but the effect changed from positive to negative. The effect of Ta on SIF in the total growing season disappeared, indicating that the effect of Ta on SIF was derived from the effect of PAR on SIF. The influence of Ta on the half-hour scale of SIF in the spring and summer changed direction, and Ta only had a significant negative effect on SIF in the summer at the daily scale. That is to say, the effect of the VPD on SIF in the summer mainly comes from Ta, and the effect of the VPD on SIF in the spring and autumn mainly comes from RH.