## 3 Results
### Altitudinal Patterns of \(SIF_{yield}\) Changes
#### 3.1.2 Altitude-Dependent \(SIF_{yield}\) Changes at Interannual Scale  
Since the growing stage of plants, the latitude of the subsolar point, and other climatic conditions at a specific site are usually similar on the same DOY in different years, the analysis of \(SIF_{yield}\) variation at interannual scale is less disturbed by these latent variables. Whereas seasonal changes in environmental conditions, differences in the vegetation growth stage, and altitudinal variations in the species composition of the ecosystem usually confound the altitudinal variation results derived from other perspectives, they are no longer the dominant factors for altitudinal \(SIF_{yield}\) variation at the interannual scale.  
Figure 4: Temperature responses of (**a**) \(SIF\) and (**b**) \(SIF_{yield}\) at different altitudes at seasonal scales. Observations from DOY 93 (April, early regreening period at late spring). 133 (May, early regreening period at late spring), 205 (July, the peak of summer growth period), and 213 (August, the late summer growth period) are marked.  
Therefore, the variation pattern investigated from this aspect can be quite different from the patterns described above.  
Figure 5a shows the changing relationships between \(SIF_{yield}\) and environment variables (PAR and air temperature) from DOY 133-277. As the figure depicts, the R\({}^{2}\) of the \(SIF_{yield}\)-PAR relationship is high and stable throughout the period, while the R\({}^{2}\) of the \(SIF_{yield}\)-temperature relationship is small and changeable, especially during the middle of the growing season. Since R\({}^{2}\) shows the ability of independent variables to explain the variation in \(SIF_{yield}\), the smaller R\({}^{2}\) of temperature in summer indicates that the thermal condition can no longer explain the \(SIF_{yield}\) variation well, probably because it is good enough at that time. However, for PAR, R\({}^{2}\) stays relatively high. It explains the \(SIF_{yield}\) well, which is not surprising, as excessive light is a common stress in alpine regions. In addition to the changing R\({}^{2}\), the direction of the \(SIF_{yield}\)-temperature correlation is also unstable (Figure 5a), whereas the correlation between \(SIF_{yield}\) and PAR remains negative during the study period.  
Based on the 12-year observations, Figure 5b shows the relationship between \(SIF_{yield}\) and PAR at different altitudes on DOY 205. As shown in Figure 5b, the responses of \(SIF_{yield}\) to the same environmental variable, PAR, are different in different habitats. Generally, it seems that \(SIF_{yield}\) at high altitude is still higher and is more sensitive to changes in PAR. Results obtained this way may be comparable to some experimental results obtained in the laboratory, as they are concentrated on the temporal changes of the same vegetation, and the change of vegetation itself is almost negligible. Nevertheless, differences may still exist, as the former results are more \"authentic\". Because the observations come from complicated natural conditions, these results are difficult to simulate in the laboratory.