## 3 Results
### Environmental Effects on RE Spatiotemporal Variation  
#### 3.3.1 Environment Effects on RE Seasonal Dynamics  
The relationship between RE and Ta in northern China's grasslands at an eight-day timescale showed an explicit exponential form (R\({}^{2}\) = 0.97; Figure 7a). The sensitivity of RE to temperature in the TP alpine region was greater than that of the IM temperate region. This temperature-sensitive heterogeneity can be attributed to the regional climatic conditions and the vegetation types. There was a clear positive correlation between RE and PRE throughout northern China's grasslands, and the R\({}^{2}\) between the two was 0.90 (Figure 7b). We also found that the RE reached a certain saturation point with the increase in PRE. When the PRE reaches a specific threshold, the RE no longer increased and even tended to decline (Figure 7b). The saturation thresholds for RE to PRE differed in different climatic regions. In the temperate grasslands, RE began to decrease after the PRE exceeded 35 mm, while PRE at this intensity retained a continuous positive stimulus for RE in alpine grasslands. This may be associated with the different moisture requirements of the different grassland types. A significant linear positive correlation (R\({}^{2}\) = 0.93) between the RE and the EVI was observed in the northern grasslands of China (Figure 7c). Similar to Ta, PAR and RE showed an exponential positive correlation (R\({}^{2}\) = 0.69, Figure 7d). However, under the same radiation intensity, the sensitivity of RE to PAR was higher in the alpine grasslands than in the temperate grasslands.  
Figure 6: (**a**) Seasonal dynamics of RE at the regional scale from 2001–2015; (**b**) seasonal dynamics of mean 15-year seasonal RE in the seven grassland subtypes; (**c**) interannual dynamics of RE at the regional scale from 2001–2015; (**d**) the increasing rate of RE of the seven grassland subtypes.  
We further analyzed the relationship between RE and environmental variables on a seasonal scale in the seven grassland subtypes (Table 4). It was found that Ta could best explain the RE seasonal dynamics compared with other variables, in five of the seven grassland subtypes. Ta was also the secondary environmental factor explaining the RE seasonal dynamics in the remaining two grassland subtypes. To summarize, Ta was found to dominate the seasonal dynamics of RE in northern China's grasslands.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & **Grassland** & & & & \\
**Subtypes** & & & & & \\ \hline \multirow{4}{*}{TP} & KO & 0.927 & 0.528 & 0.801 & 0.931 \\  & SH & 0.938 & 0.515 & 0.807 & 0.929 \\  & SW & 0.925 & 0.674 & 0.826 & 0.951 \\  & AS & 0.624 & 0.697 & 0.564 & 0.834 \\ \hline \multirow{4}{*}{IM} & MS & 0.892 & 0.773 & 0.736 & 0.956 \\  & TS & 0.853 & 0.822 & 0.771 & 0.928 \\ \cline{1-1}  & DS & 0.748 & 0.689 & 0.672 & 0.727 \\ \hline \hline \end{tabular}
\end{table}
Table 4: The seasonal dynamic correlation (R\({}^{2}\)) between RE and environmental variables in each grassland subtype.  
Figure 7: Seasonal dynamic correlation between RE and (**a**) Ta, (**b**) PRE, (**c**) EVI, and (**d**) PAR at eight-day timescale from 2001–2015 in the northern China’s grasslands overall, alpine grasslands, and temperate grasslands, respectively.