## 4 Results
### Spatial Variations in GPP  
Figure 7 shows the spatial patterns of the annual GPP on the Tibetan Plateau averaged from 1982 to 2018. As shown in the figure, in general, the mean annual GPP decreases gradually from the southeast to the northwest. The regions with higher GPP are primarily distributed in the upper reaches of the Yellow River, Yangtze River, Lancang River, Nu River, and Yarlung Zangbo River. These areas are low in elevation and receive relatively abundant precipitation, which supports the growth of shrubs and grasses. In contrast, areas such as the Chang Tang Plateau, Qaidam Basin, Shiquan River, Tarim Basin, and Qilian Mountains show lower GPP due to their higher elevations, lower temperatures, and limited precipitation, which restrict vegetation growth. According to the statistical results, the mean annual GPP on the Tibetan Plateau was 363.80 g C\(\cdot\)m\({}^{-2}\cdot\)year\({}^{-1}\). This finding is consistent with the results of [PERSON] et al. (2015). To illustrate the changes in GPP over different periods, Figure 8 presents the decadal average GPP for 2021-2040, 2041-2060, 2061-2080, and 2081-2100 under the four SSP scenarios as a function of elevation. As seen in Figures 5 and 6, the GPP shows an increasing trend at both the interannual and seasonal scales in future periods. Here, we aim to demonstrate how these changes manifest across different elevations. From Figure 8, it is evident that, under the ssp126 scenario, the overall changes in GPP across different periods are not particularly pronounced, with noticeable relative changes occurring in the 1000-2000 m range, albeit with a limited magnitude. Under the ssp245 scenario, significant differences in GPP can be observed between elevations of 3000 and 4500 m, indicating that, with further temperature increases and CO\({}_{2}\) emissions, vegetation at these elevations is notably affected. \begin{table}
\begin{tabular}{l c c c c c c c c c c} \hline \hline \multirow{3}{*}{**Seasonal**} & \multicolumn{2}{c}{**Historical**} & \multicolumn{2}{c}{**ssp126**} & \multicolumn{2}{c}{**ssp245**} & \multicolumn{2}{c}{**ssp370**} & \multicolumn{2}{c}{**ssp585**} \\  & **1982–** & **2021–** & **2061–** & **2021–** & **2061–** & **2021–** & **2061–** & **2021–** & **2061–** & **2021–** & **2061–** \\  & **2018** & **2060** & **2100** & **2060** & **2100** & **2060** & **2100** & **2060** & **2100** & **2060** & **2100** \\ \hline \multirow{3}{*}{Spring} & trend & 1.900 & \(-\)0.102 & 0.211 & 0.249 & 0.697 & 0.324 & 1.501 & 0.297 & 1.891 \\  & \(p\) & \(<\)0.01 & 0.379 & 0.088 & 0.038 & \(<\)0.01 & 0.032 & \(<\)0.01 & 0.167 & \(<\)0.01 \\ \cline{1-1}  & trend & 4.199 & 1.228 & 1.327 & 1.677 & 2.159 & 1.994 & 1.187 & 2.984 & 0.329 \\ \cline{1-1}  & \(p\) & \(<\)0.01 & 0.011 & \(<\)0.01 & \(<\)0.01 & \(<\)0.01 & \(<\)0.01 & 0.061 & \(<\)0.01 & 0.682 \\ \cline{1-1}  & trend & 4.151 & 0.999 & 0.072 & 1.530 & 0.779 & 1.820 & 1.576 & 1.580 & 1.493 \\ \cline{1-1}  & \(p\) & \(<\)0.01 & 0.012 & 0.752 & \(<\)0.01 & 0.018 & \(<\)0.01 & \(<\)0.01 & \(<\)0.01 & \(<\)0.01 \\ \cline{1-1}  & trend & 0.778 & \(-\)0.059 & 0.029 & \(-\)0.014 & \(-\)0.153 & \(-\)0.251 & \(-\)0.177 & \(-\)0.250 & \(-\)0.056 \\ \cline{1-1}  & \(p\) & 0.074 & 0.339 & 0.684 & 0.017 & 0.028 & \(<\)0.01 & 0.040 & \(<\)0.01 & 0.533 \\ \hline \hline \end{tabular} Note: the unit of the trend is \(10^{-3}\) g C\(\cdot\)m\({}^{-2}\cdot\)d\({}^{-1}\). If the \(p\)-value is less than 0.01, the value of \(p\) is marked as \(<\)0.01; otherwise, the true \(p\) value is given in the table.  
\end{table} 
Table 4: The trends and \(p\)-values for the seasonal GPP changes in the historical and projected future periods during the 21 st century under the ssp126, ssp245, ssp370, and ssp585 scenarios. In the ssp370 scenario, the elevation band between 3000 and 4500 m exhibits noticeable changes in GPP across different periods, particularly between 2081 and 2100, which is markedly higher than that in 2061-2080.