## 3 Results  
### Dynamics in GPP as Well as Environmental Factors  
Seasonal variations in site-level GPP and climate-related factors including Rg, Ta, VPD, and P across the two contrasting subtropical conifer and broadleaved forest ecosystems are illustrated in Figures 2-4. For each forest type, a total of 8 years of flux observations was used for analysis. It implied that the GPP of both the QYZ and DHS sites showed apparent single-peak patterns. As the temperature rose in springtime (Figure 3), GPP enhanced increasingly with the plant growth status, peaked in summertime, and decreased again in autumn. However, the peak timing appeared earlier in the evergreen needleleaf forest at the end of June or early July, by comparison with the evergreen broadleaf forest during about middle to late July. In addition, the peak values of GPP had large differences, with larger photosynthetic carbon fixation potential at the QYZ site (8.76 \(\pm\) 0.71 g C m\({}^{-2}\) d\({}^{-1}\)) than that at the DHS site (5.71 \(\pm\) 0.31 g C m\({}^{-2}\) d\({}^{-1}\)). The distribution of rainfall is mainly concentrated in summer with large fluctuations throughout the measurement period (Figure 3). As a proxy for plant water stress, the VPD of the QYZ site also showed distinct seasonal dynamics, whereas the VPD of the DHS site fluctuated severely around the year.  
Figure 2: Site-level GPP observations at the two subtropical forest flux sites (QYZ and DHS) for 8-day periods from 2003 to 2010, respectively. For \(x\)-axis, the data refer to week of year (WOY) ranging from 1 to 46.  
Table 1 compared the correlations between these site-level GPP observations and the environmental factors including \(\rm R_{g}\), \(\rm T_{a}\), VPD, and P at the two subtropical forest flux sites, respectively. It revealed that, except P, almost all variables strongly affected the dynamics in forest GPP. In the evergreen needleleaf forest, GPP was proven to exert a stronger influence by \(\rm T_{a}\) (\(r=0.908\)), followed by \(\rm R_{g}\) and VPD of 0.855 and 0.793, respectively. Contrastingly, \(\rm R_{g}\) was the dominant environmental factor of GPP in the evergreen broadleaf forest (\(r=0.79\)). Then, both VPD and \(\rm T_{a}\) also strongly and positively affected the variability in GPP with similar correlations of 0.677 and 0.655, respectively.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & **Site** & \(\rm R_{g}\) & \(\rm T_{a}\) & **VPD** & **P** \\  & & **(W m\({}^{-2}\))** & (\({}^{\circ}\)**C**) & **(h Pa)** & **(mm)** \\ \hline GPP & QYZ (Evergreen needleleaf forest) & 0.855 ** & 0.908 ** & 0.793 ** & 0.051 \\ (g C m\({}^{-2}\) d\({}^{-1}\)) & DHS (Evergreen broadleaf forest) & 0.790 ** & 0.665 ** & 0.677 ** & \(-\)0.069 \\ \hline \end{tabular} Note: ** means that the correlation is significant at the 0.01 level (\(p<0.01\)).  
\end{table}
Table 1: Correlations between site-level GPP observations and the environmental factors including solar radiation (\(\rm R_{g}\)), air temperature (\(\rm T_{a}\)), vapour pressure deficit (VPD), and precipitation (P) at the two subtropical forest flux sites, respectively.  
Figure 3: Seasonal trajectories of solar radiation (\(\rm R_{g}\)), air temperature (\(\rm T_{a}\)), vapour pressure deficit (VPD), and precipitation (P) during 2003–2010 at the QYZ flux site (evergreen needleleaf forest) for 8-day periods. For \(x\)-axis, the data refer to week of year (WOY) ranging from 1 to 46.