## 5 Conclusions  
The Three Gorges Reservoir area is one of the most ecologically sensitive areas in China, and the forest landscape pattern in this region shows dramatic change due to the influence of the Three \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & **Annual Temperature** & \multicolumn{5}{c}{**NPP**} \\ \cline{3-7}  & **DBF** & **EBF** & **ENF** & **Shrub** & **MIX** \\ \hline Annual temperature & 1 & \(-\)0.235 ** & \(-\)0.242 ** & \(-\)0.321 ** & \(-\)0.248 ** & \(-\)0.319 ** \\ DBF NPP & & 1 & 0.814 ** & 0.657 ** & 0.673 ** & 0.820 ** \\ EBF NPP & & & 1 & 0.883 ** & 0.857 ** & 0.932 ** \\ ENF NPP & & & 1 & 0.883 ** & 0.857 ** & 0.932 ** \\ ENF NPP & & & & 1 & 0.938 ** & 0.970 ** \\ Sbrub NPP & & & & & 1 & 0.929 ** \\ MIX NPP & & & & & & 1 \\ \hline \hline \end{tabular} Note: ** significantly correlated at the 0.01 level (bilateral).  
\end{table} 
Table 7: Pearson correlation analysis between NPP of forest types and annual mean temperature in TGR. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \multicolumn{5}{c}{**NPP**} \\ \cline{2-7}  & **Annual Precipitation** & **DBF** & **EBF** & **ENF** & **Shrub** & **MIX** \\ \hline Annual Precipitation & 1 & 0.609 ** & 0.704 ** & 0.723 ** & 0.743 ** & 0.744 ** \\ DBF NPP & & 1 & 0.814 ** & 0.657 ** & 0.673 ** & 0.820 ** \\ EBF NPP & & & 1 & 0.883 ** & 0.857 ** & 0.932 ** \\ ENF NPP & & & & 1 & 0.938 ** & 0.970 ** \\ Shrub NPP & & & & & 1 & 0.929 ** \\ MIX NPP & & & & & & 1 \\ \hline \hline \end{tabular} Note: ** significantly correlated at the 0.01 level (bilateral).  
\end{table} 
Table 8: Pearson correlation analysis between NPP of five forest types and annual precipitation in TGR. Gorges reservoir project. The forest NPP and carbon sequestration of various forest types in this area, which were estimated based on the Biome-BGC model, indicated that total and unitary forest NPP presented obvious annual fluctuation from 1992 to 2012 under the combined influences of land use change and extreme weather events. Apart from the year 2006, from 1992 to 2012, the NPP values of each forest type showed an increasing trend, although the growth rates decreased. In 2006, due to abnormally high air temperatures and less precipitation, total and unit area forest NPP values decreased by 46.3% and 53.9%, respectively, compared to 2002. From 1992 to 2012, the carbon stocks of the forest vegetation layer, the litter layer, the soil layer, and the entire area gradually increased with a decreasing growth rates. Forest carbon stocks were high in the east and the south and low in the west and the north. Regions with higher carbon stocks included the reservoir head, the Wushan-Wuxi section, the Shizhu-Wulong section, and the southern section of the Jiangjin District. From 1992 to 2012, the variation in the forest landscape pattern and the responses of forest productivity and carbon stocks indicated that the increase in forest area and the optimization of the forest landscape pattern could improve the forest productivity and carbon stocks. In fact, the potential and historic land use changes influence not only the forest areas, but also the forest landscape patterns, such as patch size, fragmentation degree, and patches connectivity and so on. This paper only analyzed the changes in forest productivity and carbon storage caused by the changes of forest area, but did not deeply analyze the impacts of landscapes patterns. Therefore, it is an important issue for further study to clarify the contributions of landscape pattern to carbon storage based on the principle of edge effects. Based on the Biome-BGC model, the simulated NPP values and carbon density values of the coniferous forest and the mixed coniferous and broadleaf forest were close to the measured values, while those of the deciduous broadleaf forest, the evergreen broadleaf forest, and the shrub forest were lower than the measured values.