## 3 Results  
### The LPJ Model Calibration and NPP Simulation in the Yangtze River Basin  
The observed NPP site was also used to compare with the NPP simulated by the LPJ model in the Yangtze River basin (Table 1). It can be seen that the forest NPP simulated by the LPJ model fell within the range of existing field survey data, and it was determined that the estimation results had definite reliability generally. However, the simulated NPP in Badong, Songtao, Tongzi and Zhongdianxian were much lower than the observed NPP. On the contrary, the simulated NPP in Huitong and Xingshan were much higher than that of observed NPP. The comparison of the mean annual forest NPP from the LPJ, Carnegie-Ames-Stanford Approach (CASA) and atmosphere vegetation interaction model (AVIM2) and the MODIS image was also analysed in this paper. It indicated that the NPP of broad-leaf and needle-leaf forests driven by LPJ model was higher than that of AVIM2 model, while it was slightly lower than that of MODIS image and CASA model. It should be of concern that the NPP of shrubs was much higher than the NPP from MODIS image and CASA model. Meanwhile, the NPP of Mixed forests was much lower than the NPP from AVIM2 model. These differences might be attributed to the data source and study area, as well as the vegetation types and their classification accuracy (Table 2). As seen in Figure 2, the NPP simulated by the LPJ model was consistent with the remote sensing images from the MODIS in the spatial distribution in the years 2000 and 2010. However, as shown in Figure 2, there was obvious difference in the sub-basins. The simulated NPP \begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & **Sites** & **Longitude** & **Latitude** & **Period** & **Observed** & **Simulated** \\  & **(Degree)** & **(Degree)** & **(Year)** & **(gC\(\cdot\)m\({}^{-2}\)\(\cdot\)y\({}^{-1}\))** & **(gC\(\cdot\)m\({}^{-2}\)\(\cdot\)y\({}^{-1}\))** \\ \hline
1 & Qianyanzhou & 115.05 & 26.73 & 2003–2008 & 487.52 & 521.39 \\
2 & Huitong & 109.75 & 26.83 & 2008–2009 & 268.5 & 350.56 \\
3 & Ningxiang & 112.57 & 28.33 & 2013–2013 & 428.8 & 453.84 \\
4 & Anji & 119.67 & 30.47 & 2011–2013 & 585.4 & 534.82 \\
5 & Anqing & 117.03 & 30.5 & 2005–2007 & 506.1 & 508.51 \\
6 & Badong & 110.38 & 31.03 & 1961–1990 & 735 & 578.37 \\
7 & Fangxian & 101.72 & 32.05 & 1961–1990 & 540 & 573.72 \\
8 & Shennongjia & 110.67 & 31.75 & 1961–1990 & 549 & 538.93 \\
9 & Yonghexiang & 104 & 33 & 1961–1990 & 551 & 580.9 \\
10 & Baiyu & 98.83 & 31.23 & 1961–1990 & 550 & 564.13 \\
11 & Maerkangxian & 102.22 & 31.92 & 1961–1990 & 618 & 606.6 \\
12 & Jüuzhailinchang & 103.9 & 33.28 & 1961–1990 & 573 & 588.75 \\
13 & Longkangxiang & 104.2 & 33.23 & 1961–1990 & 597 & 579.16 \\
14 & Xingshan & 110.73 & 31.22 & 1961–1990 & 376 & 447.08 \\
15 & Songtao & 109.18 & 28.17 & 1961–1990 & 778 & 620.31 \\
16 & Tongzi & 106.8 & 28.13 & 1961–1990 & 768 & 585.9 \\
17 & Zhongdianxian & 99.7 & 27.8 & 1961–1990 & 730 & 661.74 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Comparison of forest NPP simulated by LPJ model with that from the observation sites in Yangtze River basin. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Data** & **Period** & **Broad-Leaf Forests** & **Needle-Leaf Forests** & **Mixed Forests** & **Shrubs** \\ \hline LPJ & 1982–2013 & 543.66 & 548.01 & 538.75 & 532.47 \\ MODIS [23] & 2000–2009 & 1463 \(\pm\) 247.05 & 633 \(\pm\) 199.4 & 631 \(\pm\) 191.2 & 489 \(\pm\) 271.8 \\ CASA [36] & 1982–1999 & 633.66 & 295.46 & — & 286.64 \\ AVIM2 [23] & 2000–2000 & 469 & 249 & 625 & 561 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Comparison of mean annual forest NPP from the LPJ model with that of other data (unit: gC\(\cdot\)m\({}^{-2}\)\(\cdot\)y\({}^{-1}\)). the upper Yangtze reaches in the year 2000, while the higher values occurred in the lower Yangtze River basin, especially in the Poyang Lake basin in the year 2010. As for the MODIS image, it exhibited higher NPP values in the upper Yangtze reaches in both 2000 and 2010. In previous studies, [PERSON] et al.