## 3 Results  
### Spatial Characteristics of Multiple Annual GPP Estimates  
Spatial distributions of annual GPP estimates from the MOD17, TL-LUE, MTL-LUE, TG, MTG, BEPS, and BTL models over Wanglang Reserve are shown in Figure 3, and their statistics are presented in Table 3. In general, multiple annual GPP estimates from the seven models over Wanglang Reserve showed similar spatial distributions. As for the three LUE models, the annual GPP estimates from the MTL-LUE model had a higher spatial variation (CV = 26%) than those from TL-LUE (CV = 20%) and MOD17 (CV = 19%) for all pixels. The annual GPP estimates from MTG and BTL models also presented a higher spatial variation than those from TG and BEPS, with CV values increased by 8% and 22%, respectively. At the watershed scale, GPP estimates from the seven models presented different annual values. The GPP estimates from MTL-LUE had a lower annual value than those from the MOD17 model for the forest, shrub, and grass pixels, with the mean value decreasing by 283, 293, and 451 gC m\({}^{-2}\)yr\({}^{-1}\), respectively. Compared to the TL-LUE model, the GPP estimates from MTL-LUE had a higher annual value for forest \begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Model**} & \multicolumn{4}{c}{**Forest**} & \multicolumn{4}{c}{**Shrub**} & \multicolumn{4}{c}{**Grass**} & \multicolumn{4}{c}{**All**} \\ \cline{2-13}  & **Mean** & **SD** & **CV** & **Mean** & **SD** & **CV** & **Mean** & **SD** & **CV** & **Mean** & **SD** & **CV** \\ \hline MOD17 & 1431 & 152 & 11 & 1006 & 143 & 14 & 1457 & 341 & 23 & 1401 & 267 & 19 \\ TL-LUE & 1021 & 116 & 11 & 829 & 134 & 16 & 1123 & 278 & 25 & 1039 & 207 & 20 \\ MTL-LUE & 1148 & 208 & 18 & 713 & 168 & 23 & 1006 & 306 & 30 & 1059 & 276 & 26 \\ TG & 527 & 192 & 36 & 218 & 153 & 71 & 159 & 177 & 112 & 370 & 255 & 69 \\ MTG & 411 & 192 & 47 & 295 & 235 & 80 & 110 & 139 & 126 & 296 & 228 & 77 \\ BEPS & 663 & 169 & 25 & 707 & 143 & 20 & 756 & 177 & 23 & 699 & 175 & 25 \\ BTL & 901 & 443 & 49 & 871 & 412 & 47 & 1088 & 463 & 43 & 963 & 457 & 47 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Mean (gC m\({}^{-2}\)yr\({}^{-1}\)), standard deviation (SD, gC m\({}^{-2}\)yr\({}^{-1}\)), and coefficient of variation (CV, %) values of multiple annual GPP estimates in forest, shrub, grass, and all pixels. \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multicolumn{1}{c}{\multirow{2}{*}{**Model**}} & \multicolumn{4}{c}{**Input Data**} \\ \cline{2-5}  & **Tower-Based (Daily)** & **Vegetation-Related (30 m)** & **Topography-Related (30 m)** \\ \hline MOD17 & \(R_{total}\)1  & \(R_{total}\), \(T_{min}\), \(VPD_{daytime}\) & LC, LAI & - \\ MTL-LUE & \(R_{total}\), \(T_{min}\), \(VPD_{daytime}\) & LC, LAI & Elevation, slope, aspect, SVF \\ TG & - & LC, EVI, LST & - \\ MTG & - & LC, EVI, LST, FPAR & Elevation, slope, aspect \\ BEPS & \(R_{total}\), \(P_{\text{re}}\)4, \(T_{min}\), \(T_{max}\), \(T_{max}\), \(T_{max}\)6  & \(R_{total}\), \(P_{\text{re}}\)4, \(T_{min}\), \(T_{max}\), \(T_{max}\)  & \(R_{total}\), \(P_{\text{re}}\)4, \(T_{min}\), \(T_{max}\), \(T_{max}\)  & \(LC\), LAI, soil type & - \\ BTL & \(R_{total}\), \(P_{\text{re}}\), \(T_{min}\), \(T_{max}\), \(T_{max}\), \(T_{max}\)  & \(LC\), LAI, soil type & - \\ BTL & \(R_{total}\), \(P_{\text{re}}\), \(T_{min}\), \(T_{max}\), \(T_{max}\), \(T_{max}\)  & \(LC\), LAI, soil type & - \\ BTL & \(R_{total}\), \(P_{\text{re}}\), \(T_{min}\), \(T_{max}\), \(T_{max}\), \(T_{max}\)  & \(LC\), LAI, soil type & - \\ BTL & \(R_{total}\), \(P_{\text{re}}\), \(T_{min}\), \(T_{max}\), \(T_{max}\), \(T_{max}\) [FOOTNOTE:4]Footnote 4: daily total incoming solar radiation; 2 daily minimum air temperature; 3 daytime average VPD; 4 daily total precipitation; 5 daily minimum air temperature; 8 daily average air temperature. value by 127 gC m\({}^{-2}\)yr\({}^{-1}\)), but a lower annual value in for shrub pixels (decreasing mean value by 116 gC m\({}^{-2}\)yr\({}^{-1}\)) and grass pixels (decreasing mean value by 117 gC m\({}^{-2}\)yr\({}^{-1}\)).