## 3 Results  
### Optimization of the MOD_17 Model  
The optimized MOD_17 model was used to estimate the forest GPP in the Greater Khingan Mountains forest area of Inner Mongolia. Figure 3 shows the distribution of GPP in different forest types in 2012, 2013, 2014, and 2015. The highest GPP values was acquired by deciduous confierous forest (DNF), next was deciduous broad-leaved forest (DBF), then the third was mixed coniferous (MF). \begin{table}
\begin{tabular}{c c c} \hline \hline
**Number** & **Parameter** & **Description** & **Unit** \\ \hline
21 & FRlab & P fine root labile proportion & DIM \\
22 & FRcel & fine root cellulose proportion & DIM \\
23 & Flab & fruit litter labile proportion & DIM \\
24 & Fcel & fruit litter cellulose proportion & DIM \\
25 & DWcel & dead wood cellulose proportion & DIM \\
26 & Wnt & canopy water interception coefficient & 1/LAI/d \\
27 & k & canopy hight extinction coefficient & DIM \\
28 & SPLR & all-sided to projected leaf area ratio & DIM \\
29 & LAIall-pro & ratio of shaded SLA:sunlit SLA & DIM \\
30 & FLNR & fraction of leaf N in Rubisco & DIM \\
31 & gsmax & maximum stomatal conductance (projected area basis) & m/s \\
32 & gcl & conductance (projected area basis) & m/s \\
33 & gbl & boundary layer conductance (projected area basis) & m/s \\
34 & SW & stem weight corresponding to maximum height & (kgC) \\
35 & Rdmax & maximum depth of rooting zone & (m) \\
36 & GR & growth resp per unit of C grown & (prop.) \\
37 & MRperm & maintenance respiration in kg C/day per kg of tissue N & (kgC/kgN/d) \\
38 & NSCScmax & theoretical maximum prop. of non-structural and structural carbohydrates & (DIM) \\
39 & NSCMR & of non-structural carbohydrates available for maintenance respiration & (DIM) \\
40 & SWClim2 & minimum of soil moisture limit2 multiplicator (full anoxic stress value) & prop \\
41 & VPDs & vapor pressure deficit: start of conductance reduction & Pa \\
42 & VPDc & vapor pressure deficit: complete conductance reduction & Pa \\
43 & TRwsl & turnover rate of willed standing biomass to litter & prop \\
44 & TRwvl & turnover rate of non-woody cut-down biomass to litter & prop \\
45 & SLA1 & canopy average specific leaf area in phenological phase 1 & m\({}^{2}\)/kg \\
46 & SLA2 & canopy average specific leaf area in phenological phase 2 & m\({}^{2}\)/kg \\
47 & SLA3 & canopy average specific leaf area in phenological phase 3 & m\({}^{2}\)/kg \\
48 & SLA4 & canopy average specific leaf area in phenological phase 4 & m\({}^{2}\)/kg \\
49 & SLA5 & canopy average specific leaf area in phenological phase 5 & m\({}^{2}\)/kg \\
50 & SLA6 & canopy average specific leaf area in phenological phase 6 & m\({}^{2}\)/kg \\
51 & SLA7 & canopy average specific leaf area in phenological phase 7 & m\({}^{2}\)/kg \\ \hline \hline \end{tabular}
\end{table} 
Table 1: _Cont._The highest value for DBF GPP was in 2013 and the highest value for DNF and MF GPP was in 2014. Table 2 shows the descriptive statistical results of the annual mean value of GPP for different forest types, including year, forest type, number of pixels (Count), mean (Mean), maximum value (Max), minimum value (Min), standard deviation (STD), and coefficient of variation (CV). The uncertainty (CV) fluctuation of DBF had the largest range, spanning from 16.1% to 22.39%, and the range of GPP value was 108.4-1312.03 g/C/m\({}^{2}\)/year. The smallest uncertainty fluctuation range of DNF ranged from 14.34% to 17.03%, and the GPP value range was from 353.94 to 1643.15 g/C/m\({}^{2}\)/year. In general, the uncertainty fluctuation range of GPP was [14.34%, 22.39%], the annual average value of GPP ranged from 561.34 to 1008.21 g/C/m\({}^{2}\)/year, and the range of GPP value was [108.4, 1643.15] g/C/m\({}^{2}\)/year.