## 3 Results
### Calibration and Validation for Each Model  
Table 3 shows the statistic summaries for the results of AVM, GR, TG VPM, and MOD_ALG at the periods of calibration and validation. Each model performs well at most sites in the period of calibration, indicating that these models have potential to capture the physical process of GPP variations. For AVM, R\({}^{2}\) values range from 0.29 (EBF) to 0.97 (MF) during the model calibration; RMSE varies from 25.98% in MF to 67.78% for croplands. It was discovered that AVM slightly underestimates GPP_EC for each land cover type from \(-\)0.64 gC/m\({}^{2}\)/eight-day (grasslands) to \(-\)16.78 gC/m\({}^{2}\)/eight-day (EBF). At the same time, R\({}^{2}\) values vary from 0.26 in EBF to 0.83 in grasslands; RMSE varies from 46.31% in ENF to 114.92% in grasslands for GR model. The GR model also slightly overestimates GPP_EC in MF, croplands and grasslands, and underestimates GPP_EC in evergreen forests. A similar phenomenon has also been found at AmeriFlux sites [27]. For the TG model, R\({}^{2}\) values range from 0.36 in EBF to 0.94 in MF; RMSE ranges from 25.58% in MF to 59.69% in croplands. The TG model generally underestimates GPP_EC, except in grasslands. For VPM, R\({}^{2}\) values range from 0.36 in EBF to 0.89 in grasslands; RMSE ranges from 41.23% in MF to 59.80% in grasslands. The VPM underestimates GPP_EC in most land cover types except for grasslands. For MOD_ALG, R\({}^{2}\) values vary from 0.17 in EBF to 0.89 in grasslands; RMSE varies from 51.81% in croplands to 77.42% in EBF. MOD_ALG usually underestimates GPP_EC, except in grasslands and croplands. Parameters of the amount of carbon fixed in photosynthesis (m) or LUE (\(\epsilon_{\mathrm{max}}\)) in different models for each land cover type are shown in Table 4. In MOD17 LOOKUP table [17], the \(\epsilon_{\mathrm{max}}\) of MF, ENF, and grasslands (5.44 gC/MJ/eight-day, 8.06 gC/MJ/eight-day, and 5.44 gC/MJ/eight-day, respectively) are close to values of MOD_ALG, but the \(\epsilon_{\mathrm{max}}\) of croplands (5.44 gC/MJ/eight-day) is  
Figure 2: Relationship between the flux measured GPP (GPP_EC, X-axis) and results of MOD17 (Y-axis) for five different land cover types. The dashed line indicates 1:1 line. The red solid line indicates a linear trend for all types. lower than the value of MOD_ALG, and the \(\varepsilon_{\text{max}}\) of EBF (9.27 gC/MJ/eight-day) is lower than the value of MOD_ALG. The large variation of \(\varepsilon_{\text{max}}\) in EBF and croplands suggest that more calibrations of LUE are necessary. In the process of model validation, the above five GPP models also perform well in most land cover types. R\({}^{2}\) values are generally larger than those in model calibration, except in ENF and EBF; for example, R\({}^{2}\) values are higher than 0.79 and 0.94 in MF and grasslands, respectively; R\({}^{2}\) between measured and estimated GPP in croplands ranges from 0.76 for AVM to 0.91 for VPM. Interestingly, although GR, TG, and MOD_ALG do not show good performance in the model calibration for croplands, all three models show better results in the model validation. However, the validation performance in ENF is poorer than that in calibration. Extreme values existing in the periods of calibration and validation may explain the discrepancy. From the above analysis, we can conclude that the five models above can be used for GPP estimations in different ecosystems in China.