## 4 Discussion  
Research shows that NEP simulated by the InTEC model is consistent with flux observation NEP at three flux sites (Figure 5), but there are still some errors and this can be analyzed from the following aspects. First, the _NPP-age_ relationship has an important impact on the simulation accuracy of NEP. However, there are a lot of forests of different ages in Zhejiang Province, and the age of forest resources survey gives the average age of the forests, which leads to NEP simulation error. Of course, NPP simulated by the BEPS model also includes a degree of error, and the transmission of its error may also affect the _NPP-age_ relationship, thus affecting the NEP simulation accuracy. Second, the kriging interpolation method was used to interpolate the forest age spatial distribution data, which has a larger kriging error for the spatial range away from the sampling plot [59]. There is a certain degree of error in the interpolation results of the spatial distribution of forest age, and it is inevitable to include error in important input data driving the InTEC model. Third, in this study, three sources of forest abundance data were used to drive the InTEC model, which solved the influence of mixed pixels on the NEP simulation to some extent. However, when the local average method is used to scale the forest distribution data, there will be errors [42], which affects the accuracy of NEP simulations. Fourth, due to the lack of deforestation data from Zhejiang Province, this study only considered the impact of falling in the initial years. This study did not consider the impact of fires because there are few fires in Zhejiang Province. These factors could also lead to errors in the results of the simulation. Although there are various uncertainties in the NEP spatiotemporal simulation of forest ecosystems in Zhejiang Province, the overall accuracy of our simulation is good, and the correlation coefficient of broadleaf forest is up to 0.75. Other than that, due to lack of spatial NEP distribution data, this study did not perform spatial verification; however, we have verified the accuracy of the model at the site scale to ensure the accuracy of the results. Therefore, the lack of spatial verification is acceptable. Figure 10: Relationship between NEP and (**a**) temperature (**b**) precipitation (**c**) relative humidity (**d**) radiation. During 1985-2015, the forest ecosystem NEP in Zhejiang Province showed an increasing trend, but it also experienced an evolution of spatiotemporal patterns from carbon source to carbon sink. After 1988, forests in Zhejiang Province gradually became dominated by carbon sink forests, and the forest carbon sink capacity gradually increased. From 1985 to 1988, forests in Zhejiang Province were carbon sources, with the NEP reaching \(-\)12.75 Tg\(\cdot\)C\(\cdot\)yr\({}^{-1}\). The main reason for this is that Zhejiang Province experienced serious man-made disturbances during this period, which led to the decline of forest quality and productivity [60]. After that, with the country's beginning to emphasize policies promoting forest resources such as the strengthening of forestry and returning farmland to forest policy [61], the forest quality of Zhejiang Province gradually improved. The forest structure has become more stable, the forest area has gradually increased, and the forest has gradually changed from young forest to a mixture of middle and young forest. Therefore, the forest carbon sink capacity of Zhejiang Province increased rapidly after 1988. It can be seen from Figure 6 that there was a significant increase in NEP in 2009. In addition to the above reasons, this can also be attributed to the precipitation surge and the suitable temperatures of 2009, during which better rain and heat conditions allowed NEP to increase rapidly. In addition, as shown in the spatial distribution of NEP (Figure 7), the carbon sink capacity in the eastern and southwestern parts of Zhejiang Province is strong, and that in the northeast is weak.