## 3 Results
### Correlations Between WUE, GPP, and ET and Driving Factors  
To detect the key factors driving GPP, ET, and WUE, a partial correlation analysis was conducted to reveal the correlations between WUE, GPP, ET, and the six driving factors, and result shown in Figure 4. The results revealed that PRE had a significantly stronger influence on GPP, ET, and WUE than the other climate factors and exhibited distinct spatial distribution characteristics. In northern China, specifically in arid and semiarid areas, PRE was positively correlated with both GPP and WUE, which was particularly pronounced in the mid-temperate semiarid region (II) (the average values were 0.59 and 0.44, respectively). However, a negative correlation was observed in the plateau temperate semiarid region (IV), the northern subtropical humid region (VI), and the edge tropical warm region (VII). In addition, PRE exhibited a significant positive correlation with ET across northern China, with average correlations exceeding 0.6 and some areas exceeding 0.9, especially in the mid-temperate semiarid region (II) and plateau temperate semiarid region (IV). However, a significant negative correlation was observed in the northern part of the northern subtropical zone (VI). RAD was the second main factor affecting GPP and WUE. Spatially, regions with a positive correlation between RAD and GPP and WUE were distributed mainly in central and eastern China, including the mid-temperate semiarid region (II), northern subtropical humid region (VI), and northern subtropical humid region (VI). Conversely, a significant negative correlation was observed in the western part of the mid-temperate and semihumid region (III). The impact of RAD on ET was most significant in the northern subtropical humid region (VI) and the mid-temperate and semiarid region (III), with the overall average exceeding 0.6 on average. However, a significant negative correlation was observed in the mid-temperate region (I). The influence of TEM on GPP and WUE was relatively weak, except for an average correlation exceeding 0.2 in the northern subtropical humid region (VI); all other regions presented average correlations below 0.2. The impact of temperature on ET is primarily concentrated in the mid-temperate semiarid region (II) and plateau temperate semiarid regions (IV), where it is generally positively correlated. In some areas, the positive correlation exceeded 0.9, but there were also significant negative correlations distributed across the region.  
The responses of GPP, ET, and WUE to the LAI were significantly stronger than those of other driving factors, indicating a generally strong positive correlation. Except for sporadic negative correlations observed in the northern subtropical humid region (VI) and edge tropical warm region (VII) for GPP and WUE, the majority of the significant areas presented positive correlations. The spatial patterns of the influence of SM on the three indicators were highly similar to those of PRE. A significant positive correlation existed in the warm temperate semihumid region (V) and in the mid-temperate and semihumid region (III). Conversely, negative correlations were observed in parts of the northern subtropical humid region (VI) and the edge tropical warm region (VII). Additionally, the spatial distributions of the VPD impacts on GPP and ET exhibited a high degree of consistency. A positive correlation predominated in the plateau temperate semiarid region (IV), whereas a negative correlation was the main feature in the mid-temperate semiarid region (II), mid-temperate and semihumid region (III), northern subtropical humid region (VI), and edge tropical warm region (VII). The influence of VPD on WUE was particularly pronounced in the plateau temperate semiarid region (IV), where a positive correlation was dominant.