## 3 Results
### Analysis of Dominant Factors for Extreme Changes in WUE
#### 3.1.2 The Relationship Between the Key Drivers of Extreme Variations in WUE and Water Supply  
The carbon-water coupling processes of vegetation are driven by its water availability, which is predominantly regulated by precipitation [63]. Therefore, to investigate whether the dominant factors driving WUE variation across different regions are also regulated by precipitation, nonlinear and linear fitting analyses were conducted between the mean annual precipitation of seven regions and the areas where only GPP and only ET drive WUE extreme variation. The results indicate that GPP and ET exhibit opposite patterns of sensitivity to increasing precipitation. When vegetation water use is maximized (WUEmax), the relationship between regional annual precipitation and the area dominated by GPP exhibits a trend of decline followed by an increase, and in semi-arid and semi-humid areas,the control of precipitation on vegetation carbon sequestration is relatively weak (Figure 3a). In contrast, when vegetation water use is under stress (WUEmin), the trend of this nonlinear variation disappears. GPP shows a highly significant positive correlation with precipitation (\(R^{2}\) = 0.72, \(p\) < 0.01) (Figure 3b). ET presents a negative correlation when vegetation water use is most efficient (WUEmax) (\(R^{2}\) = 0.47, \(p\) > 0.05) and a significantly negative correlation when WUE is under stress (WUEmin) with precipitation (\(R^{2}\) = 0.65, \(p\) < 0.05) (Figure 3c,d). The above results indicate that vegetation extreme WUE in China shows a significant linear response to precipitation when facing water stress.  
To explore the relationship between extreme WUE and climatic conditions, we analyzed drought occurrences across different regions when WUE was at extreme levels (Figure 4). The results indicate that, during periods of maximum vegetation WUE, the climate in the eastern part of the SW, the eastern NW, and the western NE is relatively humid, while the southern NE and eastern NE experience drier conditions (Figure 4a). Conversely, when WUE reaches its minimum, drought severity intensifies in NE, EC, and SC, with the area under drought conditions increasing by 7.98%, 29.71%, and 7.69%, respectively (Figure 4b,d). The regions experiencing increased aridity are mainly located in the northeastern part of the NE, the southern EC, and the northern SC, with vegetation predominantly consisting of WSN and SN (Figure 4a,c). Overall, when WUE reaches its minimum value, the proportion of areas in China experiencing normal climatic conditions decreases by 7.51%, while the proportion of areas classified as drought-prone increases by 6.71%. This indicates that lower WUE values are linked to a greater likelihood of arid meteorological conditions, particularly in the NE, EC, and SC (Figure 4b,d).  
Figure 2: Spatial distribution of the dominant factor (either GPP, ET, or GPP and ET) controlling annual WUE extreme variation during 2001–2020. (**a**) WUEmax; (**c**) WUEmin. Area covered (in percentage) by contributions of the driving factors. (**b**) WUEmax; (**d**) WUEmin.  
Figure 4: The spatial pattern of the SPEI-12 corresponding to extreme WUE (**a**) WUE\({}_{\text{max}}\) and (**c**) WUE\({}_{\text{min}}\) at annual scale. The regional proportions of statistical distribution for drought years, normal years, and humid years. (**b**) WUE\({}_{\text{max}}\), 2001–2020; (**d**) WUE\({}_{\text{min}}\), 2001–2020.  
Figure 3: The area of regions controlled solely by GPP and ET under extreme vegetation WUE conditions across seven geographical regions from 2001 to 2020, along with their fitted estimates against regional annual precipitation. The green line represents GPP, and the red line represents ET. (**a**) WUE\({}_{\text{max}}\), GPP controlled; (**b**) WUE\({}_{\text{min}}\), GPP controlled; (**c**) WUE\({}_{\text{max}}\), ET controlled; (**d**) WUE\({}_{\text{min}}\), ET controlled.