# Water Use Efficiency Spatiotemporal Change and Its Driving Analysis on the Mongolian Plateau
## 3 Results
### Potential Factors Affecting WUE Changes
#### 3.2.2 Geographical Detection Model for WUE Drivers  
The factor detector results showed that the highest degree of interpretation of NPP for WUE was 0.9066 (Figure 8a). The factors with q-values greater than 0.5 included NDVI (q = 0.7266), SW (q = 0.6009), and PRE (q = 0.5281), while TEM and ET had values below 0.5. SOS, EOS, and DSI had the lowest interpretation degrees, with q-values of less than 0.1. WUE is mainly influenced by PRE, TEM, SW, DSI, EOS, SOS, and NDVI, with NDVI and PRE showing collinear enhancements in WUE, as well as NDVI and TEM. PRE and SOS, as well as SW and EOS, have non-collinear enhancement effects on WUE. Thus, vegetation has a greater effect on WUE than water. The interaction detector results revealed that, apart from SOS and EOS, all other factors had nonlinear enhancement effects, and their interactions showed a linear enhancement effect on WUE.  
Figure 8: Geographical detection model: (**a**) calculation results of the factor detector and (**b**) factor interaction detector results between each driving factor and the annual WUE.  
2.3 Spatial Distribution of WUE Anomaly Resilience and Its Resistance to Vegetation and Meteorological Factor Anomalies  
It can be seen from the results in Figure 9a that the overall resilience of WUEA in the Mongolian Plateau is strong. The resilience of forest areas in Northeastern Inner Mongolia, especially broadleaved forest areas, as well as sandy land and artificial vegetation in the middle of Inner Mongolia, is weak, and the resilience of grassland ecosystems is strong as a whole. In addition, the forest NDVIA had a significant positive contribution to WUE, whereas the grassland ecosystem NDVIA had a significant negative contribution. WUE had weak resistance to NDVIA, mainly in humid forest areas and arid desert grassland zones.  
WUE had strong resistance to PREA overall, and only the desert steppes around the Gobi Desert and some agricultural land in the middle of Inner Mongolia had significant resistance (Figure 9c). WUE showed weak resistance to TEMA (Figure 9d). WUE was significantly positively correlated with TEMA in Central and Western Mongolia and Northeastern Inner Mongolia. A significant negative correlation was observed between Southern Mongolia and Central and Southern Inner Mongolia. The results show that TEMA has a strong effect on WUE and that it is not easy to recover from this. At the same time, the temperature anomalies in the cold, high-latitude areas and the warm, low-latitude areas show  
Figure 9: (**a**) shows the resilience index of WUE; (**b–f**) are the resistance indices of WUE regarding PREA, TEMA, SWA, and DSIA disturbances, respectively.  
the opposite trends in the interference of WUE. WUE also had strong resistance to SWA as a whole, especially in grassland ecosystems, but its significance was not high. However, its resistance to SWA disturbances in forest ecosystems in Mongolia and Northeastern Inner Mongolia was relatively weak (Figure 9e). WUE was weakly resistant to DSIA. The DSIA of grassland ecosystems made a significant positive contribution to WUE, whereas that of forest ecosystems made a significant negative contribution to WUE (Figure 9f). Overall, the WUE in the Mongolian Plateau had strong resistance to water anomalies, but weak resistance to temperature, drought, and vegetation greenness anomalies.  
Overall, the WUE on the Mongolian Plateau shows strong resilience to water anomalies but weak resistance to temperature, drought, and vegetation greenness anomalies, with forest ecosystems being more sensitive to temperature and drought disturbances.