## 3 Results
### Correlation of NEP, WUE, and CUE with Climate Variables  
#### 3.4.1 Correlation with Precipitation  
There were significant regional differences in the correlations among the factors (Figure 10). The correlation coefficients of precipitation (PRE) and NEP ranged from \(-0.60\) to \(0.73\), with a mean value of \(0.21\). In the northeastern part of the MRYR, the central part of Gansu, and the northwestern boundary of the MRYR, the NEP was significantly and positively correlated with precipitation (\(p<0.05\)), accounting for \(13.75\%\) of the MRYR. The NEP was negatively correlated with PRE in the central and southern parts of the MRYR. The correlation between the NEP and PRE was higher for the shrubs and grasslands, \(0.29\) and \(0.27\), respectively, and lower for the croplands and forests, \(0.18\) and \(0.13\), respectively. Among them, PRE was significantly and positively correlated with the NEP in \(11.45\%\) of the grasslands, \(9.58\%\) of the croplands, \(37.44\%\) of the shrubs, and \(11.89\%\) of the forests (\(p<0.05\)) (Figure 11). The forest NEP and PRE were predominantly positively correlated in northwestern Shanxi, while the forests in central and southern Shaanxi were predominantly negatively correlated.  
In the northern region, where grassland dominates, the vegetation is more able to regulate precipitation, and the WUE has a higher correlation with precipitation. A large area of negative correlation between the WUE and PRE is distributed in the south-central regions. There is a clear latitudinal zonality between water use efficiency and PRE in the MRYR. From south to north, it ranges from a negative correlation in the semi-humid zone to a positive correlation in the semi-arid zone. For the different vegetation types, positive correlations are dominant in the grasslands and croplands, while negative correlations are observed in the shrubs and forests. Among these, the grassland and cropland areas with a significant positive correlation (\(p<0.05\)) account for \(8.09\%\) and \(5.84\%\) of their respective areas, while the shrub and forest areas with a significant negative correlation (\(p<0.05\)) account for \(3.85\%\) and \(5.19\%\) of their respective areas (Figure 11).  
Figure 9: Interannual anomalies in NEP, WUE, CUE, and climate elements for different land covers in the MRYR, 2001–2022. **(a–d)** Grasslands, croplands, shrubs, and forests, respectively.  
The areas where the CUE and precipitation are negatively correlated are more widely distributed, involving more of the western region (Figure 10c). The PRE and CUE are  
Figure 11: Significance analysis of the correlations between NEP, WUE, CUE, and climate variables in the MRYR.  
Figure 10: Spatial distribution of correlations of NEP, WUE, and CUE with climate variables. (**a–c**) Correlations of NEP, WUE, and CUE with PRE, respectively; (**d–f**) correlations with TEM; and (**g–i**) correlations with DSI.  
predominantly positively correlated across the four vegetation types, with 9.40% of the grasslands, 8.78% of the croplands, 12.78% of the shrubs, and 4.92% of the forests significantly positively correlated with the CUE. Overall, the vegetation's NEP, WUE, and CUE in the MRYR show higher values in regions with more precipitation.