## 4 Discussion
### The Decoupled Effects of RSM and PRE on GPP  
[PERSON] et al. examined the independent effects of temperature and relative RSM on global GPP through data binning techniques, revealing that RSM exerted a more substantial influence on vegetation productivity than temperature in arid and semi-arid regions [18]. Similarly, investigations into the impacts of VPD and RSM on ecosystem productivity indicated that VPD predominantly governed GPP variability in humid ecosystems, whereas RSM was the primary driver of GPP fluctuations in arid and semi-arid ecosystems [24]. In the present study, statistical analyses of \(SA_{GPP}\) under varying environmental conditions were conducted using data binning. Results demonstrated that \(SA_{GPP}\) values were higher when RSM increased (\(SA_{RSM}>0\) or \(SA_{RSM}>1\)) concurrently with decreasing PRE (\(SA_{PRE}<0\) or \(SA_{PRE}<-1\)), compared to scenarios where RSM decreased (\(SA_{RSM}<0\) or \(SA_{RSM}<-1\)) alongside increasing PRE (\(SA_{PRE}>0\) or \(SA_{PRE}>1\)). These findings corroborate previous research indicating that RSM exerts a stronger influence than PRE on GPP within China's arid and semi-arid zones. Enhanced RSM in these regions improves water availability, thereby augmenting carbon sequestration capacity [19]. Further studies focusing on PRE sensitivity and its driving factors within China's agricultural systems identified RSM as the dominant determinant of GPP-PRE sensitivity [59]. This is likely attributable to PRE first replenishing RSM, which subsequently supplies water directly to vegetation via root-soil interactions. [PERSON] et al. analyzed vegetation GPP dynamics across China from 1998 to 2019, elucidating drought response and recovery patterns; notably, summer exhibited the highest recovery efficiency, with 41% of recovery duration attributed to RSM replenishment [60]. As illustrated in Figure 6a,b, within data bins characterized by PRE decline (\(SA_{PRE}\) intervals [\(-2\), \(-1.5\)) or [\(-1.5\), \(-1\))], the magnitude of \(SA_{GPP}\) increase associated with rising \(SA_{RSM}\) exceeded that observed in bins of RSM decline (\(SA_{RSM}\) intervals (\(-2\), \(-1.5\)) or (\(-1.5\), \(-1\))) accompanied by increasing \(SA_{PRE}\). This pattern underscores the more direct role of RSM in promoting GPP variability within the study area. Moreover, \(SA_{GPP}\) change rates within RSM increase bins (\(SA_{RSM}\) intervals (\(1\), \(1.5\)) or (\(1.5\), \(2\))) exhibited a deceleration or stabilization trend with respect to \(SA_{PRE}\), whereas in precipitation increase bins (\(SA_{PRE}\) intervals (\(1\), \(1.5\)) or (\(1.5\), \(2\))), \(SA_{GPP}\) change rates accelerated with \(SA_{RSM}\). These observations provide additional evidence that increases in RSM more directly enhance regional GPP growth. In arid and semi-arid ecosystems, sparse grasslands and shrublands are predominantly influenced by RSM [24]. Under drought conditions, these vegetation types tend to adopt conservative water use strategies characterized by supportive and defensive traits, such as reduced leaf length and elevated root-to-shoot ratios [61]. In barren or sparsely vegetated landscapes, vegetation can exploit RSM for water storage, thereby diminishing reliance on PRE and maintaining photosynthetic activity even during periods of reduced PRE [61]. The metric \(\Delta SA_{GPP}(SA_{RSM}\mid SA_{PRE})\) attained its highest mean value (\(0.533\)) in barren or sparsely vegetated lands, followed by grasslands, indicating RSM had greater influence on GPP in these zones of China's arid and semi-arid areas (Figure 7). Physiologically, RSM exerts more direct control over vegetation than PRE by regulating stomatal conductance, which in turn affects both photosynthesis and transpiration. Reduced RSM elevates land surface temperature and VPD, further inhibiting plant productivity [62].