## 4 Discussion
### Water (SM and P)-Caused Vegetation Anomalies  
Having derived global F statistic maps for all ELV\(\rightarrow\)VP links, the results were further subdivided into dominating biomes. In this way, terrestrial vegetation anomalies and sensitivity can be interpreted with additional spatial and climatological details. Throughout the analysis, the LAI expressed the greatest sensitivity for water availability, namely P and SM (mean F stat = 4.05 SM\(\rightarrow\)LAI, mean F stat. = 2.90 P\(\rightarrow\)LAI). The water availability-induced vegetation anomalies over arid biomes have been also confirmed by [58; 59; 60]. A possible reason why even small amounts of precipitation and soil moisture increments trigger a prominent positive change in vegetation productivity is the typical response of plant species dominantly inhabiting these (semi-) arid biomes. Variations in the frequency and magnitude of precipitation events can induce changes in the accessibility of water within shallow soil layers, leading to disparate configurations in both the profundity and the temporal extent of soil moisture infiltration [61]. The explanation of the VPs' strong water dependency in arid regions can be found in the literature. Plant genotypes in arid areas are adapted to the high variability in precipitation and show strong responses to pulsed inputs of rainfall events that drive season-long ecosystem dynamics [62; 63]. A water availability experiment on the dominant species (_Bouteloua gracilis_) was set up in this region [64]. This study concluded that the plant species showed positive responses: even a small rainfall event (\(\sim\)5 mm) increased the leaf water potential and stomatal conductance in less than 12 h and lasted for up to two days. Stomatal conductance is a key trait that is strongly associated with leaf carbon budget and photosynthetic activity [65], while leaf water potential is directly correlated to the LAI [66]. This sensitive response by vegetation aligns precisely with the observations made over arid regions, as depicted in the GC temporal profiles in Figure 2.  
An interesting phenomenon also occurred throughout the analysis of water-induced vegetation anomalies. Comparing the results of SM and P in Figure 5, a high causality of SM on vegetation over cold and polar biomes can be noticed but to a lesser extent for P, as was also noted by [PERSON] et al. [67]. The reasoning for the higher causality from SM can be explained by the snow cover. Throughout the melting seasonal snowpack, soil moisture increases and thus enhances vegetation productivity [68; 69]. The high causality on vegetation from snowmelt-induced increments in SM, especially over Northeastern Russia, was also recognized by [PERSON] et al. [70]. This finding is also confirmed by Figure 4, indicating the higher fractions of areas being explicitly caused on arid, cold, and polar biomes by SM. A noteworthy caveat is the case of the NDVI as compared to other VPs over polar biomes. The FAPAR, SIF, and the LAI causalities cover larger areas of the polar biome (0.3) than the NDVI (0.15). Due to the high spectral albedo of snow, even the lowest fractional snow covers will cause the NDVI measurement to be lower than the value for snow-free conditions [71]. Thus, even though vegetation greening occurs, the red and NIR signatures are suppressed by snow cover, and the satellite's sensor is unable to capture the underlying trends [72]. Using higher-level products such as the FAPAR, the LAI, and SIF bypasses the aforementioned issue.  
The negative effects of global changes arising from shifts in the frequency and magnitude of water availability are anticipated to exert influences on the bio-geochemical processes within ecosystems limited by water [73]. Furthermore, the arid ecosystem shall extend in its area across the globe, and it will put increasing pressure on our planet's ecosystem health; more areas will be highly dependent on water, as predicted by [PERSON] et al. [55].