Dynamics of vegetation response patterns to drought and its driving factors across China's Loess Plateau

Drought significantly affects terrestrial vegetation. Although several studies have explored vegetation response patterns to drought (VRPD), the dynamics and underlying driving factors remain unclear. This study examined the dynamics of VRPD using long-term gross primary productivity (GPP) data and multi-scale standardized precipitation evapotranspiration index (SPEI) across China's Loess Plateau (CLP). Our results indicate that vegetation in the semi-arid zone of CLP is most impacted by drought and exhibits the fastest response to drought. From 1982 to 2018, drought impacts on vegetation in the region significantly weakened, while vegetation response time to drought also significantly shortened (p < 0.01). Explainable machine learning analysis revealed that the reduced impact of drought on vegetation is due to increased precipitation and vegetation recovery. In contrast, shortened response time is associated with increased downward surface shortwave radiation and temperature. These results suggest that under the background of climate change and vegetation recovery, the VRPD in CLP significantly changed, highlight the necessary to strike a balance between ecological restoration and climate adaptation for ensuring the CLP evolves from "greening" toward "sustainably green".