## 1 Introduction  
With the intensification of global climate change and anthropogenic activities, the frequency and severity of droughts have increased annually [1, 2, 3, 4]. Drought affects ecosystems by altering soil moisture, nutrient conditions, community structure, productivity, and carbon cycling [5,6]. Drought has led to a reduction in the net primary productivity (NPP) of global terrestrial ecosystems by 0.55 PgC per year [3] and has significantly changed the plant community structure in some regions, particularly in arid areas. As the foundation of ecosystems, vegetation is sensitive to changes and can reflect the response of ecosystems to climate change; thus, it is regarded as an \"indicator\" of global change [7]. Drought not only affects the physiological processes of vegetation (such as photosynthesis and respiration) by reducing water supply but also manifests at the structural level of vegetation, leading to a notable decline in vegetation growth conditions [8,9]. Research indicates that the climate of China tends to be arid, and the wet-dry pattern has changed [10]. Xinjiang is the most arid region in China and has the largest arid land area, with the largest deserts, extensive desert forests, and grassland areas. Over the past 20 years, the drought pattern in Xinjiang has changed, with an overall trend toward increased humidity and gradual increases in precipitation [11]. However, research on the ecological responses of natural forests and grasslands to meteorological drought in extremely arid areas in the context of climate change is insufficient. Meteorological drought indices serve as proxies for tracking and quantifying climate change. Commonly used meteorological drought indices include the standardized precipitation index (SPI), the Palmer drought severity index (PDSI), and the standardized precipitation evapotranspiration index (SPEI) [12]. Among these, the SPEI combines the multi-timescale advantages of the SPI while considering the impact of temperature on drought and evaluating the degree of water deficit through the difference between precipitation and potential evapotranspiration (PET) [13]. Consequently, SPEI is widely used to characterize climate change, especially showing high applicability in monitoring the characteristics of wet and dry climates in Xinjiang. Although several scholars have conducted relevant research on vegetation and climate change in Xinjiang [14, 15, 16], most studies have focused on the correlation between single climatic factors and vegetation cover [17,18] and the timescale of the study is relatively limited, making it difficult to comprehensively reflect the impact of climate change on vegetation. Studies have shown the lagged and cumulative effects of drought on vegetation [19]. [PERSON] et al. [20] found that more than 70% of global terrestrial vegetation is affected by persistent drought, as evidenced by the use of SPEI. [PERSON] et al. [21] reported that drought simultaneously induces both lagged and cumulative effects on most vegetation types. Therefore, the use of a multiscale SPEI to characterize regional climate change can more effectively reveal the complex response mechanisms of vegetation to climate change. Vegetation indices are widely used to characterize the response of vegetation to climate change. Several scholars have used vegetation indices, such as the normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and vegetation condition index (VCI), to analyze the response mechanisms of vegetation growth to drought at the regional scale in combination with annual precipitation, soil moisture, and SPEI [22,23]. However, these vegetation indices primarily reflect the response of the vegetation canopy to drought and do not directly reflect the state of vegetation physiological activity under drought stress. Chlorophyll fluorescence is closely linked to photosynthesis and represents a rapid light signal released by plants after absorbing sunlight [24].