Evaluating the cumulative and time-lag effects of vegetation response to drought in Central Asia under changing environments

Central Asia (CA) is an arid region sensitive to climate change, and with the increase in drought events due to global warming, droughts are posing more severe threats to the vegetation in CA. However, the response of vegetation in CA to the cumulative and time-lag effects of prolonged drought remains unclear. This has limited our understanding of the mechanisms by which vegetation responds to meteorological drought in arid regions. To clarify the response of vegetation to drought in CA, this study analyzed the effects of drought and meteorological factors on vegetation growth dynamics. The extent of vegetation response to the cumulative and time-lag effects from 2001 to 2020 was evaluated using three satellite-derived vegetation indices (NDVI, EVI, NIRv) and the solar-induced chlorophyll fluorescence (SIF) and standardized precipitation evapotranspiration index (SPEI). We used the Copula-Bayes conditional probability method to assess the drought thresholds for vegetation under two scenarios: mild and severe losses. The effects of soil moisture (SM) and vapor pressure deficit (VPD) on vegetation dynamics were analyzed based on an improved partial wavelet coherence (PWC). The results show that the average response time of vegetation to the cumulative and lagged effects of drought was mostly concentrated within 4–6 months, and the lagged effect was stronger than the cumulative effect. The vegetation response to drought is nonlinear along the precipitation gradient. The SPEI values for triggering mild vegetation loss (below the 40th percentile) drought threshold range from −0.7 to −1.0, while the SPEI values for triggering severe vegetation loss (below the 10th percentile) drought threshold range from −2.0 to −2.5. The SM was the main driver affecting vegetation dynamics. This study provides deeper insight into the response of vegetation to drought in the arid zone of CA, which will further provide theoretical support for addressing global climate change and extreme drought events.