Assessment of vegetation response to compound dry-hot events in Central Asia based on the Vine-Copula conditional probability model
Chun Yang, Hui Zhang, Zhijie Ta, Guan Huang, Yuke Liu
Abstract
• Developed a Vine Copula Conditional Probability (VCCP) model incorporating agricultural intensity to assess vegetation vulnerability under compound dry-hot events in Central Asia (1983-2022). • Revealed complex interactions between climate extremes and management intensity, with high-intensity agriculture showing enhanced early-summer resilience but diminishing effectiveness under prolonged extreme conditions. • Identified distinct spatial evolution patterns, with vulnerability shifting from major agricultural regions toward central areas throughout summer, and discovered beneficial effects of elevated temperatures in northern high-altitude regions. • Found croplands surpass grasslands in late-summer vulnerability under severe scenarios, despite initial management benefits (CI=0.2: 0.627 vs 0.596; CI=0.8: 0.570 vs 0.525), highlighting the seasonal limitations of agricultural management. Global climate change has intensified the frequency and severity of extreme drought and heat events, significantly impacting vegetation growth, particularly in the arid and semi-arid regions of Central Asia. This study employs the Vine Copula conditional probability model, incorporating vegetation (NDVI), drought (SPEI), temperature (STI), and cropland intensity (CI) indices, to quantify the impact of compound dry-hot events on vegetation under different agricultural intensities in Central Asia from 1983 to 2022. The results indicate significant variations in vegetation vulnerability under different levels of cropland coverage. Under low cropland intensity (CI = 0.2), vegetation vulnerability shows an increasing trend from June to August (S3: 70.31 % to 77.45 %), with high-probability areas gradually expanding eastward. Under high cropland intensity (CI = 0.8), vulnerability increases from June to July and then slightly decreases in August (S3: 67.82 % to 71.10 % to 71.60 %), showing a similar eastward progression. Different vegetation types exhibit distinct vulnerability patterns: grasslands generally show the highest sensitivity initially, while croplands demonstrate increasing vulnerability throughout summer, exceeding grassland probabilities by August (0.627 vs 0.596 under CI = 0.2, 0.570 vs 0.525 under CI = 0.8). Forests, predominantly distributed in northern mountainous regions (around 50⁰N), maintain the lowest vulnerability across all scenarios. The findings demonstrate the effectiveness of the Vine Copula model in assessing vegetation vulnerability to compound climate extremes under different cropland intensities, providing a scientific basis for ecosystem assessment and climate adaptation strategies in Central Asia.