Evaluating vegetation vulnerability under compound dry and hot conditions using vine copula across global lands

With global warming, climate extremes are intensifying, particularly compound dry and hot events (CDHEs), which would severely impact vegetation growth. However, quantitatively evaluating vegetation vulnerability to CDHEs remains challenging in global lands. A conditional probability model was constructed using the vine copula function to evaluate responses of vegetation to CDHEs based on the Standardized Moisture Anomaly Index (SZI), the Standardized Temperature Index (STI), and the kernel Normalized Difference Vegetation Index (kNDVI). The results show that vegetation growth is more susceptible to dry and hot conditions in arid and semi-arid regions than in sub-humid and humid regions. In terms of vegetation types, shrubs, savanna, grass, and crops are more susceptible to CDHEs than to individual dry or hot events, especially in water-limited regions. In arid regions, the vegetation vulnerability for open shrubs, closed shrubs, savanna, and grass under extreme CDHEs would correspondingly increase by 45%, 23%, 15%, and 12% compared with dry conditions, indicating the necessity to consider both dry and hot conditions simultaneously when evaluating vegetation dynamics to climatic extremes. In semi-arid and sub-humid regions, broadleaf forests show higher vulnerability to CDHEs than needleleaf forests. However, evergreen broadleaf forests show the lowest vulnerability and higher resistance to CDHEs in humid regions. The Analysis of Variance (ANOVA)-based uncertainty decomposition results show that copula combination sets in vine copula trees and vine copula structures are the two main uncertainty sources, accounting for about 60%. Despite with uncertainty, the modeling results show consistent vegetation loss probability patterns simulated with different structures of the vine copula model, indicating the robustness and reliability of the results. The findings provide a profound comprehension of ecosystems' response mechanisms to compound extremes, which are essential to developing effective mitigation and adaptation strategies against the impact of future climate change.