The climate-fire nexus: Understanding post-fire vegetation recovery

In Mediterranean ecosystems, high-frequency hydroclimatic variability, along with shifts in the fire regime, are key drivers of forest degradation. In this context, understanding post-fire vegetation recovery is crucial for both ecological research and forest management standpoint. Satellite-based remote sensing, particularly through orbital platforms, provides a robust framework for tracking post-fire vegetation dynamics. We assessed recovery patterns across 30 fire-affected areas in Aragón (northeastern Spain) by analyzing temporal trends in the Leaf Area Index (LAI), a widely used proxy for canopy structure, primary productivity, and vegetation health. Using Generalized Linear Mixed Models (GLMMs), we modeled LAI trajectories as a function of fire severity, dominant plant regenerative traits, and post-fire climatic conditions (drought or wet periods), including fire location as a random effect to account for spatial heterogeneity among burn sites. The models showed strong predictive capacity (R² ≈ 0.80), and the inclusion of random effects substantially improved model fit, underscoring the importance of site-specific factors in shaping recovery dynamics. Fire severity and post-fire moisture availability—particularly during the first years—were the most influential drivers of LAI regeneration. The regeneration mechanism of dominant vegetation also contributed to early post-fire recovery, although its influence diminished over time. From a forest management perspective, these findings can inform the design of post-fire recovery strategies based on different post-fire moisture and severity conditions. • LAI trend analysis provides key insights into post-fire vegetation recovery. • Positive LAI trends occur within the first 24 months post-fire. • High burn severity and drought hinder first-year vegetation recovery. • Species reproductive strategies influence early-stage LAI recovery.