Biogeographic variability in wildfire severity and post-fire vegetation recovery across the European forests via remote sensing-derived spectral metrics.

Wildfires have large-scale and profound effects on forest ecosystems, and they force burned forest areas toward a wide range of post-fire successional trajectories from simple reduction of ecosystem functions to transitions to other stable non-forest states. Fire disturbances represent a key driver of changes in forest structure and composition due to post-fire succession processes, thus contributing to modify ecosystem resilience to subsequent disturbances. Here, we aimed to provide useful insights into wildfire severity and post-fire recovery processes at the European continental scale, contributing to improved description and interpretation of large-scale wildfire spatial patterns and their effects on forest ecosystems in the context of climate change. We analyzed fire severity and short-term post-fire vegetation recovery patterns across the European forests between 2004 and 2015 using Corine Land Cover Forest classes and bioregions, based on MODIS-derived spectral metrics of the relativized burn ratio (RBR), normalized difference vegetation index (NDVI) and relative recovery indicator (RRI). The RBR-based fire severity showed geographic differences and interannual variability in the Boreal bioregion compared to that in other biogeographic regions. The NBR-based RRI showed a slower post-fire vegetation recovery rate with respect to the NDVI, highlighting the differential sensitivities of the analyzed remote sensing-spectral metrics. Moreover, the RRI showed a significant decreasing trend during the observation period, suggesting a growing lag in post-fire vegetation recovery across European forests.