Relationship between heatwave‐induced forest die‐off and climatic suitability in multiple tree species

In recent decades, many forest die-off events have been reported in relation to climate-change-induced episodes, such as droughts and heat waves. To understand how these extreme climatic events induce forest die-off, it is important to find a tool to standardize the climatic conditions experienced by different populations during a specific climatic event, taking into account the historic climatic conditions of the site where these populations live (bioclimatic niche). In this study, we used estimates of climatic suitability calculated from species distribution models (SDMs) for such purpose. We studied forest die-off across France during the 2003 heatwave that affected Western Europe, using 2,943 forest inventory plots dominated by 14 single tree species. Die-off severity was estimated by Normalized Difference Vegetation Index (NDVI) loss using Moderate-resolution Imaging Spectroradiometer remote sensor imagery. Climatic suitability at the local level during the historical 1979-2002 period (HCS), the episode time (2003; ECS) and suitability deviance during the historical period (HCS-SD) were calculated for each species by means of boosted regression tree models using the CHELSA climate database and occurrences extracted from European forest inventories. Low HCS-SD and high mean annual temperature explained the overall regional pattern of vulnerability to die-off across different monospecific forests. The combination of high historical and low episode climatic suitability also contributed significantly to overall forest die-off. Furthermore, we observed different species-specific relationships between die-off vulnerability and climatic suitability: Sub-Mediterranean and Mediterranean species tended to be vulnerable in historically more suitable localities (high HCS), whereas Euro-Siberian species presented greater vulnerability when the hot drought episode was more intense. We demonstrated that at regional scale, past climatic legacy plays an important role in explaining NDVI loss during the episode. Moreover, we demonstrated that SDMs-derived indexes, such as HCS, ECS and HCS-SD, could constitute a tool for standardizing the ways that populations and species experience climatic variability across time and space.