Abstract
Understanding and predicting fuel moisture content (FMC) is a crucial prerequisite to increase our knowledge of forest’s vulnerability to fires in a changing climate. While live fuel moisture content (LFMC) is a main driver of fire behavior and activity in crown fires in forests and shrublands, it remains poorly understood and predicted, especially under extreme drought. A major reason for that is that LFMC sensitivity to climate is mediated by a range of location-specific factors, including soil characteristics and plant response to drought. Another reason is that LFMC is often simulated at the leaf scale while, from a fire danger perspective, canopy scale fuel moisture content (CFMC) is more relevant. Here we introduced a FMC module in the plant-hydraulic SurEau-Ecos model to simulate the dynamics of both LFMC and CFMC as a function of leaf water potential (psi_{Leaf}). CFMC integrates the impacts on moisture content of foliage mortality that can occur under extreme drought because of leaf embolism. SurEau-Ecos-FMC relies on two main mechanisms. The relationship between psi_{Leaf} and leaf relative water content of the symplasm is modeled through pressure volume curves. Percent loss of leaf conductance (PLC) is derived from psi_{Leaf} through vulnerability curves to cavitation and affects the dynamics of fuel moisture content in two different ways. At the leaf level, PLC dictates the dynamics of the leaf apoplasmic reservoir. At the canopy level, PLC drives the proportion of dead fuel within the canopy. SurEau-Ecos-FMC captured relatively well the temporal dynamics of LFMC measured in a Quercus ilex stand at the Puéchabon site over a three-years period. The model explained 69 % (RMSE = 4.27) and 74 % (RMSE = 4.92) of the variance in the minimum and maximum daily observed LFMC, respectively. The model was also able to capture the dynamics in CFMC resulting from leaf mortality during the summer drought. Indeed, we showed that the years when SurEau-Ecos-FMC predicted leaf mortality were the ones with the highest anomaly in NDVI. Multi-model projections of fire danger indices based on CFMC showed a general increase of fire danger over the next century. Under RCP8.5, the averaged minimum CFMC reached during the year is expected to decrease from 65 % to 32 % and the fire season length (number of day when CFMC