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Past fire recurrence impacts the vegetation structure, and it is consequently hypothesized to alter its future fire behaviour. We examined the fire behaviour in shrubland-forest mosaics of southeastern France, which were organized along a range of fire frequency (0 to 3-4 fires along the past 50 years) and had different time intervals between fires. The mosaic was dominated by Quercus suber L. and Erica-Cistus shrubland communities. We described the vegetation structure through measurements of tree height, base of tree crown or shrub layer, mean diameter, cover, plant water content and bulk density. We used the physical model Firetec to simulate the fire behaviour. Fire intensity, fire spread, plant water content and biomass loss varied significantly according to fire recurrence and vegetation structure, mainly linked to the time since the last fire, then the number of fires. These results confirm that past fire recurrence affects future fire behaviour, with multi-layered vegetation (particularly high shrublands) producing more intense fires, contrary to submature Quercus woodlands that have not burnt since 1959 and that are unlikely to reburn. Further simulations, with more vegetation scenes according to shrub and canopy covers, will complete this study in order to discuss the fire propagation risk in heterogeneous vegetation, particularly in the Mediterranean area, with a view to a local management of these ecosystems., (Copyright © 2015 Académie des sciences. Published by Elsevier SAS. All rights reserved.)

We investigated the power of near infrared (NIR) analysis for the quantitative assessment of soil quality in a wildfire chronosequence. The effect of wildfire disturbance and soil engineering activity of earthworms on soil organic matter quality was first assessed with principal component analysis of NIR spectra. Three soil quality indices were further calculated using an adaptation of the method proposed by Velasquez et al. [Velasquez, E., Lavelle, P., Andrade, M. GISQ, a multifunctional indicator of soil quality. Soil Biol Biochem 2007; 39: 3066-3080.], each one addressing an ecosystem service provided by soils: organic matter storage, nutrient supply and biological activity. Partial least squares regression models were developed to test the predicting ability of NIR analysis for these soil quality indices. All models reached coefficients of determination above 0.90 and ratios of performance to deviation above 2.8. This finding provides new opportunities for the monitoring of soil quality, using NIR scanning of soil samples.