Geospatial fire behaviour and fire hazard simulators, fire effects models and smoke emission software commonly use standard fuel models in order to simplify data collection and the inclusion of complex fuel scenarios. These fuel models are often mapped using remotely sensed data. However, given the great complexity of fuelbeds, with properties that vary widely in both time and space, the use of these standard fuel models can greatly limit accurate fuel mapping. This affects fuel hazard assessment, fuel reduction treatment plans, fire management decision-making and evaluation of the environmental impact of wildfire. In this study, we developed unique customized fire behaviour fuel models for shrub and bracken communities, by using k-medoids clustering analysis based on both fuel structural characteristics and potential fire behaviour. We used an original database of 722 destructive sample plots in nine different shrub and bracken communities covering the entire distribution area in Galicia (NW Spain), one of the regions in Europe most affected by forest fires. Measurements of cover, height and fuel fractions loads differentiated by size and vegetative state (live or dead) were used to estimate the potential rate of fire spread with five different models including fireline intensity, heat per unit area and the flame length for each sampling site and considering extreme environmental conditions. The optimal number of clusters was established by combining practical knowledge about the shrubland communities under study and their associated fire behaviour, with maximization of the mean value of the silhouette variable and minimization of the within-cluster sum of squares. The structural characteristics of the medoids derived from the analysis were associated with each of the proposed customized fuel models. Finally, a simple dichotomous classification based only on shrub height was developed to enable construction of spatially explicit fuel model maps based on remotely sensed data. Thus, the methodology applied allows generation of a more realistic representation of fuel distribution in the landscape, based on fuel structure measurements of natural regional ecosystems rather than on the use of standard models. We believe that the proposed methodology is generally applicable to communities composed of other shrub and fern species in different biogeographical regions.

Little is known about the interactions between the variables involved in the post-fire response of Mediterranean pine species to prescribed burning (PB). Thus, it is essential to develop an empirical model in order to assess the influence of tree and stand attributes, burn season, and fire severity on the probability of stem cambium damage occurring. Prescribed burnings were conducted in different seasons and areas covering a wide climatic and ecological range. Potential explanatory variables were measured. A random effects hurdle model framework was used to evaluate the temperature duration above 60 °C as a proxy for stem cambium damage at tree scale. The results showed significant differences in cambium damage between the PB seasons. Pinus nigra was more resistant than other pine species. Bark thickness was critical for protecting cambium. Volume of crown scorch, percentage of stem scorch, and maximum outer bark temperature were directly related to temperature duration above 60 °C in the cambium. Prescribed burning conducted under tree canopy in Mediterranean pine species generally results in a low level of cambium damage. Empirical models could help managers to predict the effects of PB and thus select the most suitable prescriptions.

Pine forests and shrublands worldwide are increasingly threatened by wildfires driven by global change, and those of temperate-humid ecosystems are no exception. Although the impact of soil bacterial of soil burn severity (SBS) on bacterial communities, has been examined in a number of studies, knowledge about their response across gradients of high SBS levels remains limited. In this study, we assessed the early effect (six weeks post-wildfire) of an SBS gradient, from moderate to extreme, previously defined, on bacterial communities in topsoil (0-2 cm) under adjacent pine and shrubland vegetation in northwestern Spain. Alpha diversity declined under moderate SBS, but no further decrease was observed at higher severity. Beta diversity increased, but community composition stabilized from moderate severity onwards, suggesting a threshold above which further compositional shifts are limited. Burned soils were enriched in Proteobacteria, Bacteroidetes, and Firmicutes, while Acidobacteria and Actinobacteria declined. Known pyrophilic genera (e.g. Massilia, Pedobacter), and others not previously reported with that character, were more abundant in burned soils. However, their increase did not extend beyond moderate SBS, reinforcing the notion of a compositional threshold. This stabilization may reflect the fire selection of fire-adapted communities' composition. Vegetation type, although a weaker driver than SBS, modulated bacterial responses: unburned pine and shrubland soils hosted similar communities that diverged after fire, with shrubland soils showing greater sensitivity. Soil pH, C, and C/N were strongly associated with bacterial composition. Our study provides evidence that moderate SBS may be sufficient to drive major shifts in soil bacterial communities, and that higher SBS levels do not necessarily lead to further changes, although confirmation through new studies is needed. The study findings may be useful for developing methods of accelerating the recovery of burned soils.