Ana Daría Ruiz-González

Modelling the vertical distribution of canopy fuel load using national forest inventory and low-density airbone laser scanning data

The fuel complex variables canopy bulk density and canopy base height are often used to predict crown fire initiation and spread. Direct measurement of these variables is impractical, and they are usually estimated indirectly by modelling. Recent advances in predicting crown fire behaviour require accurate estimates of the complete vertical distribution of canopy fuels. The objectives of the present study were to model the vertical profile of available canopy fuel in pine stands by using data from the Spanish national forest inventory plus low-density airborne laser scanning (ALS) metrics. In a first step, the vertical distribution of the canopy fuel load was modelled using the Weibull probability density function. In a second step, two different systems of models were fitted to estimate the canopy variables defining the vertical distributions; the first system related these variables to stand variables obtained in a field inventory, and the second system related the canopy variables to airborne laser scanning metrics. The models of each system were fitted simultaneously to compensate the effects of the inherent cross-model correlation between the canopy variables. Heteroscedasticity was also analyzed, but no correction in the fitting process was necessary. The estimated canopy fuel load profiles from field variables explained 84% and 86% of the variation in canopy fuel load for maritime pine and radiata pine respectively; whereas the estimated canopy fuel load profiles from ALS metrics explained 52% and 49% of the variation for the same species. The proposed models can be used to assess the effectiveness of different forest management alternatives for reducing crown fire hazard.

Modelling canopy fuel dynamics of maritime pine stands in north-west Spain

Effective silvicultural strategies for reducing the likelihood and severity of crown fires include increasing canopy base height (CBH) and reducing canopy bulk density (CBD). These variables depend to a certain degree on stand structure and are therefore responsive to stand density management through thinning. In this study, data from permanent sample plots and thinning trials were used to model the dynamics of canopy fuel variables in maritime pine stands in north-western Spain. On the basis of the state–space modelling approach, the canopy fuel conditions at any point in time were assumed to be adequately defined by three state variables: number of stems per hectare (N), canopy fuel load (CFL) and CBH. These variables were projected by simultaneous fitting of three transition functions, which explained more than 77, 96 and 97% of the observed variability in N, CFL and CBH. The effect of thinning was modelled by including a thinning response function. Once the state variables were determined for a given point in time, CBD was derived from CFL, CBH and average stand height, thus ensuring compatibility between estimates. The system of equations developed, together with fire management decision support systems, will enable assessment of the crown fire potential associated with different silvicultural alternatives.

Assessing the effect of pruning and thinning on crown fire hazard in young Atlantic maritime pine forests

Management of fuel to minimize crown fire hazard is a key challenge in Atlantic forests, particularly for pine species. However, a better understanding of effectiveness of silvicultural treatments, especially forest pruning, for hazard reduction is required. Here we evaluate pruning and thinning as two essential silvicultural treatments for timber pine forests. Data came from a network of permanent plots of young maritime pine stands in northwestern Spain. Vertical profiles of canopy bulk density were estimated for field data and simulated scenarios of pruning and thinning using individual tree biomass equations. Analyses of variance were conducted to establish the influence of each silvicultural treatment on canopy fuel variables. Results confirm the important role of both pruning and thinning in the mitigation of crown fire hazard, and that the effectiveness of the treatments is related to their intensity. Finally, models to directly estimate the vertical profile of canopy bulk density (CBD) were fitted using the Weibull probability density function and usual stand variables as regressors. The models developed include variables sensitive to pruning and thinning interventions and provide useful information to prevent extreme fire behavior through effective silviculture.