Use of national forest inventory data to develop stand density driven models for understorey shrubs and overstorey fuel variables and associated temporal dynamics in commercial plantations

Abstract

Biomass tends to accumulate both in overstorey and understorey layers of forests growing in productive areas. The rapid growth of forest plantations established in productive areas can thus also lead to the creation of fire-prone landscapes. In this study, we assessed the extent to which overstorey stand density determines current values of the fine shrub fuel load (Wshr_G1) in the understorey and also two major canopy fuel characteristics related to crown fire activity -canopy base height (CBH) and canopy bulk density (CBD)- and the temporal dynamics of these. For this purpose, we developed two types of models for the three fuel complex variables: i) extreme response models, to define the upper limit of Wshr_G1 and CBD and the lower limit of CBH, the values of which may depend on stand density; and ii) dynamic models, to estimate the probability of increasing fuel loads and rate of change when a more hazardous situation is predicted. Data were obtained from 8087 plots, measured in the third, fourth and fifth Spanish National Forest Inventories, in plantations dominated by the major commercial species in northern Spain (Pinus pinaster, Pinus radiata, Pinus sylvestris and Eucalyptus globulus). The extreme response models generally explain more than 60% of the observed variability in the three fuel complex variables. According to these models, maximum shrub fuel load and CBD and minimum CBH in stands of the four tree species were limited by stand basal area, with different responses by different species. The dynamics of the fuel complex variables were determined by canopy cover, estimated as a proxy for stand density. The use of a two-step regression approach enabled realistic modelling of the dynamics of the fuel complex variables, allowing for a decrease in the shrub fuel biomass and in CBD between two time points. The dynamic models developed are age-independent and are therefore useful for practical applications because they can be applied to any stand without the need to know the stand age. Overall, the study findings provide insights into the complex relationship between both understorey and overstorey fuels and stand density in commercial plantations. As assessment of forest fuel complex variables is a prerequisite for most fire management activities, the study findings have important implications for forest and fuel management and planning in the region.