Climatic and edaphic gradients predict variation in wildland fuel hazard in south‐eastern Australia

Abstract

Understanding spatial variation in wildland fuel is central to predicting wildfire behaviour as well as current and future fire regimes. Vegetation (plant material) – both live (biomass) and dead (necromass) – constitutes most aspects of wildland fuel (hereafter ‘fuel’). It therefore is likely that factors influencing vegetation structure and composition – climate, soils, disturbance – also will influence fuel structure and associated hazard. Nonetheless, these relationships are poorly understood in temperate environments. In this study, we used an extensive database of fuel hazard assessments to determine the extent to which environmental variables (climatic conditions and soil type) and disturbance (fire) can predict fuel hazard in native vegetation across south‐eastern Australia. Fuel hazard ratings are based on the horizontal and vertical continuity of fine fuels (dead plant material < 6 mm thick, and live plant material < 3 mm thick) that burn in the flaming front of a fire. These scores are used widely by fire managers in Australia. We used environmental and disturbance variables to develop models to predict spatial patterns of hazard for each fuel stratum (surface, near‐surface, elevated and bark) and the height of two fuel strata (near‐surface, elevated). Soil, climate and time since fire were strong predictors of fuel hazard for at least one stratum, and soil predictors were the strongest predictors of fuel hazard across all strata. We used models to predict fuel hazard by stratum at a fixed time since fire in two regions with contrasting environments in south‐eastern Australia to better understand the spatial arrangement of fuel hazard. Fuel hazard varied within and between regions, emphasising the complexity and heterogeneity of fuel patterns that affect fuel hazard from local to landscape extents. The models improve the basis for analysing fuel hazard patterns and therefore increase the capacity to predict fire regimes under future climates.

Linking fire behaviour and its ecological effects to plant traits, using FRaME in R

“…Effects on seeds are not species-specific and interactions with time and moisture content are not included (Tangney et al, 2018) been to reinforce the traditional approach of prescribed burning at the expense of new evidence (Morgan et al, 2020;Russellsmith et al, 2020). Long-unburnt forests commonly have less shrub cover (termed 'fuel hazard' in the fire industry; McColl-Gausden et al, 2019;Wilson et al, 2018), but it has been argued that low intensity prescribed fire will provide insufficient soil heating to stimulate the germination of leguminous shrubs such as Daviesia latifolia (Knox & Clarke, 2006;Santana et al, 2010).…”

“…Mitigating this is a core challenge due to dynamic increases in the scale of burned area in temperate Australian forest (Boer et al., 2020), yet a dominant response has been to reinforce the traditional approach of prescribed burning at the expense of new evidence (Morgan et al., 2020; Russell‐smith et al., 2020). Long‐unburnt forests commonly have less shrub cover (termed ‘fuel hazard’ in the fire industry; McColl‐Gausden et al., 2019; Wilson et al., 2018), but it has been argued that low intensity prescribed fire will provide insufficient soil heating to stimulate the germination of leguminous shrubs such as Daviesia latifolia (Knox & Clarke, 2006; Santana et al., 2010). Others propose that flammability is only increased if the gap between ground fuels and canopy is reduced when the canopy is killed and forced to regrow from the ground (Wilson et al., 2021).…”

Modelling Bushfire Fuel Hazard Using Biophysical Parameters

“…Soil type was also included as a random effect in all the selected models. McColl-Gausden, Bennett [13] showed that soil variables explained the greatest variation in fuel hazard in almost all fuel hazard strata examined in Victorian forests, with soil bulk density as one of the strongest predictors. Soil fertility is known to influence the distribution of species [60,61] and interactions between moisture availability and soil texture/depth are also likely to play an important role [62].…”

“…The relationship between fuel hazard and time since last fire followed a similar form to that traditionally used to predict the accumulation of litter and fuel over time [30,42]. A study by McColl-Gausden, Bennett [13] in Victoria, Australia found that relationships with time since fire varied with strata, surface and bark strata showing a similar plateau, whilst, in contrast to our study, near-surface and elevated fuel hazard increased to~10-20 years of time since fire then gradually decreased until 100 years since fire. The advantage of using generalised additive models is that the form of the relationship between each predictor variable and the fuel hazard measure being modelled is data-driven rather than based on a priori assumptions of functional form, therefore allowing for examination of these complex relationships.…”

“…Modelling of fuels based on biophysical gradients provides an opportunity to gain insight into the climatic or landscape variables responsible for fuel characteristics and distribution [10]. Several studies have found that landscape fuel dynamics can be predicted using biophysical gradients [11][12][13] and that predictive landscape models were improved by the inclusion of gradient variables such as remotely sensed productivity indices and precipitation [10]. The ability to develop biophysical models at a landscape scale will improve our understanding of the spatial distribution of fuels.…”