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.