Luke Collins

Can precipitation influence landscape controls on wildfire severity? A case study within temperate eucalypt forests of south-eastern Australia

The environmental, economic and social impacts of wildfires depend on spatial patterns of fire severity. An understanding as to how drivers of fire severity vary across broad vegetation communities exists. However, examination of variation within communities in response to gradients of moisture has received little attention so far. This study examined whether relationships between environmental variables (i.e. fire weather, topography and fuel age) and fire severity were modified by increasing mean annual precipitation. Understorey fires were more likely to occur in young fuels (i.e. <5 years since fire) in drier sites, although this effect diminished as precipitation increased. The probability of occurrence of understorey fires under non-extreme weather and on steep slopes was reduced in wetter areas. Relationships between crown fire and weather, topography and fuel age were largely unaltered by the precipitation gradient, with only a marginally significant interaction occurring between weather and mean annual precipitation. Greater fine fuel accumulation associated with increased precipitation presumably reduced fuel limitations imposed by environmental factors (i.e. fire weather, slope, fuel age), altering their relative control on the probability of understorey fire. The probability of crown fires is predominantly driven by fire weather and is consequently less sensitive to precipitation gradients. Consideration of precipitation gradients will be necessary when identifying controls of fire severity and devising effective fire management strategies.

Adding fuel to the fire? Revegetation influences wildfire size and intensity

The regrowth of woody vegetation in cleared landscapes (i.e. revegetation) has the potential to dramatically alter the spatial characteristics of vegetation and fuels, which will potentially alter fire characteristics. Understanding how revegetation alters fire size and intensity will be critical in determining the social and environmental value of revegetation. We used simulation modelling to examine (i) whether increasing native woody vegetation extent across landscapes cleared for pasture (i.e. revegetation) affects fire size and median fireline intensity and (ii) whether fuel load in the pasture matrix, the initial extent of land clearing and weather conditions during a fire alter the direction and/or magnitude of the relationships between revegetation and fire size or intensity. Simulations revealed that fire size and intensity were altered by increasing woody vegetation extent, though the direction of change was dependent upon landscape context. Increased woody vegetation extent led to (i) increased fire size in landscapes with low pasture fuel load (2 t ha(-1)) regardless of the extent of land clearing, (ii) decreased fire size in highly cleared landscapes with moderate (4.5 t ha(-1)) and high (7 t ha(-1)) pasture fuel load, and (iii) little change to fire size in landscapes subjected to low levels of clearing when pasture fuel load was moderate or high. Similar patterns were observed for fireline intensity. The magnitude of change in fire size and intensity was greatest under extreme fire weather conditions. Revegetation rarely increased median fireline intensity beyond suppressible levels (i.e. 4000 kW m(-1)), with fire weather and pasture fuel load being the main determinants of suppression potential. Our findings show that the response of fire size and intensity to revegetation will depend on landscape scale pasture management.

Influence of fuels, weather and the built environment on the exposure of property to wildfire

Wildfires can pose a significant risk to people and property. Billions of dollars are spent investing in fire management actions in an attempt to reduce the risk of loss. One of the key areas where money is spent is through fuel treatment – either fuel reduction (prescribed fire) or fuel removal (fuel breaks). Individual treatments can influence fire size and the maximum distance travelled from the ignition and presumably risk, but few studies have examined the landscape level effectiveness of these treatments. Here we use a Bayesian Network model to examine the relative influence of the built and natural environment, weather, fuel and fuel treatments in determining the risk posed from wildfire to the wildland-urban interface. Fire size and distance travelled was influenced most strongly by weather, with exposure to fires most sensitive to changes in the built environment and fire parameters. Natural environment variables and fuel load all had minor influences on fire size, distance travelled and exposure of assets. These results suggest that management of fuels provided minimal reductions in risk to assets and adequate planning of the changes in the built environment to cope with the expansion of human populations is going to be vital for managing risk from fire under future climates.

Reducing the risk of house loss due to wildfires

Wildfires will continue to reach people and property regardless of management effort in the landscape. House-based strategies are therefore required to complement the landscape strategies in order to reduce the extent of house loss. Here we use a Bayesian Network approach to quantify the relative influence of preventative and suppressive management strategies on the probability of house loss in Australia. Community education had a limited effect on the extent to which residents prepared their property hence a limited effect on the reduction in risk of house loss, however hypothetically improving property preparedness did reduce the risk of house loss. Increasing expenditure on suppression resources resulted in a greater reduction in the risk of loss than preparedness. This increase had an interaction effect with increasing the distance between vegetation and the houses. The extent to which any one action can be implemented is limited by social, environmental and economic factors. Bayesian Network models provide a powerful tool for analysing fire risk scenarios.Combining multiple data sources allow for the exploration of a range of scenarios that cannot be empirically tested.Fire risk reduction strategies can reduce risk, but other factors limit their implementation.Approaches used here are broadly applicable to other natural hazards.

Using MODIS data to analyse post-fire vegetation recovery in Australian eucalypt forests

Remote sensing observations provide useful spatially explicit and temporally dense information for monitoring post-fire vegetation recovery patterns over large areas. Although large fires are common in Australian eucalypt forests, research on remote sensing of post-fire vegetation recovery in this ecosystem has been limited. In this study, time series (2000–2012) of Normalised Difference Vegetation Index, Enhanced Vegetation Index and Normalised Differenced Infrared Index derived from Moderate Resolution Imaging Spectroradiometer (MODIS) were used to analyse post-fire vegetation recovery in eucalypt forests in Australia. The analysis focused on 11 sites which burned during 2001/02 and 2002/03 fire seasons. Results indicated that spectral recovery in Australian eucalypt forests is particularly rapid after fire as spectral indices values returned to pre-fire levels three to six years after fire. Spectral recovery was particularly rapid during the first year following fire and the influence of severity was limited to the first two years after fire.