Search

The role of live vegetation fuel properties in altering fire behaviour is increasingly being recognised. The techniques utilised to assess how fuel characteristics impact fire behaviour, however, use apparatuses that do not accurately represent the exposure of plants to fire. This study presents a replicable and precise laboratory method of testing flammability metrics in live vegetation, particularly Acacia floribunda, Cassinia arcuata and Pinus radiata. Two heating regimes were tested – a static heat flux to reflect current methods and a dynamic (increasing) heat flux to more accurately replicate an approaching fire front. Piloted ignition and autoignition were used for both heating regimes to test the effect of different ignition mechanisms on flammability metrics. The pilot igniter increased the number of samples that reached flaming ignition, and decreased the time and energy required to reach all flammability metrics. Significant differences were observed between heating regimes, suggesting it is important to test flammability of live plants under a dynamic heating regime that most accurately replicates an approaching fire front. Adoption of this methodology is recommended to ensure more realistic and standardised data on flammability of individual plant species and plant communities. This will lead to better-informed and more accurate wildfire behaviour modelling.

Background Wildfire suppression is becoming more costly and dangerous as the scale and severity of impacts from fires increase under climate change. Aims We aim to identify the key environmental and management variables influencing containment probability for forest fires in Victoria and determine how these change over time. Methods We developed Random Forest models to identify variables driving fire containment within the first 24 h of response. We used a database of ~12 000 incident records collected across Victoria, Australia. Key results Response time, fire size at first attack, number of ground resources deployed (e.g. fire fighters), ignition cause, and environmental factors that influence fire spread (e.g. elevation, humidity, wind, and fuel hazard) were key drivers of suppression success within the first 24 h. However, certainty about the factors influencing suppression reduced as the containment period increased. Conclusions Suppression success hinges on a balance between the environmental factors that drive fire spread and the rapid deployment of sufficient resources to limit fire perimeter growth. Implications Decreasing the period between an ignition and the time of arrival at the fire will allow first responders to begin suppression before the fire size has exceeded their capability to construct a control line.

Background When fire intervals are shorter than the time required for plants to reproduce, plant populations are threatened by “immaturity risk.” Therefore, understanding how the time between fires influences plants can inform ecosystem management. Quantifying periods of immaturity risk requires investigating the influence of fire intervals across plant life stages, but most studies are indiscriminate of maturity. As fire regimes are multidimensional, it is also important to consider other characteristics of fires such as severity. We conducted a field study in heathy woodland that investigated how fire severity and fire interval influence immaturity risk to serotinous resprouter species, by examining if fire severity interacts with the time since the fire to influence the occurrence of mature individuals and relative abundance of three species: silver banksia (Banksia marginata Cav.), prickly teatree (Leptospermum continentale Joy Thomps), and heath teatree (Leptospermum myrsinoides Schitdl). Results Regression modeling revealed a strong, positive influence of time since the last fire on the proportion of quadrats at a site with mature plants, for all three species. We only detected a small and uncertain influence of fire severity on the proportion of quadrats with mature heath and prickly teatree, and did not observe an effect of fire severity on the maturity of silver banksia. Interestingly, no relationships were observed between time since fire and the relative abundance of plants. That is, only when plant life stages were considered did we detect an effect of fire on plants. Populations of the three species were mostly immature in the first 7 years post-fire, suggesting if sites were uniformly burnt in this time frame, there could be increased risk of local extinctions. Conclusions Our study highlights the importance of examining population processes, such as reproduction, in addition to plant relative abundance. Surprisingly, we did not detect strong differences in plant maturation across fire severity classes; low occurrence of mature plants in recently burnt areas indicated that immaturity risk was high, regardless of fire severity. Ecological studies that distinguish between plant life stages will help to predict the impacts of fire on populations and enhance decision-making. We recommend fire intervals of ≥ 8 years to protect serotinous resprouter plants in heathy woodland vegetation of southern Australia.

Forest fire severity influences post-fire fuel structure and thus the behaviour of subsequent fires. Understanding such interactions is critical to improving predictions of fire risk and emergency management, yet few studies have quantified fire severity effects on fuel attributes. We quantify fuel structure of a fire-tolerant eucalypt forest 7 years after a landscape-scale wildfire in south-eastern Australia. We used high-density airborne lidar data to estimate understorey fuel metrics in three strata representing horizontal and vertical connectivity in 1084 plots (0.06 ha) representing four wildfire severities (unburnt, low, moderate, high). Fuel structure was changed by high-severity fire, which significantly increased the cover and horizontal connectivity of the elevated and midstorey strata and decreased space between the understorey and canopy relative to other severity types. Random Forest models indicated that understorey fuel metrics were most influenced by wildfire severity, pre-fire values of each metric, and post-fire canopy cover, and least influenced by climatic and topographic variables. Our study provides evidence of positive feedbacks to flammability by high-severity wildfire in fire-tolerant eucalypt forests through increased horizontal and vertical fuel connectivity. It demonstrates the utility of airborne lidar data for quantifying fuel structure in complex forests and providing critical data for fire risk assessments.

Knowing the abundance of different plant species provides insights into the properties of vegetation communities, such as flammability. Therefore, a fundamental goal in ecology is identifying environmental conditions affecting the abundance of plant species across landscapes. Water and light are important environmental moderators of plant growth, and by extension, abundance. In the context of understanding forest flammability, the abundance of a flammable plant species in terms of its cover or biomass can shape the flammability of the whole vegetation community. We conducted a glasshouse experiment to determine the impact of drought and shade on growth, biomass allocation and leaf morphology of forest wiregrass Tetrarrhena juncea R.Br., a rhizomatous perennial grass. When it is abundant, this species is known to contribute substantially to the flammability of eucalypt forest understories (via both ignitability and combustibility). Contrasting hypotheses in the literature predict that drought can have a weaker, stronger, or independent (uncoupled) impact on plant growth when light is limiting. We used a randomized complete block design with ten treatments from the combination of two water levels (drought, well-watered) and five light levels (100%, 80%, 60%, 40%, 20%). Drought and shade were found to have independent effects on wiregrass growth, biomass allocation, and leaf morphology, supporting the uncoupled hypothesis. Growth showed greater plasticity in response to drought, while biomass allocation and leaf morphology showed greater plasticity in response to shade. Our results suggest that wiregrass is more likely to be abundant in terms of its cover and biomass when water is not limiting. Under these conditions, the increased wiregrass abundance could create a window of increased flammability for the forest ecosystem.

Mechanical mastication is growing in popularity as a wildfire mitigation technique. Yet few studies quantify its effects on fire behaviour. Such information is needed by fire managers to evaluate its efficacy. Our aim was to develop an understanding of how mastication alters flaming and smouldering durations and the longevity of any effects. Flaming and smouldering duration are important determinants of soil heating and smoke emissions. We used a paired sampling design, collecting litter bed (hereafter surface fuel) samples from 15 sites with masticated and untreated vegetation in shrub-encroached Eucalyptus woodlands. We measured a range of fuel bed properties and then burnt the samples in the laboratory. Average smouldering durations increased 88% from 25 to 47 min in untreated v. masticated fuel; flaming durations increased 100% from 6 to 12 min. These changes were attributable to higher fine and coarse fuel loads in the masticated fuel bed. However, fine and coarse fuel load declined significantly over 4 years, meaning the effects of mastication on combustion duration are likely to be short-lived. Despite being a laboratory study, the results assist with evaluating mastication as a fuel treatment by demonstrating the potential magnitude of changes to flaming and smouldering duration.

Species distribution models are an essential tool for biodiversity conservation, with important applications such as spatial prioritisation of conservation actions and elucidating relationships between environmental predictors and species responses. These models are most useful to conservation managers when they include factors that can be readily manipulated, such as fire. In this study, we collated a comprehensive dataset of mammal records from a fire-prone region in south-east Australia where mammals have suffered declines in recent decades. We used species distribution modelling to (1) determine the relative influence of climate, fire, vegetation and topography on ground-dwelling mammal distributions; (2) determine species responses to time since fire, and; (3) provide spatial predictions of habitat suitability for conservation planning. Climate was the predominant driver of habitat suitability for most species, although other factors were influential in some cases. Time since fire was an important factor driving the distribution of only two of 16 modelled species which were more likely to be recorded in recently burnt vegetation. Habitat suitability varied spatially among species however multi-species habitat suitability was highest in the drier and hotter eastern section of the landscape, highlighting a key area for conservation efforts. The outputs from our models can be used for practical conservation actions such as finding new populations or identifying sites for reintroductions. We conclude that presence-only species distribution models are useful for determining species fire responses, complementing more systematic methods, and that including dynamic variables, such as time since fire, can increase their conservation relevance.

Understanding the relationships between spatial pattern, spatial scale and biodiversity can help ecologists to assess the impacts of environmental change and inform management plans. Spatial pattern research has often focussed on the effect of modified landscapes on species diversity. However, few studies have examined species responses to spatial pattern from other sources, including those which vary over time, such as fire. We investigated the effect of composition and configuration for topographic, ecological and disturbance factors on mammal species richness. In addition, we examined whether the magnitude and predictive strength of the relationship with richness varied with spatial scale. We sampled ground-dwelling mammals at 187 sites in the Otway Ranges of south-eastern Australia. A gradient modelling approach was used to characterise landscape composition and configuration for each predictor. Relationships with mammal richness were modelled using Bayesian Networks at ten different spatial scales (7–1165 ha). Composition and configuration were both important to species richness, although the strength and presence of relationships varied across the ten scales. Patterns in NDVI, time since fire, habitat complexity and elevation had the strongest effects on mammal species richness. Our findings highlight the importance of measuring both the composition and configuration of environmental measures at different spatial scales to assess their effect on species richness. Further, studies focusing on just one environmental measure of spatial pattern or one spatial scale will miss important relationships between environmental variables and species richness.

Fallen plant material such as leaves, needles and branches form litter beds which strongly influence fire ignition and spread. Traits of the dominant species influence litter flammability directly by determining how individual leaves burn and indirectly through the structure of the litter bed. However, we are yet to determine the relative importance of these different drivers across a range of plant species from different biomes. We undertook a meta-analysis, combining leaf trait, litter structure and flammability data for 106 species from North America, South America, Europe, Asia and Australia. The dataset encompassed broad-leaved and coniferous species from seven different experimental studies. Relationships between leaf traits, litter structure and key flammability metrics—sustainability, combustibility and consumability—were analysed using bivariate and piecewise structural equation modelling (SEM). Traits which characterise the three-dimensional nature of the leaf and how much space a leaf occupies showed much stronger associations to litter structure and flammability than other morphological traits. Leaf curl, surface area to volume ratio (SAV) and SLA predominately influence litter flammability indirectly via litter structure with SLA being the only leaf trait which had a negative direct effect on flame duration. Packing ratio and bulk density were influenced by different combinations of leaf traits and, in turn, they aligned with different flammability metrics. Bulk density predicted flame spread rate and flame duration whereas packing ratio predicted consumption. Synthesis. We identified key leaf and litter traits which influence different components of litter bed flammability. Importantly, we show that the effects of these leaf and litter traits are consistent across a wide range of taxa and biomes. Our study represents a significant step towards developing trait-based models for predicting surface wildfire behaviour. Such models will more flexibly accommodate future shifts in the composition of plant species triggered by altered fire regimes and climate change.

Above-ground biomass in forests is critical to the global carbon cycle as it stores and sequesters carbon from the atmosphere. Climate change will disrupt the carbon cycle hence understanding how climate and other abiotic variables determine forest biomass at broad spatial scales is important for validating and constraining Earth System models and predicting the impacts of climate change on forest carbon stores. We examined the importance of climate and soil variables to explaining above-ground biomass distribution across the Australian continent using publicly available biomass data from 3130 mature forest sites, in 6 broad ecoregions, encompassing tropical, subtropical and temperate biomes. We used the Random Forest algorithm to test the explanatory power of 14 abiotic variables (8 climate, 6 soil) and to identify the best-performing models based on climate-only, soil-only and climate plus soil. The best performing models explained ~50% of the variation (climate-only: R2 = 0.47 ± 0.04, and climate plus soils: R2 = 0.49 ± 0.04). Mean temperature of the driest quarter was the most important climate variable, and bulk density was the most important soil variable. Climate variables were consistently more important than soil variables in combined models, and model predictive performance was not substantively improved by the inclusion of soil variables. This result was also achieved when the analysis was repeated at the ecoregion scale. Predicted forest above-ground biomass ranged from 18 to 1066 Mg ha−1, often under-predicting measured above-ground biomass, which ranged from 7 to 1500 Mg ha−1. This suggested that other non-climate, non-edaphic variables impose a substantial influence on forest above-ground biomass, particularly in the high biomass range. We conclude that climate is a strong predictor of above-ground biomass at broad spatial scales and across large environmental gradients, yet to predict forest above-ground biomass distribution under future climates, other non-climatic factors must also be identified.

Fire behaviour research has largely focused on dry ecosystems that burn frequently, with far less attention on wetter forests. Yet, the impacts of fire in wet forests can be high and therefore understanding the drivers of fire in these systems is vital. We sought to identify and rank by importance the factors plausibly driving flammability in wet eucalypt forests, and describe relationships between them. In doing so, we formulated a set of research priorities. Conceptual models of forest flammability in wet eucalypt forests were elicited from 21 fire experts using a combination of elicitation techniques. Forest flammability was defined using fire occurrence and fireline intensity as measures of ignitability and heat release rate, respectively. There were shared and divergent opinions about the drivers of flammability in wet eucalypt forests. Widely agreed factors were drought, dead fine fuel moisture content, weather and topography. These factors all influence the availability of biomass to burn, albeit their effects and interactions on various dimensions of flammability are poorly understood. Differences between the models related to lesser understood factors (e.g. live and coarse fuel moisture, plant traits, heatwaves) and the links between factors. By documenting alternative conceptual models, we made shared and divergent opinions explicit about flammability in wet forests. We identified four priority research areas: (1) quantifying drought and fuel moisture thresholds for fire occurrence and intensity, (2) modelling microclimate in dense vegetation and rugged terrain, (3) determining the attributes of live vegetation that influence forest flammability, (4) evaluating fire management strategies.

Wildfires pose a significant risk to people and property, which is expected to grow with urban expansion into fire-prone landscapes and climate change causing increases in fire extent, severity and frequency. Identifying spatial patterns associated with wildfire activity is important for assessing the potential impacts of wildfires on human life, property and other values. Here, we model the probability of fire ignitions in vegetation across Victoria, Australia, to determine the key drivers of human- and lightning-caused wildfire ignitions. In particular, we extend previous research to consider the role that fuel moisture has in predicting ignition probability while accounting for environmental and local conditions previously identified as important. We used Random Forests to test the effect of variables measuring infrastructure, topography, climate, fuel and soil moisture, fire history, and local weather conditions to investigate what factors drove ignition probability for human- and lightning-caused ignitions. Human-caused ignitions were predominantly influenced by measures of infrastructure and local weather. Lightning-sourced ignitions were driven by fuel moisture, average annual rainfall and local weather. Both human- and lightning-caused ignitions were influenced by dead fuel moisture with ignitions more likely to occur when dead fuel moisture dropped below 20 %. In future, these models of ignition probability may be used to produce spatial likelihood maps, which will improve our models of future wildfire risk and enable land managers to better allocate resources to areas of increased fire risk during the fire season.

The rarely encountered giant burrowing frog, Heleioporus australiacus, is distributed widely in a variety of sclerophyll forest habitats east of the Great Dividing Range in south-eastern Australia. Analyses of variation in nucleotide sequences of the mitochondrial ND4 gene and thousands of nuclear gene SNPs revealed the presence of two deeply divergent lineages. Multivariate morphological comparisons show the two lineages differ in body proportions with > 91% of individuals being correctly classified in DFA. The two lineages differ in the number and size of spots on the lateral surfaces and the degree by which the cloaca is surrounded by colour patches. The mating calls are significantly different in number of pulses in the note. The presence of a F2 hybrid in the area where the distribution of the two taxa come into closest proximity leads us to assign subspecies status to the lineages, as we have not been able to assess the extent of potential genetic introgression. In our sampling, the F2 hybrid sample sits within an otherwise unsampled gap of ~90km between the distributions of the two lineages. The nominate northern sub-species is restricted to the Sydney Basin bioregion, while the newly recognised southern subspecies occurs from south of the Kangaroo Valley in the mid-southern coast of New South Wales to near Walhalla in central Gippsland in Victoria. The habitat of the two subspecies is remarkably similar. Adults spend large portions of their lives on the forest floor where they forage and burrow in a variety of vegetation communities. The southern subspecies occurs most commonly in dry sclerophyll forests with an open understory in the south and in open forest and heath communities with a dense understory in the north of its distribution. The northern subspecies is also found in dry open forests and heaths in association with eroded sandstone landscapes in the Sydney Basin bioregion. Males of both taxa call from both constructed burrows and open positions on small streams, differing from the five Western Australian species of Heleioporus where males call only from constructed burrows. Using the IUCN Red List process, we found that the extent of occupancy and area of occupancy along with evidence of decline for both subspecies are consistent with the criteria for Endangered (A2(c)B2(a)(b)).

© 2019 The Authors. Ecography published by John Wiley & Sons Ltd on behalf of Nordic Society Oikos 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.

Life cycle assessment (LCA) is a useful method for assessing environmental impacts at large scales. Biodiversity and ecosystem diversity are site-specific, often complex, and difficult to generalise within an LCA framework. There is currently no globally acceptable means of assessing biodiversity within the LCA framework. We introduce, test and revise BioImpact, a method for incorporating biodiversity into an LCA framework, on four production systems (native forestry, plantation softwood timber production, cropping and rangeland grazing) in Australia. Our proposed method, a metric we call BioImpact, incorporates biodiversity and ecological impacts through a series of semi-quantitative questions, published data and expert opinion which aim to encapsulate the main issues relating to biodiversity within a disturbance impact framework appropriate to LCA. Results are scaled to a single biodiversity measure that can be incorporated into LCA. We test and revise BioImpact scores on four production systems (native forestry, plantation softwood timber production, cropping and rangeland grazing) in comparison to species richness and net primary productivity (NPP) for these production systems. We demonstrate how the scores can be incorporated into LCA using SimaPro as a platform. For pine plantation, cropping/pastures and rangeland grazing, BioImpact demonstrated greater impact, which represents biodiversity loss for multiple species groups. Native forestry scored significantly lower impact than that of other land uses. As a comparison, all production processes scored highly for species richness of main multiple species groups (vascular plants, invertebrates, birds) and were not different in terms of NPP. Integration of BioImpact into LCA found that the softwood system, despite having a higher biodiversity impact per ha year, had a marginally lower BioImpact score per cubic metre compared to native forestry. This was possibly due to cumulative effects and consideration of the reference benchmark, e.g., low levels of pre-harvest biodiversity when not established on native forests; fewer threatened species (and lesser impact) compared to native forestry; questions not weighted sufficiently; and the difference between establishment on either agricultural cleared land or native forest area. Improvement in scaling and/or weighting within the BioImpact scores within each question is discussed. BioImpact encapsulates different components of biodiversity, is transparent, easily applied (subject to literature/ecological experts) and can be incorporated into LCA. Application of BioImpact for LCA requires co-ordination to identify key regions and production systems; develop the relevant scores with the assistance of ecologists; and make the results available in public LCA databases.

Prescribed burning is a widely used strategy in forested landscapes to reduce the risk from wildfires to human lives and valued assets. The ability for managers to undertake prescribed burns is contingent on fuel, weather and operational constraints. In practice, not all areas nominated to be burnt get completed, and within burns that occur, not all the area is burnt. There has been limited research into rates of successful implementation of prescribed burns for fuel management and the degree to which the outcomes of prescribed burning are predictable. To better understand this, we undertook a quantitative analysis of prescribed burn outcomes in the State of Victoria, Australia between July 2009 and July 2015, investigating the likelihood of burns being completed and the time between nomination and completion. For those completed, we used Generalized Additive Models to investigate patterns of burn coverage, both for individual points within burns and aggregated to the burn level. We found a large proportion (29.6%) of scheduled prescribed burns were never burnt, and the time between nomination and completion was highly variable. The size of the nominated burn area was found to influence both the likelihood of completion and the likelihood of burns being postponed. Of burns that were completed, the proportion of area burnt was highly variable (mean 74%, median 84%). Patterns of burnt area were predictable: our point level model could predict the likelihood of any point within a burn being burnt with 66% accuracy from fuel type, aridity and temperature seasonality. The model was more confident in predicting what would remain unburnt than what would burn. Our burn level model explained 55% of variation in the proportion burnt from area weighted fuel type, average aridity, temperature seasonality and the size of the nominated burn area. An ability to foresee the outcomes of prescribed burn programs is important for managers in designing effective risk reduction programs.

Wildfire extent and their impacts are increasing around the world. Fire management agencies use fire behaviour simulation models operationally (during a wildfire event) or strategically for risk assessment and treatment. These models provide agencies with increased knowledge of fire potential to improve identification of the best strategies for reducing risk. One of the greatest areas of uncertainty in fire simulations is the data relating to fuel, which are usually based on simplified response trajectories with time since fire within vegetation communities. There is a clear need to better predict relevant fuel variables across landscapes to reduce uncertainties in fire simulations. In this study, we compare the performance of fuel hazard models based on environmental variables (environmental model) with those currently implemented based on a negative exponential relationship with time since fire (NEGEXP) using the state of Victoria in south-eastern Australia as an environmentally diverse case study. The models predicted similar broadscale patterns in fuel hazard but with considerable regional variation. The NEGEXP model was less accurate than the environmental model, which had 41–47% accuracy on an independent data set cf. 24–35% for NEGEXP. Model differences resulted in significant differences in the extent and spatial location of predicted fires with NEGEXP consistently predicting larger fires. Fuel is made up of the live and dead components of vegetation, both of which are influenced by a range of environmental factors. As our study highlights, ignoring environmental factors in simple fuel models based on broad vegetation types (like NEGEXP) will likely compromise the predictive accuracy of fire behaviour models. Only when environmental factors are accounted for can we more accurately predict fuels across landscapes and thereby improve the accuracy of fire behaviour predictions and the estimation of fire risks.

Climate modes can have a large influence on the interannual variability in rainfall and streamflow. Moreover, changes in their spatial-temporal patterns are likely to shape changes in hydroclimate in the future as a result of a warming climate. Modeling the links between climate modes, rainfall and streamflow is therefore important for understanding the trajectories in water availability. We examined the effects of four climate variability modes, El Nino Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), Southern Annular Mode (SAM), and Interdecadal Pacific Oscillation (IPO) on variations in annual rainfall and streamflow in four hydroclimate regions in temperate Australian. Climate mode indices, rainfall, and streamflow data from 1975 to 2018 were analyzed for 92 predominately forested catchments in four study regions. The annual variation and long-term fluctuations of rainfall and streamflow in each region were explored using the coefficient of variation, trend analysis, and random forest models to examine relationships to ENSO, IOD, SAM, and IPO. Coefficient of variation analysis showed that the annual variation of streamflow in and among catchments in each region was higher than rainfall. Rainfall and streamflow in each region were strongly influenced by different climate modes, and a higher proportion of variation in rainfall was explained by climate modes. Extreme annual rainfall and streamflow in these regions are related to concurrent phases of regional climate phenomena. These results provide critical baseline information and context for a better understanding of how future spatial and temporal changes in rainfall and streamflow across temperate Australia may manifest.

Research highlights—Feedbacks between fire severity, vegetation structure and ecosystem flammability are understudied in highly fire-tolerant forests that are dominated by epicormic resprouters. We examined the relationships between the severity of two overlapping fires in a resprouting eucalypt forest and the subsequent effect of fire severity on fuel structure. We found that the likelihood of a canopy fire was the highest in areas that had previously been exposed to a high level of canopy scorch or consumption. Fuel structure was sensitive to the time since the previous canopy fire, but not the number of canopy fires. Background and Objectives—Feedbacks between fire and vegetation may constrain or amplify the effect of climate change on future wildfire behaviour. Such feedbacks have been poorly studied in forests dominated by highly fire-tolerant epicormic resprouters. Here, we conducted a case study based on two overlapping fires within a eucalypt forest that was dominated by epicormic resprouters to examine (1) whether past wildfire severity affects future wildfire severity, and (2) how combinations of understorey fire and canopy fire within reburnt areas affect fuel properties. Materials and Methods—The study focused on ≈77,000 ha of forest in south-eastern Australia that was burnt by a wildfire in 2007 and reburnt in 2013. The study system was dominated by eucalyptus trees that can resprout epicormically following fires that substantially scorch or consume foliage in the canopy layer. We used satellite-derived mapping to assess whether the severity of the 2013 fire was affected by the severity of the 2007 fire. Five levels of fire severity were considered (lowest to highest): unburnt, low canopy scorch, moderate canopy scorch, high canopy scorch and canopy consumption. Field surveys were then used to assess whether combinations of understorey fire (&lt, 80% canopy scorch) and canopy fire (&gt, 90% canopy consumption) recorded over the 2007 and 2013 fires caused differences in fuel structure. Results—Reburn severity was influenced by antecedent fire severity under severe fire weather, with the likelihood of canopy-consuming fire increasing with increasing antecedent fire severity up to those classes causing a high degree of canopy disturbance (i.e., high canopy scorch or canopy consumption). The increased occurrence of canopy-consuming fire largely came at the expense of the moderate and high canopy scorch classes, suggesting that there was a shift from crown scorch to crown consumption. Antecedent fire severity had little effect on the severity patterns of the 2013 fire under nonsevere fire weather. Areas affected by canopy fire in 2007 and/or 2013 had greater vertical connectivity of fuels than sites that were reburnt by understorey fires, though we found no evidence that repeated canopy fires were having compounding effects on fuel structure. Conclusions—Our case study suggests that exposure to canopy-defoliating fires has the potential to increase the severity of subsequent fires in resprouting eucalypt forests in the short term. We propose that the increased vertical connectivity of fuels caused by resprouting and seedling recruitment were responsible for the elevated fire severity. The effect of antecedent fire severity on reburn severity will likely be constrained by a range of factors, such as fire weather.

Variations in global patterns of burning and fire regimes are relatively well measured, however, the degree of influence of the complex suite of biophysical and human drivers of fire remains controversial and incompletely understood. Such an understanding is required in order to support current fire management and to predict the future trajectory of global fire patterns in response to changes in these determinants. In this study we explore and compare the effects of four fundamental controls on fire, namely the production of biomass, its drying, the influence of weather on the spread of fire and sources of ignition. Our study area is southern Australia, where fire is currently limited by either fuel production or fuel dryness. As in most fire-prone environments, the majority of annual burned area is due to a relatively small number of large fires. We train and test an Artificial Neural Network’s ability to predict spatial patterns in the probability of large fires (>1,250 ha) in forests and grasslands as a function of proxies of the four major controls on fire activity. Fuel load is represented by predicted forested biomass and remotely sensed grass biomass, drying is represented by fraction of the time monthly potential evapotranspiration exceeds precipitation, weather is represented by the frequency of severe fire weather conditions and ignitions are represented by the average annual density of reported ignitions. The response of fire to these drivers is often non-linear. Our results suggest that fuel management will have limited capacity to alter future fire occurrence unless it yields landscape-scale changes in fuel amount, and that shifts between, rather than within, vegetation community types may be more important. We also find that increased frequency of severe fire weather could increase the likelihood of large fires in forests but decrease it in grasslands. These results have the potential to support long-term strategic planning and risk assessment by fire management agencies.

QUESTIONS: Are factors influencing plant diversity in a fire‐prone Mediterranean ecosystem of southeast Australia scale‐dependent? LOCATION: Heathy woodland, Otways region, Victoria, southeast Australia METHODS: We measured patterns of above‐ground and soil seed bank vegetation diversity and associated them with climatic, biotic, edaphic, topographic, spatial and disturbance factors at multiple scales (macro to micro) using linear mixed effect and generalized dissimilarity modelling. RESULTS: At the macro‐scale, we found species richness above‐ground best described by climatic factors and in the soil seed bank by disturbance factors. At the micro‐scale we found species richness best described above‐ground and in the soil seed bank by disturbance factors, in particular time‐since‐last‐fire. We found variance in macro‐scale β‐diversity (species turnover) best explained above‐ground by climatic and disturbance factors and in the soil seed bank by climatic and biotic factors. CONCLUSIONS: Regional climatic gradients interact with edaphic factors and fire disturbance history at small spatial scales to influence species richness and turnover in the studied ecosystem. Current fire management regimes need to incorporate key climatic–disturbance–diversity interactions to maintain floristic diversity in the studied system.

Logging and fires represent the major disturbance regimes in Eucalyptus forests and these can have varying effects on populations of forest fauna depending on their intensity and/ or frequency. Knowledge of the effects of fires on arboreal marsupials is limited and to the best of our knowledge no previous research has considered the effect of fire frequency on populations of these species. The aim of this study was to examine the effects of fire frequency (canopy-consuming wildfires) and logging intensity on the Greater Glider, Petauroides volans, a species of hollow dependent gliding possum that has recently been listed as vulnerable to extinction under Australian biodiversity law. Surveys were completed across a selective logging intensity and fire frequency gradient in tall wet (WSF) and tall dry sclerophyll forests (DSF) in north-eastern New South Wales, Australia. Generally, P. volans was restricted to WSF, where even a single fire, 10 years prior, significantly reduced the density of P. volans in comparison to unburnt areas. Significant negative impacts from intensive logging were also detected. These effects may explain observed declines in the abundance of P. volans over much of its range as well as its scarcity in the more fire prone DSF. To counteract these effects, we recommend not implementing prescribed fire under high or greater fire weather danger conditions near high-density populations of this species, along with increased retention of hollow-bearing trees during timber harvesting and/ or wider riparian buffers in areas where high density populations of P. volans occur.

Fuel moisture is a key driver of forest flammability as it influences ignition likelihood, fire intensity and resultant fire severity. Changes to forest canopy cover following disturbances like wildfire or logging may alter forest flammability by changing the microclimatic conditions that influence fine fuel moisture. Wet forests dominated by Mountain Ash (Eucalyptus regnans) are highly valued for their flora and fauna, timber, carbon and water. Wildfires are an important part of the lifecycle of these forests, but too frequent fire can threaten post-fire regeneration. With large tracts of Mountain Ash forest recovering from recent wildfires (in 2009 and 1983) there is a need to understand the mechanisms driving flammability in these forests, particularly as the forest structure changes following fire. This study sought to understand the effects of fire history on the flammability of Mountain Ash forests by specifically considering fuel moisture for different times since fire and fire severities. We measured canopy cover (plant area index) and fuel moisture within 8 forest sites last burnt between 7 and 200 years ago by wildfires of low or high severity. Fuel moisture and fuel availability (i.e. number of days when fine fuels are dry enough to ignite and sustain spreading fire) were strongly associated with canopy cover; with denser canopied forests having higher fuel moisture. The largest differences in canopy cover occurred between the recently burnt high and low severity forests. For the longer-unburnt forests there were no systematic differences evident in canopy cover with time since fire or fire severity. The fuel moisture was higher and fuels only available to burn on one day in the forest recently burnt by high severity fire (in association with a dense canopy). In contrast, fuels were drier and available to burn on 238 days in the forest recently burnt by low severity fire (in association with a sparser canopy). For the longer-unburnt forests (33 or more years since fire) there were no clear trends between fuel moisture and time since fire and fire severity suggesting that fires do not have a lasting impact on fuel moisture within these wet forests. Overall, this study shows that wildfires have immediate impacts on fuel moisture in Mountain Ash forests but as the time since fire increases, moisture appears to be more a function of canopy properties than fire history.

Wildfires impact upon populations where development has occurred within or adjacent to natural vegetation. Even with extensive management interventions in the landscape, wildfires will continue to impact upon some properties. Residents in wildfire prone areas need to prepare themselves and their properties. Studies have found cost is one of the main reasons there is a generally low level of preparation by residents. In this study, we quantify the cost for residents to prepare themselves and retrofit their property for wildfire in an intermix and interface community. We combine this with semi-structured interviews to identify limitations to preparedness and willingness to contribute to a shared cost scheme with local government. Wide variation in the level of preparedness was found for the five case study homes in the intermix area and the five in the interface area with intermix houses being better prepared than those at the interface. All buildings were found not to comply with any building standards for wildfire resilience, despite most being considered to have the highest level of wildfire exposure. The total up-fronts cost to prepare residents and their homes ranged from approximately $8500 to $47,000 with an average of $24,600. Based on these figures, the financial investment required was significantly higher than residents felt they were able to cover. Ultimately, the choice to live in a wildfire-prone area will always involve the acceptance of some risk, regardless of the construction of the property and preparedness of the household.

Wildfires can result in significant social, environmental and economic losses. Fires in which dynamic fire behaviours (DFBs) occur contribute disproportionately to damage statistics. Little quantitative data on the frequency at which DFBs occur exists. To address this problem, we conducted a structured survey using staff from fire and land management agencies in Australia regarding their experiences with DFBs. Staff were asked which, if any, DFBs were observed within fires greater than 1000 ha from the period 2006&ndash, 2016 that they had experience with. They were also asked about the nature of evidence to support these observations. One hundred thirteen fires were identified. Eighty of them had between one and seven DFBs with 73% (58 fires) having multiple types of DFBs. Most DFBs could commonly be identified through direct data, suggesting an empirical analysis of these phenomena should be possible. Spotting, crown fires and pyro-convective events were the most common DFBs (66%), when combined with eruptive fires and conflagrations, these DFBs comprise 89% of all cases with DFBs. Further research should be focused on these DFBs due to their high frequencies and the fact that quantitative data are likely to be available.

Vegetation in urban areas provides many essential ecosystem services. These services may be indirect, such as carbon sequestration and biological diversity, or direct, including microclimate regulation and cultural values. As the global population is becoming ever more urbanized these services will be increasingly vital to the quality of life in urban areas. Due to the combined effects of shading and evapotranspiration, trees have the potential to cool urban microclimates and mitigate urban heat, reduce thermal discomfort and help to create comfortable outdoor spaces for people. Understory vegetation in the form of shrubs and grass layers are also increasingly recognized for the positive role they play in human aesthetics and supporting biodiversity. However, in fire-prone urban landscapes there are risks associated with having denser and more complex vegetation in public open spaces. We investigated the effects of plant selection and planting arrangement on fire risk and human thermal comfort using the Forest Flammability Model and Physiological Equivalent Temperature (PET), to identify how planting arrangement can help balance the trade-offs between these risks and benefits. Our research demonstrated the importance of vertical separation of height strata and suggests that Clumped and Continuous planting arrangements are the most effective way of keeping complex vegetation in public open space to deliver the greatest human thermal comfort benefit while minimizing potential fire behaviour. This study provides an example of how existing research tools in multiple ecological fields can be combined to inform positive outcomes for people and nature in urban landscapes.

Environmental decision-making requires an understanding of complex interacting systems across scales of space and time. A range of statistical methods, evaluation frameworks and modeling approaches have been applied for conducting structured environmental decision-making under uncertainty. Bayesian Decision Networks (BDNs) are a useful construct for addressing uncertainties in environmental decision-making. In this paper, we apply a BDN to decisions regarding fire management to evaluate the general efficacy and utility of the approach in resource and environmental decision-making. The study was undertaken in south-eastern Australia to examine decisions about prescribed burning rates and locations based on treatment and impact costs. Least-cost solutions were identified but are unlikely to be socially acceptable or practical within existing resources; however, the statistical approach allowed for the identification of alternative, more practical solutions. BDNs provided a transparent and effective method for a multi-criteria decision analysis of environmental management problems.

Preventing the loss of human lives and the destruction of houses is a focus of land management in fire prone environments. An understanding of the location and nature of risks to assets is important to plan mitigation activities. House destruction during wildfires has been found to be a function of landscape properties, including fuel proximity, topography and proximity to other houses. Additionally, conditions during wildfires are important, with houses likely to be destroyed when flames are intense. We propose an approach to predict destruction that considers both landscape attributes and fire conditions by using historic fires to train a destruction function. This was achieved by linking observations of house impacts in historic fires to fire behaviour reconstructed using a fire behaviour simulator. These observations were used to create an empirically fitted destruction function particular to the simulator used. We collated data for 17 wildfires that occurred in Victoria, Australia. These were replicated within the simulator PHOENIX RapidFire. The landscape data and simulator outputs were superimposed over house destruction/survival information and these were used to predict destruction likelihood. The best model explained 55% of the variation in house impacts, with fire and landscape predictors contributing to 50% of explained variation. It had an accuracy of 90.4%, in comparison to 46.4% of an alternative model that used simulated fire data alone. Incorporating empirically fitted asset impact functions in fire simulation systems can provide for improved projections of likely risk, supporting land managers to make evidence-based decisions that optimise the allocation of resources. Summary A key focus of wildfire management is the reduction of risk to life and property. We present an approach whereby observations of over 15,000 houses exposed to wildfires were used to develop models of the likelihood of destruction using a combination of simulated fire behaviour and landscape attributes. House destruction was found to be a function of both, with each contributing to around 50% of the model’s performance, which accounted for 55% of observed variation. This approach can provide an indication of the possible processes that result in asset destruction and can be incorporated into fire simulation systems to better estimate potential impacts.

Shrub encroachment of grassland and woodland ecosystems can alter wildfire behaviour and threaten ecological values. Australian fire managers are using mechanical mastication to reduce the fire risk in encroached ecosystems but are yet to evaluate its effectiveness or ecological impact. We asked: (1) How does fuel load and structure change following mastication?, (2) Is mastication likely to affect wildfire rates of spread and flame heights?, and (3) What is the impact of mastication on flora species richness and diversity? At thirteen paired sites (masticated versus control, n = 26), located in Victoria, Australia, we measured fuel properties (structure, load and hazard) and floristic diversity (richness and Shannon’s H) in 400 mP2 plots. To quantify the effects of mastication, data were analysed using parametric and non-parametric paired sample techniques. Masticated sites were grouped into two categories, 0–2 and 3–4 years post treatment. Fire behaviour was predicted using the Dry Eucalypt Forest Fire Model. Mastication with follow-up herbicide reduced the density of taller shrubs, greater than 50 cm in height, for at least 4 years. The most recently masticated sites (0–2 years) had an almost 3-fold increase in dead fine fuel loads and an 11-fold increase in dead coarse fuel loads on the forest floor compared with the controls. Higher dead coarse fuel loads were still evident after 3–4 years. Changes to fuel properties produced a reduction in predicted flame heights from 22 m to 5–6 m under severe fire weather conditions, but no change in the predicted fire rate of spread. Reductions in flame height would be beneficial for wildfire suppression and could reduce the damage to property from wildfires. Mastication did not have a meaningful effect on native species diversity, but promoted the abundance of some exotic species.