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The McArthur grassland and forest fire danger indices, widely used in Australia, predict six fire danger classes from ‘Low-Moderate’ to ‘Catastrophic.’ These classes were linked to the rate of fire spread and difficulty of suppression. However, the lack of rate of fire spread data, especially for elevated fire danger classes, has hindered improvement of the McArthur methodology or an alternate approach. We explored the relationship between fire danger classes and burned areas (derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite instrument) within six climate zones during the 2000–2016 Australian fire seasons. A negative binomial linear regression model was used to explore this relationship. The fire danger classes demonstrated a corresponding increase in burned area from ‘Low-Moderate’ to ‘Very High’ classes in Australia’s inland regions. The elevated fire danger classes did not contribute to this trend. In coastal regions, the satellite-derived burned area showed no relationship between fire danger classes and satellite-derived burned area. We used accumulated burned area from the daily MODIS product, which could be subjected to lagged detection as observed in the Kilmore East fire. Thus, the satellite-derived total burned area may not be a suitable metric for informing the McArthur fire danger classes across Australia.

Analyses of the effects of topography, weather, land management, and fuel on fire severity are increasingly common, and generally apply fire severity indices derived from satellite optical remote sensing. However, these indices are commonly interpreted with insufficient appreciation for their limitations and may be inappropriately invoked as representing physical fire effects and fire behaviour. For a large wildfire in southeast Australia, we investigated three considerations for inferring robust insights from fire severity analyses – the potentially confounding influences of pre-fire vegetation height and tall vegetation cover, and the choice of fire severity response variable. Using nonparametric regression, we found that different fire severity indices gave rise to substantially different modelled relationships with commonly invoked environmental predictors, as is consistent with dissimilarities in index design. Further, pre-fire vegetation height was a strong control of fire severity, with equivalent importance to weather. Importantly, strong covariation between vegetation height and environmental predictors suggests that modelled fire severity effects are strongly influenced by variation in vertical distance between flames and vegetation, and this confounds fire behaviour insights. To enable more robust and mechanistic insights into the determinants of fire severity, we recommend greater consideration of the meaning and limitations of optical remote sensing indices.

Spectral indices derived from satellite optical remote sensing data have typically been used for fire severity estimation, although other remote sensing systems such as Light Detection and Ranging (LiDAR) are increasingly applied. Despite a multitude of remotely sensed fire severity estimation methods, comparisons of method performance are few. Insights into the merits and limitations of remotely sensed fire severity methods help develop appropriate spatial tools for the management of fire-affected areas. We evaluated the performance of seven passive (optical) and active (LiDAR) remotely sensed fire severity estimation methods in classifying and explaining variation in a field-estimated modified Composite Burn Index (MCBI) for a recent large wildfire in south-eastern Australia. Our evaluation included three commonly applied indices; the differenced Normalized Burn Ratio (dNBR), Relative dNBR (RdNBR) and Relative Burn Ratio (RBR). We compared these NBR indices against two recently proposed fire severity estimation methods that have not previously been evaluated with CBI field data–the Vegetation Structure Perpendicular Index (VSPI) spectral index and the LiDAR point cloud-derived Profile Area Change (PAC), along with experimental relativized forms of these indices (RVSPI and RPAC, respectively). The RVSPI (κ = 0.47) demonstrated similar overall classification accuracy (N classes = 4) to the PAC (κ = 0.48), however both indices had lower classification accuracy than the dNBR (κ = 0.59), RdNBR (κ = 0.59) and RBR (κ = 0.61). The VSPI and PAC were unable to accurately represent non-structural changes caused by lower severity fire. Application of these optical and LiDAR indices should consider their discussed limitations in relation to the objectives of their application.

Fire drives animal population dynamics across many ecosystems. Yet, we still lack an understanding of how most species recover from fire and the effects of fire severity and patchiness on recovery processes. This information is crucial for fire‐mediated biodiversity conservation, particularly as fire regimes change globally. We conducted an experiment to test whether post‐fire recovery is driven by in situ survival or recolonisation, and to determine whether this varies with fires of increasing percentage area burnt (burn cover) and severity. We used the pale field rat Rattus tunneyi as a model, because it represents the extinction process for a suite of mammal species suffering population collapse across Australia's northern savannas. Our treatments spanned a gradient from patchy, low severity fires (simulating early dry season management burns) to thorough, high severity fires (simulating wildfires). We performed capture–mark–recapture, vegetation and aerial surveys before, 6 weeks after and 1 year after fire. Six weeks after fire, pale field rats were only captured in unburnt patches of vegetation, and capture rates were proportional to the amount of unburnt habitat. One year later, both vegetation and pale field rat populations recovered across all sites. However, population recovery after low severity fires was likely achieved through in situ survival and reproduction in unburnt micro‐refuges, compared to recolonisation driving recovery after high severity fires. Synthesis and applications. Pale field rat persistence is strongly dependent on the retention of unburnt habitat patches within fire‐affected areas. Management strategies that increase micro‐refugia within burnt areas may facilitate pale field rat population recovery. Globally, building recovery mechanisms into fire management will be vital for supporting the long‐term persistence of fire‐affected species.

Forests exhibit thresholds in disturbance intervals that influence sustainability of production and natural values including sawlog production, species existence and habitat attributes. Fire is a key disturbance agent in temperate forests and frequency of fire is increasing, threatening sustainability of these forest values. We used mechanistically diverse, theoretical fire interval distributions for mountain ash forest in Victoria, Australia, in the recent past and future to estimate the probability of realising: (i) minimum sawlog harvesting rotation time; (ii) canopy species maturation; and (iii) adequate habitat hollows for fauna. The likelihood of realising fire intervals exceeding these key stand age thresholds diminishes markedly for the future fire regime compared with the recent past. For example, we estimate that only one in five future fire intervals will be sufficiently long (~80 years) to grow sawlogs in this forest type, and that the probability of forests developing adequate habitat hollows (~180 years) could be as low as 0.03 (3% of fire intervals). Therefore, there is a need to rethink where sawlogs can be sourced sustainably, such as from fast-growing plantations that can be harvested and then regrown rapidly, and to reserve large areas of existing 80-year-old forest from timber harvesting.

Foliage fuel load (FFL) is a critical factor affecting crown fire intensity and rate of spread. Satellite observations provide the potential for monitoring FFL dynamics across large areas. Previous studies commonly used empirical methods to estimate FFL, which potentially lacks reproducibility. This study applied Landsat 7 ETM+ and 8 OLI data for FFL retrieval using radiative transfer model (RTM) and machine learning method. To this end, the GeoSail, SAIL, and PROSPECT RTMs were first coupled together to model the near-realistic scenario of a two-layered forest structure. Second, available ecological information was applied to constrain the coupled RTM modeling phases in order to decrease the probability of generating unrealistic simulations. Third, the coupled RTMs were linked to three machine learning models—random forest, support vector machine, and multilayer perceptron—as well as the traditional lookup table. Finally, the performance of each method was validated by FFL measurements from Southwest China and Sweden. The resulting multilayer perceptron ( R 2 = 0.77, RMSE = 0.13, and rRMSE = 0.43) outperformed the other three methods. The evaluation of the applicability of the FFL estimates was conducted in a southwest China forest where two occurred in 2014 and 2020. The FFL dynamics from 2013 through 2020 showed that the fire was likely to occur when the FFL accumulated to a critical point (around 27 × 106 kg), highlighting the relevance of remote sensing derived FFL estimates for understanding potential fire occurrence.

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.

Litter moisture content plays a critical role in fire danger rating systems and forest ecosystems. Soil moisture content has been proposed to affect litter moisture due to vapour flux and capillary rise from the soil. However, few models consider soil water content when predicting litter moisture, and to our knowledge, no model includes capillary fluxes. In this study, we represented soil moisture coupling in a physics-based litter moisture prediction model by describing the vapour and capillary fluxes from the soil to litter. We aimed to evaluate if litter moisture predictions can be improved by incorporating the hydrological process at the soil-litter interface and explored the possible role of soil moisture in litter moisture simulations. Three model versions were compared against observations at a dry and wet experimental site in Australia: the original physics-based model, a model version extended with soil vapour flux only, and a version that incorporates both soil vapour flux and capillary rise. The simulation results suggest that soil moisture considerably influences litter moisture through soil vapour flux and capillary rise, which can lead to more than 10% of oven-dried weight, particularly under wet soil conditions. The corresponding model showed the best performance in comparison with field observations. The contribution of upward soil moisture fluxes was small after long dry and warm periods but noticeable during more moist periods. Further research is needed to evaluate the revised model for a broader range of weather, soil and litter conditions.

Fuel moisture content (FMC) of fine surface litter fuel plays a decisive role in determining fire ignition and spread. Understanding physical processes that determine litter moisture dynamics is necessary to accurately predict litter FMC. It is known that vapour exchange, precipitation and latent heat transfer are dominant factors governing changes in litter FMC. However, limited research has been undertaken on physical processes at the soil-litter interface, despite the presumed importance of soil moisture in hydrating litter. In this study, we investigated the influence of soil moisture on litter FMC in factorial controlled field experiments at a dry and a wet site in Canberra, Australia. Each site had two treatments: with and without contact between soil and litter. Litter FMC, temperature and relative humidity were automatically and continuously measured in both surface and subsurface litter with a combination of fuel moisture, temperature and relative humidity sensors. The two treatments showed a different influence of soil moisture on litter FMC at the dry and wet site. There was limited moisture transport from soil to litter at the dry site, almost certainly dominated by vapour flux. Here, the influence of soil moisture on litter FMC is through its influence on local humidity in the litter layer. However, at the wet site capillary flow occurred in addition to vapour flux from the soil. The capillary flow responded to the matric potential gradient between soil and litter. The measurements confirmed that subsurface litter was more strongly coupled to the soil than the surface litter, which was more strongly coupled with the atmosphere. The improved understanding of physical processes governing water transport from soil to litter should help predict litter FMC more accurately, especially under wet soil conditions. Further research is needed to incorporate soil-litter interactions in litter FMC simulations.

Fire is one of the predominant drivers of the structural and functional dynamics of forest ecosystems. In recent years, novel fire regimes have posed a major challenge to the management of pyrodiverse forests. While previous research efforts have focused on quantifying the impacts of fire on above-ground forest biodiversity, how microbial communities respond to fire is less understood, despite their functional significance. Here, we describe the effects of time since fire, fire frequency and their interaction on soil and leaf litter fungal and bacterial communities from the pyrodiverse, Eucalyptus pilularis forests of south-eastern Australia. Using structural equation models, we also elucidate how fire can influence these communities both directly and indirectly through biotic–abiotic interactions. Our results demonstrate that fire is a key driver of litter and soil bacterial and fungal communities, with effects most pronounced for soil fungal communities. Notably, recently burnt forest hosted lower abundances of symbiotic ectomycorrhizal fungi and Acidobacteria in the soil, and basidiomycetous fungi and Actinobacteriota in the litter. Compared with low fire frequencies, high fire frequency increased soil fungal plant pathogens, but reduced Actinobacteriota. The majority of fire effects on microbial communities were mediated by fire-induced changes in litter and soil abiotic properties. For instance, recent and more frequent fire was associated with reduced soil sulphur, which led to an increase in soil fungal plant pathogens and saprotrophic fungi in these sites. Pathogenic fungi also increased in recently burnt forests that had a low fire frequency, mediated by a decline in litter carbon and an increase in soil pH in these sites. Synthesis. Our findings indicate that predicted increases in the frequency of fire may select for specific microbial communities directly and indirectly through ecological interactions, which may have functional implications for plants (increase in pathogens, decrease in symbionts), decomposition rates (declines in Actinobacteriota and Acidobacteriota) and carbon storage (decrease in ectomycorrhizal fungi). In the face of predicted shifts in wildfire regimes, which may exacerbate fire-induced changes in microbial communities, adaptive fire management and monitoring is required to address the potential functional implications of fire-altered microbial communities. Published version This work was funded by the Australian Research Council, Parks Australia and the Australian Department of Defence through ARC Linkage Project LP170100152.

Fire and herbivores alter vegetation structure and function. Future fire activity is predicted to increase, and quantifying changes in vegetation communities arising from post-fire herbivory is needed to better manage natural environments. We investigated the effects of post-fire herbivory on understory plant communities in a coastal eucalypt forest in southeastern Australia. We quantified herbivore activity, understory plant diversity, and dominant plant morphology following a wildfire in 2017 using two sizes of exclosures. Statistical analysis incorporated the effect of exclusion treatments, time since fire, and the effect of a previous prescribed burn. Exclusion treatments altered herbivore activity, but time since fire did not. Herbivory reduced plant species richness, diversity, and evenness and promoted the dominance of the most abundant plants within the understory. Increasing time since fire reduced community diversity and evenness and influenced morphological changes to the dominant understory plant species, increasing size and dead material while decreasing abundance. We found the legacy effects of a previous prescribed burn had no effect on herbivores or vegetation within our study. Foraging by large herbivores resulted in a depauperate vegetation community. As post-fire herbivory can alter vegetation communities, we postulate that management burning practices may exacerbate herbivore impacts. Future fire management strategies to minimize herbivore-mediated alterations to understory vegetation could include aggregating management burns into larger fire sizes or linking fire management with herbivore management. Restricting herbivore access following fire (planned or otherwise) can encourage a more diverse and species-rich understory plant community. Future research should aim to determine how vegetation change from post-fire herbivory contributes to future fire risk.

Summary Forested environments are subject to large and high intensity unplanned fire events, owing to, among other factors, the high quantity and complex structure of fuel in these environments. Compiling accurate and spatially comprehensive fuel information is necessary to inform various aspects of land management in forested environments. Remote sensing may offer distinct advantages for this in comparison to traditional site-based approaches. We conducted a literature review of the past 10 years of research in the remote sensing of fire fuel in forested environments, with a focus on emerging methods of fuel estimation, and the fuel attributes estimated. We position our review of remote sensing research in relation to the fuel attributes that influence fire behaviour, as suggested by contemporary physics-based fire behaviour knowledge, and a summary of fuel inputs to widely applied forest fire behaviour models. We find a disconnect between recent remote sensing research and fuel characterisations relevant to contemporary fire behaviour knowledge. Specifically, we find a tendency in remote sensing research towards estimation of forest overstorey fuel attributes, and a relative lack of research that estimates more obscured, though highly relevant, fuel components such as understorey, surface, and bark fuel. We also find a tendency for recent remote sensing research to conceptualise fire fuel by existing fire behaviour models, with particular emphasis on matching pre-existing fuel model classifications. A case is made for remotely sensed forest fuel estimation grounded in current knowledge of fire behaviour processes and the fuel attributes known to influence these processes. Shortcomings in remote sensing of key forest fuel attributes are partly due to inherent limitations of current technologies, and we discuss recent and expected advancements in remote sensing research and technology that may drive significant future advancement in forest fuel estimation. Further, we suggest that recognition of interactions between fuel attributes and measurable biophysical forest properties can assist in addressing present limitations in remote sensing of key forest fuel attributes. Such process-based methods would be more spatially and temporally applicable, encourage new techniques for estimating fuel attributes using remote sensing data, and may encourage the development of fire behaviour and risk prediction systems that are more suited to remote sensing.

Fuel moisture content (FMC) of the litter is a critical factor determining fire ignition and spread and is an important input for most fire behaviour prediction models. Several models, ranging from empirical regression functions to physics-based models, have been developed to forecast litter FMC. Soil moisture below the litter layer has been shown to influence litter FMC, but few models explicitly consider its effect. This study aimed to evaluate how soil moisture content may affect litter FMC by coupling soil moisture as a boundary condition to the physics-based ‘Koba’ model, which simulates radiation, energy and moisture fluxes in the surface and subsurface litter layer. The coupled model was tested at five sites in Victoria, Australia, where litter FMC values were recorded continuously during 2014-2015 using calibrated fuel stick sensors. Two versions of the model were compared against the observations: an uncoupled model and a model version accounting for the vapour flux from soil to litter. The simulation results show that the influence of soil moisture depends on environmental conditions. Soil moisture appeared to have a minor influence on FMC when both soil and litter are dry, but a stronger influence when the soil is relatively wet. Correspondingly, the coupled model explained observed FMC better than the uncoupled model for the two wetter study sites. As expected, the subsurface litter in contact with the soil appeared more sensitive to soil moisture conditions than the surface litter. The influence of soil vapour flux on litter FMC can be considerable during the transition from wet to dry litter and soil conditions. This has implications for hazard reduction burning, which is typically planned to take advantage of transitional fuel moisture conditions. Further research is needed to understand the influence of the structure and thickness of litter on the importance of soil vapour flux.

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.

Fuel Moisture Content (FMC) is one of the primary drivers affecting fuel flammability that lead to fires. Satellite observations well-grounded with field data over the highly climatologically and ecologically diverse Australian region served to estimate FMC and flammability for the first time at a continental-scale. The methodology includes a physically-based retrieval model to estimate FMC from MODIS (Moderate Resolution Imaging Spectrometer) reflectance data using radiative transfer model inversion. The algorithm was evaluated using 360 observations at 32 locations around Australia with mean accuracy for the studied land cover classes (grassland, shrubland, and forest) close to those obtained elsewhere (r = 0.58, RMSE = 40%) but without site-specific calibration. Logistic regression models were developed to generate a flammability index, trained on fire events mapped in the MODIS burned area product and four predictor variables calculated from the FMC estimates. The selected predictor variables were actual FMC corresponding to the 8-day and 16-day period before burning; the same but expressed as an anomaly from the long-term mean for that date; and the FMC change between the two successive 8-day periods before burning. Separate logistic regression models were developed for grassland, shrubland and forest. The models obtained an “Area Under the Curve” calculated from the Receiver Operating Characteristic plot method of 0.70, 0.78 and 0.71, respectively, indicating reasonable skill in fire risk prediction., Bushfire and Natural Hazards CRC

Removing vegetation close to houses is at the forefront of advice provided to home owners by fire management agencies. However, widespread clearing of trees and shrubs near houses impacts aesthetics, privacy, biodiversity, energy consumption and property values. Thus, stakeholders may oppose this practice. Regulators and property owners therefore require options for vegetation management that reduce risk to houses during wildfires without complete removal of trees and shrubs. Using data from 499 houses impacted by wildfires, we tested three hypotheses: (1) maintaining ‘green’ vegetation affords houses additional protection during wildfires; (2) risk posed by trees and shrubs near houses is reduced where they are arranged as many discrete patches; and (3) trees and shrubs retained in the upwind direction from which wildfires arrive represent greater risk to houses than trees and shrubs retained in the downwind direction. We found empirical support for each hypothesis. Increasing the mean Normalised Vegetation Difference Index (NDVI) (a measure of “greenness”) of vegetation near houses had the same effect on reducing house losses as removing some trees and shrubs. Trees and shrubs within 40 m of houses arranged as many discrete patches posed less risk than the same cover of trees and shrubs arranged as few discrete patches. Trees and shrubs retained downwind from houses represented less risk than trees and shrubs retained upwind. Our findings represent options for regulators or home owners seeking to balance risk posed by wildfires with benefits associated with retaining trees and shrubs near houses.

Understanding how landscape heterogeneity mediates the effects of fire on biodiversity is increasingly important under global changes in fire regimes. We used a simulation experiment to investigate how fire regimes interact with topography and weather to shape neutral and selection-driven genetic diversity under alternative dispersal scenarios, and to explore the conditions under which micro-refuges can maintain genetic diversity of populations exposed to recurrent fire. Spatial heterogeneity in simulated fire frequency occurred in topographically-complex landscapes, with fire refuges and fire-prone ‘hotspots’ apparent. Inter-annual weather variability reduced the effect of topography on fire patterns, with refuges less apparent under high weather variability. Neutral genetic diversity was correlated with long-term fire frequency under spatially heterogeneous fire regimes, being higher in fire refuges than fire-prone areas, except under high dispersal or low fire severity (low mortality). This generated different spatial genetic structures in fire-prone and fire-refuge components of the landscape, despite similar dispersal. In contrast, genetic diversity was only associated with time since the most recent fire in flat landscapes without predictable refuges and hotspots. Genetic effects of selection driven by fire-related conditions depended on selection pressure, migration distance and spatial heterogeneity in fire regimes. Allele frequencies at a locus conferring higher fitness under successional environmental conditions followed a pattern of ‘temporal adaptation’ to contemporary conditions under strong selection pressure and high migration. However, selected allele frequencies were correlated with spatial variation in long-term mean fire frequency (relating to environmental predictability) under weak dispersal, low selection pressure and strong spatial heterogeneity in fire regimes. This article is protected by copyright. All rights reserved.

Fire is a powerful ecological and evolutionary force. Animals that modify drivers of fire behaviour could therefore have far-reaching effects on ecosystems. Yet, with a few notable exceptions, effects of animals on fire have been often overlooked. We show how animals can affect fire behaviour by modifying the amount, structure, or condition of fuel or, more rarely, by altering other controls on fire such as wind speed or ignition patterns. Some effects are readily observed and quantified. Others are more subtle but could be considerable when accumulated over time, space, and animal taxa. A combination of manipulative experiments, landscape studies, and multiscale fire models will be necessary to understand the consequences of widespread changes in animal populations for landscape fire.

Bushfires are one of the most frequent natural hazards experienced in Australia. Fires play an important role in shaping the landscape and its ecological dynamics, but may also have devastating effects that cause human injuries and fatalities, as well as broad-scale environmental damage. While there has been considerable effort to quantify changes in the occurrence of bushfire in Australia, a comprehensive assessment of the most extreme bushfire cases, which exact the greatest economic and environmental impacts, is lacking. In this paper we reflect upon recently developed understanding of bushfire dynamics to consider (i) historical changes in the occurrence of extreme bushfires, and (ii) the potential for increasing frequency in the future under climate change projections. The science of extreme bushfires is still a developing area, thus our conclusions about emerging patterns in their occurrence should be considered tentative. Nonetheless, historical information on noteworthy bushfire events suggests an increased occurrence in recent decades. Based on our best current understanding of how extreme bushfires develop, there is strong potential for them to increase in frequency in the future. As such there is a pressing need for a greater understanding of these powerful and often destructive phenomena.

Wildland fire intensity influences natural communities, soil properties, erosion, and sequestered carbon. Measuring effectiveness of fuel treatment for reducing area of higher intensity unplanned fire is argued to be more meaningful than determining effect on total unplanned area burned. To contrast the relative importance of fuel treatment effort, ignition management effort and weather for simulated total area burned and area burned by moderate-to-high intensity fire, and to determine the level of consensus among independent models. Published and previously unreported data from simulation experiments using three landscape fire models, two incorporating weather from south-eastern Australia and one with weather from a Mediterranean location, were compared. The comparison explored variation in fuel treatment and ignition management effort across ten separate years of daily weather. Importance of these variables was measured by the Relative Sum of Squares in a Generalised Linear Model analysis of total pixels burned and pixels burned with moderate-to-high intensity fire. Variation in fuel treatment effort, from 0 to 30 % of landscape treated, explained less than 7 % of variation in both total area burned and area burned by moderate-to-high intensity fire. This was markedly less than that explained by variation in ignition management effort (0–75 % of ignitions prevented or extinguished) and weather year in all models. Increased fuel treatment effort, within a range comparable to practical operational limits, was no more important in controlling simulated moderate-to-high intensity unplanned fire than it was for total unplanned area burned.

Exploring interactions between ecological disturbance, species’ abundances and community composition provides critical insights for ecological dynamics. While disturbance is also potentially an important driver of landscape genetic patterns, the mechanisms by which these patterns may arise by selective and neutral processes are not well‐understood. We used simulation to evaluate the relative importance of disturbance regime components, and their interaction with demographic and dispersal processes, on the distribution of genetic diversity across landscapes. We investigated genetic impacts of variation in key components of disturbance regimes and spatial patterns that are likely to respond to climate change and land management, including disturbance size, frequency, and severity. The influence of disturbance was mediated by dispersal distance and, to a limited extent, by birth rate. Nevertheless, all three disturbance regime components strongly influenced spatial and temporal patterns of genetic diversity within subpopulations, and were associated with changes in genetic structure. Furthermore, disturbance‐induced changes in temporal population dynamics and the spatial distribution of populations across the landscape resulted in disrupted isolation by distance patterns among populations. Our results show that forecast changes in disturbance regimes have the potential to cause major changes to the distribution of genetic diversity within and among populations. We highlight likely scenarios under which future changes to disturbance size, severity, or frequency will have the strongest impacts on population genetic patterns. In addition, our results have implications for the inference of biological processes from genetic data, because the effects of dispersal on genetic patterns were strongly mediated by disturbance regimes.

Our understanding of the impacts of time since fire on reptiles remains limited, partly because there are relatively few locations where long‐term, spatially explicit fire histories are available. Such information is important given the large proportion of some landscapes that are managed with frequent prescribed fire to meet fuel management objectives. We conducted a space‐for‐time study across a landscape in southeastern Australia where the known fire history spanned 6 months to at least 96 years. Four methods were used to survey reptiles in 81 forest and woodland sites to investigate how time since fire (TSF), habitat, and environmental variables affect reptile richness, abundance, and composition. We used generalized linear models, generalized linear mixed‐effects models, PERMANOVA, and SIMPER to identify relationships between the reptile assemblage (richness, abundance, and composition, respectively) and TSF, habitat, and environmental variables. All three reptile metrics were associated with TSF. Reptile richness and abundance were significantly higher in sites >96 years postfire than younger fire ages (0.5–12 years). Reptile composition at long‐unburned sites was dissimilar to sites burned more recently but was similar between sites burned 0.5–2 and 6–12 years prior to sampling. Synthesis and applications. Long‐unburned forests and woodlands were disproportionately more important for reptile richness and abundance than areas burned 6 months to 12 years prior to sampling. This is important given that long‐unburned areas represent

We present the first continental-scale methodology for estimating Live Fuel Moisture Content (FMC) and flammability in Australia using satellite observations. The methodology includes a physically-based retrieval model to estimate FMC from MODIS (Moderate Resolution Imaging Spectrometer) reflectance data using radiative transfer model inversion. The algorithm was evaluated using 363 observations at 33 locations around Australia with mean accuracy for the studied land cover classes (grassland, shrubland, and forest) close to those obtained elsewhere $(\mathrm{r}^{2}=0.57,\ \text{RMSE} =40\%)$ but without site-specific calibration. Logistic regression models were developed to predict a flammability index, trained on fire events mapped in the MODIS burned area product and four predictor variables calculated from the FMC estimates. The selected predictor variables were actual FMC corresponding to the 8-day and 16-day period before burning; the same but expressed as an anomaly from the long-term mean for that date; and the FMC change between the two successive 8-day periods before burning. Separate logistic regression models were developed for grassland, shrubland and forest, obtaining performance metrics of 0.70, 0.78 and 0.71, respectively, indicating reasonable skill in fire risk prediction.

The wildland fire sector faces increased frequency and size of fires and increasing community expectations and costs of management, and is turning more to economics to inform management and policy decisions. However, the literature on costs and benefits of wildland fires and their management is disparate and unstructured and requires critical review and synthesis to better inform potential users. We reviewed 60 economic studies to identify why, what and how evaluations were undertaken. We synthesised the results into a systematic framework of the types of economic evaluations and methods that can be undertaken to inform fire management and policy. We found that key challenges in undertaking economic evaluations include risk and uncertainty surrounding decisions, and data limitations. Most studies have focused on sector management-level decisions of pre-suppression and suppression activities, dominated by US applications. There are opportunities to undertake evaluations in other decision and geographic con...

Monitoring and evaluation (M&E) of biodiversity has been heavily criticised. However, these criticisms have yet to be tested empirically across a range of geographical environments and institutions. We surveyed 243 protected area staff from 55 countries to describe how M&E is undertaken and to identify variables statistically associated with effective M&E. We found that M&E is routinely employed: 78% of respondents indicated that monitoring occurred and 64% responded that monitoring persisted for at least as long that a management action was implemented. However, our results suggested there is scope to improve the way that M&E is conducted: only 46% of respondents thought that M&E worked well, just 36% provided an example of monitoring informing management and 38% of respondents indicated that management is not undertaken in different ways to facilitate adaptive management. Monitoring and evaluation was generally perceived to be working better in non-government organisations (NGOs), where data are entered in existing databases, and where research and management staff work cooperatively. Monitoring had a greater probability of informing management where documented thresholds were in place that trigger management intervention and where monitoring data were stored in a publicly available database. Management was most likely to be implemented in different ways to facilitate adaptive management in NGOs, where management intervention options were documented, monitoring had persisted as long as the management action and where reporting is done regularly. The most common suggestions that respondents gave to improve M&E were increased funding, better science management integration, and improving organisational culture and commitment.

Environmental disturbance underpins the dynamics and diversity of many of the ecosystems of the world, yet its influence on the patterns and distribution of genetic diversity is poorly appreciated. We argue here that disturbance history may be the major driver that shapes patterns of genetic diversity in many natural populations. We outline how disturbance influences genetic diversity through changes in both selective processes and demographically driven, selectively neutral processes. Our review highlights the opportunities and challenges presented by genetic approaches, such as landscape genomics, for better understanding and predicting the demographic and evolutionary responses of natural populations to disturbance. Developing this understanding is now critical because disturbance regimes are changing rapidly in a human-modified world.

An assessment of the relative importance of vegetation change and disturbance as agents of landscape change under current and future climates would (1) provide insight into the controls of landscape dynamics, (2) help inform the design and development of coarse scale spatially explicit ecosystem models such as Dynamic Global Vegetation Models (DGVMs), and (3) guide future land management and planning. However, quantification of landscape change from vegetation development and disturbance effects is difficult because of the large space and long time scales involved. Comparative simulation modeling experiments, using a suite of models to simulate a set of scenarios, can provide a platform for investigating landscape change over more ecologically appropriate time and space scales that control vegetation and disturbance. We implemented a multifactorial simulation experiment using five landscape fire succession models to explore the role of fire and vegetation development under various climates on a neutral landscape. The simulation experiment had four factors with two or three treatments each: (1) fire (fire and no fire), (2) succession (dynamic and static succession), (3) climate (historical, warm-wet, warm-dry), and (4) weather (constant, variable). We found that, under historical climates, succession changed more area annually than fire by factors of 1.2 to 34, but one model simulated more landscape change from fire (factor of 0.1). However, we also found that fire becomes more important in warmer future climates with factors decreasing to below zero for most models. We also found that there were few differences in simulation results between weather scenarios with low or high variability. Results from this study show that there will be a shift from vegetation processes that control today's landscape dynamics to fire processes under future warmer and drier climates, and this shift means that detailed representations of both succession and fire should be incorporated into models to realistically simulate interactions between disturbance and vegetation.

The worldwide "wildfire" problem is headlined by the loss of human lives and homes, but it applies generally to any adverse effects of unplanned fires, as events or regimes, on a wide range of environmental, social, and economic assets. The problem is complex and contingent, requiring continual attention to the changing circumstances of stakeholders, landscapes, and ecosystems; it occurs at a variety of temporal and spatial scales. Minimizing adverse outcomes involves controlling fires and fire regimes, increasing the resistance of assets to fires, locating or relocating assets away from the path of fires, and, as a probability of adverse impacts often remains, assisting recovery in the short-term while promoting the adaptation of societies in the long-term. There are short- and long-term aspects to each aspect of minimization. Controlling fires and fire regimes may involve fire suppression and fuel treatments such as prescribed burning or non-fire treatments but also addresses issues associated with unwanted fire starts like arson. Increasing the resistance of assets can mean addressing the design and construction materials of a house or the use of personal protective equipment. Locating or relocating assets can mean leaving an area about to be impacted by fire or choosing a suitable place to live; it can also mean the planning of land use. Assisting recovery and promoting adaptation can involve insuring assets and sharing responsibility for preparedness for an event. There is no single, simple, solution. Perverse outcomes can occur. The number of minimizing techniques used, and the breadth and depth of their application, depends on the geographic mix of asset types. Premises for policy consideration are presented.

Aim The increased incidence of large fires around much of the world in recent decades raises questions about human and non-human drivers of fire and the likelihood of increased fire activity in the future. The purpose of this paper is to outline a conceptual framework for examining where human-set fires and feedbacks are likely to be most pronounced in temperate forests world-wide and to establish and test a methodology for evaluating this framework using palaeoecological records.

Aim Comparative analyses of fire regimes at large geographical scales can potentially identify ecological and climatic controls of fire. Here we describe Australia’s broad fire regimes, and explore interrelationships and trade-offs between fire regime components. We postulate that fire regime patterns will be governed by trade-offs between moisture, productivity, fire frequency and fire intensity. Location Australia. Methods We reclassified a vegetation map of Australia, defining classes based on typical fuel and fire types. Classes were intersected with a climate classification to derive a map of ‘fire regime niches’. Using expert elicitation and a literature search, we validated each niche and characterized typical and extreme fire intensities and return intervals. Satellite-derived active fire detections were used to determine seasonal patterns of fire activity. Results Fire regime characteristics are closely related to the latitudinal gradient in summer monsoon activity. Frequent low-intensity fires occur in the monsoonal north, and infrequent, high-intensity fires in the temperate south, demonstrating a trade-off between frequency and intensity: that is, very high-intensity fires are only associated with very low-frequency fire regimes in the high biomass eucalypt forests of southern Australia. While these forests occasionally experience extremely intense fires (> 50,000 kW m), such regimes are exceptional, with most of the continent dominated by grass fuels, typically burning with lower intensity (< 5000 kW m). Main conclusions Australia’s fire regimes exhibit a coherent pattern of frequent, grass-fuelled fires in many differing vegetation types. While eucalypts are a quintessential Australian entity, their contribution as a dominant driver of high-intensity fire regimes, via their litter and bark fuels, is restricted to the forests of the continent’s southern and eastern extremities. Our analysis suggests that the foremost driver of fire regimes at the continental scale is not productivity, as postulated conceptually, but the latitudinal gradient in summer monsoon rainfall activity.

The influence of plant traits on forest fire behaviour has evolutionary, ecological and management implications, but is poorly understood and frequently discounted. We use a process model to quantify that influence and provide validation in a diverse range of eucalypt forests burnt under varying conditions. Measured height of consumption was compared to heights predicted using a surface fuel fire behaviour model, then key aspects of our model were sequentially added to this with and without species-specific information. Our fully specified model had a mean absolute error 3.8 times smaller than the otherwise identical surface fuel model (p < 0.01), and correctly predicted the height of larger (≥1 m) flames 12 times more often (p < 0.001). We conclude that the primary endogenous drivers of fire severity are the species of plants present rather than the surface fuel load, and demonstrate the accuracy and versatility of the model for quantifying this.

Wildfires pose significant risks to people and human infrastructure worldwide. The treatment of fuel in landscapes may alter these risks but the magnitude of this effect on risk is poorly understood. Evidence from Australian Eucalyptus forests suggests that mitigation of risk using prescribed burning as a fuel treatment is partial because weather and fuel dynamics are conducive to regular high intensity fires. We further examine the response of risk to treatment in eucalypt forests using landscape simulation modelling. We model how five key measures of wildfire activity that govern risk to people and property may respond to variations in rate and spatial pattern of prescribed fire. We then model effects of predicted climate change (2050 scenarios) to determine how the response of risk to treatment is likely to be altered in the future. The results indicate that a halving of risk to people and property in these forests is likely to require treatment rates of 7-10% of the area of the landscape per annum. Projections of 2050 weather conditions under climate change further substantially diminished the effect of rate of treatment. A large increase in rates of treatment (i.e. circa. 50% over current levels) would be required to counteract these effects of climate change. Such levels of prescribed burning are unlikely to be financially feasible across eucalypt dominated vegetation in south eastern Australia. Despite policy imperatives to expand fuel treatment, a reduction rather than an elimination of risk will result. Multi-faceted strategies will therefore be required for the management of risk.

Knowing how species respond to fire regimes is essential for ecologically sustainable management. This axiom raises two important questions: (1) what knowledge is the most important to develop and (2) to what extent can current research methods deliver that knowledge? We identify three areas of required knowledge: (i) a mechanistic understanding of species' responses to fire regimes; (ii) knowledge of how the spatial and temporal arrangement of fires influences the biota; and (iii) an understanding of interactions of fire regimes with other processes. We review the capacity of empirical research to address these knowledge gaps, and reveal many limitations. Manipulative experiments are limited by the number and scope of treatments that can be applied, natural experiments are limited by treatment availability and confounding factors, and longitudinal studies are difficult to maintain, particularly due to unplanned disturbance events. Simulation modelling is limited by the quality of the underlying empirical data and by uncertainty in how well model structure represents reality. Due to the constraints on large-scale, long-term research, the potential for management experiments to inform adaptive management is limited. Rather than simply recommending adaptive management, we define a research agenda to maximise the rate of learning in this difficult field. This includes measuring responses at a species level, building capacity to implement natural experiments, undertaking simulation modelling, and judicious application of experimental approaches. Developing ecologically sustainable fire management practices will require sustained research effort and a sophisticated research agenda based on carefully targeting appropriate methods to address critical management questions. (C) 2010 Elsevier Ltd. All rights reserved.

Plant species in fire-prone environments possess specific traits which allow them to survive fire. Species are commonly classified according to whether they survive fire and resprout or whether they are killed by fire and regenerate from seed. However, different populations of the same species have been shown to vary in their responses. Therefore, the classification of a species into a single category based on fire-response traits may not necessarily be representative of every population under every circumstance. This study examined the extent of within-species variation in fire-response traits of woody plants in south-eastern Australia after the 2003 fires. Species were then classified using two approaches: (i) using data from a field survey of fire-response traits, taking into account within-species variation; and (ii) using species' fire responses listed in a pre-existing fire-response database compiled from a variety of primary sources. Field data showed that the majority of species in the study area resprouted after fire with around one in 10 species variable in their resprouting response. Almost half of all species varied from site to site according to whether they regenerated from seed, either solely or in addition to resprouting. The numbers of species classified as resprouters and seed regenerators varied according to the classification method used. Differences were also found between the classification method when calculating the mean proportion of resprouters and seed regenerators across sites. The fire-response traits for some species from the database were found to differ from the observed field responses. This study demonstrated that the application of a fire-response trait, reported in a trait database, to an entire species, may not adequately represent the actual fire responses of the populations of interest. Rather than considering the fire-response traits of a species, accurate prediction may be better achieved by considering how different populations of plants will respond to fire.

Fuel hazard is often assumed to increase with fuel age, or the time-since-fire. However, studies on fuel hazard in long-unburned forests are scarce. We measured overall fuel hazard in Eucalyptus forests and woodlands in south-eastern Australia at 81 sites where time-since-fire spans 0.5 years to at least 96 years. Overall fuel hazard was higher in forests and woodlands burned 6–12 years previously than those unburned for at least 96 years. The probability of high, very high or extreme overall fuel hazard – which is an operational threshold considered to equate with almost no chance of wildfire suppression in severe fire-weather – was highest 0.5–12 years post-fire, and lowest where fire had not occurred for at least 96 years. Frequent burning can maintain forest understorey in an early successional ‘shrubby’ state, leading to higher overall fuel hazard than forests where a lack of fire is associated with the senescence of shrubs. Protecting long-unburned sites from fire and managing to transition a larger proportion of forest to a long-unburned state may benefit fuel-hazard management within these forests in the long-term.

Increasing density of mid-storey vegetation since European settlement has been observed in forests and woodlands in several parts of the world and may result in greater fire fuel hazard. This phenomenon is often attributed to a longer interval between fires since European settlement, but may also be influenced by tree removal during the same period. We hypothesised that the number of mature trees in a stand reduces mid-storey vegetation cover and the associated fire fuel hazard through competition. To test this hypothesis, we examined associations between mid-storey cover and fire fuel hazard and the mean diameter of trees within stands of open forest and woodland in south-eastern Australia, a region prone to wildfires. We found that vegetation cover between 2 and 4 m and 4 and 6 m above the ground and two measures of fire fuel hazard were negatively associated with the quadratic mean tree diameter. Our results suggested that the removal of mature trees since European settlement may have triggered tree and shrub regeneration, resulting in higher mid-storey cover and fire fuel hazard. Thus, managing stands for the persistence and replacement of mature trees may contribute to long-term fuel reduction in Australian forests and woodlands.

Plant responses to fire are variable between and within species and are influenced by numerous factors including fire severity. This study investigated the effects of fire severity on the regeneration and recruitment of forest eucalypts in the Cotter River Catchment, Australian Capital Territory (ACT). This study also examined the potential for the obligate seeder Eucalyptus delegatensis R.T. Baker (Myrtaceae) to expand into adjacent stands dominated by the facultative resprouter Eucalyptus fastigata H. Deane & Maiden (Myrtaceae) by seed shed and seedling establishment beyond the pre-fire boundary. Sites were located in areas of either higher or lower fire severity, and transects were placed across the boundary of stands of E. delegatensis and E. fastigata. Species distributions, tree survival and seedling densities and heights were recorded, and the location of each boundary was determined as the region of maximum change in species composition along the transects. Eucalyptus delegatensis was the only eucalypt killed by higher severity fire. However, E. delegatensis seedling density was greater at higher severity sites than lower severity sites. Eucalyptus fastigata seedling density was low across all sites, with other eucalypts producing few, if any, seedlings. There was no evidence that E. delegatensis had increased its range into downslope stands dominated by E. fastigata. Patterns of vegetative recovery and seedling recruitment may be related to a number of factors, including differences in allocation patterns between seeders and sprouters, and the effects of overstory and understory competition. It is unclear what processes impede E. delegatensis seedling establishment beyond the stand boundary, but may involve an inability of E. delegatensis to shed seed sufficiently far downslope; unsuitable conditions for germination beyond the boundary; or, competition from a retained or resprouting overstory, despite the potential for increased dispersal distance soon after fire.

Summary A range of research priorities arising from the 2002–2003 bushfire season in south-eastern Australia are presented. Research imperatives relate to questions about the ignition of fires, the spread of fires in landscapes, the impact on ecosystems, and about managing bushfire risk in a changing world. Research leading to improved understanding of spatial patterns of lightning-fire ignitions will lead to increased efficiency and effectiveness of prescribed burning programs. Similarly, analysis of initial fire-attack success under severe drought conditions may result in improved management of fire ignitions. Models of fire spread that are effective in the domain of severe fire weather are lacking and research into improving fire models is suggested. There is also a need for analysis and simulation of the effectiveness of programs of prescribed burning in reducing bushfire risk at the landscape scale. Related to this is the need for resolving long-lasting and contentious debates about the nature of fir...