The severity and extent of the Australia 2019-20 Eucalyptus forest fires are not the legacy of forest management.

The 2019-20 wildfires in eastern Australia presented a globally important opportunity to evaluate the respective roles of climatic drivers and natural and anthropogenic disturbances in causing high-severity fires. Here, we show the overwhelming dominance of fire weather in causing complete scorch or consumption of forest canopies in natural and plantation forests in three regions across the geographic range of these fires. Sampling 32% (2.35 Mha) of the area burnt we found that >44% of the native forests suffered severe canopy damage. Past logging and wildfire disturbance in natural forests had a very low effect on severe canopy damage, reflecting the limited extent logged in the last 25 years (4.5% in eastern Victoria, 5.3% in southern New South Wales (NSW) and 7.8% in northern NSW). The most important variables determining severe canopy damage were broad spatial factors (mostly topographic) followed by fire weather. Timber plantations affected by fire were concentrated in NSW and 26% were burnt by the fires and >70% of the NSW plantations suffered severe canopy damage showing that this intensive means of wood production is extremely vulnerable to wildfire. The massive geographic scale and severity of these Australian fires is best explained by extrinsic factors: an historically anomalous drought coupled with strong, hot dry westerly winds that caused uninterrupted, and often dangerous, fire weather over the entire fire season.

Experiments on the influence of spot fire and topography interaction on fire rate of spread.

Spotting is thought to increase wildfire rate of spread (ROS) and in some cases become the main mechanism for spread. The role of spotting in wildfire spread is controlled by many factors including fire intensity, number of and distance between spot fires, weather, fuel characteristics and topography. Through a set of 30 laboratory fire experiments on a 3 m x 4 m fuel bed, subject to air flow, we explored the influence of manually ignited spot fires (0, 1 or 2), the presence or absence of a model hill and their interaction on combined fire ROS (i.e. ROS incorporating main fire and merged spot fires). During experiments conducted on a flat fuel bed, spot fires (whether 1 or 2) had only a small influence on combined ROS. Slowest combined ROS was recorded when a hill was present and no spot fires were ignited, because the fires crept very slowly downslope and downwind of the hill. This was up to, depending on measurement interval, 5 times slower than ROS in the flat fuel bed experiments. However, ignition of 1 or 2 spot fires (with hill present) greatly increased combined ROS to similar levels as those recorded in the flat fuel bed experiments (depending on spread interval). The effect was strongest on the head fire, where spot fires merged directly with the main fire, but significant increases in off-centre ROS were also detected. Our findings suggest that under certain topographic conditions, spot fires can allow a fire to overcome the low spread potential of downslopes. Current models may underestimate wildfire ROS and fire arrival time in hilly terrain if the influence of spot fires on ROS is not incorporated into predictions.

Australian forests, megafires and the risk of dwindling carbon stocks.

Over the Austral spring and summer of 2019/20 > 7 million ha of Eucalyptus forest and woodland, including some of Australia's most carbon dense ecosystems, were burnt on the east coast of Australia. We estimated bootstrapped mean CO2 emissions of c. 0.67 Pg, with other available estimates ranging from 0.55 to 0.85 Pg. Eucalyptus forests are renowned for their ability to resist and recover from wildfire so it would be expected that emitted CO2 will be reabsorbed. The combination of drought and frequent fires is likely reducing the capacity to recover from the fire so future Australian forests may store less carbon. Broadscale prescribed burning is a widely promoted approach to reduce uncontrolled wildfires, yet the benefits for the management of carbon stores are controversial. Prescribed burning can reduce carbon losses from subsequent wildfire, yet the "carbon costs" of it may equal or outweigh the "carbon benefits" in reduced wildfire emissions. Likewise, mechanical thinning of vegetation to reduce fuel loads also carries heavy carbon costs with uncertain carbon benefits. Research involving empirical measurements, modelling and a mix of large-scale management intervention is urgently required to determine what interventions can maximise carbon storage in the face of climate change-driven fires.

Developing and testing models of the drivers of anthropogenic and lightning-caused wildfire ignitions in south-eastern Australia.

Considerable investments are made in managing fire risk to human assets, including a growing use of fire behaviour simulation tools to allocate expenditure. Understanding fire risk requires estimation of the likelihood of ignition, spread of the fire and impact on assets. The ability to estimate and predict risk requires both the development of ignition likelihood models and the evaluation of these models in novel environments. We developed models for natural and anthropogenic ignitions in the south-eastern Australian state of Victoria incorporating variables relating to fire weather, terrain and the built environment. Fire weather conditions had a consistently positive effect on the likelihood of ignition, although they contributed much more to lightning (57%) and power transmission (55%) ignitions than the 7 other modelled causes (8-32%). The built environment played an important role in driving anthropogenic ignitions. Housing density was the most important variable in most models and proximity to roads had a consistently positive effect. In contrast, the best model for lightning ignitions included a positive relationship with primary productivity, as represented by annual rainfall. These patterns are broadly consistent with previous ignition modelling studies. The models developed for Victoria were tested in the neighbouring fire prone states of South Australia and Tasmania. The anthropogenic ignition model performed well in South Australia (AUC = 0.969) and Tasmania (AUC = 0.848), whereas the natural ignition model only performed well in South Australia (AUC = 0.972; Tasmania AUC = 0.612). Model performance may have been impaired by much lower lightning ignition rates in South Australia and Tasmania than in Victoria. This study shows that the spatial likelihood of ignition can be reliably predicted based on readily available meteorological and biophysical data. Furthermore, the strong performance of anthropogenic and natural ignition models in novel environments suggests there are some universal drivers of ignition likelihood across south-eastern Australia.

Aboveground carbon sequestration in dry temperate forests varies with climate not fire regime.

The storage of carbon in plant tissues and debris has been proposed as a method to offset anthropogenic increases in atmospheric [CO2 ]. Temperate forests represent significant above-ground carbon (AGC) "sinks" because their relatively fast growth and slow decay rates optimise carbon assimilation. Fire is a common disturbance event in temperate forests globally that should strongly influence AGC because: discrete fires consume above-ground biomass releasing carbon to the atmosphere, and the long-term application of different fire-regimes select for specific plant communities that sequester carbon at different rates. We investigated the latter process by quantifying AGC storage at 104 sites in the Sydney Basin Bioregion, Australia, relative to differences in components of the fire regime: frequency, severity and interfire interval. To predict the potential impacts of future climate change on fire/AGC interactions, we stratified our field sites across gradients of mean annual temperature and precipitation and quantified within- and between-factor interactions between the fire and climate variables. In agreement with previous studies, large trees were the primary AGC sink, accounting for ~70% of carbon at sites. Generalised additive models showed that mean annual temperature was the strongest predictor of AGC storage, with a 54% near-linear decrease predicted across the 6.1°C temperature range experienced at sites. Mean annual precipitation, fire frequency, fire severity and interfire interval were consistently poor predictors of total above-ground storage, although there were some significant relationships with component stocks. Our results show resilience of AGC to frequent and severe wildfire and suggest temperature mediated decreases in forest carbon storage under future climate change predictions.

Understorey productivity in temperate grassy woodland responds to soil water availability but not to elevated [CO2 ].

Rising atmospheric [CO2 ] and associated climate change are expected to modify primary productivity across a range of ecosystems globally. Increasing aridity is predicted to reduce grassland productivity, although rising [CO2 ] and associated increases in plant water use efficiency may partially offset the effect of drying on growth. Difficulties arise in predicting the direction and magnitude of future changes in ecosystem productivity, due to limited field experimentation investigating climate and CO2 interactions. We use repeat near-surface digital photography to quantify the effects of water availability and experimentally manipulated elevated [CO2 ] (eCO2 ) on understorey live foliage cover and biomass over three growing seasons in a temperate grassy woodland in south-eastern Australia. We hypothesised that (i) understorey herbaceous productivity is dependent upon soil water availability, and (ii) that eCO2 will increase productivity, with greatest stimulation occurring under conditions of low water availability. Soil volumetric water content (VWC) determined foliage cover and growth rates over the length of the growing season (August to March), with low VWC (<0.1 m3  m-3 ) reducing productivity. However, eCO2 did not increase herbaceous cover and biomass over the duration of the experiment, or mitigate the effects of low water availability on understorey growth rates and cover. Our findings suggest that projected increases in aridity in temperate woodlands are likely to lead to reduced understorey productivity, with little scope for eCO2 to offset these changes.

Biophysical Mechanistic Modelling Quantifies the Effects of Plant Traits on Fire Severity: Species, Not Surface Fuel Loads, Determine Flame Dimensions in Eucalypt Forests.

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.

Resolving future fire management conflicts using multicriteria decision making.

Management strategies to reduce the risks to human life and property from wildfire commonly involve burning native vegetation. However, planned burning can conflict with other societal objectives such as human health and biodiversity conservation. These conflicts are likely to intensify as fire regimes change under future climates and as growing human populations encroach farther into fire-prone ecosystems. Decisions about managing fire risks are therefore complex and warrant more sophisticated approaches than are typically used. We applied a multicriteria decision making approach (MCDA) with the potential to improve fire management outcomes to the case of a highly populated, biodiverse, and flammable wildland-urban interface. We considered the effects of 22 planned burning options on 8 objectives: house protection, maximizing water quality, minimizing carbon emissions and impacts on human health, and minimizing declines of 5 distinct species types. The MCDA identified a small number of management options (burning forest adjacent to houses) that performed well for most objectives, but not for one species type (arboreal mammal) or for water quality. Although MCDA made the conflict between objectives explicit, resolution of the problem depended on the weighting assigned to each objective. Additive weighting of criteria traded off the arboreal mammal and water quality objectives for other objectives. Multiplicative weighting identified scenarios that avoided poor outcomes for any objective, which is important for avoiding potentially irreversible biodiversity losses. To distinguish reliably among management options, future work should focus on reducing uncertainty in outcomes across a range of objectives. Considering management actions that have more predictable outcomes than landscape fuel management will be important. We found that, where data were adequate, an MCDA can support decision making in the complex and often conflicted area of fire management.

Identifying the location of fire refuges in wet forest ecosystems.

The increasing frequency of large, high-severity fires threatens the survival of old-growth specialist fauna in fire-prone forests. Within topographically diverse montane forests, areas that experience less severe or fewer fires compared with those prevailing in the landscape may present unique resource opportunities enabling old-growth specialist fauna to survive. Statistical landscape models that identify the extent and distribution of potential fire refuges may assist land managers to incorporate these areas into relevant biodiversity conservation strategies. We used a case study in an Australian wet montane forest to establish how predictive fire simulation models can be interpreted as management tools to identify potential fire refuges. We examined the relationship between the probability of fire refuge occurrence as predicted by an existing fire refuge model and fire severity experienced during a large wildfire. We also examined the extent to which local fire severity was influenced by fire severity in the surrounding landscape. We used a combination of statistical approaches, including generalized linear modeling, variogram analysis, and receiver operating characteristics and area under the curve analysis (ROC AUC). We found that the amount of unburned habitat and the factors influencing the retention and location of fire refuges varied with fire conditions. Under extreme fire conditions, the distribution of fire refuges was limited to only extremely sheltered, fire-resistant regions of the landscape. During extreme fire conditions, fire severity patterns were largely determined by stochastic factors that could not be predicted by the model. When fire conditions were moderate, physical landscape properties appeared to mediate fire severity distribution. Our study demonstrates that land managers can employ predictive landscape fire models to identify the broader climatic and spatial domain within which fire refuges are likely to be present. It is essential that within these envelopes, forest is protected from logging, roads, and other developments so that the ecological processes related to the establishment and subsequent use of fire refuges are maintained.

Learning to coexist with wildfire.

The impacts of escalating wildfire in many regions - the lives and homes lost, the expense of suppression and the damage to ecosystem services - necessitate a more sustainable coexistence with wildfire. Climate change and continued development on fire-prone landscapes will only compound current problems. Emerging strategies for managing ecosystems and mitigating risks to human communities provide some hope, although greater recognition of their inherent variation and links is crucial. Without a more integrated framework, fire will never operate as a natural ecosystem process, and the impact on society will continue to grow. A more coordinated approach to risk management and land-use planning in these coupled systems is needed.

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

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

Structural adjustments in resprouting trees drive differences in post-fire transpiration.

Following disturbance many woody species are capable of resprouting new foliage, resulting in a reduced leaf-to-sapwood area ratio and altered canopy structure. We hypothesized that such changes would promote adjustments in leaf physiology, resulting in higher rates of transpiration per unit leaf area, consistent with the mechanistic framework proposed by Whitehead et al. (Whitehead D, Jarvis PG, Waring RH (1984) Stomatal conductance, transpiration and resistance to water uptake in a Pinus sylvestris spacing experiment. Can J For Res 14:692-700). We tested this in Eucalyptus obliqua L'Hér following a wildfire by comparing trees with unburnt canopies with trees that had been subject to 100% canopy scorch and were recovering their leaf area via resprouting. In resprouting trees, foliage was distributed along the trunk and on lateral branches, resulting in shorter hydraulic path lengths. We evaluated measurements of whole-tree transpiration and structural and physiological traits expected to drive any changes in transpiration. We used these structural and physiological measurements to parameterize the Whitehead et al. equation, and found that the expected ratio of transpiration per unit leaf area between resprouting and unburnt trees was 3.41. This is similar to the observed ratio of transpiration per unit leaf area, measured from sapflow observations, which was 2.89 (i.e., resprouting trees had 188% higher transpiration per unit leaf area). Foliage at low heights (<2 m) was found to be significantly different to foliage in the tree crown (14-18 m) in a number of traits, including higher specific leaf area, midday leaf water potential and higher rates of stomatal conductance and photosynthesis. We conclude that these post-fire adjustments in resprouting trees help to drive increased stomatal conductance and hydraulic efficiency, promoting the rapid return of tree-scale transpiration towards pre-disturbance levels. These transient patterns in canopy transpiration have important implications for modelling stand-level water fluxes in forests capable of resprouting, which is frequently done on the basis of the leaf area index.

Demographic patterns of a widespread long-lived tree are associated with rainfall and disturbances along rainfall gradients in SE Australia.

Predicting species distributions with changing climate has often relied on climatic variables, but increasingly there is recognition that disturbance regimes should also be included in distribution models. We examined how changes in rainfall and disturbances along climatic gradients determined demographic patterns in a widespread and long-lived tree species, Callitris glaucophylla in SE Australia. We examined recruitment since 1950 in relation to annual (200-600 mm) and seasonal (summer, uniform, winter) rainfall gradients, edaphic factors (topography), and disturbance regimes (vertebrate grazing [tenure and species], fire). A switch from recruitment success to failure occurred at 405 mm mean annual rainfall, coincident with a change in grazing regime. Recruitment was lowest on farms with rabbits below 405 mm rainfall (mean = 0-0.89 cohorts) and highest on less-disturbed tenures with no rabbits above 405 mm rainfall (mean = 3.25 cohorts). Moderate levels of recruitment occurred where farms had no rabbits or less disturbed tenures had rabbits above and below 405 mm rainfall (mean = 1.71-1.77 cohorts). These results show that low annual rainfall and high levels of introduced grazing has led to aging, contracting populations, while higher annual rainfall with low levels of grazing has led to younger, expanding populations. This study demonstrates how demographic patterns vary with rainfall and spatial variations in disturbances, which are linked in complex ways to climatic gradients. Predicting changes in tree distribution with climate change requires knowledge of how rainfall and key disturbances (tenure, vertebrate grazing) will shift along climatic gradients.

Defining pyromes and global syndromes of fire regimes.

Fire is a ubiquitous component of the Earth system that is poorly understood. To date, a global-scale understanding of fire is largely limited to the annual extent of burning as detected by satellites. This is problematic because fire is multidimensional, and focus on a single metric belies its complexity and importance within the Earth system. To address this, we identified five key characteristics of fire regimes--size, frequency, intensity, season, and extent--and combined new and existing global datasets to represent each. We assessed how these global fire regime characteristics are related to patterns of climate, vegetation (biomes), and human activity. Cross-correlations demonstrate that only certain combinations of fire characteristics are possible, reflecting fundamental constraints in the types of fire regimes that can exist. A Bayesian clustering algorithm identified five global syndromes of fire regimes, or pyromes. Four pyromes represent distinctions between crown, litter, and grass-fueled fires, and the relationship of these to biomes and climate are not deterministic. Pyromes were partially discriminated on the basis of available moisture and rainfall seasonality. Human impacts also affected pyromes and are globally apparent as the driver of a fifth and unique pyrome that represents human-engineered modifications to fire characteristics. Differing biomes and climates may be represented within the same pyrome, implying that pathways of change in future fire regimes in response to changes in climate and human activity may be difficult to predict.

Contrasting fire responses to climate and management: insights from two Australian ecosystems.

This study explores effects of climate change and fuel management on unplanned fire activity in ecosystems representing contrasting extremes of the moisture availability spectrum (mesic and arid). Simulation modelling examined unplanned fire activity (fire incidence and area burned, and the area burned by large fires) for alternate climate scenarios and prescribed burning levels in: (i) a cool, moist temperate forest and wet moorland ecosystem in south-west Tasmania (mesic); and (ii) a spinifex and mulga ecosystem in central Australia (arid). Contemporary fire activity in these case study systems is limited, respectively, by fuel availability and fuel amount. For future climates, unplanned fire incidence and area burned increased in the mesic landscape, but decreased in the arid landscape in accordance with predictions based on these limiting factors. Area burned by large fires (greater than the 95th percentile of historical, unplanned fire size) increased with future climates in the mesic landscape. Simulated prescribed burning was more effective in reducing unplanned fire activity in the mesic landscape. However, the inhibitory effects of prescribed burning are predicted to be outweighed by climate change in the mesic landscape, whereas in the arid landscape prescribed burning reinforced a predicted decline in fire under climate change. The potentially contrasting direction of future changes to fire will have fundamentally different consequences for biodiversity in these contrasting ecosystems, and these will need to be accommodated through contrasting, innovative management solutions.

The efficacy of fuel treatment in mitigating property loss during wildfires: Insights from analysis of the severity of the catastrophic fires in 2009 in Victoria, Australia.

Treatment of fuel (e.g. prescribed fire, logging) in fire-prone ecosystems is done to reduce risks to people and their property but effects require quantification, particularly under severe weather conditions when the destructive potential of fires on human infrastructure is maximised. We analysed the relative effects of fuel age (i.e. indicative of the effectiveness of prescribed fire) and logging on remotely sensed (SPOT imagery) severity of fires which occurred in eucalypt forests in Victoria, Australia in 2009. These fires burned under the most severe weather conditions recorded in Australia and caused large losses of life and property. Statistical models of the probability of contrasting extremes of severity (crown fire versus fire confined to the understorey) were developed based on effects of fuel age, logging, weather, topography and forest type. Weather was the primary influence on severity, though it was reduced at low fuel ages in Moderate but not Catastrophic, Very High or Low fire-weather conditions. Probability of crown fires was higher in recently logged areas than in areas logged decades before, indicating likely ineffectiveness as a fuel treatment. The results suggest that recently burnt areas (up to 5-10 years) may reduce the intensity of the fire but not sufficiently to increase the chance of effective suppression under severe weather conditions. Since house loss was most likely under these conditions (67%), effects of prescribed burning across landscapes on house loss are likely to be small when weather conditions are severe. Fuel treatments need to be located close to houses in order to effectively mitigate risk of loss.