Influence of fuel structure derived from terrestrial laser scanning (TLS) on wildfire severity in logged forests.

CONTEXT: Logging and wildfire can reduce the height of the forest canopy and the distance to the understorey vegetation below. These conditions may increase the likelihood of high severity wildfire (canopy scorch or consumption), which may explain the greater prevalence of high severity wildfire in some recently logged or burnt forests. However, the effects of these structural characteristics on wildfire severity have not clearly been demonstrated. OBJECTIVES: We aimed to assess how the structure of forests affected by logging and wildfire influence the probability of high severity wildfire. METHODS: We used terrestrial laser scanning to measure the connectivity of canopy and understorey vegetation in forests at various stages of recovery after logging and wildfire (approximately 0-80 years since disturbance). These sites were subsequently burnt by mixed severity wildfire during the 2019-20 'Black Summer' fire season in south-eastern Australia. We assessed how these forest structure metrics affected the probability of high severity wildfire. RESULTS: The probability of high severity fire decreased as the canopy base height increased, and the distance between the canopy base and understorey increased. High severity wildfire was less likely in forests with taller understoreys and greater canopy or understorey cover, but these effects were not considered causal. Fire weather was the strongest driver of wildfire severity, which was also affected by topography. CONCLUSIONS: These findings demonstrate a link between forest structure characteristics, that are strongly shaped by antecedent logging and fire, and fire severity. They also indicate that vertical fuel structure should be incorporated into assessments of fire risk.

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.

Limits to post-fire vegetation recovery under climate change.

Record-breaking fire seasons in many regions across the globe raise important questions about plant community responses to shifting fire regimes (i.e., changing fire frequency, severity and seasonality). Here, we examine the impacts of climate-driven shifts in fire regimes on vegetation communities, and likely responses to fire coinciding with severe drought, heatwaves and/or insect outbreaks. We present scenario-based conceptual models on how overlapping disturbance events and shifting fire regimes interact differently to limit post-fire resprouting and recruitment capacity. We demonstrate that, although many communities will remain resilient to changing fire regimes in the short-term, longer-term changes to vegetation structure, demography and species composition are likely, with a range of subsequent effects on ecosystem function. Resprouting species are likely to be most resilient to changing fire regimes. However, even these species are susceptible if exposed to repeated short-interval fire in combination with other stressors. Post-fire recruitment is highly vulnerable to increased fire frequency, particularly as climatic limitations on propagule availability intensify. Prediction of community responses to fire under climate change will be greatly improved by addressing knowledge gaps on how overlapping disturbances and climate change-induced shifts in fire regime affect post-fire resprouting, recruitment, growth rates, and species-level adaptation capacity.

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.

Aboveground forest carbon shows different responses to fire frequency in harvested and unharvested forests.

Sequestration of carbon in forest ecosystems has been identified as an effective strategy to help mitigate the effects of global climate change. Prescribed burning and timber harvesting are two common, co-occurring, forest management practices that may alter forest carbon pools. Prescribed burning for forest management, such as wildfire risk reduction, may shorten inter-fire intervals and potentially reduce carbon stocks. Timber harvesting may further increase the susceptibility of forest carbon to losses in response to frequent burning regimes by redistributing carbon stocks from the live pools into the dead pools, causing mechanical damage to retained trees and shifting the demography of tree communities. We used a 27-yr experiment in a temperate eucalypt forest to examine the effect of prescribed burning frequency and timber harvesting on aboveground carbon (AGC). Total AGC was reduced by ~23% on harvested plots when fire frequency increased from zero to seven fires, but was not affected by fire frequency on unharvested plots. The reduction in total AGC associated with increasing fire frequency on harvested plots was driven by declines in large coarse woody debris (≥10 cm diameter) and large trees (≥20 cm diameter). Small tree (<20 cm DBH) AGC increased with fire frequency on harvested plots, but decreased on unharvested plots. Carbon in dead standing trees decreased with increasing fire frequency on unharvested plots, but was unaffected on harvested plots. Small coarse woody debris (<10 cm diameter) was largely unaffected by fire frequency and harvesting. Total AGC on harvested plots was between 67% and 82% of that on unharvested plots, depending on burning treatment. Our results suggest that AGC in historically harvested forests may be susceptible to declines in response to increases in prescribed burning frequency. Consideration of historic harvesting will be important in understanding the effect of prescribed burning programs on forest carbon budgets.

The influence of planting size and configuration on landscape fire risk.

Revegetating cleared land with native trees and shrubs is increasingly used as a means of addressing loss of biodiversity, degraded soil and water resources and sequestration of carbon. However, revegetation also brings a potential to alter fire risk due to changing fuel types across the landscape. Previous research has found that increasing the area of revegetation does not increase the risk of fire at a landscape scale, but it remains unclear whether the design of revegetation can be optimised to minimise risk. We evaluated if size and arrangement of revegetation affects fire size and intensity within an agricultural setting using a simulation modelling approach. Three revegetation planting designs were assessed, including small (3.2 ha) dispersed plantings, small (3.2 ha) plantings clustered into one third of the landscape, and large (29.2 ha) dispersed plantings, all resulting in the same overall percentage of revegetation (approximately 10% of the landscape). We simulated fires using Phoenix Rapidfire under varying planting design, weather, surrounding pasture conditions, and fire suppression. Planting design had little effect on fire sizes across the landscape, with larger plantings resulting in slightly larger fire sizes. Fires were smaller in landscapes with all planting designs compared with current landscape patterns. There was no significant influence of planting design on fire intensity. Weather and suppression had the strongest influence on both fire size and intensity, with larger and more intense fires under extreme weather conditions, with higher adjacent pasture loads and with no simulated suppression. Management of fuel loads in the pasture surrounding revegetation, weather and suppression are far greater risk factors for fire in these landscapes than planting design.

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.

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.

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.

The drivers of wildfire enlargement do not exhibit scale thresholds in southeastern Australian forests.

Wildfires are complex adaptive systems, and have been hypothesized to exhibit scale-dependent transitions in the drivers of fire spread. Among other things, this makes the prediction of final fire size from conditions at the ignition difficult. We test this hypothesis by conducting a multi-scale statistical modelling of the factors determining whether fires reached 10 ha, then 100 ha then 1000 ha and the final size of fires >1000 ha. At each stage, the predictors were measures of weather, fuels, topography and fire suppression. The objectives were to identify differences among the models indicative of scale transitions, assess the accuracy of the multi-step method for predicting fire size (compared to predicting final size from initial conditions) and to quantify the importance of the predictors. The data were 1116 fires that occurred in the eucalypt forests of New South Wales between 1985 and 2010. The models were similar at the different scales, though there were subtle differences. For example, the presence of roads affected whether fires reached 10 ha but not larger scales. Weather was the most important predictor overall, though fuel load, topography and ease of suppression all showed effects. Overall, there was no evidence that fires have scale-dependent transitions in behaviour. The models had a predictive accuracy of 73%, 66%, 72% and 53% accuracy at 10 ha, 100 ha, 1000 ha and final size scales. When these steps were combined, the overall accuracy for predicting the size of fires was 62%, while the accuracy of the one step model was only 20%. Thus, the multi-scale approach was an improvement on the single scale approach, even though the predictive accuracy was probably insufficient for use as an operational tool. The analysis has also provided further evidence of the important role of weather, compared to fuel, suppression and topography in driving fire behaviour.

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.

Divergent responses of fire to recent warming and drying across south-eastern Australia.

The response of fire to climate change may vary across fuel types characteristic of differing vegetation types (i.e. litter vs. grass). Models of fire under climatic change capture these differing potential responses to varying degrees. Across south-eastern Australia, an elevation in the severity of weather conditions conducive to fire has been measured in recent decades. We examined trends in area burned (1975-2009) to determine if a corresponding increase in fire had occurred across the diverse range of ecosystems found in this part of the continent. We predicted that an increase in fire, due to climatic warming and drying, was more likely to have occurred in moist, temperate forests near the coast than in arid and semiarid woodlands of the interior, due to inherent contrasts in the respective dominant fuel types (woody litter vs. herbaceous fuels). Significant warming (i.e. increased temperature and number of hot days) and drying (i.e. negative precipitation anomaly, number of days with low humidity) occurred across most of the 32 Bioregions examined. The results were mostly consistent with predictions, with an increase in area burned in seven of eight forest Bioregions, whereas area burned either declined (two) or did not change significantly (nine) in drier woodland Bioregions. In 12 woodland Bioregions, data were insufficient for analysis of temporal trends in fire. Increases in fire attributable mostly to warming or drying were confined to three Bioregions. In the remainder, such increases were mostly unrelated to warming or drying trends and therefore may be due to other climate effects not explored (e.g. lightning ignitions) or possible anthropogenic influences. Projections of future fire must therefore not only account for responses of different fuel systems to climatic change but also the wider range of ecological and human effects on interactions between fire and vegetation.

Globe-LFMC 2.0, an enhanced and updated dataset for live fuel moisture content research.

Globe-LFMC 2.0, an updated version of Globe-LFMC, is a comprehensive dataset of over 280,000 Live Fuel Moisture Content (LFMC) measurements. These measurements were gathered through field campaigns conducted in 15 countries spanning 47 years. In contrast to its prior version, Globe-LFMC 2.0 incorporates over 120,000 additional data entries, introduces more than 800 new sampling sites, and comprises LFMC values obtained from samples collected until the calendar year 2023. Each entry within the dataset provides essential information, including date, geographical coordinates, plant species, functional type, and, where available, topographical details. Moreover, the dataset encompasses insights into the sampling and weighing procedures, as well as information about land cover type and meteorological conditions at the time and location of each sampling event. Globe-LFMC 2.0 can facilitate advanced LFMC research, supporting studies on wildfire behaviour, physiological traits, ecological dynamics, and land surface modelling, whether remote sensing-based or otherwise. This dataset represents a valuable resource for researchers exploring the diverse LFMC aspects, contributing to the broader field of environmental and ecological research.

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.

The impact of antecedent fire area on burned area in southern California coastal ecosystems.

Frequent wildfire disasters in southern California highlight the need for risk reduction strategies for the region, of which fuel reduction via prescribed burning is one option. However, there is no consensus about the effectiveness of prescribed fire in reducing the area of wildfire. Here, we use 29 years of historical fire mapping to quantify the relationship between annual wildfire area and antecedent fire area in predominantly shrub and grassland fuels in seven southern California counties, controlling for annual variation in weather patterns. This method has been used elsewhere to measure leverage: the reduction in wildfire area resulting from one unit of prescribed fire treatment. We found little evidence for a leverage effect (leverage = zero). Specifically our results showed no evidence that wildfire area was negatively influenced by previous fires, and only weak relationships with weather variables rainfall and Santa Ana wind occurrences, which were variables included to control for inter-annual variation. We conclude that this is because only 2% of the vegetation burns each year and so wildfires rarely encounter burned patches and chaparral shrublands can carry a fire within 1 or 2 years after previous fire. Prescribed burning is unlikely to have much influence on fire regimes in this area, though targeted treatment at the urban interface may be effective at providing defensible space for protecting assets. These results fit an emerging global model of fire leverage which position California at the bottom end of a continuum, with tropical savannas at the top (leverage = 1: direct replacement of wildfire by prescribed fire) and Australian eucalypt forests in the middle (leverage ~ 0.25).