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Fire regimes have shaped extant vegetation communities, and subsequently fuel arrays, in fire-prone landscapes. Understanding how resilient fuel arrays are to fire regime attributes will be key for future fire management actions, given global fire regime shifts. We use a network of 63-field sites across the Sydney Basin Bioregion (Australia) to quantify how fire interval (short: last three fires <10 years apart, long: last two fires >10 years apart) and severity (low: understorey canopy scorched, high: understorey and overstorey canopy scorched), impacted fuel attribute values 2.5 years after Australia's 2019–2020 Black Summer fires. Tree bark fuel hazard, herbaceous (near-surface fuels; grasses, sedges <50 cm height) fuel hazard, and ground litter (surface fuels) fuel cover and load were higher in areas burned by low- rather than high-severity fire. Conversely, midstorey (elevated fuels: shrubs, trees 50 cm–200 m in height) fuel cover and hazard were higher in areas burned by high- rather than low-severity fire. Elevated fuel cover, vertical connectivity, height and fuel hazard were also higher at long rather than short fire intervals. Our results provide strong evidence that fire regimes rearrange fuel arrays in the years following fire, which suggests that future fire regime shifts may alter fuel states, with important implications for fuel and fire management. [ABSTRACT FROM AUTHOR]

Smoke pollution from landscape fires is a major health problem, but it is difficult to predict the impact of any particular fire. For example, smoke plumes can be mapped using remote sensing, but we do not know how the smoke is distributed in the air-column. Prescribed burning involves the deliberate introduction of smoke to human communities but the amount, composition, and distribution of the pollution may be different to wildfires. We examined whether mapped plumes produced high levels of particulate pollution (PM2.5) at permanent air quality monitors and factors that influenced those levels. We mapped 1237 plumes, all those observed in 17 years of MODIS imagery over New South Wales, Australia, but this was only ~20% of known fires. Prescribed burn plumes tended to occur over more populated areas than wildfires. Only 18% of wildfire plumes and 4% of prescribed burn plumes passed over a monitor (n = 115). A minority of plumes caused a detectable increase in PM2.5: prescribed burn plumes caused an air quality exceedance for 33% of observations in the daytime and 11% at night, wildfire plumes caused exceedances for 48% and 22% of observations in the day and night-time, respectively. Thus, most plumes remained aloft (did not reach the surface). Statistical modelling revealed that wind speed, temperature, and mixing height influenced whether a plume caused an exceedance, and there was a difference between prescribed and wild fires. In particular, in wind speeds below 1 kmhr−1, exceedance was almost certain in prescribed burns. This information will be useful for planning prescribed burning, preparing warnings, and improving our ability to predict smoke impacts. [ABSTRACT FROM AUTHOR]

To address uncertainties surrounding the impacts of unprecedented 2019–20 bushfires in south‐eastern Australia, we convened a symposium on field‐measured impacts on biodiversity for the 2020 Ecological Society of Australia conference. Nine presentations covered a range of studies on plant species and communities, and reptiles and mammals. Here, we summarize the presentations and review other field studies from NSW, some of which are currently unpublished. The impacts were extensive, but results also estimated survival rate perhaps higher than first reported in the media. More than half of individual mammal, reptile and threatened rainforest trees may have survived the fire, though small populations remain very vulnerable to second fire in the near future. Comprehensive understanding of the impacts of these fires requires much more field study, and for the results to be interpreted in the context of the broader fire regime. The symposium was an important early step in that understanding. [ABSTRACT FROM AUTHOR]

Wildfires and hazard reduction burns produce smoke that contains pollutants including particulate matter. Particulate matter less than 2.5 µ m in diameter (PM 2.5) is harmful to human health, potentially causing cardiovascular and respiratory issues that can lead to premature deaths. PM 2.5 levels depend on environmental conditions, fire behaviour and smoke dispersal patterns. Fire management agencies need to understand and predict PM 2.5 levels associated with a particular fire so that pollution warnings can be sent to communities and/or hazard reduction burns can be timed to avoid the worst conditions for PM 2.5 pollution. We modelled PM 2.5 , measured at air quality stations in New South Wales (Australia) from ∼ 1400 d when individual fires were burning near air quality stations, as a function of fire and weather variables. Using Visible Infrared Imaging Radiometer Suite (VIIRS) satellite hotspots, we identified days when one fire was burning within 150 km of at least 1 of 48 air quality stations. We extracted ERA5 gridded weather data and daily active fire area estimates from the hotspots for our modelling. We created random forest models for afternoon, night and morning PM 2.5 levels to understand drivers of and predict PM 2.5. Fire area and boundary layer height were important predictors across the models, with temperature, wind speed and relative humidity also being important. There was a strong increase in PM 2.5 with decreasing distance, with a sharp increase when the fire was within 20 km. The models improve our understanding of the drivers of PM 2.5 from individual fires and demonstrate a promising approach to PM 2.5 model development. However, although the models predicted well overall, there were several large under-predictions of PM 2.5 that mean further model development would be required for the models to be deployed operationally. [ABSTRACT FROM AUTHOR]

Aim: To estimate loss of above‐ground carbon (AGC) and conversion of live carbon to dead carbon following understorey and canopy fire. Location: South‐eastern Australia. Time period: 2019–2020. Major taxa studied: Four widespread resprouting eucalypt forests. Methods: Above‐ground carbon was measured in 15 plots in each of four forest types one‐year post‐fire. We also assessed topkill, that is, trees subject to canopy loss that failed to resprout epicormically. Results: While canopy fire was associated with greater declines in AGC than understorey fire, this was only statistically significant for only one forest type, where AGC declined from 154 to 85 Mg C ha−1 following canopy fire. Significant post‐fire increases in dead AGC were observed in one forest type, where dead carbon increased from 22 to 60% after canopy fire. Topkill of trees following canopy fire (48–78% of stems) was higher than topkill after understorey fire (36–53% of stems) and in unburnt forest (12–55%). Topkill occurred primarily in small‐diameter stems. Consequently, there was no effect of fire on the proportion of dead AGC in trees, with the exception of the forest with lowest productivity (i.e., lowest biomass) and lowest annual rainfall, where dead tree carbon increased from 8% in unburnt forest to 13 and 53% after understorey and canopy fire, respectively. AGC in understorey vegetation and coarse woody debris was similar or lower in burnt compared with unburnt forest. Litter carbon was significantly lower and pyrogenic carbon significantly higher in burnt forest, with no difference between understorey and canopy fire. Main conclusions While increased fire severity was associated with increased changes to carbon stocks, there were differences among forest types. Specifically, the driest forest type had the highest rates of topkill following canopy fire. These results highlight the importance of spatial variability in fire severity and forest type in determining the effects of fire on carbon stocks. [ABSTRACT FROM AUTHOR]

Wildfires and controlled hazard reduction burns produce smoke that contains pollutants including particulate 45 matter. Particulate matter less than 2.5 μm in diameter (PM2.5) is harmful to human health, potentially causing cardiovascular and respiratory issues that can lead to premature deaths. PM2.5 levels depend on environmental conditions, fire behaviour and smoke dispersal patterns. It is important for forest-fire management agencies to understand and predict PM2.5 levels associated with a particular fire, so that pollution warnings can be sent to communities and/or hazard reduction burns can be timed to avoid the worst conditions for PM2.5 pollution. We modelled PM2.5, measured at air quality stations in NSW Australia, from 1500 historical individual fires as a function of fire and weather variables. Using VIIRS satellite hotspots, we identified days where one fire was burning within 150 km of one of 48 air quality station. We extracted ERA5 gridded weather data and fire area estimates from the hotspots for our modelling. We created random forest models for afternoon, night and morning PM2.5 to understand drivers of and predict PM2.5. Fire area and boundary layer height were important predictors across the models, with temperature, wind speed and relative humidity also important. There was a strong increase in PM2.5 modelled with decreasing distance, with a sharp increase when the fire was within 15 km. The models improve understanding of drivers of PM2.5 from individual fires and demonstrate a promising approach to PM2.5 model development. However, although the models predicted well overall, there were several large under-predictions of PM2.5 that mean further model development would be required for the models to be deployed operationally. [ABSTRACT FROM AUTHOR]

Recent landscape‐scale wildfires in eastern Australia have made apparent the need for a greater understanding of the flammability dynamics of forested ecosystems. Fire severity is a measure of the impact of a fire on vegetation, but little is known about the landscape‐scale response of the fire‐prone dry sclerophyll forests of eastern Australia to different levels of fire severity. Species in these forests have multiple responses to fire, which can be dependent on the fire severity. In this study, we aimed to determine the effect of fire severity on the vegetation structure, and therefore flammability, of these forests. We addressed two hypotheses that 1) High severity fire would result in a denser understory than low severity fire after 5 years and that 2) High severity fire would reduce the vertical separation between understory and canopy after 5 years. Field surveys of 38 forest sites with differing fire severity but standardised time since fire and forest type, in Sydney region of New South Wales, Australia, were used to test these hypotheses. We found lower canopy cover and greater understory cover (0.5–4 m height) after high severity fire compared with sites which burnt at low severity. Vertical separation was less between the canopy and understory at sites after high severity fire than after low severity fire. The greater quantity of understory fuel and greater vertical continuity in fuel structure observed suggests a potential increase in forest flammability after high severity fire compared with lower severity fires in these forest types. [ABSTRACT FROM AUTHOR]

Fire severity is the impact of a fire on the landscape, particularly the physical impact on vegetation. Previous studies have established that the severity of a fire can be influenced by the severity of previous fires. Many of these studies were conducted in mixed‐conifer forests, while little is known of this process in temperate eucalypt forests. Barker and Price in their 2018 publication ("Positive severity feedback between consecutive fires in dry eucalypt forests of southern Australia," Ecosphere 9:e02110) found that high severity fire promotes high severity fire in eucalypt forests, but how is the severity of a fire in these systems affected by the severity of two sequential previous fires? This was investigated using remotely sensed and mapped fire severity data. We found that high severity fire is more likely after at least one previous high severity fire, regardless of its position in the sequence. A sequence of low or moderate severity fire followed by low severity fire resulted in the lowest proportion of high severity in the response fire. Our results suggest that low severity fire maintains the structure of forest fuels, so flammability remains relatively constant. A single high severity fire drives change, altering the structure and flammability of the vegetation and promoting more severe fire. However, the effects were small, so a cycle of high severity fire may be easily broken due to the influence of other variables, such as weather. Repeated high severity fire may also result in a decline in the ability of plants to recover from fire, leading to a compositional and structural change and potentially reducing the flammability of a forest. [ABSTRACT FROM AUTHOR]

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. In this Invited Review, we briefly describe the geographic scale of the 2019/20 Australian Black Summer Fires and undertake a quasi‐estimate of CO2 emissions from these fires. Although it is assumed the CO2 will be reabsorbed by post‐fire regrowth, we review evidence that this may not be the case because of climate change. We consider possible management interventions to reduce carbon losses from fires and reflect on the carbon costs and benefits of these management approaches. We conclude by highlighting the need for a much better understanding of fire‐driven carbon dynamics in Australian Eucalyptus forests to underpin future management. [ABSTRACT FROM AUTHOR]

We analysed the influence of wildfire area, topography, fuel, surface weather and upper-level weather conditions on long-distance spotting during wildfires. The analysis was based on a large dataset of 338 observations, from aircraft-acquired optical line scans, of spotting wildfires in south-east Australia between 2002 and 2018. Source fire area (a measure of fire activity) was the most important predictor of maximum spotting distance and the number of long-distance spot fires produced (i.e. >500 m from a source fire). Weather (surface and upper-level), vegetation and topographic variables had important secondary effects. Spotting distance and number of long-distance spot fires increased strongly with increasing source fire area, particularly under strong winds and in areas containing dense forest and steep slopes. General vegetation descriptors better predicted spotting compared with bark hazard and presence variables, suggesting systems that measure and map bark spotting potential need improvement. The results from this study have important implications for the development of predictive spotting and wildfire behaviour models. We investigated the main drivers of spotting in wildfires by analysing infrared aerial images and environmental data for 338 spotting wildfires in south-east Australia. We found source fire area to be the most important predictor of spotting distance and number of spot fires (>500 m), with important secondary effects of fuel, weather and topography. [ABSTRACT FROM AUTHOR]

We present a method to quantify and map the probability of fires reaching the vicinity of assets in a wildfire-prone region, by extending a statistical fire spread model developed on historical fire patterns in the Sydney region, Australia. It calculates the mean probability of fire spreading along sample lines around assets, weights the probability according to ignition probability and also estimates the change in spread probability that fuel reduction in treatment blocks would achieve. We have developed an R package WildfireRisk to implement the analysis and demonstrate it with two case studies in forested eastern Australia. The probability of a fire reaching the vicinity of an asset was highest in the heavily forested parts of each case study, but when weighted for ignition probability, the high probability shifted to the wildland–urban interface. Further, when weighted by asset location, high-priority areas for treatment were in blocks next to the wildland–urban interface. This method is objective, fast and based on the behaviour of real historical fires. We recommend its use in wildfire risk planning, as an adjunct to heuristic methods and simulations. Additional functionality can be incorporated into our method, for instance via a function for building impact. We present a statistical method to quantify and map wildfire spread to assets and the reduction gained by removing fuel from treatment blocks based on fire spread patterns in historical fires. The likelihood of spread to assets was highest in areas with high forest cover, but spread reduction was highest in treatment blocks at the wildland–urban interface. [ABSTRACT FROM AUTHOR]

Fire regimes have long-term effects on ecosystems which can be subtle, requiring study at a large spatial scale and temporal scale to fully appreciate. The way in which multiple fires interact to create a fire regime is poorly understood, and the relationship between the severities of consecutive fires has not been studied in Australia. By overlaying remotely sensed severity maps, our study investigated how the severity of a fire is influenced by previous fire severity. This was done by sampling points at 500-m spacing across 53 fires in dry eucalypt forests of southeast Australia, over a range of time since fire spanning every major fire season for 30 yr. Generalized additive models were used to determine the influence of previous severity on the probability of crown fire and understory fire, controlling for differences in time since fire, topography, and weather. We found that a crown fire is more than twice as likely after a previous crown fire than previous understory fire, and understory fire is more likely after previous understory fire. Our findings are in line with the results of studies from North America and suggest that severe fire promotes further fire. This may be evidence of a runaway positive feedback, which can drive ecological change, and lead to a mosaic of divergent vegetation, but research into more than two consecutive fires is needed to explore this. Our results also suggest that a low-severity prescribed fire may be a useful management option for breaking a cycle of crown fires. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Fuel load is a primary determinant of fire spread in Australian forests. In east Australian forests, litter and canopy fuel loads and hence fire hazard are thought to be highest at and beyond steady-state fuel loads 15–20 years post-fire. Current methods used to predict fuel loads often rely on course-scale vegetation maps and simple time-since-fire relationships which mask fine-scale processes influencing fuel loads. Here we use Light Detecting and Remote Sensing technology (LiDAR) and field surveys to quantify post-fire mid-story and crown canopy fuel accumulation and fire hazard in Dry Sclerophyll Forests of the Sydney Basin (Australia) at fine spatial-scales (20 × 20 m cell resolution). Fuel cover was quantified in three strata important for crown fire propagation (0.5–4 m, 4–15 m, >15 m) over a 144 km 2 area subject to varying fire fuel ages. Our results show that 1) LiDAR provided a precise measurement of fuel cover in each strata and a less precise but still useful predictor of surface fuels, 2) cover varied greatly within a mapped vegetation class of the same fuel age, particularly for elevated fuel, 3) time-since-fire was a poor predictor of fuel cover and crown fire hazard because fuel loads important for crown fire propagation were variable over a range of fire fuel ages between 2 and 38 years post-fire, and 4) fuel loads and fire hazard can be high in the years immediately following fire. Our results show the benefits of spatially and temporally specific in situ fuel sampling methods such as LiDAR, and are widely applicable for fire management actions which aim to decrease human and environmental losses due to wildfire. [ABSTRACT FROM AUTHOR]

Wildfires can have devastating effects on life, property and the environment. Official inquiries following major damaging fires often recommend management actions to reduce the risk of future losses from wildfires. Understanding where wildfires are most likely to occur in the landscape is essential to determining where wildfires pose the greatest risk to people and property. We investigated the spatial patterns of wildfire ignitions at a bioregional scale in New South Wales and Victoria using generalised linear models. We used a combination of social and biophysical variables and examined whether different categories of ignitions respond to different explanatory variables. Human-caused ignitions are the dominant source of ignitions for wildfires in south-eastern Australia and our results showed that for such ignitions, population density was the most important variable for the spatial pattern of ignitions. In future years, more ignitions are predicted in the coastal and hinterland areas due to population increases and climate change effects. [ABSTRACT FROM AUTHOR]

Fire management attempts to coerce fire into a desired regime using three primary strategies: prescribed burning, fire suppression and ignition management. The West Arnhem Land Fire Abatement project ( WALFA), where prescribed Early Dry Season burning is used to reduce unplanned Late Dry Season burning, is heralded as model for prescribed burning. However, a previous analysis found that Late Dry Season area burnt in WALFA had been reduced further than would be expected based purely on the Early Dry Season treatment area. This study investigated whether treatment has reduced the number and size of unplanned fires. Daily burnt area mapping from MODIS satellite sensors was used to identify individual fires to compare fire activity before and after management was introduced in WALFA (2005) and in a control region in East Arnhem Land. Late Dry Season area burnt reduced after treatment in WALFA but also in the control region. The number of fires in August- October increased after treatment. There is a period from early August until late September when human ignitions can cause huge fires. Late Dry Season area burnt was strongly influenced by the size of the largest single fire and only weakly by the number of ignitions. Early Dry Season area burnt had modest effects on both the number and maximum size of Late Dry Season fires. Eliminating the largest fire in each 1600 km2 sample block would have halved the total Late Dry Season area burnt. A similar reduction could be obtained from a 14% annual treatment with Early Dry Season fire, but this may not reduce the overall area burnt. If overall fire frequency is the main threat to biodiversity in the savannas, then the best solution will be to prevent the small subset of fires that have the potential to become very large. [ABSTRACT FROM AUTHOR]

Aim To examine the potential of remotely sensed abiotic measures as surrogates for the abundance, diversity and community composition of temperate rocky reef fishes and sessile invertebrates. Location Batemans Marine Park, south-eastern Australia. Methods We used high-resolution bathymetric side-scan sonar imagery to quantify abiotic measures of rocky reef habitat, within a marine protected area ( MPA), and examine the relationship between abiotic measures and (1) sessile invertebrate abundance, (2) sessile invertebrate species richness, (3) total fish abundance, (4) fish species richness, and (5) Monacanthidae abundance using generalized additive mixed models ( GAMMs). We chose GAMMs as the preferred statistical analysis to account for the spatial autocorrelation present in our data. Results We found a strong positive relationship between abiotic measures and sessile invertebrate abundance and diversity ( r2 > 0.64). By far the most important predictor was vertical relief within a 75 m radii seascape surrounding the faunal survey. Overall, abiotic measures were poor predictors of total fish abundance ( r2 = 0.175) and fish species richness ( r2 = 0.276), with minimum adequate models producing low explanatory power. In contrast, Monacanthids exhibited a strong positive relationship with abiotic variables ( r2 = 0.385), with increased abundance associated with greater depth and distance from soft sediment. Main conclusions Remotely sensed abiotic measures are important predictors in describing the spatial patterns of sessile invertebrate abundance and diversity and Monacanthid abundance. In contrast, abiotic variables were poor predictors of total fish abundance and diversity. Habitat could be a useful cost-effective surrogate to determine areas of conservation value for certain temperate rocky reef assemblages. This information is valuable for future MPA development and design. [ABSTRACT FROM AUTHOR]

Abstract: 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. [Copyright &y& Elsevier]

Aim Fire is a key agent in savanna systems, yet the capacity to predict fine-grained population phenomena under variable fire regime conditions at landscape scales is a daunting challenge. Given mounting evidence for significant impacts of fire on vulnerable biodiversity elements in north Australian savannas over recent decades, we assess: (1) the trajectory of fire-sensitive vegetation elements within a particularly biodiverse savanna mosaic based on long-term monitoring and spatial modelling; (2) the broader implications for northern Australia; and (3) the applicability of the methodological approach to other fire-prone settings. Location Arnhem Plateau, northern Australia. Methods We apply data from long-term vegetation monitoring plots included within Kakadu National Park to derive statistical models describing the responses of structure and floristic attributes to 15 years of ambient (non-experimental) fire regime treatments. For a broader 28,000 km2 region, we apply significant models to spatial assessment of the effects of modern fire regimes (1995-2009) on diagnostic closed forest, savanna and shrubland heath attributes. Results Significant models included the effects of severe fires on large stems of the closed forest dominant Allosyncarpia ternata, stem densities of the widespread savanna coniferous obligate seeder Callitris intratropica, and fire frequency and related fire interval parameters on numbers of obligate seeder taxa characteristic of shrubland heaths. No significant relationships were observed between fire regime and eucalypt and non-eucalypt adult tree components of savanna. Spatial application of significant models illustrates that more than half of the regional closed forest perimeters, savanna and shrubland habitats experienced deleterious fire regimes over the study period, except in very dissected terrain. Main conclusions While north Australia's relatively unmodified mesic savannas may appear structurally intact and healthy, this study provides compelling evidence that fire-sensitive vegetation elements embedded within the savanna mosaic are in decline under present-day fire regimes. These observations have broader implications for analogous savanna mosaics across northern Australia, and support complementary findings of the contributory role of fire regimes in the demise of small mammal fauna. The methodological approach has application in other fire-prone settings, but is reliant on significant long-term infrastructure resourcing. [ABSTRACT FROM AUTHOR]

Planned fire is used globally to minimise the risk of unplanned fire, but it is important to measure the return for effort in terms of the reduction of risk per unit area of planned fire. Here, we use 30 years of fire mapping from four subregions of the Sydney region to compare the annual extent of unplanned fire with previous planned and unplanned fire. Using linear mixed modelling, we were able to discriminate the relative influence of previous fire, seasonal rainfall and weather during the peak fire season. The mean annual area burnt over the period was 4.11%, comprising 0.53% planned and 3.58% unplanned. We found that weather during the fire season was the most influential factor. Annual rainfall had a modest negative relationship with unplanned fire area. Past fire had some influence, but the relationship implied that approximately three units of planned fire are required to reduce the unplanned fire area by one unit. Managers would need to burn 5.4% per year to halve unplanned fire extent, a ten-fold increase on recent levels. This would increase the total area burnt, and have other effects that need to be considered (from smoke and greenhouse gas emissions, and changes to biodiversity). [ABSTRACT FROM AUTHOR]

The article presents a study which assesses the decadal responses of eucalypt-dominated savanna to close fire regimes in Australia and Africa. The study shows the mean annual frequency of plot burning at 0.53 over the study period. It illustrates the variability of species and structural responses due to stem recruitment and juvenile declines. It also demonstrates the effect of significant regional fire regime change, though it obtains undesirable structural consequences and risks.

• It is often assumed that most biomass is consumed in fire. • However, often only "fine" biomass (<6 mm diameter) is consumed. • We present allometric equations to quantify the mass of fine fuel in shrubs. • Planned burns reduced fine fuel loads, but above-ground biomass losses were small. Accurate quantification of fine fuel loads (e.g. foliage and twigs) in forests is required for many fire behaviour models, and for assessing post-fire changes in carbon stocks and modelling smoke emissions. Fine fuels burn readily and are thus often targeted for fuel load assessments. Estimates of fine live fuel loads often rely on visual assessments or utilise allometric equations that relate stem diameter of plants to total above-ground biomass. Here, we develop allometric equations for shrubs that relate stem diameter to the portion of above-ground biomass comprised of fine fuel. Our study area is within the temperate eucalypt forests of south-eastern Australia. We present equations for (i) foliage; (ii) all biomass < 3 mm diameter; (iii) all biomass < 6 mm diameter; and (iv) all above-ground biomass. Simple power-law models were developed for five shrub species and saplings of two tree species. Models combining all species (RMSE = 0.03–0.0.06) worked similarly well to species-specific models (RMSE = 0.01–0.08). We then applied these all-species combined models to field observations of shrub stem diameters, measured before and after planned burns. In unburnt forest, the proportion of shrub biomass comprised of fine fuel varied considerably (from 6 to 58%). Fine fuel loads were positively related to total above-ground biomass (R 2 = 0.75) and basal area of shrubs (R 2 = 0.79). There was considerable variation in consumption of fine fuel. The median reduction in fine fuel load was 22.4%, whereas the median reduction in total above-ground biomass was only 2.3%. Our models of shrub fine fuels can be readily applied to field-based assessments or combined with existing models or remotely sensed estimates of above-ground biomass to model fine fuel loads over large heterogeneous study areas. [ABSTRACT FROM AUTHOR]

We surveyed herbaceous biomass across the range of Eucalyptus tetrodonta savannas in north-western Australia. Sample sites ( n = 211) were stratified within four broad geographical regions characterized by different mixes of land management regimes. Grasses dominated (87% mean) the herbaceous biomass. After controlling for climatic and edaphic gradients, herbaceous biomass was highest in the Greater Darwin region (2.2 t ha−1) which is managed predominantly by Europeans, and least under semi-traditional Aboriginal management in Arnhem Land region (1.1 t ha−1). In the drier Gulf of Carpentaria and Kimberley regions, where a mix of Aboriginal, conservation and pastoral land uses occurs, fuel loads were higher than in Arnhem Land region but still considerably lower than around Darwin. Sarga was recorded in all regions except the Gulf of Carpentaria and had the highest biomass in Darwin (0.88 t ha−1) and lowest biomass in the Kimberley (0.54 t ha−1). The proportion of herbaceous biomass made up of perennial grasses was least in Darwin (17%) and greatest in the Gulf (77%) regions. We suggest that climate, soils and land management account for differences between the drier pastoral regions of the Gulf of Carpentaria and the Kimberley and the wet Greater Darwin region relative to the Arnhem Land region. The high frequency, and larger spatial scale, of fires in the Greater Darwin region relative to the Arnhem Land region underpins the contrasting trends in total herbaceous biomass and abundance of flammable annual grasses. [ABSTRACT FROM AUTHOR]

The authors discuss the use of problem-based learning (PBL) in medical education and programs in Australia, wherein students acquired knowledge in basic sciences. Topics include the integration of basic sciences in hospital clinical services, the growth of information technology in patient care models, and the concerns among students on whether their knowledge about gross anatomy is adequate for cadaver dissection and medical practice.

A letter to the editor is presented in response to the article "Reform forest fire management," coauthored by M.P. North in the September 18, 2015 issue.

The article focuses on a study that used fire history mapping derived mostly from Landsat imagery over the period 1990 -- 2009 and statistical modelling to quantify the mitigation of late dry-season wildfire through prescribed burning. From 2005, there has been a reduction in mean annual total proportion burnt and particularly of late dry-season fires.

Models that predict wildfire rate of spread (ROS) play an important role in decision-making during firefighting operations, including fire crew placement and timing of community evacuations. Here, we use a large set of remotely sensed wildfire observations, and explanatory data (focusing on weather), to demonstrate a Bayesian probabilistic ROS modelling approach. Our approach has two major advantages: (1) Using actual wildfire observations, instead of controlled fire observations, makes models developed well-suited to wildfire prediction; (2) Bayesian modelling accounts for the complex nature of wildfire spread by explicitly considering uncertainty in the data to produce probabilistic ROS predictions. We show that highly informative probabilistic predictions can be made from a simple Bayesian model containing wind speed, relative humidity and soil moisture. We provide current operational context to our work by calculating predictions from widely used deterministic ROS models in Australia. • A Bayesian approach to wildfire rate of spread modelling is demonstrated and discussed. • Bayesian statistics is shown to have several notable advantaged when applied to rate of spread modelling. • Large collection of line scans acquired by Australian firefighting agencies are used for rate of spread modelling. [ABSTRACT FROM AUTHOR]

Forest fire size, frequency and severity are increasing worldwide, with corresponding reductions in long-unburnt habitat and greater modification of forest structure over wider areas. Understanding the implications for animals is imperative in optimizing management for species persistence and overall biodiversity. We investigated how avian responses to historical high-severity fire differ in forests at short (five years) and mid-range (16 years) time since fire, including whether increased time since fire mitigates any negative responses to high-severity fire. Sites were established in fire-prone dry forests of the Greater Blue Mountains World Heritage Area, Australia. A Bayesian latent variable analysis of bird data obtained from acoustic recordings was used to estimate the occurrence of 74 species in relation to time since fire (short, mid-range), the spatial extent of historical high-severity fire (limited, extensive), and their interaction. Time since fire influenced the number of species present, but only where high-severity fire had been extensive. Here, the lowest and highest number of species in the study occurred where time since fire was short and mid-range, respectively. At least ten species responded either positively or negatively to high-severity fire, but for nine of these species the response did not change with time since fire, potentially implicating persistent effects of such fires on habitat. Six other species were unlikely to occur at short time since fire, requiring habitat at mid-range time since fire. This finding suggests that these species would benefit from strategic retention of forest with longer fire-ages under increased fire activity associated with climate change. • Positive and negative responses among species to historical high-severity fire • Species responses to high-severity fire remained the same over time since fire. • Nine percent of all species were unlikely to occur where time since fire was short. • More species at longer time since fire where high-severity fire had been extensive. [ABSTRACT FROM AUTHOR]

Smoke from Hazard Reduction Burns (HRBs) and wildfires contains pollutants that are harmful to human health. This includes particulate matter less than 2.5 μm in diameter (PM2.5), which affects human cardiovascular and respiratory systems and can lead to increased hospitalisations and premature deaths. Better models are needed to predict PM2.5 levels associated with HRBs so that agencies can properly assess smoke pollution risk and balance smoke risk with the wildfire mitigation benefits of HRBs. Given this need, our aim was to develop a probabilistic model of daily PM2.5 using Bayesian regression. We focused on the region around Sydney, Australia, which regularly has hazard reduction burning, wildfires and associated smoke. We developed two regional models (mean daily and maximum daily) from observed PM2.5, weather reanalysis and satellite fire hotspot data. The models predict that the worst PM2.5 in Sydney occurs when PM2.5 was high the previous day, there is low ventilation index (i.e. the product of wind speed and planetary boundary layer height), low temperature, west to northwest winds in the Blue Mountains, an afternoon sea breeze and large areas of HRBs are being conducted, particularly to the west and north of Sydney. A major benefit of our approach is that models are fast to run, require simple inputs and Bayesian predictions convey both predicted PM2.5 and associated prediction uncertainty. Future research could include the application of similar methods to other regions, collecting more data to improve model precision and developing Bayesian PM2.5 models for wildfires., Competing Interests: The authors have declared that no competing interests exist.

Background: To our knowledge, immediate post-operative complication rates after resection of colorectal cancer (CRC) have not been compared between public and private hospitals in the Australian health care system. We compared the frequency of surgical and medical complications between a public tertiary referral hospital and a private hospital., Methods: Data were drawn from a prospective registry of all patients having a resection for CRC between 2000 and 2010 performed by members of the Concord Hospital colorectal surgical unit, either at this hospital or at a single private hospital with which they were affiliated. Complication rates were compared after adjustment for preoperative and perioperative features by logistic regression., Results: Among the 16 surgical complications, the only significant difference after adjustment for other features was a higher rate of septicaemia in the public hospital (odds ratio (OR) 2.2, 95% confidence interval (CI) 1.1-4.6). Among the seven medical complications, the only significant differences were a higher risk of cardiac complications in patients with cardiac co-morbidity (OR 1.8, 95% CI 1.1-3.0) and of respiratory complications in patients without respiratory co-morbidity (OR 3.1, 95% CI 2.2-5.9) in the public hospital., Conclusion: In this study, where the same group of surgeons performed all reported CRC resections in the two hospitals, no independent effect of the type of hospital was found on 15 of 16 surgical complications and 5 of 7 medical complications. Type of hospital had no impact on rates of specific complications apart from septicaemia and cardiorespiratory complications, which were higher in the public hospital., (© 2014 Royal Australasian College of Surgeons.)

Background: Data from the northern hemisphere suggest that patients with ulcerative colitis (UC) have similar survival to the general population, whereas mortality in Crohn's disease (CD) is increased by up to 50%. There is a paucity of data from the southern hemisphere, especially in Australia., Methods: A prevalence cohort (1977-1992) of patients with inflammatory bowel disease (IBD) diagnosed after 1970 was studied. Survival status data and causes of death up to December 2010 were extracted from the National Death Index. Relative survival analysis was carried out separately for men and women., Results: Of 816 cases (384 men, 432 women; 373 CD, 401 UC, 42 indeterminate colitis), 211 (25.9%) had died by December 2010. Median follow-up was 22.2 years. Relative survival of all patients with IBD was not significantly different from the general population at 10, 20, and 30 years of follow-up. Separate analyses of survival in CD and UC also showed no differences from the general population. There was no difference in survival between patients diagnosed earlier (1971-1979) or later (1980-1992). At least 17% of the deaths were caused by IBD. Fatal cholangiocarcinomas were more common in IBD (P < 0.001), and fatal colorectal cancers more common in UC (P = 0.047)., Conclusions: In Australia, IBD patient survival is similar to the general population. In contrast to data from Europe and North America, survival in CD is not diminished in Australia. IBD caused direct mortality in 17%, especially as biliary and colorectal cancers are significant causes of death.

Examination of a large collection of echinothurioid echinoids from museum collections in New Zealand and Australia revealed six new species in the genus Araeosoma (A. bidentatum sp. nov., A. migratum sp. nov., A. anatirostrum sp. nov., A. tertii sp. nov., A. leppienae sp. nov., and A. bakeri sp. nov.) and one in the genus Hapalosoma (H. amynina sp. nov.), while the recorded presence of A. coriaceum in northwest New Zealand was found to be incorrect. Several of the species described are rarely collected, their distribution being strongly associated with seamount type habitat in a relatively narrow depth range. The majority of the records of these new species are from the New Zealand region, with a strong centre of diversity revealed among the seamounts of the Bay of Plenty. The new species are clearly distinguished from known forms by characters of their pedicellariae, spines, coronal plate structure, colouring, and tuberculation. A key to the Echinothuriinae of the region is included.

In 1991 this journal published the report of an international working party to the World Congress of Gastroenterology regarding the clinicopathological staging of colorectal cancer. Since that time staging has continued to evolve as further prognostic factors in colorectal cancer have been elucidated in studies of increasingly large databases in several countries. This review summarizes several of the key issues that have arisen during this evolutionary process and raises matters which still remain controversial in staging at the present time., (© 2011 Journal of Gastroenterology and Hepatology Foundation and Blackwell Publishing Asia Pty Ltd.)

Fascin, an actin-bundling protein, is expressed in many neoplasms including colorectal cancer. It is considered to be a mediator of tumor cell invasion and an indicator of aggressive phenotype; however, there are few reports on the association between fascin and prognosis in colorectal cancer. The aims of this study were to: (a) investigate the expression of fascin in the central part of the tumor and at the invasive front in patients who had a potentially curative resection for node-positive colonic carcinoma; (b) examine the method of scoring fascin expression; and (c) investigate the association between fascin expression and overall survival and other clinicopathologic features. Fascin expression was assessed by immunostaining of microarrays from archived tissue of 470 patients who were followed for a minimum of 5 years after resection. Other clinicopathologic data had been recorded prospectively according to a standardized protocol. Analysis of overall survival was by the Kaplan-Meier method and Cox regression. For both central tumor tissue and the invasive front, it was found that the percentage of stained cells was a sufficient measure of fascin expression in relation to survival, with staining intensity providing no significant additional information. At both levels, there was a significant independent association between high fascin expression and diminished survival, although this association was much stronger in the central region (adjusted hazard ratio 1.6, P<0.001) than at the invasive front (adjusted hazard ratio 1.1, P=0.044). Fascin expression predicted overall survival but did not displace other routinely collected clinicopathologic predictors.

Predicting patient outcome for colorectal carcinoma (CRC) with lymph node but not distant metastases remains challenging. Various prognostic markers have been identified including microsatellite instability (MSI) and possibly expression of the MHC Class II protein, HLA-DR. About 15% of sporadic CRC exhibits MSI associated with methylation of the DNA mismatch repair gene hMLH1 promoter. In addition, a significant proportion of unselected CRC demonstrates expression of HLA-DR. We sought to examine the relationship between HLA-DR expression, MSI status and prognosis in sporadic Australian Clinicopathological (ACP) Stage C CRC. Two hundred seventy consecutive patients with sporadic ACP Stage C CRC were treated at Concord Repatriation General Hospital between 1986 and 1992. None of these patients received adjuvant chemotherapy and all were followed for a minimum of 5 years or until death. DNA was extracted from paraffin sections and MSI status determined by PCR. HLA-DR expression was determined immunohistochemically using an antibody against the HLA-DR alpha chain. MSI status could be assigned in 235 cases: 176 CRCs (74.9%) were microsatellite stable, whereas 23 (9.8%) had high levels of MSI (MSI-H) and 36 (15.3%) had low levels of MSI (MSI-L). HLA-DR expression by CRC cells was seen in 148 (60.1%) cases and correlated with the presence of tumor-infiltrating lymphocytes (p = 0.0005) and peritumoral lymphocytes (p = 0.003), but not other clinicopathological features or MSI status. HLA-DR-positive CRCs were strongly associated with better patient outcome (p < 0.0001)., (2009 UICC.)