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Extreme fire seasons characterised by very large ‘mega-fires’ have demonstrably increased area burnt across forested regions globally. However, the effect of extreme fire seasons on fire severity, a measure of fire impacts on ecosystems, remains unclear. Very large wildfires burnt an unprecedented area of temperate forest, woodland and shrubland across south-eastern Australia in 2019/2020, providing an opportunity to examine the impact of extreme fires on fire severity patterns. We developed an atlas of wildfire severity across south-eastern Australia between 1988 and 2020 to test (a) whether the 2019/2020 fire season was more severe than previous fire seasons, and (b) if the proportion of high-severity fire within the burn extent (HSp) increases with wildfire size and annual area burnt. We demonstrate that the 2019/2020 wildfires in south-eastern Australia were generally greater in extent but not proportionally more severe than previous fires, owing to constant scaling between HSp and annual fire extent across the dominant dry-forest communities. However, HSp did increase with increasing annual fire extent across wet-forests and the less-common rainforest and woodland communities. The absolute area of high-severity fire in 2019/2020 (∼1.8 M ha) was larger than previously seen, accounting for ∼44% of the area burnt by high-severity fire over the past 33 years. Our results demonstrate that extreme fire seasons are a rare but defining feature of fire regimes across forested regions, owing to the disproportionate influence of mega-fires on area burnt.

Aim Megafires are increasing in intensity and frequency globally. The impacts of megafires on biodiversity can be severe, so conservation managers must be able to respond rapidly to quantify their impacts, initiate recovery efforts and consider conservation options within and beyond the burned extent. We outline a framework that can be used to guide conservation responses to megafires, using the 1.5 million hectare 2019/2020 megafires in Victoria, Australia, as a case study. Location Victoria, Australia. Methods Our framework uses a suite of decision support tools, including species attribute databases, ~4,200 species distribution models and a spatially explicit conservation action planning tool to quantify the potential effects of megafires on biodiversity, and identify species‐specific and landscape‐scale conservation actions that can assist recovery. Results Our approach identified 346 species in Victoria that had >40% of their modelled habitat affected by the megafire, including 45 threatened species, and 102 species with >40% of their modelled habitat affected by high severity fire. We then identified 21 candidate recovery actions that are expected to assist the recovery of biodiversity. For relevant landscape‐scale actions, we identified locations within and adjacent to the megafire extent that are expected to deliver cost‐effective conservation gains. Main conclusion The 2019/2020 megafires in south‐eastern Australia affected the habitat of many species and plant communities. Our framework identified a range of single‐species (e.g., supplementary feeding, translocation) and landscape‐scale actions (e.g., protection of refuges, invasive species management) that can help biodiversity recover from megafires. Conservation managers will be increasingly required to rapidly identify conservation actions that can help species recover from megafires, especially under a changing climate. Our approach brings together commonly used datasets (e.g., species distribution maps, trait databases, fire severity mapping) to help guide conservation responses and can be used to help biodiversity recover from future megafires across the world.

Satellite-derived spectral indices such as the relativized burn ratio (RBR) allow fire severity maps to be produced in a relatively straightforward manner across multiple fires and broad spatial extents. These indices often have strong relationships with field-based measurements of fire severity, thereby justifying their widespread use in management and science. However, satellite-derived spectral indices have been criticized because their non-standardized units render them difficult to interpret relative to on-the-ground fire effects. In this study, we built a Random Forest model describing a field-based measure of fire severity, the composite burn index (CBI), as a function of multiple spectral indices, a variable representing spatial variability in climate, and latitude. CBI data primarily representing forested vegetation from 263 fires (8075 plots) across the United States and Canada were used to build the model. Overall, the model performed well, with a cross-validated R2 of 0.72, though there was spatial variability in model performance. The model we produced allows for the direct mapping of CBI, which is more interpretable compared to spectral indices. Moreover, because the model and all spectral explanatory variables were produced in Google Earth Engine, predicting and mapping of CBI can realistically be undertaken on hundreds to thousands of fires. We provide all necessary code to execute the model and produce maps of CBI in Earth Engine. This study and its products will be extremely useful to managers and scientists in North America who wish to map fire effects over large landscapes or regions.

Wildfire occurrence and severity are projected to increase in response to anthropogenic climate change, leading to fire regimes that may exceed the limits of tolerance for some species. Plants capable of regenerating from aerial shoots following high intensity fires, termed ‘epicormic resprouters’, are assumed to be resilient to changes in fire regimes. However, empirical tests of the response of epicormic resprouters to extreme fire regimes, such as repeated canopy fires at short intervals, are currently lacking. This study examined the effect of combinations of understorey fire and canopy fire across two successive wildfires (2007, 2013) on the resilience of eucalypts that resprout epicormically. The study took place in a temperate eucalypt forest in south eastern Australia. Measures used to infer community resilience included stem topkill and damage, and seedling recruitment. It was predicted that: (a) stems will exhibit lower resistance (i.e. increased topkill and damage) to canopy fire than understorey fire; (b) recruitment will be higher following canopy fire than understorey fire; (c) prior exposure to canopy fire will reduce stem resistance and recruitment in response to subsequent wildfires; and (d) stem resistance will vary depending on bark traits. Topkill of saplings and small stems (<30 cm diameter at breast height) was higher in sites that recently (i.e. 2013) experienced canopy fire as opposed to understorey fire. Recent fire severity had no effect on topkill of large trees. Tree species with dense bark on the main stem and larger branches were less prone to topkill or partial stem and branch mortality than species with fibrous bark or exposed branches. Seedling recruitment was greater following canopy fire than understorey fire. Exposure to past canopy fire (i.e. in 2007) did not decrease stem resistance or recruitment. Synthesis. The results of this study suggest that communities of eucalypts that can resprout epicormically following fire will experience demographic shifts following repeated canopy fires. However, given the high resistance of large trees and rapid post‐fire recovery of the seedbank, ecosystem conversion appears unlikely. The findings support the presumption that forest communities of epicormic resprouters are highly resilient to shifts in fire regimes. Communities of eucalypts that can resprout epicormically show resilience to biome change following repeated canopy fires, owing to the resistance of large trees and rapid post‐fire recovery of the seedbank. However, repeated canopy fires will change forest structure by increasing stem and branch mortality, leading to reduced stocking of small trees and lowering of the canopy.

A woman, aged 35 years, presented with new symptoms of sudden onset left lower limb paraesthesia (without sensory loss), gait abnormalities and escaLating fatigue. Over several days, the paraesthesia had fluctuated with overall progression in a non-continuous fashion, and her gait had changed, with knee buckling and a tendency to limp on the left leg. These new symptoms were in the context of a previous diagnosis of a clinically isolated syndrome, defined as a single episode of demyelination, similar to that which can be seen in multiple sclerosis (MS), but which does not yet meet full criteria for MS. This was characterised by one episode of left-sided optic neuritis 12 months prior, with work-up at that time revealing a single unmatched oligoclonal band and magnetic resonance imaging (MRI) showing non-specific white matter abnormalities. On examination, the demonstrated gait was variable, alternating between left-sided antalgic limping and left-leg dragging with knee buckling. She could complete tandem gait with some mild unsteadiness but without overbalancing and she was able to hop on either leg. There was give-way weakness (initial resistance followed by sudden loss of strength) throughout the left upper and lower limb when testing power with intermittent bursts of normal power. Hoover's sign (resolution of hip extensor weakness on contralateral hip flexion against resistance) was positive. The remainder of the limb neurological examination, including tone, coordination, reflexes and sensory testing, was normal.

Chatbots are increasingly being applied in the context of health care, providing access to services when there are constraints on human resources. Simple, rule-based chatbots are suited to high-volume, repetitive tasks and can therefore be used effectively in providing users with important health information. In this Viewpoint paper, we report on the implementation of a chatbot service called Ask Anxia as part of a wider provision of information and support services offered by the UK national charity, Anxiety UK. We reflect on the changes made to the chatbot over the course of approximately 18 months as the Anxiety UK team monitored its performance and responded to recurrent themes in user queries by developing further information and services. We demonstrate how corpus linguistics can contribute to the evaluation of user queries and the optimization of responses. On the basis of these observations of how Anxiety UK has developed its own chatbot service, we offer recommendations for organizations looking to add automated conversational interfaces to their services.

The 2019–20 Australian fire season was heralded as emblematic of the catastrophic harm wrought by climate change. Similarly extreme wildfire seasons have occurred across the globe in recent years. Here, we apply a pyrogeographic lens to the recent Australian fires to examine the range of causes, impacts and responses. We find that the extensive area burnt was due to extreme climatic circumstances. However, antecedent hazard reduction burns (prescribed burns with the aim of reducing fuel loads) were effective in reducing fire severity and house loss, but their effectiveness declined under extreme weather conditions. Impacts were disproportionately borne by socially disadvantaged regional communities. Urban populations were also impacted through prolonged smoke exposure. The fires produced large carbon emissions, burnt fire-sensitive ecosystems and exposed large areas to the risk of biodiversity decline by being too frequently burnt in the future. We argue that the rate of change in fire risk delivered by climate change is outstripping the capacity of our ecological and social systems to adapt. A multi-lateral approach is required to mitigate future fire risk, with an emphasis on reducing the vulnerability of people through a reinvigoration of community-level capacity for targeted actions to complement mainstream fire management capacity.

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.

In fire-prone forests of south-east Australia, rainforests have longer fire-return-intervals than the dominant and adjoining eucalypt forests, because rainforests occur in topographic positions which are typically too wet to burn. Thus, rainforests often act as natural barriers to fire spread. Although rare, severe drought can make rainforests available to burn, and this can promote very large and intense wildfires by increasing fuel availability across landscapes. Here, we explore how ten fuel moisture indices impact wildfire occurrence in rainforest patches of south-east Australia, when compared with wet and dry sclerophyll eucalypt forest types which are drier and have shorter fire-return-intervals. Vapour pressure deficit was the strongest and most ubiquitous moisture index predicting wildfire occurrence across all forest types, followed by soil moisture and live fuel moisture. Vapour pressure deficit thresholds facilitating a wildfire probability >0.5 also did not differ between forest types. However, the percentage of days exceeding vapour pressure deficit thresholds increased from rainforests to wet eucalypt forests and peaked in dry eucalypt forests. Collectively, our results suggest that the same fuel moisture thresholds promote wildfire in rainforests and fire-prone eucalypt forests; however, wildfire is less common in rainforests because they experience less time in a dry combustible state. Our results provide a framework to forecast wildfire probability across wet and dry forests at large spatial scales.

Certain crops depend upon pollination services for fruit set, and, of these, almonds are of high value for Australia. Stressors, such as diseases, parasites, pesticides, and nutrition, can contribute to honey bee Apis mellifera L. colony decline, thereby reducing bee activity and pollination efficiency. In Australia, field studies are required to monitor honey bee health and to ascertain whether factors associated with colony decline are impacting hives. We monitored honey bee colonies during and after pollination services of almond. Video surveillance technology was used to quantify bee activity, and bee-collected pollen was periodically tested for pesticide residues. Plant species diversity was also assessed using DNA metabarcoding of the pollen. Results showed that bee activity increased in almond but not in bushland. Residues detected included four fungicides, although the quantities were of low risk of oral toxicity to bees. Floral diversity was lower in the pollen collected by bees from almonds compared to bushland. However, diversity was higher at the onset and conclusion of the almond bloom, suggesting that bees foraged more widely when availability was low. Our findings suggest that commercial almond orchards may sustain healthier bee colonies compared to bushland in early spring, although the magnitude of the benefit is likely landscape-dependent.