This study examined how sleep and shift characteristics relate to brain function in wildland firefighters. Our findings showed that firefighters often experience poor sleep and long shifts, which are both associated with declines in brain function. These results highlight the importance of evidence-based fatigue management strategies to support firefighter safety and wellbeing.

How can homeowners make their gardens safer from wildfire? This study reveals that while residents recognise wildfire risks, they often overlook crucial hazards near their homes. Property-specific assessments help motivate change, but success requires balancing safety measures with homeowners' emotional connections to their gardens.

This study examines public risk perceptions following wildfires, with a focus on Bijie, China, and compares these perceptions with those from other countries. The research utilizes the ‘information-trust-confidence’ framework and surveys 408 residents in Bijie. International comparisons highlight diverse methodologies and distinct differences in risk perceptions across countries and regions.

In this paper predictive spatial models for structure loss to wildfire in Australia were presented. Structure counts, cleared land percentage, surrounding structures, terrain ruggedness and tree canopy height were used as predictors. Model outputs can be used to generate spatial predictions complementing existing fire behaviour predictions.

The study applies the MaxEnt model to map wildfire risk across Kazakhstan using machine learning and remote sensing. Environmental data from satellites were analyzed, achieving a prediction accuracy of 72%. The resulting high-resolution map identifies fire-prone areas, aiding resource allocation and strategy development for wildfire management, especially in climate-sensitive regions.

Wildfire risk is increasing owing to human actions, requiring improved fire danger models. The RISICO model, used in Italy for decades, integrates fuel characteristics and hourly outputs. Testing over 16 years shows RISICO outperforms traditional indices, enhancing spatial and temporal fire danger prediction for better wildfire management.

This article belongs to the collection: Fire Behaviour and Fuels Conference.

This study uses a large language model to analyze formal risk assessments from a census of 6630 complex wildfires in the United States. It identifies the barriers to fire spread that decision-makers write about in each assessment.

We compared models of initial attack (IA) success with and without the inclusion of spruce budworm (SBW) defoliation data. We found the fire size at IA was the most important determinant of fire containment. Despite SBW’s effects on fuels, its inclusion did not greatly improve model performance.

We examined whether the location or type of peat affected the minimum moisture needed to prevent ignition or sustained burning. Landform and physical and chemical factors were also assessed for their importance. We found peat type and moisture content were sufficient to predict whether the peat would ignite or burn.

This article belongs to the collection: Fire Behaviour and Fuels Conference.

Relationships between terpenes, FMC and flammability varied over time, patterns differing according to species, and the effect of FMC being overridden by terpenes. Species flammability could be enhanced by higher terpene concentrations outside summer, the fire season in Mediterranean regions. This should be accounted for in WUI fire prevention.

The amount of energy released by fuels is more variable than previously assumed by fire behaviour models, due to differences in fuel moisture and calorific values of species.

Northwestern Patagonia, Argentina, is witnessing accelerated changes in fire regimes. Wildfires ignited by lightning have increased 1700% over the last 70 years over four national parks. A combination of increased atmospheric instability and extreme fire weather induced by climate change, is producing unprecedentedly frequent, large and severe naturally-ignited wildfires.

Wildland firefighters face brain health risks from wildfire smoke, heat, physical strain and disrupted sleep. These hazards increase neuroinflammation, cognitive decline and mental health challenges like post-traumatic stress disorder (PTSD) and depression. Protective measures, including better gear, hydration, recovery time and mental health support, are essential. Research is needed to understand and mitigate long-term effects.

This study investigated the impact of connection methods and classification criteria of factor attributes on wildfire hazard assessment. An integrated risk framework was constructed to reveal southwestern Sichuan’s mountainous regions as critical high-risk zones influenced by hazard-vulnerability-adaptive capacity interactions, offering targeted prevention strategies.

This article belongs to the collection: Multi-scale Measurements in Support of Improved Fire, Fuel, and Smoke Models of Landscape-Level Wildland Fires.