Fire shapes the biodiversity of tropical savannas, yet challenges exist in accessing and interpreting the breadth of fire-ecology evidence to support appropriate management. We compiled a comprehensive fire–biodiversity database for Australian tropical savannas to improve knowledge discovery and support the iterative development of fire-management principles. Using systematic thematic synthesis, we mapped evidence on fire–biodiversity relationships across contemporary science and Traditional Knowledge (TK). Publication metadata were extracted, standardised and classified using a large language model (LLM)-assisted workflow, then manually reviewed and cross-validated against an independently curated subset. LLM-assisted extraction performed comparably to human extraction, but only with careful parameterisation and quality control. The database spans 382 publications from the Australian savanna biome. The evidence base is dominated by terrestrial flora (≈51%) and studies of mixed-element fire regimes (≈28%), fire frequency (≈17%) and time since fire (≈17%). Partnerships with Indigenous organisations or entities were reported in ≈23% of publications, but only 22 explicitly incorporated TK or Indigenous partners as co-investigators. Evidence is geographically clustered and taxonomically uneven, revealing clear knowledge gaps. Our thematic synthesis map and accompanying database provide a platform to inform culturally grounded, evidence-based fire management and highlight future research priorities.
Background Previously published versions of the ‘Balbi model’ describing surface fire propagation consist of a set of equations based on simplified conservation laws. Their main equation calculating the fire rate of spread (ROS) relied on an iterative process to account for the effect of environmental drivers. Aims We formulated a new version of this model that considers a 3D flame front composed of peaks and troughs, integrates distinct radiation and convection heat transfer mechanisms, and outputs the physical characteristics of a flame front as they are influenced by weather, fuel and topographical conditions. A simpler operational version, composed of only one equation, is also exhibited. Methods While maintaining its characteristics (physics-oriented, fully predictive and faster than real time) from older versions, the global structure of the proposed model is changed to obtain a set of algebraic equations easy to solve and to code. Key results We described the model and provided an analysis of model response to key environmental variables. Model evaluation against independent data is provided in a companion paper. Conclusions A simplified physical propagation model for surface fires has been exhibited. Implications The algebraic nature of the model’s equations makes it suitable to incorporate into fire management decision-making tools to support suppression activities.
Background Smoldering in forest litters is prone to transition to flaming under dry and windy conditions. Most studies focus on smoldering-to-flaming (StF) transition under steady wind conditions, however, a knowledge gap persists regarding periodic wind oscillations in wildfires. Aims This study aims to elucidate the effects of unsteady wind on the StF transition in moist pine needle beds (PNBs), focusing on moisture content (MC), maximum wind speed, wind frequency and direction. Methods Laboratory-scale experiments combined with Fast Fourier Transform (FFT) technique and theoretical analysis were conducted. Key results Higher wind frequencies reduced the peak smoldering temperatures and lateral spread rate, delaying the StF transition. Theoretical analysis derived that the pressure penetration depth is inversely proportional to the square root of the frequency (i.e. δp∝f−1/2), indicating shallower gas penetration at higher frequencies. This limits oxygen transport to deeper char layers, suppressing deep-seated char oxidation . Conversely, the predicted gas penetration velocity increased with wind frequency (i.e. uy(t)=−φπfκP∞μ(1−1e)ηρ∞U0Asin(2πft+ϕ)), enhancing surface convective cooling. Conclusions The dual mechanism of suppressed deep-seated char oxidation and intensified surface cooling impeded the necessary heat accumulation for the StF transition, explaining the observed StF transition delay under high-frequency wind conditions. Implications This work advances the fundamental understanding of the StF transition behavior in unsteady wind fields closely linked to realistic wildfire scenarios.
Background The ‘Balbi model’ is a simplified physical model for surface fires which provides the main physical characteristics of a fire front and its rate of spread (ROS) as a function of general environmental conditions. In the first part of this work, we describe a simplification of this model, which we call Balbi operational model, that leads to a set of explicit algebraic equations. Aims After calibrating the model, we aim to assess its performance by comparing the predicted ROS with laboratory- and field-measured ROS. Methods A small set (n = 40) of laboratory fires was used to find the required model parameters. We evaluated the model against (1) a set of laboratory experimental fires (n = 549), representing a range of fuel bed types and arrangements, and (2) a set of shrubland and grassland field fires (n = 357) from different world regions. We assessed the predictive capacity of the model and compared it with other empirical and semi-empirical models. An analysis on the importance of each heat transfer mechanism is performed. Key results The proposed model performs as well as its previous iteration on shrubland fires and is found to increase accuracy when tested against grassland fires. Conclusions The operational ‘Balbi model’ shares many properties with empirical models, while grounded on physical heat transfer principles. The model is suitable for application to several types of fuels and configurations of slope and wind. Implications Its intrinsic characteristics and verified fit make it a candidate to be used in wildfire propagation simulators.
Background Regional climate controls on wildfires in China remain complex due to high spatial heterogeneity and strict suppression policies. Aims This study aims to objectively identify coherent high-activity wildfire regions in China and clarify the climatic pathways regulating wildfire activity during the fire season. Methods We applied an optimized clustering approach to MCD64A1 burned area data (2001–2024) to delineate fire regimes, and used Pearson and partial correlations to analyze regional climate-fire relationships. Key results Two representative high-activity wildfire regions were identified: the Northeast fire regime area (NFR) and the Southwest fire regime area (SFR). Burned area peaks in both regions during February–April, when soil moisture (SM) deficit acts as a proximal control. However, the climatic drivers regulating SM differ between regions. In the NFR, SM is associated with both snow cover and temperature, both governed by February–March Arctic Oscillation (AO) conditions. SM in the SFR is negatively related to temperature, which is positively associated with February–March El Niño conditions. Conclusions Winter-spring wildfires in the NFR are governed by a cryosphere–temperature pathway while in the SFR are dominated by a thermally driven pathway. Implications These distinct climate-fire linkages emphasize the importance of region-specific wildfire research under strict fire suppression policies.
Background There is interest in expanding the use of prescribed fire, but smoke management is often seen as a barrier to burning. Information about perception of prescribed fire smoke is limited. Aims This study examines perceptions of wildland fire and smoke, and willingness to minimize smoke exposure. We further investigate variations in perceptions relative to fire activity and smoke concentrations. Methods We surveyed residents of an area with regular prescribed burning to assess their opinions of fire and smoke, how they would reduce smoke exposure and the influence of prior experience with fire. We surveyed residents of an area with regular prescribed burning to assess their opinions of fire and smoke, how they would reduce smoke exposure and the influence of prior experience with fire. Key results There is a high acceptance of prescribed fire among survey respondents. Prescribed fire smoke is perceived as a low concern and is more acceptable than smoke from other sources. The largest differences in perceptions were observed among different land types. Conclusions This study finds strong support for the use of prescribed fire among respondents. Concerns about health impacts from smoke decrease with increasing prescribed fire acceptance. Most respondents expressed a high willingness to act to reduce smoke exposure. Implications With expanding prescribed fire use, effectively communicating smoke risks will be increasingly important as public concerns, perceived vulnerability and willingness to act may not align.
Background The increase in destructive wildland–urban interface (WUI) fires necessitates improved risk assessment methods for communities. Specifically, there is a need to quantify the impact of fire conditions on structures. Aim We present a framework to develop fragility functions that express the probability of structure destruction considering damageability, given exposure to fire hazard. Methods Lacking field measurements during wildfires, we simulate flame and ember conditions for the 2017 Tubbs Fire case study. Logistic regression is used to relate hazard, exposure and damage, incorporating fire modeling, property characteristics and post-fire damage data. The resulting fragility functions indicate the probability of structure destruction as hazard level increases. Key results Notably, zero simulated exposure does not equate to zero destruction chance, and maximum hazard is not 100% correlated with destruction – owing to the exclusion of structure-to-structure fire spread in simulations. Destruction probability was lower, regardless of hazard level, for structures subject to stricter building codes, greater structure separation and increased vegetation clearance. Conclusions This methodology links structure loss in the WUI to hazard exposure using landscape-scale fire modeling. Implications Though demonstrated using one event, the fragility analysis framework is broadly applicable and scalable, supporting improved understanding and mitigation of WUI fire risk.
Background Indigenous fire stewardship has historically shaped fire-adapted ecosystems across the southwestern USA. Colonial land-use practices and fire suppression disrupted these traditions, severing long-standing human–fire–land relationships. Aims This review explores how academic research has addressed Indigenous fire practices over time, with a focus on trends in disciplinary engagement, author identity and recognition of Indigenous Knowledge (IK) systems. Methods A systematic literature review was conducted using standards developed by the Collaboration for Environmental Evidence. From 1241 initial records, 113 peer-reviewed studies were selected based on relevance to Indigenous fire practices in the southwestern USA. Key results Studies increasingly incorporate IK and Indigenous-authored scholarship. Interdisciplinary approaches have grown since the 1990s, yet ecological studies remain dominant. Barriers include colonial policy legacies, limited co-management and marginalization of Indigenous worldviews. Conclusions Indigenous fire stewardship is a dynamic, site-specific practice embedded in cultural, ecological and governance systems. Recognition of these practices remains limited, even amid increasing scholarly attention. Implications Expanding Indigenous-led collaborations and reforming land governance could strengthen the resilience of landscapes and communities to fire while supporting cultural revitalization. Embedding Indigenous stewardship in land management offers a tangible path toward inclusive, adaptive fire policy.
Background Wildfires abruptly change landscapes by altering soil properties and vegetation cover. These changes are thought to reduce soil infiltration capacity, making landscapes susceptible to runoff and erosion. However, post-fire soil response is complex and likely varies across locations and time. Aims Here, we aim to understand regional post-fire soil response and recovery by tracking changes across different northern California (USA) lithology and vegetation types. Methods We conducted repeat in situ soil infiltration tests for 3 years post-fire at 31 burned and 10 unburned sites spanning the 2021 Dixie, 2020 LNU Lightning Complex, 2020 Walbridge and 2020 Glass fires. Key results Our two main findings are: (1) burned chaparral soils have increased hydraulic conductivity compared with unburned sites, and (2) infiltration rates return to pre-fire conditions within 3 years across most lithologies and vegetations. Conclusions Recovery might be generalizable by vegetation and lithology but differ regionally, making it important to identify meaningful hydrologic response units (HRUs). Multi-year studies with paired burned and unburned measurements can constrain the recovery timeline and provide information missed by observations solely of burned soils. Implications Understanding where, and for how long, soil remains susceptible to runoff and erosion can help prioritize areas and time periods most in need of mitigation.
Starting my role as an Associate Editor for the International Journal of Wildland Fire (IJWF), I’m struck by how quickly wildfire-associated health has moved from the margins to mainstream fire research. This shift is evident in the growing number of high-profile conference sessions and presentations across International Association of Wildland Fire (IAWF)-associated and related meetings, including the 4th International Smoke Symposium in Tallahassee this year. It is also reflected in expanding global funding pathways for wildfire-health research, spanning agencies and schemes such as the US National Science Foundation, EU Horizon, UK Wellcome Trust, and Australia’s National Health and Medical Research Council (NHMRC) funding bodies, among others. IJWF has long helped our community understand the drivers and consequences of fire fuels, fire behaviour, suppression, and social-ecological impacts. Yet the people who plan for, respond to, and recover from wildfire, the workforce itself, are increasingly exposed to conditions that test physical and mental health over weeks, seasons, and entire careers. In that context, bringing a medical and health-focused lens into IJWF feels less like adding a new topic area and more like extending how we understand wildfire systems.
Background In the aftermath of a wildland–urban interface (WUI) wildfire, documenting subsequent reconstruction can help anticipate the consequences of future destructive events. Aims This case study chronicles the post-disaster rebuilding patterns of the 2011 Bastrop County Complex Fire (BCCF), the most destructive wildfire in the history of Texas, United States. Methods By analyzing tax account records from 2011 to 2021, we assess single-family home rebuilding rates and examine the disaster’s impact on single-family lot sales. Key results By 2021, the fire-impacted area had been rebuilt as a WUI residential development with more single-family homes within the fire perimeter than had existed in 2011. While new development within the fire perimeter accounted for some of the buildings at risk, single-family home construction was disproportionately focused on single-family lots containing a destroyed building. Single-family lots within the fire perimeter, whether destroyed or not, were more likely to be sold at least once during the period 2011–2021. Conclusions Our study is the first to document the post-wildfire rebuilding patterns of the most destructive Texas wildfire. Implications In the decade following the 2011 wildfire, Bastrop County’s WUI was rebuilt and expanded. This could increase future wildfire losses unless the community incorporates effective mitigation measures.
Background The reference condition is the expected proportions of reference vegetation classes per ecological system (hereafter, system) within an area and has been measured with non-spatial state-and-transition simulation models (STSM). Aims Demonstrate that reference conditions varied between non-spatial and spatial STSMs from an eastern Nevada, USA landscape. Methods The same STSM database was used to simulate the non-spatial and spatial reference conditions, except additional input were added for spatial simulations. The reference condition was obtained from averaged vegetation class proportions of replicated simulations. Key results Mean fire return intervals (MFRI) were always shorter in spatial than non-spatial simulations. The dissimilarity between the spatial and non-spatial reference conditions was generally higher for smaller systems and those with long MFRIs (≥100 years). Conclusions Non-spatial and spatial reference conditions were comparable for large systems with 50–100-year MFRI. The proportions of older vegetation classes for spatial systems were smaller for large systems with long MFRIs compared to non-spatial results, but those proportions were larger for smaller systems with shorter MFRIs, likely because fires can spatially exit small narrow systems. Implications National and local assessments that use departure from non-spatial reference conditions to determine vegetation treatments should recognize that spatial simulations can lead to revisions of treatment decisions.
Background Frequent fire characterises Australia’s tropical savannas and strongly influences vegetation structure and carbon (C) stocks. Fire management is widely used to reduce greenhouse gas emissions, but long-term effects of fire timing and frequency on woody C accumulation remain uncertain. Aims To quantify stand-level woody C stocks and assess cumulative multi-decadal effects of fire timing and frequency in northern Australian savannas. Methods Field measurements and historical biomass and basal area data from three long-term (17–30-year) fire trials were analysed. Treatments included unburnt controls and burned plots with up to four fire frequencies within a 6-year range and two fire seasons (early and late dry season). Carbon stocks were quantified for standing biomass, coarse woody debris and litter. Key results Total woody C accumulation was greater under early dry season fire than late dry season fire regimes. Longer between-fire intervals (particularly late dry season) may increase woody C stocks, although effect sizes were uncertain. Conclusions Early dry season burning was associated with greater long-term woody C accumulation than late dry season burning. Implications are that early dry season fire management remains important for reducing savanna fire emissions, but optimal fire regimes should consider site-specific conditions and broader ecological objectives.
Background There is a lack of scientific consensus on prioritization of mitigation actions to reduce susceptibility to wildfire. Aims This study identifies priority mitigation actions dependent on wildland–urban interface (WUI) community type while highlighting knowledge gaps to direct research needs. Methods This literature review examines the state of research from 28 relevant papers that explore post-fire housing survivability. Key results These studies suggest that house-, parcel-, neighborhood- and environment-scale characteristics influence housing survivability, including community design, such that priorities often differ between WUI community types. Although inconsistencies exist across observational studies, there are mitigation opportunities that effectively improve housing survivability, particularly within the home ignition zone. Conclusions Identified inconsistencies often arise from aggregating post-fire data across differing temporal and spatial scales or analyzing survivability associated with incident-specific fire behavior, leading to either a lack specificity or elevating event-specific characteristics that may not be consistent during another fire event. Importantly, suppression response, by either firefighters or civilians, is a critical determinant of housing survivability, although response is rarely evaluated because of data scarcity. Implications We identified knowledge gaps and make recommendations to fill those gaps with experimental testing and standardization of wildfire investigations. We also recommend establishing a fire behavior benchmark to evaluate mitigation effectiveness.
Background: Southern Africa’s extensive miombo woodland ecosystem is vital to global carbon sequestration but faces escalating threats from deforestation, degradation, and climate change. To successfully implement REDD+ initiatives and support local livelihoods, critical knowledge gaps in carbon dynamics and conservation strategies must be addressed. Aims: This review synthesises current knowledge on carbon dynamics in the miombo ecosystem and evaluates the opportunities and challenges for REDD+ implementation. Methods: A systematic review of published literature and recent assessments was conducted, focusing on carbon storage in above- and below-ground biomass and soils, and on the socio-ecological drivers influencing sequestration. Key results: Miombo ecosystems sequester 0.5–1.2 t ha⁻¹ yr⁻¹ of carbon, with variability driven by rainfall, soil fertility, and disturbance history. Sustainable management could secure 6–10 Pg of carbon globally. However, anthropogenic pressures, including fuelwood extraction, charcoal production, and shifting cultivation, constrain carbon accounting and policy integration. Conclusions: Effective REDD+ implementation requires robust measurement frameworks, equitable benefit-sharing, and strong community participation. Addressing these challenges is critical to advancing climate mitigation and biodiversity conservation. Implications: Investing in the long-term viability of miombo woodlands offers a dual opportunity: advancing global climate action while strengthening local livelihoods and promoting sustainable regional development.
Background. Ignition of natural fuels by hot porous particles originating from electrical faults and firebrands is a major cause of wildfire initiation and spread. Methods. This study investigated the ignition behavior of pine needles with a moisture content of 13% induced by a hot hollow steel particle. Particle effective energy was varied by adjusting the void ratio (0-0.85), while particle temperature (700-1100 degrees C) and diameter (8-16 mm) were independently controlled under a constant ambient wind speed of 2 m/s. Key results and conclusions. Three distinct phenomena were observed, namely direct flaming ignition, smoldering-to-flaming (StF) transition and no ignition. The results reveal that the controlling parameter for ignition depends on the ignition pathway. The overall critical ignition temperature is governed by particle effective energy, which determines the ability of the particle to sustain smoldering within the fuel bed. In contrast, direct flaming ignition is primarily controlled by particle temperature and size. Although hollow particles exhibit critical temperatures for direct flaming ignition comparable with solid particles, their reduced effective energy suppresses self-sustained smoldering, thereby increasing the overall critical ignition temperature. Implications. This study improves the understanding of the interaction between hot porous particles and natural fuels during wildfire initiation.
Background Quantifying and predicting wildland fire behavior is crucial for fire management, ecological research and mitigating wildfire impacts. Rate of spread (ROS), fireline intensity (FI) and fire radiative power (FRP) are key fire behavior metrics.Aims This study leverages uncrewed aircraft systems (UASs) equipped with thermal infrared (TIR) sensors and machine learning models to quantify and predict fire behavior.Methods Using repeat-pass UAS-based TIR imagery, we derived high-resolution FRP, FI and ROS estimates and trained artificial neural network (ANN) and random forest (RF) models to predict ROS.Key results This approach predicted ROS with low error (mean absolute errors (MAEs) below 0.04 m s-1, root mean squared errors (RMSEs) below 0.06 m s-1 and R2 values above 0.90) in short-term predictions for a single prescribed grassland fire, while maintaining computational efficiency.Conclusions Both ANN and RF models performed well, but RF performed better, with less training data, lower propensity for overfitting and less sensitivity to spatial autocorrelation.Implications Although currently demonstrated as a proof of concept at a single site with a specific fuel type and short-term prediction horizon, our integrated methodology shows research and development potential for supporting data-driven wildfire management strategies aimed at mitigating fire impacts, optimizing resource allocation and improving firefighter safety.
Background Satellite-based remote sensing is important for managing wildfires. However, cloud cover could hinder its effectiveness.Aims We examine potential cloud cover impacts on satellite-based wildfire detection and monitoring in Canada, analysing spatio-temporal patterns and relationships with local fire conditions.Methods Geostationary Operational Environmental Satellite 16 (GOES-16) Clear Sky Mask (CSM) data at relevant satellite overpass times in Ontario and Alberta are used to characterise cloud cover at a variety of spatial and temporal scales. Two potential fire behaviour indicators are compared under cloudy and clear conditions.Key results Cloud cover can vary by time of day, seasonally and by sub-region. In general, cloud cover was lowest overnight, during July-August and typically greatest at the overpass time of the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) instruments (13:30). Initial Spread Index (ISI) and Head Fire Intensity (HFI) distributions were similar under clear and cloudy conditions.Conclusions Satellite-derived active fire products will experience omission error rates varying in space-time and this could occur under potentially dangerous fire behaviour conditions. Care may need to be taken when relying on these products for fire monitoring and detection.Implications Wildfire-detection and monitoring strategies should leverage satellite, airborne and ground-based methods.
Background Wildfires in California have become larger and spread more rapidly over the past decade, burning forests and the wildland-urban interface (WUI).Aims Because these fires are a major source of air pollutants, there is a pressing need to develop accurate ground-based modeling systems of hazardous emissions.Methods The Carnegie-Ames-Stanford Approach (CASA) model, based on satellite observations of monthly vegetation cover, was used to estimate daily emissions of fine particulate matter (PM2.5), CO and CO2 from four destructive wildfires in California. CASA included refined emission factors for vegetation biomass, building structures and vehicle burning, resulting in a daily CASA-WUI modeling approach that produced 'bottom-up' emissions estimates at 30-m spatial resolution.Key results We compared daily species burning totals of PM2.5 and CO from CASA-WUI modeling with region- to global-scale wildfire emission models. The PM2.5 daily emission rates from developed urban areas were typically five times higher than from wildland areas owing to lower fuel densities in the wildlands.Conclusions Locations and neighborhoods with the highest estimated PM2.5 emissions had the highest fraction of Low Intensity Developed urban structure density.Implications This suggests the air quality was far worse in developed urban areas during the high smoke emission dates of the Thomas, Tubbs and Carr Fires than in remote wooded areas.
