Invasive species can fundamentally alter fire regimes by modifying fuel characteristics, yet predicting their impacts on fire behavior remains challenging. Cogongrass (Imperata cylindrica), a highly invasive grass spreading across the southeastern US, has been associated with increased fuel loads and fire intensity, but it is unclear how its impacts on fuel load and fire behavior vary across environmental and seasonal gradients. We measured fuel characteristics across 159 cogongrass invaded and non-invaded plots spanning from central Florida to southern Mississippi across multiple seasons. Using these data, we developed custom fuel models in BehavePlus to predict cogongrass effects on surface fire behavior and tree torching across spatial and temporal gradients. Cogongrass invasion increased live fuel loads by up to 1.96 t/ha, with effects strongest in summer and at lower latitudes, and dead fuel loads by up to 1.88 t/ha across all sites. Latitude × invasion interactions indicated that fuel load differences between invaded and non-invaded plots diminished toward northern sites. Cogongrass-driven fuel load alterations elevated surface fire rate of spread (median + 0.75 m/min), and flame length (+ 0.16 m), with the largest increases observed in spring (rate of spread: + 2.60 m/min; flame length: + 0.80 m). Invasion also consistently increased the crown fire transition probability, with magnitudes mirroring those of surface fire effects. Our findings highlight the potential for cogongrass to substantially alter fire behavior across a range of environmental conditions, although the magnitude of these effects varies geographically and tends to be strongest at lower latitudes. These results underscore the importance of targeted management in regional fire planning of invaded landscapes.
Fire simulators are computer programs that represent the key processes of fire spread, based on mathematical models of the physical processes of combustion and landscape fire propagation. The complexity and pace of change in fire regimes, science and technology pose challenges to the effective development and use of fire simulators. In this review, we address the nature of current fire simulators, their most common uses, and how to judge their performance. We find that fire simulators can be classified based on their underlying modeling approach: physical and quasi-physical, empirical and quasi-empirical, and coupled fire-atmosphere models. We find that faithful representation of fire spread and its drivers remains a primary focus and is being addressed through improved input data, spread models, and more robust validation standards. However, evidence suggests that fitness-for-purpose may be a more flexible and effective basis of simulator performance as it is able to incorporate both technical and contextual factors. Our findings can be used by fire-prone countries and jurisdictions to support the development of an effective fire simulator “ecosystem” that addresses both technical and contextual issues.
Computer-model simulations of wildfire behavior and associated wildfire risk are critically needed to inform the design and implementation of fuels treatments for proactive management of landscape wildfire risks. Available computer-models require maps of fire behavior fuel models (FBFMs) to simulate wildfire behavior, which are challenging to create for mixed woody/herbaceous vegetation. This problem is compounded in the fire-prone sagebrush steppe of the western USA, owing to the vast and remote areas of concern. One solution is to crosswalk readily measured vegetation variables (i.e., cover data) to FBFMs. To demonstrate this approach, we related FBFM assignments from 3700 recently burned and unburned plots to plant cover estimated using either line-point intercept (LPI, 25–50-m field transects), or grid-point intercept from aerial photos (GPI, digital, high-resolution, 6 m2 areas), or coarsely over 13-m radius area in the field without guides (so-called ocular estimation), throughout the Great Basin. Random forest models of the cover-to-FBFM relationships were generated and their accuracy assessed using data withheld from parameterization, and then used to create decision trees for selecting FBFMs from vegetation cover. Examples of findings from random forest-informed decision trees included (1) 7–10
Wildfire behaviour is influenced by the physiological state of vegetation, particularly live fuel moisture content (LFMC), which affects fire spread and ignition. LFMC represents the ratio of water mass to dry mass in plant tissues. To understand LFMC dynamics, it is important to investigate interrelated traits such as leaf water per area (LWA), dry matter content (DMC) and specific leaf area (SLA). LWA quantifies water content per unit leaf area while SLA and DMC capture different aspects of leaf physiology. Understanding the diurnal and seasonal variability of LFMC alongside LWA, DMC and SLA is essential for predicting wildfire dynamics. We examined the diurnal and seasonal variations in these traits under progressive drought in two Australian species: Eucalyptus torquata and Corymbia maculata. Sampling day and time influenced trait dynamics. LFMC showed clear diurnal patterns with lower values at midday than in morning or late afternoon, consistent with previous reports. We found that drought altered the diurnal behaviour of related leaf traits particularly LWA, DMC and SLA, and that these responses differed within species. In E. torquata, LFMC in drought-treated plants showed a steeper diurnal drop from day 29 onward with LFMC falling below 60
Historically frequent-fire forest ecosystems are now facing fires of increased size, frequency, and severity attributed to climate change, intensive forest management, and fire exclusion policies. Understanding post-fire resilience in forest ecosystems is critical amidst escalating challenges posed by recent increases in fire activity. Coast redwood (Sequoia sempervirens) forests provide a model system for examining post-fire persistence via resprouting in a highly fire-resilient ecosystem. Here, we identify the most informative fire-damage metrics for post-fire basal resprouting, quantify the relative influence of tree-, stand-, and climate-level drivers of post-fire basal resprouting, and examine the relationship between epicormic and basal resprouting following fire for redwood. Post-fire redwood basal resprout responses (presence and abundance) had a strong, positive association with bole char ratio (a relativized measure of fire damage calculated as the ratio of bole char height to total tree height). Both the presence and abundance of basal resprouting did not detectably decline with increasing fire damage but rather increased continuously. In addition to fire damage, the probability of basal resprouting, total resprout biomass, and other responses decreased with higher climatic water deficit. Epicormic resprouting of the tree bole was positively related to basal resprout probability. As climate change drives increased fire activity and severity in many forest ecosystems, prolific post-fire resprouting can facilitate rapid recovery and the long-term persistence of redwoods. These positive post-fire outcomes are slightly tempered by observations of reduced resprouting abundance (both basal and epicormic) in warmer and drier locations, suggesting there may be climatic limitations in the post-fire resprouting ability of redwoods. Our study provides forest managers with sound expectations that resprouting will promote redwood persistence, though may be hindered in the future by extreme drought events.
Peatlands combine large belowground organic fuel stores with high moisture conditions that often limit combustion, making peatland fire occurrence difficult to interpret from fuel availability or wetness alone. In Sweden, extensive drainage has altered peatland hydrology and vegetation, but it remains unclear whether mapped drainage intensity explains where peatland fires occur. We conducted an exploratory national geospatial analysis of fire occurrence from 2001 to 2023 by intersecting two satellite-derived fire datasets (mapped burned-area perimeters and thermally anomalous active-fire footprints) with peatland extent, mapped land cover, hydroclimatic indicators, ditch density, and road density within a Swedish analysis domain defined by forestland and open-wetland land-cover classes. Peatlands were not underrepresented among fire-affected areas. Nationally, peatlands accounted for 27.4
Measurement of downed woody debris (DWD) across large areas is needed to realistically represent heterogenous fuel landscapes. Such measurements are key for improving predictions of fire behavior, effects, consumption, and emissions, and to develop and implement more effective forest management plans. However, DWD varies in amount, size, and structure, with its spatial distribution across the forest floor being driven by complex and interacting factors, such as forest productivity, tree growth dynamics, decomposition, disturbances, weather, and mortality events. Remote sensing, particularly airborne laser scanning (ALS), and ecological based knowledge can be leveraged to improve fuel characterization by estimating fuel properties at operational scales. In this study, we quantified DWD fuel loads using ALS data by linking expected rates of tree wood biomass (branch and bole biomass) annual deposition to surface fuel loads in fire-maintained woodlands dominated by longleaf pine. Terrestrial laser scanning (TLS) data were additionally used to develop crown proportion equations to estimate the branch biomass corresponding to fine (≤7.6 cm) and coarse (>7.6 cm) branch size components. We accounted for DWD accumulation by considering fire return intervals and decomposition rates by applying a spatially explicit implementation of the Olson fuel accumulation model, then accounting for fuel removal due to previous prescribed fire. The model provided unbiased estimates, suggesting that it can represent variability at broader spatial scales; however, we found a negligible relationship between fine woody debris estimates and independently collected field observations, which highlights the difficulty of both characterizing and assessing model performance of highly variable DWD loading at high spatial resolution. Many variables, such as consumption during previous fires, annual rates of branch deposition and decomposition, and the likely undersampling of the field data used for comparison contribute to the uncertainties of the estimates. Our analyses suggest that, a priori, the within-stand spatial distribution of DWD is not driven solely by the spatial distribution of live trees, and consumption during prescribed fire is likely patchier compared to constant and uniform rates considered in this study. Further refinement and parameterization are required to model DWD and improve the characterization of within-stand fuel distribution; however, the methodology is a first step for integrating remote sensing into an ecological conceptual framework that provides DWD estimates to build heterogeneous fuel beds and may help fuel and fire managers more effectively address wildfire-related natural resource management challenges.
Surface fuels strongly influence forest fire behavior, yet their distribution and composition are often not known in detail. As surface fuels result from forest litter and vegetation dynamics, we hypothesize that fuel loads vary systematically with forest structure and composition. If so, forest structural characteristics could be used to predict surface fuels and improve fire modeling efforts. Here, we assess the relationship between forest structure and fuel loads of various surface fuel classes (leaves, needles, cones, acorns, woody debris, moss, grass, and herb) in Central European forests (Germany, Czechia) and along a gradient from pine (Pinus sylvestris) to oak (Quercus spp.) dominated plots. Across 53 plots, we derive highly detailed, observer-independent structural and compositional metrics using terrestrial laser scanning (TLS) and field-measured surface fuel loads using destructive sampling in replicated microplots. Random forest models show the strongest predictive performance for fuel classes composed of smaller, evenly distributed particles (leaves, needles, and the complete fuel load) with R2 values up to 0.72. When modeling all plots along the species gradient together, simple forest inventory metrics that distinguish between coniferous and deciduous trees are most important for predicting surface fuel loads. When modeling pure-species plots separately, more complex descriptors of vegetation density and height become essential. Relatively simple, inventory-based metrics, many of which are available in existing forest databases, can sufficiently predict key surface fuel components across the surveyed species gradient. This enables more accessible and scalable fuel mapping for broad analysis, spanning a range of species compositions. Integrating this into fire behavior models could significantly enhance fire risk assessment and support proactive forest management strategies. More detailed models focusing on single species and pure stands, on the other hand, benefit from the additional information provided by 3D structural metrics. Here, vegetation density in the canopy is an important predictor of surface fuel load.
Prescribed fire is an effective method to control woody encroachment into sagebrush steppe, which covers 40 million hectares of the Western United States. Medium resolution remote sensing products (e.g., Landfire) are widely available but do not adequately meet the needs of rangeland prescribed fire planners and fuels managers who require fine-scale, spatial depictions of fuel type (vegetation) composition and burn severity outcomes to ensure resource conservation and effective fire treatments. We compared the accuracy of pre-fire and post-fire datasets at different spatial resolutions and assessed the tradeoffs of using the data for machine learning modeling of burn severity. Our study focused on a prescribed fire that took place in a sagebrush (Artemisia spp.) dominated watershed in Southwestern Idaho for juniper control on 6 October 2023. We found that high resolution 0.5 m WorldView-2 pre-fire fuel maps were 83.0
Savanna landscapes have returned to the centre of socio-environmental debate as climate variability, agricultural expansion, and prohibition-oriented policies reshape how fire is understood and governed. Focusing on Brazil’s largest maroon (quilombola) territory, we examine how Kalunga communities mobilize fire as both a productive technology and a preventive tool within agropastoral socioecological mosaics of the Cerrado. Our mixed-methods approach combines semi-structured interviews, participant observation across dry and wet seasons, and analysis of historical climate series (1980–2024) for precipitation, temperature, relative humidity, and wind. We show that roças de toco (rainfed swidden fields) form dynamic patchworks that sustain soil fertility, conserve useful native species, fragment fuel continuity, and may contribute to limiting wildfire spread. Cropping and grazing are coordinated through locally defined burning windows, ash-mediated nutrient inputs, and community firebreaks, producing landscapes that support livelihoods while regulating wildfire risk. Local perceptions of delayed rainy seasons, prolonged droughts, and “hot winds” are consistent with instrumental climate trends, indicating increasingly dry and flammable dry seasons, thereby narrowing the safety margins for controlled burning. Simultaneously, external pressures—including shifts towards poorly adapted cattle breeds, expansion of planted pastures, enforcement of “zero-fire” policies, and land conflicts—are reconfiguring local practices and redistributing risks. We argue that, in Kalunga systems, fire operates as a technology of socioecological governance, sustaining production while contributing to wildfire-risk reduction through fuel fragmentation, low-intensity burning practices, and community-based monitoring. We conclude that blanket fire prohibitions should be replaced by co-managed governance arrangements that formalize locally defined burning windows, maintain community firebreaks, and integrate Traditional Ecological Knowledge with technical criteria within adaptive and risk-aware fire and water governance frameworks in the Brazilian savanna.
Disturbances may shift forest ecosystem disease dynamics when they affect populations of insects that vector plant pathogens. Sawyer beetles (Monochamus spp.) are common in conifer forests and beetles recruit to and colonize stressed hosts including those exposed or adjacent to wildfires. Monochamus spp. are also vectors of a lethal vascular wilt caused by pinewood nematode (Bursaphelenchus xylophilus), which is phoretic on beetles. Here we tested whether temporal and spatial proximity to wildfire events (2020 Cameron Peak and Cal-Wood Fires, Colorado, USA) predict detection of B. xylophilus in two sympatric Monochamus species (M. clamator and M. scutellatus) in the southern Rocky Mountains. Beetle flight phenology was also tested relative to B. xylophilus phoresy. Beetles were collected over three field seasons corresponding to 1, 2, and 4 years post-wildfire (2021, 2022, and 2024) using panel traps and subsequently tested for B. xylophilus. Detection of B. xylophilus was elevated in beetle populations 1 year following wildfire (29.8 and 11.8
The dominant natural habitats in the southeastern US depend on frequent fire ignited by humans or lightning. However, fire activity has sharply declined in the region since the early 1900s, and reduced fire activity has degraded natural habitats and increased wildfire risk. Identifying changes in fire use during recent decades is necessary to guide the conservation of fire-dependent wildlife, management of hazardous fuels, and identify areas where increased fire use could improve ecosystem resilience. To address this need, we created the Southeast FireMap dataset by fine-tuning the US Geological Survey’s Landsat Burned Area product to track burned area and provide a fire history across the southeastern US. We used the Southeast FireMap data to quantify changes in areas frequently burned, as measured by areas with multiple burns within a decade. We compared the periods 2000–2009 and 2010–2019 to identify where frequently burned area is increasing or declining. We examined patterns of change across ownership, land cover, and soil orders to provide geographic context, and we considered future implications of these changes for land use categories of ecological interest. Frequently burned area increased between decades across the region. This increase occurred on both private and public lands, in upland vegetation types, and on upland soils, though these increases were moderately offset by decreased wetland burning and its associated soil orders. However, changes varied among states, with burned area decreasing in some states. The overall increase in frequently burned area across the region reflects a summation of positive and negative shifts associated with specific combinations of physiography, ownership class, and government jurisdiction. SE FireMap marks a significant advancement in our ability to identify changes in prescribed burning within the geographic and cultural contexts that will likely influence the complex future of fire in the region.
Foliar moisture content (FMC) is a central determinant of plant flammability and strongly influences fire behavior and effects. In this study, we examined whether FMC varied with vertical crown position in three of the tallest conifer species of northwestern California: coast redwood (Sequoia sempervirens), Douglas-fir (Pseudotsuga menziesii), and Sitka spruce (Picea sitchensis). Specifically, we tested whether (1) FMC decreases with increasing crown position height, (2) the vertical FMC gradient persists across both new and old foliage, (3) the strength of the vertical FMC gradient varies by species, and (4) the vertical FMC gradient is associated with changes in leaf and shoot morphology. We found that FMC declined significantly with increasing relative crown position height for both new and old foliage in all three tree species. FMC around mid-crown positions was approximately 20
Studies on plant germination responses to fire have primarily relied on laboratory simulations, typically using oven-based heat shock treatments and liquid smoke applications. However, the extent to which these approaches reproduce real fire conditions remains debated, and an alternative experimental approach involves the use of controlled biomass burning. In this study, we compared germination responses under controlled biomass burns with those under equivalent laboratory treatments, using cacti as a model system. Cacti are conspicuous components of arid and semiarid ecosystems across the Americas and are increasingly threatened by anthropogenic pressures, including changes in fire regimes. Despite much of their distribution occurring in fire-prone environments, few studies have evaluated their germination responses to fire. We assessed germination (percentage and mean germination time) of 16 cactus species using two experimental approaches across seven treatments: a control; four biomass burning treatments with different fuel loads (50 g, 50 g + ash, 100 g, and 100 g + ash); and two equivalent laboratory treatments (100 °C/5 min and 130 °C/5 min), both combined with liquid smoke. We also evaluated the effect of seed mass on germination. Germination responses differed markedly between experimental approaches. Under biomass burning treatments, germination was consistently very low—often null—across all species, whereas laboratory treatments elicited germination responses in most species. Under the moderate-intensity laboratory treatment (100 °C + smoke), responses did not differ significantly from the control. Mean germination time varied among species: in some cases it did not differ from the control, whereas in others it either increased or decreased under laboratory treatments. Seed mass had no significant effect on germination percentage, but significantly influenced mean germination time. Overall, our results indicate that conventional laboratory experiments do not adequately reproduce real fire conditions and may substantially overestimate germination responses in cacti.
Wildfire risk in Switzerland is expected to increase in the future due to a hotter and drier climate and more extreme weather events. This makes community-level preparedness and coping capacity increasingly important. This article focuses on the 2023 wildfire on the Riederhorn mountain in Canton Valais as a case study of a Swiss mountain community directly impacted by wildfire. Through narrative analysis of semi-structured interviews conducted with local residents and professionals managing the event (n = 12), the article explores peoples’ experiences of the wildfire and how these experiences influence understandings of risk. The results show that peoples’ perceptions are shaped by sensory impressions, emotional responses, and embodied memories, which are often linked to community cohesion and sense of agency. Experiencing the Riederhorn wildfire increased local awareness of risk in the short-term, but its long-term effects arguably depend on collective narratives and institutional practices. The article concludes by highlighting the benefits of strengthening community agency and integrating emotional dimensions and volunteerism into Swiss wildfire governance and hazards management.
Frequent and extensive fires in the late dry season are a feature of the miombo woodlands of central Africa. A knowledge of prevailing fire regimes at a local scale is required to set realistic and appropriate targets that will sustainably conserve ecosystems and to plan accordingly. We used data from satellite remote sensing (Landsat and Sentinel) to quantify the recent fire regimes in the Kafue National Park (KNP) and surrounding Game Management Areas (GMAs) in Zambia between 2014 and 2025. We then assessed whether current management targets would be achievable and appropriate in the light of existing ecological understanding and the realities of current burning practices. Fire frequency was very high across the entire study area, with a median fire return interval of 1.39 years. Fire return intervals differed slightly between the KNP and the GMAs (1.26 and 1.49 years, respectively). Fire survival curves indicated that 50
Herbivores grazing and fires have historically shaped Mediterranean shrublands by maintaining open habitats and diverse plant communities. Rural abandonment has reversed this process, resulting in fuel accumulation, increased forest connectivity, and wildfire risk. Pyric herbivory, combining prescribed burning and grazing, can mitigate these threats by reducing fuel loads, controlling woody encroachment, and restoring ecosystem processes. This case study investigated the short-medium term effects of prescribed burning and pyric herbivory with two different burning seasons in Mediterranean shrublands with different scrub types. We conducted a 2-year field experiment applying spring and autumn prescribed burns ranging from moderate to high intensity, with and without low-intensity grazing by sheep, across four vegetation types: low- and medium-cover areas, and dense areas dominated by Macrochloa tenacissima or Genista scorpius. The observed patterns suggest that both prescribed burning and pyric herbivory reduced fuel loads while preserving forage quality, but only combined fire, mostly in autumn, and grazing seemed to increase plant diversity, and only in the dense areas. In dense Macrochloa areas, spring burns during active growth, apparently, favored rapid Macrochloa clonal recovery and competitive dominance, limiting diversity, whereas autumn burns during plant dormancy seemed to reduce Macrochloa vigor, enabling more diverse herbaceous establishment under grazing. In Genista areas, irrespective of burning season, its lignotuber resprouting and seed-bank recruitment probably allowed its recovery, albeit slower, favoring a maximized increase in diversity when burns were followed by grazing. These findings underscore the need for vegetation- and season-specific fire-grazing regimes that align with plant phenology, growth forms, and life strategies. Pyric herbivory emerges as an adaptable strategy to mitigate wildfire risk, maintain pasture quality, and enhance biodiversity in fire-prone Mediterranean landscapes.
Wildfires increasingly threaten structures and communities in the wildland-human interface of forested biomes. We present an integrated fuel break placement optimization model that is designed to assist with the planning of landscape scale fuel break configuration to mitigate wildfire risk to structures. The model combines three components: a burn probability simulation model, a structural loss rate model, and a network-based optimization model for fuel break placement. We applied the models to a fire-prone forest landscape encompassing a military training base with frequent ignitions and restricted access zones, and its surrounding communities and residential structures. We evaluated 198 scenarios with different budget levels, management priorities, and jurisdictional constraints to find optimal fuel break placement solutions. Our results show significant fire hazard and risk reduction potential even at modest fuel treatment budgets. Fire risk to structures is reduced most when fuel breaks are placed inside and outside the jurisdiction of the military base. The proposed framework offers a workable decision-support tool for land managers and allows accommodating for real-world jurisdictional constraints, budget limitations, and risk reduction priorities in fire-prone regions.
Prescribed burning is an important management tool for mitigating wildfire risk and maintaining ecological values in fire-prone landscapes. Burnability, defined as the probability that a location will burn, varies across space and time at fine scales. Understanding these patterns and how they respond to forecast weather could help practitioners identify suitable burn windows and anticipate burn outcomes. We aimed to develop a spatially explicit logistic regression model to predict burnability and tested whether incorporating dynamic variables (microclimate and soil moisture) improved predictions relative to models with only static variables (e.g., topography). Using a spatial dataset of historic prescribed burns in eucalypt forests, we related point-scale burn outcomes (burnt vs. unburnt) to gridded topographic, weather, and moisture variables as well as the fuel management zone as a proxy for burn objectives. Dynamic predictors improved model performance. In the dynamic model, in-forest vapor pressure deficit and soil moisture supplemented topographic position index and fuel management zone to predict spatial patterns in burnability at a 30-m resolution, and how it varies day-by-day. Overall predictive performance was moderate (cross-validated AUC = 0.68), indicating limited ability to fully discriminant between burned and unburned areas. Burnability models provide an objective, pre-ignition assessment of likely burn coverage. This can support practitioners in identifying suitable windows for prescribed burning. Incorporating dynamic microclimatic variables improves predictive performance and enables models to respond to changing weather conditions. However, predictive accuracy remains constrained by the inability to fully represent on-ground management decisions.
Public domain allotments in California are ecologically, culturally, and politically significant individual parcels of land held in trust by the federal government for California Indian people. Their political importance is rooted in the unfulfilled promises of the 18 treaties negotiated between the USA and California Indian nations in 1851–1852. When the Senate refused to ratify those treaties, it denied California Indians the sovereign right to protect their lands from federal and private expropriation. Today a patchwork of federal statutes, executive orders, and regulations define and control Native land ownership in California. Public domain allotments are part of this patchwork; beginning in 1887, the federal government set aside public domain allotments for Native people not living on reservations. At one time, public domain allotments in California comprised over 336,000 acres. Today, only about 17,000 acres remain. For descendants of allottees who are not members of federally recognized tribes, these lands serve as critical sites of political recognition and formal legal connection to the USA, and hubs of cultural continuity. Ecologically, allotments are vital landscapes that sustain culturally important plant communities, wildlife corridors, and function as climate refugia for species central to food, medicine, ceremony, and traditions. The reintroduction of mixed-severity fire is critical on allotments to maintain both ecological health and cultural practice. Yet current regulations governing burning are designed for tribal governments with administrative capacity, not for dispersed allottee families and individuals. Chronic Bureau of Indian Affairs understaffing further compounds these barriers, creating regulatory frameworks that do not align with Indigenous concepts of fire sovereignty. This paper analyzes the policy context shaping the return of fire to public domain allotments and identifies pathways to support restoration and resilience planning on Indian allotment lands.
