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Parcel-level risk (PLR) describes how wildfire risk varies from home to home based on characteristics that relate to likely fire behavior, the susceptibility of homes to fire, and the ability of firefighters to safely access properties. Here, we describe the WiRē Rapid Assessment (RA), a parcel-level rapid wildfire risk assessment tool designed to evaluate PLR with a small set of measures for all homes in a community. We investigate the relationship between 2019 WiRē RA data collected in the Columbine Lake community in Grand County, Colorado, and whether assessed homes were destroyed in the 2020 East Troublesome Fire. We find that the overall parcel-level risk scores, as well as many individual attributes, relate to the chance that a home was destroyed. We also find strong evidence of risk spillovers across neighboring properties. The results demonstrate that even coarsely measured RA data capture meaningful differences in wildfire risk across a community. The findings also demonstrate the importance of accounting for multiple aspects of PLR, including both hazards and susceptibility, when assessing the risk of wildfire to homes and communities. Finally, the results underscore that relatively small actions by residents before a fire can influence wildfire outcomes.

Background: In most wildland–urban interface (WUI) fires, damage to buildings results from poor surrounding vegetation management. No simulation had been conducted yet on historical WUI fires with Computational Fluid Dynamics modelling.Aims: It was interesting to check the feasibility of this modelling in simulating past fire cases for different scenarios of vegetation management and fire propagation.Methods: We studied three cases of WUI dwellings surrounded by gardens (subject to French regulations on fuel reduction) adjacent to forest affected by a past fire. The 3D fire propagation was assessed using the Fire Dynamic Simulator model (FDS) and taking into account accurate fire environment (fine vegetation distribution, terrain, etc.).Key results: Results showed that, in the current model state, brush-clearing mitigated fire intensity and propagation and damage to ornamental vegetation. However, it sometimes highlighted that this measure could be strengthened when the effects of topography and wind were combined.Conclusions: FDS modelling at the WUI scale using accurate vegetation distribution proved to be functionally satisfactory, exhibiting realistic fire behaviour.Implications: Once validated, this modelling will ultimately help to assess when fuel reduction is efficient in fire mitigation and to pinpoint possible limitations.

Background Wildfires, like many disturbances, can be catalysts for ecosystem change. Given projected climate change, tree regeneration declines and ecosystem shifts following severe wildfires are predicted. We reviewed scientific literature on post-fire tree regeneration to understand where and why no or few trees established. We wished to distinguish sites that won’t regenerate to trees because of changing climate from sites where trees could grow post fire if they had a seed source or were planted, thus supporting forest ecosystem services for society and nature, such as timber supply, habitat, watershed protection, and carbon storage. Results Our literature review showed that little to no post-fire tree regeneration was more common in low-elevation, dry forest types than in high-elevation forest types. However, depending on the region and species, low tree regeneration was also observed in high elevation, moist forests. Regeneration densities varied by species and seedling densities were attributed to distances to a seed source, water stress or precipitation, elevation, slope, aspect, and plant competition. Our findings provide land managers with two primary considerations to offset low tree regeneration densities. First, we supply a decision support tool of where to plant tree seedling in large high severity burned patches. Second, we recommend possibilities for mitigating and limiting large high severity burned patches to increase survival of trees to be sources of seed for natural regeneration. Conclusions Few or no tree seedlings are establishing on some areas of the 150+ forest fires sampled across western US, suggesting that forests may be replaced by shrublands and grasslands, especially where few seed source trees survived the wildfires. Key information gaps on how species will respond to continued climate change, repeated disturbances, and other site factors following wildfires currently limit our ability to determine future trends in forest regeneration. We provide a decision tree to assist managers in prioritizing post-fire reforestation. We emphasize prioritizing the interior of large burned patches and considering current and future climate in deciding what, when, and where to plant trees. Finally, managing fires and forests for more seed-source tree survival will reduce large, non-forested areas following wildfires where post-fire management may be necessary.

This study investigates post-fire vegetation transitions and spectral responses in the Snowstorm Fire (2017) and South Sugarloaf Fire (2018) in Nevada using Landsat 8 Operational Land Imager (OLI) surface reflectance imagery and unsupervised ISODATA classification. By comparing pre-fire and post-fire conditions, we have assessed changes in vegetation composition, spectral signatures, and the emergence of novel land cover types. The results revealed widespread conversion of shrubland and conifer-dominated systems to herbaceous cover with significant reductions in near-infrared reflectance and elevated shortwave infrared responses, indicative of vegetation loss and surface alteration. In the South Sugarloaf Fire, three new spectral classes emerged post-fire, representing ash-dominated, charred, and sparsely vegetated conditions. A similar new class emerged in Snowstorm, highlighting the spatial heterogeneity of fire effects. Class stability analysis confirmed low persistence of shrub and conifer types, with grassland and herbaceous classes showing dominant post-fire expansion. The findings highlight the ecological consequences of high-severity fire in sagebrush ecosystems, including reduced resilience, increased invasion risk, and type conversion. Unsupervised classification and spectral signature analysis proved effective for capturing post-fire landscape change and can support more accurate, site-specific post-fire assessment and restoration planning.

Wildfires cause substantial ecological disturbances, altering vegetation dynamics and soil properties over extended periods. This study investigated the influence of vegetation burn severity on post-fire vegetation recovery rates using multi-temporal Landsat 8 surface reflectance imagery from 2014 to 2023. Two major fire events in Nevada, the Snowstorm Fire (2017) and the South Sugar Loaf Fire (2018), were examined through four spectral indices: the Normalized Difference Vegetation Index (NDVI), Moisture Stress Index (MSI), Modified Chlorophyll Absorption Ratio Index 2 (MCARI2), and Land Surface Temperature (LST). Statistical techniques, including the Mann–Kendall trend test and Linear Mixed Effects models, were applied to assess pre- and post-fire trends across burn severity classes. Results showed that vegetation recovery was primarily driven by temporal factors rather than burn severity, especially in the Snowstorm Fire. In the South Sugar Loaf Fire, significant changes were observed in LST and NDVI scores in low-severity areas, while MSI and MCARI2 scores exhibited significant recovery differences in high-severity zones. These findings suggest that post-fire vegetation dynamics vary spatially and temporally, with severity effects more pronounced in certain conditions. The study underscores the effectiveness of spectral indices in capturing post-disturbance recovery and supports their application in guiding site-specific restoration and long-term ecosystem management.

Drought-induced wildfires have increased in frequency and extent over the tropics. Yet, the long-term (greater than 10 years) responses of Amazonian lowland forests to fire disturbance are poorly known. To understand post-fire forest biomass dynamics, and to assess the time required for fire-affected forests to recover to pre-disturbance levels, we combined 16 single with 182 multiple forest census into a unique large-scale and long-term dataset across the Brazilian Amazonia. We quantified biomass, mortality and wood productivity of burned plots along a chronosequence of up to 31 years post-fire and compared to surrounding unburned plots measured simultaneously. Stem mortality and growth were assessed among functional groups. At the plot level, we found that fire-affected forests have biomass levels 24.8 ± 6.9% below the biomass value of unburned control plots after 31 years. This lower biomass state results from the elevated levels of biomass loss through mortality, which is not sufficiently compensated for by wood productivity (incremental growth + recruitment). At the stem level, we found major changes in mortality and growth rates up to 11 years post-fire. The post-fire stem mortality rates exceeded unburned control plots by 680% (i.e. greater than 40 cm diameter at breast height (DBH); 5–8 years since last fire) and 315% (i.e. greater than 0.7 g cm−3 wood density; 0.75–4 years since last fire). Our findings indicate that wildfires in humid tropical forests can significantly reduce forest biomass for decades by enhancing mortality rates of all trees, including large and high wood density trees, which store the largest amount of biomass in old-growth forests. This assessment of stem dynamics, therefore, demonstrates that wildfires slow down or stall the post-fire recovery of Amazonian forests. This article is part of a discussion meeting issue ‘The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications’.

Wildland fires dramatically affect forest ecosystems, altering the loss of their biodiversity and their sustainability. In addition, they have a strong impact on the global carbon balance and, ultimately, on climate change. This review attempts to provide a comprehensive meta-analysis of studies on remotely sensed methods and data used for estimation of forest burnt area, burn severity, post-fire effects, and forest recovery patterns at the global level by using the PRISMA framework. In the study, we discuss the results of the analysis based on 329 selected papers on the main aspects of the study area published in 48 journals within the past two decades (2000–2020). In the first part of this review, we analyse characteristics of the papers, including journals, spatial extent, geographic distribution, types of remote sensing sensors, ecological zoning, tree species, spectral indices, and accuracy metrics used in the studies. The second part of this review discusses the main tendencies, challenges, and increasing added value of different remote sensing techniques in forest burnt area, burn severity, and post-fire recovery assessments. Finally, it identifies potential opportunities for future research with the use of the new generation of remote sensing systems, classification and cloud performing techniques, and emerging processes platforms for regional and large-scale applications in the field of study.

Wildfires constitute the most important natural disturbance of Mediterranean forests, driving vegetation dynamics. Although Mediterranean species have developed ecological post-fire recovery strategies, the impacts of climate change and changes in fire regimes may endanger their resilience capacity. This study aims at assessing post-fire recovery dynamics at different stages in two large fires that occurred in Mediterranean pine forests (Spain) using temporal segmentation of the Landsat time series (1994–2018). Landsat-based detection of Trends in Disturbance and Recovery (LandTrendr) was used to derive trajectory metrics from Tasseled Cap Wetness (TCW), sensitive to canopy moisture and structure, and Tasseled Cap Angle (TCA), related to vegetation cover gradients. Different groups of post-fire trajectories were identified through K-means clustering of the Recovery Ratios (RR) from fitted trajectories: continuous recovery, continuous recovery with slope changes, continuous recovery stabilized and non-continuous recovery. The influence of pre-fire conditions, fire severity, topographic variables and post-fire climate on recovery rates for each recovery category at successional stages was analyzed through Geographically Weighted Regression (GWR). The modeling results indicated that pine forest recovery rates were highly sensitive to post-fire climate in the mid and long-term and to fire severity in the short-term, but less influenced by topographic conditions (adjusted R-squared ranged from 0.58 to 0.88 and from 0.54 to 0.93 for TCA and TCW, respectively). Recovery estimation was assessed through orthophotos, showing a high accuracy (Dice Coefficient ranged from 0.81 to 0.97 and from 0.74 to 0.96 for TCA and TCW, respectively). This study provides new insights into the post-fire recovery dynamics at successional stages and driving factors. The proposed method could be an approach to model the recovery for the Mediterranean areas and help managers in determining which areas may not be able to recover naturally.

Post‐fire stand water balance is a critical factor influencing tree regeneration and survival, which are often modulated by fire severity. We examined influences of the post‐fire vegetation matrix and fire severity on diurnal, seasonal, and multi‐year variation in evapotranspiration (ET) by analyzing the relationship between post‐fire vegetation and ECOsystem Spaceborne Thermal Radiometer Experiment on the International Space Station (ECOSTRESS) ET data using multivariate and linear mixed effects modeling. Unlike many high‐severity fire sites where ET drops after burning, post‐fire ET was high at shrubland sites that burned at high fire severity in southern Arizona, USA. In this study, post‐fire ET was driven by plant species composition and tree canopy cover. ET was significantly higher in the morning and midday in densely vegetated post‐fire shrublands than pine‐dominated forests that remained 5–7 years after wildfire. Our results demonstrate that plant functional traits such as resprouting and desiccation tolerance drive post‐fire ET patterns, and they are likely to continue to play critical roles in shaping post‐fire plant communities and forest water cycling under future environmental change. Wildfire‐driven transitions from forests to shrublands are an increasingly prevalent landscape feature, as fires across western North America continue to grow in size and severity under climate change. Post‐fire stand water balance is a critical factor influencing tree regeneration and survival success, which are often modulated by fire severity. We examined influences of the post‐fire vegetation matrix and fire severity on diurnal, seasonal, and multi‐year variation in evapotranspiration (ET) ECOSTRESS remotely sensed data via multivariate and linear mixed effects modeling. Unlike many high‐severity fire sites where ET drops after burning, post‐fire ET was high at type‐converted shrubland sites in southern Arizona, USA. Five‐ to seven‐year‐old post‐fire shrublands had higher ET in the morning and at midday than pine‐dominated forests that remained intact after the wildfire. This study highlights the importance of post‐fire plant species composition as a control on stand water status and cycling.

The experimental quantification of retention factors related to the post-fire strength as well as the post-fire ductility of intentionally selected stainless steel grades applied in construction is the objective of the research presented here. These steel grades are characterized by a two-phase austenitic–ferritic microstructure of the duplex type. In this context, two mutually corresponding chromium–nickel–molybdenum steel grades are subjected to analysis, namely X2CrNiMoN22-5-3 steel belonging to the standard duplex group (DSS 22% Cr) and X2CrMnNiN21-5-1 steel belonging to the lean duplex group (LDSS). The similarities and differences in the mechanical properties exhibited by these steel grades after effective cooling, following more or less prolonged simulated fire action conforming to several development scenarios, are identified and indicated. The resistance of a given steel grade to permanent structural changes induced by the heating program proved to be the critical factor determining these properties and resulting in many cases in increased susceptibility to brittle fracture. The results obtained experimentally seem to confirm the quantitative estimates of post-fire retention factors forecast by Molkens and his team, specified for the steels exhibiting a duplex-type structure and tested by us. However, several of these estimates might be considered somewhat risky. Nevertheless, our results do not confirm the significant post-fire strengthening of steel grades belonging to the LDSS group following prior heating at a sufficiently high temperature, as reported earlier by Huang Yuner and B. Young.