Large Wildfires Research Articles

Biodiversity impacts of the 2019-2020 Australian megafires.

With large wildfires becoming more frequent1,2, we must rapidly learn how megafires impact biodiversity to prioritize mitigation and improve policy. A key challenge is to discover how interactions among fire-regime components, drought and land tenure shape wildfire impacts. The globally unprecedented3,4 2019-2020 Australian megafires burnt more than 10 million hectares5, prompting major investment in biodiversity monitoring. Collated data include responses of more than 2,000 taxa, providing an unparalleled opportunity to quantify how megafires affect biodiversity. We reveal that the largest effects on plants and animals were in areas with frequent or recent past fires and within extensively burnt areas. Areas burnt at high severity, outside protected areas or under extreme drought also had larger effects. The effects included declines and increases after fire, with the largest responses in rainforests and by mammals. Our results implicate species interactions, dispersal and extent of in situ survival as mechanisms underlying fire responses. Building wildfire resilience into these ecosystems depends on reducing fire recurrence, including with rapid wildfire suppression in areas frequently burnt. Defending wet ecosystems, expanding protected areas and considering localized drought could also contribute. While these countermeasures can help mitigate the impacts of more frequent megafires, reversing anthropogenic climate change remains the urgent broad-scale solution.

Widespread resilience of animal species, functional diversity, and predator–prey networks to an unprecedented gigafire

Abstract Climate change is altering fire regimes globally, leading to an increased incidence of large and severe wildfires, including gigafires (>100,000 ha), that homogenise landscapes. Despite this, our understanding of how large, severe wildfires affect biodiversity at the landscape scale remains limited. We investigated the impact of a gigafire that occurred during the unprecedented 2019–20 Australian ‘Black Summer’ on terrestrial fauna. We selected 24 study landscapes, each 0.785 km2 in size, that represented a gradient in the extent of high severity fire, unburnt vegetation, and the diversity of fire severity classes (‘pyrodiversity’). We used wildlife cameras to survey biodiversity across each landscape and quantified species activity, community and functional diversity, and predator–prey network metrics. We used Bayesian mixed‐effects models to assess the influence of fire‐induced landscape properties on these measures. Most native species showed resilience to the 2019–20 wildfires, displaying few relationships with fire‐induced properties of landscapes, including the extent of high severity fire, unburnt vegetation, or pyrodiversity. Community and functional diversity and measures of predator–prey networks were also largely unaffected by fire‐induced landscape properties, although landscapes with a greater proportion of high severity fire had higher abundance and richness of introduced animal species. Synthesis and applications: Despite prevailing narratives of widespread ecological destruction following the 2019–20 wildfires, our findings suggest widespread resilience, potentially facilitated by evolutionary adaptations of animals to fire. Interventions aimed at helping such species recover may not be necessary and could instead focus on the subset of species that are vulnerable to severe fire. While mixed‐severity fires are often advocated to promote biodiversity through pyrodiversity, our results suggest that such management efforts might not be necessary in our study region. Given that severe fire favours introduced animal species, invasive species management could focus on large, severely burnt areas.

The Efficacy of Red Flag Warnings in Mitigating Human-Caused Wildfires across the Western United States

Abstract Red flag warnings (RFWs) are issued by the US National Weather Service to alert fire and emergency response agencies of weather conditions that are conducive to extreme wildfire growth. Distinct from most weather warnings that aim to reduce exposure to anticipated hazards, RFWs may also mitigate hazards by reducing the occurrence of new ignitions. We examined the efficacy of RFWs as a means of limiting human-caused wildfire ignitions. From 2006-2020, approximately 8% of wildfires across the western United States, and 19% of large wildfires (≥40 ha), occurred on days with RFWs. Although the occurrence of both lightning- and human-caused wildfires was elevated on RFW days compared to adjacent days without RFWs, we found evidence that modification of short-term behavioral choices on RFW days may reduce the number of certain human-caused ignitions (e.g., debris burning). By contrast, there is limited historical evidence that RFWs reduce the number of ignitions caused by habitual behaviors (e.g., smoking) or infrastructure (e.g., powerlines). Furthermore, the conditional probability of a human-caused wildfire becoming a large wildfire was 33% greater on days with RFWs, underscoring the value of wildfire prevention on these days. While RFWs are helpful in certain cases, our results suggest that their efficacy as a wildfire prevention measure has been somewhat limited in the western United States. As biophysical wildfire potential and the density of people living in wildfire-prone areas increase, so do the benefits of improved wildfire early warning systems that complement other wildfire mitigation and adaptation efforts.

Differential impacts of fire and inundation on a wetland plant community after wildfire

Context Understanding fire and inundation impacts on wetland vegetation communities is crucial for effective post-fire wetland management. Aims We aimed to determine the impact of post-fire inundation on plant community structure and seedling germination and establishment after a large wildfire. We asked two questions, namely (1) did fire, drought or inundation affect plant communities the most; and (2) did fire or inundation affect seedling germination and establishment? Methods Using a before–after–control–impact (BACI) design, we monitored vegetation changes in water-couch wetland communities before and after a wildfire. Also, soil samples were collected from burnt and unburnt sites and assessed for impacts of fire and post-fire inundation regimes on seed germination and seedling establishment. Key results Inundation variables had more pronounced and more consistent impacts on vegetation measures than did fire or drought variables. Fire impacts were mainly short-term, with impact thresholds at 72 and 143 days after fire. Low germination levels and zero seedling survival were observed without inundation. Conclusions Fire was a major but short-term contributor to wetland vegetation change, whereas drought had longer-term impacts, and inundation regimes had the greatest impacts. Implications Providing a range of inundation conditions post-fire may enhance wetland vegetation recovery and have modifying effects on invasive species.

Interpreting the shifts in forest structure, plant community composition, diversity, and functional identity by using remote sensing-derived wildfire severity

BackgroundWildfires are increasingly impacting ecosystems worldwide especially in temperate dry habitats, often interplaying with other global changes (e.g., alien plant invasions). Understanding the ecological consequences of wildfires is crucial for effective conservation and management strategies. The aim of this study was to investigate the impacts of wildfire severity on plant community (both the canopy trees and herbaceous layer) and alien plant invasion, combining field observations and remotely sensed data.We conducted an observational study in the Karst forests (North-East Italy) 1 year after the large wildfire which affected the area in 2022. We assessed the impact through 35 field plots (200 m2 each) distributed among different fire severity (i.e., the loss of organic matter) classes assessed using the differenced normalized burn ratio (dNBR) calculated from satellite images. In each plot, tree species, diameter, vitality, resprouting capacity, and seedling density were measured. In addition, herb species richness (taxonomical diversity) was quantified, and plant cover was visually estimated. Functional diversity was also assessed considering six functional traits retrieved from databases.ResultsSome woody species (e.g., Quercus pubescens) showed a higher resistance to the fire (i.e., lower mortality rate), while others showed a higher resilience (i.e., recovery after fire through resprouting or seedlings, e.g., Cotinus coggygria). The transition to a shrub-dominated community (i.e., Cotinus coggygria) where fire severity was the highest underlines the dynamic nature of the post-fire succession. We detected a significant variation in the herbaceous plant community composition, diversity, and functional identity (i.e., community-weighted mean of trait) along the fire severity gradient. In particular, high-fire severity areas exhibited higher species richness compared to low-severity or unburned areas. Total alien plant cover increased with fire severity, while native cover remained constant. We also found shifts in species that enhance traits related to germination potential and growth strategy.ConclusionsOur results highlight the vulnerability of the forest stands to an increase in wildfire severity, resulting in significant mortality and changes in tree community structure. This study contributes to the understanding of ecological processes after wildfires using a novel remote sensing approach in a temperate forest, emphasizing the need for conservation strategies aimed at mitigating high severity wildfires.

Spatiotemporal patterns and drivers of extreme fire severity in Spain for the period 1985–2018

Extreme fire severity patterns driven by climate change have deep consequences on vegetation, subsequent fire regimes and have consequences on the effectiveness of extinction. In this work, we aimed to determine if extreme fire severity defined as the 90th percentile of RdNBR has changed in Spain in the last 3 decades, if extreme fire severity patterns have differed among the different vegetation types and what drivers have influenced extreme fire severity in both summer and non-summer fires. We have used perimeters of large wildfires (≥100 ha, n = 1719) from 1985 to 2018 in four pyroregions and the main dominant vegetation types. We have analyzed time series for each pyroregion and vegetation type to determine if there were significant trends and breakpoints in extreme fire severity. We have also analyzed the effects of drought, weather, topography and vegetation on extreme fire severity in seasonal wildfires.Extreme fire severity increased in summer fires from 1985 to 2018, especially in the East and North pyroregions, while the Southwest pyroregion reached highest values in summer. There has been an increase of severity in shrubland, mosaic vegetation and conifer forests in summer. Broadleaved forests had the lowest values of fire severity and did not show any trend in the period considered. The most important drivers of extreme fire severity are, in order of importance, pyroregion, elevation, slope, vapor pressure deficit (VPD) and vegetation type for summer fires, and VPD, vegetation types, pyroregion, windspeed and drought for non-summer fires. Global change is increasing climate-related events. Our results indicate that extreme fire severity in summer has been on the rise in recent decades in Spain, suggesting that, in a climate warming context, without strategic management of these increasingly flammable landscapes, further increases may be likely.

Projecting Large Fires in the Western US With an Interpretable and Accurate Hybrid Machine Learning Method

AbstractMore frequent and widespread large fires are occurring in the western United States (US), yet reliable methods for predicting these fires, particularly with extended lead times and a high spatial resolution, remain challenging. In this study, we proposed an interpretable and accurate hybrid machine learning (ML) model, that explicitly represented the controls of fuel flammability, fuel availability, and human suppression effects on fires. The model demonstrated notable accuracy with a F1‐score of 0.846 ± 0.012, surpassing process‐driven fire danger indices and four commonly used ML models by up to 40% and 9%, respectively. More importantly, the ML model showed remarkably higher interpretability relative to other ML models. Specifically, by demystifying the “black box” of each ML model using the explainable AI techniques, we identified substantial structural differences across ML fire models, even among those with similar accuracy. The relationships between fires and their drivers, identified by our model, were aligned closer with established fire physical principles. The ML structural discrepancy led to diverse fire predictions and our model predictions exhibited greater consistency with actual fire occurrence. With the highly interpretable and accurate model, we revealed the strong compound effects from multiple climate variables related to evaporative demand, energy release component, temperature, and wind speed, on the dynamics of large fires and megafires in the western US. Our findings highlight the importance of assessing the structural integrity of models in addition to their accuracy. They also underscore the critical need to address the rise in compound climate extremes linked to large wildfires.

Improving fire severity prediction in south-eastern Australia using vegetation-specific information

Abstract. Wildfire is a critical ecological disturbance in terrestrial ecosystems. Australia, in particular, has experienced increasingly large and severe wildfires over the past 2 decades, while globally fire risk is expected to increase significantly due to projected increases in extreme weather and drought conditions. Therefore, understanding and predicting fire severity is critical for evaluating current and future impacts of wildfires on ecosystems. Here, we first introduce a vegetation-type-specific fire severity classification applied to satellite imagery, which is further used to predict fire severity during the fire season (November to March) using antecedent drought conditions, fire weather (i.e. wind speed, air temperature, and atmospheric humidity), and topography. Compared to fire severity maps from the fire extent and severity mapping (FESM) dataset, we find that fire severity prediction results using the vegetation-type-specific thresholds show good performance in extreme- and high-severity classification, with accuracies of 0.64 and 0.76, respectively. Based on a “leave-one-out” cross-validation experiment, we demonstrate high accuracy for both the fire severity classification and the regression using a suite of performance metrics: the determination coefficient (R2), mean absolute error (MAE), and root-mean-square error (RMSE), which are 0.89, 0.05, and 0.07, respectively. Our results also show that the fire severity prediction results using the vegetation-type-specific thresholds could better capture the spatial patterns of fire severity and have the potential to be applicable for seasonal fire severity forecasts due to the availability of seasonal forecasts of the predictor variables.

Effectiveness of pre-fire forest management on post-fire forest conditions in southeastern Arizona

BackgroundWestern forests in the United States are facing multiple threats that have the potential to permanently alter forest composition and structure. In particular, wildfire can either have beneficial or adverse effects on overall forest health and resilience. Monitoring and assessing the effectiveness of existing forest treatment plans for meeting forest management goals is becoming more critical to increase the capacity for managers to prepare for and accommodate uncertainty associated with changing disturbance regimes. We used a combination of fine-scale vegetation and microclimate surveys on 57 plots, active remotely sensed data (light detection and ranging: LiDAR), and high-resolution satellite imagery to evaluate the effectiveness of an existing management strategy to increase disturbance resistance and resilience of an isolated mixed-conifer forest following a recent large-scale wildfire in southeastern Arizona, USA. We specifically assessed the effectiveness of forest overstory live tree thinning treatments (silviculture) as well as understory fuel reduction treatments (fuel) for influencing post-fire abiotic and biotic conditions, reducing direct post-fire tree mortality, and increasing resilience as compared to untreated forest stands.ResultsWe found that forest silviculture and fuel reduction treatments implemented prior to a large wildfire had mixed results on post-fire fine-scale vegetation composition and structure, microclimate conditions, tree mortality, and tree resilience. Fine-scale vegetation characteristics within silviculture- and fuel-treated forest units displayed higher herbaceous diversity and decreased density of new tree snags as compared to untreated units post-fire. Relevant to seedling emergence, we found that variance in spring soil moisture content was lower overall in treated units; however, units that received overstory thinning (silviculture) treatments were also associated with higher average summer high soil temperatures as compared to untreated units. Additionally, direct tree mortality and rate of recovery of trees post-fire differed between two treatment types (silviculture and fuel reduction) when compared to untreated units and among contrasting levels of burn severity. Post-fire tree mortality and tree resilience did not differ between control and silviculture units; however, these characteristics did differ between control and fuel units. Unlike control units, probability of tree mortality changed little between burn severity categories in fuel treatments (53.4% of mortality occurring in unburned/low vs. 46.7% in moderate/high severity) and resilience increased an average of 2.04% for trees from unburned/low to moderate/high-severity burn categories.ConclusionsOur methodology could be applied to any forested system experiencing increasing intensity and frequency of wildfire. Our results indicate that post-fire forest conditions and resilience are influenced by forest management strategies, particularly fuel reduction treatments. To accommodate uncertainty associated with changing disturbance regimes and climate change, implementing post-fire and post-treatment assessments and monitoring as presented in this study will be essential for developing attainable goals and for maintaining desired forest conditions.

Post‐fire sediment attenuation in beaver ponds, Rocky Mountains, CO and WY, USA

AbstractWe evaluated the post‐fire sediment dynamics in beaver ponds to examine these ponds' contributions to sediment storage following disturbance. Beaver dams and beaver mimicry structures impound water and sediment, a function that is of growing interest in wildfire‐prone landscapes. Wildfires typically lead to high sediment loading into rivers in the years following fire, constituting a disturbance to aquatic ecosystems and a challenge to water resource managers. Previous work establishes that beaver dams trap substantial volumes of sediment, but sedimentation appears spatially and temporally heterogeneous and it remains unclear the extent to which short‐term pulses of sediment are attenuated by these structures. We examine the conditions under which beaver dams and beaver mimicry structures store post‐fire sediment by quantifying the sediment volume of 40 ponds, about half of which were burned in large wildfires in the Colorado and Wyoming Rocky Mountains in 2020. The median relative volume of burned ponds is 85%, which is greater than the median for unburned ponds (58%), meaning that burned ponds store higher relative volumes of sediment when pond size is accounted for. Furthermore, sediment accumulated at a median rate of 3.0 cm/year over the entire history of the pond. Post‐fire sedimentation rates, with a median of 20.4 cm/year, were an order of magnitude higher than pre‐fire rates with a median of 1.8 cm/year. In addition, vegetation and geomorphic characteristics correlated with sediment storage in ponds. Sediment surveys confirmed that ponds with greater surface areas contain higher volumes of sediment. Additionally, older ponds and ponds abandoned by beavers stored higher volumes of sediment compared to recently constructed ponds, ponds actively maintained by beaver, and beaver mimicry structures. These findings demonstrate that beaver ponds and mimicry structures may function as sediment sinks capable of attenuating post‐fire sediment. The biogeomorphic context, defined across multiple scales from the pond to the catchment, provides additional explanation for the wide range of sediment storage observed and remains an important consideration for beaver‐based restoration, catchment sediment management, and resilience evaluation.

Perspective article: Mitigating social and economic impact of wildfires

Wildfires are a natural part of the earth's ecosystem. Over time, the social and economic consequences have significantly increased as development in or near forested areas (i.e. the wildland/urban interface or WUI) has continued, resulting in more value and lives exposed to wildfire events, and due to increasingly large wildfire prone regions and extended seasons caused by changes in the climate. The most significant events are, by some measures, hardly ‘wildland fires’, they are more massive conflagrations affecting communities of burning homes and businesses. The total area around the world that can reasonably be regarded in ‘high fire risk’ is beyond the level of controlled burns, forest thinning, or one-by-one implementation of defensible spaces around structures and homes. Current policies are not effective at the scale of the problem. Better capabilities are needed to provide key decisionmakers including land use planners, building code officials, and wildland managers the right tools to manage this risk. A well designed and governed public private partnership is required. The combustion research community will be at the core of the development that can make it successful, but they will need to band together to bring their numerous individual skills to the table together.

Large wildfires alter the potential capacity of fire-prone Mediterranean pine forests to provide wild edible mushrooms over the long term

Projected trends of intensified wildfires due to climate warming and fuel-load accumulation are expected to significantly alter fungal diversity, but we know little about how these changes will impact ecosystem services. We aimed to analyze how large wildfires alter the capacity of fire-prone Mediterranean ecosystems dominated by Pinus pinaster Ait. to deliver the provisioning ecosystem service of mushroom production throughout the post-fire succession. We assessed this at early (<10 years), medium (10-20 years), and late (>20 years) stages after fire, compared to an unburned forest. Our results evidenced that large wildfires significantly reduced the capacity of these forests to provide mushroom harvesting opportunities. This adverse effect was most pronounced in the first few years after wildfire but persisted even after 20 years of post-fire succession. The total fungal species richness, abundance, diversity, and productivity at the post-fire successional stages remained lower than in the unburned forest, failing to reach their pre-fire levels even after two decades. However, the presence of commercially valuable edible fungal species, along with their species richness and productivity, began to recover in the medium and late stages after fire. In the immediate aftermath of the fire, saprotrophic fungal species dominated, while mycorrhizal species became more prevalent during the medium and late stages of secondary succession. Additionally, the abundance and productivity of mycorrhizal species in the late succession stage approached those found in the unburned forest. Soil pH and biochemical variables (microbial biomass C and β-glucosidase enzymatic activity) were key drivers of changes in species composition along the successional stages. This knowledge is essential to guide management solutions aimed at reducing ecosystem service loss and increasing resilience to the new scenario of extreme large wildfire events at shorter fire-free intervals, especially in southern Europe.

Landcover-categorized fires respond distinctly to precipitation anomalies in the South-Central United States

Satellite detection of active fires has contributed to advance our understanding of fire ecology, fire and climate dynamics, fire emissions, and how to better manage the use of fires as a tool. In this study, we use active fire data of 12 years (2012–2023) combined with landcover information in the South-Central United States to derive a monthly, open-access dataset of categorized fires. This is done by calculating a fire predominance index used to rank fire-prone landcovers, which are then grouped into four main landscapes: grassland, forest, wildland, and crop fires. County-level aggregated analyses reveal spatial distributions, climatologies, and peak fire months that are particular to each fire type. Using the Standardized Precipitation Index (SPI), it was found that during the climatological fire peak-month, the SPI and fires exhibit an inverse relationship in forests and crops, whereas grassland and wildland fires show less consistent inverse or even direct relationship with the SPI. This varied behavior is discussed in the context of landscapes’ responses to anomalies in precipitation and fire management practices, such as prescribed fires and crop residue burning. In a case study of Osage County (OK), we find that large wildfires, known to be closely related to climate anomalies, occur where forest fires are located in the county and absent in areas of grassland fires. Weaker grassland fire response to precipitation anomalies can be attributed to the use of prescribed burning, which is normally planned under environmental conditions that facilitate control and thus avoided during droughts. Crop fires, on the other hand, are set to efficiently burn residue and are practiced more intensely in drier years than in wetter years, explaining the consistently strong inverse correlation between fires and precipitation anomalies. In our increasingly volatile climate, understanding how fires, vegetation, and precipitation interact has become imperative to prevent hazardous fire conflagrations and to better manage ecosystems.

Fire refugia patch dynamics differ between prescribed fires and wildfires in longleaf pine savanna

Increasing wildfire activity has spurred an increasing push for the application of prescribed fire to reduce wildfire risk while simultaneously acting as a surrogate for fire’s historical role as a fundamental ecosystem process. However, prescribed fires are often ignited using uniform ignitions to maintain operational control and there are concerns that they may not be able to replicate the landscape heterogeneity, particularly patterns in unburned patches, generated by historical fires. Fire refugia, unburned areas within fire perimeters, play an integral role in determining post-fire recovery and community structure. We assess patterns in fire refugia across 443 large (>200 ha) wildfire and prescribed fire perimeters using remotely sensed fire severity data in longleaf pine (Pinus palustris) savannas of the Florida Panhandle. Contrary to concerns, large prescribed fires had a significantly greater proportion of unburned area than wildfires, driven by larger refugia patch sizes. Drier conditions promoted smaller and more numerous fire refugia patches. Our study demonstrates differences in wildfires versus prescribed fire outcomes on landscape structure, with implications for future longleaf pine savanna management.

Movement patterns of two northern quolls after a large wildfire

AbstractUnderstanding how animals respond to fire is crucial for conservation efforts in fire‐prone regions across the world. How fire affects animal movement is of particular interest, as it determines access to resources, exposure to risks, and connectivity of populations. We report on observations of the movement patterns and habitat selection of two northern quolls (Dasyurus hallucatus, an endangered marsupial predator), one male and one female, in the Pilbara region of Western Australia. We employed GPS tracking and integrated step selection functions to analyse habitat preferences in relation to fire, and used accelerometry data to assess the energetic costs of using burnt areas. The male northern quoll avoided recently burnt areas, likely due to increased energetic demands and predation risks during the breeding season. In contrast, the female northern quoll neither avoided nor preferred burnt areas, but showed a preference for rocky areas. The female appeared to move through burnt areas to access suitable breeding habitat. The movement patterns observed in the two individuals might reflect a broader pattern of sex‐specific responses to fire, but further research is required to confirm how general the pattern is. Our observations indicate that fire can influence northern quoll movement, with female dependence on rocky areas increasing use of suboptimal habitats, and male avoidance of burnt areas raising potential implications for breeding dispersal and population dynamics. Given the expected increases in fire size and frequency, further research on northern quoll responses to fire in the Pilbara is needed to determine if the pattern we observed is consistent across the broader population.

A Systematic Approach to Map and Evaluate the Wildfire Behavior at a Territorial Scale in the Northwestern Iberian Peninsula

In the current context of extreme wildfires, understanding fire behavior at a territorial level has proven crucial for territory planning. This type of analysis is usually conducted by analyzing past wildfire statistics. In this study, we forego the past information related to wildfires and analyze, instead, the behavior of the entire territory in the face of wildfires. This allows for the distribution of ignition points to be systematized and for typical and atypical weather scenarios to be considered. This analysis relies on the use of wildfire simulation software. Ignition points used for the simulations were distributed using a systematic 1 × 1 km grid throughout the whole study area. Wildfires were simulated for each ignition point using eight different weather scenarios representing both typical and atypical weather conditions. The fire behavior on the territory was analyzed using rate of spread and intensity parameters for each simulated wildfire. It was observed that this territory is extremely prone to large wildfires both in typical and atypical weather conditions and that there is a tendency for extreme behaviors to develop. Some features were identified as prevention issues that ought to be addressed. This study develops a strategy to evaluate, in a systematic manner, the response of the territory to the threat of wildfires.

Post-Fire Vegetation (Non-)Recovery across the Edges of a Wildfire: An Unexplored Theme

Wildfires have a significant influence on ecosystems globally, shaping vegetation, biodiversity, landscapes, soil properties, and other ecosystem processes. Despite extensive research on different aspects of wildfires, the edges of burned areas remain understudied, even though they involve complex dynamics. In this study, we analyzed the post-fire vegetation recovery across the edges of a large wildfire in a Mediterranean area. The investigations were focused on patches of woodlands that, in a previous study, showed a normalized burn ratio (NBR) decline one year after the fire. Field vegetation surveys were carried out in areas characterized by different NBR recovery rates and in areas outside the burned area as controls. Five hypotheses were tested, identifying delayed tree mortality as a key factor linked to NBR decline, particularly in low-severity fire zones in proximity to the fire edges. Delayed mortality, observed predominantly near the edges, may also affect unburned or less severely burned patches within the main fire perimeter, highlighting the need for ongoing monitoring. As these areas play a crucial role in the post-fire succession and vegetation dynamics, understanding the second-order effects of a fire is imperative for effective ecosystem management. This study underscores the importance of the long-term assessment of fire impacts, emphasizing the necessity of field surveys alongside remote sensing. Continued observation is essential to elucidate the enduring impacts of wildfires and to facilitate informed restoration strategies.

The influence of burn severity on dissolved organic carbon concentrations across a stream network differs based on seasonal wetness conditions

Abstract. Large, high-severity wildfires in many regions across the globe have increased concerns about their impacts on carbon cycling in watersheds. Altered sources of carbon and changes in catchment hydrology after wildfire can lead to shifts in dissolved organic carbon (DOC) concentrations in streams, which can have negative impacts on aquatic ecosystem health and downstream drinking-water treatment. Despite its importance, post-fire DOC responses remain relatively unconstrained in the literature, and we lack critical knowledge of how burn severity, landscape elements, and climate interact to affect DOC concentrations. To improve our understanding of the impact of burn severity on DOC concentrations, we measured DOC at 129 sites across a stream network extending upstream, within, and downstream of a large, high-severity wildfire in Oregon, USA. We collected samples across the study sub-basin during four distinct seasonal wetness conditions. We used our high-spatial-resolution data to develop spatial stream network (SSN) models to predict DOC across the stream network and to improve our understanding of the controls on DOC concentrations. Spatially, we found no obvious wildfire signal – instead, we observed a pattern of increasing DOC concentrations from the high-elevation headwaters to the sub-basin outlet, while the mainstem maintained consistently low DOC concentrations. This suggests that effects from large wildfires may be “averaged” out at higher stream orders and larger spatial scales. When we grouped DOC concentrations by burn severity group, we observed a significant decrease in the variability of DOC concentrations in the moderate and high burn severity sub-catchments. However, our SSN models were able to predict decreases in DOC concentrations with increases in burn severity across the stream network. Decreases in DOC concentrations were also highly variable across seasonal wetness conditions, with the greatest (−1.40 to −1.64 mg L−1) decrease occurring in the high-severity group during the wetting season. Additionally, our models indicated that in all seasons, baseflow index was more influential in predicting DOC concentrations than burn severity was, indicating that groundwater discharge can obscure the impacts of wildfire in a stream network. Overall, our results suggested that landscape characteristics can regulate the DOC response to wildfire. Moreover, our results also indicated that the seasonal timing of sampling can influence the observed response of DOC concentrations to wildfire.

Numerical analysis of transient soil temperature variation during wildfires

In this study, transient behavior of soil temperature during large forest fires is analyzed using the Comsol© software package. The increase in soil temperature during large wildfires can be very critical, especially when oil or gas pipelines have been laid at a certain depth in the soil mainly near forests. During forest fires, the temperature of the soil surface can reach extreme levels that penetrate deep into the ground if the fire is not extinguished within a short time. This increase in temperature on the soil surface can lead to extremely dangerous situations if the laying depth of the pipeline is not sufficient, as the heat conducted through the soil causes the surface temperature of the pipeline and therefore that of the fluid inside it to reach even high values. This can lead to a sudden rupture of the pipeline and ultimately lead to catastrophic consequences. The present study is conservative due to the assumptions made in structuring the numerical model. However, it is believed to provide invaluable information about the considerations in selecting gas pipeline locations and pipeline laying depths taking into account extreme temperatures due to wildfires. There is limited research on the topic regarding the time dependent conduction heat transfer through soils as a result of fires, but only in one dimension. Current study, being multi-dimensional, is therefore believed to be novel in the field. Future research could include extensive study on the energy content of different species of forest trees, considering their time-dependent heat release rates (HRR) during a forest fire, as well as experimental work if a field setup could be designed.

Influence of wildfires on the conflict (2006–2022) in eastern Ukraine using remote sensing techniques (MODIS and Sentinel-2 images)

Humans primarily alter fire regimes in three ways: changing the distribution and density of ignitions, shifting the seasonality of burning, or altering available fuels. Remote sensing techniques are a highly feasible and effective tool for monitoring wildfires, delineating burn perimeters, describing patterns of fire occurrence, characterizing the degree of intensity, or fire risk mapping. In this study MODIS and Sentinel-2 satellite images were used to analyze the burned areas in the Luhansk and Donetsk Regions of Ukraine (2006–2022), and specifically how the political and military hostilities in 2014 impacted fire activity. The burned areas detected by the MODIS sensor were selected using a size (32 ha) and temporal (May–October) filter. The Relativized Burn Ratio (RBR) index was used to identify burned areas, while the Normalized Difference Water Index (NDWI) was employed to discriminate the water bodies in Sentinel-2 images. We analyzed the burned area data over the 17-year period, eight of them during the years before the conflict and the other nine after the conflict. The results show that burned area has increased from the pre-conflict period (2008–2013) by 689,898 ha to the post-conflict period (2014–2022) around the contact line. In addition, the frequency of fires has increased in the post-war period, especially towards the south of Donetsk. Finally, Sentinel-2 imagery was used to map Large Wildfires (LAWF), which means fires with a burned area >500 ha. Our study concluded that MODIS MCD64A1 underestimates the burned area with a recorded difference of up to 40% of the area in one of the analyzed fires. In addition, an analysis of the burned areas classified according to the main land use has been performed for both sensors. The results obtained show a regression for the total area of R2 = 0,97 and both sensors show high correlation between them for each land use analyzed. Grasslands and agricultural land covers were most affected by LAWFs during the conflict period (2014–2022), noting that fires near urban entities were also more frequent in the war period.