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The growing frequency, extent and severity of wildfire is destabilizing carbon sinks in western North America, underscoring an urgent need to better understand fire impacts on soil carbon stocks, carbon stability, and fungi that regulate soil carbon cycling. Here, we examined the effects of wildfire two years post-burn on soil carbon and fungal communities across a fire severity gradient in Douglas-fir forests in central British Columbia, Canada. We observed no significant differences in soil carbon or fungal community composition between low-severity and unburned stands. In contrast, high-severity wildfire resulted in a 49 % reduction in belowground carbon stocks (20.7 Mg C·ha−1), a 91 % decline in ectomycorrhizal fungi, 5- to 27-fold increases in pathogenic fungi, and a proliferation of pyrophilous taxa compared to unburned stands. Carbon was lost primarily as light particulate organic matter, whereas impacts to mineral-associated carbon were muted. Pyrogenic carbon preferentially associated with the mineral fraction, modestly increasing (∼0.15 Mg C·ha−1) the proportion of carbon resistant to decay in this stable fraction. Select helotialean (e.g. Phialocephala fortinii) and other pyrophilous taxa were well-correlated with pyrogenic carbon, suggesting this consortium is well-adapted to decompose persistent carbon and will likely continue to mineralize soil carbon even after high severity wildfire. The markedly higher abundance of pathogenic fungi and reduced ectomycorrhizal abundance in stands affected by high-severity fires pose risks to post-fire recovery, particularly if pathogen proliferation reduces conifer fitness. These results highlight that low-severity wildfires have comparatively muted impacts on soil carbon and fungal communities relative to high-severity wildfires, underscoring the importance of management strategies such as thinning and prescribed burns to mitigate the catastrophic effects of high-severity wildfires.

Forest fires are the main threat to ecosystems and human life. The frequency, seasonality, extent and severity of fires affect ecosystems and the physical and chemical properties of the soil by direct (heating) and indirect (ash) effects. This could affect biodiversity and forest residency in the face of climate change. In this study, we evaluated the impact of fire severity on soil physical and chemical properties caused by forest fires in a high Andean area of Peru. For this purpose, the severity levels, the degree of hydrophobicity, and the physical and chemical properties of the soil were analyzed by sampling in affected areas (Pinus radiata D. Don plantation and shrubland) and unaffected areas. The results showed a very low severity in soil components, with a strong hydrophobicity, more persistent in the forest plantation area than in the shrubland. The physical properties of the soil did not show variations; however, in the Pinus plantations they showed variations in their chemical properties such as pH, electrical conductivity, organic matter, nitrogen and cation exchange capacity compared to areas not affected by the forest fires. Likewise, in the study area an adequate regeneration process was evidenced; in fact, it is important to apply mechanisms to accelerate the restoration of the vegetation cover and the physical and chemical quality of the vegetation.

The area burned in Spain exceeded historical records in 2022, when exceptionally warm conditions influenced wildfire events. The predicted intensification of wildfire regimes includes an increase in frequency, severity, and size. Therefore, a study of the wildfires that occurred in 2022 is necessary to understand their behaviour and possible environmental impacts. The objective of this study is to analyse the applicability of using spectral indices and Geographic Information System (GIS) approaches to map the spatial distribution and estimate potential soil losses using Sentinel-2 imagery and fire severity field data. Soil losses were estimated using an empirical model based on soil burn severity data collected in the field after wildfire. The relationship between the Normalized Difference Infrared Index (NDII), Difference Normalized Wildfire Ash Index (dNWAI), and the Blue Normalized Difference Vegetation Index (BNDVI) with the estimated soil losses was then evaluated. In addition, the influence of different time scales of the satellite images was analysed. The first period considered (Date I) ranges from 8 to 20 days after the beginning of the wildfire, which coincides with the field data collection. The second period considered (Date II) ranges from 28 to 35 days after the start of the wildfire. The results obtained showed a significant dependence relationship between the BNDVI index (using satellite images of Date I) and the estimated soil losses (R2 = 0.756), while the results of the NDII (R2 = 0.31) and dNWAI (R2 = 0.061), showed no spatial relationship with the estimated soil losses. Three of the largest wildfires in 2022 in Spain were analysed, and the results showed strong correlations of BNDVI index for Folgoso do Courel (R2 = 0.808), for Carballeda de Valedorras (R2 = 0.906), and for Sierra de la Culebra (R2 = 0.939). In addition, these results allowed the mapping and quantification of potential soil losses in areas where fire severity was high, totalling ∼2,50,000 Mg ha−1 in Folgoso do Courel, ∼3,70,000 Mg ha−1 in Carballeda de Valdeorras, and ∼4,70,000 Mg ha−1 in Sierra de la Culebra. Moreover, BNDVI values for estimating soil loss vary by vegetation type, and there is a positive correlation between severity classes and the BNDVI index. This approach can inform post-fire land management decisions in future wildfires and could be applied to other regions.

The Hengduan Mountains in Southwest China are currently facing a recurring and escalating threat of forest fires, posing a significant challenge to vegetation restoration efforts given the ecological value of this region. However, the effects of artificial restoration compared to natural regeneration on vegetation recovery dynamics have been less explored. This study focused on two sites in the Hengduan Mountains, primarily composed of conifer forests. One site employed a mix of artificial restoration measures, including tree planting, aerial grass seeding, and fertilizer application. The other site, which is relatively drier and colder, relied on natural regeneration. Four fire events in these two sites were compared to examine the effects of artificial restoration on vegetation recovery using remotely sensed data from Landsat and MODIS. Fire severity was classified using the differenced Normalized Burn Ratio (dNBR) and validated with field samples. Vegetation greenness loss and recovery trajectory were quantified using the near-infrared reflectance of vegetation (NIRv). The effects of artificial restoration were further analyzed after employing unburnt controls to minimize the impact of climate fluctuations. Results showed that fire severity mapping achieved an overall accuracy of 82%. The average NIRv loss across the four fires was 30%, 49%, and 69% in areas of low, moderate, and high severity, respectively. In low severity areas, natural and artificial recovery rates were similar, at 21% and 26% respectively, three years post-fire. In moderate severity areas, artificial restoration achieved a 46% recovery rate compared to 31% for natural recovery. In high severity areas, artificial restoration resulted in a 63% recovery rate versus 45% for natural recovery. Although the differences in recovery patterns may also be attributed to inherent variations in the vegetation composition, physical environment, and their interactions, this study suggests that high severity areas benefit significantly from artificial intervention for rapid recovery. Future studies should include more controlled experiments at the plot scale to further elucidate the processes of vegetation response to different artificial restoration measures.

Bushfires are a natural component of the ecology of many landscapes, but megafires such as those experienced in Australia between July 2019 and April 2020 have substantial direct and indirect impacts on wildlife. Following these megafires, bushfires have begun to be considered a significant emerging threat to the vulnerable grey-headed flying-fox (Pteropus poliocephalus). In this study, we quantified the impact of the 2019–20 megafires on all known roost locations of the species by (1) determining the number of roosts within burnt areas represented by three fire severity mapping products, (2) classifying burnt roosts according to the severity with which they burnt, and (3) examining the distribution of distances to the nearest burnt areas for unburnt roosts. Our findings indicate that the impacts of the 2019–20 megafires on roosting habitat of the grey-headed flying-fox have hitherto been underestimated. Of 874 known grey-headed flying-fox roosts, we found that 134 roosts were situated within burnt areas, equating to 15 % of the species’ roost locations. Depending on the mapping products applied, part or all canopy vegetation was severely burnt in 27–36 % of burnt roosts, while in 11–14 % of burnt roosts, the canopy vegetation was burnt entirely. Of the 740 unburnt roosts, 50 % were located within 6.85 km from burnt areas, suggesting that, at a substantial number of roosts, flying-foxes were also indirectly affected by the fires, through the effects of smoke on roosting and locally foraging individuals, and through destruction of local foraging resources from burning. We discuss the implications of these findings for the conservation management of this vulnerable species.

Precise quantification of forest fire impacts is critical for management strategies in support of post-fire mitigation. In this regard, optical remote sensing imagery in combination with spectral unmixing has been widely used to measure fire severity by means of fractional cover of photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV), charcoal (CH) and further ground components such as ash, bare soil and rocks. However, most unmixing analyses have made use of a single post-fire image without accounting for the pre-fire state. We aim to assess fire severity from Sentinel-2 data using a bi-temporal spectral unmixing analysis that provides a quantitative fire impact description and is oriented towards the process of change by including pre-fire and post-fire information. Unmixing was based on Random Forest Regression (RFR) modeling using synthetic training data from a bi-temporal spectral library. We describe fire severity as changes associated with the combustion of photosynthetic vegetation (PV–CH fraction) and dieback of photosynthetic vegetation (PV-NPV fraction). Unburned forest was mapped as stable photosynthetic vegetation (PV-PV fraction). We evaluated our approach on a forest fire that burned in a temperate forest region in eastern Germany in 2018. Independent validation was carried out based on reference fractions obtained from very high-resolution (VHR) imagery such as Plante Scope, SPOT6, orthophotos, aerial photos, and Google Earth. The results underline the effectiveness of our unmixing approach, with Root Mean Squared Errors (RMSE) of 0.072 for PV-CH, 0.09 for PV-NPV, and 0.08 for PV-PV fractions. Most of the errors were caused by spectral similarity between charcoal and shadow effects caused by trees, and the coloring of foliage and NPV in the late phenological season of the post-fire Sentinel-2 image. Based on the two-dimensional feature space of PV-CH and PV-NPV fractions, we calculated two metrics to characterize fire impacts: distance, an indicator of disturbance severity (sum of combustion and dieback), and angle, a measure of disturbance composition (gradient between combustion and dieback). Furthermore, we compared the fraction-based metrics with the difference Normalized Burn Ratio (dNBR). Since the dNBR is most sensitive to combustion and presence of charcoal, it does not fully characterize fire-related vegetation loss associated with dieback. The bi-temporal fraction-based indices provide more ecologically meaningful information on fire severity, particularly for regions that are less prone to severe wildfires such as Central Europe.

The impacts of fires on society and the environment are wide-ranging, and examining such fire incidents is of critical importance to communities, governments, and scientists. Satellite imagery analysis enables the monitoring of burned scars and can help us better understand the social, ecological, and economic consequences of fires in more detail. However, most satellite studies measuring fire area and impacts focus on large areas in natural landscapes, typically forests. We highlight the need to develop methods for fire detection and analysis in human-dominated landscapes, specifically, such vulnerable populations as those found in refugee camps globally. We calculate a suite of spectral indices (SI’s) developed from Sentinel-2 data with a random forest algorithm to quantify the fire impact on the Rohingya refugee camps in Teknaf, Bangladesh. For this study, we developed a method called the Fractional Charred Index (FCI) using the field plots within the burn areas inside the refugee camp settlements and compared the FCI with differenced Spectral Indices (dSI’s) to quantitively assess the burn severity at four levels: (i) high severity, (ii) moderate severity, (iii) low severity and (iv) unburned camp. Our study identified 140 acres of burn area, damaging over 8,000 refugee shelters, 1,760 of which were severely damaged and 3,452 of which suffered moderate damage. The FCI-dSIs relationship was measured by a simple linear model which indicated that the differenced Normalized Burned Index (dNBR) and the differenced Char Soil Index (dCSI) have the strongest positive correlation and can be used interchangeably to assess the scale and intensity of the fire-caused damage and fire severity assessment in this and similar types of case studies. The novel method presented here to determine fire severity in human-dominated landscapes, specifically refugee camps, may be quickly deployed and is easily interpretable and computationally inexpensive. Therefore, the proposed method of identifying burned settlements in refugee camps has significant potential for impact monitoring, disaster management, and recovery efforts after such fire events.

As a result of extreme weather conditions associated with anthropogenic climate change, fire regimes are expected to continue to change in the boreal forest over the 21st century and beyond. Consequently, changes in ecological attributes like stand composition, tree density and forest carbon stock can be expected. In the present study, we used an adjusted version of the CanFIRE model to project long-term (1971–2100) changes in burn rates, fire severity and fire-induced shifts in vegetation composition in response to anticipated scenarios of climate change, in the black spruce-feather moss subdomain of Western Quebec. The model provides decadal-scale estimates of the immediate physical effects of fire on forest communities by computing expected fire behavior and the resulting ecological effects. Changes in species composition of the forest is also computed based on mechanisms of succession in natural forest communities and fire-mediated vegetation transitions. Projections suggest an increase in potential burn rates across the study area under future weather conditions and also an overall reduction in percent tree mortality and total fuel consumption. This reduction is caused by negative feedback from vegetation composition that shifts to less-fire prone states. Although common forest communities will remain the same in the studied subdomain until 2100 (recurrence dynamics), significant losses of productive area (LPA) are projected, particularly in forest management units rich in forest communities dominated by black spruce or jack pine, as a result of regeneration failure due to very short intervals between successive fires. While remaining similar under moderate (RCP4.5) and high-end (RCP8.5) warming scenarios in all forest management units, LPA will vary from 25 to 36% of the percent cover by 2100 compared to 1970. These results provide insights to policy makers and land managers, and they attract attention to the pressing need to adjust management practices in the context of climate change.

The increasing threat of high-severity wildfires in Mediterranean Wildland-Urban Interface (WUI) areas demands to develop effective fire risk assessment and management strategies. Simultaneously, the newfound accessibility of spaceborne hyperspectral data represents a significant potential for generating fire severity assessments, whereas National Forest Inventories (NFI) offer a vast dataset related to vegetation and fuel loads, which is essential for shaping the planning and strategies of forest services. This research work aims to advance the state-of-the-art in WUI fire risk mapping in the western Mediterranean Basin by combining PRISMA spaceborne hyperspectral data and Spanish NFI data. The proposed methodology had three main stages: (i) fire severity assessment at local scale (a wildfire) by using PRISMA hyperspectral data and Multi-Endmember Spectral Mixture Analysis (MESMA) leveraging field-based measurements of the Composite Burn Index (70 plots); (ii) development of a high fire severity probability map at regional scale from the extrapolation of a Random Forest predictive model calibrated from fire severity estimates, NFI data and topo-climatic variables at local scale (overall accuracy = 92 %; Kappa = 0.8); and (iii) identification and characterization of zones that concentrate WUIs with high probability of high fire severity if a fire event occurs (hot-spot WUIs) by crossing the information from the previous regional high fire severity probability map and a WUI cartography developed at regional scale. Study area was Castilla y León Autonomous Region (larger Spanish region, 94,226 km 2 ), where the second-largest extreme Spanish wildfire event (28,000 ha) occurred. We identified hot-spot WUIs so that stakeholders and decision-makers could (i) prioritize resources and interventions for effective fire management and mitigation, (ii) allocate resources for prevention, and (iii) plan evacuation measures to safeguard lives and property. This study contributes to the development of next-generation fire risk assessment methods that combine remote sensing technologies with comprehensive ground-level datasets., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Central Chile experienced a very extended and devastating fire season during 2016–17. After 3 years, here we present the results of an analysis of behavior of the wildfires occurred in that season. We used a modeling approach to estimate the physical parameters of fire behavior: speed of linear spread, front-line intensity and flame length; as well as qualified fire severity, and the potential danger of recurrent fires. We selected eight study areas in four regions of Central Chile, under sclerophyllous forest and shrublands with variable composition. To run the model, we gathered data on vegetation structure and composition, and physical information. The values of the physical parameters were in a comparable range in the eight studied areas, with two of these areas showing maximum values. This could result from differences in vegetation. We detected rapid regrowth post-fire, despite the high levels of fire intensity and damage, ascribed to a high availability of very dry fine biomass. Given the predictions of increased drought, we should expect recurrence of wildfires. Based on our results, we anticipate fires of high severity and damage, with emphasis in areas with very high increase of dry biomass. We suggest restoration programs, with frequent monitoring of passive restoration practices, resorting to more active physical support in areas more severely affected.

Plant phenology describes the timing of reproductive events including flowering and fruiting, which for many species are affected by fire disturbance. Understanding phenological responses to fire provides insights into how forest demographics and resources may shift alongside increasing fire frequency and intensity driven by climate change. However, isolating the direct effects of fire on a species' phenology and excluding potential confounders (e.g. climate, soil) has been difficult due to the logistical challenges of monitoring species-specific phenological events across myriad fire and environmental conditions. Here, we use CubeSat-derived crown-scale flowering data to estimate the effects of fire history (time since fire and fire severity over a 15-year time span) on flowering of the eucalypt Corymbia calophylla across a Mediterranean-climate forest (814km 2 ) in southwest Australia. We found that fire reduced the proportion of flowering trees at the landscape-scale, and flowering recovered at a rate of 0.15 % (±0.11% SE) per year. Further, this negative effect was significant due to high crown scorch fires (>20% canopy scorch), yet there was no significant effect from understory burns. Estimates were obtained using a quasi-experimental design which identifies the effect of time since fire and severity on flowering by comparing proportional flowering within target fire perimeters (treatment) and adjacent past fire perimeters (control). Given the majority of fires studied were managed fuel reduction burns, we applied the estimates to hypothetical fire regimes to compare flowering outcomes under more or less frequent prescribed burning. This research demonstrates the landscape-scale effects of burning on a tree species' reproduction, which could broadly impact forest resiliency and biodiversity., Competing Interests: Declaration of competing interest The work described here has not been published previously. It is not under consideration for publication elsewhere, that its publication is approved by all authors and tacitly or explicitly by the responsible authorities where the work was carried out, and that, if accepted, it will not be published elsewhere in the same form, in English or in any other language, including electronically without the written consent of the copyright-holder., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Wildfire regimes affected by global change have been the cause of major concern in recent years. Both direct prevention (e.g., fuel management planning) and land governance strategies (e.g., agroforestry development) can have an indirect regulatory effect on wildfires. Herein, we tested the hypothesis that active land planning and management in Italy have mitigated wildfire impacts in terms of loss of ecosystem services and forest cover, and burned wildland-urban interface, from 2007 to 2017. At the national scale, we assessed the effect size of major potential fire drivers such as climate, weather, flammability, socio-economic descriptors, land use changes, and proxies for land governance (e.g., European funds for rural development, investments in sustainable forest management, agro-pastoral activities), including potential interactions, on fire-related impacts via Random Forest modelling and Generalized Additive Mixed Model. Agro-forest districts (i.e., aggregations of neighbouring municipalities with homogeneous forest and agricultural characteristics) were used as spatial units of analysis. Our results confirm that territories with more active land governance show lower wildfire impacts, even under severe flammability and climatic conditions. This study supports current regional, national, and European strategies towards "fire resistant and resilient landscapes" by fostering agro-forestry, rural development, and nature conservation integrated policies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Characterizing the fire regime in regions prone to extreme wildfire behavior is essential for providing comprehensive insights on potential ecosystem response to fire disturbance in the context of global change. We aimed to disentangle the linkage between contemporary damage-related attributes of wildfires as shaped by the environmental controls of fire behavior across mainland Portugal. We selected large wildfires (≥100 ha, n = 292) that occurred during the 2015-2018 period, covering the full spectrum of large fire-size variation. Ward's hierarchical clustering on principal components was used to identify homogeneous wildfire contexts at landscape scale on the basis of fire size, proportion of high fire severity, and fire severity variability, and their bottom-up (pre-fire fuel type fraction, topography) and top-down (fire weather) controls. Piecewise Structural Equation Modeling was used to disentangle the direct and indirect relationships between fire characteristics and fire behavior drivers. Cluster analysis evidenced severe and large wildfires in the central region of Portugal displaying consistent fire severity patterns. Thus, we found a positive relationship between fire size and proportion of high fire severity, which was mediated by distinct fire behavior drivers involving direct and indirect pathways. A high fraction of conifer forest within wildfire perimeters and extreme fire weather were primarily responsible for those interactions. In the context of global change, our results suggest that pre-fire fuel management should be targeted at expanding the fire weather settings in which fire control is feasible and promote less flammable and more resilient forest types., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

The American Southwest is experiencing drastic increases in aridity and wildfire incidence, triggering conversion of some frequent surface forests to non-forest. Extensive research has focused on these dynamics in regional ponderosa pine forests, but we know much less about Madrean pine-oak forests, which are broadly distributed from the Sierra Madre in Mexico to the Sky Island mountain ranges in the U.S. Increased fire incidence and drought in these forests are limiting pine regeneration and driving conversion of biodiverse forests to oak shrublands. We investigated regeneration patterns in Pinus engelmannii and P. leiophylla during severe drought 10 years after the Horseshoe Two Megafire in the Chiricahua Mountains, Arizona-a follow-up to an assessment five years post-fire. In long-term plots, we examined changes in pine seedling and resprout recruitment. Past research demonstrated that topography and fire severity influenced pine recruitment across environmental gradients. We investigated here whether Landsat-8 normalized difference vegetation index (NDVI) and evapotranspiration estimated by the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) added explanatory value to our understanding of these patterns. Conversion of Madrean pine-oak forest to oak shrublands continued 6-10 years post-fire. A dense, low oak canopy continued to coalesce in sites subject to severe fire. The importance of resprouts in P. leiophylla regeneration accelerated because these plants outgrew competing oak resprouts. Topography and fire severity (dNBR) were important predictors of 2021 patterns of pine recruitment. NDVI added explanatory value to these models, suggesting its potential in tracking forest dynamics. Evapotranspiration did not add value, likely because ECOSTRESS' larger pixel sizes and moving pixel locations created excessive subpixel heterogeneity in this highly dissected landscape. These models suggest that P. engelmannii is more drought sensitive, was more negatively affected by drought and fire, and is more at risk to shifts in climate and wildfires than P. leiophylla., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

The large environmental and socioeconomic impacts of wildfires in Southern Europe require the development of efficient generalizable tools for fire danger analysis and proactive environmental management. With this premise, we aimed to study the influence of different environmental variables on burn severity, as well as to develop accurate and generalizable models to predict burn severity. To address these objectives, we selected 23 wildfires (131,490 ha) across Southern Europe. Using satellite imagery and geospatial data available at the planetary scale, we spatialized burn severity as well as 20 pre-burn environmental variables, which were grouped into climatic, topographic, fuel load-type, fuel load-moisture and fuel continuity predictors. We sampled all variables and divided the data into three independent datasets: a training dataset, used to perform univariant regression models, random forest (RF) models by groups of variables, and RF models including all predictors (full and parsimonious models); a second dataset to analyze interpolation capacity within the training wildfires; and a third dataset to study extrapolation capacity to independent wildfires. Results showed that all environmental variables determined burn severity, which increased towards the mildest climatic conditions, sloping terrain, high fuel loads, and coniferous vegetation. In general, the highest predictive and generalization capacities were found for fuel load proxies obtained though multispectral imagery, both in the individual analysis and by groups of variables. The full and parsimonious models outperformed all, the individual models, models by groups, and formerly developed predictive models of burn severity, as they were able to explain up to 95%, 59% and 25% of variance when applied to the training, interpolation and extrapolation datasets respectively. Our study is a benchmark for progress in the prediction of fire danger, provides operational tools for the identification of areas at risk, and sets the basis for the design of pre-burn management actions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Wildfires have large-scale and profound effects on forest ecosystems, and they force burned forest areas toward a wide range of post-fire successional trajectories from simple reduction of ecosystem functions to transitions to other stable non-forest states. Fire disturbances represent a key driver of changes in forest structure and composition due to post-fire succession processes, thus contributing to modify ecosystem resilience to subsequent disturbances. Here, we aimed to provide useful insights into wildfire severity and post-fire recovery processes at the European continental scale, contributing to improved description and interpretation of large-scale wildfire spatial patterns and their effects on forest ecosystems in the context of climate change. We analyzed fire severity and short-term post-fire vegetation recovery patterns across the European forests between 2004 and 2015 using Corine Land Cover Forest classes and bioregions, based on MODIS-derived spectral metrics of the relativized burn ratio (RBR), normalized difference vegetation index (NDVI) and relative recovery indicator (RRI). The RBR-based fire severity showed geographic differences and interannual variability in the Boreal bioregion compared to that in other biogeographic regions. The NBR-based RRI showed a slower post-fire vegetation recovery rate with respect to the NDVI, highlighting the differential sensitivities of the analyzed remote sensing-spectral metrics. Moreover, the RRI showed a significant decreasing trend during the observation period, suggesting a growing lag in post-fire vegetation recovery across European forests., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

The effect of fire severity and recurrence on the recovery of enzymatic activities (β-glucosidase, urease, acid phosphatase) and bacterial activity was monitored. Unburned and burned soil samples from soil affected by a high severity wildfire and by a low severity experimental fire were subjected in laboratory to a temperature gradient to simulate different fire severities. These samples were subjected to a second laboratory heat treatment to simulate the effect of recurrence. Soil temperature was measured and used to calculate the degree-hours reached by the soil. The results showed: a) a strong effect of repeated soil heating at different temperatures on soil microbial activity; b) a different sensitivity of enzymatic activities and bacterial activity to fire, c) the magnitude of changes in these biochemical properties was related to the extent of heat supplied to samples and the previous fire/heat history, and d) degree-hours are adequate to quantify the severity of heat treatments and to examine their effects on soil microbial activity. The relationships between degree-hours and the different biochemical properties analyzed clearly demonstrate that the usefulness of these biochemical properties to detect the soil microbial community response to the heat stress followed the order: urease activity > acid phosphatase activity > β-glucosidase activity ≫ bacterial activity., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.)

This study describes a multivariate statistical model (derived using partial least squares regression, PLS-R) that derives charring intensity (reaction temperature and duration) from the attenuated total reflectance (ATR) Fourier Transform Infrared (FTIR) spectra of charcoal. Data for the model was obtained from a library of charcoal samples produced under laboratory conditions at charring intensities (CI) relevant to wildfires and a series of feedstocks representing common tree species collected from Australia. The PLS-R model developed reveals the potential of FTIR to determine the charring intensity of charcoal. Though limited by the differences between laboratory-produced charcoal and the more heterogeneous and less-structured charcoal produced in a wildfire, the method was tested against fossil charcoal from a well-dated sediment core collected from Thirlmere Lakes National Park, Australia and showed a distinct change in CI that can be related to other climatic and environmental proxies. We suggest that the method has the potential to offer insights into the conditions under which natural charcoal is formed including the modelling of charring intensities of fossil charcoal samples isolated from sediments, archaeological applications or characterisation of contemporary fire events from charcoal in soils., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Chilean territory is recurrently affected by severe wildfires, which drastically reduce the forest cover and promote runoff, soil erosion and slope instabilities. To understand how the geomorphic system responds to wildfires in terms of sediment dynamics, the assessment of sediment connectivity, i.e. the property describing the relationships between compartments of a geomorphic system, is crucial. This study aims to quantify the spatial linkages between fire severity and sediment connectivity to identify common patterns and driving factors. The compound use of field data and open-source satellite imagery helped to apply the Relative differenced Normalized Burn Ratio (RdNBR) and the Index of Connectivity (IC) in the context of two consecutive wildfires, occurred in 2002 and 2015, in the Rio Toro catchment (Chile). The fire severity assessment showed that the 2002 event affected 90% of the catchment, with high severity areas representing around 70%. The 2015 wildfire instead, affected 76% of the catchment with moderate severity around 42%. Accordingly, as result of the sudden reduction in forest cover in severely affected areas, the IC changed after both wildfires with an overall increase of 1.07 and 0.54, respectively. However, only for the second disturbance, it was possible to observe a clear relationship between the RdNBR and the IC variations. The different degree of vegetation cover heterogeneity between the two pre-wildfire scenarios contributed to different fire severity and IC variability between the two disturbances. The use of open-source satellite data and the development of a weighting factor (W), to be used in IC and able to capture the land cover change driven by the wildfires, could make the application of this approach straightforward, promoting its reproducibility in other catchments for land management and risk mitigation purposes., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Wildfires strongly regulate carbon (C) cycling and storage in boreal forests and account for almost 10% of global fire C emissions. However, the anticipated effects of climate change on fire regimes may destabilize current C-climate feedbacks and switch the systems to new stability domains. Since most of these forests are located in upland soils where permafrost is widespread, the expected climate warming and drying combined with more active fires may alter the greenhouse gas (GHG) budgets of boreal forests and trigger unprecedented changes in the global C balance. Therefore, a better understanding of the effects of fires on the various spatial and temporal patterns of GHG fluxes of different physical environments (permafrost and nonpermafrost soils) is fundamental to an understanding of the role played by fire in future climate feedbacks. While large amounts of C are released during fires, postfire GHG fluxes play an important role in boreal C budgets over the short and long term. The timescale over which the vegetation cover regenerates seems to drive the recovery of C emissions after both low- and high-severity fires, regardless of fire-induced changes in soil decomposition. In soils underlain by permafrost, fires increase the active layer depth for several years, which may alter the soil dynamics regulating soil GHG exchange. In a scenario of global warming, prolonged exposition of previously immobilized C could result in higher carbon dioxide emission during the early fire succession. However, without knowledge of the contribution of each respiration component combined with assessment of the warming and drying effects on both labile and recalcitrant soil organic matter throughout the soil profile, we cannot advance on the most relevant feedbacks involving fire and permafrost. Fires seem to have either negligible effects on methane (CH 4 ) fluxes or a slight increase in CH 4 uptake. However, permafrost thawing driven by climate or fire could turn upland boreal soils into temporary CH 4 sources, depending on how fast the transition from moist to drier soils occurs. Most studies indicate a slight decrease or no significant change in postfire nitrous oxide (N 2 O) fluxes. However, simulations have shown that the temperature sensitivity of denitrification exceeds that of soil respiration; thus, the effects of warming on soil N 2 O emissions may be greater than on C emissions., (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)

Short-term fire-induced changes to the soil microbial community are usually closely associated to fire severity, which essentially consists in the fire-induced loss or decomposition of organic matter above ground and below ground. Many functional processes and soil properties, including plant recolonization and soil microorganism activity, depend on fire severity. Seven days after burning, we evaluated the impact of two fire severities (low and high) on basic soil properties and the microbial communities in an outdoor experimental controlled system composed of six forest soil monoliths. The magnitude of change in microbial community was far greater than the change in physical and chemical soil properties. Total N was the only selected soil property that significantly varied depending on fire severity. The severely burned soils experienced significant changes in overall microbial biomass composition and phylogenetic composition of bacterial communities in comparison with control plots. Immediately after the fire, in fact, phyla and genera such as Acidobacteria-Gp4 or Bacteroidetes-Ohtaekwangia were much more abundant in the control monoliths. On the other hand, Firmicutes or Proteobacteria (e.g. Firmicutes Paenibacillus, Proteobacteria Phenylobacterium) were relatively more abundant in the monoliths burned with high severity in comparison with the low severity burned ones. Overall, the effect of fire on soil microbial communities was greater in the high severity burned monoliths than in the low severity burned ones. We concluded that in Mediterranean forest ecosystems, fire significantly alters soil bacterial composition depending on its severity., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Eucalypts, especially blue gum (Eucalyptus globulus), have been extensively planted in Portugal and nowadays dominate most of its forest landscapes. Large-scale forestation programs can intensify fire activity, and blue gum plantations are often viewed as highly flammable due to the nature and structure of the fuel complex. The role of eucalypt plantations in the fire regime of Mediterranean climate regions is increasingly debated following the recent catastrophic wildfires in Portugal and elsewhere. In this study we examined the effects of eucalypt forestation on burned area (BA), fire size, and fire severity in Portugal. This was based on fire and vegetation mapping and statistics, fire weather data, satellite imagery, and national forest inventory data. Eucalypt BA comprised an average of 12.5% of total BA (1980-2017) and did not increase over time and with eucalypt expansion. Eucalypt metrics did not explain interannual BA variability after accounting for the effects of other variables. Forest fires started within eucalypt stands were the least likely to become large, and large fire size was irresponsive to forest composition. Likewise, forest type was a generally minor influence in mega-fire severity and accounted for just 1.4-8.6% of surface fuel-hazard metrics variation. In general, large-scale conversion of maritime pine to eucalypt stands (1970-2015) implied lower fuel accumulation. Fire activity results are consistent with fuel hazard results and express trade-offs between short-rotation forestry and fire behaviour in blue gum stands, with high spotting potential versus modest crown fire likelihood. We found no support for the contention of a modified fire regime as a result of eucalypt forestation in Portugal, but the rising undermanaged and abandoned blue gum estate, especially after large-fire seasons, is a concern for the future. However, it remains to be determined whether post-fire eucalypt regrowth is a higher fire threat than native vegetation in the same context., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Fire modifies soil surface, and hence soil hydrological properties change after wildland fires. High fire severity causes partial or total removal of vegetation, reduction of soil aggregate stability and increased water repellency, which are associated with high runoff and erosion. The spatial connection among these runoff sources is an important factor to consider when evaluating fire-induced changes on hillslope and catchment hydrology, as fire generates connected areas of bare soil, which may increase hydrological connectivity and hence post-fire runoff and erosion. The aim of this study was to quantify changes in hydrological connectivity and efficiency in two burned areas in central Mexico. By integrating rainfall simulation and spatial analysis, an index of connectivity (IC) and the lateral hydrological efficiency index (LHEI) were computed based on land/cover use, fire severity and topography within 287 burned sub-basins. Post-fire IC and LHEI were compared with the pre-fire scenario, and the relationship between LHEI and the proportion of burned area was assessed at the sub-basin level. Thresholds of the burned area per fire severity needed to increase LHEI were determined by a classification tree. The index of connectivity and LHEI were higher after wildland fires. The burned area was positively related with LHEI, and at least 43.3% of area burned with high severity is sufficient to produce the highest LHEI. The results are evidence of the effect of fire on hydrological connectivity and efficiency which adds to the understanding of fire-hydrology relations and can be used for integrated catchment management, ecological restoration and risk assessment., (Copyright © 2018. Published by Elsevier B.V.)

Both topography and the occurrence of wildfire can strongly affect soil properties in forest successions. Although numerous studies have examined the effects of fire and topography, few have explored their shifting relative importance with time since fire. We measured physical, chemical, and biological soil properties in two topographic positions (north-facing and south-facing) in a Chinese boreal forest along a gradient of fire history. In the control site, topography strongly influenced soil properties, with north-facing slopes having higher soil moisture (SM), depth of organic matter layer (OML), total carbon and inorganic N concentrations, and lower pH, dissolved organic carbon (DOC) and nitrogen (DON). In the 1-year-post-fire site, wildfire erased topographic effects on soil variables, and greater changes in soil properties occurred on the north-facing slopes. The wildfire significantly increased soil pH, DON, ammonium and nitrate, and decreased SM, OML, DOC and microbial biomass, while no significant differences in soil properties appeared between high- and low-severity plots. In the 11-year-post-fire site, most soil properties were similar to the control except for microbial biomass, OML and DOC; topography again became a significant factor in explaining variations in soil properties. Fire severity was highly correlated only with soil pH in the 1-year-post-fire site, whereas topographic factors were always correlated with some soil properties in the three sites. In the 1-year-post-fire site, wildfire explained almost five times more variance than topography for most soil properties, whereas in the 11-year-post-fire site, the proportion of variance explained by topography increased and even surpassed that by wildfire. These results demonstrate that the resilience of Larix gmelinii forest soils might be controlled by wildfires in the short term but by topography in the long term., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Wildfire disturbance is a major driver of biogeochemical processes in Eurasian boreal forests, yet little is known about the response of soil nutrient stoichiometry to wildfire in this ecosystem. To fill this gap, we measured the composition of available soil nutrients and their stoichiometric ratios in a Chinese boreal forest along a gradient of fire history. In the 1-year-post-fire site, wildfire increased the relative abundances of element nitrogen (N), phosphorus (P), Sulphur (S), iron (Fe), and aluminum (Al), and reduced the abundances of element calcium (Ca), magnesium (Mg), and potassium (K). Available soil N:K, N:S, P:K, P:S, and S:K ratios were 240%, 70%, 440%, 160%, and 150% higher than the control, but N:P ratio was not significantly different. In the 11-year-post-fire site, the soil nutrient composition recovered to the pre-fire levels. Although most of the soil nutrient stoichiometry returned to pre-fire levels, soil N:P ratios became significantly higher. These results showed immediate wildfire effects on soil nutrient availability and composition were strongly related to fire severity, but such effects could be subdued by soil environment and topographical variations over time. Although wildfire effects on soil nutrients are mostly short-term, it could produce relatively long-term effects on balance between N and P., (Copyright © 2018. Published by Elsevier B.V.)

Despite Mediterranean ecosystems' high resilience to fire, both climate and land use change, and alterations in fire regimes increase their vulnerability to fire by affecting the long-term natural recovery of ecosystem services. The objective of this work is to study the effects of fire severity on biochemical soil indicators, such as chemical composition or enzymatic activity, related to time after fire and natural vegetation recovery (soil-plant interphase). Soil samples from three wildfires occurring 3, 15 and 21 years ago were taken in the south-eastern Iberian Peninsula (semiarid climate). Sampling included three fire severity levels in naturally regenerated (and changing to shrublands) Pinus halepensis Mill. forests. In the short-term post-fire period, phosphorus concentration, electrical conductivity and urease activity were positively linked to fire severity, and also influenced β-glucosidade activity in a negative relationship. During the 15-21-year post-fire period, the effects related to medium-high fire severity were negligible and soil quality indicators were linked to natural regeneration success. The results showed that most soil properties recovered in the long term after fire (21 years). These outcomes will help managers and stakeholders to implement management tools to stabilise soils and to restore burned ecosystems affected by medium-high fire severity. Such knowledge can be considered in adaptive forest management to reduce the negative effects of wildfires and desertification, and to improve the resilience of vulnerable ecosystems in a global change scenario., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Fire severity, defined as the magnitude of fire effects in an ecosystem, is a key factor to consider in planning management strategies for protecting forests against fire. Although prescribed burning has been used as a fuel reduction tool in forest ecosystems, it is quite limited in the Mediterranean region. Furthermore, little is known about how tree crowns are affected by prescribed underburning aimed at reducing fire severity in conifer stands. As part of an ongoing study to assess the effects of prescribed burning on the tree canopy, litterfall is currently being monitored in a network of experimental plots located in mixed (Pinus nigra and Pinus pinaster) and pure (P. nigra) conifer stands in the Cuenca Mountains (Castilla La Mancha, Spain). A total of 12 study plots (30m×30m) were established in a completely randomized experimental design to determine the effect of burning, with 2 treatments: no burning (control) and burning (i.e. with three replicate plots for each treatment and site). Burning was conducted in May 2016. In each plot, 8 litterfall collectors were installed at regular intervals, according to international protocols (ICP Forests), and all biomass falling into the collectors is being monitored monthly. The specific objective of this study is to assess how prescribed burning affects the rate of generation of foliar and non-foliar litterfall biomass due to the fire. In addition, the Leaf Area Index was estimated before burning and one year later to verify possible changes in the structure of the stands. This information could be used to help minimize the negative impacts of prescribed underburning on litterfall. To our knowledge, this study represents the first attempt to evaluate the effect of prescribed burning on litterfall biomass in Europe., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Wildfires affect ecosystems depending on the fire regime. Long-term studies are needed to understand the ecological role played by fire, especially as regards its impact on soils. The aim of this study is to monitor the long-term effects (18years) of a wildfire on soil properties in two areas affected by low and high fire severity regimes. The properties studied were total nitrogen (TN), total carbon (TC), C/N ratio, soil organic matter (SOM) and extractable calcium (Ca), magnesium (Mg), sodium (Na) and potassium (K). The study was carried out in three phases: short- (immediately after the wildfire), medium- (seven years after the wildfire) and long-term (18years after the wildfire). The results showed that in both fire regimes TN decreased with time, TC and SOM were significantly lower in the burned plots than they were in the control in the medium- and long-terms. C/N ratio was significantly lower at short-term in low wildfire severity area. Extractable Ca and Mg were significantly higher in control plot than in the burned plots in the medium-term. In the long-term, extractable Ca and Mg were significantly lower in the area exposed to a high severity burning. No differences were identified in the case of extractable Na between plots on any of the sampling dates, while extractable K was significantly higher in the plot exposed to low wildfire than it was in the control. Some restoration measures may be required after the wildfire, especially in areas affected by high severity burning, to avoid the long-term impacts on the essential soil nutrients of TC, SOM, extractable Ca and Mg. This long-term nutrient depletion is attributable to vegetation removal, erosion, leaching and post-fire vegetation consumption. Soils clearly need more time to recover from wildfire disturbance, especially in areas affected by high severity fire regimes., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Forest fires are part of many ecosystems, especially in the Mediterranean Basin. Depending on the fire severity, they can be a great disturbance, so it is of special importance to know their impact on the ecosystem elements. In this study, we measured the sensitivity of glomalin related soil protein (GRSP), a glycoprotein produced by arbuscular mycorrhizal fungi (AMF), to fire perturbation. Two wildfire-affected areas in the SE Spain (Gata and Gorga) were studied. Soil organic carbon (SOC) was also measured. Effects on GRSP immediately after fire were analyzed in both areas, while in Gorga a monitoring of GRSP stocks over a year period after the fire was also carried out. Soil samplings were carried out every 4months. Plots (1×2m 2 ) were installed beneath pines and shrubs in burned and an adjacent control area. Results of GRSP content immediately after a fire only showed significant differences for shrub plots (burned vs control) (p<0.01) in the Gorga site. However, a year of monitoring showed significant fire effect on GRSP content in both plot types (pines and shrubs). Control plots varied considerably over time, while in burned plots GRSP content remained constant during the whole studied period. This research provides evidence of the sensitivity of GRSP to a wildfire perturbation., (Copyright © 2015 Elsevier B.V. All rights reserved.)

Understanding the emissions of mercury (Hg) from wildfires is important for quantifying the global atmospheric Hg sources. Emissions of Hg from soils resulting from wildfires in the Western United States was estimated for the 2000 to 2013 period, and the potential emission of Hg from forest soils was assessed as a function of forest type and soil-heating. Wildfire released an annual average of 3100±1900kg-Hgy(-1) for the years spanning 2000-2013 in the 11 states within the study area. This estimate is nearly 5-fold lower than previous estimates for the study region. Lower emission estimates are attributed to an inclusion of fire severity within burn perimeters. Within reported wildfire perimeters, the average distribution of low, moderate, and high severity burns was 52, 29, and 19% of the total area, respectively. Review of literature data suggests that that low severity burning does not result in soil heating, moderate severity fire results in shallow soil heating, and high severity fire results in relatively deep soil heating (<5cm). Using this approach, emission factors for high severity burns ranged from 58 to 640μg-Hgkg-fuel(-1). In contrast, low severity burns have emission factors that are estimated to be only 18-34μg-Hgkg-fuel(-1). In this estimate, wildfire is predicted to release 1-30gHgha(-1) from Western United States forest soils while above ground fuels are projected to contribute an additional 0.9 to 7.8gHgha(-1). Land cover types with low biomass (desert scrub) are projected to release less than 1gHgha(-1). Following soil sources, fuel source contributions to total Hg emissions generally followed the order of duff>wood>foliage>litter>branches., (Copyright © 2016 Elsevier B.V. All rights reserved.)