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Wildfires represent a significant threat to both ecosystems and human assets in Mediterranean countries, where fire occurrence is frequent and often devastating. Accurate assessments of the initial fire severity are required for management and mitigation efforts of the negative impacts of fire. Evapotranspiration (ET) is a crucial hydrological process that links vegetation health and water availability, making it a valuable indicator for understanding fire dynamics and ecosystem recovery after wildfires. This study uses the Mapping Evapotranspiration at High Resolution with Internalized Calibration (eeMETRIC) and Operational Simplified Surface Energy Balance (SSEBop) ET models based on Landsat imagery to estimate fire severity in five large forest fires that occurred in Spain and Portugal in 2022 from two perspectives: uni- and bi-temporal (post/pre-fire ratio). Using-fine-spatial resolution ET is particularly relevant for heterogeneous Mediterranean landscapes with different vegetation types and water availability. ET was significantly affected by fire severity according to eeMETRIC (F > 431.35; p-value < 0.001) and SSEBop (F > 373.83; p-value < 0.001) metrics, with reductions of 61.46% and 63.92%, respectively, after the wildfire event. A Random Forest machine learning algorithm was used to predict fire severity. We achieved higher accuracy (0.60 < Kappa < 0.67) when employing both ET models (eeMETRIC and SSEBop) as predictors compared to utilizing the conventional differenced Normalized Burn Ratio (dNBR) index, which resulted in a Kappa value of 0.46. We conclude that both fine resolution ET models are valid to be used as indicators of fire severity in Mediterranean countries. This research highlights the importance of Landsat-based ET models as accurate tools to improve the initial analysis of fire severity in Mediterranean countries. [ABSTRACT FROM AUTHOR]

This study explored, for the first time, the drivers shaping large fire size and high severity of forest fires classified as level-2 in Spain, which pose a great danger to the wildland–urban interface. Specifically, we examined how bottom-up (fuel type and topography) and top-down (fire weather) controls shaped level-2 fire behavior through a Random Forest classifier at the regional scale in Galicia (NW Spain). We selected for this purpose 93 level-2 forest fires. The accuracy of the RF fire size and severity classifications was remarkably high (>80%). Fire weather overwhelmed bottom-up controls in controlling the fire size of level-2 forest fires. The likelihood of large level-2 forest fires increased sharply with the fire weather index, but plateaued at values above 40. Fire size strongly responded to minimum relative humidity at values below 30%. The most important variables explaining fire severity in level-2 forest fires were the same as in the fire size, as well as the pre-fire shrubland fraction. The high-fire-severity likelihood of level-2 forest fires increased exponentially for shrubland fractions in the landscape above 50%. Our results suggest that level-2 forest fires will pose an increasing danger to people and their property under predicted scenarios of extreme weather conditions. [ABSTRACT FROM AUTHOR]

Understanding how fire severity affects resprouting plants during post-fire regeneration is key to anticipating Mediterranean vegetation vulnerability in a context of increasingly large fires with high intensity and severity due to climate change. Here, we monitored the water status, leaf gas exchange, and plant growth in holm oaks (Quercus ilex) of central Spain burned with different fire severity throughout the first post-fire year. The Q. ilex burned with high severity (HB+) showed higher water potential and shoot growth than those burned with low severity (LB+) or unburned (B−), especially during spring and summer. In summer, resprouting HB+ and LB+ plants exhibited higher carbon assimilation than unburned ones. Moreover, we also found that plants with higher water availability and growth, i.e., HB+ individuals, had higher specific leaf area and lower water use efficiency. Overall, our study shows that holm oak forests exhibit high plasticity to fire and that Q. ilex burned with high severity have a faster short-term regeneration than those burned with low severity. However, this rapid regeneration is based on a less conservative water-use strategy, which could jeopardize their populations in case of extreme drought events increasingly common in the current context of climate change. [ABSTRACT FROM AUTHOR]

The effectiveness of mulching in reducing the risk of erosion has been evaluated in numerous studies. However, its effect on carbon loss has received less attention, despite the potentially negative effects on ecosystem recovery. In this study, the effects of straw helimulching on soil erosion and carbon loss in sediments were investigated after a severe wildfire in NW Spain during the first three years after fire. During the first year after the fire, the accumulated mean sediment yield was 12.4 Mg ha−1 in the control plots and 0.5 Mg ha−1 in the mulched plots. Soil erosion decreased sharply during the second year after the fire and was almost inexistent during the third year after the fire. No differences in carbon concentration were detected between treatments during the period of study. A significantly lower amount of carbon was lost after the mulching treatment due to its effectiveness in reducing sediment erosion. The mulching treatment did not significantly influence the amount of carbon sequestered in the vegetation. Although the application of mulch did not affect carbon fixation in vegetation, its application after fire can be considered a sustainable way of managing forest ecosystems to reduce the impact of fire on carbon emissions. [ABSTRACT FROM AUTHOR]

Background: Salvage logging is commonly carried out after forest fires, and mastication of the logging slash is usually prescribed to reduce the risk of infestation by insect pests in NW Spain. Aims: To evaluate how post-fire masticated slash depth affected vegetation regeneration (cover, diversity and load) and soil variables (soil organic carbon and soil compaction). Methods: In October 2017, a fire that completely burned tree crowns and caused moderate soil burn severity was selected for study. At the end of 2017, the burned trees were logged and logging slash was masticated. Twenty plots were established in June 2020 in those areas to analyse the effect of the depth of masticated slash on soil compaction, vegetation recovery, fuel distribution and carbon accumulation. Key results: The depth of masticated slash did not affect soil compaction, total vegetation cover or species diversity. Mean pine seedling density was significantly higher areas where the masticated slash depth was lower. Fuel loads and soil carbon content did not vary with the depth of masticated slash. Conclusions: A lower masticated slash depth seems to be more favourable for pine regeneration. Implications: These results may be useful for managers to favour natural regeneration in similar pine stands after fire. This study aimed to evaluate how post-fire masticated slash depth affected vegetation regeneration to provide information for forest management planning. The masticated slash depth did not have significant effects on vegetation cover or species diversity 2.5 years after treatments. A lower slash depth favoured pine regeneration. [ABSTRACT FROM AUTHOR]

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 (30 m × 30 m) 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. [ABSTRACT FROM AUTHOR]

Forest fires are a recurrent natural phenomenon in the Mediterranean basin. Fires can affect physical, chemical and biological soil properties. The effects on soil properties are closely controlled by fire severity, which is a consequence of temperatures reached and the length of residence of heat in the soil. In this study, the response of glomalin-related soil protein (GRSP) − a glycoprotein produced by arbuscular mycorrhizal fungi − to heating temperature has been studied. Laboratory heating treatments were carried out at 180°C, 200°C, 250°C, 300°C, 400°C and 500°C in soil samples from eight different sites in SE Spain. The sites selected had mainly different soil characteristics. The results of heating on soil water repellency and soil organic carbon (SOC) were also included in the study. GRSP response to temperature was different between sites. Redundancy analyses divided sandy soils from the rest of soil types. Total content of aggregates, SOC and clay and sand content were the most significant properties explaining the response of GRSP to heating treatments. Results showed that GRSP was affected even at low temperature. SOC response to temperature was very similar between sites. Soil water repellency did not appear after heating in wettable soils and disappeared in water-repellent ones at temperatures over 200°C. Our results indicate that GRSP could provide relevant information about fire severity. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Treatments that minimize soil erosion after large wildfires depend, among other factors, on fire severity and landscape configuration so that, in practice, most of them are applied according to emergency criteria. Therefore, simple tools to predict soil erosion risk help to decide where the available resources should be used first. In this study, a predictive model for soil erosion degree, based on ordinal logistic regression, has been developed and evaluated using data from three large forest fires in South-eastern Spain. The field data were successfully fit to the model in 60% of cases after 50 runs (i.e., agreement between observed and predicted soil erosion degrees), using slope steepness, slope aspect, and fire severity as predictors. North-facing slopes were shown to be less prone to soil erosion than the rest. [ABSTRACT FROM AUTHOR]

Mediterranean pine forests in Spain experience wildland fire events with different frequencies, intensities, and severities which result in diverse socio-ecological consequences. In order to predict fire severity, spectral indices derived from remotely sensed images have been used extensively. Such spectral indices are usually used in combination with ground sampling to relate detected radiometric changes to actual fire effects. However, the potential of the tridimensional information captured by Airborne Laser Scanners (ALS) to severity mapping has been less explored. With the objective of addressing this question, in this paper, explanatory variables extracted from ALS point clouds are related to field estimations of the Composite Burn Index collected in four fires located in Aragón (Spain). Logistic regression models were developed and statistically tested and validated to map fire severity with up to 85.5% accuracy. The canopy relief ratio and the percentage of all returns above one meter height were the most significant variables and were therefore used to create a continuous map of severity levels. [ABSTRACT FROM AUTHOR]

Abstract: Soil water repellency is a widespread property of Pinus pinaster forest soils in Galicia (NW Spain) that can be intensified by soil heating during fires. Fire-induced or -enhanced soil water repellency, in combination with reduced vegetation and litter cover, is widely considered to be one of the main causes of increased overland flow and accelerated soil erosion on recently burnt hill slopes. In this work, we assessed the natural severity of water repellency in forest soils of different texture under P. pinaster in Galicia (NW Spain) and we examined the specific effect of a forest fire in an area under granite substrate and P. pinaster plantation on the severity and persistence of soil water repellency. Because the burnt area included zones that were affected to a different extent by the fire, we focused on the effect of its severity on soil water repellency from surface level down to a depth of 40cm immediately after the fire and 15months later. Persistency in the soil water repellency was assessed with the water drop penetration time test (WDPT). Water repellency in the sampled soils was found to be extremely persistent in the surface layer (0–5cm). Also, the soils of a coarser texture, exhibit more persistence repellency and at greater depths than those of a finer texture. Fire severity was found to influence the persistence of water repellency and the thickness of the hydrophobic layer in the burnt zones. Such persistence in the soil affected by low-severity fire not differed significantly from that in unburnt soil; also, repellency remained severe to extreme down to 10cm. On the other hand, soil water repellency in areas subject to fire of medium–high severity was completely suppressed within the top 2cm of soil, but increased with depth (extreme water repellency between 2 and 20cm). Fifteen months after the fire, both burnt and unburnt zones exhibited water repellency throughout the sampled profile (0–40cm); however, the burnt zone affected by fire of medium–high severity exhibited decreased water repellency in the surface layer but increased at depths of 2–40cm than it was both in the unburnt zone and in the zone burnt by low-severity fire. [Copyright &y& Elsevier]

The high incidence of hunting activity and forest fires in different ecosystems (particularly in Mediterranean ecosystems) requires a model, which allows for the comprehensive management of hunting resources and estimating the potential damage caused by this type of disturbance. This paper proposes a model for evaluating the socio-economic effects of forest fires on hunting. Its cornerstone lies in evaluating hunting resource availability for each ecosystem within its territorial mosaic. Each game management unit (GMU) is identified by vegetation structure and habitat type. It presents a novel approach in which the economic value of each game management unit is linked to potential forest fire damages. The effect a forest fire has on an entire ecosystem depends on the intensity of its flames. A sample study was undertaken in the province of Huelva in Andalusia (southern Spain). The socio-economic hunting vulnerability of the province of Huelva was 45,188,000€. The results obtained confirmed the need for an economic appraisal of non-forest products in the forest and other woodland areas. Geographic Information System increases the flexibility and simplicity of our methodology which permits immediate extrapolation to other agroforestry territories. [Copyright &y& Elsevier]

The article discusses a study which compared the soil erosion assessment of the Revised Universal Soil Loss Equation (RUSLE) and the revised Morgan-Morgan-Finney (MMF) model after fire and rehabilitation treatments in Northwest Spain. Both models were found to be effective in determining action priorities specifically in areas prone to degradation by erosion after fire. Coefficient of efficiency, root mean squared errors and the Wilcoxon rank sum method were used to evaluate predicted annual soil losses values.

Abstract: The effect of fire severity and post-fire management on Pinus pinaster recruitment was evaluated in three burnt areas in Galicia (NW Spain) exhibiting different levels of serotiny. Three sites were sampled, each of which had two of the following levels of fire severity: combusted crown, scorched crown and unaffected crown. Viable seed rain was closed related to the canopy cone bank and stand serotiny level. Soil burn severity also favoured seed dispersal. Relative germination success increased with soil burn severity whereas initial and final seedling density depended on both the canopy cone bank and soil burn severity. A positive influence of fire severity on the final/initial seedling density and final density/total seed dispersal ratios was also observed. Different post-fire management options were used at each experimental site following local operational routines. Harvesting and slash logging resulted in significantly higher seedling mortality. However, at the end of the study period, seedling density in all stands was sufficient to ensure re-establishment of P. pinaster forest. [Copyright &y& Elsevier]

Fire severity assessment is crucial for predicting ecosystem response and prioritizing post-fire forest management strategies. Although a variety of remote sensing approaches have been developed, more research is still needed to improve the accuracy and effectiveness of fire severity mapping. This study proposes a unitemporal simulation approach based on the generation of synthetic spectral databases from linear spectral mixing. To fully exploit the potential of these training databases, the Random Forest (RF) machine learning algorithm was applied to build a classifier and regression model. The predictive models parameterized with the synthetic datasets were applied in a case study, the Sierra de Luna wildfire in Spain. Single date Landsat-8 and Sentinel-2A imagery of the immediate post-fire environment were used to develop the validation spectral datasets and a Pléiades orthoimage, providing the ground truth data. The four defined severity categories – unburned (UB), partial canopy unburned (PCU), canopy scorched (CS), and canopy consumed (CC) – demonstrated high accuracy in the bootstrapped (about 95%) and real validation sets (about 90%), with a slightly better performance observed when the Sentinel-2A dataset was used. Abundance of four ground covers (green vegetation, non-photosynthetic vegetation, soil, and ash) was also quantified with moderate (~45% for NPV) or high accuracy (higher than 75% for the remaining covers). No specific pattern in the comparison of sensors was observed. Variable importance analysis highlighted the complementary behavior of the spectral bands, although the contrast between the near and shortwave infrared regions stood out above the rest. Comparison of procedures reinforced the usefulness of the approach, as RF image-derived models and the multiple endmember spectral unmixing technique (MESMA) showed lower accuracy. The capabilities for detailed mapping are reflected in the development of different types of cartography (classification maps and fraction cover maps). The approach holds great potential for fire severity assessment, and future research needs to extend the predictive modeling to other burned areas – also in different ecosystems – and analyze its competence and the possible adaptations needed. Unlabelled Image • Approach to fire severity mapping from unitemporal Landsat-8 and Sentinel-2 data • Accurate estimation of fire severity from synthetic spectral data and Random Forest • Successful application to a Mediterranean burned area, with high adaptability • Towards improvement of fire severity mapping for forest management practices [ABSTRACT FROM AUTHOR]

Tree and plant structures remaining after fires reflect well their degree of consumption, and are therefore good indicators of fire severity. Satellite optical images are commonly used to estimate fire severity. However, depending on the severity of a fire, these sensors have a limited ability to penetrate the canopy down to the ground. Airborne light detection and ranging (LiDAR) can overcome this limitation. Assessing the differences between areas that have been burned in different fire severities based on satellite images of plant and tree structures remaining after fires is important, given its widespread use to characterize fires and fire impacts (e.g., carbon emissions). Here, we measured the remaining tree structures after a fire in a forest stand burned in SE Spain in the summer of 2017. We used high-resolution LiDAR data, acquired from an unmanned aerial vehicle (UAV) six months after the fire. This information was crossed with fire severity levels based on the relativized burnt ratio (RBR) derived from Sentinel 2A images acquired a few months before and after fire. LiDAR tree structure data derived from vertical canopy profiles (VCPs) were classified into three clusters, using hierarchical principal component analysis (HPCA), followed by a random forest (RF) to select the most important variables in distinguishing the cluster groups. Among these, crown leaf area index (LAI), crown leaf area density (LAD), crown volume, tree height and tree height skewness, among others, were the most significant variables, and reflected well the degree of combustion undergone by the trees based on the response of these variables to variations in fire severity from RBR Sentinel 2A. LiDAR metrics were able to distinguish crown fire from surface fire through changes in the understory LAI and understory and midstory vegetation. The three tree structure clusters were well separated among each other and significantly related with the RBR Sentinel 2A-derived fire severity categories. Unburned and low-severity burned areas were more diverse in tree structures than moderate and high severity burned ones. The LiDAR metrics derived from VCPs demonstrated promising potential for characterizing fine-grained post-fire plant structures and fire damage when crossed with satellite-based fire severity metrics, turning into a promising approach for better characterizing fire impacts at a resolution needed for many ecological processes. [ABSTRACT FROM AUTHOR]

Fire severity is a function of dynamic interactions between vegetation and burning conditions. To understand the factors that control it, accurate methods for estimating prefire vegetation structure and composition as well as fire propagation conditions are required. Here we analyzed the spatial variability of fire severity in a mixed-severity fire (3217 ha) that occurred in southeast Spain (Yeste, Albacete) from 27th July to 1th August 2017, burning mostly a pine woodland, including part of an earlier fire in 1994. Fire severity was estimated using three satellite-based indices derived from the Normalized Burn Ratio (NBR) using Sentinel 2 and Landsat 8 images from the dates before and immediately after fire. The field-based Composite Burn Index (CBI) was used for validation. Prefire vegetation conditions and fuel models were derived from LiDAR metrics and other vegetation data. Fire propagation conditions were estimated based on a fire progression map provided by the Forestry Services of Castilla-La Mancha. In addition, hourly fire weather and aligned (i.e., in the sense of the propagating fire-front) slope and wind speed were calculated for each burning period. Regression models using different spectral fire severity indices and their driving factors were obtained applying Boosted Regression Trees (BRTs). Fire severity was highly predicted by both burning conditions and prefire vegetation (mean adjusted R2 [Adj.R2: 86% ± 0.04 and 68% ± 0.05 for training and validation sets, respectively). Alone, burning conditions explained more variance than LiDAR metrics and vegetation separately. The single variables that contributed most to the models were the rate of spread of the fire-front, biomass proxies (i.e., Leaf Area Index [LAI] and fraction of Photosynthetically Active Radiation [fPAR]) and understory vegetation (i.e., density of LiDAR points 1–2 m). Higher fire severity occurred in areas burning uphill, with a high rate of spread driven by high velocity winds and under high maximum temperature. Fire severity was high in wooded stands that were heterogeneous in height, composed by scattered and small Pinus halepensis trees, with high and homogeneous understory cover. In contrast, lower fire severity occurred in mature stands dominated by tall Pinus pinaster and Pinus nigra trees. There were strong interactions between vegetation, weather, fire-aligned topography and rate of spread. Because vegetation variables were important drivers of fire severity, even under extreme fire weather conditions, fuel management treatments to limit fire severity and, potentially, fire size should be implemented. [ABSTRACT FROM AUTHOR]

• Thin-only could reduce the likelihood of active crown fires and spread in the midterm. • For low and moderate intensities, fuel moisture surpassed wind speed effect on fire severity. • Thin-only has a minor influence on the reduction of fire severity and soil protection. • Surface fuel reduction is needed to increase thin-only efficiency. Fuel hazard reduction is an essential component of pine plantation management. In NW Spain, plantation managers assume that thin-only reduces the potential fire behavior and effects by decreasing the quantity and continuity of canopy fuels. Nevertheless, thin-only can alter additional variables than control fire behavior and effects such as surface fuel availability and microclimate conditions. Moreover, the duration of thinning effects could vary and be species-specific. We present an approach linking field-measured fuel variables to well-established models for assessing the mid-term effects (six years) of thin-only on potential fire behaviour and severity and ability of burned stands to protect soil against erosion. Field variables were obtained from 41 thinning trials installed in stands of P. pinaster (22 locations) and P. radiata (19 locations). Canopy fuel load and canopy bulk density were still significantly lower in treated sample plots for both species six years after treatments, whereas total and fine understory fuel loads were slightly but significantly larger in thinned plots in P. pinaster. In a simulation process, different fire danger scenarios were considered through two fire-related weather variables: the 10-m open wind speed and the fine dead fuel moisture content. Results showed that thin-only could significantly reduce the likelihood of active crown fire and its rate of spread for both species, particularly in P. pinaster, while passive crown fire probability increased. The potential fire severity, in terms of crown scorch height, scorch volume and tree mortality, hardly worsened by thinning. For fireline intensities lower than 4000 kW m−1, dead fuel moisture content effect on fire severity surpassed the wind speed influence. Moreover, protection of soil against erosion improved only slightly when thinning was previously carried out. The results of the study reveal that, in the mid-term, it is unlikely that thin-only, without intervention in the surface fuels, may have a marked influence on the reduction of the severity of a subsequent fire. The results also highlight the need of a comprehensive assessment of the effects of thin-only on both the whole fuel complex and microclimatic variables for obtaining realistic results. [ABSTRACT FROM AUTHOR]

To optimize suppression, restoration, and prevention plans against wildfire, postfire assessment is a key input. Since little research has been carried out on applying Sentinel-2 imagery through an integrated approach to evaluate how environmental parameters affect fire severity, this work aims to fill this gap. A set of large forest fires that occurred in northwest Spain during extreme weather conditions were adopted as a case study. Sentinel-2 information was used to build the fire severity map and to evaluate the relation between it and a set of its driving factors: land cover, aspect, slope, proximity to the nearest stream, and fire recurrence. The cover types most affected by fire were scrubland, rocky areas, and Eucalyptus. The presence of streams was identified as a major cause of the reduced severity of fires in broadleaves. The occurrence of fires in the past is linked to the severity of fires, depending on the land cover. This research aims to help fire researchers, authority managers, and policy makers distinguish the conditions under which the damage by fire is minimized and optimize the resources allocated to restoration and future fire suppression. [ABSTRACT FROM AUTHOR]

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.)