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Wildfires have a strong influence on various geotechnical and hydraulic properties of soils and sediments, which may become more vulnerable to landslides or debris flows. In the present study, a case investigation of the 2018 post-wildfire debris flows in Montecito, California, USA, was conducted, with a focus on the wildfire-affected areas and debris volume estimation. Significant debris were deposited around four major creeks, i.e., Montecito Creek, San Ysidro Creek, Buena Vista Creek, and Romero Creek in January, 2018, one month after the Thomas fire. Satellite images utilizing remote sensing techniques and geographic information system (GIS) data were analyzed to identify areas affected by the wildfire. Relevant data, including the slope, catchment area, and rainfall were used in two empirical models to estimate the debris volumes around the four creeks. As compared with field observation, each debris volume estimated with these empirical models was within the same order of magnitude. The debris volumes were generally underestimated when using the rainfall recorded at the Montecito Weather Station; the estimates considerably improved with the rainfall record from the Doulton Tunnel Station. The results showed that, overall, such empirical approaches are still of benefit for engineering practice, as they are capable of offering first-order approximations. The accuracy and availability of rainfall data are critical factors; the rainfall data in mountainous areas are generally higher than in the low lands, and consequently were more suitable for debris volume estimation in the present study, where the debris flows typically occurred in areas with steep slopes and at higher elevations.

During the 2019 Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) study, the NASA DC-8 carried out in situ chemical measurements in smoke plumes emitted from wildfires and agricultural fires in the contiguous United States. The DC-8 payload included a modified proton-transfer-reaction time-of-flight mass spectrometer (PTR-ToF-MS) for the fast measurement of gaseous ammonia (NH3) and a high-resolution time-of-flight aerosol mass spectrometer (AMS) for the fast measurement of submicron particulate ammonium (NH4+). We herein report data collected in smoke plumes emitted from 6 wildfires in the Western United States, 2 prescribed grassland fires in the Central United States, 1 prescribed forest fire in the Southern United States, and 66 small agricultural fires in the Southeastern United States. Smoke plumes contained double to triple digit ppb levels of NH3. In the wildfire plumes, a significant fraction of NH3 had already been converted to NH4+ at the time of sampling (≥2 h after emission). Substantial amounts of NH4+ were also detected in freshly emitted smoke from corn and rice field fires. We herein present a comprehensive set of emission factors of NH3 and NHx, with NHx=NH3+NH4+. Average NH3 and NHx emission factors for wildfires in the Western United States were 1.86±0.75 g kg−1 and 2.47±0.80 g kg−1 of fuel burned, respectively. Average NH3 and NHx emission factors for agricultural fires in the Southeastern United States were 0.89±0.58 and 1.74±0.92 g kg−1, respectively. Our data show no clear inverse correlation between modified combustion efficiency (MCE) and NH3 emissions. The observed NH3 emissions were significantly higher than measured in previous laboratory experiments in the FIREX FireLab 2016 study.

Peatland restoration is essential to preserve biodiversity and carbon stored in peat soils. Common restoration techniques such as rewetting do not always result in the full recovery of peatland taxonomic and functional properties, threatening the resilience of restored peatlands and their carbon stores. Here, we study the use of peat moss inoculation in stimulating the short-term taxonomic and functional recovery of a wildfire-impacted peatland using mesocosms at high and low water table depth, representing ideal and adverse hydrological conditions respectively. Inoculation in conjunction with high water tables accelerated the recovery of the vascular plant and prokaryote communities. Importantly, Sphagnum—the keystone genus in these peatlands—only established in inoculated mesocosms. Together, this resulted in an increased CO2 uptake by approximately 17 g m−2 day−1 and reduced overall nutrient content in the peat pore water. Synthesis and applications. Our results indicate that inoculation can be used to accelerate the establishment of peatland-specific species. In addition, they suggest the potential to combine peat moss inoculation and hydrological restoration to accelerate the uptake of carbon back into the system post-fire. This offers a basis for future work exploring the long-term use of inoculation to return disturbed peatlands to their pre-degraded state, and a wider application of soil inoculation as a mechanism for functional recovery.

Peatland restoration is essential to preserve biodiversity and carbon stored in peat soils. Common restoration techniques such as rewetting do not always result in the full recovery of peatland taxonomic and functional properties, threatening the resilience of restored peatlands and their carbon stores. Here, we study the use of peat moss inoculation in stimulating the short-term taxonomic and functional recovery of a wildfire-impacted peatland using mesocosms at high and low water table depth, representing ideal and adverse hydrological conditions respectively. Inoculation in conjunction with high water tables accelerated the recovery of the vascular plant and prokaryote communities. Importantly, Sphagnum—the keystone genus in these peatlands—only established in inoculated mesocosms. Together, this resulted in an increased CO2 uptake by approximately 17 g m−2 day−1 and reduced overall nutrient content in the peat pore water. Synthesis and applications. Our results indicate that inoculation can be used to accelerate the establishment of peatland-specific species. In addition, they suggest the potential to combine peat moss inoculation and hydrological restoration to accelerate the uptake of carbon back into the system post-fire. This offers a basis for future work exploring the long-term use of inoculation to return disturbed peatlands to their pre-degraded state, and a wider application of soil inoculation as a mechanism for functional recovery.

Son yıllarda küresel ısınmanın etkisi ile orman yangınları giderek yıkıcı tahribatlara neden olmaktadır. Orman yangınlarının, orman alanlarında meydana getirdiği tahribatın belirlenmesi zaman alıcı ve maliyetli bir iştir. Orman yangınları sonucunda yanan orman alanlarının ve yanma şiddeti açısından alanın haritalanması, rehabilitasyon çalışmaları açısından büyük önem taşımaktadır. Orman alanlarına ait haritalama ve izleme çalışmalarında uzaktan algılama ve CBS teknikleri yaygın bir şekilde kullanılmaktadır. Uzaktan algılama, pratik, uygun maliyetli ve hassas sonuçlar vermesi açısından orman yangınları sonrasında yanan alan büyüklüğü ve yanma şiddeti açısından alanın haritalanmasında önemli avantajlar sunmaktadır. Bu çalışmada, 2022 yılı eylül ayında Mersin ili Gülnar ilçesinde meydana gelen orman yangınına ait yanan alan miktarının belirlenmesi ve farklı uzaktan algılama indislerinin yanan alan büyüklüğünün belirlenmesindeki performansları karşılaştırılmıştır. Çalışma alanına ait haritalama kapsamında Sentinel-2 uydu görüntüsü kullanılmıştır. Yanan alan miktarı, dNDVI (Differenced normalized difference vegetation index), dSAVI (Differenced soil adjusted vegetation index) ve dNBR (Differenced normalized burn ratio) indislerine göre tahmin edilmiştir. Çalışma kapsamında kullanılan üç farklı indise ait performans değerleri doğruluk analizi ile ortaya konmuştur. Yanan alan büyüklüğünün tespit edilmesinde, dNDVI, dSAVI ve dNBR indislerine ait genel doğruluk değerleri sırasıyla % 75.56, % 84.44 ve % 88.89 olarak bulunmuştur. dNDVI indisine ait doğruluk oranı kabul edilebilir düzeydeyken, dSAVI ve dNBR indisleri yanan alan büyüklüğünün tespit edilmesinde oldukça iyi performans göstermiştir. Orman yangınları sonucu zarar gören alanlar, uydu görüntüleri ve uzaktan algılama teknikleri ile hızlı ve hassas bir şekilde tespit edilebilmektedir., In recent years, with the effect of global warming, wildfires are causing increasingly destructive damages. Determining the destruction caused by wildfires in forest areas is a time-consuming and cost effective. The mapping of the forest areas burned as a result of wildfires and the area in terms of burn severity is of great importance in terms of rehabilitation activities. Remote sensing and GIS techniques are widely used in mapping and monitoring studies of forest areas. In terms of providing practical, cost-effective and sensitive results, remote sensing offers significant advantages in mapping the area in terms of burned area and burn severity after wildfires. In this study, the determination of the amount of burned area belonging to the wildfire that occurred in Mersin province Gülnar district in September 2022 and the performances of different remote sensing indices in determining the size of the burned area were compared. Sentinel-2 satellite image was used in the mapping of the study area. The amount of burned area was estimated according to the dNDVI (Differenced normalized difference vegetation index), dSAVI (Differenced soil adjusted vegetation index) and dNBR (Differenced normalized burn ratio) indices. The performance values of three different indices used within the scope of the study were revealed by accuracy analysis. The general accuracy values of the dNDVI, dSAVI and dNBR indices were found to be 75.56%, 84.44% and 88.89%, respectively, in determining the size of the burned area. While the accuracy of the dNDVI was acceptable, the dSAVI and dNBR indices performed very well in detecting the size of the burned area. Areas damaged by wildfires can be detected quickly and precisely with satellite images and remote sensing techniques.

The Mediterranean mixed coniferous and broad-leaved forest of Moarda (Palermo) was affected by a large wildfire in summer 2020. In spring 2021, burned and unburned loam soil sites were sampled and the water drop penetration time (WDPT) and ethanol percentage (EP) tests applied to assess the influence of wetting-drying processes and soil water content on post-fire soil water repellency (SWR) as well as its vertical distribution. According to the WDPT test, the surface layer of the natural unburned soils was severely hydrophobic at intermediate soil water contents roughly corresponding to wilting point and SWR reduced either for very dry conditions (air- or oven-dried conditions) or wetter conditions close to field capacity. For these soils, EP test yielded results in agreement with WDPT. An influence of the wetting/drying cycle was detected as, for a given soil water content, WDPT was generally higher for the drying than the wetting process. The surface of burned soils was always wettable independently of the soil water content. The vertical distribution of SWR was modified by wildfire and the maximum hydrophobicity layer, that was located at the surface of the unburned soils, moved to a depth of 2–4 cm in the soils of burned sites. The results confirmed that wildfire can induce destruction of soil water repellency (SWR) naturally occurring at the surface of forest soils and create a shallow hydrophobic layer that may increase overland flow and erosion risk.

The increasing frequency and severity of forest fires necessitate early detection and rapid response to mitigate their impact. This project aims to design a cyber-physical system for early detection and rapid response to forest fires using advanced technologies. The system incorporates Internet of Things sensors and autonomous unmanned aerial and ground vehicles controlled by the robot operating system. An IoT-based wildfire detection node continuously monitors environmental conditions, enabling early fire detection. Upon fire detection, a UAV autonomously surveys the area to precisely locate the fire and can deploy an extinguishing payload or provide data for decision-making. The UAV communicates the fire’s precise location to a collaborative UGV, which autonomously reaches the designated area to support ground-based firefighters. The CPS includes a ground control station with web-based dashboards for real-time monitoring of system parameters and telemetry data from UAVs and UGVs. The article demonstrates the real-time fire detection capabilities of the proposed system using simulated forest fire scenarios. The objective is to provide a practical approach using open-source technologies for early detection and extinguishing of forest fires, with potential applications in various industries, surveillance, and precision agriculture.

Fire might occur under natural conditions in the Pantanal of Brazil; however, with climate change, severe periods of drought potentiated the devasting fires in 2020, resulting in substantial wildlife loss. Considering that mammal communities are strongly affected by fire and habitat alterations, the aim of this study was to evaluate possible differences in mammal diversity and the number of records before and one year after the fire in one region of the Pantanal of Mato Grosso, Brazil (Parque SESC Baía das Pedras - PSBP). The data collection was performed using camera trapping between 2015 and 2017 and 2021, together with visual field observations in PSBP. We observed that the mammal assemblage composition was similar before and one year after the fire. Four species were more or less frequent in burned areas than in unburned ones. Since the fire was controlled in this area, avoiding its total destruction, and the species that fled from the surrounding areas, which were completely burnt, might be using PSBP as a refuge while the vegetation recovers elsewhere. Therefore, the PSBP might have contributed to protecting mammal species after the fire and maintaining and conserving biodiversity on a regional scale in the Pantanal of Mato Grosso, Brazil.

Tree hollows are an important landscape resource used by fauna for shelter, nesting, and predator avoidance. In fire-prone landscapes, wildfire and climate may impact hollow dynamics; however, assessments of their concurrent impacts are rare. We conducted a field survey at 80 sites in the Sydney Basin bioregion (Australia) to understand how fire frequency, fire severity, mean annual temperature, and mean annual precipitation concurrently impacted the site-density of small- (10 cm entry width) tree hollows and tree basal scars (which mediate hollow formation via invertebrate access to heartwood), when tree-size and dead/live status were considered. A unimodal relationship occurred between medium- and large-sized hollow densities and fire frequency and severity, respectively, with hollow densities greatest at intermediate frequencies/severities. Increases of 1.82, 1.43, and 1.17 hollows per site were observed between the 1 (reference) and 2, 2 and 3, and 3 and >3 fire frequency categories. Increases of 1.26, 1.75 and 0.75 hollows per site were observed between the low (reference) and moderate, moderate and high, and high and very high fire severity categories. Fire severity was also positively associated with basal scar density, with increases of 2.52, 8.15, and 8.47 trees per site between the low (reference) and moderate, moderate and high, and high and very high categories. A weak positive and stronger negative association was observed between mean annual temperature and small-sized hollow and basal scar density, respectively. Dead and medium-sized tree density was positively associated with medium-sized hollow and basal scar tree density, respectively. Collectively, our results suggest that wildfires, and in some cases climate, have diverse and size-specific impacts on tree hollow and basal scar density. Our results imply that fire regimes that allow for moderately severe wildfire will promote larger-sized tree hollows, which are a limiting resource for many fauna species.

Cambodia has the most fires per area in Southeast Asia, with fire activity have significantly increased since the early 2000s. Wildfire occurrences are multi-factorial in nature, and isolating the relative contribution of each driver remains a challenge. In this study, we quantify the relative importance of each driver of fire by analyzing annual spatial regression models of fire occurrence across Cambodia from 2003 to 2020. Our models demonstrated satisfactory performance, explaining 69 to 81% of the variance in fire occurrence. We found that deforestation was consistently the dominant driver of fire across 48 to 70% of the country throughout the study period. Although the influence of low precipitation on fires has increased in 2019 and 2020, the period is not long enough to establish any significant trends. During the study period, wind speed, elevation, and soil moisture had a slight influence of 6–20% without any clear trend, indicating that deforestation continues to be the main driver of fire. Our study improves the current understanding of the drivers of biomass fires across Cambodia, and the methodological framework developed here (quantitative decoupling of the drivers) has strong potential to be applied to other fire-prone areas around the world.

The horizontal storm structure surrounding 92,512 lightning-ignited wildfires is examined in the mid to eastern sections of the United States from 2003 to 2015 using Vaisala’s National Lightning Detection Network (NLDN), NCEP’s Stage IV gauge-corrected radar precipitation mosaic, and the US Forest Service’s Fire Occurrence Database. Though lightning flash density peaks strongly around fire ignitions on the instantaneous 1 km scale, on the hourly 10 km scale, both the lightning and precipitation peaks are typically offset from fire ignitions. Lightning density is higher, and precipitation is lower around ignition points compared to non-ignition points. The average spatial distribution of total lightning flashes around fire ignitions is symmetrical, while that of precipitation and positive flashes is not. Though regression is consistent with the claim that positive flashes have a stronger association with ignition than negative flashes, the statistical significance is ambiguous and is contradicted by an unchanging positive flash fraction in the vicinity of wildfires.

The Mediterranean Basin is a biogeography shaped by fires for millions of years. For the restoration of burned areas in the Mediterranean Basin, therefore, planning should increase resistance and resilience of plant communities to fire by considering adaptation strategies of plant species to fire. In this study, following the fire of 2021, affected approximately 12,500 hectares in Marmaris region, a rapid assessment method and post-fire restoration prescriptions were developed for the Datça-Bozburun Special Environmental Protection Area. By using EFFIS and Sentinel-2 satellite images, the burned area was determined and classified to fire severity with normalized burn ratio difference The regeneration potential of burned areas was revealed by counting the number of serotinous cones of Turkish red pine (Pinus brutia) and estimating potential coverage of maquis species in sampling areas based on stand type and burn severity levels. Open pine stands had the highest serotiny and high resprouting potential following maquis vegetation, while the young pine stands have the lowest level of serotiny. Considering results and slope degrees, six restoration prescriptions were developed for burned areas. While 6% of the burned area was recommended to be left unmanaged, natural regeneration + laying out branches with cones and natural regeneration with additional seeding, and artificial regeneration by planting saplings after terracing and tillaging were foreseen for the remaining areas. This simple and cost-effective methodology developed in this study is highly applicable to local practitioners and decision makers, as it can be carried out within two months following the fire., Akdeniz Havzası, milyonlarca yıldan beri yangınlara maruz kalan ve yangınlar sonucunda şekillenmiş bir biyocoğrafyadır. Bu nedenle Akdeniz Havzası’ndaki yanan alanların restorasyonunda bitki türlerinin yangına uyarlanma stratejilerinin dikkate alınarak, bitki topluluklarının sonraki yangına karşı direnç ve direngenliğinin artırılmasına yönelik planlamaların yapılması gereklidir. Bu çalışma kapsamında, Marmaris civarında yaklaşık 12.500 hektarlık alanı etkilemiş olan 2021 yangını sonrasında hızlı değerlendirme metodu geliştirilerek Datça-Bozburun Özel Çevre Koruma Bölgesi (ÖÇKB) için yangın sonrası restorasyon önerileri hazırlanmıştır. Çalışmada EFFIS (European Forest Fire Information System) ve Sentinel-2 uydu görüntülerinden faydalanılarak yanan alan sınırı belirlenmiş, alan yangın şiddetinin göstergesi olarak kullanılan normalize edilmiş yanma oranı farkı (dNBR) değerlerine göre sınıflandırılmıştır. Yanan alanların yenilenme potansiyeli, farklı meşcere tipleri ve yanma oranı sınıflarında belirlenen örnekleme alanlarında kızılçam (Pinus brutia) serotin kozalak sayısı ve maki elemanlarının potansiyel örtüş yüzdelerinin ölçülmesi ile ortaya konmuştur. Boşluklu kapalı kızılçam meşcerelerinin en yüksek serotinliğe ve makiliklerden sonra en fazla sürgün verme potansiyeline sahip olduğu, genç kızılçam meşcerelerinin (a ve b çağı) ise serotinlik bakımından en düşük değerde olduğu belirlenmiştir. Elde edilen bulgular ve alanların eğim dereceleri dikkate alınarak, Datça-Bozburun ÖÇKB içerisindeki yanan alanlar için aktif ve pasif restorasyon dahil altı farklı restorasyon önerisi geliştirilmiştir. Yanan alanın %6’sının kendi haline bırakılması önerilirken, geri kalan alanlar için doğal gençleştirme + kozalaklı dal serme ve tohum ekimi destekli doğal gençleştirme yöntemleri ile teraslama ve toprak işleme sonrası fidan dikimi gibi suni gençleştirmeler önerilmiştir. Bu çalışmada geliştirilen metodolojinin, yangını takiben iki ay içinde gerçekleştirilebilmesi ve basit ve düşük maliyetli olması itibariyle, yerel uygulamacılar ve karar vericiler için uygulanabilirliği yüksektir.

Background: Natural disasters adversely impact individuals living in places where they occur, resulting in emotional distress. The wildfire that occurred in Fort McMurray (FMM), Alberta in 2016 is no different. Objective: This study aims to identify the prevalence and predictors of Generalized Anxiety Disorder (GAD) symptoms in residents of FMM five years after the devastating wildfires. Methods: Data for the study were collected through a cross-sectional survey conducted online from the 24th of April to the 2nd of June 2021. A validated instrument, the GAD-7 scale, was used to collect information on anxiety. Results: This study involved 186 residents of FMM, of which the majority were females (85.5%), employed (94.1%), working at school boards (50.0%), and were either married, cohabiting, or partnered (71.0%). The prevalence of likely GAD among the study sample was 42.5%. Unemployed respondents were seventeen times more likely to develop GAD symptoms (OR = 16.62; 95% C.I. 1.23–223.67) while respondents who would like to receive mental health counseling were five times more likely to experience GAD symptoms (OR = 5.35; 95% C.I. 2.03–14.15). Respondents who suffered a loss of property because of the wildfire were two times more likely to develop GAD symptoms (OR = 2.36; 95% C.I. 1.01–22.62). Conclusion: Policymakers may mitigate GAD symptoms, particularly after natural disasters, by making long-term mental health counseling available and a key component of post-disaster management, and by investing in the social capital of the people to build resilience and support to deal with the post-disaster mental health effects.

This is the second part of a series of two papers concerning fire-spotting generated fires. While, in the first part, we focus on the impact of macro-scale factors on the growth of the burning area by considering the atmospheric stability conditions, in the present study we focus on the impact of meso-scale factors by considering the effects of the flame geometry and terrain slope. First, we discuss the phenomenological power law that relates flame length and fireline intensity by reporting literature data, analysing a formula originally proposed by Albini, and deriving an alternative formula based on the energy conservation principle. Subsequently, we extend the physical fire-spotting parametrisation RandomFront adopted in the first part by including flame geometry and slope. Numerical examples show that fire-spotting is affected by flame geometry and, therefore, cannot be neglected in simplified fire-spread models used in operational software codes for wild- fire propagation. Meanwhile, we observe that terrain slope enhances the spread of a fire at a higher rate than the augmentation of fire-spotting generated fires, such that a rapid merging occurs among independent fires., BERC 2014–2017 BERC 2018–2021 SEV-2013-0323 MTM2016-76016-R PID2019-107685RB-I00 PhD grant “La Caixa 2014”.

Recurring wildfires pose a critical global issue as they undermine social and economic stability and jeopardize human lives. To effectively manage disasters and bolster community resilience, the development of wildfire susceptibility maps (WFSMs) has emerged as a crucial undertaking in recent years. In this research endeavor, two deep learning algorithms were leveraged to generate WFSMs using two distinct remote sensing datasets. Specifically, the Moderate-Resolution Imaging Spectroradiometer (MODIS) and Landsat-8 images were utilized to monitor wildfires that transpired during the year 2021. To develop an effective WFSM, two datasets were created by incorporating 599 wildfire locations with Landsat-8 images and 232 sites with MODIS images, as well as twelve factors influencing wildfires. Deep learning algorithms, namely the long short-term memory (LSTM) and recurrent neural network (RNN), were utilized to model wildfire susceptibility using the two datasets. Subsequently, four WFSMs were generated using the LSTM (MODIS), LSTM (Landsat-8), RNN (MODIS), and RNN (Landsat-8) algorithms. The evaluation of the WFSMs was performed using the area under the receiver operating characteristic (ROC) curve (AUC) index. The results revealed that the RNN (MODIS) (AUC = 0.971), RNN (Landsat-8) (AUC = 0.966), LSTM (MODIS) (AUC = 0.964), and LSTM (Landsat-8) (AUC = 0.941) algorithms demonstrated the highest modeling accuracy, respectively. Moreover, the Gini index was employed to assess the impact of the twelve factors on wildfires in the study area. The results of the random forest (RF) algorithm indicated that temperature, wind speed, slope, and topographic wetness index (TWI) parameters had a significant effect on wildfires in the study region. These findings are instrumental in facilitating efficient wildfire management and enhancing community resilience against the detrimental effects of wildfires.

Resin tapping has long been an important traditional economic activity in less advantaged areas that serves as a source for income to local populations as well as an important management tool intricately linked with ecosystem services. In Greece, the majority of the remaining resin tappers are located in communities close to Pinus halepensis stands in the northern part of Evia Island. However, on 3 August 2021, a wildfire burned more than 50,000 Ha in the region, bringing the remaining resin tappers to a standstill. This paper aims to examine the views of 89 resin tappers in N. Evia and their perspectives on their profession as expressed during personal interviews. According to the participants’ replies, resin production is expected to bounce back to pre-fire levels in 40 years. A considerable portion of those interviewed (39.3%) were forced to work in other professions near their communities during the period that followed the fire. They were very dissatisfied by the fire management and initial mitigation actions, and fairly satisfied by the ecosystem recovery works that followed. However, they have high expectations for employment in a seven-year long government-funded support program which will allow them to continue living in their communities, and in this context they are willing to make a professional shift to forest operations work. In this context, the role of state authorities is expected to be crucial. The provision of vocational training and financial incentives could be decisive in preventing them from transitioning to alternative production sectors.

Mapping fire risk in South Florida depends on spatially varying water levels, fuel characteristics, and topography. When surface water levels recede below the lowest topographic features (cypress strands, marshes, etc.), the ecosystem loses its natural, wetted fire breaks, and landscape-level fire risk increases. We developed a geospatial method to generate daily, categorical fire risk maps; the maps visualize low-to-high risk areas using a newly developed 100 m DEM, modeled water levels, fuel types, and fire management units. We assigned fire risk by creating a water level distribution for each unique combination of fuel type and fire management unit; fire risk was then assigned for each pixel based on risk percentiles commonly used by fire management agencies. Assigning risk based on unique fuel types and management units helped avoid over- or under-assigning fire risk that may occur when applying landscape-level “average” risk relationships. Daily maps also incorporated (1) energy release component data to better estimate fuel moisture and (2) historical burn footprints to reduce risk in recently burned areas. Our data-driven approach generated at management-relevant spatial scales may enable more informed prescribed burn planning and may increase the efficiency of staff and resource allocation across the landscape on high-wildfire-risk days.

The Camp Fire was one of California’s deadliest and most destructive wildfires, and its widespread smoke threatened human health over a large area in Northern California in November 2018. To analyze the Camp Fire influence on air quality on a 200 km distant site in Berkeley, highly time-resolved total carbon (TC), black carbon (BC), and organic carbon (OC) were measured using the Carbonaceous Aerosol Speciation System (CASS, Aerosol Magee Scientific), comprising two instruments, a Total Carbon Analyzer TCA08 in tandem with an Aethalometer AE33. During the period when the air quality was affected by wildfire smoke, the BC concentrations increased four times above the typical air pollution level presented in Berkeley before and after the event, and the OC increased approximately ten times. High-time-resolution measurements allow us to study the aging of OC and investigate how the characteristics of carbonaceous aerosols evolve over the course of the fire event. A higher fraction of secondary carbonaceous aerosols was observed in the later phase of the fire. At the same time, the amount of light-absorbing organic aerosol (brown carbon) declined with time.

This policy brief reviews the economic incentives for wildfire risk reduction beingapplied in Europe (where the bulk of action has occurred) and beyond. We present incentives addressingdecision making of landowners and managers, their administrations and communities, pointing outwhat we at this stage can learn from these experiences. This policy brief is part of Task 3.1 in WP3 of the FIRE-RES project.

The number of intense wildfires may increase in the upcoming years as a consequence of climate change. Changing aerosol conditions may lead to changes in regional and global cloud and precipitation pattern. One key aspect of research is presently whether or not wildfire smoke particles can initiate ice nucleation. We found strong evidence that aged smoke particles (dominated by organic aerosol particles) originating from wildfires in North America triggered significant ice nucleation at temperatures from−47 to −53°C and caused the formation of extended cirrus layers. Our study is based on lidar observations over Limassol, Cyprus, from 27 October to 3 November 2020 when extended wildfire smoke fields crossed the Mediterranean Basin from Portugal to Cyprus. The observations suggest that the ice crystals were nucleated just below the tropopause in the presence of smoke particles serving as ice-nucleating particles (INPs). The main part of the 2-3 km thick smoke layer was,however, in the lower stratosphere just above the tropopause. With actual radiosonde observations of temperature and relative humidity and lidar-derived smoke particle surface area concentrations as starting values, gravity wave simulations show that lofting by 90-180 m is sufficient to initiate significant ice nucleation on the smoke particles, expressed in ice crystal number concentrations of 1-100 L−1 The authors acknowledge the ‘EXCELSIOR’: ERATOSTHENES: EXcellence reseacrh Centre for Earth Surveillance and Space-Based Monitoring of the Environment H2020 Widespread Teaming project (www.excelsior2020.eu). The ‘EXCELSIOR’ project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 857510, from the Government of the Republic of Cyprus through the Directorate General for the European Programmes, Coordination and Development and the Cyprus University of Technology. The authors acknowledge support through the European Research Infrastructure for the observation of Aerosol, Clouds and Trace Gases ACTRIS under grant agreement no. 654109 and 739530 from the European Union’s Horizon 2020 research and innovation programme. The PollyXT-CYP was funded by the German Federal Ministry of Education and Research (BMBF) via the PoLiCyTa project (grant no. 1LK1603A).The study is supported by “ACCEPT” project (Prot. No: LOCALDEV-0008) co-financed by the Financial Mechanism of Norway (85%) and the Republic of Cyprus (15%) in the framework of the programming period 2014 - 2021. The lidar analysis on smoke-cirrus interaction was further supported by BMBF funding of the SCiAMO project (MOSAIC-FKZ 03F0915A). DAK acknowledges support by U.S. Department of Energy’s (DOE) Atmospheric System Research (ASR) program, Office of Biological and Environmental Research (OBER) (grant no. DE-SC0021034).

Fire events are increasing in frequency, duration, and severity worldwide. The combination of ash and uncovered land might increase the transportation of pollutants into the streams, potentially affecting the water supply systems. The intensifying fires in Brazil’s Cerrado biome, responsible for 70% of the country’s water supply, give rise to profound ecological, climatic, and socio-economic concerns that require urgent and effective mitigation strategies. However, little attention has been paid to the consequences of fire events on water resources in the region. In this study, the Fire Impact on Water Resources Index (FIWRI) is proposed and applied in six different water supply watersheds to analyse fire behaviour from 2003 to 2020 and its potential impact on inland water bodies. This is the first remote-sensing-based index for fire impact on water resources developed for the Brazilian territory, to support water management on a watershed scale and uses variables such as terrain slope, river proximity, and vegetation to classify fire events as having a low to high potential to contaminate water bodies. We observed that all six water supply watersheds suffered frequent fire events, with different FIWRI proportions, which ranged from High to Low FIWRI. The proposed index could be used in real-time fire monitoring alert systems in order to support water supply management.

Wildfires can cause debris flow events in affected areas due to changes in the physical properties of burned soils, which are linked to burn severity. A study in California’s Sierra Nevada explored the impact of burn severity on soil physical properties using various tests. Results showed that higher burn-severity soils had higher total organic carbon content and liquid limit, and the plastic limit was also higher. The plasticity index was highest among low burn-severity soils, and high burn-severity soils had lower smectite and kaolinite/chlorite abundances compared to lower burn-severity soils. Grain size distribution and shear strength were not significantly impacted by burn severity. The study suggests that total organic carbon content is the most significant factor affecting the physical and mechanical properties of soil. These findings may help assess debris flow hazards in burned areas and highlight the need for further research on the effects of wildfires on soil properties and their contribution to debris flow events.

1. Pollutants in the air we breathe are detrimental to human health. Long-term exposure to air particulate matter in Acre, Brazil, has decreased the average life expectancy by an estimated 2–3 years. Smoke from rural fires is the major source affecting air quality at Rio Branco. 2. Observations of fine particulate matter (PM2.5) have become available in Acre through the Purple Air project. Uncorrected data shows that in Rio Branco, an estimated 125 days exceeded the WHO’s daily guidance for PM2.5 levels during the dry season in 2019. 3. Satellite observations indicate that rural fires are densely distributed around Rio Branco itself, North Rondônia, as well as northeastern and central Bolivia. 4. The source of the smoke arriving at Rio Branco within 6 days comes from nearby areas to the north and east (64% of the time), from the south (31% of the time) or from the east (5% of the time). The average 6-day air parcel spends half of its time inside a radius of just 266 km around Rio Branco. 5. Rural fires around Rio Branco are expected to increase due to changes in climate by 38% within 500 km by 2090, under the fossil fuel intensive IPCC scenario. Our analysis also shows that the number of smoke-producing rural fires within two days of wind transport of Rio Branco is expected to increase by a third by 2090. This does not include the effect of increased tree mortality in the region or changes in land cover and land use. 6. To improve air quality, fires must be reduced now from their present level. For more information about this analysis, or Woodwell’s other climate risk assessments, please contact us at policy@woodwellclimate.org. To learn more about Woodwell, please visit our website at woodwellclimate.org.

Record-breaking wildfires raged in southeastern Australia in late December 2019 and early January 2020. Rather strong pyrocumulonimbus (pyroCb) convection developed over the fire areas and lofted enormous amounts of biomass burning smoke into the tropopause region and caused the strongest wildfire-related stratospheric aerosol perturbation ever observed around the globe. We discuss the geometrical, optical, and microphysical properties of the stratospheric smoke layers and the decay of this major stratospheric perturbation. A multiwavelength polarization Raman lidar at Punta Arenas (53.2∘ S, 70.9∘ W), southern Chile, and an elastic backscatter Raman lidar at Río Grande (53.8∘ S, 67.7∘ W) in southern Argentina, were operated to monitor the major record-breaking event until the end of 2021. These lidar measurements can be regarded as representative for mid to high latitudes in the Southern Hemisphere. A unique dynamical feature, an anticyclonic, smoke-filled vortex with 1000 km horizontal width and 5 km vertical extent, which ascended by about 500 m d−1, was observed over the full last week of January 2020. The key results of the long-term study are as follows. The smoke layers extended, on average, from 9 to 24 km in height. The smoke partly ascended to more than 30 km height as a result of self-lofting processes. Clear signs of a smoke impact on the record-breaking ozone hole over Antarctica in September–November 2020 were found. A slow decay of the stratospheric perturbation detected by means of the 532 nm aerosol optical thickness (AOT) yielded an e-folding decay time of 19–20 months. The maximum smoke AOT was around 1.0 over Punta Arenas in January 2020 and thus 2 to 3 orders of magnitude above the stratospheric aerosol background of 0.005. After 2 months with strongly varying smoke conditions, the 532 nm AOT decreased to 0.03-0.06 from March–December 2020 and to 0.015–0.03 throughout 2021. The particle extinction coefficients at 532 nm were in the range of 10–75 Mm−1 in January 2020 and, later on, mostly between 1 and 5 Mm−1. Combined lidar–photometer retrievals revealed typical smoke extinction-to-backscatter ratios of 69 ± 19 sr (at 355 nm), 91 ± 17 sr (at 532 nm), and 120 ± 22 sr (at 1064 nm). An ozone reduction of 20 %–25 % in the 15–22 km height range was observed over Antarctica and New Zealand ozonesonde stations in the smoke-polluted air, with particle surface area concentrations of 1–5 µm2 cm−3.

Many fire management agencies aim to detect and suppress all ignitions within their jurisdiction and may benefit from understanding the causes of year-to-year variation. Ignition variation is likely to be associated with climatically driven changes in fuel quantity or moisture in landscapes where ignition sources vary little over similar temporal scales. We assessed how monthly ignitions varied in south-eastern Australia in response to climate anomalies over approximately nine years. Once accounting for seasonal effects, ignitions increased with temperature and vapour pressure deficit anomalies and decreased with precipitation anomalies. These findings indicate that climatic conditions play a role in limiting ignition frequency via effects on fuel moisture. Our models predicted that warmer and drier conditions during our study caused considerable increases in ignition frequency compared to the long-term average reference period (1961–1990). Like many fire-prone landscapes around the world, our study area is projected to become hotter and drier because of climate change. Fire management agencies will need to improve fire detection and suppression capabilities under a future climate.

With climate change and the resulting rise in temperatures, wildfire risk is increasing all over the world, particularly in the Western United States. Communities in wildland–urban interface (WUI) areas are at the greatest risk of fire. Such fires cause mass evacuations and can result in traffic congestion, endangering the lives of both citizens and first responders. While existing wildfire evacuation research focuses on social science surveys and fire spread modeling, they lack data on traffic operations during such incidents. Additionally, traditional traffic data collection methods are unable to gather large sets of data on historical wildfire events. However, the recent availability of connected vehicle (CV) data containing lane-level precision historical vehicle movement data has enabled researchers to assess traffic operational performance at the region and timeframe of interest. To address this gap, this study utilized a CV dataset to analyze traffic operations during a short-notice evacuation event caused by a wildfire, demonstrating that the CV dataset is an effective tool for accurately assessing traffic delays and overall traffic operation conditions during the selected fire incident. The findings also showed that the selected CV dataset provides high temporal coverage and similar travel time estimates as compared to an alternate method of travel time estimation. The study thus emphasized the importance of utilizing advanced technologies, such as CV data, to develop effective evacuation strategies and improve emergency management.

Fires and their associated carbon and air pollutant emissions have a broad range of environmental and societal impacts, including negative effects on human health, damage to terrestrial ecosystems, and indirect effects that promote climate change. Previous studies investigated future carbon emissions from the perspective of response to climate change and population growth, but the compound effects of other factors like economic development and land use change are not yet well known. We explored fire carbon emissions throughout the 21st century by changing five factors (meteorology, biomass, land use, population density, and gross domestic product [GDP] per capita). Compared to the historical period (2006–2015), global future fire carbon emissions decreased, mainly caused by an increase in GDP per capita, which leads to improvement in fire management and capitalized agriculture. We found that the meteorological factor has a strong individual effect under higher warming cases. Fires in boreal forests were particularly expected to increase because of an increase in fuel dryness. Our research should help climate change researchers consider fire-carbon interactions. Incorporating future spatial changes under diverse scenarios will be helpful to develop national mitigation and adaptation plans.

Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (MobileNet) was trained to identify key features of various satellite images that contained fire or without fire. Then, the trained system is used to classify new satellite imagery and sort them into fire or no fire classes. A cloud-based development studio from Edge Impulse Inc. is used to create a NN model based on the transferred learning algorithm. The effects of four hyperparameters are assessed: input image resolution, depth multiplier, number of neurons in the dense layer, and dropout rate. The computational cost is evaluated based on the simulation of deploying the neural network model on an Arduino Nano 33 BLE device, including Flash usage, peak random access memory (RAM) usage, and network inference time. Results supported that the dropout rate only affects network prediction performance; however, the number of neurons in the dense layer had limited effects on performance and computational cost. Additionally, hyperparameters such as image size and network depth significantly impact the network model performance and the computational cost. According to the developed benchmark network analysis, the network model MobileNetV2, with 160 × 160 pixels image size and 50% depth reduction, shows a good classification accuracy and is about 70% computationally lighter than a full-depth network. Therefore, the proposed methodology can effectively design an ML application that instantly and efficiently analyses imagery from a spacecraft/weather balloon for the detection of wildfires without the need of an earth control centre.

11 Pág., Background: More than a decade of fire suppression has changed the structure of fire-adapted shrubland ecosystems in Spain's National Parks, which are now at extreme risk of uncontrolled wildfires. Prescribed burning can mitigate the risk of wildfires by reducing the fuel load but prescribed burning may also alter the soil properties and reduce microbial and fungal activity, causing changes in the availability of nutrients deep in the soil layer. Although fungal communities are a vital part of post-fire restoration, some fire effects remain unclear. To examine the short-term effects of prescribed burning on soil fungal communities in Doñana Biological Reserve (SW Spain), we collected soil samples pre-burn and 1 day, 6 and 12 months post-burn from burned plots to perform physicochemical and metabarcode DNA analyses. Results: Prescribed burning had no significant effect on the total fungal operational taxonomic unit richness and abundance. However, changes in soil pH, nitrogen and potassium content post-burn affected fungal community composition. Small non-significant changes in pH and phosphorous affected the composition of ectomycorrhizal fungi. Conclusions: The ectomycorrhizal fungal community appears to be resilient to the effects of low-to moderate-intensity fires and saprotrophic taxa may benefit from this kind of fire. This finding revealed that prescribed burning is a potentially valuable management tool for reducing fire hazards in shrublands that has little effect on the total richness and abundance of fungal communities., This research was funded by: Spanish R&D projects MYCOINFOR (Mycosilviculture Applied to Forest Fire Prevention in Mediterranean Systems; PID2019-105188RB-I00); VIS4FIRE (Comprehensive vulnerability of forest systems to fire: implications for forest management tools; RTA2017-00042-C05-01); and Interreg-POCTEP CILIFO (Iberian Centre for Research and Forest Firefighting; 0753-CILIFO-5-E). This study was also financed by European Social Fund “NextGenerationEU” through a grant “Margarita Salas” awarded to Juncal Espinosa into the project GFIRE.

Ethnographic observations suggest that Indigenous peoples employed a distinct regime of frequent, low-intensity fires in the Australian landscape in the past. However, the timing of this behaviour and its ecological impact remain uncertain. Here, we present detailed analysis of charcoal, including a novel measure of fire severity using Fourier transform infrared (FTIR) spectroscopy, at a site in eastern Australia that spans the last two glacial/interglacial transitions between 135–104 ka and 18–0.5 ka BP (broadly equivalent to Marine Isotope Stage (MIS) 6-5 and 2-1, respectively). The accumulation of charcoal and vegetation composition was similar across both periods, correlating closely with Antarctic ice core records, and suggesting that climate is the main driver of fire regimes. Fire severity was lower over the past 18,000 years compared to the penultimate glacial/interglacial period and suggests increasing anthropogenic influence over the landscape during this time. Together with local archaeological records, our data therefore imply that Indigenous peoples have been undertaking cultural burning since the beginning of the Holocene, and potentially the end of the Last Glacial Maximum. We highlight the fact that this signal is not easily discernible in the other proxies examined, including widely used charcoal techniques, and propose that any anthropogenic signal will be subtle in the palaeo-environmental record. While early Indigenous people’s reasons for landscape burning were different from those today, our findings nonetheless suggest that the current land management directions are based on a substantive history and could result in a reduction in extreme fire events.

Wildfire modifies the short- and long-term exchange of carbon between terrestrial ecosystems and the atmosphere, with impacts on ecosystem services such as carbon uptake. Dry western US forests historically experienced low-intensity, frequent fires, with patches across the landscape occupying different points in the fire-recovery trajectory. Contemporary perturbations, such as recent severe fires in California, could shift the historic stand-age distribution and impact the legacy of carbon uptake on the landscape. Here, we combine flux measurements of gross primary production (GPP) and chronosequence analysis using satellite remote sensing to investigate how the last century of fires in California impacted the dynamics of ecosystem carbon uptake on the fire-affected landscape. A GPP recovery trajectory curve of more than five thousand fires in forest ecosystems since 1919 indicated that fire reduced GPP by 157.4 ± 7.3 g C m − 2 y − 1 ( mean ± SE, n = 1926 ) in the first year after fire, with average recovery to prefire conditions after ∼ 12 y. The largest fires in forested ecosystems reduced GPP by 393.8 ± 15.7 g C m − 2 y − 1 ( n = 401) and took more than two decades to recover. Recent increases in fire severity and recovery time have led to nearly 9.9 ± 3.5 MMT CO 2 (3-y rolling mean) in cumulative forgone carbon uptake due to the legacy of fires on the landscape, complicating the challenge of maintaining California’s natural and working lands as a net carbon sink. Understanding these changes is paramount to weighing the costs and benefits associated with fuels management and ecosystem management for climate change mitigation.

From 9 March 2015, a wildfire burned an area of 25.7 km2, or approximately half of the Jonkershoek catchment (Western Cape, South Africa), over the course of 3 days. During this period, large areas of fynbos and commercial forest plantations were razed, and rocks, including boulders and smaller rocks, were exposed to high temperatures. While a substantial body of work has been carried out to investigate the effects of wildfire on landscape development, less is known about the effect of wildfire on rock weathering within a landscape. Previous studies have reported the overall effect of wildfire on rock deterioration, but the effect of intra-fire temperature differences associated with heat behaviour on a slope has not been sufficiently addressed. In this study we investigate the effects of topography and proximity to moisture on rock deterioration processes. In particular, we focus on the use of in-field rock deterioration measurements and GIS to investigate the relative influences of distance from burn source, distance from moisture source and topographical positioning of the sample site. The results indicate that boulder size and lithology are of secondary importance to the placement of fire-affected rocks within the wider topography of the landscape, and that rock exposure to moisture, also a function of landscape position, is likely to exacerbate the response of the rocks to heat. No direct correlation was observed between the type and severity of the outwardly visible damage sustained on the sampled rocks, and the size, lithology or proximity to burn source. We argue that these findings call for a re-evaluation of fire-related damage in the wider context of rock response as a function of topographical variations.

Objectives Due to accelerating wildland fire activity, there is mounting urgency to understand, prevent, and mitigate the occupational health impacts associated with wildland fire suppression. The objectives of this review of academic and grey literature were to: Identify the impact of occupational exposure to wildland fires on physical, mental, and emotional health; and Examine the characteristics and effectiveness of prevention, mitigation, or management strategies studied to reduce negative health outcomes associated with occupational exposure to wildland fire. Methods Following established scoping review methods, academic literature as well as government and industry reports were identified by searching seven academic databases and through a targeted grey literature search. 4679 articles were screened using pre-determined eligibility criteria. Data on study characteristics, health outcomes assessed, prevention or mitigation strategies studied, and main findings were extracted from each included document. The results of this scoping review are presented using descriptive tables and a narrative summary to organize key findings. Results The final sample was comprised of 100 articles: 76 research articles and 24 grey literature reports. Grey literature focused on acute injuries and fatalities. Health outcomes reported in academic studies focused on respiratory health (n = 14), mental health (n = 16), and inflammation and oxidative stress (n = 12). The identified studies evaluated short-term outcomes measuring changes across a single shift or wildland fire season. Most research was conducted with wildland firefighters and excluded personnel such as aviation crews, contract crews, and incident management teams. Five articles reported direct study of mitigation strategies, focusing on the potential usage of masks, advanced hygiene protocols to reduce exposure, fluid intake to manage hydration and core temperature, and glutamine supplementation to reduce fatigue. Conclusions While broad in scope, the evidence base linking wildland fire exposure to any one health outcome is limited. The lack of long-term evidence on changes in health status or morbidity is a clear evidence gap and there is a need to prioritize research on the mental and physical health impact of occupational exposure to wildland fire.

Wildfires are a major concern around the globe because of the immediate impact they have on people's lives, local ecosystems, and the environment. Soil moisture is one of the most important factors that influence wildfire occurrences and spread. However, it is also one of the most challenging hydrological variables to measure routinely and accurately. Therefore, soil moisture is significantly underutilized in operational wildfire risk applications. Thus, the aim here is to use a well-established operational soil moisture product to isolate the soil moisture-fire relationship and assess the utility of using soil moisture as a leading indicator of potential fire risk. We evaluated the value of remotely-sensed soil moisture observations from the soil moisture active passive sensor for monitoring and predicting fire risk in Australia and California. We quantified the relationship between observed fire activity and soil moisture conditions and analyzed the soil moisture conditions for two extreme fire events. Our findings show that fire activity is strongly associated with soil moisture anomalies. Lagged correlation analysis demonstrated that a remote-sensing based soil moisture product could predict fire activity with a 1–2 month lead-time. Soil moisture anomalies consistently decreased in the months preceding fire occurrence, often from normal to drier conditions, according to a spatiotemporal analysis of soil moisture in two extreme fire events. Overall, our findings indicate that soil moisture conditions prior to large wildfires can aid in their prediction and operational satellite-based soil moisture products such as the one used here have real value for supporting wildfire susceptibility and impacts.

The present work focus was developing a system for early automatic detection of smoke plumes in visible-light images. The system used a realistic dataset gathered in 274 different days from a total of nine real surveillance cameras, with most smoke plumes being viewed from afar and 85% of them occupying less than 5% of the image area. We employed the innovative strategy of using the whole image for classification but “asking” the neural networks to indicate, in a multidimensional output, which image regions contained a smoke plume. The multidimensional output helped to focus the detector on the smoke regions. At the same time, the use of the whole image prevented wrong image classification caused by a constrained view of the landscape under analysis. Another strategy used was to rectify the detection results using a visual explanation algorithm, Gradient-weighted Class Activation Mapping (Grad-CAM), to ensure that detections corresponded to the smoke regions in an image. The detection algorithms tested were residual neural networks (ResNet) and EfficientNet of various sizes because these two types have given good results in the past in multiple domains. The training was done using transfer learning. Our dataset contained a total of 14125 and 21203 images with and without smoke, respectively, making it, to the best of the author’s knowledge, one of the largest or even the largest reported dataset in the scientific literature in terms of the number of images with smoke collected from large distances of various kilometers. This dataset was fundamental to achieve realistic results concerning smoke detection efficiency. Our best result in the test set was an Area Under Receiver Operating Characteristic curve (AUROC) of 0.949 obtained with an EfficientNet-B0.

Anthropogenic disturbances, including wildfires, threaten the diversity of tropical Andean ecosystems. However, the response of tropical Andean plant communities to wildfires in human-modified landscapes has to be discovered. Quercus humboldtii is the southernmost species of this genus in the Neotropics and is almost exclusively distributed in Colombia. While the extent of Q. humboldtii forests has decreased recently, to what time these results from the species' inability to thrive under the current climate and disturbance regimes are still being determined. In this study, we describe post-fire resprouting and acorn and seedling density in and around Q. humboldtii forest patches in the Iguaque mountains in Colombia. We discuss the implications for the conservation and restoration of these forests. Resprouting probability was high in burned trees two years after the fire (ca. 80%). Resprouting ability depended on fire severity and tree size. The proportion of trees resprouting from the stump was related to the severity of fire damage and tree size. Acorn density was higher in burned than unburned areas and depended on the slope, distance to the forest edge, and distance to the nearest oak. Conversely, the density of healthy acorns was low across all sites, particularly in burned areas. Seedling density was relatively high in unburned areas, but seedlings could not withstand recurrent fires. The density of acorns and seedlings decreased in the periphery of forest patches. Despite the strong impact of fire on forest structures, Quercus humboldtii adults may withstand the current fire regime thanks to their strong capacity for vegetative and sexual regeneration. However, the ability of this species to establish in areas where oaks are no longer present is scarce. As Q. humboldtii forest cover and spatial continuity have decreased in response to the increasing frequency of wildfires, the current fire regime represents a threat to the recovery of this species. Our results have important implications for the management of Q. humboldtii and Andean forests as they emphasize the need to control the severity and frequency of wildfires and to use assisted regeneration to restore Q. humboldtii forests in degraded areas. This work was supported by the Research Institute of Biological Resources Alexander von Humboldt, Colombia. In addition, JCS participation is financially supported by the Spanish Ministry of Science and Innovation and European Regional Development Funds (FEDER; project COSTERA, RTI2018-095954-B-I00) and Generalitat Valenciana, Conselleria d'Innovació, Universitats, Ciència i Societat Digital (R2D, CIPROM/2021/001).

Volcanic islands are special ecosystems for studying biogeographical and evolutionary processes. Occasional disturbance events, such as eruptions, tsunami or big fires, can represent major drivers of such processes leading to biotic sterilisation or major changes in island biotas. In this study, through remotely sensed data, we investigated the intensity and the extent of a large fire event that occurred on the small volcanic island of Stromboli (Aeolian archipelago, Italy) on 25–26 May 2022, to assess the short-term effect of fire damages on local plant communities. For this purpose, two different spectrally sensitive indices, i. e. the differential Normalised Burned Index (dNBR) and the Normalised Difference Vegetation Index (NDVI), were used. The dNBR was also used to quantify the extent of early-stage vegetation recovery, dominated by Saccharum biflorum Forssk. (Poaceae), a rhizomatous C4 perennial grass of paleotropical origin. The burned area was estimated to have an extension of around 337.83 ha, corresponding to 27.7 % of the island surface and to 49.8 % of Stromboli’s vegetated area. On the one hand, this event considerably damaged the native plant communities, hosting many species of high biogeographic interest. On the other hand, Saccharum biflorum clearly benefited from arson. In fact, it showed a very high vegetative performance after burning, being able to exert unchallenged dominance in the early stages of the post-fire succession, reaching within a few months stem density values that are only slightly lower than those of the unburned stands. Our results confirm the complex and probably synergic impact of different human disturbances (recurrent fires, introduction of invasive alien plants) on the structure and the functioning of natural ecosystems on small volcanic islands. The natural dynamics of such ecosystems is dependent on the complex relation between successional processes and the intensity and frequency of natural or anthropogenic disturbance, which can regulate mid- and long-term response of Saccharum. In fact, although the expansion of Saccharum proves to be surprisingly fast, its decline may also be relatively rapid as well, if local vegetation is no more affected by fire. After the abandonment of the agricultural practices in the highest portion of the island, the rewilding process could lead to the replacement of the large beds dominated by this invasive grass by native woody vegetation within a few decades.

Understanding the benefits provided by restoring overstocked forests is crucial to guiding the choice of management actions, policy initiatives, and investments by beneficiaries, that is, monetizing ecosystem services. Using stakeholder-based fuzzy cognitive mapping, collected through workshops with natural-resource professionals, we mapped the interactions of ecosystem services and the perceived effects of management actions on them. In line with current concerns in the California study area, we found that fire protection was perceived as central (i.e., having a high degree of congruence with other ecosystem services) with improved fire protection providing important secondary effects on other ecosystem services, notably air-quality protection, provision of habitat, and carbon storage. Forest restoration involves multiple fuels-reduction actions, which were perceived as benefiting fire protection, with subsets also offering strong benefits to other ecosystem services. Prescribed burning, defensible-space creation, understory thinning, and replanting showed particularly large differences in effects when accounting for interactions of ecosystem services. Resource managers and other nonmanager professionals prioritized similar ecosystem services, with the second group placing more importance on interactions between different ecosystem services. Ecosystem-service valuation that includes interactions offers a salient, credible, and legitimate approach to inform multi-benefit forest management, particularly where partnerships must monetize some of those benefits to finance critical landscape restoration.

Few fires are known to have burned the tundra of the Arctic Slope north of the Brooks Range in Alaska, USA. A total of 90 fires between 1969 and 2022 are known. Because fire has been rare, old burns can be detected by the traces of thermokarst and distinct vegetation they leave in otherwise uniform tundra, which are visible in aerial photograph archives. Several prehistoric tundra burns have been found in this way. Detection of tundra fires in this sparsely populated and remote area has been historically inconsistent and opportunistic, relying on reports by aircraft pilots. Fire reports have been logged into an administrative database which, out of necessity, has been used to scientifically evaluate changes in the fire regime. To improve the consistency of the record, we completed a systematic search of Landsat Collection 2 for the Brooks Range Foothills ecoregion over the period 1972–2022. We found 57 unrecorded tundra burns, about 41% of the total, which now numbers 138. Only 15% and 33% of all fires appear in MODIS and VIIRS satellite-borne thermal anomaly products, respectively. The fire frequency in the first 37 years of the record is 0.89 y−1 for natural ignitions that spread ≥10 ha. Frequency in the last 13 years is 2.5 y−1, indicating a nearly three-fold increase in fire frequency.

We analyzed the distribution and number of forest fire occurrences, burned areas, and seasonality, and their trends of human- and lightning-caused small (

Wildfires are increasing in scale, frequency and longevity, and are affecting new locations as environmental conditions change. This paper presents a dataset collected during a community evacuation drill performed in Roxborough Park, Colorado (USA) in 2019. This is a wildland-urban interface community including approximately 900 homes. Data concerning several aspects of community response were collected through observations and surveys: initial population location, pre-evacuation times, route use, and arrival times at the evacuation assembly point. Data were used as inputs to benchmark two evacuation models that adopt different modelling approaches. The WUI-NITY platform and the Evacuation Management System model were applied across a range of scenarios where assumptions regarding pre-evacuation delays and the routes used were varied according to original data collection methods (and interpretation of the data generated). Results are mostly driven by the assumptions adopted for pre-evacuation time inputs. This is expected in communities with a low number of vehicles present on the road and relatively limited traffic congestion. The analysis enabled the sensitivity of the modelling approaches to different datasets to be explored, given the different modelling approaches adopted. The performance of the models were sensitive to the data employed (derived from either observations or self-reporting) and the evacuation phases addressed in them. This indicates the importance of monitoring the impact of including data in a model rather than simply on the data itself, as data affects models in different ways given the modelling methods employed. The dataset is released in open access and is deemed to be useful for future wildfire evacuation modelling calibration and validation efforts. This study was supported by National Institute of Standards and Technology, U.S. Department of Commerce under award 60NANB18D255. The EMS was developed by the University of Cantabria within the ASSISTANCE project funded by the European Union’s H2020 research and innovation programme under grant agreement No. 832576.

The wildland-urban interface (WUI) is simply where human development mingles with wildland, or in other words, developed land next to undeveloped land. This area is at the highest risk for damage from wildfire. As our communities grow outward, the WUI is only expanding, putting more people at risk from wildfire. Therefore, it is important for homes built there to have fire-protective landscaping. Also, because Utah is a desert state currently in a drought, low-water landscaping is important for all Utah landscapes, including the WUI. This fact sheet addresses these issues and provides guidance on fire-protective and low-water landscaping.

To evaluate the impact of different plume rise schemes on aerosol dispersion and photochemistry modeling during the 2020 recording-breaking wildfire season, four CMAQ simulations were conducted. In the first run (B69), we used the CMAQ default plume rise scheme based on Briggs (1969). In the second run (F07), we implemented the Freitas et al. (2007) scheme into the CMAQ model and used it to calculate the plume injection height. In the third run (S12), we used the Sofiev et al. (2012) plume rise scheme as implemented in Li et al. (2021). In the fourth run (NoFire), we turned off all types of biomass burning emissions. Wildfire impact is represented by the difference between the simulation with fire and the NoFire run. All four experiments were conducted using the George Mason University (GMU) air quality modeling system. This system uses CMAQ Version 5.3.1 (U.S. EPA, 2020a) as the chemical transport model and the Weather Research and Forecasting (WRF; Skamarock et al., 2019) model V4.2 output as the meteorology inputs for the CMAQ model. The model domain is configured with 12 km by 12 km horizontal resolution and 35 vertical layers (the same horizontal and vertical resolution as NOAA’s operational National Air Quality Forecasting Capability). The initial and boundary conditions for WRF are from the Global Data Assimilation System (GDAS) 0.25-degree analysis and forecast. The main physics choices were the Grell-Freitas scheme (Grell & Freitas, 2014) for parameterized cumulus processes, the Mellor-Yamada-Janjic scheme (Janjic, 1994) for planetary boundary layer (PBL) processes, the two-moment Morrison microphysics (Morrison et al., 2009) for cloud physics processes, the RRTMG scheme (Iacono et al., 2008) for longwave and shortwave radiation, and the Noah scheme (Koren et al., 1999) for land surface processes. The biomass burning emissions product used in this study is the 0.1 degree daily blended Global Biomass Burning Emissions Product from Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) (GBBEPx V3, Zhang, et al., 2012, 2019). The GBBEPx Fire radiative power (FRP) in the GBBEPx is averaged from observations from MODIS on Terra and Aqua MODIS and VIIRS M-band on Suomi National Polar-orbiting Partnership (SNPP) and the Joint Polar Satellite System-1 (JPSS) VIIRS. A climatological diurnal cycle from the Western Regional Air Partnership (WRAP) work was applied to the daily GBBEPx emission to derive hourly model-ready emission input. Anthropogenic emissions were prepared with the 2016v1 Emissions Modelling Platform, using the baseline emissions taken from the National Emissions Inventory (NEI) 2016 Collaborative (Eyth et al., 2020). We then shifted the base year emission to the prediction year 2020 using representative days of each month (U.S. EPA, 2020b). The model-ready emission files are processed and generated by the Sparse Matrix Operator Kernel Emissions (SMOKE) model (Houyoux et al., 2000) V4.7. The CB6 gas-phase chemical mechanism (Luecken et al., 2019), AE07 aerosol scheme (Pye et al., 2015; Xu et al., 2018), and aqueous chemistry (Fahey et al., 2017) is used in the CMAQ system. Details about the system setup are shown in Li et al. (2021)., {"references":["Briggs, G. A.: Plume rise, Tech. Rep. Crit. Rev. Ser. 81pp., Natl. Tech. Inf. Serv., Springfield, VA, 1969.","Freitas, S. R., Longo, K. M., Chatfield, R., Latham, D., Silva Dias, M. A. F., Andreae, M. O., Prins, E., Santos, J. C., Gielow, R., & Carvalho, J. A. Jr.: Including the sub‐grid scale plume rise of vegetation fires in low resolution atmospheric transport models. Atmospheric Chemistry and Physics, 7(13), 3385– 3398. https://doi.org/10.5194/acp-7-3385-2007, 2007.","Sofiev, M., Ermakova, T., & Vankevich, R.: Evaluation of the smoke-injection height from wild-land fires using remote-sensing data. Atmospheric Chemistry and Physics, 12(4), 1995–2006. https://doi.org/10.5194/acp-12-1995-2012, 2012.","Li, Y., Tong, D., Ma, S., Zhang, X., Kondragunta, S., Li, F., & Saylor, R.: Dominance of wildfires impact on air quality exceedances during the 2020 record-breaking wildfire season in the United States. Geophysical Research Letters, 48, e2021GL094908. https://doi.org/10.1029/2021GL094908, 2021.","United States Environmental Protection Agency: CMAQ (Version 5.3.2) [Software]. Available from https://doi.org/10.5281/zenodo.4081737, 2020a.","United States Environmental Protection Agency: Technical Support Document (TSD) Preparation of Emissions Inventories for 2016v1 North American Emissions Modeling Platform, section 3.3, p120-121. Available at: https://www.epa.gov/sites/default/files/2020-10/documents/2016v1_emismod_tsd_508.pdf, 2020b.","Skamarock, W. C., J. B. Klemp, J. Dudhia, D. O. Gill, Z. Liu, J. Berner, W. Wang, J. G. Powers, M. G. Duda, D. M. Barker, and X.-Y. Huang: A Description of the Advanced Research WRF Version 4. NCAR Tech. Note NCAR/TN-556+STR, 145 pp, doi:10.5065/1dfh-6p97, 2019.","Grell, G. A., & Freitas, S. R.: A scale and aerosol aware stochastic convective parameterization for weather and air quality modeling. Atmospheric Chemistry and Physics, 14(10), 5233–5250. https://doi.org/10.5194/acp-14-5233-2014, 2014.","Janjić, Z. I.: The Step-Mountain Eta Coordinate Model: Further developments of the convection, viscous sublayer, and turbulence closure schemes. Monthly Weather Review, 122(5), 927–945. https://doi.org/10.1175/1520-0493(1994)1222.0.CO;2, 1994.","Morrison, H., Thompson, G., & Tatarskii, V.: Impact of cloud microphysics on the development of trailing Stratiform precipitation in a simulated squall line: Comparison of one- and two-moment schemes. Monthly Weather Review, 137(3), 991–1007. https://doi.org/10.1175/2008MWR2556.1, 2009.","Iacono, M. J., Delamere, J. S., Mlawer, E. J., Shephard, M. W., Clough, S. A., & Collins, W. D.: Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models. Journal of Geophysical Research, 113, D13103. https://doi.org/10.1029/2008JD009944, 2008.","Koren, V., Schaake, J., Mitchell, K., Duan, Q.-Y., Chen, F., & Baker, J. M.: A parameterization of snowpack and frozen ground intended for NCEP weather and climate models. Journal of Geophysical Research, 104, 19,569–19,585. https://doi.org/10.1029/1999JD900232, 1999.","Zhang, X., Kondragunta, S., Da Silva, A., Lu, S., Ding, H., Li, F., & Zhu, Y.: The blended global biomass burning emissions product from MODIS and VIIRS observations (GBBEPx) version 3.1, https://www.ospo.noaa.gov/Products/land/gbbepx/docs/GBBEPx_ATBD.pdf, 2019.","Zhang, X., Kondragunta, S., Ram, J., Schmidt, C., & Huang, H.-C.: Near-real-time global biomass burning emissions product from geostationary satellite constellation. Journal of Geophysical Research: Atmospheres, 117(D14). https://doi.org/10.1029/2012JD017459, 2012.","Eyth, A., Vukovich, J., Farkas, C., & Strum, M.: Technical Support Document (TSD) Preparation of Emissions Inventories for 2016v1 North American Emissions Modeling Platform, 2020.","Houyoux, M., Vukovich, J., Brandmeyer, J. E., Seppanen, C., & Holland, A.: Sparse matrix operator kernel emissions modeling system-SMOKE User manual. Prepared by MCNC-North Carolina Supercomputing Center, Environmental Programs, Research Triangle Park, NC, 2000.","Luecken, D.J., Yarwood, G., & Hutzell, W.H.: Multipollutant of ozone, reactive nitrogen and HAPs across the continental US with CMAQ-CB6. Atmospheric Environment, 201, 62-72. doi: 10.1016/j.atmosenv.2018.11.060, 2019.","Pye, H.O.T., Luecken, D.J., Xu, L., Boyd, C.M, Ng, N.L., Baker, K.R., Ayres, B.R., Bash, J.O., Baumann, K., Carter, W. P.L., Edgerton, E., Fry, J.L., Hutzell, W.T., Schwede, D.B., Shepson, P.B.: Modeling the current and future roles of particulate organic nitrates in the southerneastern United States. Environ Sci Technol 2015, 49(24), 14195-14203. doi: 10.1021/acs.est.5b03738, 2015.","Xu, L., Pye, H. O. T., He, J., Chen, Y. L., Murphy, B. N., Ng, N. L.: Experimental and model estimates of the contributions from biogenic monoterpenes and sesquiterpenes to secondary organic aerosol in the southeastern United States. Atmos. Chem. Phys., 18: 12613-12637. doi: 10.5194/acp-18-12613-2018, 2018.","Fahey, K.M., Carlton, A.G., Pye, H.O.T., Baek, J., Hutzell, W.T., Stanier, C.O., Baker, K.R., Appel, K.W., Jaoui, M., & Offenberg, J.H.: A framework for expanding aqueous chemistry in the Community Multiscale Air Quality (CMAQ) model version 5.1. Geoscientific Model Development, 10, 1587-1605. doi: 10.5194/gmd-10-1587-2017, 2017."]}

Wildfires are worsening in Canada and globally, partly due to climate change. The government of Canada is designing and building WildFireSat, the world’s first purpose-built operational satellite system for wildfire monitoring. It will provide new fire intelligence to support decision-making. It takes time for fire management agencies to use new information: to understand it and its implications, change processes, develop training, and modify computer systems. Preparing for the system’s prelaunch will allow agencies to benefit more rapidly from the new information. We present (1) an assessment of the readiness of 12 Canadian fire management agencies to integrate WildFireSat information and (2) guidance for reducing readiness gaps. We used survey and other data to score readiness indicators for three readiness components: understanding, organization, and information technology. We weighted the influence of each indicator score on each component. We modelled scoring and weighting uncertainties and used Monte Carlo simulation to generate distributions of aggregated agency readiness. The results indicated that most agencies have a moderate level of readiness while others have a higher level of readiness. Cluster analysis was used to group agencies by similarity in multiple dimensions. Strategies for increasing readiness are highlighted. This identifies opportunities for agencies and the WildFireSat team to collaborate on enhancing readiness for the forthcoming WildFireSat data products.

Fires are one of the most widespread factors of changes in the ecosystems of boreal forests. The paper presents the results of a study of the morphological and physicochemical properties and soil organic matter (SOM) of Albic Podzols under pine forests (Pinus sylvestris L.) of the middle taiga zone of Siberia (Krasnoyrsky kray) with various time passed after a surface fire (from 1 to 121 years ago). The influence of forest fires in the early years on the chemical properties of Albic Podzols includes a decrease in acidity, a decrease in the content of water-soluble compounds of carbon and nitrogen and an increase in the content of light polycyclic aromatic hydrocarbons (PAHs) in organic and upper mineral horizons. Podzols of pine forests that were affected by fires more than forty-five years ago are close to manure forest soils according to most physical and chemical properties. Significant correlations were found between the thickness (r = 0.75, p < 0.05), the moisture content (r = 0.90, p < 0.05) of organic horizons and the content of ∑PAHs in the organic horizon (r = −0.71, p < 0.05) with the time elapsed after the fire (i.e., from 1 to 121 years). The index of the age of pyrogenic activity (IPA) calculated as the ratio of ∑ PAHs content in the organic horizon to ∑ PAHs at the upper mineral horizon is significantly higher in forests affected by fires from 1 to 23 years than for plots with «older» fires (45–121 years). Thus, the article presents the conserved and most changing factors under the impact of fires in the boreal forests of Russia.

Wildfires are an increasing concern due to rising temperatures and incidence of droughts associated with changing climate, poor land management, and direct human interference. Most studies of the impact of fire on temperate heathland and bog examined the consequences of controlled or prescribed burning. Less is known about the impacts of uncontrolled wildfires on sites designated for their conservation value. We examined the initial impact and short-term trajectory (3.5 years) of cool temperate peatland plant and arthropod communities on designated upland sites in Northern Ireland following wildfires, that is, unplanned with respect to where and when they occur, severity, and duration. These near simultaneous wildfires were often due to a failure to control prescribed burns. Wildfires were associated with a loss of blanket bog and heath indicator species. Broad vegetation groups showed initial recovery characterized by a decrease in bare ground and increasing cover of shrub species and bryophytes. However, at a species level, spp and bryophyte communities, which are central to peatland ecosystem functioning, showed no sign of recovery to prefire composition. Rather, bryophyte communities became more divergent over the course of the study and were mainly characterized by increased abundance of the alien pioneer acrocarp . Similarly, composition of arthropod communities (ground beetles and spiders) differed between burnt and unburnt areas and showed no evidence of a return to species composition in unburnt areas. The nationally rare beetle was more common in the aftermath of wildfire. . Whilst, long-term recovery was not investigated, these short-term changes suggest enduring detrimental impacts on the distinctive communities associated with peatlands, primarily through the loss of spp , affecting ecosystem services such as carbon sequestration and water and soil retention. It may not be possible to restore exact prefire species composition of plant and animal communities. We suggest a precautionary approach involving management of upland vegetation, public education, and vigilance, to prevent further wildfires and protect these key upland habitats. [Abstract copyright: © 2023 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.]

Wildfires in Arctic regions impact landforms via permafrost degradation and subsequent deformation that can last for many years. However, it remains uncertain on if and how much deformations occur, and what controls their magnitude, particularly during the first couple of years. Here, we examine the transient post-fire deformation responses near the Batagaika megaslump, which is the world's largest retrogressive thaw slump at Batagay, Sakha Republic. There were wildfires in the summers of 2018 and 2019 on the same slope, which could trigger the formation of another megaslump; many fires occurred nearby in 2019. We use interferometric synthetic aperture radar (InSAR) to measure surface displacements, including both post-fire and span-fire images. We also perform onsite measurements of temperature and thaw depth around the two scars near Batagaika megaslump in 2019, 2020, and 2021 and around the 2014 scar in 2019. At the three fire scars formed in 2018 and 2019, we demonstrate year-to-year and location-specific changes in the amplitude of subsidence, heave, and duration. The 2018 scar shows cumulative subsidences of up to 10 cm by March 2021, more clearly than the nearby 2019 scar. On the other hand, another 2019 scar adjacent to the 2014 scar shows up to 13 cm net subsidence during the first span-fire year, although the subsiding area is limited. These diverse transient post-fire responses demonstrate that under the yedoma area the spatial heterogeneities of the active layer depth and the timing of fires will control subsequent thermokarst processes.

Forest fires are caused naturally by lightning, high atmospheric temperatures, and dryness. Forest fires have ramifications for both climatic conditions and anthropogenic ecosystems. According to various research studies, there has been a noticeable increase in the frequency of forest fires in India. Between 1 January and 31 March 2022, the country had 136,604 fire points. They activated an alerting system that indicates the location of a forest fire detected using MODIS sensor data from NASA Aqua and Terra satellite images. However, the satellite passes the country only twice and sends the information to the state forest departments. The early detection of forest fires is crucial, as once they reach a certain level, it is hard to control them. Compared with the satellite monitoring and detection of fire incidents, video-based fire detection on the ground identifies the fire at a faster rate. Hence, an unmanned aerial vehicle equipped with a GPS and a high-resolution camera can acquire quality images referencing the fire location. Further, deep learning frameworks can be applied to efficiently classify forest fires. In this paper, a cheaper UAV with extended MobileNet deep learning capability is proposed to classify forest fires (97.26%) and share the detection of forest fires and the GPS location with the state forest departments for timely action.

Fuel moisture content (FMC) is a crucial driver of forest fires in many regions world-wide. Yet, the dynamics of FMC in forest canopies as well as their physiological and environmental determinants remain poorly understood, especially under extreme drought.We embedded a FMC module in the trait-based, plant-hydraulic SurEau-Ecos model to provide innovative process-based predictions of leaf live fuel moisture content (LFMC) and canopy fuel moisture content (CFMC) based on leaf water potential (psi Leaf$$ {\psi}_{\mathrm{Leaf}} $$). SurEau-Ecos-FMC relies on pressure-volume (p-v) curves to simulate LFMC and vulnerability curves to cavitation to simulate foliage mortality.SurEau-Ecos-FMC accurately reproduced psi Leaf$$ {\psi}_{\mathrm{Leaf}} $$ and LFMC dynamics as well as the occurrence of foliage mortality in a Mediterranean Quercus ilex forest. Several traits related to water use (leaf area index, available soil water, and transpiration regulation), vulnerability to cavitation, and p-v curves (full turgor osmotic potential) had the greatest influence on LFMC and CFMC dynamics. As the climate gets drier, our results showed that drought-induced foliage mortality is expected to increase, thereby significantly decreasing CFMC.Our results represent an important advance in our capacity to understand and predict the sensitivity of forests to wildfires.

Aquest és un treball final del Grau en Enginyeria de Vehicles Aeroespacials de la Universitat Politècnica de Catalunya. Consisteix en un estudi de modelització basada en agents per al cas paradigmàtic del riscos forestals del Parc Natural de Collserola, partint de models de la llibreria NetLogo -com a referència per a desenvolupar-ne de nous- i de l’edició d’un ràster de Collserola amb Arc GIS per incloure’l en un dels models i les seves extensions. Amb aquest estudi es pretén reforçar la hipòtesi que hi ha un elevat risc d’incendi a Collserola i alhora conèixer millor el foc i per extensió els trets característics de fenòmens crítics de la natura així com la seva autoorganització. Les catàstrofes naturals com els grans incendis forestals comporten riscos per a la vida humana, l’ecosistema i les infraestructures. En conseqüència, aquest treball d’enginyeria s’emmarca en l’àmbit de la sostenibilitat, la modelització i la complexitat, en un context mundial d’emergència climàtica.