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Changes in the area and proportional area of high-severity fire from 1987 to 2017. Left panels: Area and proportional area burnt by high-severity fire in each of 162 wildfires (line represents significant relationship between variables). Right panels: Standardized coefficients for high-severity area (top, log transformed) and the proportion high-severity area (bottom, arcsine transformed) indicating the relationship between area burnt and time. Each panel displays results for a single model for all regions ("Victoria") and for individual bioregions (Acronyms of bioregions are defined in Table 1); Dot points represent mean estimated coefficient along with the 90 th (solid line) and 95 th (dashed line) percentile intervals. Coefficients denote significant changes when interval does not include zero. https://doi.org/10.1371/journal.pone.0242484.g003
Source publication
Wildfires have increased in size and frequency in recent decades in many biomes, but have they also become more severe? This question remains under-examined despite fire severity being a critical aspect of fire regimes that indicates fire impacts on ecosystem attributes and associated post-fire recovery. We conducted a retrospective analysis of wil...
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Wildfire is capable of rapidly releasing the energy stored in forests, with the amount of water in live and dead biomass acting as a regulator on the amount and rate of energy release. Here, we used temperature and fuel moisture data to examine climate‐driven changes in fuel moisture content over the past three decades. We then calculated the chang...
Fire weather indices are used to assess the effect of weather on wildfire behaviour and to support fire management. Previous studies identified the high daily severity rating percentile (DSRp) as being strongly related to the total burnt area (BA) in Portugal, but it is still poorly understood how this knowledge can support fire management at a sma...
Fuel and wildfire management decisions related to fuel break construction, maintenance, and use in fire suppression suffer from limited information on fuel break success rates and drivers of effectiveness. We built a dataset of fuel break encounters with recent large wildfires in Southern California and their associated biophysical, suppression, we...
Background
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Citations
... Wildfires are among the most important agents of natural forest disturbances in regions such as Fenno-Scandia (Clear et al. 2014), Central Europe (Neumann et al. 2022), Northern Asia (Feurdean et al. 2020), Australia (Tran et al. 2020), and Pacific North America (Halofsky et al. 2020). The extent, frequency, and severity of these fires are increasing under global climate change (Zheng et al. 2021). ...
Key message
We propose a framework to derive the direct loss of aboveground carbon stocks after the 2020 wildfire in forests of the Chornobyl Exclusion Zone using optical and radar Sentinel satellite data. Carbon stocks were adequately predicted using stand-wise inventory data and local combustion factors where new field observations are impossible. Both the standalone Sentinel-1 backscatter delta (before and after fire) indicator and radar-based change model reliably predicted the associated carbon loss.
Context
The Chornobyl Exclusion Zone (CEZ) is a mosaic forest landscape undergoing dynamic natural disturbances. Local forests are mostly planted and have low ecosystem resilience against the negative impact of global climate and land use change. Carbon stock fluxes after wildfires in the area have not yet been quantified. However, the assessment of this and other ecosystem service flows is crucial in contaminated (both radioactively and by unexploded ordnance) landscapes of the CEZ.
Aims
The aim of this study was to estimate carbon stock losses resulting from the catastrophic 2020 fires in the CEZ using satellite data, as field visitations or aerial surveys are impossible due to the ongoing war.
Methods
The aboveground carbon stock was predicted in a wall-to-wall manner using random forest modelling based on Sentinel data (both optical and synthetic aperture radar or SAR). We modelled the carbon stock loss using the change in Sentinel-1 backscatter before and after the fire events and local combustion factors.
Results
Random forest models performed well (root-mean-square error (RMSE) of 22.6 MgC·ha ⁻¹ or 37% of the mean) to predict the pre-fire carbon stock. The modelled carbon loss was estimated to be 156.3 Gg C (9.8% of the carbon stock in burned forests or 1.5% at the CEZ level). The standalone SAR backscatter delta showed a higher RMSE than the modelled estimate but better systematic agreement (0.90 vs. 0.73). Scots pine ( Pinus sylvestris L.)-dominated stands contributed the most to carbon stock loss, with 74% of forests burned in 2020.
Conclusion
The change in SAR backscatter before and after a fire event can be used as a rough proxy indicator of aboveground carbon stock loss for timely carbon map updating. The model using SAR backscatter change and backscatter values prior to wildfire is able to reliably estimate carbon emissions when on-ground monitoring is impossible.
... BS is closely linked to fire intensity and here is defined as the immediate degree of overall environmental change caused by a fire in ecosystems, including biomass loss, vegetation mortality, and biochemical and physical impacts on soil [15]. Moreover, BS determines the post-fire processes, playing a key role in the future ecosystem pathways [15][16][17][18], and its characterization is essential for the refinement of carbon emission models [5,15,19]. ...
... The evolution of BA and BS arouses great interest in the media and in the scientific community, which frequently warned about the increase or worsening of fire activity during recent years [7], often attributing that assumed trend to climate change (see examples in [17,[27][28][29]). In this sense, climate warming is expected to cause increases in fire weather danger in many regions [14], which is a driver of BA in a large proportion of Earth's land surface [13] and influences BS [24,25]. ...
... For instance, it is well documented a shift from low to high severity fire regimes in southwestern US forests, caused by the implementation of fire suppression policies after the European settlement [1], and extensive spatiotemporal studies have revealed a generalized increase in high-severity fires in some parts of Western US between 1984-2015 [21]. In Australia, an increase in the proportion of BA at high severity has been detected between 2013 and 2017 [17], and in Europe, an increased prevalence of extreme wildfire events attributed to climate change and human alterations of landscapes has been reported [29]. ...
It is a widespread assumption that burned area and severity are increasing worldwide due to climate change. This issue has motivated former analysis based on satellite imagery, revealing a decreasing trend in global burned areas. However, few studies have addressed burn severity trends, rarely relating them to climate variables, and none of them at the global scale. Within this context, we characterized the spatiotemporal patterns of burned area and severity by biomes and continents and we analyzed their relationships with climate over 17 years. African flooded and non-flooded grasslands and savannas were the most fire-prone biomes on Earth, whereas taiga and tundra exhibited the highest burn severity. Our temporal analysis updated the evidence of a decreasing trend in the global burned area (−1.50% year−1; p < 0.01) and revealed increases in the fraction of burned area affected by high severity (0.95% year−1; p < 0.05). Likewise, the regions with significant increases in mean burn severity, and burned areas at high severity outnumbered those with significant decreases. Among them, increases in severely burned areas in the temperate broadleaf and mixed forests of South America and tropical moist broadleaf forests of Australia were particularly intense. Although the spatial patterns of burned area and severity are clearly driven by climate, we did not find climate warming to increase burned area and burn severity over time, suggesting other factors as the primary drivers of current shifts in fire regimes at the planetary scale.
... In turn, in temperate zone of Central Europe the role of fire in the functioning of woodlands has been traditionally marginalized (Tinner et al. 2005;Adámek et al. 2018). However, especially due to a projected increase in the frequency of heat and drought occurring in growing season (Knutti and Sedlacek 2013;Ciais et al. 2005), nowadays, the risk of the extreme events occurrence in temperate forests has clearly increased (Zell and Hanewinkel 2015), which is also highlighted directly to forest fires with reference to different regions of the globe (Schelhaas et al. 2003;Tran et al. 2020;Masinda et al. 2022;Jahdi et al. 2023). This trend has already been recognized based on the analysis of fire frequency in temperate European forests for the period 2009-2018(Fernandez-Anez et al. 2021. ...
Due to the ongoing climate changes, temperate forests are increasingly exposed to fires. However, until now the functioning of post-fire temperate forest ecosystems with regard to used forest management method has been weakly recognized. Here, we examined three variants of forest restoration after fire (two variants of natural regeneration with no soil preparation—NR, and artificial restoration by planting following soil preparation—AR) regarding their environmental consequences in development of post-fire Scots pine (Pinus sylvestris) ecosystem. The study was conducted using a 15-year timespan in a long-term research site located in the Cierpiszewo area (N Poland) being one of the biggest post-fire grounds in European temperate forests in last decades. We focused on soil and microclimatic variables as well as on growth dynamics of post-fire pines generation. We found that the restoration rates of soil organic matter, carbon and most studied nutritional elements stocks were higher in NR plots than in AR. This could be primarily linked to the higher (p < 0.05) density of pines in naturally regenerated plots, and the subsequent faster organic horizon reconstruction after fire. The difference in tree density also involved regular differences in air and soil temperature among plots: consistently higher in AR than in both NR plots. In turn, lower water uptake by trees in AR implied that soil moisture was constantly the highest in this plot. Our study delivers strong arguments to pay more attention to restore post-fire forest areas with the use of natural regeneration with no soil preparation.
... These effects, which may be subtle and often neglected (Dafni et al., 2012), are related to medium-and long-term post-fire changes in the abundance and composition of the faunal assemblage, in the quantity and quality of resources available to the animals, and also in the structural characteristics of the vegetation (Barlow and Peres, 2006;Andersen, 2021;González et al., 2021). Postfire vegetative cover and the availability of unburnt patches are affected by fire attributes, such as severity and extent of the burned area (Leonard et al., 2014;Tran et al., 2020). These factors, in their turn, alter the abundance and behavior of rodents, ants, and birds, which are the main predators of post-dispersed seeds (e.g., Manson and Stiles, 1998;Monamy and Fox, 2000;Fox et al., 2003;Lassau et al., 2004;. ...
... Forest resilience is threatened by the extreme fire events identified in central Portugal, as in other regions worldwide (e.g. Bowman et al., 2014;Tepley et al., 2017;Steel et al., 2018;Tran et al., 2020). These concerns are related with potential transitions of plant communities to alternate stable states that could be mediated by large and severe wildfires (Knox and Clarke, 2012), but also with the reburning potential of vegetation legacies , availability of fire refugia (Krawchuk et al., 2016) and stand-age distributions (Whitman et al., 2018) associated with homogeneous patterns of fire severity in the landscape. ...
Characterizing the fire regime in regions prone to extreme wildfire behavior is essential for providing comprehensive insights on potential ecosystem response to fire disturbance in the context of global change. We aimed to disentangle the linkage between contemporary damage-related attributes of wildfires as shaped by the environmental controls of fire behavior across mainland Portugal. We selected large wildfires (≥100 ha, n = 292) that occurred during the 2015-2018 period, covering the full spectrum of large fire-size variation. Ward's hierarchical clustering on principal components was used to identify homogeneous wildfire contexts at landscape scale on the basis of fire size, proportion of high fire severity, and fire severity variability, and their bottom-up (pre-fire fuel type fraction, topography) and top-down (fire weather) controls. Piecewise Structural Equation Modeling was used to disentangle the direct and indirect relationships between fire characteristics and fire behavior drivers. Cluster analysis evidenced severe and large wildfires in the central region of Portugal displaying consistent fire severity patterns. Thus, we found a positive relationship between fire size and proportion of high fire severity, which was mediated by distinct fire behavior drivers involving direct and indirect pathways. A high fraction of conifer forest within wildfire perimeters and extreme fire weather were primarily responsible for those interactions. In the context of global change, our results suggest that pre-fire fuel management should be targeted at expanding the fire weather settings in which fire control is feasible and promote less flammable and more resilient forest types.
... In contrast, the temperate biomes have been experiencing a relatively high rate of increase (>1.5 % /yr) in fire danger potential over all vegetation types (broadleaf and mixed forests; grasslands, savannas and shrublands; and conifer forests) in comparison to all other biomes. The temperate forests in Australia have also seen a significant historical increase in the number of large wildfires (>10 km 2 ) (Tran et al., 2020). Thus, this region is experiencing increasing fire weather conditions that are conducive to the development of more frequent wildfire events. ...
This study 1) identifies the seasons and biomes that exhibit significant (1980-2019) changes in fire danger potential, as quantified by the Canadian Fire Weather Index (FWI); 2) explores what types of fire behavior potentials may be contributing to changes in fire danger potential, as quantified by the United States Energy Release Component (ERC) and the Ignition Component (IC); 3) provides spatiotemporal insight on how fire danger potential and fire behavior potential are responding in relation to changes in seasonal precipitation totals and seasonal mean air temperature across biomes. Time series of these fire potentials, as well as seasonal mean temperature, and seasonal precipitation totals are generated using data from the 0.25° ECMWF spatial resolution Reanalysis 5th Generation (ERA5) and the Climatic Research Unit gridded Time Series (CRU TS). The Mann-Kendall test is then applied to identify significant spatiotemporal trends across each biome. Results indicate that the September-November season (SON) exhibits the greatest rate of increase in fire danger potential, followed by the June-August season (JJA), December, January-February season (DJF), and March-May season (MAM), and this is predominant over the Tropical and Subtropical Moist Broadleaf Forest Biome, as well as all vegetation types of the temperate biomes. Similarly, the temperate biomes experience the greatest rate of increase in fire intensity potential and ignition potential, but prevalent during the DJF and MAM seasons. Furthermore, there is a significant positive correlation between fire danger potential and seasonal mean air temperature during JJA in the Northern Hemisphere for the temperate biomes in North America and Europe, as well as the Tropical and Subtropical biomes in Africa. Our analysis provides quantitative insight as to how fire danger potential and fire behavior potential have been responding to changes in seasonal mean temperature and seasonal precipitation totals across different ecoregions around the world.
... Mos relevant wildfires that took place in Australia from 2007 to 2021[42][43][44][45]. ...
One of the United Nations (UN) Sustainable Development Goals is climate action (SDG-13), and wildfire is among the catastrophic events that both impact climate change and are aggravated by it. In Australia and other countries, large-scale wildfires have dramatically grown in frequency and size in recent years. These fires threaten the world's forests and urban woods, cause enormous environmental and property damage, and quite often result in fatalities. As a result of their increasing frequency, there is an ongoing debate over how to handle catastrophic wildfires and mitigate their social, economic, and environmental repercussions. Effective prevention, early warning, and response strategies must be well-planned and carefully coordinated to minimise harmful consequences to people and the environment. Rapid advancements in remote sensing technologies such as ground-based, aerial surveillance vehicle-based, and satellite-based systems have been used for efficient wildfire surveillance. This study focuses on the application of space-borne technology for very accurate fire detection under challenging conditions. Due to the significant advances in artificial intelligence (AI) techniques in recent years, numerous studies have previously been conducted to examine how AI might be applied in various situations. As a result of its special physical and operational requirements, spaceflight has emerged as one of the most challenging application fields. This work contains a feasibility study as well as a model and scenario prototype for a satellite AI system. With the intention of swiftly generating alerts and enabling immediate actions, the detection of wildfires has been studied with reference to the Australian events that occurred in December 2019. Convolutional neural networks (CNNs) were developed, trained, and used from the ground up to detect wildfires while also adjusting their complexity to meet onboard implementation requirements for trusted autonomous satellite operations (TASO). The capability of a 1-dimensional convolution neural network (1-DCNN) to classify wildfires is demonstrated in this research and the results are assessed against those reported in the literature. In order to enable autonomous onboard data processing, various hardware accelerators were considered and evaluated for onboard implementation. The trained model was then implemented in the following: Intel Movidius NCS-2 and Nvidia Jetson Nano and Nvidia Jetson TX2. Using the selected onboard hardware , the developed model was then put into practice and analysis was carried out. The results were positive and in favour of using the technology that has been proposed for onboard data processing to enable TASO on future missions. The findings indicate that data processing onboard can be very beneficial in disaster management and climate change mitigation by facilitating the generation of timely alerts for users and by enabling rapid and appropriate responses.
... According to the analysis of the MODIS burned area dataset (MCD64A1), between 2001 and 2018, approximately 63 million hectares of temperate forests were burned (Hislop et al. 2020). Large and severe forest fire occurrences are expected to grow as warmer temperatures, drier conditions, and longer fire seasons increase in frequency (Tran et al. 2020;Masinda et al. 2022). In temperature-fire-prone ecosystems, shifts in forest composition and structure will result from climate changes (Keenan 2015). ...
We implemented a fire modeling approach to evaluate the effectiveness of silvicultural treatments in reducing potential losses to the Hyrcanian temperate forests of northern Iran, in the Siahkal National Forest (57,110 ha). We compared the effectiveness of selection cutting, low thinning, crown thinning, and clear-cutting treatments implemented during the last ten years (n = 241, 9500-ha) on simulated stand-scale and landscape-scale fire behavior. First, we built a set of fuel models for the different treatment prescriptions. We then modeled 10,000 fires at the 30-m resolution, assuming low, moderate, high, very high, and extreme weather scenarios and human-caused ignition patterns. Finally, we implemented a One-way ANOVA test to analyze stand-level and landscape-scale modeling output differences between treated and untreated conditions. The results showed a significant reduction of stand-level fire hazard, where the average conditional flame length and crown fire probability was reduced by about 12 and 22%, respectively. The conifer plantation patches presented the most significant reduction in the crown fire probability (>35%). On the other hand, we found a minor increase in the overall burn probability and fire size at the landscape scale. Stochastic fire modeling captured the complex interactions among terrain, vegetation, ignition locations, and weather conditions in the study area. Our findings highlight fuel treatment efficacy for moderating potential fire risk and restoring fuel profiles in fire-sensitive temperate forests of northern Iran, where the growing persistent droughts and fuel buildup can lead to extreme fires in the near future.
... Warming and drying may increase wildfire frequency and spatial extent. Mountain forests often have relatively thick organic layers that provide abundant fuel for wildfires (Tran et al. 2020). Accordingly, wildfires are regarded as an important factor in forest disturbance (Buma et al. 2020). ...
PurposeMountains have unique microclimates and rich plant diversity, resulting in different patterns and dynamics of soil organic carbon (SOC) across plant communities and elevations. Nevertheless, few studies have systematically reviewed the drivers of the dynamics of global SOC in mountainous regions.Materials and methodHere, we collected relevant published literature to analyze the main drivers of the dynamics of global SOC at different elevations and plant communities. Specifically, we analyzed the impact of natural variability and human activity on SOC.Results and discussionWe found that natural factors mainly included climate change, plant succession, and wildfires. Anthropogenic factors mainly included land use changes and grazing practices. SOC stocks at low elevations were more susceptible to grazing, precipitation, and land use changes. Conversely, higher elevations were more susceptible to warming and plant community succession. Notably, montane forests and permafrost, which are important terrestrial carbon sinks, were more easily regulated by wildfires and climate change. However, grazing had different effects on SOC in montane grasslands.Conclusions
This review highlights the synergy of multiple drivers that should be fully considered when investigating mechanisms underlying montane SOC. We recommend that future work explore the impact of extreme weather events on montane SOC.
... Annual area burned, the area burned by high severity fire and the size of high severity patches have increased across the eucalypt forest biome of south-eastern Australia over the past three decades, in response to worsening drought and fire weather (Tran et al. 2020;Collins et al. 2022). Very large wildfires (>100 000 ha) with large contiguous patches of high severity fire (>5000 ha) are becoming a more frequent component of fire regimes across this biome (Collins et al. 2021a). ...
Wildfire severity is assumed to be an important driver of habitat availability and species' distributions in forest ecosystems. Many studies have focused on the immediate or short‐term effects of fire severity in fire‐prone ecosystems, with much less focus on how long the effect of fire severity may persist. We examined the effect of fire severity on the distribution of arboreal mammals at 3 and 10 years post‐fire, in a temperate forest ecosystem dominated by eucalypts that have strong resistance and resilience to low and high severity fire, respectively. The study took place within areas affected by the 2009 Kilmore East‐Murrindindi wildfires in south‐eastern Australia. Sites were established across a gradient of fire severity (unburnt through to canopy consumption) and surveyed at 3 and 10 years following fire. Owing to low detection rates for many species, analyses were limited to greater glider (Petauroides volans) occurrence and arboreal species richness. At both 3 and 10 years post‐fire, the greater glider was restricted to unburnt forest or sites affected only by understorey fire, which acted as fire refugia. Greater gliders were absent from sites affected by high severity, canopy‐consuming fires at both points in time. Greater glider occurrence was associated with high levels of canopy cover (>50%), which were typically those areas that were unburnt or burnt at low severity. The richness of arboreal mammals increased over time and was greater in unburnt or minimally affected forest. Our findings emphasize: (i) that fire severity is an important driver of the distribution of arboreal mammals; and (ii) the importance of recognizing longer‐term effects of fire severity in assessing species distributions, even in highly resilient forest communities. Recent advances in mapping fire severity provide new opportunities to assess the effects of fire severity on the distributional patterns of fauna in eucalypt forests.
