Large Wildfires Research Articles

Tracking Wildfires With Weather Radars

AbstractThere is a need for nowcasting tools to provide timely and accurate updates on the location and rate of spread (ROS) of large wildfires, especially those impacting communities in the wildland urban interface. In this study, we demonstrate how fixed‐site weather radars can be used to fill this gap. Specifically, we develop and test a radar‐based fire‐perimeter tracking tool that leverages the tendency for local maxima in the radar reflectivity to be collocated with active fire perimeters. Reflectivity maxima are located using search radials from points inside a fire polygon, and perimeters are updated at intervals of ∼10 min. The algorithm is tested using publicly available Next Generation Weather Radar radar data for two large and destructive wildfires, the Camp and Bear Fires, both occurring in northern California, USA. The radar‐based fire perimeters are compared with available, albeit limited, satellite and airborne infrared observations, showing good agreement with conventional fire‐tracking tools. The radar data also provide insights into fire ROS, revealing the importance of long‐range spotting in generating ROS that exceeds conventional estimates. One limitation of this study is that high‐resolution fire perimeter validation data are sparsely available, precluding detailed error quantification for the radar estimates drawn from samples spanning a range of environmental conditions and radar configurations. Nevertheless, the radar tracking approach provides the basis for improved situational awareness during high‐impact fires.

Predicting ignitability from firebrands in mature wet eucalypt forests

Forest ignitability varies spatially and temporally across landscapes as a function of fuel moisture. Wetter forests are often more difficult to ignite and therefore act as a barrier to the spread of wildfire. However, when these forests dry out and transition to an ignitable-state, the landscape is primed for large wildfires. Fire managers require information about forest ignitability to predict the timing of this switch. Yet, an understanding of the drivers and thresholds for ignitability in wetter forests remains incomplete. Our study sought to address this knowledge gap by evaluating a range of in-forest and landscape variables as predictors of ignitability in wet eucalypt forests. We conducted ignition experiments over two fire seasons at six sites in mature wet and damp eucalypt forest in south-eastern Australia. Each experiment involved 30 ignition attempts within each site on a single day using two types of flaming firebrands with different heats of combustion. The success and sustainability of each ignition attempt was recorded and this process repeated 8–9 times per site culminating in 1590 ignition attempts across a range of fuel moisture conditions. Ignition results were evaluated against 21 different in-forest and landscape variables. In-forest variables were generally stronger predictors of ignition and sustained ignition than landscape variables. The more energetic firebrand yielded more successful ignitions and sustained ignitions, but rankings for the predictor variables were similar for both types of firebrand. The strongest predictor of ignition and sustained ignition was in-forest vapour pressure deficit (VPD) (R2 = 0.65 for ignition and R2 = 0.55 sustained ignition), which is a measure of atmospheric dryness that is strongly associated with dead fuel moisture content. Past studies have identified strong links between VPD, burned area and fire severity at broader spatial and temporal scales. Our results show that VPD is also important at the time of ignition and could be used to predict wildfire risk in wet eucalypt forests.

Cascadia Burning: The historic, but not historically unprecedented, 2020 wildfires in the Pacific Northwest, USA

AbstractWildfires devastated communities in Oregon and Washington in September 2020, burning almost as much forest west of the Cascade Mountain crest (“the westside”) in 2 weeks (~340,000 ha) as in the previous five decades (~406,00 ha). Unlike dry forests of the interior western United States, temperate rain forests of the Pacific Northwest have experienced limited recent fire activity, and debates surrounding what drove the 2020 fires, and management strategies to adapt to similar future events, necessitate a scientific evaluation of the fires. We evaluate five questions regarding the 2020 Labor Day fires: (1) How do the 2020 fires compare with historical fires? (2) How did the roles of weather and antecedent climate differ geographically and from the recent past (1979–2019)? (3) How do fire size and severity compare to other recent fires (1985–2019), and how did forest management and prefire forest structure influence burn severity? (4) What impact will these fires have on westside landscapes? and (5) How can we adapt to similar fires in the future? Although 5 of the 2020 fires were much larger than any others in the recent past and burned ~10 times the area in high‐severity patches >10,000 ha, the 2020 fires were remarkably consistent with historical fires. Reports from the early 1900s, along with paleo‐ and dendro‐ecological records, indicate similar and potentially even larger wildfires over the past millennium, many of which shared similar seasonality (late August/early September), weather conditions, and even geographic locations. Consistent with the largest historical fires, strong east winds and anomalously dry conditions drove the rapid spread of high‐severity wildfire in 2020. We found minimal difference in burn severity among stand structural types related to previous management in the 2020 fires. Adaptation strategies for similar fires in the future could benefit by focusing on ignition prevention, fire suppression, and community preparedness, as opposed to fuel treatments that are unlikely to mitigate fire severity during extreme weather. While scientific uncertainties remain regarding the nature of infrequent, high‐severity fires in westside forests, particularly under climate change, adapting to their future occurrence will require different strategies than those in interior, dry forests.

Polycyclic aromatic hydrocarbons in the Upper Cretaceous lacustrine deposits from the Songliao Basin (NE China): Implications for wildfires and paleoclimate

Changes in wildfires and paleoclimate during the Late Cretaceous have been widely discussed in the literature, yet terrestrial evidence for these changes is temporally limited. This study presents biomarker evidence for wildfires and paleoclimate using polycyclic aromatic hydrocarbons (PAHs) from drill core J79 of the Nenjiang Formation (K2n1+2, boundary at about 83.3 Ma) deposited during the Late Santonian in the Songliao Basin, NE China. A variety of di-ring to hepta-ring aromatic hydrocarbons, including pyrogenic-derived, petrogenic-derived and mixed PAHs, was identified in the lacustrine deposits using gas-chromatography mass-spectrometry. According to fluorene and its derivates, the PAHs in the K2n1 were dominantly preserved under an anoxic water column, with a shift to preservation under a weakly oxidizing water column (around 83.3 Ma) in the lower part of K2n2. The occurrence of higher-plant-derived PAHs (e.g., retene, simonellite, cadalene, perylene and 6-isopropy-1-isohexyl-2-methylnaphthalene) is as probable plant fingerprint, representing a relatively humid condition and a semi-humid to arid paleoclimate condition during the lower part of K2n1 and lower part of K2n2 and during the upper part of K2n1, respectively. Sharp increases in the abundance of pyrogenic PAHs compounds (e.g., benzo[h]fluoranthenes, benzo[e]pyrene, and coronene) are interpreted as indicators of intense wildfires in the K2n. The scale of fire events in the lower part of K2n1 and lower part of K2n2 was larger than that in the upper part of K2n1. This change in wildfire extent may have been caused by the wetter climate stimulating the growth of sufficient biomass to fuel large wildfires. Therefore, the availability of fuel likely played an important role in controlling fire frequency during the Late Cretaceous.

Carbon dioxide and particulate emissions from the 2013 Tasmanian firestorm: implications for Australian carbon accounting

BackgroundUncontrolled wildfires in Australian temperate Eucalyptus forests produce significant smoke emissions, particularly carbon dioxide (CO2) and particulates. Emissions from fires in these ecosystems, however, have received less research attention than the fires in North American conifer forests or frequently burned Australian tropical savannas. Here, we use the 2013 Forcett–Dunalley fire that caused the first recorded pyrocumulonimbus event in Tasmania, to understand CO2 and particulate matter (PM2.5) emissions from a severe Eucalyptus forest fire. We investigate the spatial patterns of the two emissions using a fine scale mapping of vegetation and fire severity (50 m resolution), and utilising available emission factors suitable for Australian vegetation types. We compare the results with coarse-scale (28 km resolution) emissions estimates from Global Fire Emissions Database (GFED) to determine the reliability of the global model in emissions estimation.ResultsThe fine scale inventory yielded total CO2 emission of 1.125 ± 0.232 Tg and PM2.5 emission of 0.022 ± 0.006 Tg, representing a loss of 56 t CO2 ha−1 and 1 t PM2.5 ha−1. The CO2 emissions were comparable to GFED estimates, but GFED PM2.5 estimates were lower by a factor of three. This study highlights the reliability of GFED for CO2 but not PM2.5 for estimating emissions from Eucalyptus forest fires. Our fine scale and GFED estimates showed that the Forcett–Dunalley fire produced 30% of 2013 fire carbon emissions in Tasmania, and 26–36% of mean annual fire emissions for the State, representing a significant single source of emissions.ConclusionsOur analyses highlight the need for improved PM2.5 emission factors specific to Australian vegetation, and better characterisation of fuel loads, particularly coarse fuel loads, to quantify wildfire particulate and greenhouse gas emissions more accurately. Current Australian carbon accountancy approach of excluding large wildfires from final GHG accounts likely exaggerates Tasmania’s claim to carbon neutrality; we therefore recommend that planned and unplanned emissions are included in the final national and state greenhouse gas accounting to international conventions. Advancing these issues is important given the trajectory of more frequent large fires driven by anthropogenic climate change.

Impacts of the Gospers Mountain Wildfire on the flora and fauna of mining-impacted Newnes Plateau Shrub Swamps in Australia’s Eastern Highlands

ABSTRACT The Gospers Mountain Fire was the largest wildfire on record in New South Wales. All of the swamps on the Newnes Plateau were burnt, with some areas experiencing fire of very high severity. Despite this severity, the vegetation in all unmined reference swamps recovered relatively quickly, with substantial vegetation cover and biomass returning within 10 weeks. These swamps retained most of their peat and plant species, and both their surveyed endangered fauna species (Blue Mountains Water Skink Eulamprus leuraensis; Giant Dragonfly Petalura gigantea). This demonstrated the resilience of reference Newnes Plateau Shrub Swamps and their endangered species populations to significant bushfire events. In stark contrast, after the wildfire there was evidence of extensive combustion and oxidization of peat soils in swamps located above the footprint of prior longwall coal mining operations. Populations of endangered species, which were already in significant decline (due to longwall mining impacts on swamp hydrology), are now vulnerable to localised extinctions in these undermined swamps. Mining is ongoing in these areas and failure to protect the remaining Newnes Plateau Shrub Swamps from the hydrological impacts of longwall mining will likely lead to further ecosystem collapse in undermined swamps, and further localised extinctions of endangered species populations in these swamps.

Interactions Between Fire Refugia and Climate-Environment Conditions Determine Mesic Subalpine Forest Recovery After Large and Severe Wildfires

Infrequent stand-replacing wildfires are characteristic of mesic and/or cool conifer forests in western North America, where forest recovery within high-severity burn patch interiors can be slow, yet successful over long temporal periods (decades to centuries). Increasing fire frequency and high-severity burn patch size, under a warming climate, however, may challenge post-fire forest recovery, promoting landscape-level shifts in forest structure, composition, and distribution of non-forest patches. Crucial to a delay and/or impediment to this shift, fire refugia (i.e., remnant seed sources) may determine forest recovery trajectories and potential forest state-transitions. To examine how fire refugia attributes (i.e. extent, composition, and structure) interact with local climate and environmental conditions to determine post-fire forest recovery responses, we developed fine-grain maps of fire refugia via remote sensing and conducted field-based assessment of post-fire conifer tree establishment largely originating (i.e., dispersed) from fire refugium in the Central Cascade Range of the Pacific Northwest United States. We found that limitations on seed availability, represented by the distance2-weighted density (D2WD) of fine-grain refugia extent, largely explained post-fire tree establishment responses within our relatively mesic and cool subalpine study sites. Interactions between seed availability, climate, and environmental conditions indicated that the structural attributes of refugia (e.g., tree height) and site abiotic/biotic environmental controls (e.g., climate water deficit, canopy cover, and coarse woody debris cover) interplayed to constrain or enhance species-specific tree establishment responses. Importantly, these interactions illustrate that when seed availability is critically low for a given area, climate-environment conditions may strongly determine whether forests recover following fire(s). Toward modelling and predicting tree establishment responses and potential forest state-transitions after large stand-replacing fires(s), our study demonstrates the importance of accurately quantifying seed availability via the fine-grain extent, configuration, and attributes of remnant seed source legacies.

Comparing Geography and Severity of Managed Wildfires in California and the Southwest USA before and after the Implementation of the 2009 Policy Guidance

Managed wildfires, i.e., naturally ignited wildfires that are managed for resource benefits, have the potential to reduce fuel loads, minimize the effects of future wildfires, and restore critical natural processes across many forest landscapes. In the United States, the 2009 federal wildland fire policy guidance was designed to provide greater flexibility in the use of managed wildfires, but the effects of this policy on wildfires in the western US are not yet fully understood. Our goal was to compare managed and full suppression wildfires and to also analyze the differences between managed wildfires across space (Arizona/New Mexico and California) and time (before and after 2009) using four metrics for each wildfire: (1) distance to wilderness, (2) distance to the wildland–urban interface (WUI), (3) the percentage of area burned with high severity, and (4) the number of land management agencies. Across the study area, we found that managed wildfires were significantly closer to wilderness areas, were farther from the WUI, had a lower percentage of area that was burned at high severity, and had fewer agencies involved in managing the fire compared to full suppression wildfires. In California, managed wildfires occurred closer to wilderness and had a larger percentage of high-severity burn area compared to those in the southwest US (Arizona and New Mexico). Within each region, however, there were no significant geographic differences between managed wildfires before and after the implementation of the 2009 policy guidance. Despite the greater flexibility of the 2009 policy guidance, the basic geographic properties of managed wildfires in these two regions have not changed. As the climate warms and droughts intensify, the use of managed wildfires will need to expand during favorable weather conditions in order to address the threat of large and uncharacteristic wildfires to people and ecosystems.

Data-driven surrogate model with latent data assimilation: Application to wildfire forecasting

The large and catastrophic wildfires have been increasing across the globe in the recent decade, highlighting the importance of simulating and forecasting fire dynamics in near real-time. This is extremely challenging due to the complexities of physical models and geographical features. Running physics-based simulations for large wildfire events in near real-time are computationally expensive, if not infeasible. In this work, we develop and test a novel data-model integration scheme for fire progression forecasting, that combines Reduced-order modelling, recurrent neural networks (Long-Short-Term Memory), data assimilation, and error covariance tuning. The Reduced-order modelling and the machine learning surrogate model ensure the efficiency of the proposed approach while the data assimilation enables the system to adjust the simulation with observations. We applied this algorithm to simulate and forecast three recent large wildfire events in California from 2017 to 2020. The deep-learning-based surrogate model runs around 1000 times faster than the Cellular Automata simulation which is used to generate training data-sets. The daily fire perimeters derived from satellite observation are used as observation data in Latent Assimilation to adjust the fire forecasting in near real-time. An error covariance tuning algorithm is also performed in the reduced space to estimate prior simulation and observation errors. The evolution of the averaged relative root mean square error (R-RMSE) shows that data assimilation and covariance tuning reduce the RMSE by about 50% and considerably improves the forecasting accuracy. As a first attempt at a reduced order wildfire spread forecasting, our exploratory work showed the potential of data-driven machine learning models to speed up fire forecasting for various applications.

Mid-term effects of wildfire and salvage logging on gross and net soil nitrogen transformation rates in a Swedish boreal forest

Wildfires are natural and important disturbances of boreal forest ecosystems, and they are expected to increase in parts of the boreal zone through climate warming. There is a broad understanding of the immediate effects of fire on soil nitrogen (N) transformation rates, but less is known about these effects several years after fire. In July 2014, a large wildfire in the boreal forest zone of Central Sweden took place. Four years after the wildfire, we measured processes linked to the soil N cycle using the 15N pool dilution method (for gross N mineralization, consumption and nitrification) and the buried bags method (for net N mineralization), in soils from stands of different fire severity that had or had not been subjected to salvage logging. Gross N mineralization and consumption rates per unit carbon (C) increased by 81 % and 85 % respectively, in response to high fire severity, and nitrification rates per unit C basis decreased by 69 % in response to high fire severity, while net N mineralization was unresponsive. There was no difference in the effect of salvage logging across stands of differing fire severity on N transformation rates, although concentrations of resin adsorbed nitrate (NO3–) were overall 50 % lower in logged compared to unlogged stands. We also found that irrespective of burn severity, N immobilization rates exceeded N nitrification rates, and immobilization was therefore the dominant pathway of gross N consumption. Gross N consumption rates were higher in burned than unburned stands, despite there being a higher active microbial biomass in unburned soil, which suggests an even higher immobilization of N over time as the microbial biomass recovers following fire. Our study shows that soil N transformation rates were more affected by changes in fire severity than by salvage logging, and that four years after the fire many aspects of the N cycle did not differ between burned and unburned stands, suggesting substantial resilience of the N cycle to fire and salvage logging. However, we note that long term impact and many additional ecosystem properties or processes should be evaluated before concluding that salvage logging has no ecosystem impact. Furthermore, shortened fire regimes following climate warming accompanied with shorter intervals between salvage logging practices, could still impact the capability for the N cycle to recover after an intense fire. While wildfire in the boreal region results in a shift from nutrient conserving to nutrient demanding plant species, our results suggest this shift is dependent on a relatively short-lived pulse of higher N cycling processes that would have likely dissipated within a few years after the fire.

A Protection for LPG Domestic Cylinders at Wildland-Urban Interface Fire

Wildland fires are frequent events worldwide, particularly in the European-Mediterranean region, USA, and Australia. These fires have been more frequent and intense in recent years due to climate changes and may cause significant damage, especially when reaching the Wildland-Urban Interface (WUI) areas. The presence of liquefied petroleum gas (LPG) cylinders may cause severe events in WUI areas, as occurred in Portugal during the large wildfires of 2017, which could have been avoided if the cylinders were protected. Devices for protecting the parts of houses under WUI fire were previously presented, but a protective device for cylinders was not. In this work, a protective device for LPG cylinders made with a thin fabric with an aluminum coating on the external face was tested in laboratory and field conditions. The cylinder and the fabric were equipped with thermocouples and heat flux sensors attached to their surfaces. The tests showed that the device gave effective protection to the cylinder, decreasing the radiative heat flux that reaches it and keeping it in a safe condition when exposed to a fire; consequently preventing extreme behavior such as an explosion.

Warmer and drier conditions have increased the potential for large and severe fire seasons across south‐eastern Australia

AbstractAimThe aims were: (1) to identify the environmental drivers of interannual variation in wildfire extent and severity; (2) to examine temporal trends in climatic potential for large and severe wildfires; and (3) to assess whether environmental conditions experienced during the 2019–2020 mega‐fire season were anomalous.LocationSouth‐eastern Australia.Time period1953–2020.Major taxa studiedTemperate forests.MethodsWe used satellite‐derived fire severity mapping from 1988 to 2020 to model the effects of drought, weather and fuels on the annual area burned and the proportion of the area burned that was impacted by high‐severity fire across four bioregions. Trends in wildfire extent and severity were then estimated from 1953 to 2020 using these derived models and gridded climate data to assess changes in climatic potential for large and severe wildfires. Estimates of wildfire extent and severity for the 2019–2020 fire season were then assessed against prior seasons (1953–2019).ResultsAnnual area burned was positively related to the severity of seasonal drought and frequency of fire weather conditions that promote substantial daily fire growth. Wildfire severity was elevated in years with severe fire weather and increased with increasing antecedent drought in years without severe fire weather. Fuels had a lesser effect on wildfire extent and severity than climate. Potential fire extent and severity have increased over time in response to an increased severity of drought and worsening fire weather conditions. Estimates of wildfire extent and severity during the 2019–2020 fire season approached the upper extreme within each bioregion, owing to widespread extreme climatic conditions.Main conclusionsThe climatic potential for large and severe forest fires has increased across south‐eastern Australia since the 1950s, probably because of anthropogenic climate change. The magnitude and severity of the 2019–2020 fires reflected climatic conditions that are driving an increase in the size and severity of wildfires.

Climate-induced fire regime amplification in Alberta, Canada

Acting as a top-down control on fire activity, climate strongly affects wildfire in North American ecosystems through fuel moisture and ignitions. Departures from historical fire regimes due to climate change have significant implications for the structure and composition of boreal forests, as well as fire management and operations. In this research, we characterize the relationship between trends in climate and fire regime characteristics, for a study area predominantly in Alberta, Canada. We examined trends of fire and climate in northwestern boreal forests using time series analysis of downscaled historical annual climate, fire history (1970–2019), and fire severity (the impacts of wildfire on plants and organic biomass; 1985–2018). We represented fire severity using the relativized burn ratio (RBR) calculated from multispectral Landsat imagery. The climate of the study area has significantly warmed and dried over the past 50 years. Over the same period the annual number of large wildfires, area burned, and fire sizes in the study area significantly increased. Furthermore, the likelihood, area, and number of extreme short-interval reburns (≤15 years between fires; 1985–2019) also significantly increased. During the study period, the portion of forested unburned islands within fire perimeters significantly declined, and fire severity (RBR) increased in open conifer and mixedwood forests. These fire regime changes are significantly correlated with annual climate variability, and a path analysis supports the hypothesis that annual climate patterns have led to fire regime shifts. The increasing fire activity in this region has implications for forest ecology and habitat availability, as the disruption of the fire regime is likely to alter forest recovery. Managers may face increasing challenges to fire suppression if the observed trends of increasing hotter and drier annual climate in the study area persist, driving extreme fire activity.

High-resolution mapping of wildfire drivers in California based on machine learning

Wildfires are important natural disturbances of ecosystems; however, they threaten the sustainability of ecosystems, climate and humans worldwide. It is vital to quantify and map the controlling drivers of wildfires for effective wildfire prediction and risk management. However, high-resolution mapping of wildfire drivers remains challenging. Here we established machine-learning (Random Forests) models using 23 climate and land surface variables as model inputs to reconstruct the spatial variability and seasonality of wildfire occurrence and extent in California. The importance of individual drivers was then quantified based on the Shapley value method. Thus, we provided spatially resolved maps of wildfire drivers at high resolutions up to 0.004° × 0.004°. The results indicated that precipitation and soil moisture are the major drivers dominating 37% of the total burnt area for large and extreme wildfires in summer and 63% in autumn, while elevation plays a major role for 15–58% of burnt areas in small wildfires in all seasons. Winds are also an important contributor to summer wildfires, accounting for 41% of large and extreme burnt areas. This study enhanced our knowledge of spatial variability of wildfire drivers across diverse landscapes in a fine-scale mapping, providing valuable perspectives and case studies for other regions of the world with frequently occurred wildfire.

Comparison of contrasting optical and LiDAR fire severity remote sensing methods in a heterogeneous forested landscape in south-eastern Australia

ABSTRACT Spectral indices derived from satellite optical remote sensing data have typically been used for fire severity estimation, although other remote sensing systems such as Light Detection and Ranging (LiDAR) are increasingly applied. Despite a multitude of remotely sensed fire severity estimation methods, comparisons of method performance are few. Insights into the merits and limitations of remotely sensed fire severity methods help develop appropriate spatial tools for the management of fire-affected areas. We evaluated the performance of seven passive (optical) and active (LiDAR) remotely sensed fire severity estimation methods in classifying and explaining variation in a field-estimated modified Composite Burn Index (MCBI) for a recent large wildfire in south-eastern Australia. Our evaluation included three commonly applied indices; the differenced Normalized Burn Ratio (dNBR), Relative dNBR (RdNBR) and Relative Burn Ratio (RBR). We compared these NBR indices against two recently proposed fire severity estimation methods that have not previously been evaluated with CBI field data – the Vegetation Structure Perpendicular Index (VSPI) spectral index and the LiDAR point cloud-derived Profile Area Change (PAC), along with experimental relativized forms of these indices (RVSPI and RPAC, respectively). The RVSPI (κ = 0.47) demonstrated similar overall classification accuracy (N classes = 4) to the PAC (κ = 0.48), however both indices had lower classification accuracy than the dNBR (κ = 0.59), RdNBR (κ = 0.59) and RBR (κ = 0.61). The VSPI and PAC were unable to accurately represent non-structural changes caused by lower severity fire. Application of these optical and LiDAR indices should consider their discussed limitations in relation to the objectives of their application.

Photochemical evolution of the 2013 California Rim Fire: synergistic impacts of reactive hydrocarbons and enhanced oxidants

Abstract. Large wildfires influence regional atmospheric composition, but chemical complexity challenges model predictions of downwind impacts. Here, we elucidate key connections within gas-phase photochemistry and assess novel chemical processes via a case study of the 2013 California Rim Fire plume. Airborne in situ observations, acquired during the NASA Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) mission, illustrate the evolution of volatile organic compounds (VOCs), oxidants, and reactive nitrogen over 12 h of atmospheric aging. Measurements show rapid formation of ozone and peroxyacyl nitrates (PNs), sustained peroxide production, and prolonged enhancements in oxygenated VOCs and nitrogen oxides (NOx). Observations and Lagrangian trajectories constrain a 0-D puff model that approximates plume photochemical history and provides a framework for evaluating process interactions. Simulations examine the effects of (1) previously unmeasured reactive VOCs identified in recent laboratory studies and (2) emissions and secondary production of nitrous acid (HONO). Inclusion of estimated unmeasured VOCs leads to a 250 % increase in OH reactivity and a 70 % increase in radical production via oxygenated VOC photolysis. HONO amplifies radical cycling and serves as a downwind NOx source, although impacts depend on how HONO is introduced. The addition of initial HONO (representing primary emissions) or particulate nitrate photolysis amplifies ozone production, while heterogeneous conversion of NO2 suppresses ozone formation. Analysis of radical initiation rates suggests that oxygenated VOC photolysis is a major radical source, exceeding HONO photolysis when averaged over the first 2 h of aging. Ozone production chemistry transitions from VOC sensitive to NOx sensitive within the first hour of plume aging, with both peroxide and organic nitrate formation contributing significantly to radical termination. To simulate smoke plume chemistry accurately, models should simultaneously account for the full reactive VOC pool and all relevant oxidant sources.

EVALUATION OF FIELD-BASED BURN INDICES FOR ASSESSING FOREST FIRE SEVERITY IN LUHANSK REGION, UKRAINE

Evaluation of forest fire severity is a basis of post-fire forest management. Remote sensing-based methods enable reliable delineation of fire perimeters, however, assessments of the degree of forest damage need to be verified and adjusted through field sampling. The forest damage assessment conducted in this study is useful for practitioners to understand and justify the design of clear cuts for restoration purposes. Thus, the aim of the study is to verify the different approaches to field assessment of forest fire severity. In this paper, the authors present a site-specific assessment of large wildfires in Luhansk oblast, Ukraine occurred in 2020 using field-based burn severity indices. The Composite Burn Index (CBI) and the Geometrically Structured Composite Burn Index (GeoCBI) were used to estimate the extent of forest damage. The Burned Area Emergency Response (BAER) methodology was also tested to assess the extent of soil damage. The authors used PlanetScope images to delineate perimeters of burned areas. These perimeters were overlaid over a forest inventory database to extract forest attributes and site characteristics for all forested and unforested areas affected by fires. Within the fire perimeters, the burned area was stratified into six strata to independently account for forest damage in diverse types of land cover. In total 73 test plots were proportionally distributed among different classes of land cover to assess fire severity using CBI, GeoCBI, and BAER approaches. It was found that the fire’s footprints covered 39,782 hectares. Among that area, 21.2% were forested lands. About 78% of burned forests were pine plantations. The highest fire intensity levels were estimated within pure pine plantations that were grown in very dry sites, while the lowest ones were associated with hardwoods forests in moisture site conditions. The average estimates of fire severity using the field-based indices varied within strata (CBI>GeoCBI) which could be an issue for assessing burn severity using remote sensing-based approaches. The authors also concluded that the BAER methodology contributed less to assessing the fire intensity because soil burn severity is not directly related to vegetation damage. This work creates a foundation for further assessment of fire severity using satellite imagery. As a result of this study, a spatial data set of sample plots was proposed that can facilitate calibrating approaches used to map fire severity in the region

Differential Responses of Native Fishes in Two Headwater Tributaries of the Gila River Following Severe Wildfires

High-severity wildfires are becoming increasingly common across the American Southwest, and knowledge of how these fires affect native organisms is essential for their conservation. We evaluated changes in fish densities and habitat over 7 and 23 years in 2 tributaries of the Gila River, New Mexico, that experienced large wildfires. The Miller Fire affected Little Creek in 2011 and was followed by moderate monsoonal flooding. The Silver Fire affected Black Canyon in 2013 and was followed by a large monsoonal flood. These 2 headwater streams responded differently to wildfire. Influx of sediments reduced stream depth by 59% and increased fine substrates by 51% following the fire in Black Canyon, while these parameters were relatively unchanged by fire in Little Creek. Native fish densities declined to zero immediately following the wildfire and monsoonal flooding in Black Canyon, and recovery was slow (∼8 years). In contrast, Little Creek fish density declined marginally following wildfires and returned to near prefire levels within one year. The response to wildfires at these 2 locations illustrates how the interaction of wildfire characteristics, catchment features, and post-wildfire precipitation events influence the impact of wildfire disturbance of stream ecosystems.

Wildfire smoke destroys stratospheric ozone.

Large wildfires inject smoke and biomass-burning products into the mid-latitude stratosphere, where they destroy ozone, which protects us from ultraviolet radiation. The infrared spectrometer on the Atmospheric Chemistry Experiment satellite measured the spectra of smoke particles from the "Black Summer" fires in Australia in late 2019 and early 2020, revealing that they contain oxygenated organic functional groups and water adsorption on the surfaces. These injected smoke particles have produced unexpected and extreme perturbations in stratospheric gases beyond any seen in the previous 15 years of measurements, including increases in formaldehyde, chlorine nitrate, chlorine monoxide, and hypochlorous acid and decreases in ozone, nitrogen dioxide, and hydrochloric acid. These perturbations in stratospheric composition have the potential to affect ozone chemistry in unexpected ways.

Linking robust spatiotemporal datasets to assess and monitor habitat attributes of a threatened species.

Accessibility of multispectral, multitemporal imagery combined with recent advances in cloud computing and machine learning approaches have enhanced our ability to model habitat characteristics across broad spatial and temporal scales. We integrated a large dataset of known nest and roost sites of a threatened species, the Mexican spotted owl (Strix occidentalis lucida), in the southwestern USA with Landsat imagery processed using the Continuous Change Detection and Classification (CCDC) time series algorithm on Google Earth Engine. We then used maximum entropy modeling (Maxent) to classify the landscape into four ‘spectral similarity’ classes that reflected the degree to which 30-m pixels contained a multispectral signature similar to that found at known owl nest/roost sites and mapped spectral similarity classes from 1986–2020. For map interpretation, we used nationally consistent forest inventory data to evaluate the structural and compositional characteristics of each spectral similarity class. We found a monotonic increase of structural characteristics typically associated with owl nesting and roosting over classes of increasing similarity, with the ‘very similar’ class meeting or exceeding published minimum desired management conditions for owl nesting and roosting. We also found an increased rate of loss of forest vegetation typical of owl nesting and roosting since the beginning of the 21st century that can be partly attributed to increased frequency and extent of large (≥400 ha) wildfires. This loss resulted in a 38% reduction over the 35-year study period in forest vegetation most similar to that used for owl nesting and roosting. Our modelling approach using cloud computing with time series of Landsat imagery provided a cost-effective tool for landscape-scale, multidecadal monitoring of vegetative components of a threatened species’ habitat. Our approach could be used to monitor trends in the vegetation favored by any other species, provided that high-quality location data such as we presented here are available.