Fire Severity Research Articles

From the severity patch to the landscape: Wildfire and spatial heterogeneity in northern Sierra Nevada conifer forests

AbstractAimsProlonged fire suppression in conifer forests of the Sierra Nevada Mountain range, California, USA, has led to ingrowth of conifer seedlings, converting the open heterogeneous structure into uniformly dense and layered forest. The threat of a stand‐replacing fire has increased because of fuel buildup in combination with rising drought and extreme heat frequency caused by climate change. With such high severity fire, there is also rising concern regarding conifer forest converting to shrublands as severe fire favors the establishment of large shrub patches altering landscape vegetation pattern and heterogeneity. However, a clear understanding of the effects of increased fire severity, size, and frequency on landscape‐scale heterogeneity and postfire patch dynamics is lacking, which is critical in implementing restoration and forest management activities. Our aim was to understand multiscale dynamics and spatial heterogeneity patterns of conifer forests and chaparral shrublands due to repeated mixed‐severity fire.LocationA mosaic of burned and unburned patches spanning the boundary of Lassen and Plumas National Forests, CA, USA.MethodsWe used secondary geospatial landcover data classified by cover type before modern fires (1999) and after eight modern fires (2014). We calculated various landscape diversity and fragmentation metrics at patch and landscape scales using FRAGSTATS for comparison before and after fires.ResultsAt the fire severity patch scale, high‐severity fire reduced vegetation cover type heterogeneity by half, but reburning at low to moderate severity nearly doubled cover type heterogeneity. At the full landscape scale mixed‐severity fire, including all burn severities, increased vegetation cover type heterogeneity. Fragmentation indexes confirmed that fire created larger patches of shrub and fragmented patches of conifer forest.ConclusionsThe effects of frequent large fire events on vegetation pattern and heterogeneity vary with the scale of analysis. Hence, heterogeneity and vegetation pattern change need to be evaluated at more than one scale to understand past and future ecological processes before prioritizing management actions for the conifer forests of the Sierra Nevada Mountain range.

Modeling parameters for predicting the fire-induced progressive collapse in steel framed buildings

Fire is one of the extreme loading events that a building may experience during its service life and can have severe consequences on the safety of its occupants, first responders, and the structure. Steel framed buildings under severe fires can experience high levels of instability at a local or global level, which in turn can lead to the partial or progressive collapse of the structure. However, in current practice, fire resistance of structures is obtained without due consideration to a number of critical factors, and this is mainly due to the high level of complexity in undertaking advanced analysis of structures under fire exposure. This paper presents a parametric study on a ten-story braced steel framed building subjected to fire exposure wherein six different parameters are evaluated: fire severity, fire spread, load paths, temperature-induced creep, local instability, and analysis regime. Results from validated finite element models are utilized to evaluate the influence of the different parameters and recommend critical parameters to be incorporated in the analysis. Results show that the susceptibility of fire-induced progressive collapse significantly depends on the severity of the fire exposure scenario, including fire intensity, fire spread, and extent of burning. Also, accounting for the full effects of transient creep in fire-induced progressive collapse analysis is needed to obtain conservative failure times under severe to very intense fire exposure. Additionally, results from the parametric study infer that the sectional classification of a steel section based on local instability can alter under fire exposure and this effect is more critical in steel columns located in the higher stories of the building; a nonslender column at ambient conditions can transform to a slender section at elevated temperatures. This can induce temperature-induced local instability in the column and lead to an early onset of instability at member and structural levels.

Wildfire smoke exposure has significant economic impacts on California’s licensed cannabis industry

California (USA) supports the largest legal cannabis market in the world, yet faces increasing risk from wildfire. While anecdotal evidence of impacts to cannabis crops has been documented during recent extreme fire seasons, the economic losses resulting from smoke exposure and other indirect effects (e.g., ash fall, mandatory evacuations, power outages) are not well understood. We conducted an online survey of licensed cannabis farms across the state, reporting wildfire impacts on cannabis crops from 2018 through 2021. We summarized regional variation in reported cannabis crop losses, fit a hierarchical multinomial model to assess the effects of proximity to fire and smoke exposure on crops, and trained a random forest model to make impact predictions for all state-licensed outdoor cannabis farms. We found that cannabis farms experienced wildfire-related crop losses across all cannabis growing regions in 2020, but that northern regions experienced particularly high crop loss across all four study years. We also found that exposure to wildfire smoke was a stronger predictor of reported impacts than proximity to wildfire. The output of our random forest model suggested substantial impacts for the cannabis industry in 2020, with predicted crop losses between 4.54% and 21.61% statewide, and between 9.09% and 42.83% in the northernmost counties. Estimated potential economic losses in 2020 and 2021 were as high as $1.44 billion and $970.04 million, respectively—losses which themselves exceed annual values of many of California’s other agricultural commodities. Together our results indicate substantial impacts of wildfire for the California cannabis industry as a whole. We suggest that more attention be given to strategies for mitigating cannabis crop losses from wildfires, especially in light of increasing fire occurrence and severity under climate change.

Caution is needed across Mediterranean ecosystems when interpreting wall-to-wall fire severity estimates based on spectral indices

The use of comprehensive, multi-strata fire severity metrics measured in the field, such as the composite burn index (CBI), is the most commonly used approach to calibrate remote sensing-based products and obtain wall-to-wall fire severity estimates. However, the extent to which specific ecological changes as measured by individual CBI attributes per stratum actually drive the spectral variability in Mediterranean fire-prone ecosystems has not been deciphered yet. In addition, it is not clear if these relationships are consistent across different Mediterranean ecosystems, particularly when fire effects across strata can be decoupled. To bridge these knowledge gaps, we examined the fire severity divergence among CBI strata in different types of Mediterranean forest (both conifer- and broadleaf-dominated) and shrubland ecosystems with 240 plots distributed across five wildfires in the westernmost part of the Mediterranean Basin and Chile. Then, we compared the relationship of two spectral fire severity indices with the CBI scores by strata. Finally, we used a wrapper algorithm (VSURF) around Random Forest regression to assess the potential contribution and redundancy of individual CBI attributes in shaping the spectral response of fire severity indices computed from multispectral Sentinel-2 data. The Relativized Burn Ratio (RBR) index fitted CBI field data better than the differenced Normalized Burn Ratio (dNBR). Fire effects were strongly decoupled and, for example, the substrate stratum experienced the lowest severity in conifer forests and shrublands, whereas the upper strata remained largely unaffected in broadleaf forests. This has substantial implications since we found differential responses of the RBR signal to fire effects by strata as measured by distinct individual CBI attributes. Specifically, the fire impact on the green vegetation fraction of upper strata in broadleaf and conifer forests, and on the substrate stratum in shrublands, were identified as non-redundant and most contributing fire effects shaping the spectral signal variability in burned Mediterranean ecosystems. These results, together with decoupled fire severity effects across strata, suggest that aggregated CBI metrics may obscure ecologically relevant fire-induced changes, and noticeable disconnects may exist between wall-to-wall fire severity estimates and actual fire effects in the field.

Spatio-temporal prediction of climate and wildfire in Hugumbrda Grat-Kahsu forest, Tigray: priority for early warning

Ethiopia’s forest fires are causing biodiversity loss and ecosystem destruction, highlighting the need for preventative measures. However, there is limited knowledge regarding the future impact of climate on forest fires in Ethiopia. Hence, this study primarily examines the past and future climate patterns and their potential impact on occurrence of wildfires. Climate data from the baseline (1980–2020) were projected for the future period (2021–2099) under RCP4.5 and RCP8.5 scenarios using R-software. The trends in climate were analysed using Anclim and Weather-Datatool software. To estimate the occurrence of fire, Keetch-Byram-Drought-Index was calculated using climate data and antecedent soil moisture. The result of the study indicates a projected increase in temperature, with variation in precipitation. A moderate fire risk is projected in 2021–2039 that increases to moderate-to-high probability in 2040–2069 and 2070–2099. In the future, the annual severity of fires will be 27.2–27.8% moderate and 3.3–7.8% high. The highest risk of fire will be experienced in the dry season, more in the 2070–2099 under RCP8.5 scenario. Based on the analysis this study concludes that climate change is expected to have an impact on the occurrence of wildfires. The study emphasizes the importance of taking proactive measures for effective fire management.

Fire in the clouds: How changing land use shaped an Andean biodiversity hotspot

Past land use, particularly fire, affects modern tropical forests. Charcoal from lake sediments is commonly used to estimate past fire parameters such as burn severity and frequency, but fire intensity also plays a major role in shaping vegetation and vegetation change. Past fire intensity has remained elusive using common paleoecological approaches. We present a new approach to reconstruct past fire (pyrolysis) temperature, a metric of fire intensity, and reveal how human fire use changed and shaped biodiverse Andean montane forests over the last 2100 years. We use spectra obtained from micro-Fourier Transformed Infrared Spectroscopy (FTIR) of individual charcoal particles recovered from the sediments of Lagua de los Condores (Peru) to characterize its chemical composition. We then compare the spectra generated from the sedimentary charcoal fragments with a modern reference dataset to infer the pyrolysis temperature at which they were formed. Reconstructed maximum pyrolysis temperature varied with changes in land use and changes in precipitation. Mid-temperature fires (500–600 °C) dominated the record, and co-occurred with maize cultivation. After 1200 CE the Chachapoya people, referred to as cloud warriors by the Incas, started to use the site for ceremonial purposes as the climate got wetter. We demonstrate a concomitant change in the complete fire regime with fires becoming less severe, less frequent and burning at a lower temperature after this transition. This change in land use resulted in the first forest recovery in 2000 years, which was mainly composed of species with low bark thickness, a trait of fire sensitivity. Our reconstruction of pyrolysis temperature demonstrates that the analysis of fire severity, frequency, and our added metric of intensity, is needed to understand the drivers of past vegetation change.

Camera traps link population-level activity patterns with wildfire smoke events for mammals in Eastern Washington State

BackgroundDue to anthropogenic climate change and historic fire suppression, wildfire frequency and severity are increasing across the western United States. Whereas the indirect effects of fire on wildlife via habitat change are well studied, less is known about the impacts of wildfire smoke on animal health and behavior. In this study, we explore the effects of wildfire smoke on the behavior of eight medium- to large-bodied mammalian species in a heterogenous study area in Washington, USA. We linked population-level activity metrics derived from camera trap data to concentrations of fire-specific fine particulate matter (PM2.5). We hypothesized that mammalian activity would decline during smoke events, as animals attempt to reduce potential health impacts of smoke inhalation. We used occupancy models and Poisson regression models to test the effect of fire-specific PM2.5 levels on daily detection probability and the number of detections per day, respectively, for each study species.ResultsWhile we did not observe any significant responses to daily mean concentrations of PM2.5 in the occupancy models, we found three species with significant responses in their rates of detections per day in the Poisson regression. Specifically, for each standard deviation increase in the daily mean concentration of PM2.5, there was a 12.9% decrease in the number of bobcat detections per day, an 11.2% decrease in the number of moose detections per day, and a 5.8% increase in the number of mule deer detections per day. In general, the effects of PM2.5 were small compared to other relevant covariates.ConclusionsWe generally found little evidence to support our hypothesis that animals would reduce their activity in response to wildfire smoke. However, our study demonstrated that mammals exhibited species-specific behavioral responses to smoke, which are possibly adaptive responses to reduce health impacts from smoke inhalation. Though we found only a few immediate behavioral responses to smoke exposure, we note that longer-term health consequences of smoke exposure for wildlife are also likely and generally unknown. Our study shows how camera traps, which are already widely used to study wildlife, can also be used to investigate the impacts of wildfire smoke on animal behavior and provides a step towards developing methods to better understand this increasing source of environmental stress on wildlife.

Widespread exposure to altered fire regimes under 2 °C warming is projected to transform conifer forests of the Western United States

Changes in wildfire frequency and severity are altering conifer forests and pose threats to biodiversity and natural climate solutions. Where and when feedbacks between vegetation and fire could mediate forest transformation are unresolved. Here, for the western United States, we used climate analogs to measure exposure to fire-regime change; quantified the direction and spatial distribution of changes in burn severity; and intersected exposure with fire-resistance trait data. We measured exposure as multivariate dissimilarities between contemporary distributions of fire frequency, burn severity, and vegetation productivity and distributions supported by a 2 °C-warmer climate. We project exposure to fire-regime change across 65% of western US conifer forests and mean burn severity to ultimately decline across 63% because of feedbacks with forest productivity and fire frequency. We find that forests occupying disparate portions of climate space are vulnerable to projected fire-regime changes. Forests may adapt to future disturbance regimes, but trajectories remain uncertain.

Mapping Forest Vulnerability to Fire and Landslides in the Cordillera Region, Philippines

Forest fires and landslides pose significant threats to the Cordillera's forests. Despite their detrimental impact, the vulnerability of forests in this region has received limited attention in previous studies. To address this research gap, this study employs satellite imagery and remotely sensed datasets to identify forest areas in the region that are susceptible to fires and landslides. In 2021, the forest cover in the region spans approximately 1.35 million hectares, accounting for over 73% of its total land area. However, approximately 116 thousand hectares, or 8.5% of the forest in the region, are prone to fires. The study notes an increasing trend of fire incidents and burned areas observed in both natural and plantation forests in the region. This trend could be linked to the region's rising temperatures and extended drought. In the next four decades, a projected rise in temperature of 1.1 to 1.3°C and a decrease in precipitation (-8.8 mm) during the dry season could result in more severe forest fires, larger burned areas, and longer fire durations. Furthermore, nearly 73% of the region's forests are vulnerable to landslides at a high to extremely high level. This vulnerability is reflected in the 182 landslides that occurred in the region between 2007 and 2018. The output of this study could be used in the adaptation and mitigation plans, and risk reduction activities in the region. The findings of this study highlight the need for urgent action to prevent further forest degradation due to anthropogenic and natural hazards.

Studying the Synergetic Effect of Point-Extraction and Longitudinal Ventilation on the Maximum Smoke Temperature and Back-Layering Length in Tunnel Fires

This study investigates the impact of combining longitudinal and point-extraction ventilated systems on temperature distribution and back-layering length in tunnel fires. Numerical simulations are conducted using a fire dynamic simulator (FDS), and reduced-scale tunnel fire experiments with a scale of 1/10 are introduced to provide supplementary data. Results indicate that the longitudinal velocity is more critical than other factors in reducing the highest temperature and casualties. Lowering the temperature below the tunnel ceiling is not caused by increasing the ceiling extraction velocity. Additionally, the study reveals that the fire source-ceiling distance and their relative positions play a crucial role in temperature distribution and plug-holing phenomenon in the tunnel. By using the Taguchi method, it is determined that a fire at a height of 0.125 m has a maximum ceiling temperature of 1.8, 1.3, and 1.1 times when the fire source happens on the floor with longitudinal velocities of 0.133, 0.265, and 0.53 m/s, respectively. The extraction point has diverse effects provided that the longitudinal ventilation velocity is set by critical velocity. The study’s objective is to provide tunnel engineering managers with a correlation to predict the highest temperature, which is a vital parameter for emergency evacuation. In conclusion, this study highlights the importance of considering longitudinal and point-extraction ventilated systems and their relative speeds in reducing the severity of tunnel fires.

Fire severity influences the post‐fire habitat structure and abundance of a cool climate lizard

AbstractIn the spring and summer of 2019–2020, the ‘Black Summer’ bushfires burned more than 97 000 km2 of predominantly Eucalyptus dominated forest habitat in eastern Australia. The Black Summer bushfires prompted great concern that many species had been imperilled by the fires. Here, we investigate the effects that fire severity had on the habitat and abundance of a cool climate lizard Eulamprus tympanum that was identified as a species of concern because 37% of its habitat was burnt in the Black Summer bushfires. We quantified habitat structure and the abundance of E. tympanum at sites which were unburnt, burnt at low severity and at high severity 10, 15 and 23 months after the fires. Our classification of fire severity based on scorch height and canopy status corresponded well with the Australian Government Google Earth Engine Burnt Area Map (AUS GEEBAM) fire severity layer. Ten months after the fires, sites burnt at high severity had less canopy cover, more bare ground and less fine fuel than sites burnt at low severity or unburnt sites. The abundance of E. tympanum varied with survey occasion and was greatest during the warmest sampling period and lowest during the coolest sampling period. The abundance of E. tympanum was consistently lower on sites burnt at high severity than sites burnt at low severity or unburnt sites. Our findings show that higher severity fires had a greater effect on E. tympanum than low severity fires. Our results suggest that E. tympanum were likely to have persisted in burnt sites, with populations in low severity and unburnt sites facilitating population recovery in areas burnt at high severity. Our results also suggest that wildfire impacts on E. tympanum populations will increase because the frequency and extent of severe fires are expected to increase due to climate change.

Burn severity and proximity to undisturbed forest drive post-fire recovery in the tropical montane forests of northern Vietnam

BackgroundIn recent decades, fire has increasingly occurred in the tropical montane rainforests of northern Vietnam. However, there are few studies of the effects of fire on forest composition and recovery in this region, and understanding these effects is critical for effective forest fire management and conservation. Forest plant species richness, structure (density, basal area), and composition were quantified for 133 forest plots randomly located in unburned (> 20 years since last fire) and recently burned (3–9 years since fire) vegetation associated with ten selected wildfires in three provinces of northern Vietnam where fires since 2000 were most frequent. Linear mixed effect models and nonmetric multidimensional scaling (NMDS) ordination were used to explore the structure, richness, and composition of burned and unburned forests and their environmental drivers, and to explore the key drivers of regeneration patterns in burned forest, including time since fire occurrence, fire severity, and distance to unburned forest edge.ResultsTotal species richness and diversity, tree species richness, tree density, and basal area were higher in unburned (vs. burned) forest plots, low (vs. high) severity burn areas, near (vs. far) from the closest unburned forest edge, and longer (vs. shorter) time since last fire. Results suggest that while burned forests were recovering on a trajectory back towards unburned forest composition, recovery was likely to be markedly slowed where fires were large (distance from edge effects) and/or of high severity, and forests may shift towards a different state (i.e., composition and structure) where more than one fire affects the same area over short time intervals.ConclusionsThis study provides insights into the effects of fire and other environmental factors on forest composition and recovery in the tropical montane forests of northern Vietnam, crucial for informing policymakers involved in forest conservation and management.

Mapping fire severity in the Cederberg Mountains, South Africa

Mapping fire severity in the Cederberg Mountains, South Africa

Assessing tree crown fire damage integrating linear spectral mixture analysis and supervised machine learning on Sentinel-2 imagery

ABSTRACT Crown fire damage is a mixture of three principal fire-related components: charred material, scorched foliage, and unaltered green canopy. This study estimated the abundance of these physical alterations in two immediate post-fire Mediterranean forest contexts (Portugal and Italy) by applying linear spectral mixture analysis (LSMA) on Sentinel-2 imagery. The tree crowns fire damage was subsequently mapped, integrating fractional abundance information in a random forest (RF) algorithm, comparing the accuracy resulting from the adoption of generic or image spectral libraries as the primary investigative goal. Although image-derived endmembers resulted in more effectiveness in terms of fire-related components abundance quantification (LMSA-derived RMSE < 0.1), the F-scores always were ≥ 90% whether generic endmembers or image endmembers derived information was employed. The environmental heterogeneity of the two study areas affected the fire severity gradients, with a prevalence of the charred (PT) (45–46%) and green class (IT) (44–53%). Post-fire temporal monitoring was initialized by applying the proposed strategies, and the preliminary results showed a positive recovery trend in forest vegetation from the first year following the fire event, with a reduced charcoal predominance and an increasing proportion of green components.

Geo-Based Assessment of Vegetation Health Related to Agroecological Practices in the Southeast of Togo

In the context of climate change, the need to contribute to achieving Sustainable Development Goal (SDG) 2 is no longer in doubt, especially in sub-Saharan Africa. In this study of the landscape within 10 km of the Donomadé model farm, southeastern Togo, researchers sought to assess vegetation health in ecosystems and agrosystems, including their capacity to produce biomass for agroecological practices. Sentinel-2 sensor data from 2015, 2017, 2020, and 2022 were preprocessed and used to calculate the normalized vegetation fire ratio index (NBR), the vegetation fire severity index (dNBR), and CASA-SEBAL models. From these different analyses, it was found that vegetation stress increased across the landscape depending on the year of the time series. The research estimated that 9952.215 ha, 10,397.43 ha, and 9854.90 ha were highly stressed in 2015, 2017, and 2020, respectively. Analysis of the level of interannual severity revealed the existence of highly photosynthetic areas that had experienced stress. These areas, which were likely to have been subjected to agricultural practices, were estimated to be 8704.871 ha (dNBR2017–2015), 8253.17 ha (dNBR2020–2017), and 7513.93 ha (dNBR2022–2020). In 2022, the total available biomass estimated by remote sensing was 3,741,715 ± 119.26 kgC/ha/y. The annual average was 3401.55 ± 119.26 kgC/ha/y. In contrast, the total area of healthy vegetation was estimated to be 4594.43 ha, 4301.30 ha, and 4320.85 ha, in 2015, 2017, and 2022, respectively. The acceptance threshold of the net primary productivity (NPP) of the study area was 96%. The coefficient of skewness (0.81 ± 0.073) indicated a mosaic landscape. Productive and functional ecosystem components were present, but these were highly dispersed. These findings suggest a great opportunity to promote agroecological practices. Mulching may be an excellent technique for enhancing overall ecosystem services as targeted by the SDGs, by means of reconversion of plant biomass consumed by vegetation fires or slash-and-burn agricultural practices.

Mapping forest fire severity using bi-temporal unmixing of Sentinel-2 data - Towards a quantitative understanding of fire impacts

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

Impact of forest fire on the mercury stable isotope composition in litter and soil in the Amazon

Mercury (Hg) emissions from forest fires, especially tropical forests such as the Amazonian forest, were shown to contribute significantly to the atmospheric mercury budget, but new methods are still necessary to improve the traceability and to reduce the great uncertainties related to this emission source. Recent studies have shown that the combustion process can result in Hg stable isotope fractionation that allows tracking coal combustion Hg emissions, as influenced by different factors such as combustion temperature. The main goal of the present study was, therefore, to investigate for the first time the potential of Hg stable isotopes to trace forest fire Hg emissions and pathways. More specifically, small-scale and a large scale prescribed forest fire experiments were conducted in the Brazilian Amazonian forest to study the impact of fire severity on Hg isotopic composition of litter, soil, and ash samples and associated Hg isotope fractionation pathways. In the small-scale experiment, no difference was found in the mercury isotopic composition of the samples collected before and after burning. In contrast, the larger-scale experiment resulted in significant mass dependent fractionation (MDF δ202Hg) in soils and ash suggesting that higher combustion temperature influence Hg isotopic fractionation with the emission of lighter Hg isotopes to the atmosphere and enrichment with heavier Hg in ashes. As for coal combustion, mass independent fractionation was not observed. To our knowledge, these results are the first to highlight the potential of forest fires to cause Hg isotopic fractionation, depending on the fire severity. The results also allowed to establish an isotopic fingerprint for tropical forest fire Hg emissions that corresponds to a mixture of litter and soil Hg isotopic composition (resulting atmospheric δ202Hg, Δ200Hg and Δ199Hg were −1.79 ± 0.24‰, −0.05 ± 0.04‰ and −0.45 ± 0.12‰, respectively).

Investigating spatiotemporal trends of large wildfires in California (1950–2020)

Abstract. A database capturing large wildfire perimeters (&gt; 1,000 acres / 405 hectares; n=2,857) in the state of California in the United States was used to document trends in fire occurrence (as frequency of large wildfires per year) and fire severity (using total burned area as a proxy) per ecoregion for the study period 1950–2020. Approximately 20.67% of the total area of California has been burned by large wildfires during the study period; of this, approximately 8.01% of the total area of California has been burned repeatedly. Large wildfires are becoming more severe in the state of California, burning an average of 5,068 additional acres (2,051 additional hectares) of land each year, however large wildfires are not occurring more frequently across the entire state as originally postulated. Rather, certain ecoregions, particularly mountainous regions with coniferous forests, exhibit statistically significant increasing trends in both large wildfire severity and occurrence compared to other regions of the state, likely contributing to the sentiment that wildfires are becoming worse in the state overall. As conditions relating to climate change, extreme weather events, invasive species, population distribution, and fire management decisions continue to change, the impacts of larger, more frequent fires will likely be felt more broadly across the state of California.

Refining Fire–Climate Relationship Methodologies: Southern California

Efforts to delineate the influence of atmospheric variability on regional wildfire activity have previously been complicated by the stochastic occurrence of ignition and large fire events, particularly for Southern California, where anthropogenic modulation of the fire regime is extensive. Traditional metrics of wildfire activity inherently contain this stochasticity, likely weakening regional fire–climate relationships. To resolve this complication, we first develop a new method of quantifying regional wildfire activity that aims to more clearly capture the atmospheric fire regime component by aggregating four metrics of fire activity into an annual index value, the Annual Fire Severity Index (AFSI), for the 27-year period of 1992–2018. We then decompose the AFSI into trend and oscillatory components using singular spectrum analysis (SSA) and relate each component to a set of five climate predictors known to modulate macroscale fire activity in Southern California. These include the Atlantic Multidecadal Oscillation (AMO), Pacific Decadal Oscillation (PDO), El Niño–Southern Oscillation (ENSO), and Santa Ana wind (SAW) events, and marine layer frequency. The results indicate that SSA effectively isolates the individual influence of each predictor on AFSI quantified by generally moderate fire–climate correlations, |r|&gt;0.4, over the full study period, and |r|&gt;0.5 over select 13–15-year periods. A transition between weaker and stronger fire–climate relationships for each of the oscillatory PC–predictor pairs is centered around the mid-2000s, suggesting a significant shift in fire–climate variability at this time. Our approach of aggregating and decomposing a fire activity index yields a straightforward methodology to identify the individual influence of climatic predictors on macroscale fire activity even in fire regimes heavily modified by anthropogenic influence.

Response of birds that rely on mature Piedmont Forests of Northwestern Argentina to fire severity

Fire is an integral part of the ecology of Seasonal Dry Forests. However, fire severity could be a determining factor in the resilience of these forests. The Piedmont Forest is part of the Neotropical Seasonal Dry Forests, concentrates high species biodiversity and endemism and is one of the most threatened ecosystems of the Andean region. In recent decades there has been an increasing recurrency of fires of high-severity in the Piedmont Forest. Our objective was to assess the effects of fire severity on birds that rely on mature Piedmont Forest of northwestern Argentina. To achieve this, we selected a mature unburnt forest (reference) site and two sites disturbed by fires in the year 2013 of low- and high- severity. During the wet (breeding) and dry (non-breeding) seasons of the year 2016, we carried out 30 bird point counts at each site and recorded birds at different distance categories. We only considered in the analyses bird species that rely on mature forests. To determine bird density at each site we carried out Distance Sampling models. To determine if sites had different bird assemblages, we evaluated the beta diversity through Sorensen dissimilarity index. Our results show that in the wet season, birds that rely on mature forests and resident birds had a lower density in the high-severity burnt site than in the reference site. Also in the wet season, the bird assemblage that rely on mature forests and resident birds had a greater dissimilarity in high-severity burnt site compared to the reference site. In the dry season, only the density of resident birds had a significant lower density in high-severity burnt site than in the reference site. However, no dissimilarity was found for any bird group among sites in the dry season. Birds that rely on mature forests were adversely influenced by high-severe fire in the breeding season, but not in the non-breeding season. This suggests that high-severe fires in the Piedmont Forest probably reduce available nesting resources and diminishes the breeding habitat quality. High-severe fires change the vegetation structure and reduce the habitat quality for resident birds in both seasons. An important management option would be to prevent human-caused high-severity fire and consider prescribed burning to limit the fire severity. In a context where fires are becoming more severe, it is of vital importance the inclusion of information on bird response to fire severity to ensure the conservation of biodiversity.