Effects Of Wildfire Research Articles

Heterogeneity in post-fire thermal responses across Pacific Northwest streams: A multi-site study

Over the past century, water temperatures in many streams across the Pacific Northwest (PNW) have steadily risen, shrinking endangered salmonid habitats. The warming of PNW stream reaches can be further accelerated by wildfires burning forest stands that provide shade to streams. However, previous research on the effect of wildfires on stream water temperatures has focused on individual streams or burn events, limiting our understanding of the diversity in post-fire thermal responses across PNW streams. To bridge this knowledge gap, we assessed the impact of wildfires on daily summer water temperatures across 31 PNW stream sites, where 10–100% of their riparian area burned. To ensure robustness of our results, we employed multiple approaches to characterize and quantify fire effects on post-fire stream water temperature changes.Averaged across the 31 burned sites, wildfires corresponded to a 0.3 – 1°C increase in daily summer water temperatures over the subsequent three years. Nonetheless, post-fire summer thermal responses displayed extensive heterogeneity across burned sites where the likelihood and rate of a post-fire summer water temperature warming was higher for stream sites with greater proportion of their riparian area burned under high severity. Also, watershed features such as basin area, post-fire weather, bedrock permeability, pre-fire riparian forest cover, and winter snowpack depth were identified as strong predictors of the post-fire summer water temperature responses across burned sites. Our study offers a multi-site perspective on the effect of wildfires on summer stream temperatures in the PNW, providing insights that can inform freshwater management efforts beyond individual streams and basins.

Testing for synergistic effects of natural and anthropogenic disturbance on ecological communities at a landscape scale

ContextAnthropogenic and natural disturbances may interact synergistically, magnifying their individual effects on biodiversity. However, few studies have measured responses of ecological communities to multiple stressors at landscape scales.ObjectivesWe use a long-term dataset to test for synergistic effects of anthropogenic and natural disturbance on plant community diversity and composition in a large protected area.MethodsWe quantified changes in plant communities over two decades in 98 plots in Waterton Lakes National Park, Canada. Fifty-three plots burned in a wildfire in the interim. We modeled the effects of wildfire, proximity to trails or roads, and their interaction on changes in species richness, community composition, relative abundance of disturbance-associated species, and colonization by exotic species.ResultsInteractions between wildfire and proximity to roads and trails affected all metrics except species richness. Only one interaction was synergistic: the relative abundance of disturbance-associated species following wildfire was magnified closer to recreational corridors. The other community metrics showed unexpected patterns. For example, plots with no exotic species in the baseline survey that burned in the wildfire were more likely to gain exotic species than unburned plots only when they were distant from recreational corridors.ConclusionsOur study demonstrates interactive effects of natural and anthropogenic disturbance at landscape scales within a protected area. Plant community response to wildfire was influenced by proximity to recreational corridors, sometimes in surprising ways. As the frequency and severity of anthropogenic and natural disturbances both continue to rise, documenting the prevalence and magnitude of interactions between them is key to predicting long-term effects and designing mitigation strategies.

Excess prenatal loss and respiratory illnesses of infant macaques living outdoors and exposed to wildfire smoke.

Global climate change has transformed predictions of fire seasons in the near future, and record-breaking wildfire events have had catastrophic consequences in recent years. In September 2020, multiple wildfires subjected Oregon to hazardous air quality for several days. In this retrospective cohort study, we aimed to examine prenatal loss, morbidity, and mortality of rhesus (Macaca mulatta) and Japanese macaques (Macaca fuscata) exposed to poor air quality from the nearby wildfires. Detailed medical records from 2014 to 2020 of 580 macaques housed outdoors at a research facility in Beaverton, Oregonwere used to evaluate the association between these health outcomes and wildfire smoke exposure. Logistic regression models estimated excess prenatal loss, hospitalization rates, respiratory problems, and mortality during and following the wildfire event, and Kruskal-Wallis statistics were used to determine if infant growth was affected by wildfire smoke exposure. Risk of pregnancy loss (relative risk = 4.1; p < 0.001) and odds of diagnosis with a respiratory problem (odds ratio = 4.47; p = 0.003) were higher in exposed infant macaques compared to nonexposed infants. Infant growth was not affected by poor air quality exposure. Our findings suggest wildfire smoke exposure poses a risk to the health of infants and pregnant individuals and should be monitored more closely in the future.

Social valuation of biodiversity relative to other types of assets at risk in wildfire.

Environmental crises, such as wildfires, can cause major losses of human life, infrastructure, biodiversity, and cultural values. In many such situations, incident controllers must make fateful choices about what to protect-and hence what to abandon. With an online representative survey of >2000 adult Australians, we investigated social attitudes to this dilemma. We used best-worst scaling to assess preferences across a set of 11 assets representing human life, infrastructure, biodiversity, and cultural values. Survey respondents overwhelmingly prioritized a single human life (best-worst score of 6647 out of possible score ranging from -10695 to 10695), even if that choice resulted in extinction of other species. Inanimate (replaceable) objects were accorded lowest priority (best-worst scores of -4655 for a shed and -3242 for a house). Among biodiversity assets, respondents prioritized protecting a population of the iconic koala (Phascolarctos cinereus) (best-worst score of 1913) ahead of preventing the extinction of a snail (score -329) and a plant species (-226). These results variably support current policy in that they emphasize the importance the community places on protection of human life, but results diverged from conventional practice in rating some biodiversity assets ahead of infrastructure. The preference for protecting a population of koalas ahead of action taken to prevent the extinction of an invertebrate and plant species corroborates previous research reporting biases in the way people value nature. If noncharismatic species are not to be treated as expendable, then the case for preventing their extinction needs to be better made to the community. Given the increasing global incidence of high-severity wildfires, further sampling of societal preferences among diverse asset types is needed to inform planning, policy, and practice relating to wildfire. Other preemptive targeted management actions (such as translocations) are needed to conserve biodiversity, especially noniconic species, likely to be imperiled by catastrophic events.

The effect of wildfires on air quality in Kathmandu, Nepal

Air pollution spikes in the central Himalayas' southern regions, including Nepal and northern India, occur mainly from wildfires during March to May. Despite being a significant contributor to pre-monsoon pollution, wildfire smoke remains under-researched. This study used multiple datasets and trajectory analysis to examine hazardous air pollution levels in Nepal's Kathmandu Valley from 2018-2022. It found 47 days exceeding the daily PM2.5 limit of 100 μg/m3, peaking at 305 μg/m3. The pollution was largely due to wildfire smoke from neighboring and transboundary areas, with a strong correlation between active fire counts and pollution levels. The correlation peaked at 0.89 (p<0.05) when lagged by two days during high fire years, like 2021, highlighting the valley's vulnerability due to its bowl-shaped structure. Our findings can inform legislation to mitigate wildfire-induced air pollution, which impacts both public health and the economy.

Low-Intensity Wildfire Alters Selected Soil Properties in the Tropical Shorea robusta Forest

Wildfires may impact specific soil properties differently, including positive, negative, or neutral effects. However, due to the absence of uniformity in comprehending how wildfires influence soil nutrients, this research endeavors to scrutinize the particular effect of wildfire on selected soil properties in the tropical Shorea robusta forest. We analyzed 42 soil samples obtained from the topsoil of 0–10 cm comprising 21 samples from the fire-affected area and 21 from the fire-unaffected area. The physicochemical parameters of the soil including soil pH, soil organic carbon (SOC), total nitrogen (TN), available phosphorus, and available potassium were examined and compared in two sites. The impact of fire was statistically tested after comparing each variable between the two sites. Using the Mann–Whitney U test and the Pearson correlation coefficient, we analyzed the data. The results indicated that the average chemical parameters of the soil except for pH in the fire-affected area (pH = 5.43, SOC = 1.6%, TN = 0.1%, and P=246.85 kg·ha−1) were greater than those in the fire-unaffected area (pH = 5.71, SOC = 1.21%, TN = 0.09%, and P=174.21 kg·ha−1). There were statistically significant differences in the soil parameters, including pH, SOC, TN, and P, but not with K. The soil pH was reduced in the fire-affected area, with a significant positive correlation with SOC, TN, and K. Overall, the low-intensity wildfire facilitated the proliferation of soil chemical properties in the tropical S. robusta forest. Hence, low-intensity wildfire could be a suitable forest management strategy to alter soil nutrient status. Additionally, these findings can aid in enhancing forest fire management strategies for effectively managing the tropical S. robusta forest.

Wildfires exacerbate inequalities in indoor pollution exposure

Wildfires lead to dramatic increases in fine particulate matter pollution concentrations. Based on the premise that higher-income households purchase more defensive investments to reduce the degree to which outdoor pollution infiltrates indoors, in this study, we investigate how income contributes to outdoor–indoor pollution infiltration rates during wildfire events. Using crowd-sourced data from the PurpleAir Real-Time Air Quality Monitoring Network and econometric models that explore variations in monitor readings over time, we find increases in outdoor pollution lead to significant increases in indoor pollution, but disproportionately so in lower-income areas. The results highlight a new inequality in pollution exposure: not only are outdoor pollution levels higher for lower-income individuals, but indoor pollution levels are higher even for similar outdoor pollution levels.

The Impact of Wind Characteristics on the Spatial Distribution of Damage to the Built Environment during Wildfire Events: The 2022 Marshall Fire

The Impact of Wind Characteristics on the Spatial Distribution of Damage to the Built Environment during Wildfire Events: The 2022 Marshall Fire

Assessing Sentinel-2, Sentinel-1, and ALOS-2 PALSAR-2 Data for Large-Scale Wildfire-Burned Area Mapping: Insights from the 2017–2019 Canada Wildfires

Wildfires play a crucial role in the transformation of forest ecosystems and exert a significant influence on the global climate over geological timescales. Recent shifts in climate patterns and intensified human–forest interactions have led to an increase in the incidence of wildfires. These fires are characterized by their extensive coverage, higher frequency, and prolonged duration, rendering them increasingly destructive. To mitigate the impact of wildfires on climate change, ecosystems, and biodiversity, it is imperative to conduct systematic monitoring of wildfire progression and evaluate their environmental repercussions on a global scale. Satellite remote sensing is a powerful tool, offering precise and timely data on terrestrial changes, and has been extensively utilized for wildfire identification, tracking, and impact assessment at both local and regional levels. The Canada Centre for Mapping and Earth Observation, in collaboration with the Canadian Forest Service, has developed a comprehensive National Burned Area Composite (NBAC). This composite serves as a benchmark for curating a bi-temporal multi-source satellite image dataset for change detection, compiled from the archives of Sentinel-2, Sentinel-1, and ALOS-2 PALSAR-2. To our knowledge, this dataset is the inaugural large-scale, multi-source, and multi-frequency satellite image dataset with 20 m spatial resolution for wildfire mapping, monitoring, and evaluation. It harbors significant potential for enhancing wildfire management strategies, building upon the profound advancements in deep learning that have contributed to the field of remote sensing. Based on our curated dataset, which encompasses major wildfire events in Canada, we conducted a systematic evaluation of the capability of multi-source satellite earth observation data in identifying wildfire-burned areas using statistical analysis and deep learning. Our analysis compares the difference between burned and unburned areas using post-event observation solely or bi-temporal (pre- and post-event) observations across diverse land cover types. We demonstrate that optical satellite data yield higher separability than C-Band and L-Band Synthetic Aperture Radar (SAR), which exhibit considerable overlap in burned and unburned sample distribution, as evidenced by SAR-based boxplots. With U-Net, we further explore how different input channels influence the detection accuracy. Our findings reveal that deep neural networks enhance SAR’s performance in mapping burned areas. Notably, C-Band SAR shows a higher dependency on pre-event data than L-Band SAR for effective detection. A comparative analysis of U-Net and its variants indicates that U-Net works best with single-sensor data, while the late fusion architecture marginally surpasses others in the fusion of optical and SAR data. Accuracy across sensors is highest in closed forests, with sequentially lower performance in open forests, shrubs, and grasslands. Future work will extend the data from both spatial and temporal dimensions to encompass varied vegetation types and climate zones, furthering our understanding of multi-source and multi-frequency satellite remote sensing capabilities in wildfire detection and monitoring.

Monitoring biomass burning aerosol transport using CALIOP observations and reanalysis models: a Canadian wildfire event in 2019

Abstract. In May–June 2019, smoke plumes from wildfires in Alberta, Canada, were advected all the way to Europe. To analyze the evolution of the plumes and to estimate the amount of smoke aerosols transported to Europe, retrievals from the spaceborne lidar CALIOP (Cloud-Aerosol LIdar with Orthogonal Polarization) were used. The plumes were located with the help of a trajectory analysis, and the masses of smoke aerosols were retrieved from the CALIOP observations. The accuracy of the CALIOP mass retrievals was compared with the accuracy of ground-based lidars/ceilometer near the source in North America and after the long-range transport in Europe. Overall, CALIOP and the ground-based lidars/ceilometer produced comparable results. Over North America the CALIOP layer mean mass was 30 % smaller than the ground-based estimates, whereas over southern Europe that difference varied between 12 % and 43 %. Finally, the CALIOP mass retrievals were compared with simulated aerosol concentrations from two reanalysis models: MERRA-2 (Modern-Era Retrospective analysis for Research and Applications, Version 2) and CAMS (Copernicus Atmospheric Monitoring System). The simulated total column aerosol optical depths (AODs) and the total column mass concentration of smoke agreed quite well with CALIOP observations, but the comparison of the layer mass concentration of smoke showed significant discrepancies. The amount of smoke aerosols in the model simulations was consistently smaller than in the CALIOP retrievals. These results highlight the limitations of such models and more specifically their limitation to reproduce properly the smoke vertical distribution. They indicate that CALIOP is a useful tool monitoring smoke plumes over secluded areas, whereas reanalysis models have difficulties in representing the aerosol mass in these plumes. This study shows the advantages of spaceborne aerosol lidars, e.g., being of paramount importance to monitor smoke plumes, and reveals the urgent need of future lidar missions in space.

Are fire intensity and burn severity associated? Advancing our understanding of FRP and NBR metrics from Himawari-8/9 and Sentinel-2

Burn severity has been widely studied. Typical approaches use spectral differencing indices from remotely sensed data to extrapolate in-situ severity assessments. Next generation geostationary data offer near-continuous fire behaviour information, which has been used for fire detection and monitoring but remains underutilized for fire impact estimation. Here, we explore the association between remotely sensed fire intensity metrics and spectral differencing severity indices to understand whether and where they describe similar wildfire effects. The commonly used Differenced Normalised Burn Ratio (dNBR) severity index was calculated for Advanced Himawari Imager (AHI − 2 km) and Sentinel-2 (20 m) data and compared to different Fire Radiative Power (FRP) metrics derived from fire hotspot detections from AHI data across Australia. The comparison was implemented through different stratifications based on biogeographical region, land cover, fire type, and percentage of AHI pixel burned (fire fractional cover). The results indicate that FRP and dNBR metrics do not correlate in most scenarios, noting correlations being marginally stronger for hotter fires. However, correlations become significantly stronger when data are grouped using fire type information and fire fractional cover, with correlations peaking (R = 0.75) for large fires that burned 41–60 % of an AHI pixel. In conclusion, remotely sensed fire intensity and severity proxies capture different aspects of wildfire impact, that only correlate with each other after using auxiliary data. Spectral differencing severity metrics have been used extensively during the past decades, however high-frequency fire intensity estimations have the potential to augment the existing information and reveal new ways of characterizing wildfire impact over large areas.

Cellular automata-based simulators for the design of prescribed fire plans: the case study of Liguria, Italy

Abstract Background Socio-economic changes in recent decades have resulted in an accumulation of fuel within Mediterranean forests, creating conditions conducive to potential catastrophic wildfires intensified by climate change. Consequently, several wildfire management systems have integrated prescribed fires as a proactive strategy for land management and wildfire risk reduction. The preparation of prescribed fires involves meticulous planning, entailing the identification of specific objectives, verification of prescriptions, and the definition of various scenarios. During the planning phase, simulation models offer a valuable decision-support tool for the qualitative and quantitative assessment of different scenarios. In this study, we harnessed the capabilities of the well-established wildfire simulation tool , to identify areas where prescribed fires can be performed, optimizing the wildfire risk mitigation and the costs. We selected a case study in the Liguria region, Italy, where the model is utilized operationally by the regional wildfire risk management system in emergency situations. Results Initially, we employed the propagation model to simulate a historical wildfire event, showcasing its potential as an emergency response tool. We focused on the most significant fire incident that occurred in the Liguria region in 2022. Subsequently, we employed to identify optimal areas for prescribed fires with the dual objectives of maximizing the mitigation of wildfire risk and minimizing treatment costs. The delineation of potential areas for prescribed fires has been established in accordance with regional regulations and expert-based insights. The methodology put forth in this study is capable of discerning the most suitable areas for the implementation of prescribed burns from a preselected set. A Monte Carlo simulation framework was employed to evaluate the efficacy of prescribed burns in mitigating the spread of wildfires. This assessment accounted for a variety of conditions, including fuel loads, ignition points, and meteorological patterns. The model was utilized to simulate the progression of wildfire spread. Conclusions This study underscores the utility of in offering both quantitative and qualitative insights that can inform prescribed fire planning. Our methodology has been designed to involve active engagement with subject matter experts throughout the process, to develop scenarios grounded in their expert opinions. The ability to assess diverse scenarios and acquire quantitative information empowers decision-makers to make informed choices, thereby advancing safer and more efficient fire management practices.

Evaluating the performance of WRF in simulating winds and surface meteorology during a Southern California wildfire event

The intensity and frequency of wildfires in California (CA) have increased in recent years, causing significant damage to human health and property. In October 2007, a number of small fire events, collectively referred to as the Witch Creek Fire or Witch Fire started in Southern CA and intensified under strong Santa Ana winds. As a test of current mesoscale modeling capabilities, we use the Weather Research and Forecasting (WRF) model to simulate the 2007 wildfire event in terms of meteorological conditions. The main objectives of the present study are to investigate the impact of horizontal grid resolution and planetary boundary layer (PBL) scheme on the model simulation of meteorological conditions associated with a Mega fire. We evaluate the predictive capability of the WRF model to simulate key meteorological and fire-weather forecast parameters such as wind, moisture, and temperature. Results of this study suggest that more accurate predictions of temperature and wind speed relevant for better prediction of wildfire spread can be achieved by downscaling regional numerical weather prediction products to 1 km resolution. Furthermore, accurate prediction of near-surface conditions depends on the choice of the planetary boundary layer parameterization. The MYNN parameterization yields more accurate prediction as compared to the YSU parameterization. WRF simulations at 1 km resolution result in better predictions of temperature and wind speed than relative humidity during the 2007 Witch Fire. In summary, the MYNN PBL parameterization scheme with finer grid resolution simulations improves the prediction of near-surface meteorological conditions during a wildfire event.

Unhealthy air quality secondary to wildfires is associated with lower blastocyst yield

To study the impact of unhealthy air quality from the 2020 Oregon wildfires on outcomes for patients undergoing invitro fertilization (IVF) treatment. A retrospective cohort study. A university-based fertility clinic. Subjects were undergoing IVF treatment from the 6 weeks preceding the wildfires through a 10-day exposure period. Cohorts were classified on the basis of whether subjects experienced patient and/or laboratory exposure to unhealthy air quality. Patient exposure was defined as at least 4 days of ovarian stimulation overlapping with the exposure, and laboratory exposure was defined as at least 2 days of IVF treatment and embryogenesis overlapping with the exposure. The unexposed cohort consisted of remaining subjects without defined exposure, with cycles in the 6 weeks preceding the wildfires. As some subjects had dual exposure and appeared in both patient and laboratory exposure cohorts, each cohort was separately compared with the unexposed control cohort. A 10-day period of unhealthy air quality caused by smoke plumes from a wildfire event. The primary outcome was the blastulation rate. Secondary outcomes included fertilization rate, number of blastocysts obtained, and cycles with no blastocysts frozen or transferred. Sixty-nine subjects underwent ovarian stimulation and IVF treatment during the 6 weeks preceding the wildfires through the 10-day period of unhealthy air quality. Of these, 15 patients were in the laboratory exposure cohort, 16 were in the patient exposure cohort, and 44 were unexposed. Six subjects appeared in both laboratory and patient exposure cohorts. Although neither exposure cohort had significantly decreased blastulation rate compared with the unexposed, the median number of blastocysts obtained was significantly lower in the laboratory exposure cohort than the unexposed group (2 [range 0-14] vs. 4.5 [range 0-21], respectively). The laboratory exposure cohort had significantly more cycles with no blastocysts obtained (3/15 [20%] vs. 1/44 [2%]). There were no significant differences in IVF treatment outcomes between patient exposure and unexposed cohorts. These findings persisted after controlling for age. There were no significant differences in pregnancy outcomes observed after embryo transfer between the exposure group and the unexposed group. For a cohort of patients undergoing IVF treatment, an acute episode of outside wildfire smoke exposure during fertilization and embryogenesis was associated with decreased blastocyst yield.

Pyrogeography of the Western Great Plains: A 40-Year History of Fire in Semi-Arid Rangelands

This study describes spatial and temporal patterns in fire across the US Western Great Plains over the last 40 years. Although pyrogeographic studies have explored the nexus of fire patterns in relation to the bio-physical environment and socio-ecological trends, most of this research has focused on forested ecosystems and regions long known for conflict between wildfires and human development, especially at the wildland–urban interface. But evidence suggests large wildfire activity is increasing in the US Great Plains, and the Western Great Plains—a Land Resource Region comprised of four ecoregions, Northwestern Plains, High Plains, Nebraska Sandhills, and Southwestern Tablelands—not only contains some of the largest areas of rangeland in the US but also the highest concentration of public land in the Great Plains. As such, the Western Great Plains provides an opportunity to explore fire activity in primarily rural landscapes with a combination of public and private ownership, all dominated by rangeland vegetation. We combined several publicly-available datasets containing fire records between 1992 and 2020 to create two databases, one with georeferenced point data on 60,575 wildfire events in the region, and another with georeferenced perimeter data for 2665 fires. Ignition by humans was the dominant cause of fires. No ecoregion showed a statistically significant trend towards either increasing or decreasing the annual burned area. The Northwestern Plains had the most burned area and the greatest number of incidents—consistently around or above 1000 incidents per year since 1992—with the majority in July. The High Plains showed the greatest increase in annual fire incidence, never reaching more than 200–300 per year 1992–2009, and averaging above 1000 incidents per year since 2010. Few long-term trends in human population, weather, or fuel metrics appear strongly associated with fire patterns in any ecoregion, although the years 2006, 2012, and 2017 stood out for their levels of fire activity, and these years often frequently logged extreme values in wildland fuel metrics. These relationships merit much closer examination in the Western Great Plains, because like other rangeland-dominated landscapes, the fine fuels that comprise these wildland fuelbeds are much more responsive to fine-scale changes in moisture conditions. Rural Western Great Plains landscapes are a mosaic of public and private land ownership, and an increasing impact of wildfires on public grazing lands—which are often situated within other jurisdictions or ownership—will likely have an impact on rural livelihoods.

Improving Fire Severity Analysis in Mediterranean Environments: A Comparative Study of eeMETRIC and SSEBop Landsat-Based Evapotranspiration Models

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

Drought legacy interacts with wildfire to alter soil microbial communities in a Mediterranean climate-type forest

Mediterranean forest ecosystems will be increasingly affected by hotter drought and more frequent and severe wildfire events in the future. However, little is known about the longer-term responses of these forests to multiple disturbances and the forests' capacity to maintain ecosystem function. This is particularly so for below-ground organisms, which have received less attention than those above-ground, despite their essential contributions to forest function. We investigated rhizosphere microbial communities in a resprouting Eucalyptus marginata forest, southwestern Australia, that had experienced a severe wildfire four years previously, and a hotter drought eight years previously. Our aim was to understand how microbial communities are affected over longer-term trajectories by hotter drought and wildfire, singularly, and in combination. Fungal and bacterial DNA was extracted from soil samples, amplified, and subjected to high throughput sequencing. Richness, diversity, composition, and putative functional groups were then examined. We found a monotonic decrease in fungal, but not bacterial, richness and diversity with increasing disturbance with the greatest changes resulting from the combination of drought and wildfire. Overall fungal and bacterial community composition reflected a stronger effect of fire than drought, but the combination of both produced the greatest number of indicator taxa for fungi, and a significant negative effect on the abundance of several fungal functional groups. Key mycorrhizal fungi, fungal saprotrophs and fungal pathogens were found at lower proportions in sites affected by drought plus wildfire. Wildfire had a positive effect on bacterial hydrogen and bacterial nitrogen recyclers. Fungal community composition was positively correlated with live tree height. These results suggest that microbial communities, in particular key fungal functional groups, are highly responsive to wildfire following drought. Thus, a legacy of past climate conditions such as hotter drought can be important for mediating the responses of soil microbial communities to subsequent disturbance like wildfire.

Measurement report: Assessing the impacts of emission uncertainty on aerosol optical properties and radiative forcing from biomass burning in peninsular Southeast Asia

Abstract. Despite significant advancements in improving the dataset for biomass burning (BB) emissions over the past few decades, uncertainties persist in BB aerosol emissions, impeding the accurate assessment of simulated aerosol optical properties (AOPs) and direct radiative forcing (DRF) during wildfire events in global and regional models. This study assessed AOPs (including aerosol optical depth (AOD), aerosol absorption optical depth (AAOD), and aerosol extinction coefficients (AECs)) and DRF using eight independent BB emission inventories applied to the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) during the BB period (March 2019) in peninsular Southeast Asia (PSEA), where the eight BB emission inventories were the Global Fire Emissions Database version 4.1s (GFED), Fire INventory from NCAR version 1.5 (FINN1.5), the Fire Inventory from NCAR version 2.5 MOS (MODIS fire detections; FINN2.5 MOS), the Fire Inventory from NCAR version 2.5 MOSVIS (MODIS + VIIRS fire detections; FINN2.5 MOSVIS), Global Fire Assimilation System version 1.2s (GFAS), Fire Energetics and Emissions Research version 1.0 (FEER), Quick Fire Emissions Dataset version 2.5 release 1 (QFED), and Integrated Monitoring and Modelling System for Wildland FIRES project version 2.0 (IS4FIRES), respectively. The results show that in the PSEA region, organic carbon (OC) emissions in the eight BB emission inventories differ by a factor of about 9 (0.295–2.533 Tg M−1), with 1.09 ± 0.83 Tg M−1 and a coefficient of variation (CV) of 76 %. High-concentration OC emissions occurred primarily in savanna and agricultural fires. The OC emissions from the GFED and GFAS are significantly lower than the other inventories. The OC emissions in FINN2.5 MOSVIS are approximately twice as high as those in FINN1.5. Sensitivity analysis of AOD simulated by WRF-Chem to different BB emission datasets indicated that the FINN scenarios (v1.5 and 2.5) significantly overestimate AOD compared to observation (VIIRS), while the other inventories underestimate AOD in the high-AOD (HAOD; AOD &gt; 1) regions range from 15–22.5∘ N, 97–110∘ E. Among the eight schemes, IS4FIRES and FINN1.5 performed better in terms of AOD simulation consistency and bias in the HAOD region when compared to AERONET sites. The AAOD in WRF-Chem during the PSEA wildfire period was assessed, using satellite observations (TROPOMI) and AERONET data, and it was found that the AAOD simulated with different BB schemes did not perform as well as the AOD. The significant overestimation of AAOD by FINN (v1.5 and 2.5), FEER, and IS4FIRES schemes in the HAOD region, with the largest overestimation for FINN2.5 MOSVIS. FINN1.5 schemes performed better in representing AAOD at AERONET sites within the HAOD region. The simulated AOD and AAOD from FINN2.5 MOSVIS always show the best correlation with the observations. AECs simulated by WRF-Chem with all the eight BB schemes trends were consistent with CALIPSO in the vertical direction (0.5 to 4 km), demonstrating the efficacy of the smoke plume rise model used in WRF-Chem to simulate smoke plume heights. However, the FINN (v1.5 and 2.5) schemes overestimated AECs, while the other schemes underestimated it. In the HAOD region, BB aerosols exhibited a daytime shortwave radiative forcing of −32.60 ± 24.50 W m−2 at the surface, positive forcing (1.70 ± 1.40 W m−2) in the atmosphere, and negative forcing (−30.89 ± 23.6 W m−2) at the top of the atmosphere. Based on the analysis, FINN1.5 and IS4FIRES are recommended for accurately assessing the impact of BB on air quality and climate in the PSEA region.

Brief communication: The Lahaina Fire disaster – how models can be used to understand and predict wildfires

Abstract. Following the destructive Lahaina Fire in Hawaii, our team has modeled the wind and fire spread processes to understand the drivers of this devastating event. The results are in good agreement with observations recorded during the event. Extreme winds with high variability, a fire ignition close to the community, and construction characteristics led to continued fire spread in multiple directions. Our results suggest that available modeling capabilities can provide vital information to guide decision-making and emergency response management during wildfire events.

Exposure to Wildfires Exposures and Mental Health Problems among Firefighters: A Systematic Review

Firefighters are severely impacted by climate events, yet they are an underexamined population with regard to climate change research. This systematic review aims to synthesize the existing literature on the psychological effects of wildfire events on firefighters and to discuss some of the major gaps in disaster research relating to first responders and their mental health. A thorough search of the existing literature through June 2023 on the topic of wildfires and first responder psychological health was conducted through the databases PubMed, PsychINFO, and Embase. This search yielded 13 final studies which met the exclusion and inclusion criteria for this review. The final studies consisted of populations that responded to wildfire events from four different countries (two from Israel, one from Canada, two from Greece, and eight from Australia). The data gathered by this review suggest that firefighters may experience many environmental and occupational exposures during wildfire suppression, which are linked to an increased risk of PTSD and other psychological symptoms even months after the event. This review brings to light the need for further research of the compounded effect of the environmental and psychological exposures of first responders and the potential psychological effects of those exposures.