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Recently, the United States has experienced, on average, costs of USD 20 billion due to natural and climate disasters, such as hurricanes and wildfires. In this study, we focus on wildfires, which have occurred more frequently in the past few years. This paper examines how various factors, such as the PM10 levels, elevation, precipitation, SOX, population, and temperature, can influence the intensity of wildfires differently across counties in California. More specifically, we use Bayesian analysis to classify all counties of California into two groups: those with more wildfires and those with fewer wildfires. The Bayesian model incorporates prior knowledge and uncertainty for a more robust understanding of how these environmental factors impact wildfires differently among county groups. The findings show a similar effect of the SOX, population, and temperature, while the PM10, elevation, and precipitation have different implications for wildfires across various groups. [ABSTRACT FROM AUTHOR]

An increasing amount of California's landscape has burned in wildfires in recent decades, in conjunction with increasing temperatures and vapor pressure deficit due to climate change. As the wildland-urban interface expands, more people are exposed to and harmed by these extensive wildfires, which are also eroding the resilience of terrestrial ecosystems. With future wildfire activity expected to increase, there is an urgent demand for solutions that sustain healthy ecosystems and wildfire-resilient human communities. Those who manage disaster response, landscapes, and biodiversity rely on mapped projections of how fire activity may respond to climate change and other human factors. California wildfire is complex, however, and climate-fire relationships vary across the state. Given known geographical variability in drivers of fire activity, we asked whether the geographical extent of fire models used to create these projections may alter the interpretation of predictions. We compared models of fire occurrence spanning the entire state of California to models developed for individual ecoregions and then projected end-of-century future fire patterns under climate change scenarios. We trained a Maximum Entropy model with fire records and hydroclimatological variables from recent decades (1981 to 2010) as well as topographic and human infrastructure predictors. Results showed substantial variation in predictors of fire probability and mapped future projections of fire depending upon geographical extents of model boundaries. Only the ecoregion models, accounting for the unique patterns of vegetation, climate, and human infrastructure, projected an increase in fire in most forested regions of the state, congruent with predictions from other studies. [ABSTRACT FROM AUTHOR]

Evaluation metrics for prediction error, model selection and model averaging on space–time data are understudied and poorly understood. The absence of independent replication makes prediction ambiguous as a concept and renders evaluation procedures developed for independent data inappropriate for most space–time prediction problems. Motivated by air pollution data collected during California wildfires in 2008, this manuscript attempts a formalization of the true prediction error associated with spatial interpolation. We investigate a variety of cross-validation (CV) procedures employing both simulations and case studies to provide insight into the nature of the estimand targeted by alternative data partition strategies. Consistent with recent best practice, we find that location-based cross-validation is appropriate for estimating spatial interpolation error as in our analysis of the California wildfire data. Interestingly, commonly held notions of bias-variance trade-off of CV fold size do not trivially apply to dependent data, and we recommend leave-one-location-out (LOLO) CV as the preferred prediction error metric for spatial interpolation. [ABSTRACT FROM AUTHOR]

Background: Autumn and winter Santa Ana Winds (SAW) are responsible for the largest and most destructive wildfires in southern California. Aims: (1) To contrast fires ignited on SAW days vs non-SAW days, (2) evaluate the predictive ability of the Canadian Fire Weather Index (CFWI) for these two fire types, and (3) determine climate and weather factors responsible for the largest wildfires. Methods: CAL FIRE (California Department of Forestry and Fire Protection) FRAP (Fire and Resource Assessment Program) fire data were coupled with hourly climate data from four stations, and with regional indices of SAW wind speed, and with seasonal drought data from the Palmer Drought Severity Index. Key results: Fires on non-SAW days were more numerous and burned more area, and were substantial from May to October. CFWI indices were tied to fire occurrence and size for both non-SAW and SAW days, and in the days following ignition. Multiple regression models for months with the greatest area burned explained up to a quarter of variation in area burned. Conclusions: The drivers of fire size differ between non-SAW and SAW fires. The best predictor of fire size for non-SAW fires was drought during the prior 5 years, followed by a current year vapour pressure deficit. For SAW fires, wind speed followed by drought were most important. Fires ignited on Santa Ana Wind days are the largest and most destructive fires but other fires are more numerous and account for greater area burned. Fire indices on days after ignition are important predictors of fire size, but drought and wind speed are most closely tied to fire size. [ABSTRACT FROM AUTHOR]

Wildfires in the southwestern United States, particularly in northern California (nCA), have grown in size and severity in the past decade. As they have grown larger, they have been associated with large emissions of absorbing aerosols and heat into the troposphere. Utilizing satellite observations from MODIS, CERES, and AIRS as well as reanalysis from MERRA-2, the meteorology associated with fires during the wildfire season (June–October) was discerned over the nCA-NV (northern California and Nevada) region during the period 2003–2022. Wildfires in the region have a higher probability of occurring on days of positive temperature (T) anomalies and negative relative humidity (RH) anomalies, making it difficult to discern the radiative effects of aerosols that are concurrent with fires. To attempt to better isolate the effects of large fire emissions on meteorological variables, such as clouds and precipitation, variable anomalies on high fire emission days (90th percentile) were compared with low fire emission days (10th percentile) and were further stratified based on whether surface relative humidity (RH s) was anomalously high (75th percentile) or low (25th percentile) compared with typical fire season conditions. Comparing the simultaneously high fire emission and high RH s data with the simultaneously low fire emission and high RH s data, positive tropospheric T anomalies were found to be concurrent with positive AOD anomalies. Further investigation found that due to shortwave absorption, the aerosols heat the atmosphere at a rate of 0.041 ± 0.016 to 0.093 ± 0.019 K d -1 , depending on whether RH conditions are anomalously positive or negative. The positive T anomalies were associated with significant negative 850–300 hPa RH anomalies during both 75th percentile RH s conditions. Furthermore, high fire emission days under high RH s conditions are associated with negative CF anomalies that are concurrent with the negative RH anomalies. This negative CF anomaly is associated with a significantly negative regional precipitation anomaly and a positive net top-of-atmosphere radiative flux anomaly (a warming effect) in certain areas. The T , RH, and CF anomalies under the simultaneously high fire emission and high RH s conditions compared with the simultaneously low fire emission and high RH s conditions have a significant spatial correlation with AOD anomalies. Additionally, the vertical profile of these variables under the same stratification is consistent with positive black carbon mass mixing ratio anomalies from MERRA-2. However, causality is difficult to discern, and further study is warranted to determine to what extent the aerosols are contributing to these anomalies. [ABSTRACT FROM AUTHOR]

In 2020, wildfires scarred over 4,000,000 hectares in the western United States, devastating urban populations and ecosystems alike. The significant impact that wildfires have on plants, animals, and human environments makes wildfire adaptation, management, and mitigation strategies a critical task. This study uses satellite imagery from Landsat to calculate burn severity and map the fire progression for the Dolan Fire of central Coastal California which occurred in August 2020. Several environmental factors, such as temperature, humidity, fuel type, topography, surface conditions, and wind velocity, are known to affect wildfire spread and burn severity. The aim of this study is the investigation of the relationship between these environmental factors, estimates of burn severity, and fire spread patterns. Burn severity is calculated and classified using the Difference in Normalized Burn Ratio (dNBR) before being displayed as a time series of maps. The Dolan Fire had a moderate severity burn with an average dNBR of 0.292. The ignition site location, when paired with the patterns of fire spread, is consistent with wind speed and direction data, suggesting fire movement to the southeast of the fire ignition site. Patterns of increased burn severity are compared with both topography (slope and aspect) and fuel type. Locations that were found to be more susceptible to high burn severity featured Long Needle Timber Litter and Mature Timber fuels, intermediate slope angles between 15 and 35°, and north- and east-facing slopes. This study has implications for the future predictive modeling of wildfires that may serve to develop wildfire mitigation strategies, manage climate change impacts, and protect human lives. [ABSTRACT FROM AUTHOR]

The increase in both the frequency and magnitude of natural disasters, coupled with recent advancements in artificial intelligence, has introduced prospects for investigating the potential of new technologies to facilitate disaster response processes. Preliminary Damage Assessment (PDA), a labor-intensive procedure necessitating manual examination of residential structures to ascertain post-disaster damage severity, stands to significantly benefit from the integration of computer vision-based classification algorithms, promising efficiency gains and heightened accuracy. Our paper proposes a Vision Transformer (ViT)-based model for classifying damage severity, achieving an accuracy rate of 95%. Notably, our model, trained on a repository of over 18,000 ground-level images of homes with damage severity annotated by damage assessment professionals during the 2020–2022 California wildfires, represents a novel application of ViT technology within this domain. Furthermore, we have open sourced this dataset—the first of its kind and scale—to be used by the research community. Additionally, we have developed a publicly accessible web application prototype built on this classification algorithm, which we have demonstrated to disaster management practitioners and received feedback on. Hence, our contribution to the literature encompasses the provision of a novel imagery dataset, an applied framework from field professionals, and a damage severity classification model with high accuracy. [ABSTRACT FROM AUTHOR]

In California, wildfires caused by electrical infrastructure have left the state's investor-owned power utilities with major and growing liabilities. But even in such an incendiary environment, the financial industry has demonstrated that it can profit from disaster. This paper uses the 2019-2020 bankruptcy of Pacific Gas & Electric to explain how. In it, I show how "risk" in California's electricity industry is legally constituted, mediated, and allocated. First, I explain how financial perceptions of wildfire risk in California's electricity industry are shaped by the state's legal and regulatory environment, and how the law is used to manage this risk. I then turn to PG&E's bankruptcy to show how litigation functions as a financial strategy. In court, risk is endogenous to legal-financial practice. I develop the concepts of "legal arbitrage" and "leverage" to explain how law mediates the relationship between risk and finance. I adapt the concept of legal arbitrage to show how financial assets (like those in a utility with unprecedented wildfire liabilities) can possess both legal and market value, which can and often do diverge in circumstances of distress. I use the term leverage to refer to a particular kind of legal-financial power which enables actors to transfer risk away from themselves and onto others. In working through these concepts, I argue that that mainstream perceptions of risk in the financial industry are inadequate, especially in an era of increasing climate insecurity. [ABSTRACT FROM AUTHOR]

Wildfires have become more frequent and intense due to climate change and outdoor wildfire fine particulate matter (PM2.5) concentrations differ from relatively smoothly varying total PM2.5. Thus, we introduced a conceptual model for computing long-term wildfire PM2.5 and assessed disproportionate exposures among marginalized communities. We used monitoring data and statistical techniques to characterize annual wildfire PM2.5 exposure based on intermittent and extreme daily wildfire PM2.5 concentrations in California census tracts (2006 to 2020). Metrics included: 1) weeks with wildfire PM2.5 > 5 µg/m3; 2) days with non-zero wildfire PM2.5; 3) mean wildfire PM2.5 during peak exposure week; 4) smoke waves (= 2 consecutive days with > 15 µg/m3 wildfire PM2.5); and 5) mean annual wildfire PM2.5 concentration. We classified tracts by their racial/ethnic composition and CalEnviroScreen (CES) score, an environmental and social vulnerability composite measure. We examined associations of CES and racial/ethnic composition with the wildfire PM2.5 metrics using mixed-effects models. Averaged 2006 to 2020, we detected little difference in exposure by CES score or racial/ethnic composition, except for non-Hispanic American Indian and Alaska Native populations, where a 1-SD increase was associated with higher exposure for 4/5 metrics. CES or racial/ethnic × year interaction term models revealed exposure disparities in some years. Compared to their California-wide representation, the exposed populations of non-Hispanic American Indian and Alaska Native (1.68×, 95% CI: 1.01 to 2.81), white (1.13×, 95% CI: 0.99 to 1.32), and multiracial (1.06×, 95% CI: 0.97 to 1.23) people were over-represented from 2006 to 2020. In conclusion, during our study period in California, we detected disproportionate long-term wildfire PM2.5 exposure for several racial/ethnic groups. [ABSTRACT FROM AUTHOR]

As wildfire becomes increasingly frequent, many serotinous plant populations risk local extirpation if fire recurs prior to sufficient seed accumulation in the canopy (i.e., "immaturity risk"). Following two 2018 wildfires in northwestern California, we studied seed viability, cone production, and postfire regeneration of a serotinous conifer, knobcone pine (Pinus attenuata), with stand ages (time since fire) ranging from 6 to 79 years. Cone density per tree was more strongly associated with tree diameter than age, and cone density was positively related to postfire seedling regeneration. Most of the postfire knobcone pine regeneration established during the first year with high survivorship in the following first postfire year. Adjusting for survivorship, the estimated minimum age for knobcone pine to promote self‐replacement (one recruit per tree) was 9.5 years (or 4.6‐cm dbh) and the probability of reburning at the modern fire rotation of 43 years was 19.8%. Based on our results, we found that immaturity risk was currently low for knobcone pine. Our approach provides a quantitative method to assess immaturity risk in knobcone pine and other serotinous conifer species that can be used to evaluate future risk under rapidly changing climate and fire conditions. [ABSTRACT FROM AUTHOR]

Damages from wildfires have increased dramatically in recent years. This study uses a boundary discontinuity design to estimate the effect of wildfire-hazard disclosure on house prices. Using the universe of single-family sales transactions from Zillow's Transaction and Assessment Database in California from 2015 through 2022, we find that, on average, homes facing disclosure requirements sold for approximately 4.3% less than nearby homes that did not. Price impacts are higher in recent years, after several damaging wildfires. Our findings highlight the use of disclosure regulations to ensure that disaster risks are reflected in housing markets. [ABSTRACT FROM AUTHOR]

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 CAand 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. [ABSTRACT FROM AUTHOR]

Copyright of Fire Ecology is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Fire Ecology is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Wildfires in the southwestern United States, particularly in northern California (nCA), have grown in size and severity in the past decade. As they have grown larger, they have been associated with large emissions of absorbing aerosols in to the troposphere. Utilizing satellite observations from MODIS, CERES, AIRS, and CALIPSO, the meteorological effects of aerosols associated with fires during the wildfire season (June–October) were discerned over the nCA-NV (northern California and Nevada) region in the 2003–2022 time frame. As higher temperatures and low relative humidity RH dominate during high surface pressure ps atmospheric conditions, the effects of the aerosols on high (90th percentile) fire days compared to low fire (10th percentile) days were stratified based on whether ps was anomalously high or anomalously low (10th percentile). An increase in tropospheric temperatures was found to be concurrent with more absorbing aerosol aloft, which is associated with significant reductions in tropospheric RH during both 90th and 10th percentile ps conditions. Furthermore, high fire days under low ps conditions are associated with reduced cloud fraction CF , which is consistent with the traditionally-defined aerosol- cloud semi-direct effect. The reduced CF , in turn, is associated with reduced T OA SW radiative flux, a warmer surface, and less precipitation. These changes could create a positive feedback that could intensify fire weather, and therefore extend fire lifetime and impacts. [ABSTRACT FROM AUTHOR]

Innovative solutions are necessary for efficient monitoring and mitigation techniques as climate change increases the frequency and severity of natural catastrophes. In this study, we investigate how Cloud Internet of Things (IoT) might help mitigate climate-related calamities. Through the use of cloud computing and sensor networks, Cloud IoT facilitates the capture, processing, and distribution of data in near-real time. This strategy promotes catastrophe planning, response, and recovery by offering early warnings, predictive insights, and simplified communication. The article emphasises the cumulative influence of Cloud IoT components such as sensor networks, data analytics, decision support systems, and remote control in the context of disaster management. Cloud IoT is useful in real-world scenarios, such as the tracking of floods in Bangladesh and the identification of wildfires in California. These cases show how the technology may prevent injuries and preserve property through early warnings and well-coordinated responses. Despite its potential, it faces obstacles including ensuring the safety of data and dealing with issues related to the necessary infrastructure. In conclusion, including Cloud IoT in disaster management provides a cost-effective, scalable, and efficient solution, greatly contributing to constructing resilient communities and creating a sustainable future in the face of climate-induced natural catastrophes. [ABSTRACT FROM AUTHOR]

Novel wildfire regimes are rapidly changing global ecosystems and pose significant challenges for biodiversity conservation and ecosystem management. In this study, we used DNA metabarcoding to assess the response of arthropod pollinator communities to large‐scale wildfires across diverse habitat types in California. We sampled six reserves within the University of California Natural Reserve System, each of which was partially burned in the 2020 Lightning Complex wildfires in California. Using yellow pan traps to target pollinators, we collected arthropods from burned and unburned sites across multiple habitat types including oak woodland, redwood, scrub, chamise, grassland, forest, and serpentine habitats. We found no significant difference in alpha diversity values between burned and unburned sites; instead, seasonal variations played a significant role in arthropod community dynamics, with the emergence of plant species in Spring promoting increased pollinator richness at all sites. When comparing all sites, we found that burn status was not a significant grouping factor. Instead, compositional differences were largely explained by geographic differences, with distinct communities within each reserve. Within a geographic area, the response of arthropods to fire was dependent on habitat type. While communities in grasslands and oak woodlands exhibited recovery following burn, scrublands experienced substantial changes in community composition. Our study highlights the importance of examining community responses to wildfires across broad spatial scales and diverse habitat types. By understanding the nuanced dynamics of arthropod communities in response to fire disturbances, we can develop effective conservation strategies that promote resilience and maintain biodiversity in the face of increasing wildfire frequency and severity driven by climate change. [ABSTRACT FROM AUTHOR]

Fire is a dominant force shaping patterns of plant diversity in Mediterranean‐type ecosystems. In these biodiversity hotspots, including California's endangered coastal scrub, many species remain hidden belowground as seeds and bulbs, only to emerge and flower when sufficient rainfall occurs after wildfire. The unique adaptations possessed by these species enable survival during prolonged periods of unfavorable conditions, but their continued persistence could be threatened by nonnative plant invasion and environmental change. Furthermore, their fleeting presence aboveground makes evaluating these threats in situ a challenge. For example, nitrogen (N) deposition resulting from air pollution is a well‐recognized threat to plant diversity worldwide but impacts on fire‐following species are not well understood. We experimentally evaluated the impact of N deposition on post‐fire vegetation cover and richness for three years in stands of coastal sage scrub that had recently burned in a large wildfire in southern California. We installed plots receiving four levels of N addition that corresponded to the range of N deposition rates in the region. We assessed the impact of pre‐fire invasion status on vegetation dynamics by including plots in areas that had previously been invaded by nonnative grasses, as well as adjacent uninvaded areas. We found that N addition reduced native forb cover in the second year post‐fire while increasing the abundance of nonnative forbs. As is typical in fire‐prone ecosystems, species richness declined over the three years of the study. However, N addition hastened this process, and native forb richness was severely reduced under high N availability, especially in previously invaded shrublands. An indicator species analysis also revealed that six functionally and taxonomically diverse forb species were especially sensitive to N addition. Our results highlight a new potential mechanism for the depletion of native species through the suppression of ephemeral post‐fire bloom events. [ABSTRACT FROM AUTHOR]

Accentuated by climate change, catastrophic wildfires are a growing, distributed global public health risk from inhalation of smoke and dust. Underrecognized, however, are the health threats arising from fire-altered toxic metals natural to soils and plants. Here, we demonstrate that high temperatures during California wildfires catalyzed widespread transformation of chromium to its carcinogenic form in soil and ash, as hexavalent chromium, particularly in areas with metal-rich geologies (e.g., serpentinite). In wildfire ash, we observed dangerous levels (327-13,100 µg kg−1) of reactive hexavalent chromium in wind-dispersible particulates. Relatively dry post-fire weather contributed to the persistence of elevated hexavalent chromium in surficial soil layers for up to ten months post-fire. The geographic distribution of metal-rich soils and fire incidents illustrate the broad global threat of wildfire smoke- and dust-born metals to populations. Our findings provide new insights into why wildfire smoke exposure appears to be more hazardous to humans than pollution from other sources. Carcinogenic heavy metals are an underappreciated public health concern from wildfire. Fire severity, geology, and ecosystem type influence landscape-scale production of hexavalent chromium, concentrated in wind-dispersible particles. [ABSTRACT FROM AUTHOR]

Over the past two decades, wildfire activity in the western USA has increased, especially in California. Wildfires not only affect air quality but also the environment at large, including chemical and physical properties of fire-affected soils, which are of great interest for prediction and mitigation of hydrological consequences. Hyperspectral reflectance can be used to remotely assess the effects of fires on soil and here we use it to characterize soils before and after three 2021 California wildfires (Dixie, Beckwourth Complex, and Caldor fire). We acquired reflectance spectra and compared changes in these spectra with changes in the chemistry of analyzed soils. For all three fires, the results show that 700 nm wavelength reflectance of ash samples collected 1 and 1.5 years after fire decreased between 36% and 76% compared to that of samples collected right after the fires. Additionally, significantly higher visible reflectance has been found for unburned compared to burned soil samples in each region that was studied. Infrared transmission measurements were used to characterize the carbonate content of soil and ash samples demonstrating a mostly positive relationship between carbonate content and visible reflectance, indicating a possible cause and effect between the two. [ABSTRACT FROM AUTHOR]

Natural disasters, such as wildfires, can cause widespread devastation. Future-proofing infrastructure, such as buildings and bridges, through technological advancements is crucial to minimize their impact. Fires in disasters often stem from damaged fuel lines and electrical equipment, such as the 2018 California wildfire caused by a power line fault. To enhance safety, IoT applications can continuously monitor the health of emergency personnel. Using Bluetooth 5.0 and wearables in mesh networks, these apps can alert others about an individual's location during emergencies. However, fire can disrupt wireless networks. This study assesses Bluetooth 5.0's performance in transmitting signals in fire conditions. It examined received signal strength indicator (RSSI) values in a front open-fire chamber using both Peer-to-Peer (P2P) and mesh networks. The experiment considered three transmission heights of 0.61, 1.22, and 1.83 m and two distances of 11.13 m and 1.52 m. The study demonstrated successful signal transmission with a maximum loss of only 2 dB when transmitting through the fire. This research underscores the potential for reliable communication in fire-prone environments, improving safety during natural disasters. [ABSTRACT FROM AUTHOR]

In December 2017, one of the largest wildfires in California history, the Thomas Fire, created a large smoke and ash plume that extended over the northeastern Pacific Ocean. Here, we explore the impact of Thomas Fire ash deposition on seawater chemistry and the growth and composition of natural microbial communities. Experiments conducted in coastal California waters during the Thomas Fire revealed that leaching of ash in seawater resulted in significant additions of dissolved nutrients including inorganic nitrogen (nitrate, nitrite and ammonium), silicic acid, metals (iron, nickel, cobalt and copper), organic nitrogen and organic carbon. After exposure to ash leachate at high (0.25 g ash l−1) and low (0.08 g ash l−1) concentrations for 4 days, natural microbial communities had 59–154% higher particulate organic carbon concentrations than communities without ash leachate additions. Additionally, a diverse assemblage of eukaryotic microbes (protists) responded to the ash leachate with taxa from 11 different taxonomic divisions increasing in relative abundance compared with control treatments. Our results suggest that large fire events can be important atmospheric sources of nutrients (particularly nitrogen) to coastal marine systems, where, through leaching of various nutrients, ash may act as a 'food for all' in protist communities. [ABSTRACT FROM AUTHOR]

This study explored the feasibility of using fish skin bandages as a therapeutic option for third-degree skin burns. Following the California wildfires, clinical observations of animals with third-degree skin burns demonstrated increased comfort levels and reduced pain when treated with tilapia fish skin. Despite the promises of this therapy, there are few studies explaining the healing mechanisms behind the application of tilapia fish skin. In this study, mice with third-degree burns were treated with either a hydrocolloid adhesive bandage (control) (n = 16) or fish skin (n = 16) 7 days post-burn. Mice were subjected to histologic, hematologic, molecular, and gross evaluation at days 7, 16, and 28 post-burn. The fish skin offered no benefit to overall wound closure compared to hydrocolloids. Additionally, we detected no difference between fish skin and control treatments in regard to hypermetabolism or hematologic values. However, the fish skin groups exhibited 2 times more vascularization and 2 times higher expression of antimicrobial defensin peptide in comparison to controls. Proteomic analysis of the fish skin revealed the presence of antimicrobial peptides. Collectively, these data suggest that fish skin can serve as an innovative and cost-effective therapeutic alternative for burn victims to facilitate vascularization and reduce bacterial infection. [ABSTRACT FROM AUTHOR]

Modeling the spread of wildland fires is essential for assessing and managing fire risks. However, this task remains challenging due to the partially stochastic nature of fire behavior and the limited availability of observational data with high spatial and temporal resolutions. Herein, we propose an attention-based deep learning modeling approach that can be used to learn the complex behaviors of wildfires across different fire-prone regions. We integrate optimized spatial and channel attention modules with a convolutional neural network (CNN) modeling architecture and train the attention-based fire spread models using a recently derived fire-tracking satellite observational dataset in conjunction with corresponding fuel, terrain, and weather conditions. The evaluation results and their comparison with benchmark models, such as a deeper and more complex autoencoder model and the semi-empirical FARSITE fire behavior model, demonstrate the effectiveness of the attention-based models. These new data-driven fire spread models exhibit promising modeling performances in both the next-step prediction (i.e., predicting fire progression from one timestep earlier) and recursive prediction (i.e., recursively predicting final fire perimeters from initial ignition points) of observed large wildfires in California, and they provide a foundation for further practical applications including short-term active fire spread prediction and long-term fire risk assessment. [ABSTRACT FROM AUTHOR]

Interactions between humans and wildfires have increased in many regions over the last decades driven by climate and land-use changes. A shift towards more adaptive fire management and policies is urgently needed but remains difficult to achieve. Better understanding of public interest in wildfire can facilitate this transition, as the public is a key driver for policy decisions. We used Google Trends to assess temporal patterns (2004–2020) in public interest on wildfires worldwide and in five case study countries (Australia, Canada, Indonesia, Portugal, USA). Public interest consistently shows a cyclic pattern with low background and short-lasting spikes during fire seasons and catastrophic events. Wildfires that receive the most interest worldwide are located in Western countries, especially the USA. There is usually high demand for news on wildfires when spikes in interest happen. Overall global interest in wildfire has risen twice: first for a short period in 2007–2008, concomitant to catastrophic wildfires in California, and again since 2017, probably triggered by a series of catastrophic fire events around the globe. Nevertheless, public interest in wildfire is low when compared with socioeconomically more costly earthquakes or hurricanes. The short and seasonal interest in wildfire may present an important obstacle to the implementation of wildfire mitigation policies that require year-round approaches. However, the fact that the public uses the internet to obtain basic knowledge about wildfire functioning and impacts, especially during the interest spikes, can facilitate targeting awareness campaigns. These could be not only about wildfires but also about broader related environmental issues. • Worldwide public interest in wildfires is on the rise (measured using Google Trends). • Interest shows a cyclic pattern with spikes during fire seasons and catastrophic events. • Global public interest strongly linked to wildfires in the West (especially USA). • Public interest in wildfire much lower than for earthquakes, hurricanes and storms. • Very strong correlation between public interest and demand for news on the topic. [ABSTRACT FROM AUTHOR]

For evacuations, people must make the critical decision to evacuate or stay followed by a multi-dimensional choice composed of concurrent decisions of their departure time, transportation mode, route, destination, and shelter type. These choices have important impacts on transportation response and evacuation outcomes. While extensive research has been conducted on hurricane evacuation behavior, little is known about wildfire evacuation behavior. To address this critical research gap, particularly related to joint choice-making in wildfires, we surveyed individuals impacted by the 2017 December Southern California Wildfires (n = 226) and the 2018 Carr Wildfire (n = 284). Using these data, we contribute to the literature in two key ways. First, we develop two latent class choice models (LCCMs) to evaluate the factors that influence the decision to evacuate or stay/defend. We find an evacuation keen class and an evacuation reluctant class that are influenced differently by mandatory evacuation orders. This nuance is further supported by different membership of people to the classes based on demographics and risk perceptions. Second, we develop two portfolio choice models (PCMs), which jointly model choice dimensions to assess multi-dimensional evacuation choice. We find several similarities between wildfires including a joint preference for within-county and nighttime evacuations and a joint dislike for within-county and highway evacuations. Altogether, this paper provides evidence of heterogeneity in response to mandatory evacuation orders for wildfires, distinct membership of populations to different classes of people for evacuating or staying/defending, and clear correlation among key wildfire evacuation choices that necessitates joint modeling to holistically understanding wildfire evacuation behavior. [ABSTRACT FROM AUTHOR]

The frequency of wildfires increases yearly and poses a constant threat to the environment and human beings. Different factors, for example surrounding infrastructure to an area (e.g., campfire sites or power lines) contribute to the occurrence of wildfires. In this paper, we propose using a Spatio-Temporal Knowledge Graph (STKG) based on OpenStreetMap (OSM) data for modeling such infrastructure. Based on that knowledge graph, we use the RDF2vec approach to create embeddings for predicting wildfires, and we align different vector spaces generated at each temporal step by partial rotation. In an experimental study, we determine the effect of the surrounding infrastructure by comparing different data composition strategies, which involve a prediction based on tabular data, a combination of tabular data and embeddings, and solely embeddings. We show that the incorporation of the STKG increases the prediction quality of wildfires. [ABSTRACT FROM AUTHOR]

Over the past four decades, annual area burned has increased significantly in California and across the western USA. This trend reflects a confluence of intersecting factors that affect wildfire regimes. It is correlated with increasing temperatures and atmospheric vapour pressure deficit. Anthropogenic climate change is the driver behind much of this change, in addition to influencing other climate-related factors, such as compression of the winter wet season. These climatic trends and associated increases in fire activity are projected to continue into the future. Additionally, factors related to the suppression of the Indigenous use of fire, aggressive fire suppression and, in some cases, changes in logging practices or fuel management intensity, collectively have produced large build-ups of vegetative fuels in some ecosystems. Human activities provide the most common ignition source for California's wildfires. Despite its human toll, fire provides a range of ecological benefits to many California ecosystems. Given the diversity of vegetation types and fire regimes found in the state, addressing California's wildfire challenges will require multi-faceted and locally targeted responses in terms of fuel management, human-caused ignitions, building regulations and restrictions, integrative urban and ecosystem planning, and collaboration with Tribes to support the reinvigoration of traditional burning regimes. [ABSTRACT FROM AUTHOR]

Background: People with HIV (PWH) are disproportionately vulnerable to the impacts of wildfires, given the need for frequent access to healthcare systems, higher burden of comorbidities, higher food insecurity, mental and behavioral health challenges, and challenges of living with HIV in a rural area. In this study, we aim to better understand the pathways through which wildfires impact health outcomes among PWH. Methods: From October 2021 through February 2022, we conducted individual semi-structured qualitative interviews with PWH impacted by the Northern California wildfires and clinicians of PWH who were impacted by wildfires. The study aims were to explore the influence of wildfires on the health of PWH and to discuss measures at the individual, clinic, and system levels that helped to mitigate these impacts. Results: We interviewed 15 PWH and 7 clinicians. While some PWH felt that surviving the HIV epidemic added to their resilience against wildfires, many felt that the wildfires compounded the HIV-related traumas that they have experienced. Participants outlined five main routes by which wildfires negatively impacted their health: (1) access to healthcare (medications, clinics, clinic staff), (2) mental health (trauma; anxiety, depression, or stress; sleep disturbances; coping strategies), (3) physical health (cardiopulmonary, other co-morbidities), (4) social/economic impacts (housing, finances, community), and (5) nutrition and exercise. The recommendations for future wildfire preparedness were at the (1) individual-level (what to have during evacuation), (2) pharmacy-level (procedural, staffing), and (3) clinic- or county-level (funds and vouchers; case management; mental health services; emergency response planning; other services such as telehealth, home visits, home laboratory testing). Conclusions: Based on our data and prior research, we devised a conceptual framework that acknowledges the impact of wildfires at the community-, household-, and individual-level with implications for physical and mental health outcomes among PWH. These findings and framework can help in developing future interventions, programs, and policies to mitigate the cumulative impacts of extreme weather events on the health of PWH, particularly among individuals living in rural areas. Further studies are needed to examine health system strengthening strategies, innovative methods to improve access to healthcare, and community resilience through disaster preparedness. Trial registration: N/A. [ABSTRACT FROM AUTHOR]

Wildfire modifies the short- and long-term exchange of carbon between terrestrial ecosystems and the atmosphere, with impacts on ecosystem services such as carbon uptake. Dry western US forests historically experienced low-intensity, frequent fires, with patches across the landscape occupying different points in the fire-recovery trajectory. Contemporary perturbations, such as recent severe fires in California, could shift the historic stand-age distribution and impact the legacy of carbon uptake on the landscape. Here, we combine flux measurements of gross primary production (GPP) and chronosequence analysis using satellite remote sensing to investigate how the last century of fires in California impacted the dynamics of ecosystem carbon uptake on the fire-affected landscape. A GPP recovery trajectory curve of more than five thousand fires in forest ecosystems since 1919 indicated that fire reduced GPP by 157:4 ± 7:3 g C m-2 y-1(mean ± SE, n = 1926) in the first year after fire, with average recovery to prefire conditions after ~12 y. The largest fires in forested ecosystems reduced GPP by 393:8 ± 15:7 g C m-2 y-1 (n = 401) and took more than two decades to recover. Recent increases in fire severity and recovery time have led to nearly 9:9 ± 3:5 MMT CO2 (3-y rolling mean) in cumulative forgone carbon uptake due to the legacy of fires on the landscape, complicating the challenge of maintaining California's natural and working lands as a net carbon sink. Understanding these changes is paramount to weighing the costs and benefits associated with fuels management and ecosystem management for climate change mitigation. [ABSTRACT FROM AUTHOR]

The rise in wildfire frequency and severity across the globe has increased interest in secondary succession. However, despite the role of soil microbial communities in controlling biogeochemical cycling and their role in the regeneration of post‐fire vegetation, the lack of measurements immediately post‐fire and at high temporal resolution has limited understanding of microbial secondary succession. To fill this knowledge gap, we sampled soils at 17, 25, 34, 67, 95, 131, 187, 286, and 376 days after a southern California wildfire in fire‐adapted chaparral shrublands. We assessed bacterial and fungal biomass with qPCR of 16S and 18S and richness and composition with Illumina MiSeq sequencing of 16S and ITS2 amplicons. Fire severely reduced bacterial biomass by 47%, bacterial richness by 46%, fungal biomass by 86%, and fungal richness by 68%. The burned bacterial and fungal communities experienced rapid succession, with 5–6 compositional turnover periods. Analogous to plants, turnover was driven by "fire‐loving" pyrophilous microbes, many of which have been previously found in forests worldwide and changed markedly in abundance over time. Fungal secondary succession was initiated by the Basidiomycete yeast Geminibasidium, which traded off against the filamentous Ascomycetes Pyronema, Aspergillus, and Penicillium. For bacteria, the Proteobacteria Massilia dominated all year, but the Firmicute Bacillus and Proteobacteria Noviherbaspirillum increased in abundance over time. Our high‐resolution temporal sampling allowed us to capture post‐fire microbial secondary successional dynamics and suggest that putative tradeoffs in thermotolerance, colonization, and competition among dominant pyrophilous microbes control microbial succession with possible implications for ecosystem function. [ABSTRACT FROM AUTHOR]

A sizable body of research has explored information seeking processes during crises and disasters, including the ways in which people seek mediated information to help make sense of the event and take action. Much of this research has postulated that information seeking is used as a mechanism for stress reduction, and that sex differences exist in terms of information seeking and risk perceptions. The current study attempted to explicate these links in the context of the 2018 California wildfires. While evidence was found for differential patterns of information seeking across sex and degree of risk perception, evidence did not support the notion that aggregate information seeking leads to a reduction in stress. Alternative theoretical explanations for sex differences in crisis information seeking and stress responses are proposed and discussed, as are implications for crisis managers and emergency responders. [ABSTRACT FROM AUTHOR]

With global wildfires becoming more widespread and severe, tracking their emissions of greenhouse gases and air pollutants is becoming increasingly important. Wildfire emissions have primarily been characterized by in situ laboratory and field observations at fine scales. While this approach captures the mechanisms relating emissions to combustion phase and fuel properties, their evaluation on regional-scale plumes has been limited. In this study, we report remote observations of total column trace gases and aerosols during the 2020 wildfire season from smoke plumes in the Sierra Nevada of California with an EM27/SUN solar Fourier transform infrared (FTIR) spectrometer. We derive total column aerosol optical depth (AOD), emission factors (EFs) and modified combustion efficiency (MCE) for these fires and evaluate relationships between them, based on combustion phase at regional scales. We demonstrate that the EM27/SUN effectively detects changes in CO, CO 2 , and CH 4 in the atmospheric column at ∼10 km horizontal scales that are attributed to wildfire emissions. These observations are used to derive total column EF CO of 120.5±12.2 and EF CH4 of 4.3±0.8 for a regional smoke plume event in mixed combustion phases. These values are consistent with in situ relationships measured in similar temperate coniferous forest wildfires. FTIR-derived AOD was compared to a nearby AERONET (AErosol RObotic NETwork) station and observed ratios of X CO to AOD were consistent with those previously observed from satellites. We also show that co-located X CO observations from the TROPOspheric Monitoring Instrument (TROPOMI) satellite-based instrument are 9.7±1.3 % higher than our EM27/SUN observations during the wildfire period. Finally, we put wildfire CH 4 emissions in context of the California state CH 4 budget and estimate that 213.7±49.8 Gg CH 4 were emitted by large wildfires in California during 2020, about 13.7 % of the total state CH 4 emissions in 2020. Our work demonstrates a novel application of the ground-based EM27/SUN solar spectrometers in wildfire monitoring by integrating regional-scale measurements of trace gases and aerosols from smoke plumes. [ABSTRACT FROM AUTHOR]

Background: Wildland–urban interface (WUI) maps identify areas with wildfire risk, but they are often outdated owing to the lack of building data. Convolutional neural networks (CNNs) can extract building locations from remote sensing data, but their accuracy in WUI areas is unknown. Additionally, CNNs are computationally intensive and technically complex, making them challenging for end-users, such as those who use or create WUI maps, to apply. Aims: We identified buildings pre- and post-wildfire and estimated building destruction for three California wildfires: Camp, Tubbs and Woolsey. Methods: We evaluated a CNN-based building dataset and a CNN model from a separate commercial vendor to detect buildings from high-resolution imagery. This dataset and model represent to end-users the state of the art of what is readily available for potential WUI mapping. Key results: We found moderate accuracies for the building dataset and the CNN model and a severe underestimation of buildings and their destruction rates where trees occluded buildings. The CNN model performed best post-fire with accuracies ≥73%. Conclusions: Existing CNNs may be used with moderate accuracy for identifying individual buildings post-fire and mapping the extent of the WUI. The implications are, however, that CNNs are too inaccurate for post-fire damage assessments or building counts in the WUI. Wildland–urban interface (WUI) maps identify communities at risk from wildfires. However, WUI maps are often outdated. We evaluated a pre-trained convolutional neural network (CNN) model and CNN-based building dataset and found that they were too inaccurate to estimate building counts and destruction, but sufficient to map where WUI is. [ABSTRACT FROM AUTHOR]

Wildfire frequency has increased in the Western US over recent decades, driven by climate change and a legacy of forest management practices. Consequently, human structures, health, and life are increasingly at risk due to wildfires. Furthermore, wildfire smoke presents a growing hazard for regional and national air quality. In response, many scientific tools have been developed to study and forecast wildfire behavior, or test interventions that may mitigate risk. In this study, we present a retrospective analysis of 1 month of the 2020 Northern California wildfire season, when many wildfires with varying environments and behavior impacted regional air quality. We simulated this period using a coupled numerical weather prediction model with online atmospheric chemistry, and compare two approaches to representing smoke emissions: an online fire spread model driven by remotely sensed fire arrival times and a biomass burning emissions inventory. First, we quantify the differences in smoke emissions and timing of fire activity, and characterize the subsequent impact on estimates of smoke emissions. Next, we compare the simulated smoke to surface observations and remotely sensed smoke; we find that despite differences in the simulated smoke surface concentrations, the two models achieve similar levels of accuracy. We present a detailed comparison between the performance and relative strengths of both approaches, and discuss potential refinements that could further improve future simulations of wildfire smoke. Finally, we characterize the interactions between smoke and meteorology during this event, and discuss the implications that increases in regional smoke may have on future meteorological conditions. Plain Language Summary: Smoke from wildfire is a growing public health concern. In order to help predict wildfire smoke exposure, we need tools that can accurately forecast where concentrated smoke will go. However, wildfires are difficult to simulate because they change quickly in response to the weather, and the behavior is sensitive to the underlying fuel which is often not well‐characterized. We used satellite observations of wildfires to constrain simulations of wildfire spread, allowing us to accurately simulate many fires occurring at the same time. This enabled simulations of 1 month of the 2020 California wildfire season, one of the worst on record. We evaluated the accuracy of this simulation using measurements of surface air quality, and using a similar simulation with a more widely used methodology. The results from this study will help us develop more accurate tools to predict smoke concentrations and impacts on meteorology during future events. Key Points: SFIRE and Fire Inventory from NCAR, two approaches for modeling wildfire smoke emissions, are comparedNovel methods of ingesting satellite data allow wildfire behavior simulations at scales useful for air quality studiesCoupled simulations of wildfire spread and atmospheric transport can accurately characterize wildfire impacts on regional air quality [ABSTRACT FROM AUTHOR]

Background: Wildfire severity mediates key dynamics, such as nutrient pulses, that regulate the recovery of ecosystem functioning. Large shifts in vegetation communities associated with plant invasions are often coupled with changes in soil communities; thus, it's critical to understand how fire severity may interact with vegetation type and soil communities to mediate ecosystem recovery. Methods: Following a 2017 wildfire in southern California, soils from areas dominated by native coastal sage scrub or exotic annual grasses that experienced a low or high severity fire event were analyzed for nutrient concentrations and two proxies for ecosystem function—microbial respiration and enzymatic activity potentials over the first-year post-fire. Aims: We predicted that increasing fire severity would positively correlate with soil nutrient concentrations. Thus, higher severity burned soil would experience a greater downregulation of enzyme activity as potential microbial nutrient limitation was alleviated, a relationship that would be stronger in shrub dominated soil. Results: We observed a strong soil nitrogen (N) pulse post-fire, which was greatest in shrub dominated soil; however, dominant vegetation had a variable effect on microbial responses. Enzyme activities were downregulated in CSS soil, but the grass dominated soil response was inconsistent. After 1 year, soil N remained elevated in burned soil, suggesting that basal soil N concentrations were altered. Conclusions: Persistent, residual soil N concentrations are of particular concern in high fire risk ecosystems, which will likely experience increasing fire frequency associated with environmental change; thus, encouraging the regrowth of opportunistic vegetation in subsequent growing seasons will be key to minimize long-term changes to these ecosystems. [ABSTRACT FROM AUTHOR]

Floods caused by atmospheric rivers and wildfires fanned by Santa Ana winds are common occurrences in California with devastating societal impacts. In this work, we show that winter weather variability in California, including the occurrence of extreme and impactful events, is linked to four atmospheric circulation regimes over the North Pacific Ocean previously named and identified as the "NP4 modes". These modes come in and out of phase with each other during the season, resulting in distinct weather patterns that recur throughout the historical record. Some phase combinations favor atmospheric river landfalls and extreme daily or multi-day precipitation, while other phase combinations favor anomalously hot weather and drying Santa Ana wind conditions over Southern California. This historical perspective of atmospheric circulation and impacts over 70 years reveals that weather patterns are changing in a way that enhances wildfire hazard in California, while the frequency of weather patterns linked to historical floods is not diminishing. These changes highlight the rising hazards of cascading weather extremes in California's present and future. [ABSTRACT FROM AUTHOR]

Increasing wildfire and declining snowpacks in mountain regions threaten water availability. We combine satellite‐based fire detections with snow seasonality classifications to examine fire activity in California's seasonal and ephemeral snow zones. We find a nearly tenfold increase in fire activity during 2020–2021 versus 2001–2019. Accumulation season broadband snow albedo declined 25%–71% at two burned sites (2021 and 2022) according to in‐situ data relative to un‐burned conditions, with greater declines associated with increased burn severity. By enhancing snowpack susceptibility to melt, both decreased snow albedo and canopy drove midwinter melt during a multi‐week dry spell in 2022. Despite similar meteorological conditions in December–February 2013 and 2022–linked to persistent high pressure weather regimes–minimal melt occurred in 2013. Post‐fire snowpack differences are confirmed with satellite measurements. With growing geographical overlap between wildfire and snow, our findings suggest California's snowpack is increasingly vulnerable to the compounding effects of dry spells and wildfire. Plain Language Summary: Satellite fire detections indicate substantial increases in wildfire activity in California's snow‐covered landscapes during 2020 and 2021, suggesting wildfire is increasingly altering mountain hydrology. During 2022, a multi‐week mid‐winter drought, or dry spell, occurred. A meteorologically‐similar dry spell occurred in 2013, and the 2022 event provides a test case to examine how post‐fire changes (canopy loss and deposition of burned dark material on snowpack) alter snowmelt patterns. Using field observations, weather station data, and satellite remote sensing of snow, we find large reductions in snow albedo and canopy cover drove rapid melt during the 2022 dry spell in burned areas whereas during 2013, minimal melt occurred. The societal connection between mountains and humans will be strained as mountains face increasing climate‐related stressors. Midwinter drought, snow loss, and increasing wildfire are expectations of a warming world. Addressing these challenges requires innovative water and forest management paradigms. Our findings motivate additional research into assessing and planning for post‐fire hydrologic changes in snow‐dominated landscapes as both wildfire and dry spells will increase in frequency with climate warming. Key Points: A 9.8x increase in satellite fire detections in California's snow zones in 2020–2021 versus 2001–2019 implies growing overlap in fire and snowPost‐fire accumulation season broadband snow albedo declined 25%–71%, driving fewer snow‐covered days and lower snow‐cover fractionCompared with the meteorologically similar 2013 dry spell, albedo and canopy declines led to rapid midwinter melt in 2022 [ABSTRACT FROM AUTHOR]

This paper examines the relationship between daily carbon emissions for California's savanna and forest wildfires and regional meteorology over the past 18 years. For each fuel type, the associated weather [daily maximum wind, daily vapor pressure deficit (VPD), and 30-day-prior VPD] is determined for all fire days, the first day of each fire, and the day of maximum emissions of each fire at each fire location. Carbon emissions, used as a marker of wildfire existence and growth, for both savanna and forest wildfires are found to vary greatly with regional meteorology, with the relationship between emissions and meteorology varying with the amount of emissions, fire location, and fuel type. Weak emissions are associated with climatologically typical dryness and wind. For moderate emissions, increasing emissions are associated with higher VPD from increased warming and only display a weak relationship with wind speed. High emissions, which encompass ∼85% of the total emissions but only ∼4% of the fire days, are associated with strong winds and large VPDs. Using spatial meteorological composites for California subregions, we find that weak-to-moderate emissions are associated with modestly warmer-than-normal temperatures and light winds across the domain. In contrast, high emissions are associated with strong winds and substantial temperature anomalies, with colder-than-normal temperatures east of the Sierra Nevada and warmer-than-normal conditions over the coastal zone and the interior of California. Significance Statement: The purpose of this work is to better understand the influence of spatially and temporally variable meteorology and spatially variable surface fuels on California's fires. This is important because much research has focused on large climatic scales that may dilute the true influence of weather (here, high winds and dryness) on fire growth. We use a satellite-recorded fire emissions dataset to quantify daily wildfire existence and growth and to determine the relationship between regional meteorology and wildfires across varying emissions in varying fuels. The result is a novel view of the relationship between California wildfires and rapidly variable, regional meteorology. [ABSTRACT FROM AUTHOR]

Background: Buildings in communities near wildlands, in the wildland–urban interface (WUI), can experience wildfire damage. Aims: To quantitatively assess the relationship between building features and damage, a building wildfire resistance index is developed and validated with the 2013–2017 CAL FIRE (DINS) database from California, USA, and the 2017 Pedrógão Grande Fire Complex post-fire investigation from Portugal. Methods: Three statistical dependence tests are compared to evaluate the relationship between selected building features and damage. The Wildfire Resistance Index (WRI), range: [–1, 1], is proposed and validated as a rating for building wildfire susceptibility. Key results: The most correlated features to wildfire damage are the presence of vent screens and deck materials in California, and exterior walls material and deck materials in Portugal. For Portugal, as WRI increases by 50%, linear regression estimates a 48% decrease in proportion of highly damaged buildings, and a 42% increase in proportion of low damage buildings (R 2 of 0.93 and 0.90, respectively). A total of 65% of California buildings with WRI = 1 were destroyed, compared to average 85% for WRI ≥−0.33. Conclusions: The WRI quantifies the wildfire damage experienced by buildings in two diverse WUI regions. Implications: The WRI could be used as an estimator of wildfire damage but it needs further development. This paper presents a statistical analysis of two post-fire building inspection databases of wildland–urban interface (WUI) damage in California and Portugal. Results compare considered building features' relative correlation to damage, and propose the Wildfire Resistance Index: an index applied to the vulnerability of WUI buildings to wildfire ignition and damage. [ABSTRACT FROM AUTHOR]

Annual burned area has increased in California over the past three decades as a result of rising temperatures and a greater atmospheric demand for moisture, a trend that is projected to continue throughout the 21st century as a result of climate change. Here, we implement a bias-correction and statistical downscaling technique to obtain high resolution, daily meteorological conditions for input into two fire weather indices: vapor pressure deficit (VPD) and the Canadian Fire Weather Index System (FWI). We focus our analysis on 10 ecoregions that together account for the diverse range of climates, ecosystems, topographies, and vegetation types found across the state of California. Our results provide evidence that fire weather conditions will become more extreme and extend into the spring and fall seasons in most areas of California by 2100, extending the amount of time vegetation is exposed to increased atmospheric demand for moisture, and heightening the overall risk for the ignition and spread of large wildfire. The ecoregion-level spatial scale adopted for this study increases the spatial specificity of fire weather information, as well as the resolution with which fire and land managers can implement strategies and counter-measures when addressing issues related to climate change. [ABSTRACT FROM AUTHOR]

The rubber boa, Charina bottae is a semi-fossorial, cold-temperature adapted snake that ranges across the wetter and cooler ecoregions of the California Floristic Province. The rubber boa is 1 of 2 species in the family Boidae native to California and currently has 2 recognized subspecies, the Northern rubber boa C. bottae bottae and the Southern rubber boa C. bottae umbratica. Recent genomic work on C. bottae indicates that these 2 subspecies are collectively composed of 4 divergent lineages that separated during the late Miocene. Analysis of habitat suitability indicates that C. bottae umbratica montane sky-island populations from southern California will lose the majority of their habit over the next 70 yr, and is listed as Threatened under the California Endangered Species Act. Here, we report a new, chromosome-level assembly of C. bottae bottae as part of the California Conservation Genomics Project (CCGP). Consistent with the reference genome strategy of the CCGP, we used Pacific Biosciences HiFi long reads and Hi-C chromatin-proximity sequencing technology to produce a de novo assembled genome. The assembly comprises 289 scaffolds covering 1,804,944,895 bp, has a contig N50 of 37.3 Mb, a scaffold N50 of 97 Mb, and BUSCO completeness score of 96.3%, and represents the first reference genome for the Boidae snake family. This genome will enable studies of genetic differentiation and connectivity among C. bottae bottae and C. bottae umbratica populations across California and help manage locally endemic lineages as they confront challenges from human-induced climate warming, droughts, and wildfires across California. [ABSTRACT FROM AUTHOR]

Clear Lake (Lake County, CA, USA) is hypereutrophic and used for drinking water, tribal use, and supports a significant fishing economy. The Mendocino Complex (2018), one of the largest wildfires in California's post‐settlement history, burned 40% of the Clear Lake watershed, providing a timely opportunity to study the impacts of historical and current wildfires on this valuable aquatic resource. Using long‐term monthly monitoring data from 1968 to 2019, paired with historical watershed fire data, we found that for the three largest fire years in the watershed's history, 3‐year postfire median July–October epilimnetic total phosphorus (TP) concentrations were below or equal to 3‐year prefire TP concentrations. However, both median TP epilimnetic concentrations and deepwater temperature across the lake have increased since the late 1960s. Long‐term TP increases were more strongly correlated with monthly maximum air temperatures than precipitation, suggesting a potential role of warming‐induced water column stratification, dissolved oxygen (DO) depletion, and high potential for internal phosphorus loading. Hypoxic occurrences were correlated with higher hypolimnetic soluble reactive phosphorus and TP concentrations, but additional high‐frequency monitoring of DO will help determine the duration of anoxia and its contribution to internal phosphorus loading. These long‐term data suggest that for this large, hypereutrophic lake, wildfires did not significantly alter in‐lake TP concentrations based on long‐term, monthly monitoring and that other internal or external sources of TP may mask any wildfire effects. Nonetheless, our study underscores the value of synthesizing decades of water quality, watershed wildfire, and climate data to build a more comprehensive, nuanced picture of multiple long‐term threats to aquatic ecosystems under global change. Moreover, monitoring and studying fire effects across a wide range of lake types beyond this study will help promote more effective lake management during changing climates and increasingly frequent large wildfires. [ABSTRACT FROM AUTHOR]

As human impacts from wildfires mount, there is a pressing need to understand why structures are lost in destructive fires. Despite growing research on factors contributing to structure loss, fewer studies have focused on why some fires are destructive and others are not. We characterized overall differences between fires that resulted in structure loss ("destructive fires") and those that did not ("non-destructive wildfires") across three California regions. Then, we performed statistical analyses on large fires only (≥100 ha) to distinguish the primary differences between large destructive large fires and large non-destructive fires. Overall, destructive fires were at least an order of magnitude larger than non-destructive fires, with the largest area burned varying by season in different regions. Fire severity was also significantly higher in destructive than non-destructive fires. The statistical analysis showed that, in the San Francisco Bay Area and the northern Sierra Nevada foothills, proximity to the Wildland Urban Interface (WUI) was by far the most important factor differentiating destructive and non-destructive wildfires, followed by different combinations of short-term weather, seasonal climate, topography, and vegetation productivity. In Southern California, wind velocity on the day of the fire ignition was the top factor, which is consistent with previous assumptions that wind-driven fires tend to be most destructive and most of the destruction occurs within the first 24 h. Additionally, Southern California's high population density increases the odds that a human-caused wildfire may occur during a severe fire-weather event. The geographical differences among regions and the variation of factors explaining the differences between large destructive and large non-destructive fires reflects the complexity inherent in decision-making for reducing wildfire risk. Land use planning to reduce future exposure of housing development to fire and increased focus on wildfire ignition prevention emerge as two approaches with substantial potential. [ABSTRACT FROM AUTHOR]

Aim: Wildfire burned area, fire size, fire severity and the ecological and socio‐economic impacts of fire have been increasing rapidly in California in recent decades. We summarize the record‐breaking 2020 wildfire season in California statistically, evaluate the drivers of high‐severity burning in the 2020 fires and consider implications for fire and resource management. Location: California, USA. Time period: 2020, with consideration of long‐term trends in many variables. Major taxa studied: Humans, vegetation and wildlife. Methods: We statistically summarize the record‐breaking 2020 fire year in California and outline the salient ecological and socio‐economic impacts. Then we fit two statistical models to determine how a suite of weather‐ and fuel‐related variables influenced high‐severity burning in different vegetation types and in different fire events during the 2020 fire season. Results: In 2020, 1.74 million ha burned in California, 2.2 times more than the previous historical record but only average when compared with pre‐Euroamerican conditions. Economic losses exceeded $19 billion, and 33 people were killed directly by fire. Vegetation type and recent fire history had important effects on burning. Variability in high‐severity burning among vegetation types was driven principally by vapour pressure deficit and wind speed; variability among fire events was related principally to time since the last fire (a surrogate for fuel loading). Main conclusions: The 2020 fires were part of an accelerating decades‐long trend of increasing burned area, fire size, fire severity and socio‐ecological costs in California. In fire‐prone forests, the management emphasis on reducing burned area should be replaced by a focus on reducing the severity of burning and restoring key ecosystem functions after fire. There have been positive developments in California vis‐à‐vis collaborative action and increased pace and scale of fuel management and pre‐ and postfire restoration, but the warming climate and other factors are rapidly constraining our options. [ABSTRACT FROM AUTHOR]

Wildfires and their resulting smoke are an increasing problem in many regions of the world. However, identifying the contribution of smoke to pollutant loadings in urban regions can be challenging at low concentrations due to the presence of the usual array of anthropogenic pollutants. Here we propose a method using the difference in PM 2.5 to CO emission ratios between smoke and typical urban pollution. For temperate wildfires, the mean emission ratio of PM 2.5 to CO is in the range of 0.14–0.18 g PM 2.5 g CO -1 , whereas typical urban emissions have a PM 2.5 to CO emissions ratio that is lower by a factor of 2–20. This gives rise to the possibility of using this ratio as an indicator of wildfire smoke. We use observations at a regulatory surface monitoring site in Sparks, NV, for the period of May–September 2018–2021. There were many smoke-influenced periods from numerous California wildfires that burned during this period. Using a PM 2.5 / CO threshold of 30.0 µgm-3ppm-1 , we can split the observations into smoke-influenced and no-smoke periods. We then develop a Monte Carlo simulation, tuned to local conditions, to derive a set of PM 2.5 / CO values that can be used to identify smoke influence in urban areas. From the simulation, we find that a smoke enhancement ratio of 140 µgm-3ppm-1 best fits the observations, which is significantly lower than the ratio observed in fresh smoke plumes (e.g., 200–300 µgm-3ppm-1). The most likely explanation for this difference is loss of PM 2.5 during dilution and transport to warmer surface layers. We find that the PM 2.5 / CO ratio in urban areas is an excellent indicator of smoke and should prove to be useful to identify biomass burning influence on the policy-relevant concentrations of both PM 2.5 and O 3. Using the results of our Monte Carlo simulation, this ratio can also quantify the influence of smoke on urban PM 2.5. [ABSTRACT FROM AUTHOR]

Wildfires in California have been progressively increasing in duration, intensity and frequency. In response, a number of best practices have been developed for mitigating and responding to fires within the state. This paper describes the lessons learned within core capabilities and describes current practices. Reflections are offered as a consideration and should not be interpreted as standards of practice. [ABSTRACT FROM AUTHOR]

At the intersection of climate change and rural development, wildfire has emerged as a threat to agriculture in the Western United States. This nexus is particularly problematic for the rapidly developing cannabis industry in California, which includes farms located outside of traditional agricultural zones and within landscapes potentially more prone to wildfire. With the goal of determining whether cannabis is uniquely vulnerable to direct wildfire impacts (in terms of crop loss to burning), we integrated fire hazard severity zone (FHSZ) data, wildfire perimeters, and future burn regime projections in relation to the location and cultivated area of cannabis farming. We then applied descriptive statistics and generalized additive models (GAMs) to compare the location of licensed cannabis farms to other agricultural types in California, including grapes, pasture, and all other general crops combined. We found cannabis farming was located more often in high and very high FHSZs and closer to wildfire perimeters than any other agricultural type. GAM estimates of likelihood of occurrence in high and very high severity zones were highest for cannabis, even after accounting for spatial clustering of farm types, although there was no reliable difference in predicted distances to wildfire. Cannabis more often occurred in projected (from 2020 to 2100) wildfire hotspots than all other agricultural types, with GAM estimates affirming a reliably higher likelihood of cannabis in future hotspots than pasture or general crops. Our findings highlight cannabis' particular vulnerability to wildfire in California and may in fact underestimate wildfire risks given the potential indirect impacts of smoke to crops and farmworkers, which were not evaluated in this study. In light of the sector's growing economic importance in the state, these vulnerabilities should be considered in future cannabis and rural development policies. [ABSTRACT FROM AUTHOR]

Wildfires are becoming more frequent and destructive in California, and it is essential to quantify their potential impacts on drinking water utilities. This study aims to measure the severity of wildfires in each California water utility based on the exposure frequency and the extent of area burned by wildfires in each service area. Our quantitative models show an association between water utility characteristics and their vulnerability to wildfires. Findings indicate that wildfire vulnerability is higher in government-owned utilities than private ones, utilities primarily relying on surface water than groundwater, and utilities using local-sourced water than purchased water. Also, we find a stronger association between wildfire vulnerability and large utilities in terms of population served than small or medium ones. Regarding geography, we find wildfire vulnerability is higher in southern and coastal California utilities than in Northern and inland California. These results help water utilities and land managers identify vulnerable locations and develop wildfire management and disaster preparedness strategies. [ABSTRACT FROM AUTHOR]