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From 2017 to 2023, British Columbians experienced four record-breaking wildfire seasons, resulting in reduced air quality, mass evacuations and the destruction of homes, properties and livelihoods. Wildfire risk reduction is vital to breaking the sequence of disaster that has befallen such communities as Kelowna, BC in 2003, Ft. McMurray, AB in 2016, and Lytton, BC in 2021. As the City of Penticton ('the City') is located in a wildfire-prone environment, its Fire Department, FireSmart Team and Emergency Program have worked closely together to facilitate a proactive and comprehensive approach towards reducing the impacts of wildfire on Penticton's neighbourhoods, businesses and residents through a variety of wildfire mitigation initiatives. This paper discusses the City's efforts to achieve a holistic wildfire risk management plan through alignment with the seven disciplines of FireSmart and the four pillars of emergency management, namely: the use of education; land use planning and development considerations; vegetation management; emergency planning; and cross training and interagency cooperation. The paper describes the challenges the City has faced, as well its successes, and provides recommendations to help other local authorities reduce the risk of wildfire in their communities. [ABSTRACT FROM AUTHOR]

Wildfires have become more frequent and intense in recent years, threatening terrestrial and aquatic ecosystems and neighboring urban communities. As a result, those responsible for managing wildland fires face increasing pressure to address this challenge strategically. Over the past 20 years, these managers have turned to decision support tools (DSTs) to help guide their actions. We conducted a systematic literature review to explore the landscape of decision support tools (DSTs) for wildfire management, focusing on their functionalities. We additionally examined potential gaps in their design and implementation. The systematic review led us to group decision support tools into categories for all DSTs, such as, Fire Behavior Models or Post Fire Models. These categories are not discrete and can be nested to address land management and fire response questions. Moreover, our findings highlighted a significant gap in tools that effectively integrate ease of use with collaborative capabilities, underscoring the urgency for developing more user-friendly and collaborative decision-making tools. Our research also revealed a disconnect between the academic literature's focus and the tools' actual field usage, emphasizing the need for more accurate documentation and a streamlined approach to wildfire management tool selection. We proposed further social science research to understand the real-world use and preferences of DSTs, aiming to bridge the gap between theoretical robustness and practical utility. This comprehensive analysis of DSTs addresses current wildfire management challenges and sets the stage for future advancements in developing more effective and user-oriented decision support systems.

This study utilizes remote sensing, Google Earth Engine (GEE), and Sentinel-2 imagery to map burn severity in Isparta province, Türkiye, in August from 2017 to 2022. Employing true color and normalized burn ratio (NBR) maps, the research assesses land conditions and vegetation dynamics. The delta normalized burn ratio (dNBR) reveals changing burn severity, particularly in agricultural and forested areas. The study granularly analyzes burn severity in agricultural areas and forested/semi-natural regions. Results show a significant decline in the 'Unburned' class, indicating altered land use and increased fire impact. 'High post-fire regrowth' expansion signifies vegetation recovery, while varied patterns in the 'Low post-fire regrowth' class suggest influences from environmental variables, fire management, and climate. Total burn severity escalates, with a 133.2% rise in agricultural zones and an 888.0% surge in forested/semi-natural regions from 2018 to 2022, highlighting the growing wildfire threat. In conclusion, this research provides crucial insights into Isparta's environmental dynamics, emphasizing the need for meticulous analysis in shaping effective fire management strategies and conducting comprehensive environmental assessments.

This document is a correction notice for a journal article titled "A quantitative wildfire risk assessment using a modular approach of geostatistical clustering and regionally distinct valuations of assets—A case study in Oregon." The correction addresses a typographical error in the abstract section and provides the correct paragraph. The study focuses on the increased intensity and scale of wildfires in the Pacific Northwest, particularly in Oregon, and the potential risks posed by climate change, population growth, and changes in land cover. The authors present the results of a multi-phase initiative that combines fire model results with valuations of resources and assets based on regional conditions. The study emphasizes the need for collaboration between different landowners, managers, and stakeholders to effectively address wildfire damage protection and mitigation. The correction also mentions errors in the data availability statement and the figures included in the article. [Extracted from the article]

Climate change increases the risk of wildfires and floods in the Mediterranean region. Yet, wildfire hazards are often overlooked in flood risk assessments and treated in isolation even though they can amplify floods. Indeed, by altering the hydrological response of burnt areas, wildfires can lead to increased runoff and cascading impacts. This study aims to comprehensively assess flood risk using a multi-criteria GIS-based approach, considering both current conditions and future scenarios for the Ebro River basin in Spain in the year 2100. More specifically, this study investigates future flood risk under the Shared Socioeconomic Pathways (SPP) 1-2.6 and SSP5-8.5 scenarios, taking into account projected socio-economic conditions and the cascading impact of wildfires. An Analytical Hierarchy Process (AHP) approach is employed to assign weights to various indicators and components of flood risk, based on insights gathered from interviews with seven experts specializing in natural hazards. Results show that the influence of wildfires on baseline flood risk is not apparent. Under the SSP1-2.6 scenario, regions with high flood risk are expected to experience a slight risk reduction, regardless of the presence of wildfires, due to an expected substantial development in adaptive capacity. The highest flood risk, almost double compared to the baseline, is projected to occur in the SSP5-8.5 scenario, especially when considering the cascading impacts of wildfires. Therefore, this research highlights the importance of adopting a multi-hazard risk management approach, as reliance solely on single-risk analyses may lead to an underestimation of the compound and cascading impacts of multi-hazards. [ABSTRACT FROM AUTHOR]

As climate change increases the frequency and severity of wildfires across the Western U.S., there is an urgent need for improved wildfire preparedness and responses. Socially marginalized communities are particularly vulnerable to wildfire effects because they disproportionately lack access to the resources necessary to prepare for and recover from wildfire and are frequently underrepresented in the wildfire planning process. As an exemplar of how to understand and improve preparedness in such communities, this research identified communities in Ventura County facing heightened marginalization and risk of wildfire using spatial analysis. Researchers then deployed a county-wide survey and held focus groups in two communities identified in the spatial analysis. Research revealed that non-English speakers, women, people of color, and newer residents in Ventura County are less prepared for wildfire than other groups. Based on these findings, this paper recommends an expansion of traditional risk mitigation programs, strengthened community engagement efforts, and strategies that increase community resources and leadership to decouple marginalization and wildfire vulnerability. [ABSTRACT FROM AUTHOR]

Climate change is expected to have long-term impacts on drought and wildfire risks in Oregon as summers continue to become warmer and drier. This paper investigates the projected changes in drought characteristics and drought propagation in the Umatilla River Basin in northeastern Oregon for mid-century (2030–2059) and late-century (2070–2099) climate scenarios. Drought characteristics for projected climates were determined using downscaled CMIP5 climate datasets from ten climate models and Soil and Water Assessment Tool to simulate effects on hydrologic processes. Short-term (three months) drought characteristics (frequency, duration, and severity) were analyzed using four drought indices, including the Standardized Precipitation Index (SPI-3), Standardized Precipitation-Evapotranspiration Index (SPEI-3), Standardized Streamflow Index (SSI-3), and the Standardized Soil Moisture Index (SSMI-3). Results indicate that short-term meteorological droughts are projected to become more prevalent, with up to a 20% increase in the frequency of SPI-3 drought events. Short-term hydrological droughts are projected to become more frequent (average increase of 11% in frequency of SSI-3 drought events), more severe, and longer in duration (average increase of 8% for short-term droughts). Similarly, short-term agricultural droughts are projected to become more frequent (average increase of 28% in frequency of SSMI-3 drought events) but slightly shorter in duration (average decrease of 4%) in the future. Historically, drought propagation time from meteorological to hydrological drought is shorter than from meteorological to agricultural drought in most sub-basins. For the projected climate scenarios, the decrease in drought propagation time will likely stress the timing and capacity of water supply in the basin for irrigation and other uses. [ABSTRACT FROM AUTHOR]

Globally, wildfires are increasing in extent, frequency, and severity. Although global climate change is a major driver and large-scale governance interventions are essential, focusing on governance at smaller scales is of great importance for fostering resilience to wildfires. Inherent tensions in managing wildfire risk are evident at such scales, as objectives and mandates may conflict, and tradeoffs and impacts vary across ecosystems and communities. Our study feeds into debates about how to manage wildfire risk to life and property in a way that does not undermine biodiversity and amenity values in social-ecological systems. Here, we describe a case study where features of adaptive governance emerged organically from a dedicated planning process for wildfire governance in Australia. We found that a governance process that is context specific, allows for dialogue about risk, benefits, and trade-offs, and allows for responsibility and risk to be distributed amongst many different actors, can provide the conditions needed to break down rigidity traps that constrain adaptation. The process enabled actors to question whether the default risk management option (in this case, prescribed burning) is aligned with place-based risks and values so they could make an informed choice, built from their participation in the governance process. Ultimately, the community supported a move away from prescribed burning in favor of other wildfire risk management strategies. We found that the emergent governance system has many features of adaptive governance, even though higher level governance has remained resistant to change. Our study offers positive insights for other governments around the world interested in pursuing alternative strategies to confronting wildfire risk [ABSTRACT FROM AUTHOR]

Wildfire prediction has drawn a lot of researchers' interest, but still presents a computational difficulty since it necessitates real-time data collected from several distributed data sources. Furthermore, because environmental Web services have, now, access to a wider range of environmental data sources, services might be functionally similar but of varying quality. In this paper, we propose a knowledge-driven framework for service composition that is based on a layered architecture. Based on these layers, the proposed framework aims to select the optimal service instances participating in a service composition schema, through a modular ontology to infer the quality of data sources (QoDS) and an outranking approach. Moreover, it aims to executing the service composition schema at runtime by dynamically readjusting both the service composition schema and the service instances via a machine learning-based service composition approach. The conducted experiments showed that the proposed framework enables (i) a reasonable reasoning time for assessing the data sources' quality, (ii) a decrease in the ELECTRE III MCDM method's execution time achieved by combining the skyline and α -dominance methods, (iii) dynamic generation of the most relevant service composition schema with the appropriate wildfire risk classes, and (iv) a high prediction accuracy using our proposed outranking approach compared to the randomly selected services. [ABSTRACT FROM AUTHOR]

In recent years, several places all over the world have experienced devastating wildfire events that have resulted in exorbitant losses. With the climate warming every year, the trend of destructive fires is expected to continue in the future as well. To be better prepared for such events, an understanding of interaction between wildfires and the built environment is required. In this study, a graph-based approach is utilized to predict the damage to individual buildings in a test area selected from the 2022 Marshall Fire–affected region. The validity of the graph model is first shown by comparing the predicted damage with the observed damaged patterns, showing 72% accuracy. The model is further utilized to investigate the sensitivity of the damage patterns to wind conditions to better understand the correlation between wind characteristics and the resulting damage. For two wind speeds, 12 and 25 m/s , polar fragilities are developed by evaluating the damage for different wind directions. The results showed the variation in damage distribution among all wind directions for 25 m/s to be more than twice that for 12 m/s , highlighting the fact that the impact of wind conditions is nonlinear and needs to be carefully considered for wildfire risk assessment. [ABSTRACT FROM AUTHOR]

Background: Wildfire smoke exposure has become a growing public health concern, as megafires and fires at the wildland urban interface increase in incidence and severity. Smoke contains many pollutants that negatively impact health and is linked to a number of health complications and chronic diseases. Communicating effectively with the public, especially at-risk populations, to reduce their exposure to this environmental pollutant has become a public health priority. Although wildfire smoke risk communication research has also increased in the past decade, best practice guidance is limited, and most health communications do not adhere to health literacy principles: readability, accessibility, and actionability. This scoping review identifies peer-reviewed studies about wildfire smoke risk communications to identify gaps in research and evaluation of communications and programs that seek to educate the public. Methods: Four hundred fifty-one articles were identified from Web of Science and PubMed databases. After screening, 21 articles were included in the final sample for the abstraction process and qualitative thematic analysis. Ten articles were based in the US, with the other half in Australia, Canada, Italy, and other countries. Fifteen articles examined communication materials and messaging recommendations. Eight papers described communication delivery strategies. Eleven articles discussed behavior change. Six articles touched on risk communications for vulnerable populations; findings were limited and called for increasing awareness and prioritizing risk communications for at-risk populations. Results: This scoping review found limited studies describing behavior change to reduce wildfire smoke exposure, characteristics of effective communication materials and messaging, and communication delivery strategies. Literature on risk communications, dissemination, and behavior change for vulnerable populations was even more limited. Conclusions: Recommendations include providing risk communications that are easy-to-understand and adapted to specific needs of at-risk groups. Communications should provide a limited number of messages that include specific actions for avoiding smoke exposure. Effective communications should use mixed media formats and a wide variety of dissemination strategies. There is a pressing need for more intervention research and effectiveness evaluation of risk communications about wildfire smoke exposure, and more development and dissemination of risk communications for both the general public and vulnerable populations. [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.)

BRIDGE (bridging science and local communities for wildfire risk reduction) is an action–research project developing a community-based disaster risk reduction (CBDRR) process which is being fostered through a collaborative innovation laboratory (InnoLab). BRIDGE integrates different forms of knowledge and action, linking science and local communities to reduce their vulnerability and to enhance strategies for forest fire risk reduction. Applied in Monchique, a forest-fire-prone municipality in Portugal, the InnoLab creates a space for dialogue and knowledge sharing between multiple actors that, directly or indirectly, manage forest territories. BRIDGE attempts to facilitate social learning about forest fire risks, strengthen collaborative networks and enhance adaptive capacities (socially and institutionally) for forest fire prevention. This paper shares results of the InnoLab activities, which include (i) school community activities on wildfire risk perception; (ii) participatory mapping of Monchique's vulnerabilities and risks; (iii) participatory sessions to create the community visioning for Monchique's territory, to define priorities and capacities to be improved, and to identify functions and responsibilities to act upon; and (iv) workshop on CBDRR strategies for action. Lessons are shared on how InnoLab can represent an innovative participatory approach to promote CBDRR processes in forest-fire-prone territories by both contributing to the recognition of local knowledge systems and encouraging the active role of forest communities through strengthened local networks for a more lasting commitment to forest fire risk reduction policy. [ABSTRACT FROM AUTHOR]

Wildfires are a significant problem in Irkutsk Oblast. They are caused by climate change, thunderstorms, and human factors. In this study, we use the Random Forest machine learning method to map the wildfire susceptibility of Irkutsk Oblast based on data from remote sensing, meteorology, government forestry authorities, and emergency situations. The main contributions of the paper are the following: an improved domain model that describes information about weather conditions, vegetation type, and infrastructure of the region in the context of the possible risk of wildfires; a database of wildfires in Irkutsk Oblast from 2017 to 2020; the results of an analysis of factors that cause wildfires and risk assessment based on Random Forest in the form of fire hazard mapping. In this paper, we collected and visualized data on wildfires and factors influencing their occurrence: meteorological, topographic, characteristics of vegetation, and human activity (social factors). Data sets describing two classes, "fire" and "no fire", were generated. We introduced a classification according to which the probability of a wildfire in each specific cell of the territory can be determined and a wildfire risk map built. The use of the Random Forest method allowed us to achieve the following risk assessment accuracy indicators: accuracy—0.89, F1-score—0.88, and AUC—0.96. The comparison of the results with earlier ones obtained using case-based reasoning revealed that the application of the case-based approach can be considered the initial stage for deeper investigations with the use of Random Forest for more accurate forecasting. [ABSTRACT FROM AUTHOR]

In this paper, we analyse the socio-economic determinants of environmental crimes such as those focused on wildfire in Italy using panel data at the regional level. We also investigate the effect of economic downturns on wildfire crime. Using the nonadditive fixed effect quantile panel regression model, it was found that socio-economic factors, such as material deprivation, play an important role in driving wildfire crime. Also, risk factors such as unemployment and income inequality were seen to affect the probability of crime in the same direction. On the other hand, a negative relationship between level of education and wildfire crime was found. The results for business cycle support the conjecture that economic downturns have a significant impact on the probability of environmental crime and that the effect is particularly binding in the southern regions where unemployment and income inequality are greater. We also found evidence of a positive correlation between organised crime and wildfire crime. Once again, the grip of organised crime appears to be stronger in the southern regions. [ABSTRACT FROM AUTHOR]

Large wildfires are increasing across numerous regions of the globe. While the West has remained a primary focus of wildfire research and resources in the U.S., recent signals suggest that wildfire risk is increasing in the eastern U.S. as well. We conducted an in‐depth assessment of large (>200 ha) wildfire regime characteristics (size, number, total hectares burned, seasonality, probability of occurrence, and ignition source) over a 36‐year period across the Eastern Temperate Forests of the U.S. to quantify geographic patterns in large‐wildfire regime and identify changing spatio‐temporal large wildfire patterns. We found increases in large wildfire size, occurrence, number, and total hectares burned in the southern and eastern regions of the Eastern Temperate Forests. In contrast, large wildfires declined or were minimal in northern ecoregions. We demonstrate increasing large wildfires across some of the most populated regions of the United States. Plain Language Summary: Large wildfires are increasing across numerous regions of the globe. While the western U.S. has remained a primary focus for wildfire research and resources, recent signals suggest that wildfire risk is also increasing in the eastern U.S. We assess patterns and changes in large (>200 ha) wildfire size, number, total hectares burned, seasonality, probability of occurrence, and ignition source over 36 years in the Eastern Temperate Forests, a region comprising most of the eastern U.S. We found that large wildfire size, occurrence, number, and total hectares burned increased in the southern and eastern portions of the Eastern Temperate Forests. In contrast, large wildfires declined or there were too few wildfires to assess in northern portions of the Eastern Temperate Forests. Our findings suggest the potential for increasing wildfire risk across some of the most populated regions of the U.S. Key Points: Large wildfires are increasing in portions of the eastern U.S.The southern and eastern regions experienced the greatest increases in large wildfire number, occurrence, size, and total hectares burnedLarge wildfire seasonality shifted across the Eastern Temperate Forests [ABSTRACT FROM AUTHOR]

Fine fuel load (FFL) is a crucial variable influencing the occurrence of wildfire. Accurate knowledge of the distribution of FFL in mountainous forests is essential for ongoing wildfire risk management and the stability of mountain ecosystems. Traditional methods of estimating forest fuel load typically involve ground surveys combined with remote sensing, which can be costly and inefficient. Therefore, low-cost, large-scale FFL estimation remains challenging. In this study, Sentinel-2A satellite imagery from the Changsha forest region was used as the data source. Firstly, different feature variables were constructed based on false-color (B843), true-color (B432), four-band (B8432) combinations, and the Normalized Difference Water Index (NDWI). Subsequently, a machine learning approach based on random convolution was employed to estimate FFL. This study also included accuracy assessments of the estimation results and the creation of FFL maps for the study area. The results showed that the FFL estimation based on the B8432 band combination achieved the highest accuracy, with RMSE and R2 values of 5.847 t·hm−2 and 0.656, respectively. FFL estimation results based on false-color imagery followed, with true-color imagery and NDWI index-based estimation results exhibiting lower accuracy. This study offers critical FFL insights using random convolution techniques applied to Sentinel-2A imagery, enhancing the ability to monitor and manage forest fuel conditions effectively, thereby facilitating more informed regional wildfire risk management strategies. [ABSTRACT FROM AUTHOR]

The increasing frequency of wildfires has posed significant challenges to communities worldwide. The effectiveness of all aspects of disaster management depends on a credible estimation of the prevailing risk. Risk, the product of a hazard's likelihood and its potential consequences, encompasses the probability of hazard occurrence, the exposure of assets to these hazards, existing vulnerabilities that amplify the consequences, and the capacity to manage, mitigate, and recover from their consequences. This paper employs the multiple criteria decision-making (MCDM) framework, which produces reliable results and allows for the customization of the relative importance of factors based on expert opinions. Utilizing the AROMAN algorithm, the study ranks counties in the state of Arizona according to their wildfire risk, drawing upon 25 factors categorized into expected annual loss, community resilience, and social vulnerability. A sensitivity analysis demonstrates the stability of the results when model parameters are altered, reinforcing the robustness of this approach in disaster risk assessment. While the paper primarily focuses on enhancing the safety of human communities in the context of wildfires, it highlights the versatility of the methodology, which can be applied to other natural hazards and accommodate more subjective risk and safety assessments. [ABSTRACT FROM AUTHOR]

Wildfire is one of the natural hazards that poses threats to the safety of forest ecological environment. It is very important to predict wildfire risk in the early stage. Most of the wildfire prediction research based on deep learning networks only extracts features on the spatial dimension. In this work, a deep learning model hybridizing 3D CNN and ConvLSTM (Convolutional Long short Term Memory) was proposed, where the strategies of multisource spatiotemporal cooperative feature fusion are adopted. Some redundant wildfire factors with high correlations by multiple collinear analysis and weight analysis were eliminated. Different from other methods, the daily weather forecast was used as the input of the study region, shortening the time prediction resolution from annual or quarterly to daily to achieve a more accurate prediction in time. Taking the daily ignition in Yunnan Province, China, as the research object, the experimental results showed that the proposed model performs well on the test dataset (AUC = 0.901 and accuracy = 0.912). Seven mainstream machine learning methods were employed for comparison with the proposed model. Ablation and comparison experiments show that the proposed model is a valid alternative tool for wildfire susceptibility prediction. [ABSTRACT FROM AUTHOR]

Wildfires, a recurring and persistent natural disaster, present direct threats to both ecological balance and human safety. Despite the northeastern region of China boasting abundant forest resources, it grapples with a significant wildfire issue. This study, focused on China's northeastern region, employs sophisticated methodologies, including the Mann–Kendall (MK) mutation test, sliding t-test, and geographical heat maps, to unveil the spatial distribution and temporal trends of wildfires. Furthermore, a random forest model is utilized to develop a wildfire susceptibility map, enabling an in-depth analysis of the relationships between various potential factors and wildfires, along with an assessment of the significance of these driving factors. The research findings indicate that wildfires in the northeastern region exhibit distinct seasonality, with the highest occurrences in the autumn and spring and fewer incidents in the summer and winter. Apart from the spring season, historical wildfires show a decreasing trend during other seasons. Geographically, wildfires tend to cluster, with over half of the high-risk areas concentrated at the junction of the Greater Khingan Mountains and Lesser Khingan Mountains in the northeastern region. The random forest model assumes a pivotal role in the analysis, accurately identifying both natural and human-induced factors, including topography, climate, vegetation, and anthropogenic elements. This research further discloses that climate factors predominantly influence wildfires in the northeastern region, with sunshine duration being the most influential factor. In summary, this study highlights the variation in various wildfire-driving factors, providing the basis for tailored management strategies and region-specific fire prevention. Through a comprehensive analysis of the spatiotemporal patterns of wildfires and associated risk factors, this research offers valuable insights for mitigating wildfire risks and preserving the region's ecological integrity. [ABSTRACT FROM AUTHOR]

Wildfire occurrences have increased and are projected to continue increasing globally. Strategic, evidence-based planning with diverse stakeholders, making use of diverse ecological and social data, is crucial for confronting and mitigating the associated risks. Prescribed fire, when planned and executed carefully, is a key management tool in this effort. Assessing where prescribed fire can be a particularly effective forest management tool can help prioritize efforts, reduce wildfire risk, and support fire-resilient lands and communities. We collaborated with expert stakeholders to develop a Bayesian network model that integrated a large variety of biophysical, socioecological, and socioeconomic spatial information for the Southeastern United States to quantify where risk is high and where prescribed fire would be efficient in mitigating risk. The model first estimated wildfire risk based on landscape-scale interactions among the likelihoods of fire occurrence and severity and the people and resources potentially exposed—accounting for socioeconomic vulnerabilities as well as key ecosystem services. The model then quantified the potential for risk reduction through prescribed fire, given the existing fuel load, climate, and other landscape conditions. The resulting expected risk estimates show high risk concentrated in the coastal plain and interior highland subregions of the Southern US, but there was considerable variation among risks to different ecosystem services and populations, including potential exposure to smoke emissions. The capacity to reduce risk through fuel reductions was spatially correlated with risk; where these diverged, the difference was largely explained by fuel load. We suggest that both risk and the capacity for risk reduction are important in identifying priorities for management interventions. The model serves as a decision support tool for stakeholders to coordinate large-landscape adaptive management initiatives in the Southern US. The model is flexible with regard to both empirical and expert-driven parameterizations and can be updated as new knowledge and data emerge. The resulting spatial information can help connect active management options to forest management goals and make management more efficient through targeted investments in priority landscapes. [ABSTRACT FROM AUTHOR]

Over the last few years, new land use planning instruments to reduce the negative consequences of recent land use/cover changes (farmland abandonment, wildfires) have been proposed in Galicia (northwest Spain). Understanding the complex relationship between biophysical constraints, socioeconomic drivers and land use/cover changes is paramount for their successful implementation. In this work, we present an analysis of recent (2005–2017) land use/cover changes in the region, along with a classification of municipalities in homogeneous groups with different patterns of land use and land use change. We then characterize those groups regarding the demographic and employment structure, the economic performance, the characteristics of the primary sector, the land ownership structure and the relative importance of recent wildfire events and the biophysical suitability for the main productions of the primary sector in the region. The results allowed us to identify four different groups of municipalities which are clearly separated by specific patterns of land use (an area where most of the population lives, an area devoted to forest production, another for farming production and a final one dominated by semi-natural covers). These four areas followed a gradient of decreasing levels of population density and economic activity. While land use patterns in different areas could be explained largely by biophysical suitability, the fragmentation of land ownership emerged as a relevant factor, which can explain the greater presence of farmland abandonment—and, therefore, higher wildfire risk—in certain areas. These results offer relevant guidelines for the successful implementation of the new land use planning instruments in the region.

In recent decades, wildfires have become common disasters that threaten people’s lives and assets, particularly in wildland–urban interfaces (WUIs). Developing an effective evacuation strategy for a WUI presents challenges to emergency planners because of the spatial variations in biophysical hazards and social vulnerability. The aim of this study was to map priority WUIs in terms of evacuation. The factors considered were the seriousness of the risk of wildfire exposure, and the population centres whose greatest constraints on the evacuation process stemmed from the nature of the exposed population and the time required to travel to the nearest shelter/refuge. An integrated framework linking wildfire hazard, social vulnerability, and the time taken to travel by foot or by car to the nearest refuge/shelter was applied. The study area includes two municipalities (Lousã and Sertã) in the mountainous areas of central Portugal that are in high-wildfire-risk areas and have very vulnerable and scattered pockets of exposed population. The combination of wildfire risk and travelling time to the nearest shelters made it possible to identify 20% of the WUIs that were priority areas for evacuation in the case of Sertã. In the case of Lousã, 3.4% were identified, because they were highly exposed to wildfire risk and had a travelling time to the nearest shelter of more than 15 min on foot. These results can assist in designing effective pre-fire planning, based on fuel management strategies and/or managing an effective and safe evacuation.

Aim: to understand how wildfire risk policies are designed to mitigate11 The goal of the analysis here is not to promote wildfire exclusion, but to reduce the likelihood of fire ignition and manage the growth and intensity of wildfire events. the impacts of wildfires. Wildfires are a growing threat in many parts of the world, posing significant risks to human life, and the environment. In recent years, wildfires have increased, driven largely by climate change, human activity, and changes in land-use patterns. Wildfire risk adaptation and mitigation measures vary widely between countries and regions around the world. Therefore, it is essential to develop a comprehensive policy approach to mitigate wildfire risks and promote sustainable forest and land management practices. This article aims to provide insight into wildfire policies, implementation actions, and their effectiveness by describing wildfire policies centered mainly on exclusion and wildfire risk mitigation. Methodology: the article examines existing wildfire-related policies and relevant literature based on 10 systematic factors. Further exploring how these policies can be enhanced to meet the challenges of the coming years for six European countries (Cyprus, France, Greece, Italy, Portugal, UK) as well as Australia, Canada, USA, and South Africa. Results: The status quo, perceived strengths, weaknesses, and recommendations from key-informants were presented to enhance wildfire policies in each country. Conclusions: The article analyses current wildfire policies in fire-prone countries, highlighting regional variations and the need for an integrated management strategy. It offers country-specific recommendations based on the participants viewpoints, for coordinated efforts to mitigate wildfire risks and promote sustainable forest management.

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.)

The increasing incidence of wildfires in the Mediterranean region has raised significant scientific and environmental concerns. This study focuses on a retrospective analysis of wildfire ignition and propagation within the context of the Monte Catillo Natural Reserve in Italy. After conducting a comprehensive review of the current state-of-the-art wildfire susceptibility mapping, propagation modeling, probability assessment, forest vulnerability models, and preventive silvicultural measures, we examine the regulatory framework surrounding wildfires in the national context, with a specific focus on prevention, prediction, and active firefighting measures. A geostatistical model of wildfire occurrence was developed, starting with the characterization of the area vegetation and anthropogenic factors influencing wildfire ignition. After that, wildfire observations from the period between 2010 and 2021 were included. The objective is to generate a wildfire hazard map for two distinct vegetation communities. To accomplish this, a statistical analysis was applied using the Poisson Model, assessing its goodness-of-fit by comparing observed frequencies with experimental data through the chi-square test. In conclusion, this model serves as a valuable tool for characterizing wildfire hazards, including ignition probabilities and propagation scenarios, within the Monte Catillo Natural Reserve. The research significantly contributes to enhancing our understanding of wildfire dynamics and plays a crucial role in the development of effective strategies for wildfire risk management. [ABSTRACT FROM AUTHOR]

Wildfire risk is greatest during high winds after sustained periods of dry and hot conditions. This paper is a statistical extreme-event risk attribution study that aims to answer whether extreme wildfire seasons are more likely now than under past climate. This requires modeling temporal dependence at extreme levels. We propose the use of transformed-linear time series models, which are constructed similarly to traditional autoregressive–moving-average (ARMA) models while having a dependence structure that is tied to a widely used framework for extremes (regular variation). We fit the models to the extreme values of the seasonally adjusted fire weather index (FWI) time series to capture the dependence in the upper tail for past and present climate. We simulate 10 000 fire seasons from each fitted model and compare the proportion of simulated high-risk fire seasons to quantify the increase in risk. Our method suggests that the risk of experiencing an extreme wildfire season in Grand Lake, Colorado, under current climate has increased dramatically relative to the risk under the climate of the mid-twentieth century. Our method also finds some evidence of increased risk of extreme wildfire seasons in Quincy, California, but large uncertainties do not allow us to reject a null hypothesis of no change. [ABSTRACT FROM AUTHOR]

The stochastic nature of environmental factors that govern the behavior of fire, such as wind and fuel, exposes wildfire modeling to a degree of uncertainty. In order to produce more realistic wildfire predictions, it is, therefore, necessary to incorporate these uncertainties within wildfire models in a way that reflects the influence of environmental stochasticity on wildfire propagation. Otherwise, the risks of the potential danger of a given wildfire may be under-represented. Specifically, environmental stochasticity in the form of wind variability results in considerable uncertainty in the output of fire spread models. Here, we consider two stochastic wind models and their implementation in the spark fire simulator framework to capture the environmental uncertainty related to wind variability. The results are compared with the output from purely deterministic wildfire spread models and are discussed in the context of the potential ramifications for wildfire risk management. [ABSTRACT FROM AUTHOR]

Background: Wildfires can have detrimental impacts on the environment and urban structures when they spread from wildland areas. Aims: In this work, a numerical study was performed to investigate the effect of downslope terrain on fire-induced flows in the presence of a building structure. Fires with intensities of 4 and 15 MW m−1 were considered on inclined terrain with downslope angles varying from 0° to −30°, and wind speeds of 6 and 12 m s−1. Methods: Simulations were conducted using a large eddy simulation (LES) solver, implemented in the open-source platform FireFOAM. Key results: The results were validated with experimental measurements of a full-scale building model. Results show that at a wind velocity of 12 m s−1, structures on steeper downslope terrains are at higher risk of wildfire damage, whereas at a constant wind velocity of 6 m s−1, these structures are at a lower risk. Conclusions: The outcomes of the study highlight the physical effect of sloped terrain on buildings downwind of a line fire. Implications: The results from this study can be used to evaluate the validity of risk management measures including building standards and asset protection zones and can better inform ways of improving these measures. Numerical simulations were used to investigate the impacts of wind, fire intensity and downslope inclination interactions on the heat exposure of an idealised building structure. At higher wind speeds, buildings on steeper downslopes were at higher risk of wildfire impacts. These results are at odds with current Australian building standards. [ABSTRACT FROM AUTHOR]

Accurate fuel mapping is crucial for effectively determining wildfire risk and implementing management strategies. The primary challenge in fuel type mapping lies in the need to develop accurate and efficient methods for identifying and categorizing the various combustible materials present in an area, often on a large scale. In response to this need, this paper presents a comprehensive approach that combines remote sensing data and Convolutional Neural Network (CNN) to discriminate between fire behavior fuel models. In particular, a CNN-based classification approach that leverages Sentinel-2 imagery is exploited to accurately classify fuel types into seven preliminary main classes (broadleaf, conifers, shrubs, grass, bare soil, urban areas, and water bodies). To further refine the fuel mapping results, subclasses were generated from the seven principles by using biomass and bioclimatic maps. These additional maps provide complementary information about vegetation density and climatic conditions, respectively. By incorporating this information, we align our fuel type classification with the widely used Standard Scott and Burgan (2005) fuel classification system. The results are highly promising, showcasing excellent CNN training performance with all three metrics—accuracy, recall, and F1 score—achieving an impressive 0.99%. Notably, the network exhibits exceptional accuracy in a test case conducted in the southern region of Sardinia, successfully identifying Burnable classes in previously unseen pixels: broadleaf at 0.99%, conifer at 0.79%, shrub at 0.76%, and grass at 0.84%. The proposed approach presents a valuable tool for enhancing fire management, contributing to more effective wildfire prevention and mitigation efforts. Thus, this tool could be leveraged by fire management agencies, policymakers, and researchers to improve the determination of wildfire risk and management. [ABSTRACT FROM AUTHOR]

In 2020 Oregon suffered one of the worst wildfire seasons on record that included a higher percentage of burned forest area, the destruction of residential areas, and significant risk to human health. The level of wildfire intensity was largely attributed as an effect of climate change, and future Oregon wildfire seasons are predicted to grow in intensity, acreage burned, and total duration. Public policy can be a tool to help to mitigate the effects of climate change, but successful policy implementation relies on public support. Therefore, this study sought to explore two factors that may influence support for climate change policy: risk experience and personal values. Oregon residents' perceptions of and experiences during the 2020 Oregon wildfire season were assessed. Results indicated the value of universalism had a significant and substantial association with support for climate change policy, and power, achievement, stimulation, selfdirection, and benevolence had significant low associations. Participants' risk experience with wildfires accounted for little total variance in regard to support for climate change policy. [ABSTRACT FROM AUTHOR]

A warmer and drier future combined with rising population trends will result in increased wildfire risk. The design of robust mitigation/adaptation strategies requires the assessment of the economy‐wide risks from potentially more frequent large wildfire events under different futures. This study uses a novel interdisciplinary approach by integrating wildfire climate and land‐use forecasts into probabilistic and simulation models of wildfires to estimate direct impacts using damage curves and indirect impacts as lost Gross Domestic Product (GDP) using a computable general equilibrium model. Based on the financial concept of Value at Risk, a probabilistic measure of extreme economy‐wide impacts was developed using GDP as the representative metric, namely "GDP at Risk (G@R)," under various climatic and socio‐economic scenarios. Using the new metric in the Waikato, New Zealand as a case study, due its primary industries' national relevance, it was identified that there is a 5% probability that the region will experience GDP losses greater or equal to NZ$0.1–1.2 billion (similar to the regional GDP growth in 2021) over a 48‐year period from future potential large wildfires affecting vulnerable primary industries. The regional impacts result in larger national GDP losses by a factor of 5 due to the high dependence of downstream sectors on the regional primary industries. While "G@R" estimates are similar across socio‐economic scenarios, there are no discernible patterns when compared across midcentury climate scenarios. The approach developed could be used to assess the consequences from afforestation projects, driven by mitigation policies, and adaptation strategies to reduce wildfire risk. Plain Language Summary: The risk posed by wildfires will increase under a warmer and drier future. Previous studies have estimated the economic risk from wildfires on the sectors that would likely be physically and directly impacted. However, to design inclusive and enduring strategies to reduce or adapt to wildfires; the potential impacts from wildfires should be assessed for entire national economic networks under many different social and climatic scenarios—including sectors that demand products from, or supply to, the ones directly affected. This study uses an interdisciplinary approach by combining computational models to estimate the potential economic impacts from wildfires on multiple sectors of the economy under various relevant scenarios. Rather than focusing on expected impacts, this study focuses on the potentially large impacts from rare, large wildfires on the Waikato region—economically important to New Zealand. The economic impacts from potentially more frequent large wildfires in the region are modest when compared to a scenario without large wildfires. However, the nationwide impacts are substantially larger than the regional ones when considering the dependent sectors outside of the affected region. The approach developed could be used to jointly assess mitigation (e.g., afforestation) and adaptation policies to reduce the risk from wildfires. Key Points: There is a 5% chance that the studied region will lose 0.008%–0.06% or more of the base Gross Domestic Product (GDP) from potentially more frequent large wildfiresThe regional impacts result in larger national GDP losses by a factor of 5 when considering the downstream sectors outside of the regionWhile the GDP loss estimates are similar across socio‐economic scenarios, there are no discernible patterns across climate scenarios [ABSTRACT FROM AUTHOR]

Anyone who has tried lighting a campfire on a windy day can appreciate how difficult it could be. However, despite real-life experience and despite laboratory experiments which have demonstrated that fire ignition risk dramatically decreases beyond a certain wind threshold, current fire weather indices (FWIs) do not take this effect into account and assume a monotonic relation between wind velocity and ignition risk. In this paper, we perform a global analysis which empirically quantifies the probability of ignition as a function of wind velocity. Using both traditional methods (a logistic regression and a generalized additive model) and machine learning techniques, we find that beyond a threshold of approximately 3–4 m/s, the ignition risk substantially decreases. The effect holds when accounting for additional factors such as temperature and relative humidity. We recommend updating FWIs to account for this issue. [ABSTRACT FROM AUTHOR]

The growing scale of natural hazards highlights the need for models of governance capable of addressing risk across administrative boundaries. However, risk governance systems are often fragmented, decentralized, and sustained by informal linkages among local-level risk mitigation planning processes. Improving resilience to the effects of environmental change requires a better understanding of factors that contribute to these linkages. Using data on the patterns of participation of 10,199 individual stakeholders in 837 community wildfire protection plans (CWPPs) within the western U.S., we document the emergence of a locally clustered but spatially extensive wildfire risk governance network. Our evaluation of factors that contribute to connectivity within this network indicates that risk interdependence (e.g., joint exposure to the same fires) between planning jurisdictions increases the prospects for linkages between planning processes, and that connectivity is also more likely among planning processes that are more proximate and similar to one another. We discuss how our results advance understanding of how changing hazard conditions prompt risk mitigation policy networks to reorganize, which in turn affects risk outcomes at multiple spatial scales. [ABSTRACT FROM AUTHOR]

As wildfire risk is projected to increase across most of the world, exposure to wildfire smoke is a growing global health issue. Clean air centers (CACs), public buildings designated to provide improved air quality to the public during a wildfire smoke event, have emerged as a community-oriented public health response to smoke. Some experts see CACs as the most effective way to reduce population exposure to wildfire smoke. Yet how and why smoke-vulnerable groups utilize CACs, as well as how CACs may be improved to meet their needs, is not well understood. Here, we explore these questions through exploratory interviews with two groups of stakeholders in California CAC development: practitioners and members of a community vulnerable to wildfire smoke. Our findings suggest that a gap remains between California's CACs and the needs of vulnerable groups. By comparing community and practitioner perspectives, we identify opportunities to close this gap. [ABSTRACT FROM AUTHOR]

As wildfires increase in both severity and frequency, understanding the role of risk saliency on human behaviors in the face of fire risks becomes paramount. While research has shown that homebuyers capitalize wildfire risk following a fire, studies of the role that risk saliency plays on residential development is limited. This paper aims to fill this gap by studying the link between wildfire risk saliency and the rate of residential development in wildfire‐prone areas, by treating recent wildfires as conditionally exogenous shocks to saliency. Using geospatial data on residential development in Colorado, we show that saliency shocks due to wildfire lead to statistically significant reductions in the rate of new development in wildfire risk zones that last upwards of 5 years, a result that is robust to a number of alternative explanations. We explore the policy implications of these findings, noting that education on fire risks may curtail some but not all of the development in these high wildfire‐risk areas due to the rapid growth of development in these regions. [ABSTRACT FROM AUTHOR]

Drawing on decolonial thought, this article provides a perspective on local indigenous knowledge and governance systems as a resource for informing wildfire risk policy approaches and collaborative environmental security. In 2019, the Indigenous Territory of Lomerío in Bolivia was heavily affected by wildfires, due to a combination of fires that penetrated the territory from outside and others that spread from inside. As result, the Bolivian Forest Management Agency (ABT) started threatening indigenous people with criminal action for using fire in their livelihood practices. In response, in 2020 and with the support of several institutions, the Union of Indigenous Communities of Lomerío (CICOL) initiated a series of activities to ensure local control of wildfire risk management in the territory. These include a written burning protocol, a fire monitoring programme, water basin and forest conservation policies, participatory research conducted by indigenous researchers about the use of fire in Lomerío and cultural revitalization strategies. The article presents the results of these different strategies and their contributions to creating awareness of appropriate regulations for wildfire risk management by national authorities from the perspective of the Monkoxɨ indigenous people. • Wildfire risk management is a central part of the Monkoxi self-determination agenda. • The Monkoxi are combining traditional and modern knowledge and techniques to manage wildfire risk in their territories. • Multiple causes of wildfire in Lomerio require multiple wildfire management strategies. • Indigenous governance has been key in coordinating actions with external actors to introduce wildfire management innovations. [ABSTRACT FROM AUTHOR]

Context: The wildland-urban interface (WUI) is an area where houses are located near wildland vegetation. As such, the WUI is a focal area of wildfire risk, human-wildlife conflicts, and other human-nature interactions. Although there is a wide consensus on the impact WUI existence might have, little is known about the WUI spatial determinants over long periods, especially in countries with long settlement history. Objectives: Our goal here was to map the WUI across Poland, and to quantify the extent to which historical legacies shape current WUI pattern, since Poland is one of the countries, which experienced substantial political changes over time, which had an impact on historical settlement development. Methods: We analysed a database of nearly 15 million building locations and a 10-m Sentinel-2-based land cover map to produce a country-wide WUI map of Poland. Then we compared the WUI pattern among parts of Poland which belonged to different political entities in 1900s and 1930s and also among different ecoregions. Lastly, we verified the effects of the historical borders or landscape units borders on WUI patterns with a discontinuity analysis. Results: We found that a substantial part of Poland is WUI, and over 60% of all buildings are in WUI. However, WUI patterns differ considerably across the country, and WUI hotspots are located around the largest metropolitan areas in central and southern part of Poland and in the Carpathians. Furthermore, WUI patterns reflect pre-1945 national borders indicating long-term legacies of past settlement patterns and urban planning approaches. Diversity among ecoregions was much less pronounced than among past political entities. Conclusions: Our work shows that current WUI pattern is to large extent shaped by former political conditions, which is likely true not only in Poland, but also in many parts of Europe and elsewhere where settlement history goes back centuries. [ABSTRACT FROM AUTHOR]

The fire season of 2023 was record-breaking in Canada given the number, severity, and intensity of wildfires. Factors contributing to the number of fires are likely to get worse in the future because of the interaction and complexity of many factors such as climate change and the legacy of decades of successful wildfire suppression. Further complicating wildfire management is the ever-continuing expansion of the wildland-urban interface and subsequent increases in values at risk. Fire management solutions including prevention and suppression will require novel approaches given rising costs and logistical complications. This paper examines the payment concept for ecosystem services whereby ranchers are paid to graze cattle in targeted high-priority areas in the wildland urban interface. Grazing can be ecologically appropriate and has long been used in fire-prone ecosystems in Europe. With some key considerations, implementing PES (Payments for Ecosystem Services) could reduce fire risk, support agricultural producers, and enhance societal protection. [ABSTRACT FROM AUTHOR]

Wildfire Risk Forecast (WRF) remains a regular procedure conducted by the National Centre for Forecast and Monitoring of Natural Hazards (NCFMNH), which is part of the Institute of GeoSciences of Albania (IGEO). WRF is generated daily by the country's administrative unit (prefecture) and disseminated to the National Civil Protection Agency (NCPA) in order to help the fire-fighting activities better coordinate in case of Fires caused or promoted by natural factors. The main purpose of this scientific work was to conduct a survey on forecast alerts and fire events during summer seasons in a period of 5 years (2017-2021). Analyses on Forecast Alert (FA), Prefecture Hit Probability (PHP) and Average Fires per Hit (AFH) were conducted on Risk-Level-bases in order to have a complete view of the topic of the study. Besides, the study put the findings on a Hazard Index Map (HIM) where Fire Risk on Prefecture basis was revealed. The calculations were made using the results of FA, PHP and AFH components in the High-Risk Level (FAHigh, PHPHigh, AFHHigh) comprising wildfire Hazard Exposure Index (HI) for the first component and wildfire Vulnerability Index (VI) for the second and third component (VI-SA and VI-SB). The methodological approach was inspired by the one used to evaluate the risk in WorldRiskReport (WRR), but due to several restrictions in this study, components for the evaluation of risk were used. The final Hazard Index Map reveals the highest risk localised in Fier Prefecture, followed by Elbasan, Vlore and Diber Prefectures. [ABSTRACT FROM AUTHOR]

Wildfires are a common phenomenon in Mediterranean environments. This study seeks to synthesize the main results of existing studies from the last decade on this topic and to highlight the need for managing soil impacted by wildfires in the Mediterranean environment. Researchers have found that the impact of fire during a forest fire on the soil, and the subsequent consequences on soil ecosystem services and functions, is great and produces negative consequences for the soil. The physical, chemical, and biological properties of soil have been extensively analyzed, and a very high number of studies during the last ten years have been performed on different study areas with a common component: the Mediterranean ecosystem. However, the effects of these fires on the multifunctionality of the soil itself, ecosystem services, and soil functionality, which they provide to humans, have not. It is therefore essential to know the impact of fires in a fire-prone ecosystem such as the Mediterranean one on the soil and how these services and functions are affected. In this way, the decision can be taken to carry out restoration measures, especially after very severe forest fires and if the recurrence is high. This conclusion is even more important in the context of global change in which more severe and recurrent fires are expected, and therefore actions to be considered are expected to be more necessary to avoid land degradation, as many of the studies compiled here have shown.

The growing threats posed by wildfires in Southern Europe are calling for the development of comprehensive and sound management and risk assessment strategies. In this work, we present the application of wildfire simulation modeling based on the minimum travel time (MTT) algorithm to assess fine-scale (100-m resolution) wildfire hazard, transmission, and exposure to communities in the Italy-France Maritime cooperation area (Sardinia, Corsica, Tuscany, Liguria and Provence-Alpes-Côte d’Azur), which cover about 72,000 km2 of land. We simulated thousands of wildfires considering the current landscape and characterized and measured fine-scale wildfire risk factors and profiles by taking into account historical fire regimes, fuels, winds and fuel moisture conditions associated with the occurrence of the largest wildfires (>100 ha) that affected the study area in the last 20 years. Individual fires were simulated at 100-m resolution, consistent with the input files. Modeled annual burn probability and ignition probability revealed that Sardinia was the Region most affected by wildfires. The wildfire simulation outputs were then combined with main land uses and building footprint locations to characterize wildfire transmission and exposure to communities, and were summarized for main vegetation types and Regions. This study presents a cross-boundary and standardized approach based on wildfire spread modeling to analyze and quantify wildfire risk profiles in Southern Europe. The stochastic wildfire modeling systems we implemented used harmonized sets of data for a vast, fire-prone Mediterranean area, where previous similar studies were conducted at coarser resolutions and covered lower extent of lands. The approach presented in this work can be used as a reference pillar for the development and implementation of a common wildfire risk monitoring, management, and governance plan in the study area. The methods and findings of this study can be replicated in neighboring Mediterranean and other regions threatened by wildfires.