Lightning-caused Fires Research Articles

Multivariate spatial regressions help explain wildfire hot spot intensities in Washington, USA

Wildfires have become increasingly prevalent in the western United States, posing threats to human communities and the built environment. This study builds upon previous research by investigating the factors influencing wildfire hot spot distribution in Washington State. Using spatial regression models (generalized linear regression and geographically weighted regression), we examine the relationships between wildfire hot spots and various geographic features, including climate variables, human-caused ignitions, land use, population density, road density, and the wildland-urban interface. Our results indicate that lightning-caused fires and road density are significant factors contributing to hot spot intensity in central Washington, while human-caused ignitions play a crucial role in eastern Washington. Surprisingly, precipitation shows varied correlations with hot spots, with some areas experiencing an unexpected positive relationship between precipitation and hot spot intensity due to increased fuel growth. The study highlights the importance of localized approaches to wildfire mitigation, emphasizing the need for tailored risk reduction strategies based on regional factors.

Consequential lightning-caused wildfires and the “let burn” narrative

BackgroundCurrent guidance for implementation of United States federal wildland fire policy charges agencies with restoring and maintaining fire-adapted ecosystems while limiting the extent of wildfires that threaten life and property, weighed against the risks posed to firefighters. These ostensibly conflicting goals can make it difficult to clearly communicate specific response objectives of a given incident. Inherent ambiguity can expose land management agencies, like the United States Department of Agriculture Forest Service (USFS), to scrutiny when once remote, lightning-ignited wildfires burn across boundaries and result in damage. One such incident was the 2021 Tamarack Fire, ignited by lightning in a remote USFS wilderness area and ultimately burning 27,776 ha across multiple jurisdictions and destroying 25 structures. Intense sociopolitical interest developed around this incident, reigniting a “let burn” policy debate of the USFS despite this policy not formally existing. We provide a first approximation at quantifying the base rates of potentially consequently lightning-caused fires like the Tamarack Fire. We use multiple sources of fire-reporting data to characterize USFS fires from 2009 to 2020 by management-strategy to identify Tamarack Fire analogs. Within Incident Command System 209 (ICS-209) reports for fires originating on USFS lands, we identified 32 wildfires with similar key characteristics to the Tamarack Fire; nearly half ignited within wilderness areas.ResultsInitial strategies were driven by resource objectives for only six of the 32 wildfires; firefighter hazard mitigation was the primary driver of all others. No fire exhibited every characteristic of the Tamarack Fire. Analog fires accounted for a small percent (3.4%) of large (> 121 ha) USFS lightning-caused ignitions. These fires were responsible for 61.6% of structures destroyed and 25.8% of total personnel commitments of large lightning-caused USFS fires.ConclusionsLightning-ignited wildfires that could have resulted in sociopolitical controversy are rare, and those with strategies driven by resource objective are even rarer. More commonly, risks posed to firefighters from terrain, snags, or accessibility are factors driving strategy, even when fires ignite within wilderness areas. These results suggest that simple definitions of strategy such as those reported within the ICS-209 lack clarity and may increase sociopolitical pressure on the agency to continue aggressive fire exclusion strategies.

Simulation Study of an Abstract Forest Ecosystem with Multi-Species under Lightning-Caused Fires

There is a complex interaction between lightning-caused fire behavior and the flora and fauna of the forest, which involves the influence of a large number of ecological factors. However, more comprehensive simulation studies under multi-system interactions between lightning ignition, forest fire spread, and animal behavior are not well developed. In this paper, we propose a forest ecosystem model based on the Agent-based modelling approach to explore the detailed linkages between different forms of lightning-caused fires and forest biodiversity. The model simulates the lightning ignition, fire spread, vegetation burning and recovery, and multi-species-survival dynamics. The experimental results show the sensitivity between environmental parameters and the magnitude of lightning-caused fires, and the beneficial ecological consequences of lightning-caused fires on forest ecosystems. By exploring detailed linkages between different forms of lightning-caused fires and forest biodiversity, we provide theoretical insights and reference suggestions for forest system governance and biodiversity conservation.

Forest Fire Patterns and Lightning-Caused Forest Fire Detection in Heilongjiang Province of China Using Satellite Data

Large forest fires can cause significant damage to forest ecosystems and threaten human life and property. Heilongjiang Province is a major forested area in China with the highest number and concentration of lightning-caused forest fires in the country. This study examined the spatial and temporal distribution patterns of forest fires in Heilongjiang Province, as well as the ability of satellite remote sensing to detect these fires using VIIRS 375 m fire point data, ground history forest fire point data, and land cover dataset. The study also investigated the occurrence patterns of lightning-caused forest fires and the factors affecting satellite identification of these fires through case studies. Results show that April has the highest annual number of forest fires, with 77.6% of forest fires being caused by lightning. However, less than 30% of forest fires can be effectively detected by satellites, and lightning-caused forest fires account for less than 15% of all fires. There is a significant negative correlation between the two. Lightning-caused forest fires are concentrated in the Daxing’an Mountains between May and July, and are difficult to monitor by satellites due to cloud cover and lack of satellite transit. Overall, the trend observed in the number of forest fire pixels that are monitored by satellite remote sensing systems is generally indicative of the trends in the actual number of forest fires. However, lightning-caused forest fires are the primary cause of forest fires in Heilongjiang Province, and satellite remote sensing is relatively weak in monitoring these fires due to weather conditions and the timing of satellite transit.

Assessing dependence between frequency and severity through shared random effects.

Research on the occurrence and the final size of wildland fires typically models these two events as two separate processes. In this work, we develop and apply a compound process framework for jointly modelling the frequency and the severity of wildland fires. Separate modelling structures for the frequency and the size of fires are linked through a shared random effect. This allows us to fit an appropriate model for frequency and an appropriate model for size of fires while still having a method to estimate the direction and strength of the relationship (e.g., whether days with more fires are associated with days with large fires). The joint estimation of this random effect shares information between the models without assuming a causal structure. We explore spatial and temporal autocorrelation of the random effects to identify additional variation not explained by the inclusion of weather related covariates. The dependence between frequency and size of lightning-caused fires is found to be negative, indicating that an increase in the number of expected fires is associated with a decrease in the expected size of those fires, possibly due to the rainy conditions necessary for an increase in lightning. Person-caused fires were found to be positively dependent, possibly due to dry weather increasing human activity as well as the amount of dry few. For a test for independence, we perform a power study and find that simply checking whether zero is in the credible interval of the posterior of the linking parameter is as powerful as more complicated tests.

Human-ignited fires result in more extreme fire behavior and ecosystem impacts

California has experienced a rapid increase in burned area over the past several decades. Although fire behavior is known to be closely tied to ecosystem impacts, most analysis of changing fire regimes has focused solely on area burned. Here we present a standardized database of wildfire behavior, including daily fire rate-of-spread and fire radiative power for large, multiday wildfires in California during 2012–2018 using remotely-sensed active fire observations. We observe that human-ignited fires start at locations with lower tree cover and during periods with more extreme fire weather. These characteristics contribute to more explosive growth in the first few days following ignition for human-caused fires as compared to lightning-caused fires. The faster fire spread, in turn, yields a larger ecosystem impact, with tree mortality more than three times higher for fast-moving fires (>1 km day−1) than for slow moving fires (<0.5 km day−1). Our analysis shows how human-caused fires can amplify ecosystem impacts and highlights the importance of limiting human-caused fires during period of extreme fire weather for meeting forest conservation targets under scenarios of future change.

Future increases in lightning ignition efficiency and wildfire occurrence expected from drier fuels in boreal forest ecosystems of western North America

Lightning-induced fire is the primary disturbance agent in boreal forests. Recent large fire years have been linked to anomalously high numbers of lightning-caused fire starts, yet the mechanisms regulating the probability of lightning ignition remain uncertain and limit our ability to project future changes. Here, we investigated the influence of lightning properties, landscape characteristics, and fire weather on lightning ignition efficiency—the likelihood that a lightning strike starts a fire—in Alaska, United States of America, and Northwest Territories, Canada, between 2001 and 2018. We found that short-term fuel drying associated with fire weather was the main driver of lightning ignition efficiency. Lightning was also more likely to ignite a wildfire in denser, evergreen forest areas. Under a high greenhouse gas emissions scenario, we predicted that changes in vegetation and fire weather increase lightning ignition efficiency by 14 ± 9% in Alaska and 31 ± 28% in the Northwest Territories per 1 °C warming by end-of-century. The increases in lightning ignition efficiency, together with a projected doubling of lightning strikes, result in a 39%–65% increase in lightning-caused fire occurrence per 1 °C warming. This implies that years with many fires will occur more frequently in the future, thereby accelerating carbon losses from boreal forest ecosystems.

Lightning patterns in the Pantanal: Untangling natural and anthropogenic-induced wildfires

The identification of fire causes and characteristics is of fundamental importance to better understand fire regimes and drivers. Particularly for Brazil, there is a gap in the quantification of lightning-caused fires. Accordingly, this work is a novel probabilistic assessment of the spatial-temporal patterns of lightning-ignited wildfires in the Pantanal wetland. Here, remote sensing information such as VIIRS active fires, MODIS burned area (BA) and STARNET lightning observations from 2012 to 2017, were combined to estimate the location, number of scars and amount of BA associated with atmospheric discharges on a seasonal basis. The highest lightning activity occurs during summer (December–February), and the lowest during winter (June–August). Conversely, the highest fire activity occurred during spring (September–November) and the lowest during autumn (March–May). Our analysis revealed low evidence of an association between fires and lightning, suggesting that human-related activities are the main source of ignitions. Weak evidence of natural-caused fire occurrence is conveyed by the low spatial-temporal match of lightning and fire throughout the studied period. Natural-caused fires accounted for only 5% of the annual total scars and 83.8% of the BA was human-caused. Most of the fires with extension larger than 1000 ha were not related to lighting. Lightning-fires seem an important element of the summer fire regime given that around half of the total BA during this season may be originated by lightning. By contrast, in the rest of the year the lightning-fires represent a minor percentage of the fire activity in the region. The density of lightning-ignited fires varies considerably, being higher in the north part of the Pantanal. This work provides a basis for a better understanding of lightning-related fire outbreaks in tropical ecosystems, particularly wetlands, which is fundamental to improve region-based strategies for land management actions, ecological studies and modeling climatic and anthropogenic drivers of wildfires.

Human- and lightning-caused wildland fire ignition clusters in British Columbia, Canada

Wildland fire is a common occurrence in western Canada, with record-setting area burned recorded in British Columbia (BC) in the past decade. Here, we used the unsupervised machine learning algorithm HDBSCAN to identify high-density clusters of both human- and lightning-caused wildfire ignitions in BC using data from 2006 to 2020. We found that human-caused ignition clusters tended to occur around population centres, First Nations communities, roads and valleys, and were more common in the southern half of the province, which is more populated. Lightning-ignition clusters were generally fewer in number and larger in size than human-caused fires for most hyperparameter settings. There were significant differences (X2 = 1884.8, d.f. = 7, P-value &lt;2.2 × 10−16) in fuels associated with lightning- versus human-caused ignition clusters, with human-ignition cluster fires being more often found within leafless aspen (D1) and ponderosas pine and Douglas fir (C7) fuel types. These high-density clusters highlight regions where the greatest densities of both lightning- and human-caused fires have occurred in the province, thereby identifying regions of potential interest to wildland fire managers, researchers and various communities and industries.

Patterns of Anthropogenic Fire within the Midwestern Tallgrass Prairie 1673–1905: Evidence from Written Accounts

We conducted literature searches of records from Illinois, Indiana, Iowa, Minnesota, Missouri, North Dakota, Ohio, and Wisconsin to create a source bibliography of wildland fire descriptions occurring between 1673 and 1905. A total of 795 landscape fire records were identified within or near the eastern tallgrass prairie–forest transition region, including 32 attributed to Native Americans, 194 to Europeans from spontaneous records in the nineteenth century, and 569 to Europeans from a systematic dataset collected during the late nineteenth and early twentieth centuries in Minnesota. From these historical accounts, we find overwhelming evidence that a two- to three-week period during October and November, known then as “Indian summer,” was the primary wildland fire season. Our records indicate that Native Americans used fire primarily for hunting, whereas Euro-American fires were set to reduce fire hazards near their habitations, to eliminate crop residues, and to facilitate plowing, or they were escapes due to mere carelessness. Only five lightning-caused fires were identified. Individual fires frequently burned thousands of hectares, creating dense smoke, damaging trees, personal property, and occasionally burning inhabitants fatally. South and southwest were the most frequent wind directions during wildfires. Drought years, including 1796, 1819, 1856, and 1871, were characterized by extensive fires, which ultimately resulted in legislation to protect property owners and public welfare. Fire events for the study period are certainly underestimated by this dataset because only large, spectacular, threatening fires were recorded, especially during European settlement. In addition, our estimate of Native American fire frequency and prevalence is less than their historical/expected frequency, due to their widespread population collapse and changed hunting methods following contact and dispossession by Europeans.

Contrasting the role of human- and lightning-caused wildfires on future fire regimes on a Central Oregon landscape

Climate change is expected to increase fire activity in many regions of the globe, but the relative role of human vs. lightning-caused ignitions on future fire regimes is unclear. We developed statistical models that account for the spatiotemporal ignition patterns by cause in the eastern slopes of the Cascades in Oregon, USA. Projected changes in energy release component from a suite of climate models were used with our model to quantify changes in frequency and extent of human and lightning-caused fires and record-breaking events based on sizes of individual fires between contemporary (2006 −2015) and mid-century conditions (2031–2060). No significant change was projected for the number of human-caused fire ignitions, but we projected a 14% reduction in lightning-caused ignitions under future conditions. Mean fire sizes were 31% and 22% larger under future conditions (2031–2060) for human and lightning-caused ignitions, respectively. All but one climate model projected increased frequency of record-breaking events relative to the contemporary period, with the largest future fires being about twice the size of those of the contemporary period. This work contributes to understanding the role of lightning- and human-caused fires on future fire regimes and can help inform successful adaptation strategies in this landscape.

Fire from the Sky in the Anthropocene

Lightning-caused fires (LCFs) and fire environments influenced by thunderstorms are increasingly implicated in extreme wildfire events around the world, with devastating consequences to society and the environment. However, the disaster potential inherent to LCFs is often neglected, especially where the fire regime is determined mostly by anthropogenic ignitions. Such disconnect between perceived risk and actual risk is illustrated with the Iberian Peninsula, where thunderstorm-driven wildfires are comparatively rare but have resulted in large-scale burning and considerable loss of human life. Even low LCF regions should embrace fire management strategies able to cope with LCFs.

Human-caused fires release more carbon than lightning-caused fires in the conterminous United States

Anthropogenic carbon emissions from fires impact the global carbon budget and contribute to global warming. However, due to the lack of inventory data, little was known about how carbon emissions differed between human-caused and lightning-caused fires previously. In this study, the Fire Program Analysis fire-occurrence database (FPA FOD) and the Global Fire Emissions Database (GFED) were combined to analyze the influences of human-caused fires on carbon emissions. We found that the GFED burned area was larger than that of the FPA FOD since the FPA FOD did not cover human-caused fire usages like prescribed fires. Carbon emissions over the conterminous United States were increasing significantly from 1997 to 2015. Human-caused fires released 9.99 Tg C yr−1 over the conterminous United States, which were approximately twice those of carbon emissions from lightning-caused fires, 5.44 Tg C yr−1. Carbon emissions of lightning-caused fires were increasing while those of human-caused fires were decreasing significantly with rising temperatures. Emissions in ecoregions such as the Eastern Temperate Forests, the Great Plains, the Marine West Coast Forests, and the Northern Forests were dominated by human-caused fire emissions, whose proportions were over 86%. These results highlight the importance of human activities on carbon emissions, offering new insights into the role of humans in climate change mitigation.

Lightning-caused fires in the Alps: Identifying the igniting strokes

Lightning is the most important natural wildfire ignition source worldwide. However, identifying the specific lightning causing a forest fire is a challenging task. The goal of this study is to understand how different methodological approaches affect the association between igniting lightning and natural fires. To this purpose, we combined data on 267 lightning-caused forest fires from Switzerland with data on cloud-to-ground lightning strokes for the period 2000–2018. We searched for the most probable igniting lightning (candidate) among all lightning that occur during the days (up to two weeks) before fire detection in the vicinity (< 10 km) of the ignition point. We tested the suitability of 14 methods that combine different spatio-temporal approaches and selection criteria. Our results show that each method selected different candidate lightning for a subset of the fires, while for other fires identical candidate lightning were selected by different methods. Methods using criteria that combine simultaneously space and time, such as the index A, selected candidate lightning with short distances from the ignition points and short holdover times (i.e., the time between ignition and fire detection). On the contrary, methods that minimize the holdover time selected a great proportion of candidate lightning located at long distances. The majority of the candidate lighting were recorded within 1 km from the fire starting point and in less than 24 h before fire detection. The proportion of positive strokes was significantly higher among candidate lightning than in the rest of lightning, which supports the hypothesis that positive lightning are more likely to ignite a forest fire than negative ones. This study highlights the importance of the methodological choice when searching for the candidate igniting lightning of a wildfire.

Evaluating Lightning-Caused Fire Occurrence Using Spatial Generalized Additive Models: A Case Study in Central Spain.

It is widely accepted that the relationship between lightning wildfire occurrence and its influencing factors vary depending on the spatial scale of analysis, making the development of models at the regional scale advisable. In this study, we analyze the effects of different biophysical variables and lightning characteristics on lightning-caused forest wildfires in CastillayLeón region (Central Spain). The presence/absence of at least one lightning-caused fire in any 4×4-km grid cell was used as a dependent variable and vegetation type and structure, terrain, climate, and lightning characteristics were used as possible covariates. Five prediction methods were compared: a generalized linear model (GLM), a random forest model (RFM), a generalized additive model (GAM), a GAM that includes a spatial trend function (GAMs) and a spatial autoregressive model (AUREG). A GAMs with just one covariate, apart from longitude and latitude for each observation included as a combined effect, was considered the most appropriate model in terms of both predictive ability and simplicity. According to our results, the probability of a forest being affected by a lightning-caused fire is positively and nonlinearly associated with the percentage of coniferous woodlands in the landscape, suggesting that occurrence is more closely associated with vegetation type than with topography, climate, or lightning characteristics. The selected GAMs is intended to inform the Regional Government of Castilla y León (the fire and fuel agency in the region) regarding identification of areas at greatest risk so it can design long-term forest fuel and fire management strategies.

Seasonality and trends in human- and lightning-caused wildfires ≥ 2 ha in Canada, 1959–2018

We examined the seasonal distribution of lightning- and human-caused wildfires ≥ 2ha in Canada for two time periods: 1959–2018 and 1981–2018. Furthermore, we investigated trends in seasonality, number of fires per year and number of days with fire starts per year for human- and lightning-caused fires. Nationally, lightning fires peaked from June to August, whereas human fires peaked during May. There was, however, notable variation in the seasonal distributions of human- and lightning-caused fires between ecozones. Likewise, trends in season start and end dates varied among ecozones and time series, with trends generally being stronger for human-caused fires. Trends in the number of fires from 1959 to 2018 suggested significant increases in the number of lightning-caused fires and days with lightning ignitions across almost all ecozones, while from 1981 to 2018 there was a significantly decreasing trend in the number of human-caused fires and days with human ignitions in almost all ecozones. The highest densities of human-caused fires occurred in the Montane Cordillera and Atlantic Maritime, while the highest density of lightning-caused fires occurred in the Boreal Shield West. The Montane Cordillera and Taiga Shield West showed significant increases in the number of lightning fires and days with lightning ignitions across both time series.

Fire regime dynamics in mainland Spain. Part 1: Drivers of change

Fire regimes are evolving worldwide driven by socioeconomic and environmental changes. Understanding the forces behind fire regime dynamics is essential to achieve effective wildfire management and policymaking. The current research belongs to a series of two manuscripts aimed at describing spatial-temporal dynamics of fire regime and its drivers in mainland Spain. In this work, we identified the main transitional pathways of fire regime zones between past (1974–1994) and current (1995–2015) conditions to identify the influence of the main wildfire drivers (demographic potential, climate trends, forest interfaces and topography). Our methodology combined Principal Component Analysis and Ward's hierarchical clustering to identify and spatialize homogenous regions of fire regime on the basis of the main fire regime features: number of fires, burned area, burnt area from lightning-caused fires, area affected by large fires (>100 ha) and seasonality. This procedure was replicated in current and past conditions to extract the most frequent combinations of fire regime typologies, eventually leading to a set of binary response variables (change versus persistence of fire regime). Finally, Random Forest regression was applied to estimate the explanatory performance of fire regime drivers for each transition path.Our results point to an overall decline in fire activity over most of the Spanish territory. The hinterlands and Mediterranean coast experienced the greatest decrease in fire activity. In contrast, winter activity has progressed in the North-western region. According to Random Forest outputs, demographic potential highlights as the main driver of fire regime change (both regressive and progressive), followed by climate dynamics (temperature and rainfall trends) and topographic features. In turn, Wildland-Agricultural Interface (WAI) and Wildland-Urban Interface (WUI) were also behind several noticeable trajectories as is the case of winter fire progression (WAI) or moderate increase in fire incidence linked to human-caused fires (WUI).

Applicability of Remote Sensing-Based Vegetation Water Content in Modeling Lightning-Caused Forest Fire Occurrences

In this study, our aim was to model forest fire occurrences caused by lightning using the variable of vegetation water content over six fire-dominant forested natural subregions in Northern Alberta, Canada. We used eight-day composites of surface reflectance data at 500-m spatial resolution, along with historical lightning-caused fire occurrences during the 2005–2016 period, derived from a Moderate Resolution Imaging Spectroradiometer. First, we calculated the normalized difference water index (NDWI) as an indicator of vegetation/fuel water content over the six natural subregions of interest. Then, we generated the subregion-specific annual dynamic median NDWI during the 2005–2012 period, which was assembled into a distinct pattern every year. We plotted the historical lightning-caused fires onto the generated patterns, and used the concept of cumulative frequency to model lightning-caused fire occurrences. Then, we applied this concept to model the cumulative frequencies of lightning-caused fires using the median NDWI values in each natural subregion. By finding the best subregion-specific function (i.e., R2 values over 0.98 for each subregion), we evaluated their performance using an independent subregion-specific lightning-caused fire dataset acquired during the 2013–2016 period. Our analyses revealed strong relationships (i.e., R2 values in the range of 0.92 to 0.98) between the observed and modeled cumulative frequencies of lightning-caused fires at the natural subregion level throughout the validation years. Finally, our results demonstrate the applicability of the proposed method in modeling lightning-caused fire occurrences over forested regions.

Fire-regime changes in Canada over the last half century

Contemporary fire regimes of Canadian forests have been well documented based on forest fire records between the late 1950s to 1990s. Due to known limitations of fire datasets, an analysis of changes in fire-regime characteristics could not be easily undertaken. This paper presents fire-regime trends nationally and within two zonation systems, the homogeneous fire-regime zones and ecozones, for two time periods, 1959–2015 and 1980–2015. Nationally, trends in both area burned and number of large fires (≥200 ha) have increased significantly since 1959, which might be due to increases in lightning-caused fires. Human-caused fires, in contrast, have shown a decline. Results suggest that large fires have been getting larger over the last 57 years and that the fire season has been starting approximately one week earlier and ending one week later. At the regional level, trends in fire regimes are variable across the country, with fewer significant trends. Area burned, number of large fires, and lightning-caused fires are increasing in most of western Canada, whereas human-caused fires are either stable or declining throughout the country. Overall, Canadian forests appear to have been engaged in a trajectory towards more active fire regimes over the last half century.

A quantitative comparison of forest fires in central and northern California under early (1911–1924) and contemporary (2002–2015) fire suppression

Most studies of fire-regime changes in western North American forests rely on a reference period that pre-dates Euro-American settlement. Less is known about fire-regime changes relative to the early onset of major change agents, i.e. fire suppression and timber harvesting. We digitised ledgers that contained over 18000 individual fire records from 1911 through 1924 (early suppression period). We performed analyses comparing a subset of these fire records, largely in mixed-conifer forests, to similar records from 2002 through 2015 (contemporary period). Mapped ignition frequencies indicated similar geographic patterns for lightning-caused fires between periods, but notable shifts in certain areas for human-caused fires. There was no statistical difference in annual number of human-caused fires between the early suppression and contemporary time periods. However, there was a major shift in the distribution of burned area across fire size classes. Fires &amp;gt;12145ha accounted for 0–6% of total burned area in the early suppression period, and 53–73% in the contemporary period. Also, both the total number and percentage of fires &amp;gt;2024ha occurred significantly earlier in the year in the contemporary period. These shifts are likely driven by large-scale changes in fuel loads and continuity, and possibly exacerbated by climatic warming.