Drivers Of Wildfires Research Articles

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.

Forest fire and its key drivers in the tropical forests of northern Vietnam

Fire increasingly threatens tropical forests in northern Vietnam as climate changes and human population grows. Understanding fire occurrence patterns may support more effective forest management and reduce fire risk. We investigated spatiotemporal patterns and drivers of wildfire across three provinces in northern Vietnam and assessed the effectiveness of the Modified Nesterov index (MNI) fire danger rating system. We explored fire occurrence and size within and between years and forest types using descriptive analyses and developed spatiotemporal Maximum Entropy (Maxent) models incorporating variables representing potential drivers of fire, including weather, fuel, topography and human activity. Most fires occurred late in the dry season and fires were most common in natural forest. Maxent models successfully predicted fire occurrence (area under the receiver operating characteristic curve (AUC) values 0.67–0.79). While the contributions of drivers varied among provinces, MNI, temperature, elevation and distance to road were consistently important. The model for combined provinces showed that fire probability was greater under higher temperature and MNI, in areas with lower population, farther from roads, at higher elevations and in natural forests. This study suggests that an assessment integrating multiple drivers better predicts fire occurrence than a system based on weather alone and may support improved fire management and education in northern Vietnam.

A review of simulation experiment techniques used to analyze wildfire effects on water quality and supply.

This review addresses the critical knowledge gap of techniques simulating combustion and heating characteristics present in natural wildfires and their use in assessing postfire impacts on water quality and quantity. Our assessment includes both laboratory and plot-scale techniques with burn and rainfall simulation components. Studies included focus on advancing understanding of changes in chemical and physical properties of soil, as well as subsequent runoff changes. Advantages of simulation experiments include: overcoming logistical challenges of collecting in situ wildfire data, reducing the high spatial variability observed in natural settings (i.e., the heterogeneity of burn intensity and the underlying vegetation and soil properties), and controlling the magnitude of key drivers of wildfire impacts. In sum, simulation experiments allow for more direct attribution of water quality and quantity responses to specific drivers than experiments conducted in situ. Drawbacks of simulation techniques include the limitation of observing only local-scale processes, the potential misrepresentation of natural settings (i.e., lack of spatial variability in vegetation, soil structure, burn intensity, etc.), uncertainty introduced through experimental error, and subsequent challenges in upscaling results to larger scales relevant for water management. This review focuses primarily on simulation techniques, with the goal of providing a foundation of knowledge for the design of future simulation experiments.

The human–grass–fire cycle: how people and invasives co‐occur to drive fire regimes

Invasive grass species can alter fire regimes, converting native terrestrial ecosystems into non‐native, grass‐dominated landscapes, creating a self‐reinforcing cycle of increasing fire activity and flammable grass expansion. Analyses of this phenomenon tend to focus on the ecology and geography of the grass–fire cycle independent of human activities. Yet people introduce non‐native grasses to new landscapes (eg via agriculture), facilitate their spread (eg via road networks), and are a primary source of ignition (eg via debris burning). We propose a new framework for this phenomenon that explicitly recognizes the important role of anthropogenic activities in the human–grass–fire cycle. We review links between land use and invasive species as well as ignitions, with a particular focus on the spatial and temporal co‐occurrences of these activities to show that these two drivers of wildfires are inextricable. Finally, management strategies that could mitigate impacts are discussed.

The relative importance of driving factors of wildfire occurrence across climatic gradients in the Inner Mongolia, China

In recent decades, wildfire regimes have been changing in many parts of the world with significant differences among climatic regions. Thus, understanding the relationship between fires and driving factors in different climatic regions is important. We investigated the relative importance of wildfire drivers across climatic gradients using a Bayesian network model during 2001–2015 in the Inner Mongolia Autonomous Region (IMAR). Our results showed that regional-scale fire relative probability (FRP) on average increased in the IMAR, which was mainly attributed to increases in annual precipitation. However, changes in FRP and driving factors of wildfire occurrence varied among climatic regions. The FRP decreased at rates of −0.02/decade and −0.001/decade in the humid and semi-humid region, respectively, while increasing at an average rate of 0.05/ decade in the arid region. Temperature was recognized as the most influential driver of wildfires in the humid region, in which the relative importance of all driving factors remained relatively stable over time. In the semi-humid region, wildfires responded primarily to human activities, of which distance to railways was of greatest importance. The relative importance of distance to railways significantly increased over time, while the effects of temperature, humidity and elevation decreased considerably. Fractional vegetation cover (FVC) was the dominant factor controlling the wildfire occurrence in the arid region, in which the relative importance of precipitation significantly increased and the effect of settlements significantly decreased. Our study suggests that because of different driving factors of wildfires across climatic gradients, different fire prevention and management strategies are required. The optimal resource allocation for fire prevention should be adjusted according to the relative importance of wildfire drivers and spatiotemporal patterns of the FRP.

Interpretable machine learning for analysing heterogeneous drivers of geographic events in space-time

ABSTRACT Machine learning (ML) interpretability has become increasingly crucial for identifying accurate and relevant structural relationships between spatial events and factors that explain them. Methodologically aspatial ML algorithms with an apparent high predictive power ignore non-stationary domain relationships in spatio-temporal data (e.g. dependence, heterogeneity), leading to incorrect interpretations and poor management decisions. This study addresses this critical methodological issue of ‘interpretability’ in ML-based modeling of structural relationships using the example of heterogeneous drivers of wildfires across the United States. Specifically, we present and evaluate a spatio-temporally interpretable random forest (iST-RF) that uses spatio-temporal sampling-based training and weighted prediction. Although the ultimate scientific objective is to derive interpretation in space-time, experiments show that iST-RF can improve predictive accuracy (76%) compared to the aspatial RF approach (70%) while enhancing interpretations of the trained model’s spatio-temporal relevance for its ensemble prediction. This novel approach can help balance prediction and interpretation with fidelity in a spatial data science life cycle. However, challenges exist for predictive modeling when the dataset is very small because in such cases locally optimized sub-model’s prediction performance can be suboptimal. With that caveat, our proposed approach is an ideal choice for identifying drivers of spatio-temporal events at country- or regional-scale studies.

The Reading Palaeofire database: an expanded global resource to document changes in fire regimes from sedimentary charcoal records

Wildfires have major impacts on terrestrial ecosystems, the global carbon cycle, atmospheric chemistry and climate. Charcoal records from sedimentary sequences provide a way to reconstruct palaeofire regimes at different temporal and spatial scales and are a key resource to improve our understanding of the drivers of wildfires. The RPD version 1 is an updated and expanded database of global charcoal records, accompanied by new Bayesian age models. The first version of the RPD contains 1681 charcoal records from 1477 sites worldwide. New age models have been run for 714 of the charcoal records.

An Analysis of the Influence of Annual Rainfall Fluctuations on Wildfire Occurrence in Protected Areas in the Northwest of Zimbabwe

The occurrence and threat from wildfires are a conservation concern in semi-arid savanna-protected areas. The risk of wildlife occurrence is uncertain under climate change scenarios. However, general predictions are that different changes are likely to occur in weather conditions in different landscapes. We sought to analyze the influence of annual precipitation on wildfire occurrence in a protected area landscape in northwest Zimbabwe. Data on annual rainfall received and wildfire occurrence for Chizarira National Park (CNP), Chirisa Safari Area (CSA), and Sengwa Wildlife Research Area (SWRA) was analyzed using regression analysis. The relationship between the annual precipitation amount received per site and the number of wildfires recorded per site showed a positive correlation only for CSA. No significant differences were observed for CNP and SWRA at a significant level of p< 0.05. The highest number of wildfires were recorded between July and November. We advance that annual rainfall is one factor among many drivers of wildfires and that this is not uniform but varies across the landscape. Effective annual precipitation contributes to high vegetation biomass production and accumulation of such biomass increases the risk of wildfires. In some instances, rainfall patterns could not explain the occurrence of wildfires. We, therefore, contend that other drivers such as human activities and natural factors are important drivers of wildfires across the three sites. The conservation implication of our finding is that robust fire management plans need to take an ecosystem approach that includes communities adjacent to protected areas.

Participatory mapping reveals socioeconomic drivers of forest fires in protected areas of the post‐conflict Colombian Amazon

Abstract Wildfires have increased in protected areas (PAs) of the Colombian Amazon following the 2016 peace agreement between the Government and the Revolutionary Armed Forced of Colombia (FARC—Spanish acronym). Recent study efforts to understand this issue suffer from data scarcity and limited consultation of local stakeholder perspectives on factors affecting wildfires. This study uses a social–ecological systems framework to investigate local perceptions of factors driving and/or preventing wildfires in the Los Picachos, La Macarena and Tinigua PAs, which are shared by two Amazonian departments experiencing wildfire increase. Four stakeholder categories were selected to represent varied and possibly conflicting interests: cattle ranchers, the national park service, local authorities and cross‐sectional stakeholders. We combined a participative mapping approach with interviews to illustrate stakeholder perceptions of interactions between key variables in graphical causal models. Network analyses were used to determine areas of agreement on key variables, and to compare local priorities with those of key informants at the national level. Local stakeholders and key informants widely agreed on the roles of extensive cattle ranching and land grabbing as key drivers of wildfires. The analysis identified areas for further research into wildfire occurrence within PAs. These include lack of governance and untitled land, as well as the effects of poor access to basic public services on unsustainable ranching methods. This study revealed contested opinions between ranchers and other stakeholders over interactions between ranching, roads and illicit crops, and consequently their effects on wildfire occurrence. This indicates the need for cautious implementation of the National Development Plan, prioritising road maintenance over expansion, integrating arable alternatives to cattle ranching and considering multiple stakeholders in regional decision‐making around wildfire reduction. The strengths and limitations of the participative mapping approach employed here are discussed with a view to aiding decision‐making in post‐conflict regions of the Global South.

Identifying Key Drivers of Wildfires in the Contiguous US Using Machine Learning and Game Theory Interpretation.

Understanding the complex interrelationships between wildfire and its environmental and anthropogenic controls is crucial for wildfire modeling and management. Although machine learning (ML) models have yielded significant improvements in wildfire predictions, their limited interpretability has been an obstacle for their use in advancing understanding of wildfires. This study builds an ML model incorporating predictors of local meteorology, land‐surface characteristics, and socioeconomic variables to predict monthly burned area at grid cells of 0.25° × 0.25° resolution over the contiguous United States. Besides these predictors, we construct and include predictors representing the large‐scale circulation patterns conducive to wildfires, which largely improves the temporal correlations in several regions by 14%–44%. The Shapley additive explanation is introduced to quantify the contributions of the predictors to burned area. Results show a key role of longitude and latitude in delineating fire regimes with different temporal patterns of burned area. The model captures the physical relationship between burned area and vapor pressure deficit, relative humidity (RH), and energy release component (ERC), in agreement with the prior findings. Aggregating the contribution of predictor variables of all the grids by region, analyses show that ERC is the major contributor accounting for 14%–27% to large burned areas in the western US. In contrast, there is no leading factor contributing to large burned areas in the eastern US, although large‐scale circulation patterns featuring less active upper‐level ridge‐trough and low RH two months earlier in winter contribute relatively more to large burned areas in spring in the southeastern US.

Modeling wildfire drivers in Chinese tropical forest ecosystems using global logistic regression and geographically weighted logistic regression

The tropics is an area with high incidence of wildfire all over the world in recent years, and the forest ecosystem in the tropics is extremely fragile. Thus, it is very important to identify drivers of wildfire in the tropics for developing effective fire management strategy. In this paper, global logistic regression (GLR) and geographically weighted regression (GWLR) models were employed to analyze the spatial distribution and drivers of tropical wildfires in Xishuangbanna and Leizhou Peninsula in tropical China from 2001 to 2018. The results show that the overall distribution of wildfire in Xishuangbanna and Leizhou Peninsula from 2001 to 2018 was spatially aggregated. In these tropical seasonal forest ecosystems, wildfire was mainly driven by meteorological factors, particularly by daily temperature range and precipitation. In Xishuangbanna (inland) peninsula, the impact of driving factors tended to be global, and the GLR model predicted the probability of wildfire occurrence better than the GWLR model. Drivers of wildfire in Leizhou Peninsula (coastal area) had clear spatial variation, and the GWLR model better explained the relationship. Furthermore, wildfire in Leizhou was more driven by human activities, especially management of agricultural lands. Our results demonstrate that effective forest management practice needs to adopt fire management practices with regional characteristics. The forest management strategy and traditional agriculture production system should pay more attention to changes in these driving factors and their relationship with wildfire.

Are Climate Factors Driving the Contemporary Wildfire Occurrence in China?

Understanding the drivers of wildfire occurrence is of great value for fire prevention and management, but due to the variation in research methods, data sources, and data resolution of those studies, it is challenging to conduct a large-scale comprehensive comparative qualitative analysis on the topic. China has diverse vegetation types and topography, and has undergone rapid economic and social development, but experiences a high frequency of wildfires, making it one of the ideal locations for wildfire research. We applied the Random Forests modelling approach to explore the main types of wildfire drivers (climate factors, landscape factors and human factors) in three high wildfire density regions (Northeast (NE), Southwest (SW), and Southeast (SE)) of China. The results indicate that climate factors were the main driver of wildfire occurrence in the three regions. Precipitation and temperature significantly impacted the fire occurrence in the three regions due to the direct influence on the moisture content of forest fuel. However, wind speed had important influence on fire occurrence in the SE and SW. The explanation power of the landscape and human factors varied significantly between regions. Human factors explained 40% of the fire occurrence in the SE but only explained less than 10% of the fire occurrence in the NE and SW. The density of roads was identified as the most important human factor driving fires in all three regions, but railway density had more explanation power on fire occurrence in the SE than in the other regions. The landscape factors showed nearly no influence on fire occurrence in the NE but explained 46.4% and 20.6% in the SE and SW regions, respectively. Amongst landscape factors, elevation had the highest average explanation power on fire occurrence in the three regions, particularly in the SW. In conclusion, this study provides useful insights into targeted fire prediction and prevention, which should be more precise and effective under climate change and socio-economic development.

Climate, Fuel, and Land Use Shaped the Spatial Pattern of Wildfire in California’s Sierra Nevada

AbstractCalifornia’s Sierra Nevada has experienced a large increase in wildfire activities over recent decades. This intensifying fire regime has coincided with a warming climate and increasing human activity, but the relative importance of the biophysical and anthropogenic drivers of wildfire remains unclear across this diverse landscape, especially at a finer spatial scale. We used multisource geospatial data sets of fire occurrence, and human, climatic, and biophysical variables to examine the spatial pattern and controls on Sierra Nevada wildfires averaged from 1984 to 2017. The maximum entropy model driven by both biophysical and anthropogenic variables predicted the spatial distribution of fire probability well, with an area under the curve (AUC) score of 0.81. Model diagnostics revealed that aspects of the climate, including vapor pressure deficit (VPD), temperature, and burning index (difficulty of control), dominated the spatial patterns of fire probability across the whole Sierra Nevada region. The VPD was the leading control, with a relative contribution of 32.1%. Population density and fuel amount were also significant drivers, each accounting for 15.8%–12.4% of relative contribution. VPD and burning index were the most important factors for fire probability in higher elevation forest, while population density was comparatively more important in the lower elevation forest regions of the Sierra Nevada. Our findings improved our understanding of the relative importance of various factors in shaping the spatial patterns of historical fire probability in the Sierra Nevada and across various subecoregions, providing insights for targeting spatially varying forest management strategies to limit potential future increases in wildfires.

Wildfire dynamics and impacts on a tropical Andean oak forest

Wildfires have increasingly damaged Andean tropical forests. However, both a poor understanding of wildfire dynamics and ecosystem response limits awareness about the magnitude of the problem and design management strategies. We estimate the impacts and significant drivers of wildfires by dating and mapping recent wildfires in an Andean tropical forest area, the Iguaque mountains. A large part of Iguaque hosts a population of the only Quercus species in South America, Quercus humboldtii. We used remote-sensing, official reports and social mapping to reconstruct the recent history of wildfires and change in oak forest patches in Iguaque. Between 1990 and 2017, 25 wildfires were recorded, with fire intervals between 4 and 21 years. These events burned 28.4% of the Iguaque mountains and showed a significant increasing trend in extent. Wildfires mostly occurred in the south, during the driest months, and their number and extent showed substantial interannual variations related to El Niño–Southern Oscillation cycles. Wildfires contributed to a 45% reduction in oak forests along with the fragmentation of existing populations. Our study presents evidence of the extent and impact of wildfires in Iguaque and provides new insights on fire dynamics in Andean tropical forests.

Increasing concurrence of wildfire drivers tripled megafire critical danger days in Southern California between1982 and 2018

Wildfire danger is often ascribed to increased temperature, decreased humidity, drier fuels, or higher wind speed. However, the concurrence of drivers—defined as climate, meteorological and biophysical factors that enable fire growth—is rarely tested for commonly used fire danger indices or climate change studies. Treating causal factors as independent additive influences can lead to inaccurate inferences about shifting hazards if the factors interact as a series of switches that collectively modulate fire growth. As evidence, we show that in Southern California very large fires and ‘megafires’ are more strongly associated with multiple drivers exceeding moderate thresholds concurrently, rather than direct relationships with extreme magnitudes of individual drivers or additive combinations of those drivers. Days with concurrent fire drivers exceeding thresholds have increased more rapidly over the past four decades than individual drivers, leading to a tripling of annual ‘megafire critical danger days’. Assessments of changing wildfire risks should explicitly address concurrence of fire drivers to provide a more precise assessment of this hazard in the face of a changing climate.

Fire regime in the Brazilian Savanna: Recent changes, policy and management

In 2019 Brazil recorded the highest wildland fire occurrence South America has seen for the last 15 years. Added to the Amazon, the Brazilian savanna (Cerrado) faces changes in fire regimes. Climatic changes and the recent weakening of environmental law enforcement are factors, but historic and large-scale trends and drivers of fire regimes must be analyzed. We discuss ecological and policy drivers of recent changes in fire regimes in the Cerrado, in order to highlight management strategies. The Cerrado has evolved with natural fires and anthropogenic fires are also common for millennia. In the past 50 years, wildfires tend to be concentrated in the late dry season and to occur every two / three years, causing serious damage in fire-sensitive vegetation. Apart from climatic variations, the drivers of wildfires are deforestation and fire suppression policies. Nearly half of the original vegetation of the Cerrado biome has disappeared largely due to agribusiness expansion. Fire is associated with deforestation in two ways: vegetation conversion to monocultures, and lack of fire management in the remaining native vegetation. Indeed, the attempts to exclude fires from this fire-prone ecosystem disrupted traditional fire management. Fire suppression policies lead to increased wildfire risks due to fuel load and the multiplication of sources of ignition (conflicts, roads). The recent advances in Integrated Fire Management in protected areas in the Cerrado are evident. However, the recent budget cuts by the Brazilian government in environmental management and research undermine the chances of decreasing occurrences of wildfires in this biodiversity hotspot.

Human activity, daylight saving time and wildfire occurrence

Wildfires shape landscapes and ecosystems, affecting health and infrastructure. Understanding the complex interactions between social organization, human activity and the natural environment that drive wildfire occurrence is becoming increasingly important as changing global environmental conditions combined with the expanding human-wildland interface, are expected to increase wildfire frequency and severity. This paper examines the anthropogenic drivers of wildfire, and the relationship between the organization of human activity in time and wildfire occurrence focusing on the effects of transitions into and out of Daylight Saving Time (DST). DST transitions shift activity in relation to natural wildfire risk within a solar day, induce changes in the time allocated to wildfire-causing activities and disrupt sleep patterns. The paper estimates short and medium run effects of DST-induced changes in the temporal organization of human activity through a Regression Discontinuity Design with time as the running variable and Fixed Effects models, using data from over 1.88 million non-prescribed ignitions recorded in the contiguous US over 23 years. Estimates suggest that DST has a quantitatively and statistically significant immediate and medium-run effect on wildfire occurrence. Wildfire occurrence jumps by around 30% in the immediate aftermath of transitions into DST, adding about 98 human-caused wildfires across the contiguous US per year, while the transition's effect is detectable for 3 weeks. Transitions induce within-day temporal displacement of wildfires in a pattern compatible with the shifting of human activity mechanism, while the result cannot be attributed exclusively on disruptions in sleep patterns. Naturally arising lightning-strike wildfires do not respond to changes in civil time, while the results are robust to changes in assumptions. Results suggest that wildfire policy should account for the temporal organization of human activity.

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).

Spatial stratification of wildfire drivers towards enhanced definition of large-fire regime zoning and fire seasons

The area affected by wildfires is experiencing an overall decrease in the Mediterranean European region. However, there is no clear trend associated to the incidence of large fire events, which continue to pose an important threat to assets-at-risk, while debates on control by meteorological or fuel drivers are ongoing. Understanding the underlying spatial and temporal patterns of large-fire drivers is of critical importance for a more efficient and science-based management, and specifically for improving wildfire season definition and informing fuel management.Taking advantage of the reliable wildfire data available in Spain, we analyzed large fires (>100 ha) in the period 2010–2015 to outline homogenous spatial-temporal regions in terms of the influence of the main drivers of large-fire activity: temperature, wind speed, slope, distance to populated places and roads, and proximity to agricultural lands. We combined Geographically Weighted Logit Regression (GWLR) models to parameterize the marginal influence of the drivers, with optimized hierarchical clustering to define uniform regions in terms of the underlying driving factors. These regions were subsequently analyzed for monthly distribution of fire occurrence and associated fuel models.We identified four different zones in terms of drivers' features, capturing dissimilar intra-annual patterns of fire activity and affected fuels: one covering the Mediterranean and two along the northern coast, and a fourth aggregation in the hinterlands that seems to act as transition area. The Mediterranean and hinterland were linked to weather-related summer ignitions, late and early summer respectively. The northern cluster gathers most winter fires starting in remote locations under steep slopes and strong wind conditions. The northwestern cluster accounts for most of the fire activity in Spain, related to complex relief and shrub-type fuels.

Future changes in fire weather, spring droughts, and false springs across U.S. National Forests and Grasslands.

Public lands provide many ecosystem services and support diverse plant and animal communities. In order to provide these benefits in the future, land managers and policy makers need information about future climate change and its potential effects. In particular, weather extremes are key drivers of wildfires, droughts, and false springs, which in turn can have large impacts on ecosystems. However, information on future changes in weather extremes on public lands is lacking. Our goal was to compare historical (1950-2005) and projected mid-century (2041-2070) changes in weather extremes (fire weather, spring droughts, and false springs) on public lands. This case study looked at the lands managed by the U.S. Forest Service across the conterminous United States including 501 ranger district units. We analyzed downscaled projections of daily records from 19 Coupled Model Intercomparison Project 5 General Circulation Models for two climate scenarios, with either medium-low or high CO2 - equivalent concentration (RCPs 4.5 and 8.5). For each ranger district, we estimated: (1) fire potential, using the Keetch-Byram Drought Index; (2) frequency of spring droughts, using the Standardized Precipitation Index; and (3) frequency of false springs, using the extended Spring Indices. We found that future climates could substantially alter weather conditions across Forest Service lands. Under the two climate scenarios, increases in wildfire potential, spring droughts, and false springs were projected in 32-72%, 28-29%, and 13-16% of all ranger districts, respectively. Moreover, a substantial number of ranger districts (17-30%), especially in the Southwestern, Pacific Southwest, and Rocky Mountain regions, were projected to see increases in more than one type of weather extreme, which may require special management attention. We suggest that future changes in weather extremes could threaten the ability of public lands to provide ecosystem services and ecological benefits to society. Overall, our results highlight the value of spatially-explicit weather projections to assess future changes in key weather extremes for land managers and policy makers.