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Understanding ownership effects on large wildfires is a precursor to the development of risk governance strategies that better protect people and property and restore fire-adapted ecosystems. We analyzed wildfire events in the Pacific Northwest from 1984 to 2018 to explore how area burned responded to ownership, asking whether particular ownerships burned disproportionately more or less, and whether these patterns varied by forest and grass/shrub vegetation types. While many individual fires showed indifference to property lines, taken as a whole, we found patterns of disproportionate burning for both forest and grass/shrub fires. We found that forest fires avoided ownerships with a concentration of highly valued resources—burning less than expected in managed US Forest Service forested lands, private non-industrial, private industrial, and state lands—suggesting the enforcement of strong fire protection policies. US Forest Service wilderness was the only ownership classification that burned more than expected which may result from the management of natural ignitions for resource objectives, its remoteness or both. Results from this study are relevant to inform perspectives on land management among public and private entities, which may share boundaries but not fire management goals, and support effective cross-boundary collaboration and shared stewardship across all-lands.

Predicting the efficacy of fuel treatments aimed at reducing high severity fire in dry-mixed conifer forests in the western US is a challenging problem that has been addressed in a variety of ways using both field observations and wildfire simulation models. One way to describe the efficacy of fuel treatments is to quantify how often wildfires are expected to intersect areas prioritized for treatment. In real landscapes treatments are static, restricted to a small portion of the landscape and against a background of stochastic fire and dynamic vegetation, thus the likelihood of fire encountering a treatment during the period treatments remain effective is small. In this paper we simulate a wide range of different treatment prioritization schemes using the forest landscape simulation model Envision to examine 50 years of fire-treatment interactions and forest succession. We first reviewed 47 fuel management projects in Oregon, USA to build prioritization schemes that addressed different fuel management objectives. We then simulated different priority schemes in the 18 planning areas of the Deschutes National Forest in central Oregon and measured potential fire-treatment interactions over time. Simulated annual area burned was used to calculate the success odds for each priority scheme and planning area. Out of the ten metrics considered only three had higher success odds than a random prioritization of planning areas. Spatial allocation of projects based on burn probability and transmitted wildfire had the highest success odds among the tested metrics. However, success odds declined sharply as desired success levels increased suggesting that fuel management goals need to be tempered to consider the stochastic nature of wildfire. Meeting long-term multiple management goals over time can benefit from consideration of short- and long-term tradeoffs from different treatment prioritization schemes. Our work contributes towards a better framing of both management and public expectations regarding the performance of fuel treatments programs.

We developed and applied a wildfire simulation package in the Envision agent-based landscape modelling system. The wildfire package combines statistical modelling of fire occurrence with a high-resolution, mechanistic wildfire spread model that can capture fine scale effects of fire feedbacks and fuel management, and replicate restoration strategies at scales that are meaningful to forest managers. We applied the model to a landscape covering 1.2 million ha of fire prone area in central Oregon, USA where wildland fires are increasingly impacting conservation, amenity values and developed areas. We conducted simulations to examine the effect of human versus natural ignitions on future fire regimes under current restoration programs, and whether contemporary fire regimes observed in the past 20 years are likely to change as result of fire feedbacks and management activities. The ignition prediction model revealed non-linear effects of location and time of year, and distinct spatiotemporal patterns for human versus natural ignitions. Fire rotation interval among replicate simulations varied from 78 to 170 years and changed little over the 50-yr simulation, suggesting a stable but highly variable and uncertain future fire regime. Interestingly, the potential for fire-on-fire feedbacks was higher for human versus natural ignitions due to human ignition hotspots within the study area. We compare the methods and findings with other forest landscape simulation model (FLSM) studies and discuss future application of FLSMs to address emerging wildfire management and policy issues on fire frequent forests in the western US.

We assessed transboundary wildfire exposure among federal, state, and private lands and 447 communities in the state of Arizona, southwestern United States. The study quantified the relative magnitude of transboundary (incoming, outgoing) versus nontransboundary (i.e., self-burning) wildfire exposure based on land tenure or community of the simulated ignition and the resulting fire perimeter. We developed and described several new metrics to quantify and map transboundary exposure. We found that incoming transboundary fire accounted for 37% of the total area burned on large parcels of federal and state lands, whereas 63% of the area burned was burned by ignitions within the parcel. However, substantial parcel to parcel variation was observed for all land tenures for all metrics. We found that incoming transboundary fire accounted for 66% of the total area burned within communities versus 34% of the area burned by self-burning ignitions. Of the total area burned within communities, private lands contributed the largest proportion (36.7%), followed by national forests (19.5%), and state lands (15.4%). On average seven land tenures contributed wildfire to individual communities. Annual wildfire exposure to structures was highest for wildfires ignited on state and national forest land, followed by tribal, private, and BLM. We mapped community firesheds, that is, the area where ignitions can spawn fires that can burn into communities, and estimated that they covered 7.7 million ha, or 26% of the state of Arizona. Our methods address gaps in existing wildfire risk assessments, and their implementation can help reduce fragmentation in governance systems and inefficiencies in risk planning.

Eucalypts planted for pulp production are highly valued forest resources often at risk in fire-prone environments. Fuel management programs can diminish fire hazard, yet little is known about how to treat, and how often, to maximize treatment effect and persistence. This study describes the temporal dynamics of fuel structure attributes and fire behaviour following the application of one of four alternative treatments in blue gum ( Eucalyptus globulus ) plantations in Portugal. We quantified fuel characteristics using non-destructive methods and attributed visual fuel hazard scores in plots ( n = 256) that had been treated between zero and 111 months earlier. Fire behaviour simulation was based on the Dry Eucalypt Forest Fire Model. We used generalized linear modelling to relate post-treatment fuel hazard metrics and fire behaviour characteristics to treatment type and time since treatment (T), plus site and stand conditions for selected dependent variables. Fuel hazard increased with T, but the proportion of explained variation in fuel metrics was moderate at best, presumably because of environmental variation among sites. Fuel dynamics in relation to T varied with treatment type and fuel metric. Immediate pots-treatment fire hazard was higher for low-impact treatments (herbicide, manual cutting) than for high-impact treatments (disk harrowing, slashing). Subsequently, low-impact treatments resulted in declining fire hazard and the opposite trend was observed for high-impact treatments; fire hazard convergence between the two treatment groups occurred at T = 3–4 years. Low-impact treatments differ from mechanical treatments in that their effects are not immediate and are limited to near-surface and elevated fuels, and thus are not recommended as a stand-alone fuel treatment practice. Independently of treatment, fire hazard increased with stand age, stand density, and productivity-related variables. Variation in those influences and in slope determines that fire suppression in blue gum stands is effective for 2–6 years after disk harrowing, currently the prevailing treatment option. Because the impact of mechanized treatments is restricted to inter-rows, improved fuel control would be achieved through low-intensity prescribed burning. Effective fuel treatment programs in industrial eucalypt plantations are constrained by a mix of natural and economic factors, which implies that adequate protection from wildfire cannot be achieved without due consideration of the plantation and fire management contexts.

Large fires account for a disproportionally high percentage of area burned with potentially severe environmental and socioeconomic impacts. This study characterizes extremely large fires (ELF, 2500–24,843 ha) in Portugal (1998–2013) and the concomitant fuel and weather conditions, analyzing the response of ELF size to their variation. ELF burned less shrubland-grassland (33% of the total ELF area) than forest (59% of total), the latter primarily composed by pine and pine-eucalypt. High fuel hazard was the norm, as indicated by median values of 0.98 for fuel load as a fraction of potential (maximum) load, and time since fire >14 years over 91% of the burned area. ELF occurred under anticyclonic circulation patterns, especially ridging, and 78% of them coincided with extreme fire danger days (corresponding to infrequent conditions) in conjunction with unstable atmosphere. Containment time, fire growth rate and energy release metrics varied by one more order of magnitude than ELF size, hence indicating that size alone is insufficient to describe extreme fires. Distinct combinations between ambient weather conditions, atmospheric instability and drought defined three categories of ELF as defined by size. Quantile regression indicated that increasingly larger fires showed gradually stronger responses to fire weather severity, highlighting the difficulty in restraining fire spread in flammable landscapes in the absence of extensive fuel treatments. Data limitations inherent to the methods used are discussed, and improvements to further advance the understanding of extreme fires are suggested.

Large fires and their impacts are a growing concern as changes in climate and land use proceed. The study of large-fire controls remains incipient in comparison with other components of the fire regime. Improved understanding of large-fire size drivers can disclose fire–landscape relationships and inform more sustainable and effective fire management. We used boosted regression tree modeling to identify the variables influent on large-fire size (100–23,219 ha, n = 609) in Portugal (1998–2008) and quantify their relative importance, globally and across the fire-size range. Potential explanatory variables included metrics pertaining to fire weather and antecedent rainfall, burned area composition, fuel connectivity, pyrodiversity (from fire recurrence patterns), topography, and land development. Large fires seldom occurred in the absence of severe fire weather. The fire-size model accounted for 70% of the deviance and included 12 independent variables, of which six absorbed 91% of the explanation. Bottom-up influences on fire size, essentially fuel-related, largely outweighed climate–weather influences, with respective importance of 85 and 15%. Fire size was essentially indifferent to land-cover composition, including forest type, and increased with high fuel connectivity and low pyrodiversity. Relevant synergies between variables were found, either positive or negative, for example, high pyrodiversity buffered the effects of extreme weather on fire size. The relative role of fire-size drivers did not vary substantially with fire size, but fires larger than 500 ha were increasingly controlled by fuel-related variables. The extent of an individual large fire is mainly a function of factors that land-use planning and forest and fuel management can tackle.

Exotic grasses are a widespread set of invasive species that are notable for their ability to significantly alter key aspects of ecosystem function. Understanding the role and importance of these invaders in forested landscapes has been limited but is now rising, as grasses from Eurasia and Africa continue to spread through ecosystems of the Americas, Australia, and many Pacific islands, where they threaten biodiversity and alter various aspects of the fire regime. The ecological, social and economic impacts of the grass-fire cycle associated with species such as cheatgrass (Bromus tectorum) have been long recognized in aridlands such as the iconic sagebrush ecosystems of the western US. However, the damaging impacts of invasive grasses in forestlands have received considerably less attention. We review literature, conceptual models, model output, and empirical evidence that indicate grass invasion in forest ecosystems may be an important yet largely under-recognized phenomenon. In combination with climate change, wildfire, and overstory management, invasive grasses could create a “perfect storm” that threatens forest resilience. Invasive grasses can be successful in forested environments or develop strongholds within forested mosaics and could provide the literal seeds for rapid change and vegetation type conversion catalyzed by wildfire or changes in climate. Although invasive grass populations may now be on the edge of forests or consist of relatively rare populations with limited spatial extent, these species may disrupt stabilizing feedbacks and disturbance regimes if a grass-fire cycle takes hold, forcing large portions of forests into alternative nonforested states. In addition, forest management actions such as thinning, prescribed fire, and fuel reduction may actually exacerbate invasive grass populations and increase the potential for further invasion, as well as broader landscape level changes through increased fire spread and frequency. Lack of understanding regarding the ecological consequences and importance of managing invasive grasses as a fuel may lead to unintended consequences and outcomes as we enter an age of novel and rapid ecological changes. This paper focuses on the contributory factors, mechanisms, and interactions that may set the stage for unexpected forest change and loss, in an effort to raise awareness about the potential damaging impact of grass invasion in forested ecosystems.

We integrated a widely used forest growth and management model, the Forest Vegetation Simulator, with the FSim large wildfire simulator to study how management policies affected future wildfire over 50 years on a 1.3 million ha study area comprised of a US national forest and adjacent lands. The model leverages decades of research and development on the respective forest growth and wildfire simulation models, and their integration creates a strategic forest landscape model that has a high degree of transparency in the existing user communities. The study area has been targeted for forest restoration investments in response to wildland fires that are increasingly impacting ecological conditions, conservation areas, amenity values, and surrounding communities. We simulated three alternative spatial investment priorities and three levels of management intensity (area treated) over a 50-year timespan and measured the response in terms of area burned, fire severity, wildland-urban interface exposure and timber production. We found that the backlog of areas in need of restoration on the national forest could be eliminated in 20 years when the treatment rate was elevated to a maximum of 3× the current level. However, higher rates of treatments early in the simulation created a future need to address the rapid buildup of fuels associated with understory shrub and tree regeneration. Restoration treatments over time had a large effect on fire severity, on average reducing potential flame length by up to 26% for the study area within the first 20 years, whereas reductions in area burned were relatively small. Although wildfire contributed to reducing flame length over time, area burned was only 16% of the total disturbed area (managed and burned with prescribed fire) under the 3× management intensity. Interactions among spatial treatment scenarios and treatment intensities were minimal, although inter-annual variability was extreme, with the coefficient of variation in burned area exceeding 200%. We also observed simulated fires that exceeded four times the historically recorded fire size. Fire regime variability has manifold significance since very large fires can homogenize fuels and eliminate clumpy stand structure that historically reduced fire size and maintained landscape resiliency. We discuss specific research needs to better understand future wildfire activity and the relative influence of climate, fuels, fire feedbacks, and management to achieve fire resiliency goals on western US fire frequent forests.

Wildland fire suppression practices in the western United States are being widely scrutinized by policymakers and scientists as costs escalate and large fires increasingly affect social and ecological values. One potential solution is to change current fire suppression tactics to intentionally increase the area burned under conditions when risks are acceptable to managers and fires can be used to achieve long-term restoration goals in fire adapted forests. We conducted experiments with the Envision landscape model to simulate increased levels of wildfire over a 50-year period on a 1.2 million ha landscape in the eastern Cascades of Oregon, USA. We hypothesized that at some level of burned area fuels would limit the growth of new fires, and fire effects on the composition and structure of forests would eventually reduce future fire intensity and severity. We found that doubling current rates of wildfire resulted in detectable feedbacks in area burned and fire intensity. Area burned in a given simulation year was reduced about 18% per unit area burned in the prior five years averaged across all scenarios. The reduction in area burned was accompanied by substantially lower fire severity, and vegetation shifted to open forest and grass-shrub conditions at the expense of old growth habitat. Negative fire feedbacks were slightly moderated by longer-term positive feedbacks, in which the effect of prior area burned diminished during the simulation. We discuss trade-offs between managing fuels with wildfire versus prescribed fire and mechanical fuel treatments from a social and policy standpoint. The study provides a useful modeling framework to consider the potential value of fire feedbacks as part of overall land management strategies to build fire resilient landscapes and reduce wildfire risk to communities in the western U.S. The results are also relevant to prior climate-wildfire studies that did not consider fire feedbacks in projections of future wildfire activity.

We assessed transboundary wildfire exposure among federal, state, and private lands and 447 communities in the state of Arizona, southwestern United States. The study quantified the relative magnitude of transboundary (incoming, outgoing) versus nontransboundary (i.e., self-burning) wildfire exposure based on land tenure or community of the simulated ignition and the resulting fire perimeter. We developed and described several new metrics to quantify and map transboundary exposure. We found that incoming transboundary fire accounted for 37% of the total area burned on large parcels of federal and state lands, whereas 63% of the area burned was burned by ignitions within the parcel. However, substantial parcel to parcel variation was observed for all land tenures for all metrics. We found that incoming transboundary fire accounted for 66% of the total area burned within communities versus 34% of the area burned by self-burning ignitions. Of the total area burned within communities, private lands contributed the largest proportion (36.7%), followed by national forests (19.5%), and state lands (15.4%). On average seven land tenures contributed wildfire to individual communities. Annual wildfire exposure to structures was highest for wildfires ignited on state and national forest land, followed by tribal, private, and BLM. We mapped community firesheds, that is, the area where ignitions can spawn fires that can burn into communities, and estimated that they covered 7.7 million ha, or 26% of the state of Arizona. Our methods address gaps in existing wildfire risk assessments, and their implementation can help reduce fragmentation in governance systems and inefficiencies in risk planning.

This study investigates how federal, state, and private corporate forest owners in a fire-prone landscape of southcentral Oregon manage their forests to reduce wildfire hazard and loss to high-severity wildfire. We evaluate the implications of our findings for concepts of social-ecological resilience. Using interview data, we found a high degree of "response diversity" (variation in forest management decisions and behaviors to reduce wildfire losses) between and within actor groups. This response diversity contributed to heterogeneous forest conditions across the landscape and was driven mainly by forest management legacies, economics, and attitudes toward wildfire (fortress protection vs. living with fire). We then used an agent-based landscape model to evaluate trends in forest structure and fire metrics by ownership. Modeling results indicated that, in general, U.S. Forest Service management had the most favorable outcomes for forest resilience to wildfire, and private corporate management the least. However, some state and private corporate forest ownerships have the building blocks for developing fire-resilient forests. Heterogeneity in social-ecological systems is often thought to favor social-ecological resilience. We found that despite high social and ecological heterogeneity in our study area, most forest ownerships do not exhibit characteristics that make them resilient to high-severity fire currently or in the future under current management. Thus, simple theories about resilience based on heterogeneity must be informed by knowledge of the environmental and social conditions that comprise that heterogeneity. Our coupled human and natural systems (CHANS) approach enabled us to understand connections among the social, economic, and ecological components of a multiownership, fire-prone ecosystem, and to identify how social-ecological resilience to wildfire might improve through interventions to address key constraints in the system. Our methods underscore the importance of looking beyond the present to future trajectories of change to fully understand the implications of current natural resource management practices for adaptation and social-ecological resilience to natural disturbances.

Fire-prone landscapes present many challenges for both managers and policy makers in developing adaptive behaviors and institutions. We used a coupled human and natural systems framework and an agent-based landscape model to examine how alternative management scenarios affect fire and ecosystem services metrics in a fire-prone multiownership landscape in the eastern Cascades of Oregon. Our model incorporated existing models of vegetation succession and fire spread and information from original empirical studies of landowner decision making. Our findings indicate that alternative management strategies can have variable effects on landscape outcomes over 50 years for fire, socioeconomic, and ecosystem services metrics. For example, scenarios with federal restoration treatments had slightly less high-severity fire than a scenario without treatment; exposure of homes in the wildland-urban interface to fire was also slightly less with restoration treatments compared to no management. Treatments appeared to be more effective at reducing high-severity fire in years with more fire than in years with less fire. Under the current management scenario, timber production could be maintained for at least 50 years on federal lands. Under an accelerated restoration scenario, timber production fell because of a shortage of areas meeting current stand structure treatment targets. Trade-offs between restoration outcomes (e.g., open forests with large fire-resistant trees) and habitat for species that require dense older forests were evident. For example, the proportional area of nesting habitat for northern spotted owl (Strix occidentalis) was somewhat less after 50 years under the restoration scenarios than under no management. However, the amount of resilient older forest structure and habitat for white-headed woodpecker (Leuconotopicus albolarvatus) was higher after 50 years under active management. More carbon was stored on this landscape without management than with management, despite the occurrence of high-severity wildfire. Our results and further applications of the model could be used in collaborative settings to facilitate discussion and development of policies and practices for fire-prone landscapes.

The relation between wildfire orientation and size is analyzed by means of a nonparametric test for directional-linear independence. The test statistic is designed for assessing the independence between two random variables of different nature, specifically directional (fire orientation, circular or spherical, as particular cases) and linear (fire size measured as burnt area, scalar), based on a directional-linear nonparametric kernel density estimator. In order to apply the proposed methodology in practice, a resampling procedure based on permutations and bootstrap is provided. The finite sample performance of the test is assessed by a simulation study, comparing its behavior with other classical tests for the circular-linear case. Finally, the test is applied to analyze wildfire data from Portugal., Comment: 19 pages, 4 figures, 3 tables

Using 100 years of fire perimeter maps, we investigate the existence of geographical patterns in fire orientation across California. We computed fire perimeter orientation, at the watershed level, using principal component analysis. Circular statistics were used to test for the existence of preferential fire perimeter orientations. Where perimeters displayed preferential orientation, we searched for evidence of orographic channeling by comparing mean fire orientation with watershed orientation. Results show that in California, 49% of the burnt area is associated with watersheds, where fires displayed preferential orientation. From these, 25% of the burnt area is aligned along the NE/SW orientation and 18% in the E/W orientation. In 27 out of 86 watersheds with preferential fire alignment, there is also correspondence between mean fire orientation and watershed orientation. Topographic influence on fire spread and dominant wind patterns during the fire season can account for the consistency in fire perimeter orientation in these regions. Our findings highlight the historical pattern of fire perimeter orientation and identify watersheds with potential orographic channeling This paper was supported by the Fundação para a Ciência e Tecnologia Ph.D. Grant SFRH/BD/40398/2007. JMCP participated in this research under the framework of research projects “Forest fire under climate, social and economic changes in Europe, the Mediterranean and other fire-affected areas of the world (FUME)”, EC FP7 Grant Agreement No. 243888.

We use the simulation model Envision to analyze long-term wildfire dynamics and the effects of different fuel management scenarios in central Oregon, USA. We simulated a 50-year future where fuel management activities were increased by doubling and tripling the current area treated while retaining existing treatment strategies in terms of spatial distribution and treatment type. We modeled forest succession using a state-and-transition approach and simulated wildfires based on the contemporary fire regime of the region. We tested for the presence of temporal trends and overall differences in burned area among four fuel management scenarios. Results showed that when the forest was managed to reduce fuels it burned less: over the course of 50 years there was up to a 40% reduction in area burned. However, simulation outputs did not reveal the expected temporal trend, i.e., area burned did not decrease progressively with time, nor did the absence of management lead to its increase. These results can be explained as the consequence of an existing wildfire deficit and vegetation succession paths that led to closed canopy, and heavy fuels forest types that are unlikely to burn under average fire weather. Fire (and management) remained relatively rare disturbances and, given our assumptions, were unable to alter long-term vegetation patterns and consequently unable to alter long-term wildfire dynamics. Doubling and tripling current management targets were effective in the near term but not sustainable through time because of a scarcity of stands eligible to treat according to the modeled management constraints. These results provide new insights into the long-term dynamics between fuel management programs and wildfire and demonstrate that treatment prioritization strategies have limited effect on fire activity if they are too narrowly focused on particular forest conditions.

Previous research has shown that fires burn certain land cover types disproportionally to their abundance. We used quantile regression to study land cover proneness to fire as a function of fire size, under the hypothesis that they are inversely related, for all land cover types. Using five years of fire perimeters, we estimated conditional quantile functions for lower (avoidance) and upper (preference) quantiles of fire selectivity for five land cover types - annual crops, evergreen oak woodlands, eucalypt forests, pine forests and shrublands. The slope of significant regression quantiles describes the rate of change in fire selectivity (avoidance or preference) as a function of fire size. We used Monte-Carlo methods to randomly permutate fires in order to obtain a distribution of fire selectivity due to chance. This distribution was used to test the null hypotheses that 1) mean fire selectivity does not differ from that obtained by randomly relocating observed fire perimeters; 2) that land cover proneness to fire does not vary with fire size. Our results show that land cover proneness to fire is higher for shrublands and pine forests than for annual crops and evergreen oak woodlands. As fire size increases, selectivity decreases for all land cover types tested. Moreover, the rate of change in selectivity with fire size is higher for preference than for avoidance. Comparison between observed and randomized data led us to reject both null hypotheses tested (a = 0.05) and to conclude it is very unlikely the observed values of fire selectivity and change in selectivity with fire size are due to chance. Funding: This paper was supported by the Fundação para a Ciência e Tecnologia Ph.D. Grant SFRH/BD/40398/2007. JMCP participated in this research under the framework of research projects ‘‘Forest fire under climate, social and economic changes in Europe, the Mediterranean and other fire-affected areas of the world (FUME)’’, EC FP7 Grant Agreement No. 243888. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

We searched for geographical patterns in the orientation of wildfires, using watersheds as spatial support for the analysis. An 1975–2005 annual fire atlas of mainland Portugal was used to compute the orientation of fire perimeters and watersheds, using principal component analysis. Circular statistics were employed to test for the existence of a preferred, as opposed to random, mean fire orientation in each watershed, and to search for evidence of orographic channelling of fire by comparing fire orientation and watershed orientation. We also tested for differences in fire orientation patterns under conditions of mild versus severe fire weather. Our findings show that in the 31 year period of the study, 84% of the overall area burned is accounted for by watersheds where fires display preferential orientation. Twelve of 102 watersheds display evidence of alignment between fire and watershed orientation and we found no distinction in fire orientation as response to fire weather. The spatial arrangement of watersheds where fires present similar orientation suggests wind as a major driver of the broader patterns found in this study. Results from this analysis ought to be relevant for supporting the delineation of landscape- scale fuelbreaks.

Wildfires pose complex challenges to policymakers and fire agencies. Fuel break networks and area-wide fuel treatments are risk-management options to reduce losses from large fires. Two fuel management scenarios covering 3% of the fire-prone Algarve region of Portugal and differing in the intensity of treatment in 120-m wide fuel breaks were examined and compared with the no-treatment option. We used the minimum travel time algorithm to simulate the growth of 150 000 fires under the weather conditions historically associated with large fires. Fuel break passive effects on burn probability, area burned, fire size distribution and fire transmission among 20 municipalities were analysed. Treatments decreased large-fire incidence and reduced overall burnt area up to 17% and burn probability between 4% and 31%, depending on fire size class and treatment option. Risk transmission among municipalities varied with community. Although fire distribution shifted and large events were less frequent, mean treatment leverage was very low (1 : 26), revealing a very high cost–benefit ratio and the need for engaging forest owners to act in complementary area-wide fuel treatments. The study assessed the effectiveness of a mitigating solution in a complex socioecological system, contributing to a better-informed wildland fire risk governance process among stakeholders.

An automated procedure is here presented that allows identifying and dating burned areas in Portugal using values of daily reflectance from near-infrared and middle-infrared bands, as obtained from the MODIS instrument. The algorithm detects persistent changes in monthly composites of the so-called (V,W) Burn-Sensitive Index and the day of maximum change in daily time series of W is in turn identified as the day of the burning event. The procedure is tested for 2005, the second worst fire season ever recorded in Portugal. Comparison between the obtained burned area map and the reference derived from Landsat imagery resulted in a Proportion Correct of 95.6%. Despite being applied only to the months of August and September, the algorithm is able to identify almost two-thirds of all scars that have occurred during the entire year of 2005. An assessment of the temporal accuracy of the dating procedure was also conducted, showing that 75% of estimated dates presented deviations between -5 and 5 days from dates of hotspots derived from the MODIS instrument. Information about location and date of burning events as provided by the proposed procedure may be viewed as complementary to the currently available official maps based on end-of-season Landsat imagery.