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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 largefire 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.

We characterized wildfire transmission and exposure within a matrix of large land tenures (federal, state, and private) surrounding 56 communities within a 3.3 million ha fire prone region of central Oregon US. Wildfire simulation and network analysis were used to quantify the exchange of fire among land tenures and communities and analyze the relative contributions of human versus natural ignitions to wildfire exposure. Among the land tenures examined, the area burned by incoming fires averaged 57% of the total burned area. Community exposure from incoming fires ignited on surrounding land tenures accounted for 67% of the total area burned. The number of land tenures contributing wildfire to individual communities and surrounding wildland urban interface (WUI) varied from 3 to 20. Community firesheds, i.e. the area where ignitions can spawn fires that can burn into the WUI, covered 40% of the landscape, and were 5.5 times larger than the combined area of the community core and WUI. For the major land tenures within the study area, the amount of incoming versus outgoing fire was relatively constant, with some exceptions. The study provides a multi-scale characterization of wildfire networks within a large, mixed tenure and fire prone landscape, and illustrates the connectivity of risk between communities and the surrounding wildlands. We use the findings to discuss how scale mismatches in local wildfire governance result from disconnected planning systems and disparate fire management objectives among the large landowners (federal, state, private) and local communities. Local and regional risk planning processes can adopt our concepts and methods to better define and map the scale of wildfire risk from large fire events and incorporate wildfire network and connectivity concepts into risk assessments.

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 ([Formula: see text] = 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.

A nonparametric test for assessing the independence between a directional random variable (circular or spherical, as particular cases) and a linear one is proposed in this paper. The statistic is based on the squared distance between nonparametric kernel density estimates and its calibration is done by a permutation approach. The size and power characteristics of various variants of the test are investigated and compared with those for classical correlation-based tests of independence in an extensive simulation study. Finally, the best-performing variant of the new test is applied in the analysis of the relation between the orientation and size of Portuguese wildfires.

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.

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.

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.

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 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.

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.