Wildfire spread and behavior can be limited by fuel treatments, even if their effects can vary according to a number of factors including type, intensity, extension, and spatial arrangement. In this ...work, we simulated the response of key wildfire exposure metrics to variations in the percentage of treated area, treatment unit size, and spatial arrangement of fuel treatments under different wind intensities. The study was carried out in a fire-prone 625 km2 agro-pastoral area mostly covered by herbaceous fuels, and located in Northern Sardinia, Italy. We constrained the selection of fuel treatment units to areas covered by specific herbaceous land use classes and low terrain slope (<10%). We treated 2%, 5% and 8% of the landscape area, and identified priority sites to locate the fuel treatment units for all treatment alternatives. The fuel treatment alternatives were designed create diverse mosaics of disconnected treatment units with different sizes (0.5–10 ha, LOW strategy; 10–25 ha, MED strategy; 25–50 ha, LAR strategy); in addition, treatment units in a 100-m buffer around the road network (ROAD strategy) were tested. We assessed pre- and post-treatment wildfire behavior by the Minimum Travel Time (MTT) fire spread algorithm. The simulations replicated a set of southwestern wind speed scenarios (16, 24 and 32 km h−1) and the driest fuel moisture conditions observed in the study area. Our results showed that fuel treatments implemented near the existing road network were significantly more efficient than the other alternatives, and this difference was amplified at the highest wind speed. Moreover, the largest treatment unit sizes were the most effective in containing wildfire growth. As expected, increasing the percentage of the landscape treated and reducing wind speed lowered fire exposure profiles for all fuel treatment alternatives, and this was observed at both the landscape scale and for highly valued resources. The methodology presented in this study can support the design and optimization of fuel management programs and policies in agro-pastoral areas of the Mediterranean Basin and herbaceous type landscapes elsewhere, where recurrent grassland fires pose a threat to rural communities, farms and infrastructures.
•Fuel treatment spatial arrangement, unit size and area treated affect wildfire spread.•Treating fuels nearby roads is the most efficient strategy for containing wildfires.•Fuel treatments on large size units perform better than those on small units.•Differences in the effectiveness of fuel treatments are amplified at high wind speed.
Wildfire risk as a socioecological pathology Fischer, A Paige; Thomas A Spies; Toddi A Steelman ...
Frontiers in ecology and the environment,
June 2016, Letnik:
14, Številka:
5
Journal Article
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Wildfire risk in temperate forests has become a nearly intractable problem that can be characterized as a socioecological âpathologyâ: that is, a set of complex and problematic interactions among ...social and ecological systems across multiple spatial and temporal scales. Assessments of wildfire risk could benefit from recognizing and accounting for these interactions in terms of socioecological systems, also known as coupled natural and human systems (CNHS). We characterize the primary social and ecological dimensions of the wildfire risk pathology, paying particular attention to the governance system around wildfire risk, and suggest strategies to mitigate the pathology through innovative planning approaches, analytical tools, and policies. We caution that even with a clear understanding of the problem and possible solutions, the system by which human actors govern fireâprone forests may evolve incrementally in imperfect ways and can be expected to resist change even as we learn better ways to manage CNHS.
The 2018 Camp fire destroyed the town of Paradise, California and resulted in 82 fatalities, the worst wildfire disaster in the US to date. Future disasters of similar or greater magnitude are ...inevitable given predicted climate change but remain highly uncertain in terms of location and timing. As with other natural disasters, simulation models are one of the primary tools to map risk and design prevention strategies. However, risk assessments have focused on estimation of mean values rather than predicting extreme events that are increasingly becoming a reality in many parts of the globe. Using the western US as a study area, we synthesized newer wildfire simulation and building location data (54 million fires, 25 million building locations) and compared the outputs to several sources of observed exposure data. The simulations used synchronized weather among spatial simulation subunits, thereby providing estimates of extreme fire seasons, fire events within them, and exceedance probabilities at multiple scales. We found that annual area burned was accurately replicated by simulations but building exposure was substantially overestimated, although the relatively small historical sample size might have influenced the comparison. We identified extreme fire seasons in the simulation record (10,000 fire years) that exceeded historical fire seasons by 278% in terms of area burned, and 1255% in terms of buildings exposed, under contemporary climate. Simulated building exposure peaked in specific regions along gradients of building density and burnable fuels. The study is the first to explore large scale extreme wildfire exposure in terms of both annual variability and magnitude, providing a broad foundation of methods to advance wildfire disaster prediction.
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•We used wildfire simulation data to predict building exposure in the western US.•We examined the relative effect of building versus fuel density on exposure.•Maximum exposure was observed at building densities between 1400 and 1500 per km2.•Building-fuels density gradients into developed areas affected maximum exposure.•Annual building exposure in extreme fire seasons exceeded historical by 1255%.
Widespread outbreaks of mountain pine beetle in North America have drawn the attention of scientists, forest managers, and the public. There is strong evidence that climate change has contributed to ...the extent and severity of recent outbreaks. Scientists are interested in quantifying relationships between bark beetle population dynamics and trends in climate. Process models that simulate climate suitability for mountain pine beetle outbreaks have advanced our understanding of beetle population dynamics; however, there are few studies that have assessed their accuracy across multiple outbreaks or at larger spatial scales. This study used the observed number of trees killed by mountain pine beetles per square kilometer in Oregon and Washington, USA, over the past three decades to quantify and assess the influence of climate and weather variables on beetle activity over longer time periods and larger scales than previously studied. Influences of temperature and precipitation in addition to process model output variables were assessed at annual and climatological time scales. The statistical analysis showed that new attacks are more likely to occur at locations with climatological mean August temperatures >15°C. After controlling for beetle pressure, the variables with the largest effect on the odds of an outbreak exceeding a certain size were minimum winter temperature (positive relationship) and drought conditions in current and previous years. Precipitation levels in the year prior to the outbreak had a positive effect, possibly an indication of the influence of this driver on brood size. Two-year cumulative precipitation had a negative effect, a possible indication of the influence of drought on tree stress. Among the process model variables, cold tolerance was the strongest indicator of an outbreak increasing to epidemic size. A weather suitability index developed from the regression analysis indicated a 2.5× increase in the odds of outbreak at locations with highly suitable weather vs. locations with low suitability. The models were useful for estimating expected amounts of damage (total area with outbreaks) and for quantifying the contribution of climate to total damage. Overall, the results confirm the importance of climate and weather on the spatial expansion of bark beetle outbreaks over time.
We describe recent advances in biophysical and social aspects of risk and their potential combined contribution to improve mitigation planning on fire‐prone landscapes. The methods and tools provide ...an improved method for defining the spatial extent of wildfire risk to communities compared to current planning processes. They also propose an expanded role for social science to improve understanding of community‐wide risk perceptions and to predict property owners’ capacities and willingness to mitigate risk by treating hazardous fuels and reducing the susceptibility of dwellings. In particular, we identify spatial scale mismatches in wildfire mitigation planning and their potential adverse impact on risk mitigation goals. Studies in other fire‐prone regions suggest that these scale mismatches are widespread and contribute to continued wildfire dwelling losses. We discuss how risk perceptions and behavior contribute to scale mismatches and how they can be minimized through integrated analyses of landscape wildfire transmission and social factors that describe the potential for collaboration among landowners and land management agencies. These concepts are then used to outline an integrated socioecological planning framework to identify optimal strategies for local community risk mitigation and improve landscape‐scale prioritization of fuel management investments by government entities.
We simulated fuel reduction treatments on a 16,000
ha study area in Oregon, US, to examine tradeoffs between placing fuel treatments near residential structures within an urban interface, versus ...treating stands in the adjacent wildlands to meet forest health and ecological restoration goals. The treatment strategies were evaluated by simulating 10,000 wildfires with random ignition locations and calculating burn probabilities by 0.5
m flame length categories for each 30
m
×
30
m pixel in the study area. The burn conditions for the wildfires were chosen to replicate severe fire events based on 97th percentile historic weather conditions. The burn probabilities were used to calculate wildfire risk profiles for each of the 170 residential structures within the urban interface, and to estimate the expected (probabilistic) wildfire mortality of large trees (>53.3
cm) that are a key indicator of stand restoration objectives. Expected wildfire mortality for large trees was calculated by building flame length mortality functions using the Forest Vegetation Simulator, and subsequently applying these functions to the burn probability outputs. Results suggested that treatments on a relatively minor percentage of the landscape (10%) resulted in a roughly 70% reduction in the expected wildfire loss of large trees for the restoration scenario. Treating stands near residential structures resulted in a higher expected loss of large trees, but relatively lower burn probability and flame length within structure buffers. Substantial reduction in burn probability and flame length around structures was also observed in the restoration scenario where fuel treatments were located 5–10
km distant. These findings quantify off-site fuel treatment effects that are not analyzed in previous landscape fuel management studies. The study highlights tradeoffs between ecological management objectives on wildlands and the protection of residential structures in the urban interface. We also advance the application of quantitative risk analysis to the problem of wildfire threat assessment.
We assessed potential economic losses and transmission to residential houses from wildland fires in a rural area of central Navarra (Spain). Expected losses were quantified at the individual ...structure level (n = 306) in 14 rural communities by combining fire model predictions of burn probability and fire intensity with susceptibility functions derived from expert judgement. Fire exposure was estimated by simulating 50,000 fire events that replicated extreme (97th percentile) historical fire weather conditions. Spatial ignition probabilities were used in the simulations to account for non-random ignitions, and were estimated from a fire occurrence model generated with an artificial neural network. The results showed that ignition probability explained most of spatial variation in risk, with economic value of structures having only a minor effect. Average expected loss to residential houses from a single wildfire event in the study area was 7955€, and ranged from a low of 740 to the high of 28,725€. Major fire flow-paths were analyzed to understand fire transmission from surrounding municipalities and showed that incoming fires from the north exhibited strong pathways into the core of the study area, and fires spreading from the south had the highest likelihood of reaching target residential structures from the longest distances (>5 km). Community firesheds revealed the scale of risk to communities and extended well beyond administrative boundaries. The results provided a quantitative risk assessment that can be used by insurance companies and local landscape managers to prioritize and allocate investments to treat wildland fuels and identify clusters of high expected loss within communities. The methodological framework can be extended to other fire-prone southern European Union countries where communities are threatened by large wildland fires.
We used simulation modeling to assess potential climate change impacts on wildfire exposure in Italy and Corsica (France). Weather data were obtained from a regional climate model for the period ...1981–2070 using the IPCC A1B emissions scenario. Wildfire simulations were performed with the minimum travel time fire spread algorithm using predicted fuel moisture, wind speed, and wind direction to simulate expected changes in weather for three climatic periods (1981–2010, 2011–2040, and 2041–2070). Overall, the wildfire simulations showed very slight changes in flame length, while other outputs such as burn probability and fire size increased significantly in the second future period (2041–2070), especially in the southern portion of the study area. The projected changes fuel moisture could result in a lengthening of the fire season for the entire study area. This work represents the first application in Europe of a methodology based on high resolution (250 m) landscape wildfire modeling to assess potential impacts of climate changes on wildfire exposure at a national scale. The findings can provide information and support in wildfire management planning and fire risk mitigation activities.
•We evaluated fuel treatment strategies to reduce fire losses in Mediterranean area.•Treatment effectiveness was assessed using the MTT fire spread modeling approach.•All strategies decreased fire ...exposure profiles compared to untreated condition.•We found significant variations in fire exposure among the diverse strategies.•Treatments nearby roads were the most effective in reducing wildfire losses.
The goal of this work is to evaluate by a modeling approach the effectiveness of alternative fuel treatment strategies to reduce potential losses from wildfires in Mediterranean areas. We compared strategic fuel treatments located near specific human values vs random locations, and treated 3, 9 and 15% of a 68,000ha study area located in Sardinia, Italy. The effectiveness of each fuel treatment was assessed by simulating 25,000 wildfires using the MTT fire spread algorithm. The simulations replicated severe wildfires observed around the study area, using historic weather and fuel moisture conditions (97th percentile). Wildfire exposure profiles for the study area as a whole and for locations with specific values of interest were analyzed. Results indicated significant variations in wildfire exposure among and within the fuel management strategies and treatment intensities. The simulated mitigation strategies substantially decreased the average wildfire exposure with respect to the untreated condition, and this effect was unequivocal for all strategies. Increasing the percentage of land treated improved the effectiveness of all fuel treatment strategies. The strategy based on road protection provided the highest performances for several wildfire exposure indicators. The methodology presented in this work can be applied to facilitate the design of fuel management programs and support policy decisions to address growing wildfire risk in the region. This work is one of the first applications of fire simulation modeling to evaluate fuel management effectiveness on wildfire risk mitigation in the Mediterranean areas.
Expansion of the wildland–urban interface (WUI) and the increasing size and number of wildfires has policy-makers and wildfire managers seeking ways to reduce wildfire risk in communities located ...near fire-prone forests. It is widely acknowledged that homeowners can reduce their exposure to wildfire risk by using nonflammable building materials and reducing tree density near the home, among other actions. Although these actions can reduce the vulnerability of homes to wildfire, many homeowners do not take them. We examined the influence of risk factors on homeowners’ perceived wildfire risk components using a survey of WUI homeowners in central Oregon (USA) and biophysical data that described wildfire risk as predicted by wildfire simulation models, past wildfire, and vegetation characteristics. Our analysis included homeowners’ perceptions of the likelihood of wildfire and resulting damage, and examined how these factors contribute to homeowners’ likelihood to conduct mitigation actions. We developed an empirical model of homeowners’ risk perceptions and mitigation behavior, which served as input into an agent-based model to examine potential landscape and behavior changes over 50 years. We found homeowners’ wildfire risk perceptions to be positively correlated with hazardous conditions predicted by fuel models and weakly predictive of mitigation behavior. Homeowners’ perceived chance of wildfire was positively correlated with actual probability of wildfire, while their perceived chance of damage to the home was positively correlated with potential wildfire intensity. Wildfire risk perceptions also were found to be correlated with past wildfire experience. Our results suggest that homeowners may be savvy observers of landscape conditions, which act as “feedbacks” that enhance homeowners’ concerns about wildfire hazard and motivate them to take mitigation action. Alternatively, homeowners living in hazardous locations are somehow receiving the message that they need to take protective measures. Mitigation compliance output from the agent-based model suggests that completion of mitigation actions is likely to increase over 50 years under various scenarios.
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