Homeowner Preferences for Wildfire Risk Mitigation in the Alaskan Wildland Urban Interface

Wildfire has become a larger threat to human life and property with the proliferation of homes into the wildland urban interface and warming climate. In this study we explored Alaskan homeowner preferences for wildfire risk mitigation in the wildland urban interface using discrete choice experiments to better understand the drivers of their risk mitigation actions. Estimates of willingness-to-pay for private mitigation actions are increased with wildfire risk reduction for all respondents. Willingness-to-pay for private mitigation is also positively associated with the presence of thinned fuel treatments on nearby public lands, but is estimated to decrease if cleared fuel treatments are present on public lands. Our study concludes that homeowners minimize wildfire risk while maintaining neighborhood amenity values. Additionally, findings suggest that there is an optimal amount of neighborhood participation to motivate individual risk mitigation actions, as well as having a say in the mitigation actions on public lands.

Detecting critical nodes in forest landscape networks to reduce wildfire spread

Although wildfires are an important ecological process in forested regions worldwide, they can cause significant economic damage and frequently create widespread health impacts. We propose a network optimization approach to plan wildfire fuel treatments that minimize the risk of fire spread in forested landscapes under an upper bound for total treated area. We used simulation modeling to estimate the probability of fire spread between pairs of forest sites and formulated a modified Critical Node Detection (CND) model that uses these estimated probabilities to find a pattern of fuel reduction treatments that minimizes the likely spread of fires across a landscape. We also present a problem formulation that includes control of the size and spatial contiguity of fuel treatments. We demonstrate the approach with a case study in Kootenay National Park, British Columbia, Canada, where we investigated prescribed burn options for reducing the risk of wildfire spread in the park area. Our results provide new insights into cost-effective planning to mitigate wildfire risk in forest landscapes. The approach should be applicable to other ecosystems with frequent wildfires.

Long-Term Effects of Fuel Reduction Treatments on Surface Fuel Loading in the Blue Mountains of Oregon

Fire exclusion and a lengthening fire season has resulted in an era of megafires. Fuel reduction treatments in forested ecosystems are designed to guard against future extreme wildfire behavior. Treatments create a heterogenous landscape and facilitate ecosystem function and resilience in fire-adapted forests of the western United States. Despite widespread recognition that repeated fuel treatments are needed to maintain desired stand characteristics over time, few field studies have evaluated treatment longevity. The Blue Mountains Fire and Fire Surrogate site in northeastern Oregon presented an opportunity to investigate woody fuel loading 15–17 years after four treatments: mechanical thin, prescribed burn, both thin and burn, and no treatment control. The principal findings were: (1) fine fuel load 15 years post-burn remained slightly below pre-treatment values; (2) rotten coarse fuel load was reduced post-burn, but sound coarse fuel was not altered by any active treatment; and (3) total woody fuel load 15–17 years post-treatment was similar to pre-treatment values. Understanding surface fuel loading is essential for predicting fire behavior. Overall, the effects of fuel reduction treatments on woody surface fuels were transitory in dry mixed conifer forests. Frequent maintenance treatments are recommended to protect values at risk in areas with high fire hazards. Quantifying the persistence of changes in forest conditions aids in the planning and analysis of future fuel treatments, along with scheduling maintenance of existing treated areas.

Combining wildfire behaviour simulations and complex network theory to support decision-making: A case-study in a Mediterranean region

<p>Wildfires represent one of the most devastating natural disasters, bearing relevant environmental and socioeconomic impacts. The Mediterranean region is characterized by large and recurring summer wildfires that often jeopardize people’s safety. Currently, wildfire management largely (if not entirely) relies on wildfire suppression, despite growing evidence of its inefficiency to control the larger and more intense wildfires [1]. Moreover, climate change is expected to significantly affect the Mediterranean region and further exacerbate such hazard, even if global warming does not exceed 1.5°C (target of the Paris Agreement) [2]. Hence, fire prevention measures based on landscape fuel reduction strategies are crucial to decrease the magnitude of the impacts of future wildfires.</p><p>Here, we used FlamMap, a widely applied fire spread simulation system, to estimate fire spread and behaviour properties in the Monchique region, a highly fire-prone area, located in Southern Portugal. Five weather scenarios were defined based on hierarchical clustering analysis of temperature, relative humidity, wind speed and direction data derived from the spreading days of large wildfires (larger than 100 ha) between 2001 and 2019. Complex networks were generated from fireline intensity and rate of spread estimates (proxies for the difficulty of suppression and safety) with the main goal of decreasing landscape fire hazard. More precisely, we aimed to: i) evaluate how different weather scenarios/conditions affect landscape connectivity; ii) identify the location of fuel treatments; and iii) assess the impact of the proposed fuel breaks on the fire properties. These challenges were addressed under the perspective of connectivity indexes and metrics from the field of network science.</p><p>The results show that, as expected, weather conditions affect both the amount of area with more intense wildfires and wildfire connectivity, with more severe weather conditions presenting the greatest hazards. Additionally, the identified optimal locations of fuel treatments were compared against the locations previously proposed for fuel breaks and the potential impact on fire properties of both was evaluated. Further analysis of the effectiveness of different management options (fraction of landscape treatment and extent of each intervention) will be assessed under the previously identified weather scenarios, considering the extent of high-intensity classes of fires and multiple landscape connectivity indexes. Based on our results, we discuss the best strategies to reduce wildfire hazard for different criteria and under different weather scenarios. Moreover, both methods can be used to assess fire transmission between land uses and then to identify the key values exposed. We demonstrate that combining network graphs and fire spread simulations have a large potential to support more informed decision-making and significantly wildfire impact mitigation.</p><p> </p><p>References</p><p>[1] Moreira, F., Ascoli, D., Safford, H. et al. (2020) Wildfire management in Mediterranean-type regions: paradigm change needed. Environmental Research Letters, 15, 011001. https://doi.org/10.1088/1748-9326/ab541e</p><p>[2] Turco, M., Rosa-Cánovas, J.J., Bedia, J. et al. (2018) Exacerbated fires in Mediterranean Europe due to anthropogenic warming projected with non-stationary climate-fire models. Nature Communications 9, 3821. https://doi.org/10.1038/s41467-018-06358-z</p>

Understanding How Fuel Treatments Interact With Climate and Biophysical Setting to Affect Fire, Water, and Forest Health: A Process-Based Modeling Approach

Fuel treatments are a key forest management practice used to reduce fire severity, increase water yield, and mitigate drought vulnerability. Climate change exacerbates the need for fuel treatments, with larger and more frequent wildfires, increasing water demand, and more severe drought. The effects of fuel treatments can be inconsistent and uncertain and can be altered by a variety of factors including the type of treatment, the biophysical features of the landscape, and climate. Variation in fuel treatment effects can occur even within forest stands and small watershed management units. Quantifying the likely magnitude of variation in treatment effects and identifying the dominant controls on those effects is needed to support fuel treatment planning directed at achieving specific fire, water, and forest health goals. This research aims to quantify and better understand how local differences in treatment, landscape features, and climate alter those fuel treatment effects. We address these questions using a mechanistic coupled ecohydrologic model—the Regional Hydro-Ecological Simulation System (RHESSys). We ran 13,500 scenarios covering a range of fuel treatment, biophysical, and climate conditions, for the Southern Sierra Nevada of California. Across fuel treatment type, biophysical, and climate parameters, we find nontrivial variation in fuel treatment effects on stand carbon, net primary productivity, evapotranspiration, and fire-related canopy structure variables. Response variable estimates range substantially, from increases (1–48%) to decreases (−13 to −175%) compared to untreated scenarios. The relative importance of parameters differs by response variable; however, fuel treatment method and intensity, plant accessible water storage capacity (PAWSC), and vegetation type consistently demonstrate a large influence across response variables. These parameters interact to produce non-linear effects. Results show that projections of fuel treatment effects based on singular mean parameter values (such as mean PAWSC) provide a limited picture of potential responses. Our findings emphasize the need for a more complete perspective when assessing expected fuel treatment outcomes, both in their effects and in the interacting biophysical and climatic parameters that drive them. This research also serves as a demonstration of methodology to assess the likely variation in potential effects of fuel treatments for a given planning unit.

Stand-Level Fuel Reduction Treatments and Fire Behaviour in Canadian Boreal Conifer Forests

Stand-level fuel reduction treatments in the Canadian boreal zone are used predominantly in community protection settings to alter the natural structure of dominant boreal conifer stands such as black spruce (Picea mariana (Mill.) BSP), jack pine (Pinus banksiana Lamb.) and lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia). The aim of these fuel treatments is to inhibit the development of fast-spreading, high-intensity crown fires that naturally occur in boreal forest ecosystems. We document fuel treatment design standards used in boreal forests in Canada and review data requirements and methodological approaches for investigating fuel treatment effects on fire behaviour. Through a series of illustrative examples and summaries of empirical observations, we explore the implications of data and modelling assumptions used to estimate fire behaviour in fuel-treated areas and identify insights about fuel treatment effectiveness in boreal conifer stands. Fuel treatments in black spruce, jack pine and lodgepole pine stands were generally effective at reducing modelled and observed fire behaviour and inhibiting crown fire development and spread under low to moderate fire weather conditions. Evidence suggests that fuel treatments in these fuel types will be ineffective when rates of spread and wind speeds are very high or extreme. High surface fuel loads combined with the relatively short stature of boreal conifer trees can further undermine fuel treatment efforts. Priority areas for future study include examining alternatives for managing surface fuel loads in treated stands, exploring the viability of alternative horizontal fuel reduction protocols such as clumped fuel configurations, and integrating suppression and containment strategies within the fuel treatment planning and design process.