Houses & WUI

Over the past 30 years, the cost of wildfire suppression and homes lost to wildfire in the U.S. have increased dramatically, driven in part by the expansion of the wildland-urban interface (WUI), where buildings and wildland vegetation meet. In response, the wildfire management community has devoted substantial effort to better understand where buildings and vegetation co-occur, and to establish outreach programs to reduce wildfire damage to homes. However, the extent to which the location of buildings affected by wildfire overlaps the WUI, and where and when outreach programs were established relative to wildfire, is unclear. We found that most threatened and destroyed buildings in the conterminous U.S. were within the WUI (59% and 69%, respectively), but this varied considerably among states. Fires with the greatest building loss were close to outreach programs (such as Firewise), but for 76% of destroyed buildings, the nearest outreach program was established post-wildfire. In these locations, as well as places new to the WUI or in areas where the fire regime is predicted to change, pre-emptive outreach could improve the likelihood of building survival and reduce the human and financial costs of structure loss.

Wildfires are a major threat to people and property in Wildland Urban Interface (WUI) communities
worldwide, but while the patterns of the WUI in North America, Europe and Oceania have been studied
before, this is not the case in Latin America. Our goals were to a) map WUI areas in central Argentina, and
b) assess wildfire exposure for WUI communities in relation to historic fires, with special emphasis on
large fires and estimated burn probability based on an empirical model. We mapped the WUI in the
mountains of central Argentina (810,000 ha), after digitizing the location of 276,700 buildings and
deriving vegetation maps from satellite imagery. The areas where houses and wildland vegetation
intermingle were classified as Intermix WUI (housing density > 6.17 hu/km2 and wildland vegetation
cover > 50%), and the areas where wildland vegetation abuts settlements were classified as Interface
WUI (housing density > 6.17 hu/km2, wildland vegetation cover < 50%, but within 600 m of a vegetated patch larger than 5 km2). We generated burn probability maps based on historical fire data from 1999 to 2011; as well as from an empirical model of fire frequency. WUI areas occupied 15% of our study area and contained 144,000 buildings (52%). Most WUI area was Intermix WUI, but most WUI buildings were in the Interface WUI. Our findings suggest that central Argentina has a WUI fire problem. WUI areas included most of the buildings exposed to wildfires and most of the buildings located in areas of higher burn probability. Our findings can help focus fire management activities in areas of higher risk, and ultimately provide support for landscape management and planning aimed at reducing wildfire risk in WUI communities.

The hazards-of-place model posits that vulnerability to environmental hazards depends on both biophysica and social factors. Biophysical factors determine where wildfire potential is elevated, whereas social factors determin where and how people are affected by wildfire. We evaluated place vulnerability to wildfire hazards in the coterminou US. We developed a social vulnerability index using principal component analysis and evaluated it against existin measures of wildfire potential and wildland–urban interface designations. We created maps showing the coincidence o social vulnerability and wildfire potential to identify places according to their vulnerability to wildfire. We found tha places with high wildfire potential have, on average, lower social vulnerability than other places, but nearly 10% of al housing in places with high wildfire potential also exhibits high social vulnerability. We summarised our data by states t evaluate trends at a subnational level. Although some regions, such as the South-east, had more housing in places with hig wildfire vulnerability, other regions, such as the upper Midwest, exhibited higher rates of vulnerability than expected. Ou results can help to inform wildfire prevention, mitigation and recovery planning, as well as reduce wildfire hazard affecting vulnerable places and populations.

Following the loss of homes to wildfire, when risk has been made apparent, homeowners must decide whethe to rebuild, and choose materials and vegetation, while local governments guide recovery and rebuilding. As wildfires ar smaller and more localised than other disasters, it is unclear if recovery after wildfire results in policy change and adaptation decreasing assets at risk, or if recovery encourages reinvestment in hazard-prone areas. We studied three wildfires on th Colorado Front Range from 2010 to 2012 that each destroyed over 150 homes, describing policy response and characterisin the built environment after wildfire. In each location, we found some adaptation, through better-mitigated homes an stronger building and vegetation mitigation standards, but also extensive reinvestment in hazard-prone environments, wit governmental support. Despite suggestions that disaster can lead to substantial policy change and elevate the role of land-us planning, we saw only modest reforms: local governments did not revise land-use regulations; a statewide task forc considered but did not require standards for building and vegetation mitigation; and only one jurisdiction strengthened it building and vegetation mitigation standards. Experiences in Colorado suggest that time after wildfire either does no provide extensive opportunities for adaptation in the built environment, or that these opportunities are easily missed.

One challenge in the effort to conserve biodiversity is identifying where to prioritize resources for active land management. Cost–benefit analyses have been used successfully as a conservation tool to identify sites that provide the greatest conservation benefit per unit cost. Our goal was to apply cost–benefit analysis to the question of how to prioritize land management efforts, in our case the application of prescribed fire to natural landscapes in Wisconsin, USA. We quantified and mapped frequently burned communities and prioritized management units based on a suite of indices that captured ecological benefits, management effort, and the feasibility of successful long- term manage-ment actions. Data for these indices came from LANDFIRE, Wisconsin’s Wildlife Action Plan, and a nationwide wildland–urban interface assessment. We found that the majority of frequently burned vegetation types occurred in the southern portion of the state. How-ever, the highest priority areas for applying prescribed fire occurred in the central, north-west, and northeast portion of the state where frequently burned vegetation patches were larger and where identified areas of high biological importance area occurred. Although our focus was on the use of prescribed fire in Wisconsin, our methods can be adapted to prioritize other land management activities. Such prioritization is necessary to achieve the greatest possible benefits from limited funding for land management actions, and our results show that it is feasible at scales that are relevant for land management decisions.