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Abstract The scale of wildfire impacts to the built environment is growing and will likely continue under rising average global temperatures. We investigate whether and at what destruction threshold wildfires have influenced human mobility patterns by examining the migration effects of the most destructive wildfires in the contiguous U.S. between 1999 and 2020. We find that only the most extreme wildfires (258+ structures destroyed) influenced migration patterns. In contrast, the majority of wildfires examined were less destructive and did not cause significant changes to out- or in-migration. These findings suggest that, for the past two decades, the influence of wildfire on population mobility was rare and operated primarily through destruction of the built environment. 

Abstract An environmental event that damages housing and the built environment may result in either a short‐ or long‐term out‐migration response, depending on residents' recovery decisions and hazard tolerance. If residents move only in the immediate disaster aftermath, then out‐migration will be elevated only in the short‐term. However, if disasters increase residents' concerns about future risk, heighten vulnerability, or harm the local economy, then out‐migration may be elevated for years after an event. The substantive aim of this research brief is to evaluate hypotheses about short‐ and long‐term out‐migration responses to the highly destructive 2005 hurricane season in the Gulf of Mexico. The methodological aim is to demonstrate a difference‐in‐differences (DID) approach analysing time series data from Gulf Coast counties to compare short‐ and long‐differences in out‐migration probabilities in the treatment and control counties. We find a large short‐term out‐migration response and a smaller sustained increase for the disaster‐affected coastal counties. 

Abstract During the first year of the COVID‐19 pandemic, federal spending on government safety net programs in the United States increased dramatically. Despite this unparalleled spending, government safety nets were widely critiqued for failing to fully meet many households' needs. Disaster research suggests thatinformalmodes of social support often emerge during times of disruption, such as the first year of the pandemic. However, use of formal government programs and informal support are rarely examined relative to each other, resulting in an incomplete picture of how households navigate disaster impacts and financial shocks. This study compares estimates of informal social support to formal government program use in the rural U.S. West, drawing on data from a rapid response survey fielded during the summer of 2020 and the 2021 Annual Social and Economic Supplement of the Current Population Survey (CPS‐ASEC). We find that informal social support systems were, on aggregate, used almost as extensively as long‐standing government programs. Our findings highlight the critical role of person‐to‐person assistance, such as sharing financial resources, among rural households during a disruptive disaster period. Routine and standardized data collection on these informal support behaviors could improve future disaster research and policy responses, especially among rural populations. 

We examine the utility of data on active and vacant residential addresses to inform local and timely monitoring and assessments of how areas impacted by wildfires and extreme weather events more broadly lose (or not) and subsequently recover (or not) their populations. Provided by the U.S. Postal Service to the U.S. Department of Housing and Urban Development and other users, these data are an underutilized and potentially valuable tool to study population change in disasteraffected areas for at least three reasons. First, as they are aggregated to the ZIP + 4 level, they permit highly local portraits of residential and, indirectly, of population change. Second, they are tabulated on a quarterly basis starting in 2010 through the most recent quarter, thereby allowing for timely assessments than other data sources. Third, one mechanism of population change—namely, underlying changes in residential occupancies and vacancies—is explicit in the data. Our findings show that these data are sufficient for detecting signals of residential and, indirectly, of population change during and after particularly damaging wildfires; however, there is also noticeable variation across cases that requires further investigations into, for example, the guidance the U.S. Postal Services provides its postal offices and carriers to classify addresses as vacant. 

As the number of highly destructive wildfires grows, it is increasingly important to understand the long-term changes that occur to fire-affected places. Integrating approaches from social and biophysical science, we document two forms of neighborhood change following the 2018 Camp Fire in the United States, examining the more than 17,000 residential structures within the burn footprint. We found that mobile or motor homes, lowervalue residences, and absentee owner residences had a significantly higher probability of being destroyed, providing evidence that housing stock filtering facilitated socially stratified patterns of physical damage. While the relationship between building value and destruction probability could be explained by measures of building density and distance to nearby roads, building type remained an independent predictor of structure loss that we could not fully explain by adding environmental covariates to our models. Using a geospatial machine learning technique, we then identified buildings that had been reconstructed within the burn footprint 20 months after the fire. We found that reconstructed buildings were more likely to have been owner-occupied prior to the fire and had higher average pre-fire property value, suggesting an emerging pattern of cost-burden gentrification. Our findings illustrate the importance of examining the built environment as a driver of socially uneven disaster impacts. Wildfire mitigation strategies are needed for mobile and motor home residents, renters, low-income residents, and dense neighborhoods. 

Abstract This paper describes a dataset mined from the public archive (1999–2020) of the US National Incident Management System Incident Status Summary (ICS-209) forms (a total of 187,160 reports for 35,170 incidents, including 34,478 wildland fires). This system captures detailed daily/regular information on incident development and response, including social and economic impacts. Most (98.4%) reports are wildland fire-related, with other incident types including hurricane, hazardous materials, flood, tornado, search and rescue, civil unrest, and winter storms. The archive, although publicly available, has been difficult to use for research due to multiple record formats, inconsistent data entry, and no clean pathway from individual reports to high-level incident analysis. Here, we describe the open-source, reproducible methods used to produce a science-grade version of the data, including formal connections made to other published wildland fire data products. Among other applications, this integrated and spatially augmented dataset enables exploration of the daily progression of the most costly, damaging, and deadly environmental-hazard events in recent US history. 

Abstract We introduce the consideration of human migration into research on economic losses from extreme weather disasters. Taking a comparative case study approach and using data from the Federal Reserve Bank of New York/Equifax Consumer Credit Panel, we document the size of economic losses attributable to migration from 23 disaster-affected areas in the United States before, during, and after some of the most costly hurricanes, tornadoes, and wildfires on record. We then employ demographic standardization and decomposition to determine if these losses primarily reflect changes in out-migration or the economic resources that migrants take with them. Finally, we consider the implications of these losses for changing spatial inequality in the United States. While disaster-affected areas and their populations differ in their experiences of and responses to extreme weather disasters, we generally find that, relative to the year before an extreme weather disaster, economic losses via migration from disaster-affected areas increase the year of and after the disaster, these changes primarily reflect changes in out-migration (vs. the economic resources that migrants take with them), and these losses briefly disrupt the status quo by temporarily reducing spatial inequality.