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Fire frequency and vulnerability in California [1]

['Miyuki Hino', 'Department Of City', 'Regional Planning', 'University Of North Carolina At Chapel Hill', 'Chapel Hill', 'Nc', 'United States Of America', 'Environment', 'Ecology', 'Energy Program']

Date: 2023-02

(A) Hazard: census tracts are color-coded based on the share of residences in Cal Fire-designated fire zones within the tract. A fire zone is any area with moderate, high, or very high fire hazard, in either local or state responsibility areas. None denotes zero properties in a fire zone, low is up to 25%, moderate is 25–75%, and high is over 75%. (B) Experience: census tracts are color-coded based on the number of fires that have affected residential property within them between 1990 and 2019. To be counted, a fire perimeter must include residential property; fires that do not contain any residential property within it are not included in this count. Properties within fire perimeters may or may not have been damaged by the fire. None denotes zero fires within the tract, low is 1–2, moderate is 3–5, and high is six or more. (C) Damage: census tracts are color-coded based on the single most damaging fire experienced between 1990 and 2019, as defined by the number of residential properties within a single fire perimeter. None represents no properties, low is 1–10 properties, moderate is 11–100 properties, and high is over 100 properties. Base layer for all three maps is from the US Census Bureau ( https://www.census.gov/programs-surveys/geography/technical-documentation/user-note/tiger-geo-line.2019.html ).

The three metrics differ substantially in their geographic pattern, as shown in Fig 1 . In particular, while FHSZ maps suggest uniformly high hazard in the inland mountains and northern forests, the experience and damage maps show much more variation within those regions. The coast features high hazard levels but a mix of experience and damage levels. All three maps point to a low level of fire concern in the Central Valley and urbanized areas.

Social and economic characteristics of communities at risk

The three metrics also paint different portraits of the communities who face wildfire risk. Incomes are relatively higher in communities with high fire hazard according to the FHSZ maps and lower in communities with high fire experience (Fig 2). Median incomes across high-hazard tracts average $97,643, compared to $76,642 in tracts with no fire hazard. Results are similar with fire damage: across high-damage tracts, the average is $101,924, compared to $79,661 in a tract that has not experienced any damaging fires. Conversely, incomes are lowest in communities with high fire experience. On average, communities that have experienced six or more fires since 1990 have a median income of $66,128, compared to $79,661 in communities with no fire experience and $100,063 in communities with 1–2 fires. The trend holds with block groups rather than tracts: the highest-experience block groups average $60,266 in median household income, compared to $82,679 for those with no fires and $101,412 for those with 1–2 fires (Fig A in S1 Appendix). The differences between the three metrics also persist when examining other indicators of financial resources such as assessed property values (Fig B in S1 Appendix). Alternative groupings, including the distribution of incomes at every level of fire experience, from 0 to 21 fires, are shown in Figs C and D in S1 Appendix.

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TIFF original image Download: Fig 2. The relationship between income and fire risk varies across indicators. When categorized by fire hazard or fire damage, median incomes are steady or increase with higher risk. However, communities with high fire experience average lower incomes than communities with low or no fire experience. Histograms show distribution of census tracts by metric, and dashed lines show group means. n denotes the number of census tracts in each group. https://doi.org/10.1371/journal.pclm.0000087.g002

Conclusions about the overlap between fire risk and low-income populations depend on the metric. Of the tracts that are high hazard, 11% are in the bottom quintile of income, and 33% are in the top quintile in income. However, with fire experience, the pattern is the opposite: 34% of high-experience tracts are in the bottom income quintile, and 8% are in the top quintile, indicating that fire experience is skewed toward communities with lower incomes.

While incomes differ sharply between high-hazard and high-experience communities, the pattern for racial composition is less varied (Fig E in S1 Appendix). The average share of the population that is white increases with fire risk for all three metrics. High hazard, experience, and damage tracts average 79%, 83%, and 80% white, respectively. This pattern in part reflects the concentration of non-white populations in urban centers with low fire risk.

The trajectory of real estate prices provides another window on the way that communities evolve with respect to different dimensions of fire risk. Property values are known to be sensitive to the effects of fire shocks, at least temporarily. It is difficult to discern the cumulative effects of repeated exposures to fires because communities with high fire frequency generally do not have 15 fire-free years, followed by 15 years of experiencing fire. Rather, effects would likely emerge and grow over time, with less of a clear time-delineated shock.

From 1990 through 2019, home prices have appreciated more in communities with no fire experience than in communities with high fire experience (Fig 3). Among the no-experience tracts, property prices increased by a factor of 2.91 (median; mean = 3.01) over that time period. In contrast, among tracts with six or more fires from 1990–2019, the median price appreciation was 2.34 (mean = 2.35). The gap between the two sets of communities has emerged in particular over the 2010–2019 time period. The discrepancies in property value appreciation persist when considering only tracts with high fire hazard: among that subset, those with no fire experience saw prices grow by 2.77 times, and those with six or more fires grew by a factor of 2.31.

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TIFF original image Download: Fig 3. Property prices have appreciated more slowly in communities with high levels of fire experience. (A) HPI values over the last 30 years for communities with different levels of fire experience. Lighter shades indicate less fire experience. (B) HPI values among four groups: tracts with no fire experience, tracts with high fire experience, tracts with a single damaging fire in 2003, and tracts where most of their fire experience has occurred in the last decade. https://doi.org/10.1371/journal.pclm.0000087.g003

We conduct several additional comparisons to further examine how price appreciation relates to fire incidence. We identified a set of 13 “recent fire” tracts with most of their fire experience in the past decade: four or more fires from 2010–2019 and three or fewer from 1990–2010. We refer to this group as the “recent fires” group. This group’s home price appreciation closely tracks that of the communities with no fire experience until the late 2000s, with prices dropping farther during the recession and growing more slowly after that (Fig 3, green line).

As a final comparison group, we examine tracts that experienced a single severe fire that affected over 100 homes within the tract. To enable straightforward comparison, we include ten tracts where this single fire occurred in 2003. The trajectory of their home price indices is shown in Fig 3 (purple line). While this group shows slower growth in the 1990s and early 2000s, their price growth has outpaced both sets of communities with higher fire frequency since then. In conjunction with other findings that the negative effects of a fire shock dissipate over time [5], this trend suggests that the current differences among groups with different fire frequencies are not due to the long-term shocks of a single event.

We use the differences in property value appreciation as a way of exploring the consequences of high fire experience. This calculation is based on the concept that the substantial differences in property values across fire experience categories are due to fire-induced differences in annual price increases that have accumulated over time. However, many factors influence property values beyond fire incidence, and we do not aim to isolate the impacts of fires here.

Grouping all tracts based on the fire experience in their tract (as in Fig 3), the median annual growth rate from 1990 through 2019 was 4.38% among high experience tracts and 4.77% among tracts with no fire experience. The approximately 182,900 single-family homes and condominiums in high-experience tracts comprise $41.9B in assessed value as of 2017. In a year in which they appreciate at 4.38% rather than 4.77%, those homeowners accrue approximately $165M less in property value. Over the 2010 to 2019 period, median growth rates were 4.35% for the high-experience group and 5.85% for those with no experience; using those appreciation rates, the annual difference increases to $630M. These estimates are based on assessed values, which are often lower than market values in California.

In comparison, the annual losses from wildfires as documented by Cal Fire range from the hundreds of millions in relatively low-loss years ($148M in 2016, $404M in 2019) to the billions in severe years—the Camp Fire alone represents about $12B in losses [22]. These loss estimates are based on the cost to replace the property and contents damaged or destroyed by fire, smoke, water, and overhaul. They do not include suppression costs or indirect loss, such as reductions in property value or business interruption losses. Thus, the indicative magnitude of differences in property value appreciation are comparable to direct losses in years without catastrophic fires but much less than direct damages from the most destructive fires.

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[1] Url: https://journals.plos.org/climate/article?id=10.1371/journal.pclm.0000087

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