Laytonville, CA
Laytonville wildfire risk explained
USFS scores Laytonville at the 87th national percentile for wildfire risk to structures (in USFS's highest wildfire-risk band nationally), a figure built from 966 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Laytonville's burn probability — fire likelihood with no building count factored in — sits at the 85th percentile nationally.
Laytonville's building exposure, zone by zone
Of Laytonville's 966 counted buildings, 91.7% carry Direct exposure and only 0% carry Minimal — a lopsided split that puts defensible-space clearing ahead of vents or roofing as the intervention worth doing first.
Laytonville against the rest of the country
Laytonville ranks lower within California (54th percentile statewide) than its 87th national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Laytonville ranks 4,149 for wildfire risk (1 is highest) and 12,177 by building count (1 is largest). Within California alone, it ranks 720 of 1,570 places by risk. See the full county-by-county picture for California on its state page.
Shopping for coverage in Laytonville
Because Laytonville is in California, a wildfire-hazard disclosure is legally required before a sale closes here — unusual nationally, since only these two states mandate it. The state's FAIR Plan alone carried 668,609 policies by the end of 2025. Full detail in the disclosure-law guide.
What would actually reduce this score
Because Direct exposure dominates in Laytonville (91.7%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Laytonville's figures come from
Laytonville's 87th-percentile score and its burn-probability figure both come from the same USFS workbook, documented in the methodology guide. The exposure-zones guide covers what Laytonville's dominant direct exposure actually means, with real examples from across the dataset.