Chaires, FL
Chaires wildfire risk explained
USFS scores Chaires at the 74th national percentile for wildfire risk to structures (well above the national norm for wildfire risk), a figure built from 240 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Chaires's burn probability — fire likelihood with no building count factored in — sits at the 74th percentile nationally.
What "at risk" means for the buildings here
97.9% of Chaires's 240 buildings sit in USFS's Direct exposure zone, roughly 235 structures close enough to burnable vegetation for flame contact, not just embers — 2.1% fall in the Indirect, ember-only zone and 0% are Minimal.
Chaires against the rest of the country
Chaires ranks lower within Florida (34th percentile statewide) than its 74th national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Chaires ranks 8,156 for wildfire risk (1 is highest) and 23,451 by building count (1 is largest). Within Florida alone, it ranks 628 of 955 places by risk. See the full county-by-county picture for Florida on its state page.
What this risk score means for insurance
Chaires's 74th-percentile, high rating is the kind of score behind a broader national pattern: insurers pulling back from the highest wildfire-risk markets, non-renewing or declining new policies outright, most visibly in California. Shopping around, not assuming automatic renewal, tends to matter here.
Lowering exposure, not just insuring around it
Because Direct exposure dominates in Chaires (97.9%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Chaires's figures come from
The methodology guide shows exactly how USFS turned 240 counted buildings into the percentiles shown above for Chaires. The exposure-zones guide covers what Chaires's dominant direct exposure actually means, with real examples from across the dataset.