Caryville, FL
How exposed is Caryville to wildfire?
Caryville's 187 buildings earn a 68th-percentile wildfire-risk score nationally under USFS's model — well above the national norm for wildfire risk. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Caryville at the 69th percentile, close to its 68th-percentile risk score.
Where Caryville's buildings actually sit
187 buildings are counted in Caryville, and 100% of them sit in USFS's Direct exposure zone — flame contact, not just ember cast, is the live possibility for most of them, against 0% rated Minimal.
How Caryville compares
Caryville's 68th national percentile looks worse in isolation than its 24th ranking inside Florida does — this place is on the milder end for its own state, by 44 points. Among the 31,521 US communities USFS scores, Caryville ranks 10,168 for wildfire risk (1 is highest) and 25,342 by building count (1 is largest). Within Florida alone, it ranks 727 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
Caryville's 68th-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
With 100% of Caryville in Direct exposure, defensible-space clearing and ember-resistant construction (vents, Class-A roofing) address the exposure this page's own numbers describe, not a generic checklist. See the home-hardening guide.
Where Caryville's figures come from
Every one of the two percentiles behind Caryville's 10,168-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Caryville's dominant direct exposure actually means, with real examples from across the dataset.