Calvert, AL
Calvert wildfire risk explained
Calvert sits at the 88th percentile nationally for wildfire risk to structures — in USFS's highest wildfire-risk band nationally — per USFS's Wildfire Risk to Communities model, built from its 222 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Calvert at the 90th percentile, close to its 88th-percentile risk score.
Where Calvert's buildings actually sit
222 buildings are counted in Calvert, and 91.9% 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 Calvert compares
Calvert's risk sits at a similar level relative to Alabama (94th percentile statewide) as it does nationally (88th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Calvert ranks 3,800 for wildfire risk (1 is highest) and 24,039 by building count (1 is largest). Within Alabama alone, it ranks 39 of 592 places by risk. See the full county-by-county picture for Alabama on its state page.
Shopping for coverage in Calvert
Calvert's 88th-percentile, very 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.
What would actually reduce this score
Because Direct exposure dominates in Calvert (91.9%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Calvert's figures come from
Every one of the two percentiles behind Calvert's 3,800-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Calvert's dominant direct exposure actually means, with real examples from across the dataset.