Montezuma, IA
Montezuma wildfire risk explained
Montezuma's 1,003 buildings earn a 63rd-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 Montezuma at the 65th percentile, close to its 63rd-percentile risk score.
Montezuma's building exposure, zone by zone
83.8% of Montezuma's 1,003 buildings fall in USFS's Indirect exposure zone — ember cast rather than direct flame — against 16.1% Direct and 0.2% Minimal. Vent screens and roofing material matter more here than lot clearing alone.
Montezuma against the rest of the country
Within Iowa, Montezuma ranks higher (86th percentile) than it does nationally (63rd) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, Montezuma ranks 11,595 for wildfire risk (1 is highest) and 11,910 by building count (1 is largest). Within Iowa alone, it ranks 139 of 1,017 places by risk. See the full county-by-county picture for Iowa on its state page.
Shopping for coverage in Montezuma
Montezuma's 63rd-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.
What would actually reduce this score
Because 83.8% of Montezuma's buildings sit in the Indirect zone, sealing the ember pathway (vents, roofing, gutters) is the intervention this page's data actually supports — see the home-hardening guide.
Where Montezuma's figures come from
Montezuma's 63rd-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 Montezuma's dominant indirect exposure actually means, with real examples from across the dataset.