St. Marys, IA
How exposed is St. Marys to wildfire?
USFS's Wildfire Risk to Communities model puts St. Marys at the 66th national percentile for risk to structures, well above the national norm for wildfire risk — a score built from 90 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts St. Marys at the 67th percentile, close to its 66th-percentile risk score.
Where St. Marys's buildings actually sit
USFS puts 66.7% of St. Marys's 90 buildings in the Indirect exposure zone, versus 33.3% Direct and 0% Minimal — a place where the fire doesn't need to reach the structure directly for embers to.
St. Marys against the rest of the country
St. Marys's 90th-percentile standing inside Iowa outpaces its 66th national percentile — this is a hotter spot than most of its own state, even though the state as a whole runs cooler nationally. Among the 31,521 US communities USFS scores, St. Marys ranks 10,715 for wildfire risk (1 is highest) and 29,492 by building count (1 is largest). Within Iowa alone, it ranks 104 of 1,017 places by risk. See the full county-by-county picture for Iowa on its state page.
What this risk score means for insurance
At the 66th percentile nationally, St. Marys carries the high rating that has pushed some carriers to limit new business in similarly-scored places elsewhere in the country. Worth comparing quotes rather than assuming last year's renewal terms still apply.
Lowering exposure, not just insuring around it
Because 66.7% of St. Marys'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 St. Marys's figures come from
St. Marys's 66th-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 St. Marys's dominant indirect exposure actually means, with real examples from across the dataset.