Atmautluak, AK
How exposed is Atmautluak to wildfire?
USFS's Wildfire Risk to Communities model puts Atmautluak at the 72nd national percentile for risk to structures, well above the national norm for wildfire risk — a score built from 104 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 Atmautluak at the 78th percentile, close to its 72nd-percentile risk score.
What "at risk" means for the buildings here
95.2% of Atmautluak's 104 buildings sit in USFS's Direct exposure zone, roughly 99 structures close enough to burnable vegetation for flame contact, not just embers — 0% fall in the Indirect, ember-only zone and 4.8% are Minimal.
How Atmautluak compares
Atmautluak's 72nd national percentile looks worse in isolation than its 56th ranking inside Alaska does — this place is on the milder end for its own state, by 17 points. Among the 31,521 US communities USFS scores, Atmautluak ranks 8,687 for wildfire risk (1 is highest) and 28,830 by building count (1 is largest). Within Alaska alone, it ranks 144 of 322 places by risk. See the full county-by-county picture for Alaska on its state page.
Atmautluak and the insurance market
At the 72nd percentile nationally, Atmautluak 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
Atmautluak's 95.2% Direct-exposure share means lot clearing around the structure typically outweighs any single material upgrade here. The home-hardening guide ranks the options for a place shaped like this.
Where Atmautluak's figures come from
Atmautluak's 72nd-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 Atmautluak's dominant direct exposure actually means, with real examples from across the dataset.