Audubon, IA
How exposed is Audubon to wildfire?
Out of every US place USFS scores, Audubon lands at the 43rd percentile for wildfire risk to structures — modestly above the national average for wildfire risk — a figure built from its 1,533 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Audubon at the 43rd percentile, close to its 43rd-percentile risk score.
Audubon's building exposure, zone by zone
Only 12.4% of Audubon's 1,533 buildings carry Direct exposure and 0% carry Indirect; the remaining 87.6% are Minimal, which shifts the risk driving this page's score toward the surrounding landscape rather than any one structure.
How Audubon compares
Within Iowa, Audubon ranks higher (59th percentile) than it does nationally (43rd) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, Audubon ranks 18,081 for wildfire risk (1 is highest) and 9,018 by building count (1 is largest). Within Iowa alone, it ranks 420 of 1,017 places by risk. See the full county-by-county picture for Iowa on its state page.
Shopping for coverage in Audubon
At the 43rd national percentile, Audubon rates elevated for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
Hardening a home in Audubon
Even with 87.6% of Audubon outside USFS's Direct and Indirect zones, basic hardening — gutter maintenance, ember-resistant vents — is inexpensive relative to the regional burn-probability risk noted above. Details in the home-hardening guide.
Where Audubon's figures come from
Every one of the two percentiles behind Audubon's 18,081-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Audubon's dominant minimal exposure actually means, with real examples from across the dataset.