Huxley, IA
Huxley wildfire risk explained
USFS scores Huxley at the 17th national percentile for wildfire risk to structures (among the lower wildfire-risk places nationally), a figure built from 1,679 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Huxley at the 17th national percentile — 0 points below its risk-to-structures score, a gap driven by how much is actually built there.
Huxley's building exposure, zone by zone
Only 22.3% of Huxley's 1,679 buildings carry Direct exposure and 0% carry Indirect; the remaining 77.7% are Minimal, which shifts the risk driving this page's score toward the surrounding landscape rather than any one structure.
How Huxley compares
There's little gap between Huxley's 17th national percentile and its 28th percentile inside Iowa, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Huxley ranks 26,059 for wildfire risk (1 is highest) and 8,496 by building count (1 is largest). Within Iowa alone, it ranks 733 of 1,017 places by risk. See the full county-by-county picture for Iowa on its state page.
Huxley and the insurance market
Huxley's low wildfire rating (17th percentile) isn't the kind of score driving the carrier pullback making news in the highest-risk Western markets — but a standard homeowners quote is still worth comparing on its own terms.
Hardening a home in Huxley
Even with 77.7% of Huxley 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 Huxley's figures come from
Huxley's 17th-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 Huxley's dominant minimal exposure actually means, with real examples from across the dataset.