Bayard, IA
Bayard, IA's wildfire risk, in USFS's own numbers
USFS's Wildfire Risk to Communities model puts Bayard at the 18th national percentile for risk to structures, among the lower wildfire-risk places nationally — a score built from 372 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Bayard at the 16th national percentile — 2 points below its risk-to-structures score, a gap driven by how much is actually built there.
Bayard's building exposure, zone by zone
USFS classifies 78.5% of Bayard's buildings as Minimal exposure, the largest of the three zones here by a wide margin over 21.5% Direct and 0% Indirect — a landscape-level risk rather than a building-by-building one.
Bayard against the rest of the country
Bayard's risk sits at a similar level relative to Iowa (28th percentile statewide) as it does nationally (18th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Bayard ranks 25,963 for wildfire risk (1 is highest) and 19,820 by building count (1 is largest). Within Iowa alone, it ranks 727 of 1,017 places by risk. See the full county-by-county picture for Iowa on its state page.
Bayard and the insurance market
Bayard's low wildfire rating (18th 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.
What would actually reduce this score
Even with 78.5% of Bayard 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 Bayard's figures come from
The methodology guide shows exactly how USFS turned 372 counted buildings into the percentiles shown above for Bayard. The exposure-zones guide covers what Bayard's dominant minimal exposure actually means, with real examples from across the dataset.