Arco, ID
Arco wildfire risk explained
USFS's Wildfire Risk to Communities model puts Arco at the 68th national percentile for risk to structures, well above the national norm for wildfire risk — a score built from 679 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Arco at the 67th national percentile — 1 points below its risk-to-structures score, a gap driven by how much is actually built there.
What "at risk" means for the buildings here
Most of Arco's buildings (90.7%) sit in the Indirect zone, where wind-blown embers rather than flame front are the mechanism USFS is scoring — ember-resistant vents and non-combustible roofing are the interventions this pattern favors, more than defensible space alone.
Arco against the rest of the country
Arco's 68th national percentile looks worse in isolation than its 34th ranking inside Idaho does — this place is on the milder end for its own state, by 34 points. Among the 31,521 US communities USFS scores, Arco ranks 10,077 for wildfire risk (1 is highest) and 14,869 by building count (1 is largest). Within Idaho alone, it ranks 154 of 232 places by risk. See the full county-by-county picture for Idaho on its state page.
What this risk score means for insurance
Arco's 68th-percentile, high rating is the kind of score behind a broader national pattern: insurers pulling back from the highest wildfire-risk markets, non-renewing or declining new policies outright, most visibly in California. Shopping around, not assuming automatic renewal, tends to matter here.
Hardening a home in Arco
Because 90.7% of Arco'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 Arco's figures come from
The methodology guide shows exactly how USFS turned 679 counted buildings into the percentiles shown above for Arco. The exposure-zones guide covers what Arco's dominant indirect exposure actually means, with real examples from across the dataset.