Mount Horeb, WI
Mount Horeb, WI's wildfire risk, in USFS's own numbers
USFS's Wildfire Risk to Communities model puts Mount Horeb at the 28th national percentile for risk to structures, close to the middle of USFS's national wildfire-risk range — a score built from 2,707 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 Mount Horeb at the 29th percentile, close to its 28th-percentile risk score.
What "at risk" means for the buildings here
Indirect exposure is dominant in Mount Horeb (74.2% of 2,707 buildings): far enough from burnable vegetation to avoid flame contact, close enough for wind-blown embers. Only 20.3% sit in the Direct zone.
How Mount Horeb compares
Mount Horeb's 56th-percentile standing inside Wisconsin outpaces its 28th national percentile — this is a hotter spot than most of its own state, even though the state as a whole runs cooler nationally. Among the 31,521 US communities USFS scores, Mount Horeb ranks 22,868 for wildfire risk (1 is highest) and 5,916 by building count (1 is largest). Within Wisconsin alone, it ranks 355 of 808 places by risk. See the full county-by-county picture for Wisconsin on its state page.
Mount Horeb and the insurance market
Mount Horeb's moderate wildfire rating (28th 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
Because 74.2% of Mount Horeb'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 Mount Horeb's figures come from
The methodology guide shows exactly how USFS turned 2,707 counted buildings into the percentiles shown above for Mount Horeb. The exposure-zones guide covers what Mount Horeb's dominant indirect exposure actually means, with real examples from across the dataset.