Mancelona, MI
Mancelona wildfire risk explained
USFS's Wildfire Risk to Communities model puts Mancelona at the 50th national percentile for risk to structures, modestly above the national average for wildfire risk — a score built from 802 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Mancelona's burn probability — fire likelihood with no building count factored in — sits at the 49th percentile nationally.
What "at risk" means for the buildings here
Indirect exposure is dominant in Mancelona (86.2% of 802 buildings): far enough from burnable vegetation to avoid flame contact, close enough for wind-blown embers. Only 13.8% sit in the Direct zone.
How Mancelona compares
Mancelona's 95th-percentile standing inside Michigan outpaces its 50th 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, Mancelona ranks 15,850 for wildfire risk (1 is highest) and 13,611 by building count (1 is largest). Within Michigan alone, it ranks 38 of 745 places by risk. See the full county-by-county picture for Michigan on its state page.
What this risk score means for insurance
Mancelona's elevated wildfire rating (50th 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.
Lowering exposure, not just insuring around it
Because 86.2% of Mancelona'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 Mancelona's figures come from
Every one of the two percentiles behind Mancelona's 15,850-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Mancelona's dominant indirect exposure actually means, with real examples from across the dataset.