Byron, MI
Byron, MI's wildfire risk, in USFS's own numbers
USFS's Wildfire Risk to Communities model puts Byron at the 10th national percentile for risk to structures, among the lower wildfire-risk places nationally — a score built from 316 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Byron at the 11th national percentile — 0 points above its risk-to-structures score, a gap driven by how much is actually built there.
Where Byron's buildings actually sit
Most of Byron's buildings (57.6%) 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.
Byron against the rest of the country
Within Michigan, Byron ranks higher (36th percentile) than it does nationally (10th) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, Byron ranks 28,277 for wildfire risk (1 is highest) and 21,207 by building count (1 is largest). Within Michigan alone, it ranks 478 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
Byron's low wildfire rating (10th 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 57.6% of Byron'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 Byron's figures come from
Byron's 10th-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 Byron's dominant indirect exposure actually means, with real examples from across the dataset.