Hardwood Acres, MI
How exposed is Hardwood Acres to wildfire?
USFS's Wildfire Risk to Communities model puts Hardwood Acres at the 23rd national percentile for risk to structures, close to the middle of USFS's national wildfire-risk range — a score built from 168 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Hardwood Acres's burn probability — fire likelihood with no building count factored in — sits at the 23rd percentile nationally.
What "at risk" means for the buildings here
168 buildings are counted in Hardwood Acres, and 83.9% of them sit in USFS's Direct exposure zone — flame contact, not just ember cast, is the live possibility for most of them, against 0% rated Minimal.
Hardwood Acres against the rest of the country
Hardwood Acres's 73rd-percentile standing inside Michigan outpaces its 23rd 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, Hardwood Acres ranks 24,202 for wildfire risk (1 is highest) and 26,098 by building count (1 is largest). Within Michigan alone, it ranks 206 of 745 places by risk. See the full county-by-county picture for Michigan on its state page.
Shopping for coverage in Hardwood Acres
Hardwood Acres's moderate wildfire rating (23rd 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 Direct exposure dominates in Hardwood Acres (83.9%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Hardwood Acres's figures come from
The methodology guide shows exactly how USFS turned 168 counted buildings into the percentiles shown above for Hardwood Acres. The exposure-zones guide covers what Hardwood Acres's dominant direct exposure actually means, with real examples from across the dataset.