Eau Claire, PA
Eau Claire, PA's wildfire risk, in USFS's own numbers
Eau Claire sits at the 41st percentile nationally for wildfire risk to structures — modestly above the national average for wildfire risk — per USFS's Wildfire Risk to Communities model, built from its 218 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Eau Claire at the 41st percentile, close to its 41st-percentile risk score.
Where Eau Claire's buildings actually sit
USFS classifies 65.1% of Eau Claire's buildings as Direct exposure, higher than its 34.9% Indirect share and far above its 0% Minimal share — a profile where 142 structures sit close enough to vegetation that lot clearing matters most.
Eau Claire against the rest of the country
Compare Eau Claire's two percentiles: 64th within Pennsylvania, only 41st nationally — a gap of 24 points that marks it as unusually exposed for its own state. Among the 31,521 US communities USFS scores, Eau Claire ranks 18,702 for wildfire risk (1 is highest) and 24,218 by building count (1 is largest). Within Pennsylvania alone, it ranks 708 of 1,991 places by risk. See the full county-by-county picture for Pennsylvania on its state page.
Shopping for coverage in Eau Claire
At the 41st national percentile, Eau Claire rates elevated for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
Lowering exposure, not just insuring around it
Because Direct exposure dominates in Eau Claire (65.1%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Eau Claire's figures come from
The methodology guide shows exactly how USFS turned 218 counted buildings into the percentiles shown above for Eau Claire. The exposure-zones guide covers what Eau Claire's dominant direct exposure actually means, with real examples from across the dataset.