Hawthorn, PA
How exposed is Hawthorn to wildfire?
Hawthorn sits at the 39th percentile nationally for wildfire risk to structures — close to the middle of USFS's national wildfire-risk range — per USFS's Wildfire Risk to Communities model, built from its 334 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 Hawthorn at the 40th percentile, close to its 39th-percentile risk score.
Where Hawthorn's buildings actually sit
USFS puts 77.5% of Hawthorn's 334 buildings in the Indirect exposure zone, versus 22.5% Direct and 0% Minimal — a place where the fire doesn't need to reach the structure directly for embers to.
Hawthorn against the rest of the country
Within Pennsylvania, Hawthorn ranks higher (61st percentile) than it does nationally (39th) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, Hawthorn ranks 19,207 for wildfire risk (1 is highest) and 20,725 by building count (1 is largest). Within Pennsylvania alone, it ranks 787 of 1,991 places by risk. See the full county-by-county picture for Pennsylvania on its state page.
Hawthorn and the insurance market
Hawthorn's moderate wildfire rating (39th 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.
Hardening a home in Hawthorn
Hawthorn's 77.5% Indirect-exposure share points at embers, not flame contact, as the main pathway — ember-resistant vents and non-combustible roofing rank ahead of defensible space here. Detail in the home-hardening guide.
Where Hawthorn's figures come from
Hawthorn's 39th-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 Hawthorn's dominant indirect exposure actually means, with real examples from across the dataset.