Tionesta, PA
How exposed is Tionesta to wildfire?
Tionesta sits at the 38th 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 378 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 Tionesta at the 37th percentile, close to its 38th-percentile risk score.
Tionesta's building exposure, zone by zone
378 buildings are counted in Tionesta, and 55.8% of them are Indirect exposure — ember-driven risk rather than the 44.2% in Direct exposure or the 0% rated Minimal.
How Tionesta compares
Tionesta's 58th-percentile standing inside Pennsylvania outpaces its 38th 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, Tionesta ranks 19,461 for wildfire risk (1 is highest) and 19,703 by building count (1 is largest). Within Pennsylvania alone, it ranks 835 of 1,991 places by risk. See the full county-by-county picture for Pennsylvania on its state page.
What this risk score means for insurance
Tionesta's moderate rating (38th percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.
What would actually reduce this score
Tionesta's 55.8% 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 Tionesta's figures come from
Tionesta's 38th-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 Tionesta's dominant indirect exposure actually means, with real examples from across the dataset.