Paxtonville, PA
Paxtonville wildfire risk explained
Out of every US place USFS scores, Paxtonville lands at the 45th percentile for wildfire risk to structures — modestly above the national average for wildfire risk — a figure built from its 181 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Paxtonville at the 42nd percentile, close to its 45th-percentile risk score.
Paxtonville's building exposure, zone by zone
181 buildings are counted in Paxtonville, and 79% 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.
How Paxtonville compares
Paxtonville's 72nd-percentile standing inside Pennsylvania outpaces its 45th 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, Paxtonville ranks 17,409 for wildfire risk (1 is highest) and 25,595 by building count (1 is largest). Within Pennsylvania alone, it ranks 558 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
At the 45th national percentile, Paxtonville rates elevated for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
What would actually reduce this score
With 79% of Paxtonville in Direct exposure, defensible-space clearing and ember-resistant construction (vents, Class-A roofing) address the exposure this page's own numbers describe, not a generic checklist. See the home-hardening guide.
Where Paxtonville's figures come from
The methodology guide shows exactly how USFS turned 181 counted buildings into the percentiles shown above for Paxtonville. The exposure-zones guide covers what Paxtonville's dominant direct exposure actually means, with real examples from across the dataset.