Talent, OR
How exposed is Talent to wildfire?
USFS's Wildfire Risk to Communities model puts Talent at the 94th national percentile for risk to structures, in USFS's highest wildfire-risk band nationally — a score built from 2,662 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Talent at the 95th national percentile — 1 points above its risk-to-structures score, a gap driven by how much is actually built there.
Talent's building exposure, zone by zone
96.4% of Talent's 2,662 buildings fall in USFS's Indirect exposure zone — ember cast rather than direct flame — against 3.6% Direct and 0% Minimal. Vent screens and roofing material matter more here than lot clearing alone.
Talent against the rest of the country
Talent's risk sits at a similar level relative to Oregon (80th percentile statewide) as it does nationally (94th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Talent ranks 1,964 for wildfire risk (1 is highest) and 5,996 by building count (1 is largest). Within Oregon alone, it ranks 83 of 420 places by risk. See the full county-by-county picture for Oregon on its state page.
What this risk score means for insurance
Talent sits in Oregon, one of two states that legally require a wildfire-risk disclosure at sale. Sellers here disclose wildfire-hazard status before closing, the same number this page reports at the 94th national percentile. More on the disclosure law.
What would actually reduce this score
Talent's 96.4% 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 Talent's figures come from
Talent's 94th-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 Talent's dominant indirect exposure actually means, with real examples from across the dataset.