Paskenta, CA
Paskenta, CA's wildfire risk, in USFS's own numbers
Paskenta's 122 buildings earn a 99th-percentile wildfire-risk score nationally under USFS's model — in USFS's highest wildfire-risk band nationally. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Paskenta at the 100th national percentile — 1 points above its risk-to-structures score, a gap driven by how much is actually built there.
What "at risk" means for the buildings here
122 buildings are counted in Paskenta, and 67.2% 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.
Paskenta against the rest of the country
Paskenta scores 99th nationally and 90th within California — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Paskenta ranks 343 for wildfire risk (1 is highest) and 28,050 by building count (1 is largest). Within California alone, it ranks 172 of 1,570 places by risk. See the full county-by-county picture for California on its state page.
What this risk score means for insurance
Paskenta sits in California, one of two states that legally require a wildfire-risk disclosure at sale. California's FAIR Plan, the state's insurer of last resort, ended 2025 with 668,609 residential policies after adding 21,859 in Q4 alone — the kind of market shift a 99th-percentile score like Paskenta's can end up mattering for. More on the disclosure law.
Hardening a home in Paskenta
Because Direct exposure dominates in Paskenta (67.2%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Paskenta's figures come from
Every one of the two percentiles behind Paskenta's 343-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Paskenta's dominant direct exposure actually means, with real examples from across the dataset.