Sylvanite, MT
Sylvanite wildfire risk explained
Sylvanite's 181 buildings earn a 98th-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.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Sylvanite at the 95th percentile, close to its 98th-percentile risk score.
What "at risk" means for the buildings here
Direct exposure dominates in Sylvanite: 100% of its 181 buildings, versus 0% Indirect and 0% Minimal. Clearing space around a structure changes the outcome here more than any single building-material swap.
Sylvanite against the rest of the country
Sylvanite scores 98th nationally and 96th within Montana — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Sylvanite ranks 792 for wildfire risk (1 is highest) and 25,588 by building count (1 is largest). Within Montana alone, it ranks 20 of 475 places by risk. See the full county-by-county picture for Montana on its state page.
Shopping for coverage in Sylvanite
Sylvanite's 98th-percentile, very high rating is the kind of score behind a broader national pattern: insurers pulling back from the highest wildfire-risk markets, non-renewing or declining new policies outright, most visibly in California. Shopping around, not assuming automatic renewal, tends to matter here.
What would actually reduce this score
With 100% of Sylvanite 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 Sylvanite's figures come from
Sylvanite's 98th-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 Sylvanite's dominant direct exposure actually means, with real examples from across the dataset.