Ashland, MT
How exposed is Ashland to wildfire?
Ashland sits at the 98th percentile nationally for wildfire risk to structures — in USFS's highest wildfire-risk band nationally — per USFS's Wildfire Risk to Communities model, built from its 594 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Ashland at the 99th national percentile — 1 points above its risk-to-structures score, a gap driven by how much is actually built there.
Where Ashland's buildings actually sit
USFS classifies 63.6% of Ashland's buildings as Direct exposure, higher than its 36.4% Indirect share and far above its 0% Minimal share — a profile where 378 structures sit close enough to vegetation that lot clearing matters most.
How Ashland compares
There's little gap between Ashland's 98th national percentile and its 98th percentile inside Montana, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Ashland ranks 725 for wildfire risk (1 is highest) and 15,914 by building count (1 is largest). Within Montana alone, it ranks 12 of 475 places by risk. See the full county-by-county picture for Montana on its state page.
What this risk score means for insurance
Ashland's very high rating (98th percentile) puts it among the places where the national carrier-pullback trend is most relevant — not a guarantee of a coverage problem, but a reason to shop rather than assume.
What would actually reduce this score
Ashland's 63.6% Direct-exposure share means lot clearing around the structure typically outweighs any single material upgrade here. The home-hardening guide ranks the options for a place shaped like this.
Where Ashland's figures come from
Every one of the two percentiles behind Ashland's 725-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Ashland's dominant direct exposure actually means, with real examples from across the dataset.