Poplar, MT
How exposed is Poplar to wildfire?
Out of every US place USFS scores, Poplar lands at the 71st percentile for wildfire risk to structures — well above the national norm for wildfire risk — a figure built from its 439 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Poplar at the 70th national percentile — 1 points below its risk-to-structures score, a gap driven by how much is actually built there.
Where Poplar's buildings actually sit
99.3% of Poplar's 439 buildings fall in USFS's Indirect exposure zone — ember cast rather than direct flame — against 0.7% Direct and 0% Minimal. Vent screens and roofing material matter more here than lot clearing alone.
How Poplar compares
Poplar ranks lower within Montana (40th percentile statewide) than its 71st national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Poplar ranks 9,207 for wildfire risk (1 is highest) and 18,482 by building count (1 is largest). Within Montana alone, it ranks 284 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
At the 71st percentile nationally, Poplar carries the high rating that has pushed some carriers to limit new business in similarly-scored places elsewhere in the country. Worth comparing quotes rather than assuming last year's renewal terms still apply.
What would actually reduce this score
With ember exposure the dominant pattern in Poplar (99.3% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.
Where Poplar's figures come from
Every one of the two percentiles behind Poplar's 9,207-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Poplar's dominant indirect exposure actually means, with real examples from across the dataset.