Nye, MT
Nye wildfire risk explained
USFS scores Nye at the 97th national percentile for wildfire risk to structures (in USFS's highest wildfire-risk band nationally), a figure built from 65 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Nye at the 97th national percentile — 0 points above its risk-to-structures score, a gap driven by how much is actually built there.
Nye's building exposure, zone by zone
100% of Nye's 65 buildings sit in USFS's Direct exposure zone, roughly 65 structures close enough to burnable vegetation for flame contact, not just embers — 0% fall in the Indirect, ember-only zone and 0% are Minimal.
Nye against the rest of the country
There's little gap between Nye's 97th national percentile and its 93rd percentile inside Montana, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Nye ranks 1,073 for wildfire risk (1 is highest) and 30,463 by building count (1 is largest). Within Montana alone, it ranks 36 of 475 places by risk. See the full county-by-county picture for Montana on its state page.
Nye and the insurance market
Nye's 97th-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.
Hardening a home in Nye
Nye's 100% 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 Nye's figures come from
Nye's 97th-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 Nye's dominant direct exposure actually means, with real examples from across the dataset.