Lawton, ND
Lawton, ND's wildfire risk, in USFS's own numbers
USFS's Wildfire Risk to Communities model puts Lawton at the 73rd national percentile for risk to structures, well above the national norm for wildfire risk — a score built from 79 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Lawton at the 70th percentile, close to its 73rd-percentile risk score.
What "at risk" means for the buildings here
Direct exposure dominates in Lawton: 77.2% of its 79 buildings, versus 22.8% Indirect and 0% Minimal. Clearing space around a structure changes the outcome here more than any single building-material swap.
How Lawton compares
Compare Lawton's two percentiles: 89th within North Dakota, only 73rd nationally — a gap of 17 points that marks it as unusually exposed for its own state. Among the 31,521 US communities USFS scores, Lawton ranks 8,578 for wildfire risk (1 is highest) and 29,937 by building count (1 is largest). Within North Dakota alone, it ranks 44 of 402 places by risk. See the full county-by-county picture for North Dakota on its state page.
What this risk score means for insurance
Lawton's 73rd-percentile, 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 77.2% of Lawton 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 Lawton's figures come from
The methodology guide shows exactly how USFS turned 79 counted buildings into the percentiles shown above for Lawton. The exposure-zones guide covers what Lawton's dominant direct exposure actually means, with real examples from across the dataset.