Diehlstadt, MO
Diehlstadt, MO's wildfire risk, in USFS's own numbers
USFS's Wildfire Risk to Communities model puts Diehlstadt at the 3rd national percentile for risk to structures, among the lower wildfire-risk places nationally — a score built from 82 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Diehlstadt's burn probability — fire likelihood with no building count factored in — sits at the 3rd percentile nationally.
Diehlstadt's building exposure, zone by zone
Only 8.5% of Diehlstadt's 82 buildings carry Direct exposure and 0% carry Indirect; the remaining 91.5% are Minimal, which shifts the risk driving this page's score toward the surrounding landscape rather than any one structure.
How Diehlstadt compares
Diehlstadt's risk sits at a similar level relative to Missouri (3rd percentile statewide) as it does nationally (3rd) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Diehlstadt ranks 30,674 for wildfire risk (1 is highest) and 29,809 by building count (1 is largest). Within Missouri alone, it ranks 1,029 of 1,062 places by risk. See the full county-by-county picture for Missouri on its state page.
Diehlstadt and the insurance market
Diehlstadt's low rating (3rd percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.
What would actually reduce this score
Even with 91.5% of Diehlstadt outside USFS's Direct and Indirect zones, basic hardening — gutter maintenance, ember-resistant vents — is inexpensive relative to the regional burn-probability risk noted above. Details in the home-hardening guide.
Where Diehlstadt's figures come from
Every one of the two percentiles behind Diehlstadt's 30,674-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Diehlstadt's dominant minimal exposure actually means, with real examples from across the dataset.