McLeod, ND
McLeod wildfire risk explained
McLeod's 70 buildings earn a 84th-percentile wildfire-risk score nationally under USFS's model — in USFS's highest wildfire-risk band nationally. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks McLeod at the 84th national percentile — 0 points below its risk-to-structures score, a gap driven by how much is actually built there.
What "at risk" means for the buildings here
Of McLeod's 70 counted buildings, 67.1% carry Direct exposure and only 0% carry Minimal — a lopsided split that puts defensible-space clearing ahead of vents or roofing as the intervention worth doing first.
How McLeod compares
McLeod scores 84th nationally and 97th within North Dakota — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, McLeod ranks 4,955 for wildfire risk (1 is highest) and 30,291 by building count (1 is largest). Within North Dakota alone, it ranks 15 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
McLeod's 84th-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.
Lowering exposure, not just insuring around it
McLeod's 67.1% 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 McLeod's figures come from
Every one of the two percentiles behind McLeod's 4,955-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what McLeod's dominant direct exposure actually means, with real examples from across the dataset.