Mimbres, NM
Mimbres wildfire risk explained
Mimbres sits at the 94th percentile nationally for wildfire risk to structures — in USFS's highest wildfire-risk band nationally — per USFS's Wildfire Risk to Communities model, built from its 513 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Mimbres at the 92nd national percentile — 2 points below its risk-to-structures score, a gap driven by how much is actually built there.
Mimbres's building exposure, zone by zone
Of Mimbres's 513 counted buildings, 100% 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 Mimbres compares
Mimbres's risk sits at a similar level relative to New Mexico (82nd percentile statewide) as it does nationally (94th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Mimbres ranks 1,800 for wildfire risk (1 is highest) and 17,133 by building count (1 is largest). Within New Mexico alone, it ranks 87 of 495 places by risk. See the full county-by-county picture for New Mexico on its state page.
Shopping for coverage in Mimbres
At the 94th percentile nationally, Mimbres carries the very 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.
Hardening a home in Mimbres
Mimbres'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 Mimbres's figures come from
Mimbres's 94th-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 Mimbres's dominant direct exposure actually means, with real examples from across the dataset.