Melrose, NM
How exposed is Melrose to wildfire?
Out of every US place USFS scores, Melrose lands at the 99th percentile for wildfire risk to structures — in USFS's highest wildfire-risk band nationally — a figure built from its 676 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Melrose at the 100th percentile, close to its 99th-percentile risk score.
Where Melrose's buildings actually sit
Most of Melrose's buildings (68.3%) sit in the Indirect zone, where wind-blown embers rather than flame front are the mechanism USFS is scoring — ember-resistant vents and non-combustible roofing are the interventions this pattern favors, more than defensible space alone.
How Melrose compares
Melrose scores 99th nationally and 97th within New Mexico — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Melrose ranks 327 for wildfire risk (1 is highest) and 14,909 by building count (1 is largest). Within New Mexico alone, it ranks 18 of 495 places by risk. See the full county-by-county picture for New Mexico on its state page.
What this risk score means for insurance
At the 99th percentile nationally, Melrose 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 Melrose
Melrose's 68.3% Indirect-exposure share points at embers, not flame contact, as the main pathway — ember-resistant vents and non-combustible roofing rank ahead of defensible space here. Detail in the home-hardening guide.
Where Melrose's figures come from
The methodology guide shows exactly how USFS turned 676 counted buildings into the percentiles shown above for Melrose. The exposure-zones guide covers what Melrose's dominant indirect exposure actually means, with real examples from across the dataset.