Nakaibito, NM
How exposed is Nakaibito to wildfire?
Out of every US place USFS scores, Nakaibito lands at the 39th percentile for wildfire risk to structures — close to the middle of USFS's national wildfire-risk range — a figure built from its 156 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 Nakaibito at the 40th percentile, close to its 39th-percentile risk score.
Nakaibito's building exposure, zone by zone
100% of Nakaibito's 156 buildings sit in USFS's Direct exposure zone, roughly 156 structures close enough to burnable vegetation for flame contact, not just embers — 0% fall in the Indirect, ember-only zone and 0% are Minimal.
Nakaibito against the rest of the country
Nakaibito's 39th national percentile looks worse in isolation than its 8th ranking inside New Mexico does — this place is on the milder end for its own state, by 32 points. Among the 31,521 US communities USFS scores, Nakaibito ranks 19,102 for wildfire risk (1 is highest) and 26,626 by building count (1 is largest). Within New Mexico alone, it ranks 458 of 495 places by risk. See the full county-by-county picture for New Mexico on its state page.
Shopping for coverage in Nakaibito
Nakaibito's moderate wildfire rating (39th percentile) isn't the kind of score driving the carrier pullback making news in the highest-risk Western markets — but a standard homeowners quote is still worth comparing on its own terms.
What would actually reduce this score
Because Direct exposure dominates in Nakaibito (100%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Nakaibito's figures come from
Nakaibito's 39th-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 Nakaibito's dominant direct exposure actually means, with real examples from across the dataset.