Yah-ta-hey, NM
Yah-ta-hey wildfire risk explained
USFS's Wildfire Risk to Communities model puts Yah-ta-hey at the 31st national percentile for risk to structures, close to the middle of USFS's national wildfire-risk range — a score built from 348 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Yah-ta-hey at the 30th national percentile — 1 points below its risk-to-structures score, a gap driven by how much is actually built there.
Where Yah-ta-hey's buildings actually sit
Direct exposure dominates in Yah-ta-hey: 95.4% of its 348 buildings, versus 4.6% Indirect and 0% Minimal. Clearing space around a structure changes the outcome here more than any single building-material swap.
How Yah-ta-hey compares
Yah-ta-hey's 31st national percentile looks worse in isolation than its 3rd ranking inside New Mexico does — this place is on the milder end for its own state, by 29 points. Among the 31,521 US communities USFS scores, Yah-ta-hey ranks 21,621 for wildfire risk (1 is highest) and 20,373 by building count (1 is largest). Within New Mexico alone, it ranks 481 of 495 places by risk. See the full county-by-county picture for New Mexico on its state page.
Yah-ta-hey and the insurance market
Yah-ta-hey's moderate wildfire rating (31st 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
With 95.4% of Yah-ta-hey in Direct exposure, defensible-space clearing and ember-resistant construction (vents, Class-A roofing) address the exposure this page's own numbers describe, not a generic checklist. See the home-hardening guide.
Where Yah-ta-hey's figures come from
Yah-ta-hey's 31st-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 Yah-ta-hey's dominant direct exposure actually means, with real examples from across the dataset.