Abram, TX
Abram, TX's wildfire risk, in USFS's own numbers
Abram sits at the 71st percentile nationally for wildfire risk to structures — well above the national norm for wildfire risk — per USFS's Wildfire Risk to Communities model, built from its 528 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Abram's burn probability — fire likelihood with no building count factored in — sits at the 71st percentile nationally.
What "at risk" means for the buildings here
Only 26.3% of Abram's 528 buildings carry Direct exposure and 28.6% carry Indirect; the remaining 45.1% are Minimal, which shifts the risk driving this page's score toward the surrounding landscape rather than any one structure.
Where Abram ranks
Abram's 71st national percentile looks worse in isolation than its 33rd ranking inside Texas does — this place is on the milder end for its own state, by 38 points. Among the 31,521 US communities USFS scores, Abram ranks 9,246 for wildfire risk (1 is highest) and 16,900 by building count (1 is largest). Within Texas alone, it ranks 1,203 of 1,795 places by risk. See the full county-by-county picture for Texas on its state page.
Abram and the insurance market
Abram's 71st-percentile, 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
Abram's 45.1% Minimal-exposure share means structure-level hardening matters less here than it would elsewhere — still worth the low-cost basics, per the home-hardening guide.
Where Abram's figures come from
The methodology guide shows exactly how USFS turned 528 counted buildings into the percentiles shown above for Abram. The exposure-zones guide covers what Abram's dominant minimal exposure actually means, with real examples from across the dataset.