WildfireRiskFinder

Bucks, AL

Bucks wildfire risk explained

Very High
89thpercentile nationally

Out of every US place USFS scores, Bucks lands at the 89th percentile for wildfire risk to structures — in USFS's highest wildfire-risk band nationally — a figure built from its 28 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 Bucks at the 91st percentile, close to its 89th-percentile risk score.

Bucks's building exposure, zone by zone

28Total buildings
100%Direct exposure
0%Indirect exposure
0%Minimal exposure

100% of Bucks's 28 buildings sit in USFS's Direct exposure zone, roughly 28 structures close enough to burnable vegetation for flame contact, not just embers — 0% fall in the Indirect, ember-only zone and 0% are Minimal.

Bucks against the rest of the country

Bucks scores 89th nationally and 95th within Alabama — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Bucks ranks 3,547 for wildfire risk (1 is highest) and 31,376 by building count (1 is largest). Within Alabama alone, it ranks 30 of 592 places by risk. See the full county-by-county picture for Alabama on its state page.

Shopping for coverage in Bucks

Bucks's very high rating (89th percentile) puts it among the places where the national carrier-pullback trend is most relevant — not a guarantee of a coverage problem, but a reason to shop rather than assume.

What would actually reduce this score

Because Direct exposure dominates in Bucks (100%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.

Where Bucks's figures come from

Bucks's 89th-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 Bucks's dominant direct exposure actually means, with real examples from across the dataset.