Tucker, MS
Tucker, MS's wildfire risk, in USFS's own numbers
USFS scores Tucker at the 63rd national percentile for wildfire risk to structures (well above the national norm for wildfire risk), a figure built from 245 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Tucker at the 65th percentile, close to its 63rd-percentile risk score.
Where Tucker's buildings actually sit
245 buildings are counted in Tucker, and 100% of them sit in USFS's Direct exposure zone — flame contact, not just ember cast, is the live possibility for most of them, against 0% rated Minimal.
Tucker against the rest of the country
Tucker's 63rd national percentile looks worse in isolation than its 40th ranking inside Mississippi does — this place is on the milder end for its own state, by 23 points. Among the 31,521 US communities USFS scores, Tucker ranks 11,755 for wildfire risk (1 is highest) and 23,301 by building count (1 is largest). Within Mississippi alone, it ranks 252 of 420 places by risk. See the full county-by-county picture for Mississippi on its state page.
What this risk score means for insurance
At the 63rd percentile nationally, Tucker carries the 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.
What would actually reduce this score
With 100% of Tucker 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 Tucker's figures come from
The methodology guide shows exactly how USFS turned 245 counted buildings into the percentiles shown above for Tucker. The exposure-zones guide covers what Tucker's dominant direct exposure actually means, with real examples from across the dataset.