Lithium, MO
Lithium wildfire risk explained
Out of every US place USFS scores, Lithium lands at the 34th percentile for wildfire risk to structures — close to the middle of USFS's national wildfire-risk range — a figure built from its 76 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 Lithium at the 34th percentile, close to its 34th-percentile risk score.
Where Lithium's buildings actually sit
Direct exposure dominates in Lithium: 60.5% of its 76 buildings, versus 39.5% Indirect and 0% Minimal. Clearing space around a structure changes the outcome here more than any single building-material swap.
Lithium against the rest of the country
Lithium ranks lower within Missouri (10th percentile statewide) than its 34th national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Lithium ranks 20,959 for wildfire risk (1 is highest) and 30,053 by building count (1 is largest). Within Missouri alone, it ranks 953 of 1,062 places by risk. See the full county-by-county picture for Missouri on its state page.
Lithium and the insurance market
Lithium's moderate rating (34th percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.
Lowering exposure, not just insuring around it
With 60.5% of Lithium 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 Lithium's figures come from
Lithium's 34th-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 Lithium's dominant direct exposure actually means, with real examples from across the dataset.