Captiva, FL
How exposed is Captiva to wildfire?
Captiva sits at the 79th 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 840 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Captiva at the 81st national percentile — 2 points above its risk-to-structures score, a gap driven by how much is actually built there.
What "at risk" means for the buildings here
Captiva rates 90.4% Minimal exposure against just 9.6% Direct and 0% Indirect — of 840 buildings counted, few sit close enough to burnable vegetation for USFS to flag them individually.
Captiva against the rest of the country
Captiva ranks lower within Florida (46th percentile statewide) than its 79th national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Captiva ranks 6,586 for wildfire risk (1 is highest) and 13,249 by building count (1 is largest). Within Florida alone, it ranks 518 of 955 places by risk. See the full county-by-county picture for Florida on its state page.
What this risk score means for insurance
Captiva's high rating (79th 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.
Hardening a home in Captiva
Even with 90.4% of Captiva outside USFS's Direct and Indirect zones, basic hardening — gutter maintenance, ember-resistant vents — is inexpensive relative to the regional burn-probability risk noted above. Details in the home-hardening guide.
Where Captiva's figures come from
Captiva's 79th-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 Captiva's dominant minimal exposure actually means, with real examples from across the dataset.