Sperry, IA
Sperry, IA's wildfire risk, in USFS's own numbers
Out of every US place USFS scores, Sperry lands at the 60th percentile for wildfire risk to structures — modestly above the national average for wildfire risk — a figure built from its 148 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Sperry at the 62nd national percentile — 2 points above its risk-to-structures score, a gap driven by how much is actually built there.
Where Sperry's buildings actually sit
Most of Sperry's buildings (71%) sit in the Indirect zone, where wind-blown embers rather than flame front are the mechanism USFS is scoring — ember-resistant vents and non-combustible roofing are the interventions this pattern favors, more than defensible space alone.
Sperry against the rest of the country
Sperry's 83rd-percentile standing inside Iowa outpaces its 60th national percentile — this is a hotter spot than most of its own state, even though the state as a whole runs cooler nationally. Among the 31,521 US communities USFS scores, Sperry ranks 12,729 for wildfire risk (1 is highest) and 26,951 by building count (1 is largest). Within Iowa alone, it ranks 174 of 1,017 places by risk. See the full county-by-county picture for Iowa on its state page.
Shopping for coverage in Sperry
At the 60th national percentile, Sperry rates elevated for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
Hardening a home in Sperry
Because 71% of Sperry's buildings sit in the Indirect zone, sealing the ember pathway (vents, roofing, gutters) is the intervention this page's data actually supports — see the home-hardening guide.
Where Sperry's figures come from
The methodology guide shows exactly how USFS turned 148 counted buildings into the percentiles shown above for Sperry. The exposure-zones guide covers what Sperry's dominant indirect exposure actually means, with real examples from across the dataset.