Gardner, CO
Gardner wildfire risk explained
USFS scores Gardner at the 72nd national percentile for wildfire risk to structures (well above the national norm for wildfire risk), a figure built from 145 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 Gardner at the 66th percentile, close to its 72nd-percentile risk score.
What "at risk" means for the buildings here
145 buildings are counted in Gardner, and 95.9% 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.
How Gardner compares
Gardner ranks lower within Colorado (41st percentile statewide) than its 72nd national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Gardner ranks 8,691 for wildfire risk (1 is highest) and 27,065 by building count (1 is largest). Within Colorado alone, it ranks 280 of 472 places by risk. See the full county-by-county picture for Colorado on its state page.
What this risk score means for insurance
Gardner's 72nd-percentile, high rating is the kind of score behind a broader national pattern: insurers pulling back from the highest wildfire-risk markets, non-renewing or declining new policies outright, most visibly in California. Shopping around, not assuming automatic renewal, tends to matter here.
What would actually reduce this score
Gardner's 95.9% Direct-exposure share means lot clearing around the structure typically outweighs any single material upgrade here. The home-hardening guide ranks the options for a place shaped like this.
Where Gardner's figures come from
Gardner's 72nd-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 Gardner's dominant direct exposure actually means, with real examples from across the dataset.