Spink Colony, SD
Spink Colony, SD's wildfire risk, in USFS's own numbers
Spink Colony's 42 buildings earn a 41st-percentile wildfire-risk score nationally under USFS's model — modestly above the national average for wildfire risk. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Spink Colony at the 34th percentile, close to its 41st-percentile risk score.
What "at risk" means for the buildings here
Only 9.5% of Spink Colony's 42 buildings carry Direct exposure and 0% carry Indirect; the remaining 90.5% are Minimal, which shifts the risk driving this page's score toward the surrounding landscape rather than any one structure.
Where Spink Colony ranks
Spink Colony ranks lower within South Dakota (14th percentile statewide) than its 41st national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Spink Colony ranks 18,733 for wildfire risk (1 is highest) and 31,128 by building count (1 is largest). Within South Dakota alone, it ranks 379 of 439 places by risk. See the full county-by-county picture for South Dakota on its state page.
What this risk score means for insurance
At the 41st national percentile, Spink Colony 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 Spink Colony
Even with 90.5% of Spink Colony 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 Spink Colony's figures come from
The methodology guide shows exactly how USFS turned 42 counted buildings into the percentiles shown above for Spink Colony. The exposure-zones guide covers what Spink Colony's dominant minimal exposure actually means, with real examples from across the dataset.