Acushnet Center, MA
Acushnet Center wildfire risk explained
Out of every US place USFS scores, Acushnet Center lands at the 14th percentile for wildfire risk to structures — among the lower wildfire-risk places nationally — a figure built from its 1,485 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 Acushnet Center at the 13th percentile, close to its 14th-percentile risk score.
What "at risk" means for the buildings here
USFS puts 90.6% of Acushnet Center's 1,485 buildings in the Indirect exposure zone, versus 9.4% Direct and 0% Minimal — a place where the fire doesn't need to reach the structure directly for embers to.
Where Acushnet Center ranks
There's little gap between Acushnet Center's 14th national percentile and its 5th percentile inside Massachusetts, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Acushnet Center ranks 26,978 for wildfire risk (1 is highest) and 9,228 by building count (1 is largest). Within Massachusetts alone, it ranks 236 of 248 places by risk. See the full county-by-county picture for Massachusetts on its state page.
What this risk score means for insurance
At the 14th national percentile, Acushnet Center rates low for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
What would actually reduce this score
With ember exposure the dominant pattern in Acushnet Center (90.6% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.
Where Acushnet Center's figures come from
The methodology guide shows exactly how USFS turned 1,485 counted buildings into the percentiles shown above for Acushnet Center. The exposure-zones guide covers what Acushnet Center's dominant indirect exposure actually means, with real examples from across the dataset.