Pedro Bay, AK
How exposed is Pedro Bay to wildfire?
Out of every US place USFS scores, Pedro Bay lands at the 31st percentile for wildfire risk to structures — close to the middle of USFS's national wildfire-risk range — a figure built from its 60 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Pedro Bay's burn probability — fire likelihood with no building count factored in — sits at the 30th percentile nationally.
Where Pedro Bay's buildings actually sit
USFS classifies 96.7% of Pedro Bay's buildings as Direct exposure, higher than its 3.3% Indirect share and far above its 0% Minimal share — a profile where 58 structures sit close enough to vegetation that lot clearing matters most.
Where Pedro Bay ranks
Pedro Bay's risk sits at a similar level relative to Alaska (26th percentile statewide) as it does nationally (31st) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Pedro Bay ranks 21,735 for wildfire risk (1 is highest) and 30,642 by building count (1 is largest). Within Alaska alone, it ranks 239 of 322 places by risk. See the full county-by-county picture for Alaska on its state page.
Pedro Bay and the insurance market
Pedro Bay's moderate wildfire rating (31st percentile) isn't the kind of score driving the carrier pullback making news in the highest-risk Western markets — but a standard homeowners quote is still worth comparing on its own terms.
What would actually reduce this score
With 96.7% of Pedro Bay in Direct exposure, defensible-space clearing and ember-resistant construction (vents, Class-A roofing) address the exposure this page's own numbers describe, not a generic checklist. See the home-hardening guide.
Where Pedro Bay's figures come from
Pedro Bay's 31st-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 Pedro Bay's dominant direct exposure actually means, with real examples from across the dataset.