Hurricanes are a major factor controlling ecosystem structure, function, and dynamics in many coastal forests, but their ecological role can be understood only by assessing impacts in space and time over a period of centuries. We present a new method for reconstructing hurricane disturbance regimes using a combination of historical research and computer modeling. Historical evidence of wind damage for each hurricane in the selected region is quantified using the Fujita scale to produce regional maps of actual damage. A simple meteorological model (HURRECON), parameterized and tested for selected recent hurricanes, provides regional estimates of wind speed, direction, and damage for each storm. Individual reconstructions are compiled to analyze spatial and temporal patterns of hurricane impacts. Long-term effects of topography on a landscape scale are then simulated with a simple topographic exposure model (EXPOS).

We applied this method to the region of New England, USA, examining hurricanes since European settlement in 1620. Results showed strong regional gradients in hurricane frequency and intensity from southeast to northwest: mean return intervals for F0 damage on the Fujita scale (loss of leaves and branches) ranged from 5 to 85 yr, mean return intervals for F1 damage (scattered blowdowns, small gaps) ranged from 10 to >200 yr, and mean return intervals for F2 damage (extensive blowdowns, large gaps) ranged from 85 to >380 yr. On a landscape scale, mean return intervals for F2 damage in the town of Petersham, Massachusetts, ranged from 125 yr across most sites to >380 yr on scattered lee slopes. Actual forest damage was strongly dependent on land use and natural disturbance history. Annual and decadal timing of hurricanes varied widely. There was no clear century-scale trend in the number of major hurricanes.

The historical-modeling approach is applicable to any region with good historical records and will enable ecologists and land managers to incorporate insights on hurricane disturbance regimes into the interpretation and conservation of forests at landscape to regional scales.