Abstract
Though fire is considered a “natural” disturbance, humans heavily influence modern wildfire regimes. Humans influence fires both directly, by igniting and suppressing fires, and indirectly, by either altering vegetation, climate, or both. We used the LANDIS disturbance and succession model to compare the relative importance of a direct human influence (suppression of low intensity surface fires) with an indirect human influence (timber harvest) on the long-term abundance and connectivity of high-risk fuel in a 2791 km2 landscape characterized by a mixture of northern hardwood and boreal tree species in northern Wisconsin. High risk fuels were defined as a combination of sites recently disturbed by wind and sites containing conifer species/cohorts that might serve as “ladder fuel” to carry a surface fire into the canopy. Two levels of surface fire suppression (high/current and low) and three harvest alternatives (no harvest, hardwood emphasis, and pine emphasis) were compared in a 2×3 factorial design using 5 replicated simulations per treatment combination over a 250-year period. Multivariate analysis of variance indicated that the landscape pattern of high-risk fuel (proportion of landscape, mean patch size, nearest neighbor distance, and juxtaposition with non fuel sites) was significantly influenced by both surface fire suppression and by forest harvest (p > 0.0001). However, the two human influences also interacted with each other (p < 0.001), because fire suppression was less likely to influence fuel connectivity when harvest disturbance was simultaneously applied. Temporal patterns observed for each of seven conifer species indicated that disturbances by either fire or harvest encouraged the establishment of moderately shade-tolerant conifer species by disturbing the dominant shade tolerant competitor, sugar maple. Our results conflict with commonly reported relationships between fire suppression and fire risk observed within the interior west of the United States, and illustrate the importance of understanding key interactions between natural disturbance, human disturbance, and successional responses to these disturbance types that will eventually dictate future fire risk.
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