Abstract

Landscape-scale wildfire has occurred in higher frequencies across the planet. Fuel reduction treatments to fire-adapted systems have been shown to reduce the impact to human values-at-risk. However, few studies have examined if these treatments contribute to ecosystem resilience, or the capacity of a system to absorb perturbation and return to a similar set of structures or processes. We defined short-term metrics of resiliency to test the hypothesis that fuel reduction treatments in mixed conifer forests increased a fire-adapted system’s resiliency to uncharacteristically severe wildfire. In addition, we tested the hypothesis that fuel reduction treatments reduced burn severity, thereby increasing protection for adjacent human communities. We examined a mixed conifer forested landscape in the southwestern U.S. that was burned by a landscape-scale “mega-fire” in 2011; fuel reduction treatments had been established around communities in the 10years prior to the fire. Fire effects were highly variable in both treated and untreated forests. However, analysis of resiliency metrics showed that: (a) treated units retained a higher proportion of large trees and had post-fire tree densities within the natural range of variability; (b) the understory herbaceous community had significantly higher cover of native grasses in the treated units, but no significant differences in nonnative cover between treated and untreated units; and (c) high-severity patch sizes were significantly larger in untreated stands and covered a larger proportion of the landscape than historical reference conditions. Fire severity, as defined by overstory mortality and basal area loss, was significantly lower in treated units; on average, trees killed per hectare in untreated units was six times the number of trees killed in treated units. Fuel reduction treatments simultaneously reduced fire severity and enhanced short-term metrics of ecosystem resiliency to uncharacteristically severe fire.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call