Evaluating and quantifying the effect of various spruce budworm intervention strategies on forest carbon dynamics in Atlantic Canada

Spruce budworm (SBW) outbreaks are one of the most devastating natural disturbances in spruce-balsam fir forests of eastern North America. Both early intervention strategy (EIS) and foliage protection strategy (FP) are being tested to limit forest losses, but the quantitative impact on forest carbon (C) dynamics is still unclear. In this study, we designed 19 separate scenarios of no intervention or varying success of EIS, FP, and their combination on SBW caused defoliation and mortality. We then used the TRIPLEX-Insect model to quantify their effects on forest C dynamics in the forests of the four provinces of Atlantic Canada. A scenario applying FP to 10% of the area with the greatest potential C losses of living biomass, protecting foliage in 10% of the forests is more realistic than higher proportion of FP given the high cost and large areas involved, resulted in reducing average cumulative net ecosystem productivity (NEP) from 2020 to 2039 by 56%–127% compared to a no outbreak scenario. Our results showed that FP would have to be applied everywhere to reduce tree mortality and increase NEP more than 8 years of successful EIS applied. However, if EIS can be successfully implemented for 12 years, it will maintain more forest C than FP applied everywhere during a moderate outbreak. We also found that the combination of EIS followed by FP in 10% of the areas disturbed by the SBW could maintain average cumulative NEP at similar levels to no defoliation in every province of Atlantic Canada. Black/red spruce forests younger than 60 years old underwent the smallest changes in C dynamics whether using EIS, FP, or both. This highlights the importance of forest species, forest age, and their interactions on the effectiveness of a treatment during SBW outbreak. Overall, 31%–76% of the study area in Atlantic Canada could convert from a C sink to a source by 2039, if no protective measures are used under the worst-case scenarios, thus contributing to future climate warming.