Background Extreme wildfires produce substantial carbon emissions and are increasingly causing some forests to transition from carbon sinks to net carbon sources. Fuel treatments are often implemented to proactively reduce the risk of severe wildfire and resulting emissions; however, there is limited existing research characterizing the effects of these treatments on forest carbon storage and stability in the seasonally dry, fire-prone forests of southeastern British Columbia, Canada. We partnered with five community forests that implemented different types of fuel treatments—involving combinations of thinning, pruning, and pile burning or chipping—between the summers of 2021 and 2022. We used allometric equations to estimate differences in above-ground carbon stored on-site pre- and post-treatment and across treatment types while also accounting for the utilization of biomass removed off-site during treatment. We then combined field data with the First Order Fire Effects Model to quantify potential tree mortality and direct carbon emissions under three future wildfire scenarios in forest stands with and without fuel treatments. Results Fuel treatments reduced above-ground carbon storage across all treatment types, 1 year after treatment. High-intensity thinning treatments resulted in greater relative decreases to total above-ground carbon than low-intensity thinning treatments; however, high-intensity thinning improved carbon stability as represented by greater decreases to potential tree mortality from wildfire. High-intensity thinning treatments had greater biomass utilization than low-intensity thinning treatments due to the removal of merchantable timber, which has a longer-term carbon storage potential. Compared to pre-treatment conditions, fuel treatments had a minor impact on potential direct carbon emissions. Conclusions This work develops ecosystem-specific knowledge to critically evaluate the short-term effects of fuel treatments on forest carbon stocks in fire-prone landscapes of British Columbia and provides a foundation for future monitoring of carbon stocks over time.
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Pekelney et al. (2026) studied this question.
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