Quantifying aboveground carbon emissions during wildfire in the montane forest of the Colorado Front Range, U.S.A

Background/Question/Methods   Recent climate change predictions suggest an increase in the spatial extent of land subjected to wildfire in the western U.S. Forest fires can result in an immediate release of carbon to the atmosphere, compared to the gradual storage of carbon in forests over decades as they grow and mature. Due to a heightened interest in determining the role of forests in the terrestrial carbon cycle and their potential to sequester anthropogenic carbon emissions, recent effort has focused on quantifying the net carbon balance associated with forest fire across a range of climates and disturbance regimes. The objective of our study is to determine the amount of carbon lost via combustion during wildland fire events in the montane forests of the Colorado Front Range. Our 3 large study sites are representative of the typical montane forests of the Rocky Mountain region. Each site is composed of unburned as well as burned areas. The burned areas were prescribed fires during fall 2007. We used allometric equations to estimate aboveground biomass loss due to fire for five fuel types: Large standing trees {ponderosa pine (Pinus ponderosa), Douglas-fir (Pseudotsuga menziesii), aspen (Populus tremuloides), limber pine (Pinus flexilis), lodgepole pine (Pinus contorta)}, small standing trees, shrubs, dead and downed woody debris, and surface litter.

Results/Conclusions   We combined these fuel components to estimate total loss of aboveground biomass during combustion. Most of the biomass lost from fire came from surface litter, relative to biomass associated with standing trees, with a significant proportion of the aboveground plant biomass remaining following fire. Long term losses due to tree death and subsequent heterotrophic respiration are likely to dominate carbon losses following fire in these systems. These results provide insight into expected wildfire emissions in the montane region, and can be applied to spatial estimates of the consequences of fire under a variety of climate predictions.