Positive feedbacks between wildfire emissions and climate are expected to increase in strength in the future; however, fires not only release carbon (C) from terrestrial to atmospheric pools, they also produce pyrogenic C (PyC) which contributes to longer-term C stability. Our objective was to quantify wildfire impacts on total C and PyC stocks in California mixed-conifer forest, and to investigate patterns in C and PyC stocks and changes across gradients of fire severity, using metrics derived from remote sensing and field observations. Our unique study accessed active wildfires to establish and measure plots within days before and after fire, prior to substantial erosion. We measured pre-and post-fire aboveground forest structure and woody fuels to calculate aboveground biomass, C and PyC, and collected forest floor and 0-5 cm mineral soil samples. Immediate tree mortality increased with severity, but overstory C loss was minimal and limited primarily to foliage. Fire released 85% of understory and herbaceous C (comprising <1.0% of total ecosystem C). The greatest C losses occurred from downed wood and forest floor pools (19.3 ± 5.1 Mg ha −1 and 25.9 ± 3.2 Mg ha −1 , respectively). Tree bark and downed wood contributed the greatest PyC gains (1.5 ± 0.3 Mg ha −1 and 1.9 ± 0.8 Mg ha −1 , respectively), and PyC in tree bark showed non-significant positive trends with increasing severity. Overall PyC losses of 1.9 ± 0.3 Mg ha −1 and 0.5 ± 0

Altered fuel conditions coupled with changing climate have disrupted fire regimes of forests historically characterised by high-frequency and low-to-moderate-severity fire. Managers use fuel treatments to abate undesirable fire behaviour and effects. Short-term effectiveness of fuel treatments to alter fire behaviour and effects is well documented; however, long-term effectiveness is not well known. We evaluated surface fuel load, vegetation cover and forest structure before and after mechanical and fire-only treatments over 8 years across 11 National Forests in California. Eight years post treatment, total surface fuel load returned to 67 to 79% and 55 to 103% of pretreatment levels following fire-only and mechanical treatments respectively. Herbaceous or shrub cover exceeded pretreatment levels two-thirds of the time 8 years after treatment. Fire-only treatments warranted re-entry at 8 years post treatment owing to the accumulation of live and dead fuels and minimal impact on canopy bulk density. In general, mechanical treatments were more effective at reducing canopy bulk density and initially increasing canopy base height than prescribed fire. However, elevated surface fuel loads, canopy base height reductions in later years and lack of restoration of fire as an ecological process suggest that including prescribed fire would be beneficial.

Inventories of greenhouse gas (GHG) emissions from wildfire provide essential information to the state of California, USA, and other governments that have enacted emission reductions. Wildfires can release a substantial amount of GHGs and other compounds to the atmosphere, so recent increases in fire activity may be increasing GHG emissions. Quantifying wildfire emissions however can be difficult due to inherent variability in fuel loads and consumption and a lack of field data of fuel consumption by wildfire. We compare a unique set of fuel data collected immediately before and after six wildfires in coniferous forests of California to fuel consumption predictions of the first-order fire effects model (FOFEM), based on two different available fuel characterizations. We found strong regional differences in the performance of different fuel characterizations, with FOFEM overestimating the fuel consumption to a greater extent in the Klamath Mountains than in the Sierra Nevada. Inaccurate fuel load inputs caused the largest differences between predicted and observed fuel consumption. Fuel classifications tended to overestimate duff load and underestimate litter load, leading to differences in predicted emissions for some pollutants. When considering total ground and surface fuels, modeled consumption was fairly accurate on average, although the range of error in estimates of plot level consumption was very large. These results highlight the importance of fuel load input to the accuracy of modeled fuel consumption and GHG emissions from wildfires in coniferous forests.

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