NHESS Natural Hazards and Earth System Sciences NHESS Nat. Hazards Earth Syst. Sci. 1684-9981 Copernicus Publications Göttingen, Germany 10.5194/nhess-10-2515-2010 Measuring the effect of fuel treatments on forest carbon using landscape risk analysis Ager A. A. 1 Finney M. A. 2 McMahan A. 3 Cathcart J. 4 USDA Forest Service, Pacific Northwest Research Station, Western Wildland Environmental Threat Assessment Center, 3160 NE 3rd Street, Prineville, OR, 97754, USA USDA Forest Service, Rocky Mountain Research Station, Fire Sciences Laboratory, 5775 Hwy. 10 West, Missoula, MT, 59808, USA USDA Forest Service, Forest Health Technology Enterprise Team, 2150A Centre Avenue, Fort Collins, CO, 80526, USA Oregon Department of Forestry, 2600 State Street, Salem, OR 97310, USA 07 12 2010 10 12 2515 2526 Copyright: © 2010 A. A. Ager et al. 2010 This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/3.0/ This article is available from https://nhess.copernicus.org/articles/10/2515/2010/nhess-10-2515-2010.html The full text article is available as a PDF file from https://nhess.copernicus.org/articles/10/2515/2010/nhess-10-2515-2010.pdf

Wildfire simulation modelling was used to examine whether fuel reduction treatments can potentially reduce future wildfire emissions and provide carbon benefits. In contrast to previous reports, the current study modelled landscape scale effects of fuel treatments on fire spread and intensity, and used a probabilistic framework to quantify wildfire effects on carbon pools to account for stochastic wildfire occurrence. The study area was a 68 474 ha watershed located on the Fremont-Winema National Forest in southeastern Oregon, USA. Fuel reduction treatments were simulated on 10% of the watershed (19% of federal forestland). We simulated 30 000 wildfires with random ignition locations under both treated and untreated landscapes to estimate the change in burn probability by flame length class resulting from the treatments. Carbon loss functions were then calculated with the Forest Vegetation Simulator for each stand in the study area to quantify change in carbon as a function of flame length. We then calculated the expected change in carbon from a random ignition and wildfire as the sum of the product of the carbon loss and the burn probabilities by flame length class. The expected carbon difference between the non-treatment and treatment scenarios was then calculated to quantify the effect of fuel treatments. Overall, the results show that the carbon loss from implementing fuel reduction treatments exceeded the expected carbon benefit associated with lowered burn probabilities and reduced fire severity on the treated landscape. Thus, fuel management activities resulted in an expected net loss of carbon immediately after treatment. However, the findings represent a point in time estimate (wildfire immediately after treatments), and a temporal analysis with a probabilistic framework used here is needed to model carbon dynamics over the life cycle of the fuel treatments. Of particular importance is the long-term balance between emissions from the decay of dead trees killed by fire and carbon sequestration by forest regeneration following wildfire.

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