HR: 1340h
AN: GC23A-0999    [Abstracts]
TI: Determining Regional Carbon Emissions Under Variable Fire Regimes in Central Siberia
AU: Hao, W
EM: whao@fs.fed.us
AF: USDA Forest Service, RMFS Fire Sciences Laboratory, 5775 US Highway 10 W., Missoula, MT 59808, United States
AU: * McRae, M J
EM: dmcrae@nrcan.gc.ca
AF: Natural Resources Canada, Canadian Forest Service, 1219 Queen St. E., Sault Ste. Marie, ON P6A 2E5, Canada
AU: Conard, S G
EM: sconard@fs.fed.us
AF: USDA Forest Service, osslyn Plaza-C, 4th Floor 1601 North Kent Street, Arlington, VA 22209, United States
AU: Ivanova, G A
EM: green@escapenet.ru
AF: Russian Academy of Sciences, Siberian Branch, V.N. Sukachev Institute, Akademgorodok, Krasnoyarsk, ON 660036, Russian Federation
AU: Baker, S p
EM: sbaker03@fs.fed.us
AF: USDA Forest Service, RMFS Fire Sciences Laboratory, 5775 US Highway 10 W., Missoula, MT 59808, United States
AU: Sukhinin, A I
EM: boss@ksc.krasn.ru
AF: Russian Academy of Sciences, Siberian Branch, V.N. Sukachev Institute, Akademgorodok, Krasnoyarsk, ON 660036, Russian Federation
AB: The Russian boreal zone is a region of global significance in terms of climate change impacts and carbon storage. Wildfires are the dominant disturbance regime here, currently burning 10 to 15 million ha annually depending upon burning conditions. Fires are projected to increase in both frequency and severity across Siberia under climate change. Changes in boreal fire regimes can be expected to lead to large changes in patterns of burn severity, with attendant effects on emissions per unit burned area and on postfire vegetation recovery. Developing accurate regional to continental estimates of carbon emissions from wildfires in Siberia requires data and models that will enable us to accurately quantify not only the areas that are burned annually, but the emissions per unit of burned area for fires of widely varying characteristics. Fire emissions are a function of the site specific fuel loading and structure, the burning conditions, and the amount of fuel consumed in a fire, all of which combine to determine the way a fire behaves and the amount of fuel that is burned. It is important in the accurate modeling of fire severity to be able to account for the heterogeneous nature of fire behavior. This is due to the constant changes in daily burning conditions, topography, and wildland fuel types. We have carried out a series of 20 experimental burns in Scots pine and larch forests of central Siberia under a variety of conditions to develop data and models that will allow us to integrate remote sensing data on active fire and burned areas with information on fuel condition and fire weather to estimate the impact of wildfires over large areas. Our research has shown that emissions from surface fires, which during normal fire years comprise roughly 80% of all fires, may range up to 3-fold as a function of the fuel type and the weather conditions preceding and during a fire. Emissions from crown fires may add another 7-15%, depending on the intensity of the fire and on crown structure. By correlating field data on fire behavior (e.g., rates of spread, energy release) and fuel consumption on these fires, we have developed models that relate these characteristics to elements of the Canadian Fire Behavior Prediction System or the Russian Moisture Index. We are now beginning to use these relationships to estimate the emissions from fires in pine and larch stands over large geographic areas of Siberia. They also have the potential to enable us to predict carbon emissions from active fires and from increased fires that might occur in the future under changing climate. Using emission factors derived from experimental fires, we can also project the emissions of various greenhouse gases and aerosols. Projecting future fire regimes and impacts of fire on carbon storage and atmospheric chemistry under a changing climate requires a baseline of recent fire activity that can be coupled with weather data and emission data to quantify past effects. This information can then be linked to outputs of climate models and projections of potential future vegetation change to predict future burned areas, fire severity and impacts on carbon storage and atmospheric chemistry.
DE: 0305 Aerosols and particles (0345, 4801, 4906)
DE: 0315 Biosphere/atmosphere interactions (0426, 1610)
DE: 0428 Carbon cycling (4806)
DE: 0468 Natural hazards
DE: 1640 Remote sensing (1855)
SC: Global Environmental Change [GC]
MN: 2007 Fall Meeting