Carbon Consequences of Land Management in the Greater Yellowstone Ecosystems (GYE) over the Past Three Decades
Abstract
Natural disturbances and land management directly change C stored in biomass and soil pools, and can have indirect impacts on long-term C balance. In this study we compared C stocks in National Parks (Yellowstone and Grand Teton) and neighboring National Forests (Caribou-Targhee, Teton, and Shoshone) to quantify carbon effects of natural disturbances and land management within National Parks (NPs) and National Forests (NFs). We used the Forest Vegetation Simulator (FVS) to evaluate carbon effects of natural disturbances and land management. The original FVS was developed to predict stand dynamics in the mixed forests of the mountainous regions in Idaho and Montana. Since then it has been widely used for forest management and carbon studies. Major disturbances and land-management activities considered in this study include forest fires, mountain pine beetle outbreaks, harvesting (clear-cuts and thinning), and fuel treatments. To account for the direct C fluxes from land management, areas of forest harvesting identified from time series Landsat images was used to calculate the average harvest rate in different stand type, which was defined by a combination of forest type, age and topography. Fuel treatment records obtained from local NF offices was used to estimate biomass change resulting from fuel treatments. The frequency and severity of the disturbances and land-management activities, derived through the disturbance mapping from time series Landsat images, was used to develop distributions of management and disturbance events in FVS, which would allow for calculation of their effects on C stocks through time in the NFs and NPs. This approach was applied to the entire GYE region and the results will be introduced at the conference.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2013
- Bibcode:
- 2013AGUFM.B33B0484Z
- Keywords:
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- 0428 BIOGEOSCIENCES Carbon cycling;
- 0480 BIOGEOSCIENCES Remote sensing