Bair, Lucas (USDA-FS, Corvallis, OR Forest Science Laboratory, 3200 SW Jefferson Way, Corvallis, OR, 97331; Phone: 541-750-7422; mail: lbair@fs.fed.us)

Projecting Private Forest Investment and Forest Carbon with the Forest and Agricultural Sector Optimization Model – Green House Gas

L.S. Bair*, R.J. Alig

Study of landowner behavior aids in designing more effective incentives for promoting activities to mitigate climate change, and owners of private timberland could play important roles in any forestry-related contributions to reducing net greenhouse gas emissions. The Forest and Agricultural Sector Optimization Model—Green House Gas version (FASOMGHG) is a dynamic, nonlinear programming model of the forest and agricultural sectors in the United States that we used to model private timberland investment behavior over a one hundred year projection. FASOMGHG is the successor to the Forest and Agricultural Sector Optimization Model (FASOM) and endogenizes timber investment, harvest, and price to simulate allocation of land over time to competing activities in both the forest and agricultural sectors and the resultant net greenhouse gas emissions. We updated the forest sector data in the FASOMGHG model to provide more specific forest type and management intensity class information. For example, the model now differentiates seven planted pine management intensity classes for the U.S. South, compared to two classes in the 1990s FASOM model. The results of the baseline scenario in FASOMGHG illustrate the potential impact of intensive management on national timber production and net greenhouse gas reductions when implemented by private timberland owners. Preliminary findings indicate that allocation of timberland area to high intensity management leaves a large area under private management to relatively low management intensities. Alternative scenarios will be implemented to identify the allocation of management intensities by private timberland owners when, for example, investment in high levels of management is restricted.