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Abstract
Forest managers face a difficult problem when required to estimate future physical and economic returns from timber stands when management strategies can vary by number and timing of thinnings, thinning type, thinning intensity and final harvest age. Field-based testing of these variables provides the most reliable information on stand and individual tree response to these practices, but is limited by the time and cost of these studies. Simulation studies based on growth models which derive their tree and stand response data on field observations are one method of exploring the response curve in greater detail and at a much lower cost in time and effort. Dynamic programming is an ideal method for exploring both stand and individual-tree response to new economic conditions and rotation schemes. Dynamic programming can be used to investigate possible responses to different thinning strategies, intensities, and timing of thinnings. It can also provide insights into management responses to changing markets and prices for wood products. However, simulation approaches are hindered by the weakness of long term (40+ years) growth projections and the ability of the computer systems to accurately model real-world constraints. In this paper, a dynamic programming (DP) based computer optimization technique is used and compared with the results of DP-based studies to previously published field studies of yellow-poplar. The similarities found lend credence to the biological reasonableness of the simulations and the ability of the simulation to provide detailed sensitivity analysis demonstrates its strengths in identifying new research questions for fieldbased studies.
Parent Publication
Citation
Pelkki, Matthew H. 1999. Using dynamic programming to explore hardwood silvicultural regimes. In: Stringer, Jeffrey W.; Loftis, David L., eds. 1999. Proceedings, 12th central hardwood forest conference; 1999 February 28-March 1-2; Lexington, KY. Gen. Tech. Rep. SRS-24. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research Station. 293 p
