Stand level silvicultural optimization utilizing a late-seral index constraint Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/76537534n

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  • A dynamic programming algorithm (MS PATH) was used to develop a stand level optimization model, FPS Optimizer. The model incorporates a late-seral constraint on the profit maximizing objective function utilizing a four-descriptor structural index as a proxy. This index, the 'Old-Growth Index', rates the late-seral structural quality of a given stand from a scale of zero to 100. Preliminary optimization trials were conducted on a generic planted stand representing industrial management practices, and a case-study stand which originated under natural conditions following harvesting. The FPS Optimizer generated silvicutural prescriptions for both stands, over a one hundred year analysis period, at varying potential final harvest ages. Optimization was conducted under two differing objective functions: 1) maximize the land expectation value of the stand; and 2) maximize the late-seral index value. Trial results indicate the preference for early, heavy thinnings across diameter classes under the late-seral objective, and moderate understory thinnings for LEV objective, followed by moderate overstory thinnings given longer final harvest ages. The industrial planted stand was able to achieve an index value of 50.0 by age 40 when optimizing on that value, but showed an inability to proceed beyond that level for several hundred years. The natural stand demonstrated a smooth and continuous development response of the old-growth index throughout the analysis period, and the FPS Optimizer model found prescriptions which both increased the LEV and index as compared to a no-harvest activity prescription. Limitations in the silvicultural capabilities of the FPS Growth Model and a simple four-variable old-growth index sometimes produced ambiguous and unrealistic results, thus illustrating limitations with the current form of the FPS Optimizer Model.
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