Abstract

Dynamic programming using a forward recursion has been found to be a flexible tool for optimizing the investment decisions involved in thinning- and rotation-age determination for several types of even-age forest growth models used by managers in various regions of the United States. This tool is also adaptable to additional decisions including planting density, pre-commercial thinning density, fertilization timing and intensity, and thinning type. Computational methods and limitations to integrating these additional decisions into several types of growth models are explained and reviewed.

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