Abstract
The lack of appropriate analytical tools to evaluate the impact of forest management policies has hindered the sustainable use of the rain forest. Decisions about the level of forest management and financial investment require accurate predictions of future forest yields. A technique, using hierarchical clustering and canonical discriminant procedures, was developed previously to pool 112 timber species with similar growth increment characteristics into seven groups suitable for the construction of growth and yield models. Compatible growth and yield models were developed for each group by the solution of a system of differential equations expressing the rate of change of ingrowth, mortality, and survival growth components within a forest stand. The solution provides the means to project the status of the timber stand at any future time given some predefined initial stand conditions. The models are useful for inventory updating, allowable annual cut calculations, and management planning for natural or man...
Published Version
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