Power analysis and sustainable forest management

This paper discusses power analysis in the context of sustainable forest management. It is suggested that a priori power analysis should be formally incorporated into the planning stage of all experiments designed to test whether forestry practices are sustainable. A priori power analysis enables researchers to estimate the probability of making a Type II error (i.e., finding no significant difference when one in fact exists). This information is critical in the statistical assessment of sustainable forestry, as unwittingly accepting a Type II error could result in poor management decisions. In addition, it is proposed that statistical assessments of sustainable forestry objectives can be more relevant if alpha (α) is liberated from its traditional value of 0.05. It is argued that in the context of sustainable forestry, making a Type II error can be more costly than making a Type I error. Consequently, it often makes sense for beta (β) to be small (say 0.05) and α to take on a larger value. In other situations the cost of making a Type I error may be more important, thus a procedure which enables researchers to determine a locally relevant α:β ratio is recommended.

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