A Test of the Mean Distance Method for Forest Regeneration Assessment

Daniel Unger, Jeremy Stovall, Brian Oswald, David Kulhavy, I-Kuai Hung


A new distance-based estimator for forest regeneration assessment, the mean distance method, was developed by combining ideas and techniques from the wandering quarter method, T-square sampling and the random pairs method.  The performance of the mean distance method was compared to conventional 4.05 square meter plot sampling through simulation analysis on 405 square meter blocks of a field surveyed clumped distribution and a computer generated random distribution at different levels of density of 100, 50 and 25%.  The mean distance method accurately estimated density on the random populations but the mean distance method estimates were more variable than those of 4.05 square meter plot sampling.  The mean distance method overestimated actual density and was less precise than plot sampling when both methods were tested on the clumped populations.  The optimum sample sizes needed for the mean distance method to achieve the same precision as 4.05 square meter plot sampling at all three density levels, for both the random and clumped spatial distributions, were at least 10 times larger than the sample size used for 4.05 square meter plot sampling.


sampling, plot, distance, accuracy, seedlings

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© 2008 Mathematical and Computational Forestry & Natural-Resource Sciences