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On Distance Estimators of Density in Randomly Distributed Forests
J. H. Pollard
Vol. 27, No. 4 (Dec., 1971), pp. 991-1002
Published by: International Biometric Society
Stable URL: http://www.jstor.org/stable/2528833
Page Count: 12
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In various journals a number of methods are described which utilize spacing distances instead of fixed-area plots for estimating plant densities. Some of these methods are studied in this paper. Maximum likelihood (ML) estimators for the forest density are given and the distributions and moments of these estimators are derived. Other distance estimators of density have been used in the past, but they do not have the advantages of ML estimators, and it even seems difficult to determine their moments. A distance method has the advantage over a fixed plot method that the sample size does not depend upon the density being measured. There are many practical difficulties in using them, however, and some of these are discussed. The trees in a natural forest will not be distributed uniformly at random, and some care must be exercised in using a distance method. The difficulty can sometimes be overcome by using a stratified sampling method. The model is described in terms of trees and forests, but it is clear that it can be applied to many different types of problem.
Biometrics © 1971 International Biometric Society