%0 Research article
%T A comparison of two parameter prediction methods for stand structure in Finland
%A Siipilehto, Jouni
%D 2000
%J Silva Fennica
%V 34
%N 4
%R doi:10.14214/sf.617
%U https://silvafennica.fi/article/617
%X The objective of this paper was to predict a model for describing stand  structure of tree heights (h) and diameters at breast height (dbh). The  research material consisted of data collected from 64 stands of Norway  spruce (Picea abies Karst.) and 91 stands of Scots pine (Pinus  sylvestris L.) located in southern Finland. Both stand types contained  birch (Betula pendula Roth and B. pubescent Ehrh.) admixtures. The  traditional univariate approach (Model I) of using the dbh distribution  (Johnson’s SB) together with a height curve (Näslund’s function) was  compared against the bivariate approaches, Johnson’s SBB distribution  (Model II) and Model Ie. In Model Ie within-dbh-class h-variation was  included by transforming a normally distributed homogenous error of  linearized Näslund’s function to concern real heights.  Basal-area-weighted distributions were estimated using the maximum  likelihood (ML) method. Species-specific prediction models were derived  using linear regression analysis. The models were compared with  Kolmogorov-Smirnov tests for marginal distributions, accuracy of stand  variables and the dbh-h relationship of individual trees. The  differences in the stand characteristics between the models were  marginal. Model I gave a slightly better fit for spruce, but Model II  was better for pine stands. The univariate Model I resulted in clearly  too narrow marginal h-distribution for pine. It is recommended applying  of a constrained ML method for reasonable dbh-h relationship instead of  using a pure ML method when fitting the SBB model.