%0 Articles
%T Methods and applications for improving parameter prediction models for stand structures in Finland
%A Siipilehto, Jouni
%D 2011
%J Dissertationes Forestales
%V 2011
%N 124
%R doi:10.14214/df.124
%U http://dissertationesforestales.fi/article/1911
%X This thesis reports attemps to improve the models for predicting forest stand structure for practical use, e.g. forest management planning (FMP) purposes in Finland. Comparisons were made between the Weibull and Johnson’s SB distribution and alternative regression estimation methods. Data used for preliminary studies was local but the final models were based on representative data. Models were validated mainly in terms of bias and RMSE in the main stand characteristics (e.g. volume) using independent data.
The bivariate SBB distribution model was used to mimic realistic variation in tree dimensions by including within-dbh-class height variation. Using the traditional method, diameter distribution with the expected height resulted in reduced height variation, whereas the alternative bivariate method utilized the error-term of the height model.The lack of models for FMP was covered to some extent by the models for peatland and juvenile stands. The validation of these models showed that the more sophisticated regression estimation methods provided slightly improved accuracy.
A flexible prediction and application for stand structure consisted of seemingly unrelated regression models for eight stand characteristics, the parameters of the three optional distributions and the Näslund’s height curve. The cross-model covariance structure was used for linear prediction application, in which the expected values of the models were calibrated with the known stand characteristics.
This provided a framework to validate the optional distributions and the optional set of stand characteristics. Height distribution is recommended for the earliest state of stands because of its continuous feature. From the mean height of about 4 m, Weibull dbh-frequency distribution is recommended in young stands if the input variables consists of arithmetic stand characteristics. In advanced stands, basal area-dbh distribution models are recommended. Näslund’s height curve proved useful. Some efficient transformations of stand characteristics are introduced, e.g. the shape index, which combined the basal area, the stem number and the median diameter. Shape index enabled SB model for peatland stands to detect large variation in stand densities. This model also demonstrated reasonable behaviour for stands in mineral soils.