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Mean height or dominant height – what to prefer for modelling the site index of Estonian forests? Cover

Mean height or dominant height – what to prefer for modelling the site index of Estonian forests?

Open Access
|Sep 2020

Abstract

The availability of a large amount of data from reliable sources is important for forest growth modelling. A permanent plot where trees are repeatedly measured provides a clearer picture of stand alterations. Various factors, including forest management, affect forest growth and accuracy of its assessment. In Estonia, mean height as a regression height prediction at mean square diameter is commonly used in forest management practice. Alternatively, dominant height can be used. The main advantage of using dominant height instead of mean height is that the growth of dominant trees is not so strongly affected by stand density (thinning). The aim of our research was to investigate the difference between mean height and dominant height when used as stand height. The research was based on the Estonian Network of Forest Research Plots (ENFRP). As a result, we found that the average mean height change was significantly greater in the case of thinning when compared to undisturbed stand development, whereas, the average dominant height change in the case of thinning compared to undisturbed development was less significant. As a side result, we developed a regression model that can be used for calculating the dominant height of the main tree species using stand attributes (mean height, quadratic mean diameter and density) with a residual standard deviation of 0.466 m.

DOI: https://doi.org/10.2478/fsmu-2020-0010 | Journal eISSN: 1736-8723 | Journal ISSN: 1406-9954
Language: English
Page range: 121 - 138
Submitted on: May 29, 2020
Accepted on: Jun 30, 2020
Published on: Sep 18, 2020
Published by: Estonian University of Life Sciences
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year

© 2020 Toomas Tarmu, Diana Laarmann, Andres Kiviste, published by Estonian University of Life Sciences
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.