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European Journal of Forest Research

, Volume 135, Issue 3, pp 581–592 | Cite as

Selecting the trees to be harvested based on the relative value growth of the remaining trees

  • Jari VauhkonenEmail author
  • Timo Pukkala
Original Paper

Abstract

Developing forest management plans based on tree-level decision factors is motivated by an increasing availability of single-tree forest inventory data and the needs to compare various silvicultural systems. Tree-level decision making makes it unnecessary to make an explicit pre-thinning choice between even- or uneven-aged forest management regimes since the cutting type is a result of optimal tree-level decisions. In this study, the management decisions were based on the development of 5-year value growth rate simulated at the level of individual trees and under varying degrees of competition. The specific objective was to retain trees with relative value growth rate higher than a specified threshold and harvest the other trees. The probability of removal was modeled using tree diameter, species, and pre-thinning average tree size and density as predictors. The feasibility of the approach was evaluated both at tree and stand levels and under the given uncertainty of prices and growth. By retaining trees that had at least 3 or 5 % value growth, the trees to be removed were mainly large dominant trees. Smaller trees were proposed to be harvested in stands where high competition called for releasing growing space to improve the relative value growth of the remaining trees. When the degree of uncertainty in growth and timber prices increased, fewer trees were harvested from small and large diameter classes. The approach provides instructions to obtain the required value growth despite changes in the timber prices and growth. These instructions are also feasible from the silvicultural point of view. Options for developing similar instructions for different regions, different types of uncertainties, such as assortment-specific trends in timber prices, or complete tree-level inventory data for large areas are discussed.

Keywords

Optimal thinning Risk Uncertainty Forest structure Adaptive optimization 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.School of Forest SciencesUniversity of Eastern FinlandJoensuuFinland

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