Improving tree selection for partial cutting through joint probability modelling of tree vigor and quality

David Pothier, Mathieu Fortin, David Auty, Simon Delisle-Boulianne, Louis Vincent Gagné, Alexis Achim

Research output: Contribution to journalArticlepeer-review

31 Scopus citations


Tree classification systems are generally designed to predict the supply of high-quality logs for the wood processing industries and to mark defective trees for removal with the aim of improving both the vigor and quality of future stands. Although these two objectives are generally inversely related, their joint consideration could enable the development of robust criteria for improved tree selection in partial cuttings of northern hardwood stands by targeting low-vigor (LV) trees of high quality (HQ). In this study, we used a copula approach to model the joint probability distribution of trees characterized by both vigor and quality, which accounts for the statistical dependence between the different classes of both classification systems. The relationships between the probability of occurrence of a tree in each joint category and tree diameter at breast height (DBH) were quite similar among the three studied species: yellow birch (Betula alleghaniensis Britt.), sugar maple (Acer saccharum Marsh.), and American beech (Fagus grandifolia Ehrh.). In particular, the probability of occurrence of LV-HQ trees was characterized by a parabolic curve with a maximum value attained at the mid-DBH range, whereas that of LV and low-quality (LQ) trees increased with increasing DBH. This suggests that instead of harvesting large and mostly LV-LQ trees, partial cutting should target smaller LV-HQ trees, so that the volume of harvested HQ trees would increase without compromising the silvicultural objective of improving the vigor of future stands.

Original languageEnglish (US)
Pages (from-to)288-298
Number of pages11
JournalCanadian Journal of Forest Research
Issue number3
StatePublished - Jan 2013
Externally publishedYes

ASJC Scopus subject areas

  • Global and Planetary Change
  • Forestry
  • Ecology


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