Canadian Forest Service Publications
Models of the longitudinal distribution of ring area as a function of tree and stand attributes for four major Canadian conifers. 2013. Cortini, F.; Groot, A.; Filipescu, C.N. Annals of Forest Science 70:637-648.
Issued by: Great Lakes Forestry Centre
Catalog ID: 35184
Availability: PDF (request by e-mail)
Available from the Journal's Web site. †
† This site may require a fee
• Context It is widely accepted that ring area increment generally increases from the tree apex to the crown base and is more-or-less constant below the crown base (Pressler's law), but few quantitative models of this distribu tion have been developed. • Aims The aim ofthis study was to develop a model of ring area increment using easily obtained crown features and other tree or stand characteristics in order to further the understand ing and prediction of tree growth, form, and wood quality. • Methods Hie models were tit to stem analysis observations from white spruce, black spruce, balsam fir. and lodgepole pine. • Results In the final model, which includes tree crown and stand variables, ring area increment within the crown region was slightly curvilinear, the slope of ring area increment below the crown was non-zero, and the effect of butt swell was appreciable up-to a relative height of 0.10. • Conclusions The high accuracyofthe mixed effects model suggests that the three-component model form is appropriate for describing ring area profiles, whereas some tree-to-tree variation remains unexplained, The tree and stand variables used in these models can be easily measured in the field or obtained from remote sensing techniques.
Plain Language Summary
We developed new models for growth of tree rings from stem analysis observations of white spruce, black spruce, balsam fir, and lodgepole pine. We want to use the models to improve our understanding and predictions of tree growth, form, and wood quality. Current models are considered to be an oversimplification of the actual patterns of ring area distribution that occur under varying environmental conditions. The new models take into account three different regions of the tree stem: crown region, below-crown area and butt zone. We showed that the models can be developed from variables that are easily measured in the field or obtained from remote sensing techniques such as high-density LiDAR. The ability to obtain information on wood quality and growth of individual trees will enhance forest utilization decision making and support better forest management.