Using disaggregation to link individual-tree and whole-stand growth models

Abstract

Data from 200 plots randomly selected from the Southwide Pine Seed Source Study of loblolly pine (Pinus taeda L.) were used to fit whole-stand and individual-tree equations. Another 100 plots, also randomly selected, were used for validation. Outputs from the individual-tree model were then adjusted to match observed stand attributes (number of trees, basal area, and volume per hectare) by four disaggregation methods: proportional yield, proportional growth, constrained least squares, and coefficient adjustment. The first three are existing methods, and the fourth is new. The four methods produced similar results, and the coefficient adjustment was then selected as the method to disaggregate predicted stand growth among trees in the tree list. Results showed that, compared to the unadjusted individual tree model, the adjusted tree model performed much better in predicting stand attributes, while providing comparable predictions of tree diameter, height, and survival probability. The proposed approach showed promise in the ongoing effort to link growth models having different resolutions.