Growth prediction for rubber tree and intercropped forest trees to facilitate environmental services valuation in South Thailand

Abstract

Tree growth parameters are necessary for valuing ecological services of trees in both natural forest and agroforest. These parameters are difficult to measure annually, and thus often lack the information needed in valuation. This study aimed to use regression analysis to create growth models for diameter at breast height (DBH), total height (TH), and merchantable height (MH) of Hevea brasiliensis Mull-Arg. (rubber tree) and five economic forest trees that are preferred by rubber farmers for intercropping, including Hopea odorata Roxb., Shorea roxburghii G.Don., Swietenia macrophylla King., Dipterocarpus alatus Roxb., and Azadirachta excelsa (Jack) Jacobs. Data were collected from 39 rubber plantations that contain rubber trees and the intercropped tree species at different ages in three provinces in South Thailand. The data were modelled using regression analysis with curve fitting to find the best-fitted curve to a given set of points by minimizing the sum of the squares of the residuals and standard error of the regression of the points from the curve. The results arrived at 21 models for the DBH, TH, and MH growth of rubber and the intercropped trees, in the forms of, power, sigmoid and exponential trends that vary according to the type of trees. The models can be used to predict tree growth parameters, which are useful for determining the value of ecosystem services such as carbon dioxide sequestration, oxygen production, and timber production.