Predicting annual stem diameter increment of selected tree species in Sinharaja rain forest by considering tree and stand level effects

Abstract

: Information on the diameter increment of tree species is important for developing a sustainable forest harvesting plan and for reforestation. Fitting a forest growth model for diameter increment can be utilized to get the information. The objective of this study was to develop a predictive model for the annual diameter increment of a multispecies stand in the Sinharaja Rain Forest in Sri Lanka. To fulfill this objective, four linear mixed-effect models were fitted to predict the annual diameter at breast height (dbh) increment of trees by using dbh, the natural logarithm of dbh, and species as a random effect. The model that contained random coefficients for the intercept term, dbh and log (dbh) were selected as the best-fitted model based on the Akaike Information Criterion (AIC) value and the likelihood ratio test. Then, the best-fitted model was expanded by adding other subsequent variables that describe the effects of competition from surrounding trees, and a size structure component, which is the maximum dbh. The final model comprised of this information dbh, log(dbh), stocking density, maximum dbh, and competition from trees smaller than the subject tree. Using the best-fitted final model, the annual dbh increment of the 10 selected abundant species was calculated. It was noted that all the selected species have growth rates that increase rapidly at the initial stage, and then reach its unique maximum growth rate. These increment patterns reflected that different species followed different annual dbh increment patterns. Therefore, this final model can be consolidated into an effective empirical model to project the future growth of a tropical rainforest.