Using plant functional attributes to quantify site productivity and growth patterns in mixed forests

Abstract

Forest growth models form one of several important prerequisites for sustainable management. The complexity of tropical moist forest means that there is often little objective information to classify sites and species for growth modelling and yield prediction. Classification based on observable morphological characteristics may be a useful surrogate for, or supplement to, other alternatives. This study investigated the utility of plant functional attributes (PFAs) for site and species classification. PFAs describe a plant in terms of its photosynthetic and vascular support system, and the sum of individual PFAs for all species on a plot provides an efficient summary of vegetation features at the site. Preliminary observations suggested that the PFA summary may also indicate site productivity, and that specific PFAs may be used to group species for modelling growth and yield. Data from 17 permanent plots in the tropical rainforests of North Queesland were used to test these preliminary observations. Standard PFA proformas were completed for each plot in January 1995, and the relationship between the PFAs, site productivity and specific growth patters were examined using discriminant analysis, linear regression and standard statistical tests. Results indicate that mean leaf size, and the incidence of species with vertical leaf inclination (more than 30.. above horizontal) are significantly correlated with site productivity. Of the PFAs assessed, five elements appear to offer a useful basis for grouping species for modelling: leaf size and inclination, a furcation index (i.e. relative height to first fork or break in the main stem), and the presence of lenticels and chlorophyllous tissue on the main stem. The restricted nature of our database limits comment on the general utility of the method, but results suggest that further work on PFAs is warranted.