Response of bamboo canopy density to terrain, soil and stand factors

Key message

A nonlinear mixed effects canopy density model developed with predictor variables describing stand characteristics and soil nutrients provides a high prediction accuracy.

Abstract

Canopy density (CD) of a forest stand is an indicator of describing tree vitality, tree growth, competition status, environmental condition, and climate change. CD is substantially influenced by several site and environmental factors, such as soil, terrain, and stand factors. However, the CD prediction model developed utilizing the important site and environmental factors is still lacking. This study developed a nonlinear mixed-effects (NLME) CD model using data from 259 sample plots distributed across the moso bamboo (Phyllostachys edulis) forests in the eight provinces of southern China. Like fast-growing tree species, moso bamboo has high rates of growth and carbon sequestration, accumulating large amount of biomass in a short period. The CD model includes the effects of factors describing characteristics of terrains, soil and forest stands. The results showed that elevation significantly affected CD. The NLME CD model developed with the significant predictors included are: stand density (N), dominant height (DH), base area (BA), total nitrogen (TN), and soil organic carbon (SOC). When modeling random effects at the provincial level, the fitting accuracy of the model was significantly improved. Among several strategies used in calibrating NLME CD model or estimating random effects, an increased accuracy was obtained with increasing number of sample plots. However, using many sample plots per province to calibrate NLME CD model may increase the inventory costs with a little gain in the accuracy. Using the two medium BA-plots in each province, slope, and elevation or two largest BA-plots at the different slope-aspect could provide a compromise between measurement cost, model use efficiency, and prediction accuracy. NLME CD model can reduce measurement requirements in the field and support forest managers for more effective bamboo forest management strategies.