Predicting seedling biomass of radiata pine from allometric variables

Abstract

Allometric equations predict tree seedling biomass from non-destructively measured variables such as stem diameter (D), height (H) and seedling silhouette area (A), measured by digital imaging. This study investigates whether one general allometric equation can predict biomass of radiata pine (Pinus radiata D.Don) seedlings grown under three levels of photosynthetic photon flux density (PPFD). It also identifies which commonly used variables (A, D2H or D2) were the best for predicting seedling biomass under these conditions. Radiata pine seedlings were grown with constant daytime (12 h d−1) PPFD = 500, 250 or 125 μmol m−2 s−1 for 11 weeks. Seedlings were randomly selected every 10 d for measurement. Analysis of covariance tested whether the relationship between seedling biomass and A, D2H or D2 varied for each PPFD level. PPFD levels influenced the relationship between biomass and A, D2H or D2. As a result, “full” allometric models which varied with PPFD levels were more accurate and precise at predicting biomass than “reduced” models which did not vary with PPFD level, although a “reduced” model using D2 also performed well.