Allometric equations to estimate aboveground biomass in spotted gum (Corymbia citriodora subspecies variegata) plantations in Queensland

By Trinh Huynh ^1,2,*, Tom Lewis ^1,3, Grahame Applegate ¹, Anibal Nahuel A. Pachas ^1,3 and David J. Lee ¹

¹  Forest Research Institute, University of the Sunshine Coast, Locked Bag 4, Maroochydore, QLD 4558, Australia; tlewis1@usc.edu.au (T.L.); gapples@usc.edu.au (G.A.); nahuel.pachas@daf.qld.gov.au (A.N.A.P.); dlee@usc.edu.au (D.J.L.)

²   Forest Science Institute of Central Highlands and South of Central, Da Lat City 670000, Vietnam

³   Department of Agriculture and Fisheries, Queensland Government, 1 Cartwright Road, Gympie, QLD 4570, Australia

*   Correspondence: trinh.huynh@research.usc.edu.au

Abstract:

Accurate equations are critical for estimating biomass and carbon accumulation for forest carbon projects, bioenergy, and other inventories. Allometric equations can provide a reliable and accurate method for estimating and predicting biomass and carbon sequestration. Cross-validatory assessments are also essential to evaluate the prediction ability of the selected model with satisfactory accuracy. We destructively sampled and weighed 52 sample trees, ranging from 11.8 to 42.0 cm in diameter at breast height from three plantations in Queensland to determine biomass. Weighted nonlinear models were used to explore the influence of different variables using two datasets: the first dataset (52 trees) included diameter at breast height (D), height (H) and wood density (ρ); and the second dataset (40 trees) also included crown diameter (CD) and crown volume (CV). Cross validation of independent data showed that using D alone proved to be the best performing model, with the lowest values of AIC = 434.4, bias = −2.2% and MAPE = 7.2%. Adding H and ρ improved the adjusted. R² (Δ adj. R² from 0.099 to 0.135) but did not improve AIC, bias and MAPE. Using the single variable of CV to estimate aboveground biomass (AGB) was better than CD, with smaller AIC and MAPE less than 2.3%. We demonstrated that the allometric equations developed and validated during this study provide reasonable estimates of Corymbia citriodora subspecies variegata (spotted gum) biomass. This equation could be used to estimate AGB and carbon in similar spotted gum plantations. In the context of global forest AGB estimations and monitoring, the CV variable could allow prediction of aboveground biomass using remote sensing datasets.

Keywords: biomass prediction; crown volume; cross-validatory assessment; destructive sampling; hardwood plantation; weighted nonlinear models

Sources: Forests 2022, 13, 486. Link: https://doi.org/10.3390/f13030486