Abstract
Abstract Forests and woodlands are critical terrestrial carbon stores. Tree aboveground biomass (AGB) can be estimated using allometric models and terrestrial laser scanning (TLS). However, internal tree stem damage from biotic decay is an unresolved source of error for both TLS and allometries, with implications for accurate carbon assessment. We destructively harvested 63 TLS‐scanned trees in an Australian savanna, quantified internal damage in each tree by sampling cross sections at multiple heights, and modelled the effect of damage on AGB estimation for individual trees and total estimated biomass. We tested the performance of TLS AGB modelling against five allometries, applying both database and field‐measured wood specific gravity. For TLS‐modelled and allometric AGB estimates, we tested if tree size and level of internal stem damage contributed to AGB deviations. Approximately half of the trees in the study sustained 1–10% damage by volume, which was most extensive in the base and main trunk, decreasing into the crown. On average, damaged trees had 5% internal stem damage (by volume, SD = 6.65%), with some as high as 30%. We found TLS‐derived quantitative structural models (TLS‐QSMs) using field‐measured wood specific gravity to be most accurate in estimating total biomass (R2 = 0.99, +0.59% bias). TLS‐QSMs tended to overpredict AGB of large, damaged trees, and AGB estimates from allometric models were largely unaffected by internal damage. For individual trees, all methods were effective for predicting field‐measured AGB (R2 > 0.84) and several ASMs performed well (± ~10% bias). In the absence of local wood specific gravity calibration, a pantropical ASM was most accurate. For systems where internal stem damage is low (<10% of tree volume), TLS can be used to estimate AGB with low levels of error, however more damaged wooded ecosystems (>10%) are likely to produce inflated biomass estimates if TLS is used without calibration for damage. Internal stem damage should be quantified in ASMs and incorporated into TLS‐modelled AGB calibration to avoid biomass overestimation and maintain high standards of precision in forest carbon accounting.
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