A two-step approximation for quantifying the effects of geographical location, environment and stand on tree allometry

Abstract Tree allometric models based on height (H) and diameter (D) are the most commonly used method to estimate forest biomass. Environments and stand characteristics are recognized to affect tree allometries. However, few studies have considered to incorporate these effects into allometric models, which restricts the use of these models in a wide domain. Adopting the power-law function Y=aGb as a basic model where Y is either tree height or biomass and the corresponding G is tree diameter D at breast height or D2H, we developed a two-step approximation procedure to quantify the effects of environments and stand characteristics on allometric coefficients a and b for Cunninghamia lanceolata and Pinus forest in China. Results show that most of the allometric coefficients are dependent on stand characteristics for C. lanceolata forest, and on mean annual temperature, stand age and latitude for Pinus forest. The allometric models via the two-step approximation Y=f(α+αjxj)Gf(β+βixi) (xj or xi are key drivers associated with environments and stand characteristics. α, αj, β and βi are regression coefficients) considerably improved the accuracy of tree height and biomass estimation. Compared to the basic model, the second approximation models significantly reduced the mean absolute bias between the observed and computed values by 25%–34% for C. lanceolata and by 21%–26% for Pinus forest, respectively. Our results highlight the necessity of incorporating environments and stand characteristics into the allometric models and provide a universal method to accurately estimate H-D-based tree biomass across a wider domain.