Biomass has been widely studied in terms of ecosystem ecology, timber production profitability, bioenergy (biofuels) and greenhouse gas emission reduction mechanisms. However, uncertainty in biomass estimation is still a current concern. In this study, direct and indirect methods were used to develop species-specific biomass estimation models (BEMs) for stem, bark, branch and crown compartments in 16-year old plantations of Eucalyptus dunnii and Corymbia citriodora. A total of 93 trees were destructively sampled. An analysis of covariance (ANCOVA) assessed the effect of species on biomass prediction. Our results indicated that equations developed by using parameters or predictors such as diameter at breast height (DBH), height (H), wood density (p) and branch diameter were generally significant (p < 0.05) and their regression lines fitted well the data (R² > 0.84). After a rigorous process that included testing hypotheses, checking diagnostic statistics, assessing model coefficients and model functionality, the most suitable stem BEMs corresponded to those ones derived from the compound variable DBH²Hp. The most reliable branch and crown BEMs used DBH and branch diameter respectively as single variable (simple linear models). Bark BEMs differ between species as DBH was the best predictor for E. dunnii whilst the compound variable DBH H predicted better for C. citriodora. The BEMs with multiple predictors, and in particular polynomial models, produced wider confidence intervals, unreliable coefficients, multicollinearity and higher proportion of outliers and leverage points. In conclusion, appropriate model diagnosis can reduce pitfalls and ensure selection of valid BEMs.

在生态系统生态，木材生产的获利能力，生物能源（生物燃料）和减少温室气体排放的机制方面，已经对生物质进行了广泛的研究。然而，生物量估计的不确定性仍然是当前关注的问题。在这项研究中，直接和间接的方法被用来为桉树和Corymbia citriodora的16年生人工林的茎，树皮，树枝和冠部隔室建立物种特异性生物量估计模型（BEM）。总共对93棵树进行了破坏性采样。协方差分析（ANCOVA）评估了物种对生物量预测的影响。我们的结果表明，通过使用参数或预测变量（例如，胸高（DBH）的直径，身高（H），木材密度（p）和分支直径通常很显着（p <0.05），它们的回归线与数据吻合很好（R ²  > 0.84）。经过严格的过程（包括检验假设，检查诊断统计数据，评估模型系数和模型功能）之后，最合适的茎BEM对应于从复合变量DBH ² H p衍生的茎BEM 。最可靠的分支BEM和拱顶BEM分别将DBH和分支直径用作单个变量（简单线性模型）。树皮BEMS物种之间不同的DBH是为最佳预测E.邓恩桉而化合物变量DBHħ预测更好C.柠檬桉。具有多个预测变量的BEM（尤其是多项式模型）产生了更宽的置信区间，不可靠的系数，多重共线性以及离群点和杠杆点的比例更高。总之，适当的模型诊断可以减少陷阱并确保选择有效的BEM。