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Fig 1.

Map of the study site.

The map was created using freely obtained shapefiles from the Ethiopian Mapping Agency.

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Table 1.

Summary of plot inventory data from studied plantation and natural forests.

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Table 2.

Distribution of harvested trees across tree size used in biomass estimation models.

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Table 3.

Model forms used to predict tree biomass.

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Table 4.

Tree species sampled and their mean of dendrometric properties for biomass modelling.

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Table 5.

Multispecies models developed in this study using different combinations of tree variables.

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Table 6.

Variable coefficients and validation metrics of cross-validated models with training set.

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Table 7.

Predictive accuracy of the viable multispecies models on the test datasets.

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Fig 2.

Relationships between predicted and observed aboveground biomass of the harvested trees.

The labelled M2-PF (Fig 2a) and M2-NF (Fig 2d) refer to the best-performing AGB models developed in this study for plantation and natural forests, respectively. Pan-tropical models are represented using the first authors’ name: Brown = Brown [18]; Chave = Chave et al. [17]. In Fig 2ac, the text “PF” indicates the AGB of harvested sample trees (n = 69) from Wef-Washa plantation forest used in testing model performance, whilst “NF” in Fig 2df signifies those from the natural forest (n = 58). rMPE (%) is the relative mean prediction error produced in the estimation of AGB. The diagonal lines show a 1:1 relation. Positive and negative rMPE values indicate under- and overestimation of the AGB, respectively. The p-value for rMPE was significantly different from zero at the 95% confidence interval when P < 0.05.

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Fig 3.

Bias in the AGB estimates of individual plots resulted from the aggregation of species in multispecies models.

The x-axis labels M1–7 correspond to multispecies models developed in this study using the dataset of plantation forest (Group I) as shown in Table 5. The remaining letters represent pan-tropical models: BR = Brown [18] and CH = Chave et al. [17]. RE (%) refers to relative errors in %. Orange dots represent AGB estimates from multispecies models that fell within the 95% confidence intervals of species-specific model estimates. Whereas, black dots indicate models whose estimates lie outside this confidence interval.

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Table 8.

Bias in across-plot average AGB estimates using data from 40 plots of plantation forest.

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Fig 4.

The mean relative error in plot-level AGB estimates resulted from the aggregation of species multispecies models.

Mean relative errors of the plot-level AGB estimates are represented by black dots; error bars show the 95% confidence interval of the mean. The x-axis labels M1–8 correspond to multispecies models developed in this study using the dataset of plantation forest. The remaining letters represent pan-tropical models: Br = Brown [18] and CH = Chave et al. [17].

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