Data on dendrometric parameters, basic wood density, below- and aboveground biomass of tree species from Mangrove, Miombo, Mopane, and Mecrusse woodlands.

Mozambique is composed by the following forest types: Miombo, Mopane, Mecrusse, and Mangrove. Data on basic wood density at different height levels, tree component dry-mass, and other dendrometric parameters (root collar diameter, diameter at breast height, crown height, crown diameter, live crown length, and stem volume) for eight species typical of Miombo (Afzelia quanzensis Welw., Millettia stuhlmannii Taub., Pterocarpus angolensis DC., Brachystegia spiciformis Benth., and Julbernardia globiflora (Benth.) Troupin), Mopane (Colophospermum mopane Kirk ex J. Léonard), Mecrusse (Androstachys johnsonii Prain), and Mangrove (Avicennia marina (Forssk.)) forests collected from five provinces (Maputo, Gaza, Inhambane, Sofala, and Manica) of Mozambique are presented in this article. Biomass data of Miombo, Mecrusse, and Mopane woodlands were collected destructively, whereas those of Mangrove forests were collected using non-destructive methods.

Least squares-based biomass conversion and expansion factors best estimate biomass than ratio-based ones: Statistical evidences based on tropical timber species.

Due to its readiness to convert stem volumes (V) into biomass, national and regional aboveground biomass estimates and greenhouse gas reporting are generally based on biomass conversion and expansion factors (BCEFs). BCEF-based biomass (W) is computed by the following regression through the origin (RTO): W = BCEF × V. However, the regression slope (BCEF) is not obtained using least squares (LS); it is obtained as the ratio of observed biomass and stem volume. Therefore, the sum of squares of the residuals is not minimum. This may lead to strongly biased biomass estimates. Furthermore, in this case, the biomass is not modelled. In the present study, it was suggested that BCEFs should be obtained using LS through RTO. The objective of this study was to compare LS-based and ratio-based BCEFs with regard to predictive accuracy and ability. A dataset of 75 trees from 4 species was used for the comparisons. •LS-based BCEFs were associated with higher predictive accuracy and ability than ratio-based ones.•It was proved that RTO is appropriated for estimating BCEFs, as the intercept α was consistently not significant.•Ratio-based BCEFs may lead to seriously biased biomass and carbon stocks estimates.•BCEFs should be estimated using least squares.

Tree component biomass expansion factors and root-to-shoot ratio of Lebombo ironwood: measurement uncertainty.

BACKGROUND: National and regional aboveground biomass (AGB) estimates are generally computed based on standing stem volume estimates from forest inventories and default biomass expansion factors (BEFs). AGB estimates are converted to estimates of belowground biomass (BGB) using default root-to-shoot ratios (R/S). Thus, BEFs and R/S are not estimated in ordinary forest inventories, which results in uncertainty in estimates of AGB and BGB. Here, we measured BEF and R/S values (including uncertainty) for different components of Lebombo ironwood (Androstachys johnsonii Prain) trees and assessed their dependence on tree size. RESULTS: The BEF values of tree components were unrelated or weakly related to tree size, and R/S was independent of tree size. BEF values varied from 0.02 for foliage to 1.31 Mg m-3 for whole tree; measurement uncertainty (SE) varied from 2.9% for stem BEF to 10.6% for whole-tree BEF. The belowground, aboveground, and whole-tree BEF-based biomass densities were 30 ± 2.3 (SE = 3.89%), 121 ± 7.84 (SE = 3.23%), and 151 ± 9.87 Mg ha-1(SE = 3.27%), respectively. R/S was 0.24 with an uncertainty of 3.4%. CONCLUSIONS: Based on the finding of independence or weak dependence of BEF on tree size, we concluded that, for A. johnsonii, constant component BEF values can be accurately used within the interval of harvested tree sizes.

Allometric equations for estimating belowground biomass of Androstachys johnsonii Prain.

BACKGROUND: The belowground component of the trees is still poorly known because it needs labour- and time-intensive in situ measurements. However, belowground biomass (BGB) constitutes a significant share of the total forest biomass. I analysed the BGB allocation patterns, fitted models for estimating root components and root system biomasses, and called attention for its possible use in predicting anchoring functions of the different root components. RESULTS: More than half and almost one third of BGB is allocated to the lateral roots and to the root collar, respectively. More than 80% of the BGB is found at a depth range of 9.6-61.2 cm. As the tree size increased, the proportion of BGB allocated to taproots decreased and that allocated to lateral roots increased. All independent models performed almost equally, with the predictors explaining, on average, 98% of the variation in the BGB. CONCLUSIONS: It was hypothesised that BGB allocation patterns are a response of the anchoring functions of the tap and lateral roots and therefore, root component biomass models can be used as a methodology to predict anchoring functions of the different root components. Based on the fact that all models performed almost equally, the models using either diameter at breast height (DBH) exclusively as a predictor should be preferred, as tree height is difficult to measure. Models using the root collar diameter (RCD) only should be preferred when the tree is found cut down, as sometimes the RCD is affected by root buttress. Given the large sample size, the validation results, and the coverage of a wide geographical, soil and climatic range, the models fitted can be applied in all A. johnsonii stands in Mozambique.