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Accurate tree biomass estimation is critical and crucial for calculating carbon stocking as well as for studying climate change, forest health, productivity, nutrient cycling and budget etc. A total of 50 individuals of Shorea robusta Gaertn. f. were harvested to assess the biomass of tree components (leaf, branch, bark and stem). Carbon and nutrients (N, P and K) content in the tree components were also measured. This study adopted component biomass models with cross-validation technique. Additive biomass models were developed following the modified Gaussian maximum likelihood aggregated approach using open source software R (version 4.0.1). Component and additive biomass model used D (Diameter at Breast Height) as a sole predictor performed satisfactorily, the inclusion of total tree height (H) in Da*Hb form showed its supremacy over all the models. The best fitted additive model (AGB = 0.002056*D2.923998*H−0.69278 + 0.00848*D2.3896*H0.29648 + 0.04224*D2.06986*H0.65549 + 0.00552*D2.06723*H0.70536) and conventional model (Ln (AGB) = -2.7977 + 2.1829*ln(D) + 0.5073*ln(H)) took the lowest AIC, MPE and MAE and the highest model efficiency values. The derived species-specific additive and non-additive model showed its superiority over the frequently used pan-tropical models and suggested using this model for estimating aboveground biomass of S. robusta in Bangladesh.

The implementation of forest-based projects to mitigate greenhouse gas emissions requires the estimation of emission factors (here the difference in biomass stocks between two forest types). The estimation of these quantities using forest inventory data and allometric models implies different sources of errors that need to be prioritized to improve the precision of estimation. Using data from permanent sample plots in a tropical moist forest in central Africa and considering four allometric models with equal likelihood, the largest source of error in the estimate of the difference of biomass between intact and logged-over forest was that due to the model choice (40 % of the sum of squares). The error due to the model choice did not cancel out in the difference due to an interaction between the model’s prediction and the diameter structure of the forest. The variability in biomass between plots was the second largest source of error, but was underestimated because of post-stratification. The error due to the model choice could be reduced by weighting the models’ predictions.

GlobAllomeTree is an international platform for tree allometric equations. It is the first worldwide web platform designed to facilitate the access of the tree allometric equation and to facilitate the assessment of the tree biometric characteristics for commercial volume, bio-energy or carbon cycling. The webplatform presents a database containing tree allometric equations, a software called Fantallomatrik, to facilitate the comparison and selection of the equations, and documentation to facilitate the development of new tree allometric models, improve the evaluation of tree and forest resources and improve knowledge on tree allometric equations. In the Fantallometrik software, equations can be selected by country, ecological zones, input parameters, tree species, statistic parameters and outputs. The continuously updated database currently contains over 5000 tree allometric equations classified according to 73 fields. The software Fantallometrik can be also used to compare equations, insert new data and estimate the selected output variables using field inventory. The GlobAllomeTree products are freely available at the URL: http://globallometree.org for a range of users including foresters, project developers, scientist, student and government staff.

Models to assist management of lowland forests in Tanzania are in most cases lacking. Using a sample of 60 trees which were destructively harvested from both dry and wet lowland forests of Dindili in Morogoro Region (30 trees) and Rondo in Lindi Region (30 trees), respectively, this study developed site specific and general models for estimating total tree volume and aboveground biomass. Specifically the study developed (i) height-diameter (ht-dbh) models for trees found in the two sites, (ii) total, merchantable, and branches volume models, and (iii) total and sectional aboveground biomass models of trees found in the two study sites. The findings show that site specific ht-dbh model appears to be suitable in estimating treeheightsince the tree allometry was found to differ significantly between studied forests. The developed general volume models yielded unbiased mean prediction error and hence can adequately be applied to estimate tree volume in dry and wet lowland forests in Tanzania. General aboveground biomass model appears to yield biased estimates; hence, it is not suitable when accurate results are required. In this case, site specific biomass allometric models are recommended. Biomass allometric models which include basic wood density are highly recommended for improved estimates accuracy when such information is available.

The introduction of nitrogen fixing species (NFS) in fast-growing tree plantations is an alternative option to reduce fertilizer inputs. However, the success of mixed-species plantations depends on the balance between positive interactions among species (resulting from facilitation and/or complementarity) and the negative effects of interspecific competition. Using a carbon budget approach and coupling measurements of standing biomass, aboveground litterfall and soil CO2 efflux, we assessed the influence of replacing half of eucalypt trees by Acacia mangium on total belowground carbon flux (TBCF), net primary production (NPP) and its partitioning between above- and belowground growth at two tropical sites in Brazil (Itatinga) and in Congo (Kissoko) exhibiting contrasting climates, edaphic conditions and wood productions. Annual soil CO2 efflux (F-S) was significantly lower in the acacia monocultures than in eucalypt monocultures and mixed-species stands at both sites. Annual F-S was significantly lower at Itatinga compared to Kissoko for all stands while TBCF was significantly lower in the eucalypt stands only. In the eucalypt monocultures we found a significantly lower aboveground NPP (ANPP) and wood production (wood NPP) at Kissoko compared to Itatinga that was almost fully balanced by a significantly higher belowground NPP (BNPP), leading to similar NPP. Similarly, acacia monocultures exhibited significantly higher ANPP and wood NPP at Itatinga than at Kissoko. The mixed-species stands exhibited a significantly lower wood NPP and ANPP than the eucalypt monocultures at the Brazilian site while NPP of the mixture was not significantly different than the average NPP of the two monocultures. At the Congolese site, NPP of the mixture was significantly higher than the average NPP of the two monocultures. NPP was similar in the mixed-species stand and the eucalypt monoculture with a significantly lower partitioning of NPP to belowground production, leading to a one third higher wood biomass at harvest in the mixed-species stand. A positive effect of growing eucalypts with the nitrogen fixing acacia trees on stand wood production occurred at Kissoko but not at Itatinga. Mixed-species plantations with NFS can be advocated at sites where the productive gains resulting from nitrogen fixation are not compromised by other resource limitations. (c) 2012 Elsevier B.V. All rights reserved.

International audience

International audience