A regional allometry for the Congo basin forests based on the largest ever destructive sampling

The estimation and monitoring of the huge amount of carbon contained in tropical forests, and specifically in the above-ground biomass (AGB) of trees, is needed for the successful implementation of climate change mitigation strategies. Its accuracy depends on the availability of reliable allometric equations to convert forest inventory data into AGB estimates. In this study, we tested whether central African forests are really different from other tropical forests with respect to biomass allometry, and further examined the regional variation in tropical tree allometry across the Congo basin forests. Following the same standardized protocol, trees were destructively sampled for AGB in six sites representative of terra firme forests. We fitted regional and local allometric models, including tree diameter, wood specific gravity, tree height, and crown radius in the AGB predictors. We also evaluated the AGB predictions at the tree level across the six sites of our new models and of existing allometric models, including the pantropical equations developed by Chave et al. (2014, 2005) and the local equations developed by Ngomanda et al. (2014) in Gabon. With a total of 845 tropical trees belonging to 55 African species and covering a large range of diameters (up to 200 cm), the original data presented here can be considered as the largest ever destructive sampling for a tropical region. Regional allometric models were established and including tree height and crown radius had a small but significant effect on AGB predictions. In contrast to our expectations, tree height and crown radius did not explain much between-site variation. Examining the performance of general models (pantropical or regional) versus local models (site-specific), we found little advantage of using local equations. Earlier pantropical equations developed for moist forests were found to provide reasonable predictions of tree AGB in most sites, though the wettest sites, i.e., evergreen forests in Equatorial Guinea and, to a lesser extent in Gabon, tended to show a wet forest allometry. For the Congo basin forests, except in Equatorial Guinea where local models might be preferred, we recommend using our regional models, and otherwise the most recent pantropical models, that were validated here. These results constitute a critical step for the estimation and monitoring of biomass/carbon stocks contained in the second largest contiguous block of tropical forests worldwide, and the successful implementation of climate change mitigation strategies, such as REDD+.