Competition and site weakly explain tree growth variability in undisturbed Central African moist forests

peer reviewedIdentifying and quantifying factors that influence tree growth are crucial issues to ensure sustainable forest management, particularly in moist tropical forests. Tree growth depends on several factors comprising ontogenic stage, competition by neighbours and environmental conditions. Several studies have focused on one or two of them, but very few have considered all three, especially in Central Africa. We investigated the effects of diameter and competition on tree growth, in four Central African sites characterized by their soil physicochemical properties, at both tree community and population levels. We calibrated growth models using diameter data collected on 29,741 trees between 2015 and 2018, on twelve 4 or 9-ha plots spread over the four sites. These models included diameter, wood density, competition indices and site effect as explainable variables at the community level and excluded wood density at the population level. At the community level, the best models explained 11% of growth variability with a decreasing effect of species wood density, diameter, site and competition. Our results show that even if low, site effect can result from different soil nutrients depending on both tree size and species wood density. We observed higher tree growth on sites with (i) high exchangeable K, organic C, total N and total P for low wood density species; (ii) high available P and C:N for small trees, high exchangeable Ca and Mg for medium to large trees, all belonging to medium and hard wood density species. At the population level, the best models explained between 0 to 43% of growth variability, with significant competition effect (resp. site effect) for 21 (resp. 9) of the 43 species studied. Site ranking varied greatly between the 9 species concerned, probably reflecting different sensitivities to the scarcity of particular soil nutrients. Synthesis. Our study provides original results on the factors influencing tree growth in Central Africa, showing that the potential effect of soil nutrients depends on tree size and species wood density. Remaining highly unpredictable at the population level, this effect makes it essential to increase the number of dynamics monitoring systems in logging concessions

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+