Jean-Louis Doucet

The Congo Basin forests are currently undervalued. Economic and social returns from forestry and timber processing are relatively low compared to some nations outside Africa. Furthermore, the ecosystem services provided by the forests, such as the net absorption and storage of atmospheric carbon, continue to be considered by the international community as a free commodity. We propose an economic model involving maximizing the proportion of third-level timber processing and planting new forests that can increase forest economies and job creation by an order of magnitude. We argue that only by making forests valuable to the people and nations of the Congo Basin will we be able to avoid the large-scale deforestation that has occurred in West Africa and in other tropical forest regions, where the economic and social benefits of conversion were higher than those linked to preservation and sustainable harvest. We discuss knowledge gaps that need to be filled, possible technological solutions and policy reforms, and fiscal incentives needed to implement our model across the Congo Basin.

Predator–prey interactions are key ecological processes structuring wildlife communities by shaping species abundances and distributions, thereby influencing ecosystem functioning. They result from the interplay of bottom–up (e.g. prey availability) and top–down (e.g. predator control) forces. By altering species diversity and behaviors, humans can reshape trophic structures and predator–prey relationships. In Central African forests, where leopards Panthera pardus and African golden cats Caracal aurata are the largest carnivores, we examined trophic structure, spatiotemporal predator–prey dynamics, and responses to human presence and hunting pressure, a largely understudied issue. We hypothesized that increasing human pressure alters community structure and trophic organization, consistent with trophic downgrading and the view of humans as ‘super predators'. Using camera trap data from three sites along a human pressure gradient in the Republic of Congo and Cameroon, we tested two predictions: (P1) in low‐pressure forests, functional diversity is higher and predator–prey dynamics are shaped by ecologically‐driven bottom–up and top–down processes; (P2) in high‐pressure forests, humans exert top–down control across multiple trophic levels, reducing functional diversity and disrupting spatiotemporal predator–prey relationships. Combining community diversity analyses, structural equation modeling, and diel activity analyses, we found patterns consistent with both predictions. In low‐pressure areas, prey availability and predator presence jointly structured spatiotemporal patterns, supporting functionally rich communities. Conversely, in the most disturbed area with higher human density and intense hunting, both focal predators were absent, ungulate detections declined by 41–89%, and small generalists became up to 23 times more common than in undisturbed areas. Prey spatiotemporal patterns also shifted, reflecting human avoidance. These findings suggest that humans can act as ‘super predators' in Central African forests, overriding natural predator–prey spatiotemporal organization and disproportionately altering mammal communities. Together, our results indicate that limiting hunting pressure across large, connected landscapes appears critical for maintaining trophic network integrity and ecosystem functioning.

Accurately quantifying aboveground biomass (AGB) in tropical forest enrichment plantations remains challenging, particularly in managed regenerating stands where tree crown architecture, size structure, and species composition differ from the datasets used to calibrate classical allometric equations. Here, we assess whether AGB in tropical forest enrichment plantations can be estimated more accurately by combining tree-specific woody volume reconstructed from mobile laser scanning (MLS) with an explicit foliar-biomass component. We combined destructive measurements from 83 trees with high-resolution MLS point clouds to quantify biomass components, calibrate leaf-mass models, and assess the contribution of foliage to total AGB. Stems accounted for most of the biomass (65%), whereas leaves contributed only 3% on average. Among the models tested, Model 3, which included DBH, projected crown area, and wood density, showed the best performance (R² = 54.4%; RMSE = 2.43 kg). The main gain relative to regional (−20.4%) and pantropical (−25.6%) allometric equations came from the use of MLS-derived woody volume combined with species wood density, whereas the inclusion of predicted leaf biomass provided a moderate additional correction to the remaining bias. These results highlight the importance of canopy structure for biomass estimation in enrichment plantations and managed regenerating stands and support the use of LiDAR data as a robust alternative for AGB assessment in this context.

Accurately quantifying aboveground biomass (AGB) in tropical forest enrichment plantations remains challenging, particularly in managed regenerating stands where tree crown architecture, size structure, and species composition differ from the datasets used to calibrate classical allometric equations. Here, we assess whether AGB in tropical forest enrichment plantations can be estimated more accurately by combining tree-specific woody volume reconstructed from mobile laser scanning (MLS) with an explicit foliar-biomass component. We combined destructive measurements from 83 trees with high-resolution MLS point clouds to quantify biomass components, calibrate leaf-mass models, and assess the contribution of foliage to total AGB. Stems accounted for most of the biomass (65%), whereas leaves contributed only 3% on average. Among the models tested, Model 3, which included DBH, projected crown area, and wood density, showed the best performance (R² = 54.4%; RMSE = 2.43 kg). The main gain relative to regional (-20.4%) and pantropical (-25.6%) allometric equations came from the use of MLS-derived woody volume combined with species wood density, whereas the inclusion of predicted leaf biomass provided a moderate additional correction to the remaining bias. These results highlight the importance of canopy structure for biomass estimation in enrichment plantations and managed regenerating stands and support the use of LiDAR data as a robust alternative for AGB assessment in this context.

The Congo Basin forests are currently undervalued. Economic and social returns from forestry and timber processing are relatively low compared to some nations outside Africa. Furthermore, the ecosystem services provided by the forests, such as the net absorption and storage of atmospheric carbon, continue to be considered by the international community as a free commodity. We propose an economic model involving maximizing the proportion of third-level timber processing and planting new forests that can increase forest economies and job creation by an order of magnitude. We argue that only by making forests valuable to the people and nations of the Congo Basin will we be able to avoid the large-scale deforestation that has occurred in West Africa and in other tropical forest regions, where the economic and social benefits of conversion were higher than those linked to preservation and sustainable harvest. We discuss knowledge gaps that need to be filled, possible technological solutions and policy reforms, and fiscal incentives needed to implement our model across the Congo Basin.

The recently adopted EU Deforestation Regulation (EUDR) requires fine-scale verification of deforestation and forest degradation associated with timber supply chains. In Central Africa, however, region-specific data remain scarce, limiting the ability to distinguish the impacts of different logging practices and to differentiate regulatory definitions of degradation from actual ecological outcomes. This study addresses this gap by proposing a drone-based methodology to assess post-harvest impacts at the tree level. Focusing on FSC-certified selective logging, which typically removes only one to two trees per hectare, we aim to establish direct relationships between harvested tree characteristics and resulting canopy openings. Using high-resolution UAV imagery acquired before and after logging, combined with forest inventory data, canopy gaps are delineated and linked to individual trees. Gap size is analyzed in relation to species identity, tree diameter, felling conditions, forest type, topography, and crown-related traits derived from allometric equations. By identifying the key drivers of canopy opening at the individual level, this approach seeks to provide operational tools to better characterize forest degradation and support more robust monitoring frameworks under the EUDR.

The Congo Basin forests are currently undervalued. Economic and social returns from forestry and timber processing are relatively low compared to some nations outside Africa. Furthermore, the ecosystem services provided by the forests, such as the net absorption and storage of atmospheric carbon, continue to be considered by the international community as a free commodity. We propose an economic model involving maximizing the proportion of third-level timber processing and planting new forests that can increase forest economies and job creation by an order of magnitude. We argue that only by making forests valuable to the people and nations of the Congo Basin will we be able to avoid the large-scale deforestation that has occurred in West Africa and in other tropical forest regions, where the economic and social benefits of conversion were higher than those linked to preservation and sustainable harvest. We discuss knowledge gaps that need to be filled, possible technological solutions and policy reforms, and fiscal incentives needed to implement our model across the Congo Basin.

Understanding how carnivores coexist is central to ecological theory and conservation. Coexistence among sympatric species arises through niche partitioning across spatial, temporal, and trophic dimensions, yet these mechanisms remain poorly explored in Central African forests where leopards (Panthera pardus) and African golden cats (Caracal aurata) act as dominant and subordinate carnivores. Using camera trap data and molecular scat analyses from two sites in northern Congo, we provided the first robust leopard density estimates for the region (i.e., semideciduous forests in Central Africa) and assessed coexistence mechanisms between the two felids across spatial, temporal, and trophic axes. Spatially explicit capture–recapture models revealed comparable leopard densities across sites (5–6 individuals/100 km²), exceeding the regional average for Central and East Africa. Spatiotemporal occupancy models indicated spatial and temporal overlap, with no evidence of predictive or reactive temporal avoidance, though fine-scale co-occurrence declined near linear forest features (i.e., main rivers and roads) where both species’ marginal occupancy was highest. Conversely, dietary analyses showed trophic segregation: leopards consumed medium- to large-sized ungulates (>20 kg), whereas golden cats relied on smaller prey (≤5 kg), identifying trophic partitioning as the main axis facilitating coexistence in this prey-rich system. Maintaining prey diversity and minimizing disturbance are key to sustaining both species and their coexistence mechanisms. Such multidimensional approaches are essential to understand intraguild interactions and anticipate community shifts under increasing pressure.

Aucoumea klaineana is the most important timber species in Central Africa, naturally forming monodominant stands. While soil fungi are crucial for plant growth, their role in promoting monodominance or supporting suppressed, light-demanding trees remains underexplored. This study, the first to analyze the root mycobiota of A. klaineana, investigates fungal communities in monodominant stands and old-growth mixed forests in Gabon, and plantations in the DRC, sampling both canopy-reaching vs. suppressed individuals, using ITS2 rDNA and 18S rDNA high-throughput sequencing. We identified high fungal diversity in both regions but found no “core mycobiota” across stand types or tree social status (canopy-reaching vs. suppressed). Fungal communities varied significantly between stand types, emphasizing a context-dependent nature. Moreover, no distinct fungal communities characterize the mycobiota of suppressed trees. Our findings indicate that fungal associations, including mycorrhizal ones, are unlikely to be a driver of monodominance in A. klaineana. These results highlight the need to consider alternative processes, not related to fungal interactions, such as root grafting, in explaining the persistence of suppressed trees and the dynamics of monodominant stands of A. klaineana. Finally, this study illustrates the highly variable and diverse belowground communities associated with A. klaineana, whose functions and interactions could contribute to the sustainable management of this major timber tree species.