Tropical forest canopies are the biosphere’s most concentrated atmospheric interface for carbon, water and energy^1,2. However, in most Earth System Models, the diverse and heterogeneous tropical forest biome is represented as a largely uniform ecosystem with either a singular or a small number of fixed canopy ecophysiological properties³. This situation arises, in part, from a lack of understanding about how and why the functional properties of tropical forest canopies vary geographically⁴. Here, by combining field-collected data from more than 1,800 vegetation plots and tree traits with satellite remote-sensing, terrain, climate and soil data, we predict variation across 13 morphological, structural and chemical functional traits of trees, and use this to compute and map the functional diversity of tropical forests. Our findings reveal that the tropical Americas, Africa and Asia tend to occupy different portions of the total functional trait space available across tropical forests. Tropical American forests are predicted to have 40% greater functional richness than tropical African and Asian forests. Meanwhile, African forests have the highest functional divergence—32% and 7% higher than that of tropical American and Asian forests, respectively. An uncertainty analysis highlights priority regions for further data collection, which would refine and improve these maps. Our predictions represent a ground-based and remotely enabled global analysis of how and why the functional traits of tropical forest canopies vary across space.

Tropical forests cover large areas of equatorial Africa and play a substantial role in the global carbon cycle. However, there has been a lack of biometric measurements to understand the forests’ gross and net primary productivity (GPP, NPP) and their allocation. Here we present a detailed field assessment of the carbon budget of multiple forest sites in Africa, by monitoring 14 one-hectare plots along an aridity gradient in Ghana, West Africa. When compared with an equivalent aridity gradient in Amazonia, the studied West African forests generally had higher productivity and lower carbon use efficiency (CUE). The West African aridity gradient consistently shows the highest NPP, CUE, GPP, and autotrophic respiration at a medium-aridity site, Bobiri. Notably, NPP and GPP of the site are the highest yet reported anywhere for intact forests. Widely used data products substantially underestimate productivity when compared to biometric measurements in Amazonia and Africa. Our analysis suggests that the high productivity of the African forests is linked to their large GPP allocation to canopy and semi-deciduous characteristics.

Tropical forests dominate terrestrial photosynthesis, yet there are major contradictions in our understanding due to a lack of field studies, especially outside the tropical Americas. A recent field study indicated that West African forests have among the highest forests gross primary productivity (GPP) yet observed, contradicting models that rank them lower than Amazonian forests. Here, we show possible reasons for this data-model mismatch. We found that biometric GPP measurements are on average 56.3% higher than multiple global GPP products at the study sites. The underestimation of GPP largely disappears when a standard photosynthesis model is informed by local field-measured values of (a) fractional absorbed photosynthetic radiation (fAPAR), and (b) photosynthetic traits. Remote sensing products systematically underestimate fAPAR (33.9% on average at study sites) due to cloud contamination issues. The study highlights the potential widespread underestimation of tropical forests GPP and carbon cycling and hints at the ways forward for model and input data improvement.

Tropical forests dominate terrestrial photosynthesis, yet there are major contradictions in our understanding due to a lack of field studies, especially outside the tropical Americas. A recent field study indicated that West African forests have among the highest forests gross primary productivity (GPP) yet observed, contradicting models that rank them lower than Amazonian forests. Here, we explore possible reasons for this data-model mismatch. We found the in situ GPP measurements higher than multiple global GPP products at the studied sites in Ghana. The underestimation of GPP by models largely disappears when a standard photosynthesis model is informed by local field-measured values of (a) fractional absorbed photosynthetic radiation (fAPAR), and (b) photosynthetic traits. Satellites systematically underestimate fAPAR in the tropics due to cloud contamination issues. The study highlights the potential widespread underestimation of tropical forests GPP and carbon cycling and hints at the ways forward for model and input data improvement.

Plant-pollinator interactions are critical to terrestrial ecosystem functioning and global food production but are experiencing increasing pressures from land use and global environmental changes. Plant functional traits and vegetation structure reflect the responses of vegetation to local environmental pressures and relate directly to the nesting and floral resources available to pollinators. Yet, little is known about the role of vegetation traits and structure in determining the organisation of plant-pollinator networks, nor on methods to predict such networks at broad spatial scales. Here, we evaluate how plant functional traits and vegetation structure influence plant-pollinator interaction patterns and how satellite remote sensing can aid in predicting such patterns at scale. We analysed a total of 209 plant-pollinator networks from across the tropics. Plant functional traits and vegetation structure were generated using spectral and LiDAR remote sensing. We found that pollination networks responded to vegetation functional traits along a spectrum of acquisitive to conservative plant resource use strategies. Networks were more modular in areas with shorter vegetation and low leaf nutrient content, while higher leaf photosynthetic capacity and leaf water content were associated with higher network connectance. Vegetation structure metrics associated with canopy openness and more acquisitive functional traits (high leaf photosynthetic capacity and phosphorus content) were associated with greater network specialisation (H₂’). Additionally, networks were more nested with increasing trait variability. Our findings reveal that plant functional strategies play an important role in structuring biotic interactions such as those between plants and pollinators, paving the way to predict these interaction networks at scale using remote sensing approaches.