Tree species hyperdominance and rarity in the South American Cerrado

The South American Cerrado, the largest savanna of the Americas and the world's most tree-biodiverse, is critically endangered, with just 8% protected and more than half deforested. However, the extent of its tree diversity and abundance remains poorly quantified. Using a unique biome-wide eco-floristic dataset with 222 one-hectare plots, we estimate the Cerrado has ~1605 tree species and has extreme hyperdominance, with fewer than 2% (30 species) accounting for half of all trees. A single family, Vochysiaceae, represents 17% of all trees, and the most abundant species, Qualea parviflora, accounts for 1 in 14 trees. In contrast, 63% of the species are rare, with fewer than 100 trees across all plots. Remote sensing and spatial modelling suggest the Cerrado has lost 24 billion trees since 1985, equivalent to three times the Earth's human population. We estimate up to 800 tree species may remain undetected in Cerrado ecosystems and could face extinction in a few decades due to deforestation. This hyperdominance parallels patterns in Amazonian forests and highlights risks both biomes face for species loss due to fragmentation, deforestation, and land-use change. Our findings highlight the Cerrado's critical but undervalued role in global biodiversity, its vulnerabilities, and the urgent need for conservation to avoid irreversible species and biome loss

Variation in wood density across South American tropical forests.

Wood density is a critical control on tree biomass, so poor understanding of its spatial variation can lead to large and systematic errors in forest biomass estimates and carbon maps. The need to understand how and why wood density varies is especially critical in tropical America where forests have exceptional species diversity and spatial turnover in composition. As tree identity and forest composition are challenging to estimate remotely, ground surveys are essential to know the wood density of trees, whether measured directly or inferred from their identity. Here, we assemble an extensive dataset of variation in wood density across the most forested and tree-diverse continent, examine how it relates to spatial and environmental variables, and use these relationships to predict spatial variation in wood density over tropical and sub-tropical South America. Our analysis refines previously identified east-west Amazon gradients in wood density, improves them by revealing fine-scale variation, and extends predictions into Andean, dry, and Atlantic forests. The results halve biomass prediction errors compared to a naïve scenario with no knowledge of spatial variation in wood density. Our findings will help improve remote sensing-based estimates of aboveground biomass carbon stocks across tropical South America

Canopy functional trait variation across Earth’s tropical forests

Tropical forest canopies are the biosphere’s most concentrated atmospheric interface for carbon, water and energy. 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 properties. This situation arises, in part, from a lack of understanding about how and why the functional properties of tropical forest canopies vary geographically. 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