Abstract
Tall trees (height ≥ 60 m) are keystone elements of tropical forests, strongly influencing biodiversity, carbon storage, and ecosystem resilience. Yet, their density and spatial distribution remain poorly quantified, especially in remote Amazonian regions, limiting our understanding of their ecological roles and contribution to forest–climate interactions.
We combined airborne LiDAR data from 900 transects across the Brazilian Amazon with environmental predictors to model tall‐tree density. Spatial extrapolations allowed us to generate regional distribution estimates and assess associations with climate, topography, and disturbance regimes.
Our model predicts that tall trees are unevenly distributed, with c. 14% of the estimated density concentrated in c. 1% of the Amazon and c. 50% within c. 11%. The highest densities occur in Roraima and the Guiana Shield provinces, where water availability is high and lightning or storm incidence is low. Modeled density strongly correlates with aboveground biomass, highlighting the disproportionate contribution of tall trees to carbon stocks. We estimate c. 55.5 million tall trees across the Brazilian Amazon.
These findings demonstrate that tall‐tree distribution is a crucial but underused predictor for biomass models. Understanding their ecological and spatial dynamics is vital for forest conservation and climate‐resilience strategies under increasing anthropogenic pressures.
We combined airborne LiDAR data from 900 transects across the Brazilian Amazon with environmental predictors to model tall‐tree density. Spatial extrapolations allowed us to generate regional distribution estimates and assess associations with climate, topography, and disturbance regimes.
Our model predicts that tall trees are unevenly distributed, with c. 14% of the estimated density concentrated in c. 1% of the Amazon and c. 50% within c. 11%. The highest densities occur in Roraima and the Guiana Shield provinces, where water availability is high and lightning or storm incidence is low. Modeled density strongly correlates with aboveground biomass, highlighting the disproportionate contribution of tall trees to carbon stocks. We estimate c. 55.5 million tall trees across the Brazilian Amazon.
These findings demonstrate that tall‐tree distribution is a crucial but underused predictor for biomass models. Understanding their ecological and spatial dynamics is vital for forest conservation and climate‐resilience strategies under increasing anthropogenic pressures.
| Original language | English |
|---|---|
| Article number | 70634 |
| Pages (from-to) | 152-168 |
| Number of pages | 17 |
| Journal | New Phytologist |
| Volume | 249 |
| Issue number | 1 |
| Early online date | 14 Oct 2025 |
| DOIs | |
| Publication status | E-pub ahead of print - 14 Oct 2025 |
Bibliographical note
Publisher Copyright:© 2025 The Author(s). New Phytologist © 2025 New Phytologist Foundation.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 13 Climate Action
Keywords
- airborne LiDAR
- spatial modeling
- biogeographic provinces
- tallest trees
- environmental factors
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