Based on a media release of the University of Oxford
Understanding tree traits and functional diversity in the tropics is crucial for biodiversity, ecosystem modelling, and conservation. Now, for the first time, thanks to satellite data from the Sentinel-2 satellites of the European Space Agency (ESA), scientists can show the great functional diversity of tropical forests as never seen before.
In a study led by the University of Oxford, and involving over 100 scientists from across the world, including the German Centre for Integrative Biodiversity Research (iDiv), researchers used data from over 1,800 vegetation plots, along with satellite, terrain, climate, and soil data, to predict variations in 13 tree traits and map the functional diversity of tropical forests.
They found that forests in the Americas, Africa, and Asia each use different parts of the available trait space. American tropical forests show 40% more functional richness than African and Asian forests, while African forests have the highest functional divergence — 32% more than American forests and 7% more than Asian ones.
The new research offers a global view of how and why tropical forest canopy traits vary across regions. The study also identifies regions needing more data to improve accuracy. State-of-the-art satellite data provided the researchers with high resolution information about what is happening in the forest canopies. On this basis, they were able to quantify the differences across continents.
The most biodiversity ecosystems on Earth
In their study, the team highlight the importance of tropical forest canopies in regulating carbon, water, and energy in the atmosphere. Tropical forests are the most biodiverse ecosystems on Earth, making up a large part of global diversity, including two-thirds of the 73,000 tree species. Over a billion people depend on them for their livelihoods.
However, we still have limited knowledge of how traits that affect forest functions (like shape, growth patterns, and responses to the environment) vary across large areas, especially in tropical forests. While factors like water, temperature, and soil influence plant traits, we don’t fully understand how they affect forest function.
There is also a need to compare predictions made by different methods. While plant trait databases help model trait distributions, the researchers say we still lack comprehensive data on traits for most tree species in tropical areas like the Amazon, which has about 15,000 species. Understanding trait variation across continents is important for predicting how ecosystems will respond to changes like climate change and land use. Previous studies have shown that plant traits vary across ecosystems and communities, reflecting how plant strategies connect to environmental conditions, allowing species to thrive in specific niches.
Artificial Intelligence can support biodiversity assessments
Thanks to the availability of field plot and trait data from local collaborators including the Mexican MONAFOR network, the Oxford Global Ecosystems Monitoring network (GEM), RAINFOR and the ForestPlots meta network, and also satellite data from the ESA, the team managed to compare the canopy functions in such detail.
Dr Benjamin Dechant from iDiv and Leipzig University investigated conceptually similar upscaling approaches for plant functional trait mapping in detail in the sTRAITS project, which was funded by iDiv’s synthesis centre sDiv. Dechant, who is also a co-author of the new paper, said: “Our paper uses a refined methodology to more directly link ground data to satellite imagery, which is crucial for the quality of the resulting trait maps. Importantly, the machine learning models were trained on a large amount of ground observations from multiple international measurement networks. The resulting maps reveal fascinating details on the spatial variability of key plant functional traits across the entire tropics, which will be very useful for numerous applications including analyses of functional biodiversity.”
Lead author Dr Jesús Aguirre-Gutiérrez, Associate Professor at the Environmental Change Institute (ECI) at the University of Oxford, said: “Artificial intelligence is rapidly improving our ability to map plant traits using deep-learning models applied to field data and photos. These models, especially convolutional neural networks, can analyse large amounts of remote-sensing data and have been combined with spectral data to map plant traits. New satellites with hyperspectral sensors and high spatial resolution, along with growing tree census data, are expanding possibilities for using AI across time and space.” But the team warn that AI should support — not replace — traditional ecological methods like field sampling and expert tree identification to ensure accurate biodiversity assessments.
Dr Aguirre-Gutiérrez added: “There’s a need for tools that can predict biodiversity distributions and its changes over time, and this approach is a step forward. In the future, satellite data could help track plant diversity annually, but this requires extensive field data, advanced models, more computing power, and strong collaborations among researchers and institutions.”
The study maps how the types of trees vary across tropical moist and dry forests, which host most of Earth’s tree species. The findings show that tree traits are strongly shaped by long-term climate, helping predict how climate change might affect these forests. The maps the researchers make available highlight key areas for future research, especially in under-studied regions like Africa and Asia. As the accuracy of predictions depends on data quality and coverage, they will improve as more data becomes available. These maps offer a significant step forward in understanding how tropical forests function globally.
Original publication
(Researchers with iDiv affiliation bolded)
Jesús Aguirre Gutiérrez, (…), Benjamin Dechant, (…), Yadvinder Malhi (2025). Canopy functional trait variation across Earth’s tropical forests. Nature, DOI: 10.1038/s41586-025-08663-2
Contact
Dr Benjamin Dechant
sDiv Synthesis Centre
German Centre for Integrative Biodiversity Research (iDiv)
Leipzig University
Phone: +49 341 9733248
Email: Benjamin.dechant@idiv.de
Kati Kietzmann
Media and Communications
German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig
Phone: +49 341 97 39222
Email: kati.kietzmann@idiv.de