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Tropical forests account for one-third of terrestrial productivity but face a multitude of threats from climate change and direct human impacts. Landscape level maps of photosynthetic capacity would help determine pan-tropical drivers of photosynthetic capacity and generate robust projections of regional and global environmental change. We use a unique dataset of photosynthesis, collected from 990 trees using standardised protocols, to map Vcmax25 and Jmax25 across the tropics. Our field sites represent 35 tropical forest plots, cover all tropical continents, and include an elevation, precipitation, and logging gradient. Photosynthetic data was geolocated using LiDAR-mapped tree crowns, and combined with Sentinel-2A imagery and environmental datasets in Google Earth Engine to create Random Forest maps of Vcmax25 and Jmax25 across lowland only and lowland-montane tropical forest. At intercontinental scales, we find that Vcmax25 and Jmax25 are mainly controlled by climate. At the regional level, trait distributions are shaped by soil type. At local levels, trait patterns reflect spectral variation arising from topography and canopy structure. Our approach offers new opportunities to measure and monitor tropical forest productivity and improve the representation of photosynthesis in the next generation of Earth System Models.


Tropical forests
Remote sensing

Eleanor Thomson

Presentation within symposium:

S-42 From traits to ecosystems: remote sensing of tropical forest structure and function under environmental change

Global mapping of the photosynthetic capacity of tropical forests using Sentinel-2A imagery


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