Remotely Predicting Leaf Age in Tropical Forests

New approach offers data across species, sites, and canopies, providing insights into carbon uptake by forests.

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Remotely Predicting Leaf Age in Tropical Forests

Leaf growth changes over time, as shown here by a six leaves from a mid‐canopy tree in Brazil. The leaves are visibly different but also have different capacities to take up carbon dioxide.

The Science

In tropical forests, knowing the age of leaves is vital to understand how trees take up carbon during different seasons. However, a robust method for efficiently estimating leaf age across multiple species and sites did not exist. Scientists designed a way to measure leaf age. The resulting method worked in diverse canopies. The team tested their method on contrasting forests in Peru and Brazil.

The Impact

This study shows that the age of leaves in tropical forest canopies can be monitored and mapped using an imaging spectroscopy approach. In addition, the research, in combination with an earlier study, highlights a way to reconstruct changes in leaf shape, physiology, and biochemistry over time. Finally, the work offers insights into age-dependent trends in plants. These trends could further inform terrestrial biosphere models and enable more accurate prediction of the terrestrial carbon sink that currently subsidizes fossil fuel use by absorbing approximately one-third of carbon dioxide emissions.


Knowing the age of leaves in a forest offers valuable information regarding the volume of carbon dioxide “consumed” by photosynthesis. Efficiently and accurately determining the age of the leaves is difficult.  Researchers devised a new way. They determined the leaf age by tagging developing leaves at budburst and following their development. They assembled data on 759 leaves from 11 tree species covering four canopy environments in forests in Brazil and Peru. The team also compared the results to a model developed for a Peruvian forest. The results suggest that canopy leaves follow constrained developmental trajectories, even in contrasting forests. The Peruvian model did not perform as well for Brazilian mid-canopy and understory leaves. Why? Because leaves in different environments have distinct traits and develop these traits in distinct trajectories. The team accounted for environment-trait linkages. The resulting, more general, model predicted leaf age across diverse forests and canopies.


BER Program Manager
Daniel Stover
U.S. Department of Energy, SC-23.1
Daniel.Stover@science.doe.gov, 301-903-0289

Lead author contact                                           
Jin Wu                                                               
Brookhaven National Laboratory                          

Institutional contact
Alistair Rogers
Brookhaven National Laboratory


J. Wu and S.P. Serbin were supported in part by the Next-Generation Ecosystem Experiment (NGEE-Tropics) project. The NGEE-Tropics project is supported by the Office of Biological and Environmental Research in the U.S. Department of Energy (DOE), Office of Science. Research in Brazil was supported by the National Science Foundation, National Aeronautics and Space Administration, and DOE. Research in Peru was supported by the Natural Environment Research Council.


J. Wu, C. Chavana-Bryant, N. Prohaska, S.P. Serbin, K. Guan, L.P. Albert, X. Yang, W.J.D. van Leeuwen, A.J. Garnello, G. Martins, Y. Malhi, F. Gerard, R. Cosme Oliviera, and S.R. Saleska  “Convergence in relationships between leaf traits, spectra and age across diverse canopy environments and two contrasting tropical forests.” New Phytologist 214(3), 1033-1048 (2016). [DOI: 10.1111/nph.10451]

Highlight Categories

Program: BER, CESD

Performer/Facility: DOE Laboratory

Additional: Collaborations, Non-DOE Interagency Collaboration, International Collaboration

Last modified: 3/26/2018 3:41:26 PM