Leaf Reflectance Spectroscopy Captures Variation in Carboxylation Capacity Across Species, Canopy Environment, and Leaf Age in Lowland Moist Tropical Forests

Understanding the pronounced seasonal and spatial variation in leaf photosynthetic capacity.

The Science

The annual fluxes of carbon in the tropics play a critical role in regulating Earth’s climate and are highly sensitive to global change; however, the process representation of the factors regulating tropical carbon uptake and loss in Earth System Models (ESMs) is poor. Tropical photosynthesis is an especially critical process to represent accurately in ESMs, and yet very limited information is available on the spatial and temporal patterns of key parameters that regulate leaf-level photosynthesis, such as the maximum carboxylation capacity (known as Vc,max). In addition, the tropics have the highest plant diversity of any terrestrial ecosystem on Earth, making it very challenging for ESMs to capture the important variations in photosynthetic capacity and leaf age across tropical species. This study investigated the capacity to provide much richer information on spatial and seasonal variation in tropical Vc,max across a broad range of tree species, using a spectroscopic approach instead of traditional gas exchange methods.

The Impact

The seasonal and spatial variation in photosynthetic capacity of terrestrial vegetation strongly regulates seasonal to annual fluxes of carbon between the land and the atmosphere, but ESMs currently lack a detailed representation of this variation given data limitations related to the logistical and technical challenges of collecting these data using traditional approaches. However, the spectroscopic approach presented here can be used to rapidly estimate plant photosynthetic capacity across a range of tropical species, leaf phenological stage, and locations, paving the way for a broad-scale remote sensing approach capable of measuring photosynthetic properties over large areas and through time.

Summary

Traditionally, Vc,max is inferred from direct measurements of leaf photosynthetic carbon assimilation rate at saturating light and at different levels of atmospheric carbon dioxide (CO2) concentration to describe the “CO2 response curve” of a leaf, which is then used to derive the maximum carboxylation capacity, or Vc,max. This direct approach is considered the “gold standard” but is also very time consuming and can be logistically challenging in remote areas such as the tropics. Instead, Brookhaven National Laboratory (BNL) scientists participating in the Next-Generation Ecosystem Experiments (NGEE)–Tropics project explored the use of spectroscopy to estimate the Vc,max of tropical leaves using only leaf-level reflectance measurements. To do this they collected leaf age and Vc,max data and linked them with measurements of leaf reflectance from a range of species sampled from tropical forests in Panama and Brazil. These results showed that leaf spectroscopy can rapidly predict Vc,max across species with high accuracy and low error. The team also showed that combining spectroscopic models enables the construction of the Vc,max-age relationship solely from leaf reflectance, suggesting that the spectroscopy technique can capture the seasonal variability in Vc,max in the tropics, potentially providing a powerful new way to inform ESMs.

Principal Investigator

Shawn Serbin
Brookhaven National Laboratory
sserbin@bnl.gov

Program Manager

Daniel Stover
U.S. Department of Energy, Biological and Environmental Research (SC-33)
Environmental System Science
daniel.stover@science.doe.gov

Funding

This work was supported by the Next-Generation Ecosystem Experiments (NGEE)–Tropics project, which is supported by the Office of Biological and Environmental Research, within the U.S. Department of Energy Office of Science.

Related Links

References

Wu, J., A. Rogers, L. P. Albert, and K. Ely, et al. "Leaf reflectance spectroscopy captures variation in carboxylation capacity across species, canopy environment and leaf age in lowland moist tropical forests". New Phytologist 224 (2), 663–674  (2019). https://doi.org/10.1111/nph.16029.