Rapid estimation of photosynthetic leaf traits of tropical plants in diverse environmental conditions using reflectance spectroscopy.

PLoS One

Environmental & Climate Sciences Department, Brookhaven National Laboratory, Upton, NY, United States of America.

Published: November 2021

AI Article Synopsis

  • Tropical forests are vital carbon sinks, but there's uncertainty about how much CO2 they absorb, with traditional assessment methods being slow and complicated.
  • Reflectance spectroscopy offers a faster alternative for measuring leaf traits that affect CO2 exchange, allowing for rapid data collection over large datasets.
  • In this study, the researchers used spectroscopy to estimate key leaf traits from 53 tropical species in different environments, finding that their models accurately predicted important traits related to photosynthesis and respiration.

Article Abstract

Tropical forests are one of the main carbon sinks on Earth, but the magnitude of CO2 absorbed by tropical vegetation remains uncertain. Terrestrial biosphere models (TBMs) are commonly used to estimate the CO2 absorbed by forests, but their performance is highly sensitive to the parameterization of processes that control leaf-level CO2 exchange. Direct measurements of leaf respiratory and photosynthetic traits that determine vegetation CO2 fluxes are critical, but traditional approaches are time-consuming. Reflectance spectroscopy can be a viable alternative for the estimation of these traits and, because data collection is markedly quicker than traditional gas exchange, the approach can enable the rapid assembly of large datasets. However, the application of spectroscopy to estimate photosynthetic traits across a wide range of tropical species, leaf ages and light environments has not been extensively studied. Here, we used leaf reflectance spectroscopy together with partial least-squares regression (PLSR) modeling to estimate leaf respiration (Rdark25), the maximum rate of carboxylation by the enzyme Rubisco (Vcmax25), the maximum rate of electron transport (Jmax25), and the triose phosphate utilization rate (Tp25), all normalized to 25°C. We collected data from three tropical forest sites and included leaves from fifty-three species sampled at different leaf phenological stages and different leaf light environments. Our resulting spectra-trait models validated on randomly sampled data showed good predictive performance for Vcmax25, Jmax25, Tp25 and Rdark25 (RMSE of 13, 20, 1.5 and 0.3 μmol m-2 s-1, and R2 of 0.74, 0.73, 0.64 and 0.58, respectively). The models showed similar performance when applied to leaves of species not included in the training dataset, illustrating that the approach is robust for capturing the main axes of trait variation in tropical species. We discuss the utility of the spectra-trait and traditional gas exchange approaches for enhancing tropical plant trait studies and improving the parameterization of TBMs.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8525780PMC
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0258791PLOS

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