Leaf reflectance spectroscopy captures variation in carboxylation capacity across species, canopy environment and leaf age in lowland moist tropical forests

Abstract

Summary Understanding the pronounced seasonal and spatial variation in leaf carboxylation capacity (Vc,max) is critical for determining terrestrial carbon cycling in tropical forests. However, an efficient and scalable approach for predicting Vc,max is still lacking. Here the ability of leaf spectroscopy for rapid estimation of Vc,max was tested. Vc,max was estimated using traditional gas exchange methods, and measured reflectance spectra and leaf age in leaves sampled from tropical forests in Panama and Brazil. These data were used to build a model to predict Vc,max from leaf spectra. The results demonstrated that leaf spectroscopy accurately predicts Vc,max of mature leaves in Panamanian tropical forests (R2 = 0.90). However, this single‐age model required recalibration when applied to broader leaf demographic classes (i.e. immature leaves). Combined use of spectroscopy models for Vc,max and leaf age enabled construction of the Vc,max–age relationship solely from leaf spectra, which agreed with field observations. This suggests that the spectroscopy technique can capture the seasonal variability in Vc,max, assuming sufficient sampling across diverse species, leaf ages and canopy environments. This finding will aid development of remote sensing approaches that can be used to characterize Vc,max in moist tropical forests and enable an efficient means to parameterize and evaluate terrestrial biosphere models.

From the Arctic to the tropics: multibiome prediction of leaf mass per area using leaf reflectance

“…pigments (Chl a , b and carotenoid), chemical concentration (water%, N%, C%, isotopic N and C), and carboxylation capacity ( V cmax )) are also very important inputs for ESMs, and critical measures of plant form and function (Xu et al ., ; van Bodegom et al ., ; Rogers, ; Butler et al ., ; Rogers et al ., ; Ricciuto et al ., ). As these plant functional traits have been shown to be connected to leaf spectral reflectance (Asner & Martin, ; Feret et al ., ; Kokaly et al ., ; Serbin et al ., , , ; Wu et al ., ), we thus expect that similar globally convergent relationships with leaf spectra could be developed for these and other traits. To explore these additional generalities, future work can leverage emerging leaf spectra and trait databases, such as EcoSIS, which will facilitate much faster and easier development, testing and refinement of spectra–trait models.…”

Benchmarking and parameter sensitivity of physiological and vegetation dynamics using the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) at Barro Colorado Island, Panama

“…We add two further datasets on leaf traits, both based on canopy crane measurements at PNM and SLZ sites: Gu et al (2016) and Rogers et al (2017) and Wu et al (2019). Each of these contain estimates of V c,max , LMA, wood density, and leaf N content.…”

Benchmarking and Parameter Sensitivity of Physiological and Vegetation Dynamics using the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) at Barro Colorado Island, Panama

“…We add two further datasets on leaf traits, both based on canopy crane measurements at PNM and SLZ sites: (Gu et al, 2016) and Wu et al, 2019). Each of these contain estimates of Vc,max, LMA, wood density, and leaf N content.…”