Convergence in relationships between leaf traits, spectra and age across diverse canopy environments and two contrasting tropical forests

Abstract

SummaryLeaf age structures the phenology and development of plants, as well as the evolution of leaf traits over life histories. However, a general method for efficiently estimating leaf age across forests and canopy environments is lacking.Here, we explored the potential for a statistical model, previously developed for Peruvian sunlit leaves, to consistently predict leaf ages from leaf reflectance spectra across two contrasting forests in Peru and Brazil and across diverse canopy environments.The model performed well for independent Brazilian sunlit and shade canopy leaves (R 2 = 0.75-0.78), suggesting that canopy leaves (and their associated spectra) follow constrained developmental trajectories even in contrasting forests. The model did not perform as well for mid-canopy and understory leaves (R 2 = 0.27-0.29), because leaves in different environments have distinct traits and trait developmental trajectories. When we accounted for distinct environment-trait linkages -either by explicitly including traits and environments in the model, or, even better, by re-parameterizing the spectra-only model to implicitly capture distinct trait-trajectories in different environments -we achieved a more general model that well-predicted leaf age across forests and environments (R 2 = 0.79). Fundamental rules, linked to leaf environments, constrain the development of leaf traits and allow for general prediction of leaf age from spectra across species, sites and canopy environments.

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

“…This classification of leaf age is very similar to the three‐age‐category (young, mature and old) used in Wu et al . (), except that mature and old age classes were grouped together into a single mature age class, the reason being that leaf age was not tracked as frequently in Panama as in Brazil (Wu et al ., ), and therefore lacked the resolution to differentiate three age classes. Field measurements in Panama were conducted in the 2016 and 2017 dry seasons on sunlit upper canopy foliage.…”

A roadmap for improving the representation of photosynthesis in Earth system models

“…the input values get converted to canopy‐scale sunlit and shaded values blurring the definition of V c,max and J max and making comparison with measured leaf level values impossible. Moreover, leaf optical properties and foliar traits change markedly within the vertical canopy profile (Serbin et al ., ; Wu et al ., ; Yang et al ., ), but are often assumed static, which will generally lead to improper representation of light interception and utilization. This improper representation will feed forward to the integration of leaf energy balance and carbon uptake.…”

On the challenges of using field spectroscopy to measure the impact of soil type on leaf traits

“…In addition, structural differences (i.e. leaf thickness, number of air water interfaces, cuticle thickness and pubescence) between leaves may have significant effects on the relationship between leaf reflectance and traits, and can complicate interpretation of data (Sims and Gamon, 2002;Wu et al, 2016). The ability of spectroscopy to measure intraspecific variation in multiples traits between soil types, particularly when some of those traits are indirectly determined through constellation effects, has not been critically evaluated.…”