Decomposing leaf mass into metabolic and structural components explains divergent patterns of trait variation within and among plant species

Abstract

Across the global flora, interspecific variation in photosynthetic and metabolic rates depends more strongly on leaf area than leaf mass. In contrast, intraspecific variation in these rates is strongly mass-dependent. These contrasting patterns suggest that the causes of variation in leaf mass per area (LMA) may be fundamentally different within vs. among species. We developed a statistical modeling framework to decompose LMA into two conceptual components – metabolic LMAm (which determines photosynthetic capacity and dark respiration) and structural LMAs (which determines leaf toughness and potential leaf lifespan) - using leaf trait data from tropical forests in Panama and a global leaf-trait database. Decomposing LMA into LMAm and LMAs improves predictions of leaf trait variation (photosynthesis, respiration, and lifespan). We show that strong area-dependence of metabolic traits across species can result from multiple factors, including high LMAs variance and/or a slow increase in photosynthetic capacity with increasing LMAm. In contrast, strong mass-dependence of metabolic traits within species results from LMAm increasing from sunny to shady conditions. LMAm and LMAs were nearly independent of each other in both global and Panama datasets. Synthesis : Our results suggest that leaf functional variation is multi-dimensional and that biogeochemical models should treat metabolic and structural leaf components separately.

Plant phenotyping relevance

LMAを代謝成分と構造成分に分解する統計モデリング枠組みを開発し、葉形質の推定・予測に用いており、植物形質の計算的抽出が中心である。

Code and data availability

The paper's Stan analysis code for fitting the LMA decomposition models is explicitly stated to be publicly available on the authors' GitHub repository. The GLOPNET trait data are cited prior work, and the Panama dataset's availability is not stated, so neither qualifies as a paper-specific public asset.