fit using the Hamiltonian Monte Carlo algorithm (HMC) implemented 279 in Stan (Carpenter et al., 2016). Posterior estimates were obtained from three independent 280 chains of 20,000 iterations after a burn-in of 10,000 iterations, thinning at intervals of 20. The 281 Stan code use to fit models are available from Github at: 282 https://github.com/mattocci27/LMApLMAs. Convergence of the posterior distribution was 283 assessed with the Gelman-Rubin statistic with a convergence threshold of 1.1 for all 284 diagnostics (Gelman et al., 2014a). 285 286 Model selection 287 Alternative LL models (Eqs. 5 and 13; see also Notes S3) fit to Panama data were compared 288 using the WAIC (Watanabe-Akaike
Open resource ↗mattocci27/LMApLMAs · pdf-raw-page:9 lines:1-76Paper record
Decomposing leaf mass into metabolic and structural components explains divergent patterns of trait variation within and among plant species
22 Mar 2017 · 10.1101/116855
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.
Code and data availability