ALBERT

Description: Functional diversity is critical for ecosystem dynamics, stability and productivity. However, dynamic global vegetation models (DGVMs) which are increasingly used to simulate ecosystem functions under global change, condense functional diversity to Plant Functional Types (PFTs) with constant parameters. Here, we develop an individual- and trait-based version of the dynamic global vegetation model (DGVM) LPJmL (Lund-Potsdam-Jena managed Land) called LPJmL-FIT (LPJmL with Flexible Individual Traits) which we apply to generate plant trait maps for the Amazon basin. LPJmL-FIT incorporates empirical ranges of five traits of tropical trees extracted from the TRY global plant trait database, namely specific leaf area ( SLA ), leaf longevity ( LL ), leaf nitrogen content ( N area ), the maximum carboxylation rate of RUBISCO per leaf area ( Vcmax area ), and wood density ( WD ). To scale the individual growth performance of trees, the leaf traits are linked by trade-offs based on the leaf economics spectrum, whereas wood density is linked to tree mortality. No pre-selection of growth strategies is taking place, because individuals with unique trait combinations are uniformly distributed at tree establishment. We validate the modeled trait distributions by empirical trait data and the modeled biomass by a remote sensing product along a climatic gradient. Including trait variability and trade-offs successfully predicts natural trait distributions and achieves a more realistic representation of functional diversity at the local to regional scale. As sites of high climatic variability, the fringes of the Amazon promote trait divergence and the coexistence of multiple tree growth strategies, whilst lower plant trait diversity is found in the species-rich center of the region with relatively low climatic variability. LPJmL-FIT enables to test hypotheses on the effects of functional biodiversity on ecosystem functioning and to apply the DGVM to current challenges in ecosystem management from local to global scales, i.e. deforestation and climate change effects. This article is protected by copyright. All rights reserved.