Plant traits – the morphological, anatomical, physiological, biochemical and phenological characteristics of plants and their organs – determine how primary producers respond to environmental factors, affect other trophic levels, influence ecosystem processes and services and provide a link from species richness to ecosystem functional diversity. Trait data thus represent the raw material for a wide range of research from evolutionary biology, community and functional ecology to biogeography. Here we present the global database initiative named TRY, which has united a wide range of the plant trait research community worldwide and gained an unprecedented buy‐in of trait data: so far 93 trait databases have been contributed. The data repository currently contains almost three million trait entries for 69 000 out of the world's 300 000 plant species, with a focus on 52 groups of traits characterizing the vegetative and regeneration stages of the plant life cycle, including growth, dispersal, establishment and persistence. A first data analysis shows that most plant traits are approximately log‐normally distributed, with widely differing ranges of variation across traits. Most trait variation is between species (interspecific), but significant intraspecific variation is also documented, up to 40% of the overall variation. Plant functional types (PFTs), as commonly used in vegetation models, capture a substantial fraction of the observed variation – but for several traits most variation occurs within PFTs, up to 75% of the overall variation. In the context of vegetation models these traits would better be represented by state variables rather than fixed parameter values. The improved availability of plant trait data in the unified global database is expected to support a paradigm shift from species to trait‐based ecology, offer new opportunities for synthetic plant trait research and enable a more realistic and empirically grounded representation of terrestrial vegetation in Earth system models.

Surveying Savannas: Savannas are structurally similar across the three major continents where they occur, leading to the assumption that the factors controlling vegetation structure and function are broadly similar, too. Lehmann et al. (p. 548 ) report the results of an extensive analysis of ground-based tree abundance in savannas, sampled at more than 2000 sites in Africa, Australia, and South America. All savannas, independent of region, shared a common functional property in the way that moisture and fire regulated tree abundance. However, despite qualitative similarity in the moisture–fire–tree-biomass relationships among continents, key quantitative differences exist among the three regions, presumably as a result of unique evolutionary histories and climatic domains.

Summary: Dynamic global vegetation models (DGVMs) are powerful tools to project past, current and future vegetation patterns and associated biogeochemical cycles. However, most models are limited by how they define vegetation and by their simplistic representation of competition. We discuss how concepts from community assembly theory and coexistence theory can help to improve vegetation models. We further present a trait‐ and individual‐based vegetation model (aDGVM2) that allows individual plants to adopt a unique combination of trait values. These traits define how individual plants grow and compete. A genetic optimization algorithm is used to simulate trait inheritance and reproductive isolation between individuals. These model properties allow the assembly of plant communities that are adapted to a site's biotic and abiotic conditions. The aDGVM2 simulates how environmental conditions influence the trait spectra of plant communities; that fire selects for traits that enhance fire protection and reduces trait diversity; and the emergence of life‐history strategies that are suggestive of colonization–competition trade‐offs. The aDGVM2 deals with functional diversity and competition fundamentally differently from current DGVMs. This approach may yield novel insights as to how vegetation may respond to climate change and we believe it could foster collaborations between functional plant biologists and vegetation modellers.

Savannas are defined based on vegetation structure, the central concept being a discontinuous tree cover in a continuous grass understorey. However, at the high-rainfall end of the tropical savanna biome, where heavily wooded mesic savannas begin to structurally resemble forests, or where tropical forests are degraded such that they open out to structurally resemble savannas, vegetation structure alone may be inadequate to distinguish mesic savanna from forest. Additional knowledge of the functional differences between these ecosystems which contrast sharply in their evolutionary and ecological history is required. Specifically, we suggest that tropical mesic savannas are predominantly mixed tree–C₄ grass systems defined by fire tolerance and shade intolerance of their species, while forests, from which C₄ grasses are largely absent, have species that are mostly fire intolerant and shade tolerant. Using this framework, we identify a suite of morphological, physiological and life-history traits that are likely to differ between tropical mesic savanna and forest species. We suggest that these traits can be used to distinguish between these ecosystems and thereby aid their appropriate management and conservation. We also suggest that many areas in South Asia classified as tropical dry forests, but characterized by fire-resistant tree species in a C₄ grass-dominated understorey, would be better classified as mesic savannas requiring fire and light to maintain the unique mix of species that characterize them.