Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects.We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives. Geosphere-Biosphere Program (IGBP) and DIVERSITAS, the TRY database (TRY-not an acronym, rather a statement of sentiment; https ://www.try-db.org; Kattge et al., 2011) was proposed with the explicit assignment to improve the availability and accessibility of plant trait data for ecology and earth system sciences. The Max Planck Institute for Biogeochemistry (MPI-BGC) offered to host the database and the different groups joined forces for this community-driven program. Two factors were key to the success of TRY: the support and trust of leaders in the field of functional plant ecology submitting large databases and the long-term funding by the Max Planck Society, the MPI-BGC and the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, which has enabled the continuous development of the TRY database.

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We report the development of a new Spatially Explicit Individual-Based Dynamic Global 2 Vegetation Model (SEIB-DGVM), the first DGVM that can simulate the local interactions 3 among individual trees within a spatially explicit virtual forest. In the model, a sample plot is 4 placed at each grid box, and then the growth, competition, and decay of each individual tree 5 within each plot is calculated by considering the environmental conditions for that tree as it 6 relates to the trees that surround it. Based on these parameters only, the model simulated time

Summary1 Maximum attainable height varies greatly between tree species in tropical rain forests and covaries with demographic and allometric traits. We examined these relationships in 27 abundant tree species in a mixed dipterocarp forest. These species were monitored over 3 years in two 1-ha plots in western Borneo. A 95-percentile upper height limit was used to represent maximum height, to avoid sample size differences among populations. 2 Average growth rate in trunk diameter was regressed against trunk diameter using a maximum likelihood model and assuming that growth rates were exponentially distributed around the average. Estimated average growth rate at small trunk diameters (up to 11 cm) was independent of maximum height among the 27 species, while the degree of growth reduction at larger diameters was larger for species with smaller maximum height. 3 The recruitment rate efficiency of saplings was negatively correlated with maximum height, regardless of the measure used to assess species abundance. In particular, sapling recruitment per unit basal area declined greatly with increasing maximum height, consistent with model predictions of the traits required for the stable coexistence of species at different heights within the canopy. 4 Allometric analyses showed that understorey species had shorter heights at the same trunk diameter, and deeper crowns at the same tree height, than canopy species. Therefore, understorey species showed adaptive morphology to deep shade. 5 The regressed size-dependent pattern of average growth rate and an assumption that the population was in a steady state readily explained the observed trunk diameter distributions for 21 species among 27 examined. These species, for which the projected size distribution hardly changed when the natural increase or decrease of the population was set at γ = ± 0.005 year − 1 , had mortality rates of more than four times the value of γ .

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