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.

Background and Aims: Soil stability is a key ecosystem function provided by agricultural landscapes. A multitude of influential factors such as soil texture and plant community structure have been suggested, but few studies compare the relative importance of these factors for soil stability in the field. In addition, studies on effects of plant traits on soil stability have ignored intraspecific trait variability (ITV) despite growing evidence of its importance for ecosystem functioning. Methods: Using path model analysis, we quantified the effect of plant functional traits (PFTs), abiotic soil characteristics (soil texture) and vegetation characteristics on three soil stability measures in 30 field margins of an agriculture landscape of Korea, comparing models with and without ITV. Results: Variance in soil stability was explained to varying degrees (from 81% for soil aggregate stability to 35% for soil shear vane strength). The three soil stability measures were mainly affected directly by root density, while PFTs and soil texture exerted indirect effects through root density and vegetation parameters, respectively. Including ITV improved model explained variance and goodness-of-fit in all cases. Conclusion: The current study demonstrates that considering ITV is essential for uncovering the substantial effect of plant functional community composition on a key ecosystem function, soil stability.

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