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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Despite recent advances in understanding tree species sensitivities to climate change, ecological knowledge on different species remains scattered across disparate sources, precluding their inclusion in vulnerability assessments. Information on potential sensitivities is needed to identify tree species that require consideration, inform changes to current silvicultural practices and prioritize management actions. A trait-based approach was used to overcome some of the challenges involved in assessing sensitivity, providing a common framework to facilitate data integration and species comparisons. Focusing on 26 abundant tree species from eastern Canada, we developed a series of trait-based indices that capture a species’ ability to cope with three key climate change stressors—increased drought events, shifts in climatically suitable habitat, increased fire intensity and frequency. Ten indices were developed by breaking down species’ response to a stressor into its strategies, mechanisms and traits. Species-specific sensitivities varied across climate stressors but also among the various ways a species can cope with a given stressor. Of the 26 species assessed, Tsuga canadensis (L.) Carrière and Abies balsamea (L.) Mill are classified as the most sensitive species across all indices while Acer rubrum L. and Populus spp. are the least sensitive. Information was found for 95% of the trait-species combinations but the quality of available data varies between indices and species. Notably, some traits related to individual-level sensitivity to drought were poorly documented as well as deciduous species found within the temperate biome. We also discuss how our indices compare with other published indices, using drought sensitivity as an example. Finally, we discuss how the information captured by these indices can be used to inform vulnerability assessments and the development of adaptation measures for species with different management requirements under climate change.