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.

Summary1. Global change is likely to alter plant community structure, with consequences for the structure and functioning of the below-ground community and potential feedbacks to climate change. Understanding the mechanisms behind these plant-soil interactions and feedbacks to the Earth-system is therefore crucial. One approach to understanding such mechanisms is to use plant traits as predictors of functioning. 2. We used a field-based monoculture experiment involving nine grassland species that had been growing on the same base soil for 7 years to test whether leaf, litter and root traits associated with different plant growth strategies can be linked to an extensive range of soil properties relevant to carbon, nitrogen and phosphorus cycling. Soil properties included the biomass and structure of the soil microbial community, soil nutrients, soil microclimate and soil process rates. 3. Plant species with a high relative growth rate (RGR) were associated with high leaf and litter quality (e.g. low toughness, high nitrogen concentrations), an elevated biomass of bacteria relative to fungi in soil, high rates of soil nitrogen mineralization and concentrations of extractable inorganic nitrogen, and to some extent higher available phosphorus pools. 4. In contrast to current theory, species with a high RGR and litter quality were associated with soils with a lower rate of soil respiration and slow decomposition rates. This indicates that predicting processes that influence carbon cycling from plant traits may be more complex than predicting processes that influence nitrogen and phosphorus cycling. 5. Root traits did not show strong relationships to RGR, leaf or litter traits, but were strongly correlated with several soil properties, particularly the biomass of bacteria relative to fungi in soil and measures relating to soil carbon cycling. 6. Synthesis. Our results indicate that plant species from a single habitat can result in significant divergence in soil properties and functioning when grown in monoculture, and that many of these changes are strongly and predictably linked to variation in plant traits associated with different growth strategies. Traits therefore have the potential to be a powerful tool for understanding the mechanisms behind plant-soil interactions and ecosystem functioning, and for predicting how changes in plant species composition associated with global change will feedback to the Earth-system.

There are numerous ways in which plants can influence the composition of soil communities. However, it remains unclear whether information on plant community attributes, including taxonomic, phylogenetic, or trait-based composition, can be used to predict the structure of soil communities. We tested, in both monocultures and field-grown mixed temperate grassland communities, whether plant attributes predict soil communities including taxonomic groups from across the tree of life (fungi, bacteria, protists, and metazoa). The composition of all soil community groups was affected by plant species identity, both in monocultures and in mixed communities. Moreover, plant community composition predicted additional variation in soil community composition beyond what could be predicted from soil abiotic characteristics. In addition, analysis of the field aboveground plant community composition and the composition of plant roots suggests that plant community attributes are better predictors of soil communities than root distributions. However, neither plant phylogeny nor plant traits were strong predictors of soil communities in either experiment. Our results demonstrate that grassland plant species form specific associations with soil community members and that information on plant species distributions can improve predictions of soil community composition. These results indicate that specific associations between plant species and complex soil communities are key determinants of biodiversity patterns in grassland soils.

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Understanding the effects of warming on greenhouse gas feedbacks to climate change represents a major global challenge. Most research has focused on direct effects of warming, without considering how concurrent changes in plant communities may alter such effects. Here, we combined vegetation manipulations with warming to investigate their interactive effects on greenhouse gas emissions from peatland. We found that although warming consistently increased respiration, the effect on net ecosystem CO2 exchange depended on vegetation composition. The greatest increase in CO2 sink strength after warming was when shrubs were present, and the greatest decrease when graminoids were present. CH4 was more strongly controlled by vegetation composition than by warming, with largest emissions from graminoid communities. Our results show that plant community composition is a significant modulator of greenhouse gas emissions and their response to warming, and suggest that vegetation change could alter peatland carbon sink strength under future climate change.