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.

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.

Aim Tropical forests store 25% of global carbon and harbour 96% of the world's tree species, but it is not clear whether this high biodiversity matters for carbon storage. Few studies have teased apart the relative importance of forest attributes and environmental drivers for ecosystem functioning, and no such study exists for the tropics. Location Neotropics. Methods We relate aboveground biomass (AGB) to forest attributes (diversity and structure) and environmental drivers (annual rainfall and soil fertility) using data from 144,000 trees, 2050 forest plots and 59 forest sites. The sites span the complete latitudinal and climatic gradients in the lowland Neotropics, with rainfall ranging from 750 to 4350 mm year−1. Relationships were analysed within forest sites at scales of 0.1 and 1 ha and across forest sites along large‐scale environmental gradients. We used a structural equation model to test the hypothesis that species richness, forest structural attributes and environmental drivers have independent, positive effects on AGB. Results Across sites, AGB was most strongly driven by rainfall, followed by average tree stem diameter and rarefied species richness, which all had positive effects on AGB. Our indicator of soil fertility (cation exchange capacity) had a negligible effect on AGB, perhaps because we used a global soil database. Taxonomic forest attributes (i.e. species richness, rarefied richness and Shannon diversity) had the strongest relationships with AGB at small spatial scales, where an additional species can still make a difference in terms of niche complementarity, while structural forest attributes (i.e. tree density and tree size) had strong relationships with AGB at all spatial scales. Main conclusions Biodiversity has an independent, positive effect on AGB and ecosystem functioning, not only in relatively simple temperate systems but also in structurally complex hyperdiverse tropical forests. Biodiversity conservation should therefore be a key component of the UN Reducing Emissions from Deforestation and Degradation strategy.

Summary1. Tropical forests are globally important, but it is not clear whether biodiversity enhances carbon storage and sequestration in them. We tested this relationship focusing on components of functional trait biodiversity as predictors. 2. Data are presented for three rain forests in Bolivia, Brazil and Costa Rica. Initial above-ground biomass and biomass increments of survivors, recruits and survivors + recruits (total) were estimated for trees ≥10 cm d.b.h. in 62 and 21 1.0-ha plots, respectively. We determined relationships of biomass increments to initial standing biomass (AGB i ), biomass-weighted community mean values (CWM) of eight functional traits and four functional trait variety indices (functional richness, functional evenness, functional diversity and functional dispersion). 3. The forest continuum sampled ranged from 'slow' stands dominated by trees with tough tissues and high AGB i , to 'fast' stands dominated by trees with soft, nutrient-rich leaves, lighter woods and lower AGB i . 4. We tested whether AGB i and biomass increments were related to the CWM trait values of the dominant species in the system (the biomass ratio hypothesis), to the variety of functional trait values (the niche complementarity hypothesis), or in the case of biomass increments, simply to initial standing biomass (the green soup hypothesis). 5. CWMs were reasonable bivariate predictors of AGB i and biomass increments, with CWM specific leaf area SLA, CWM leaf nitrogen content, CWM force to tear the leaf, CWM maximum adult height H max and CWM wood specific gravity the most important. AGB i was also a reasonable predictor of the three measures of biomass increment. In best-fit multiple regression models, CWM H max was the most important predictor of initial standing biomass AGB i . Only leaf traits were selected in the best models for biomass increment; CWM SLA was the most important predictor, with the expected positive relationship. There were no relationships of functional variety indices to biomass increments, and AGB i was the only predictor for biomass increments from recruits. 6. Synthesis. We found no support for the niche complementarity hypothesis and support for the green soup hypothesis only for biomass increments of recruits. We have strong support for the biomass ratio hypothesis. CWM H max is a strong driver of ecosystem biomass and carbon storage and CWM SLA, and other CWM leaf traits are especially important for biomass increments and carbon sequestration.