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. Ecological restoration is a global priority that holds great potential for benefiting natural ecosystems, but restoration outcomes are notoriously unpredictable. Resolving this unpredictability represents a major, but critical challenge to the science of restoration ecology. 2. In an effort to move restoration ecology toward a more predictive science, we consider the key issue of variability. Typically, restoration outcomes vary relative to goals (i.e. reference or desired future conditions) and with respect to the outcomes of other restoration efforts. The field of restoration ecology has largely considered only this first type of variation, often focusing on an oversimplified success vs. failure dichotomy. The causes of variation, particularly among restoration efforts, remain poorly understood for most systems. 3. Variation associated with restoration outcomes is a consequence of how, where and when restoration is conducted; variation is also influenced by how the outcome of restoration is measured. We propose that variation should decrease with the number of factors constraining restoration and increase with the specificity of the goal. When factors (e.g. harsh environmental conditions, limited species reintroductions) preclude most species, little variation will exist among restorations, particularly when goals are associated with metrics such as physical structure, where species may be broadly interchangeable. Conversely, when few constraints to species membership exist, substantial variation may result and this will be most pronounced when restoration is assessed by metrics such as taxonomic composition. 4. Synthesis and applications. The variability we observe during restoration results from both restoration context (how, where and when restoration is conducted) and how we evaluate restoration outcomes. To advance the predictive capacity of restoration, we outline a research agenda that considers metrics of restoration outcomes, the drivers of variation among existing restoration efforts, experiments to quantify and understand variation in restoration outcomes, and the development of models to organise, interpret and forecast restoration outcomes.

Summary Recovering biological diversity and ecosystem functioning are primary objectives of ecological restoration, yet these outcomes are often unpredictable. Assessments based on functional traits may help with interpreting variability in both community composition and ecosystem functioning because of their mechanistic and generalizable nature. This promise remains poorly realized, however, because tests linking environmental conditions, functional traits, and ecosystem functioning in restoration are rare. Here, we provide such a test through what is to our knowledge the first empirical application of the ‘response–effect trait framework’ to restoration. This framework provides a trait‐based bridge between community assembly and ecosystem functioning by describing how species respond to environmental conditions based on traits and how the traits of species affect ecosystem functioning. Our study took place across 29 prairies restored from former agricultural fields in southwestern Michigan. We considered how environmental conditions affect ecosystem functioning through and independently of measured functional traits. To do so, we paired field‐collected trait data with data on plant community composition and measures of ecosystem functioning and used structural equation modelling to determine relationships between environmental conditions, community‐weighted means of functional traits and ecosystem functioning. Environmental conditions were predictive of trait composition. Sites restored directly from tillage (as opposed to those allowed to fallow) supported taller species with larger seeds and higher specific leaf area (SLA). Site age and fire frequency were both negatively related to SLA. We also found a positive relationship between soil moisture and SLA. Both trait composition and environmental conditions predicted ecosystem functioning, but these relationships varied among the measured functions. Pollination mode (animal pollination) increased and fire frequency decreased floral resource availability, seed mass had a negative effect on below‐ground biomass production, and vegetative height increased decomposition rate. Soil moisture and fire frequency both increased while site age decreased above‐ground biomass production, and site age and soil moisture both increased decomposition rate. Synthesis and applications. Our results suggest that both trait composition and environmental conditions play a role in shaping ecosystem function during restoration, and the importance of each is dependent on the function of interest. Because of this, environmental heterogeneity will be necessary to promote multiple ecosystem functions across restored landscapes. A trait‐based approach to restoration can aid interpretation of variable outcomes through insights into community assembly and ecosystem functioning.

Summary 1.Megaherbivores likely had important influences on past vegetation dynamics, just as they do in modern ecosystems. The exact nature of megaherbivores' role can be studied using a relatively new suite of palaeoecological techniques, including the quantification of fossil spores from Sporormiella and other coprophilous fungi as indicators of megafaunal biomass in sediment records. However, a quantitative linkage of spore abundance with megaherbivore biomass or grazing intensity has been lacking. 3. Both relative (per cent) and absolute (concentration) abundances of Sporormiella were significantly higher in traps inside the enclosure and were positively correlated with bison grazing intensity. The cut-off for distinguishing between bison-grazed and ungrazed traps was determined to be 2.8% Sporormiella of the total pollen and spore sum, consistent with previous palaeoecological reconstructions. The relationship between Sporormiella abundances and available grazing area around each trap was strongest at short radii (25-100 m), suggesting that spores do not disperse far from their source. Sporormiella should thus be considered a local-scale indicator of megaherbivore presence. 4.Traps in the grazed area had significantly higher percentages of Ambrosia and lower percentages of Poaceae pollen than traps from ungrazed areas. This suggests that the pollen record has the potential to detect the ecological effects of bison grazing on grassland community composition. 5.Synthesis. This study refines the use of Sporormiella as a proxy for local megaherbivore presence, especially in grassland systems. Multiproxy Sporormiella and pollen analyses may help elucidate the past drivers of grassland dynamics, including the possible role of bison in mediating grass-forb interactions during the variable moisture regimes of the last 12,000 years.