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.

Community assembly filters, which in theory determine the suite of species that arrive at and establish in a community, have tremendous conceptual relevance to restoration. However, the concept has remained largely theoretical, with a paucity of empirical tests. As such, the applicability of assembly filters theory to ecological restoration remains incompletely known. We tested the relative strengths of dispersal and establishment filters by comparing the plant species composition, measured by species' presence/absence, in 29 restored prairies with the seed mixes used to restore each prairie. We found that both establishment and dispersal filters limited prairie similarity to the seed mix. Sown species responded differentially to filters, with a few species limited only by dispersal (seed density), many others limited only by establishment conditions (i.e. organic matter and sand content of soils, land use history, and fire frequency), and others limited by both dispersal and establishment filters. A few species, typically those sown most often, were not restricted by dispersal or establishment filters, likely because they were sown in high enough densities and all sites had suitable environmental conditions. Finally, one group of species established poorly, but we could not attribute this to either dispersal or establishment filters. This information can help land managers select species likely to establish in restorations when sown at sufficient densities. These results illustrate that dispersal and establishment filters limit the establishment of species in restored communities and these filters are species-dependent. Identifying the most limiting filter(s) for species will inform strategies to increase their establishment success.

Identifying and clearly communicating the drivers of ecosystem function is a crucially important goal for both basic and applied ecology. This has proven difficult because the putative causes (e.g., environment, species identity, biodiversity, and functional traits) are numerous and correlated. The problem is exacerbated by a lack of a formal framework for unambiguously relating theoretical language to precise, quantitative expressions of that language. Using a formal framework for the graphical expression of complex causal hypotheses, we developed a causal diagram of the concepts required to comprehensively test whether hypothesized sets of functional traits mediate the relationship between community structure and ecosystem function. We then used causal analysis, simulations, and field data to develop and test analytical strategies for understanding how community structure influences ecosystem functions via functional traits. Formal causal analysis showed that biodiversity-ecosystem function correlations are noncausal associations. Using simulations, we showed how biodiversity correlations and species identity effects can arise from misspecification or incomplete mediation by functional trait composites. We also found that different types of model misspecification result in different patterns of residuals, which may be used to diagnose gaps in functional trait hypotheses. Treating the model misspecifications eliminated associations between species identity or biodiversity and ecosystem function. Finally, we provide an example of the analysis of field data to demonstrate how to use these insights to conduct a research program that has the goal of understanding the mechanistic trait relationships that link community structure to ecosystem function.

The loss of biodiversity at local and larger scales has potentially dramatic effects on ecosystem functioning. Many studies have shown that ecosystem functioning depends on biodiversity, but the role of beta diversity, spatial variation in community composition, is less clear than that of local-scale (alpha) diversity. To test the hypothesis that beta diversity would increase ecosystem multifunctionality through variation in species functional traits, we gathered data on plant community composition, plant functional traits, and seven ecosystem functions across 29 restored prairies. We found that averaged multifunctionality (mean of seven ecosystem functions) increased with both taxonomic beta diversity and functional beta diversity. The abundance of the dominant species, big bluestem, played a more minor role, suggesting a limited role for the selection effect. Neither taxonomic nor functional alpha richness was associated with multifunctionality, though this finding may be sensitive to the identity of the functions included because alpha diversity was associated with some individual functions in opposing directions. These findings suggest that in systems structured largely by natural processes, beta diversity (a patchwork of functionally different plant communities) and dominant species abundance may be more important than alpha diversity in fostering ecosystem multifunctionality. These findings suggest the need for an increased focus on community heterogeneity to reestablish functional ecosystems during restoration.

Establishment and persistence are central to community assembly and are determined by how traits interact with the environment to determine performance (trait–environment interactions). Community assembly studies have rarely considered such trait–environment interactions, however, which can lead to incorrect inferences about how traits affect assembly. We evaluated how functional traits, environmental conditions, and trait–environment interactions structure plant establishment, as a measure of performance. Within 12 prairie restorations created by sowing 70 species, we quantified environmental conditions and counted individuals of each seeded species to quantify first‐year establishment. Three trait–environment interactions structured establishment. Leaf nitrogen interacted with herbivore pressure, as low leaf nitrogen species established relatively better under higher herbivory than species with high leaf nitrogen. Soil moisture interacted with root mass fraction (RMF), with low‐RMF species establishing better with low soil moisture and higher‐RMF species better on wetter soils. Specific leaf area (SLA) interacted with light availability, as low‐SLA species established better under high light conditions and high‐SLA species under low light conditions. Our work illustrates how community assembly can be better described by trait–environment interactions than correlating traits or environment with performance. This knowledge can assist species selection to maximize restoration success.