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. Biotic interactions do not occur in isolation but are imbedded in a network of species interactions. Network analysis facilitates the compilation and understanding of the complexity found in natural ecosystems and is a powerful tool to reveal information on the degree of specialization of the interacting partners and their niches. The indices measuring these properties are based on qualitative or quantitative observations of interactions between partners from different trophic levels, which informs about the structure of network patterns, but not about the underlying mechanisms. Functional traits may control the interaction strength between partners and also the (micro-) structure of networks. Here, we ask whether flower visitors specialize on certain plant traits and how this trait specialization contributes to niche partitioning and interaction partner diversity. 2. We introduce two novel statistical approaches suited to evaluate the dimension of the realized niche and to analyse which traits determine niches. As basis for our analysis, we measured 10 quantitative flower traits and evaluated whether 31 arthropod taxa i visited flowers displaying only subsets of the available trait characteristics, indicating a specialization on these traits by narrow trait-widths 〈S i 〉. The product of 10 trait-and species-specific trait-widths 〈S i 〉 was defined as trait-volume V i (expansion of a n-dimensional hypervolume) occupied by each taxon i. These indices are applicable beyond flower-visitor interactions to quantify realized niches based on various biotic and abiotic factors. 3. Each flower visitor species showed some degree of specialization to a unique set of flower traits (realized niche). Overall, our data suggested a hierarchical sequence of flower traits influencing the flower visitors' behaviour and thus network structure: flowering phenology was found to have the strongest effect, followed by flower height, nectar-tube depth and floral reflectance. Less important were pollen-mass/flower, sugar/flower, anther position, phylogeny, display size and abundance. 4. The species-specific specialization on traits suggests that plant communities with more diverse floral niches may sustain a larger number of flower visitors with non-redundant fundamental niches. Our study and statistical approach provide a basis for a better understanding of how plant traits shape interactions between flowers and their visitors and thus network structure.

Co-flowering plant species commonly share flower visitors, and thus have the potential to influence each other's pollination. In this study we analysed 750 quantitative plant-pollinator networks from 28 studies representing diverse biomes worldwide. We show that the potential for one plant species to influence another indirectly via shared pollinators was greater for plants whose resources were more abundant (higher floral unit number and nectar sugar content) and more accessible. The potential indirect influence was also stronger between phylogenetically closer plant species and was independent of plant geographic origin (native vs. non-native). The positive effect of nectar sugar content and phylogenetic proximity was much more accentuated for bees than for other groups. Consequently, the impact of these factors depends on the pollination mode of plants, e.g. bee or fly pollinated. Our findings may help predict which plant species have the greatest importance in the functioning of plant-pollination networks.

Floral chemistry mediates plant interactions with pollinators, pathogens, and herbivores, with major consequences for fitness of both plants and flower visitors. The outcome of such interactions often depends on compound dose and chemical context. However, chemical diversity and intraspecific variation of nectar and pollen secondary chemistry are known for very few species, precluding general statements about their composition. We analyzed methanol extracts of flowers, nectar, and pollen from 31 cultivated and wild plant species, including multiple sites and cultivars, by liquid‐chromatography–mass‐spectrometry. To depict the chemical niche of each tissue type, we analyzed differences in nectar and pollen chemical richness, absolute and proportional concentrations, and intraspecific variability. We hypothesized that pollen would have higher concentrations and more compounds than nectar, consistent with Optimal Defense Theory and pollen's importance as a male gamete. To investigate chemical correlations across and within tissues, which could reflect physiological constraints, we quantified chemical overlap between conspecific nectar and pollen, and phenotypic integration of individual compounds within tissue types. Nectar and pollen were chemically differentiated both across and within species. Of 102 compounds identified, most occurred in only one species. Machine‐learning algorithms assigned samples to the correct species and tissue type with 98.6% accuracy. Consistent with our hypothesis, pollen had 23.8‐ to 235‐fold higher secondary chemical concentrations and 63% higher chemical richness than nectar. The most common secondary compound classes were flavonoids, alkaloids, terpenoids, and phenolics (primarily phenylpropanoids including chlorogenic acid). The most common specific compound types were quercetin and kaempferol glycosides, known to mediate biotic and abiotic effects. Pollens were distinguished from nectar by high concentrations of hydroxycinnamoyl‐spermidine conjugates, which affect plant development, abiotic stress tolerance, and herbivore resistance. Although chemistry was qualitatively consistent within species and tissue types, concentrations varied across cultivars and sites, which could influence pollination, herbivory, and disease in wild and agricultural plants. Analyses of multivariate trait space showed greater overlap across sites and cultivars in nectar than pollen chemistry; this overlap reflected greater within‐site and within‐cultivar variability of nectar. Our analyses suggest different ecological roles of nectar and pollen mediated by chemical concentration, composition, and variability.