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.

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One Sentence Summary: Empirical evidence from grasslands around the world demonstrates a humped-back relationship between plant species richness and biomass at the 1 m 2 plot scale.Abstract: One of the central problems of ecology is the prediction of species diversity. The humped-back model (HBM) suggests that plant diversity is highest at intermediate levels of productivity; at low productivity few species can tolerate the environmental stresses and at high productivity a small number of highly competitive species dominate. A recent study claims to have comprehensively refuted the HBM. Here we show, using the largest, most geographically diverse dataset ever compiled and specifically built for testing this model that if the conditions are met, namely a wide range in biomass at the 1 m 2 plot level and the inclusion of plant litter, the relationship between plant biomass and species richness is hump shaped, supporting the HBM. Our findings shed new light on the prediction of plant diversity in grasslands, which is crucial for supporting management practices for effective conservation of biodiversity. 4Main Text: The relationship between plant diversity and productivity is a topic of intense debate (1-6). The HBM states that plant species richness peaks at intermediate productivity, taking above-ground biomass as a proxy for annual net primary productivity (ANPP) (7-9). This diversity peak is driven by two opposing processes; in unproductive and disturbed ecosystems where there is low plant biomass, species richness is limited by either stress, such as insufficient water and mineral nutrients, or high levels of disturbance-induced removal of biomass, which few species are able to tolerate. In contrast, in the low disturbance and productive conditions that generate high plant biomass it is competitive exclusion by a small number of highly competitive species that is hypothesized to constrain species richness (7-9). Other mechanisms proposed to explain the unimodal relationship between species richness and productivity include disturbance (10), evolutionary history and dispersal limitation (11,12), and density limitation affected by plant size (13).Different case studies have supported or rejected the HBM, and three separate meta-analyses reached different conclusions (14). This inconsistency may indicate a lack of generality of the HBM, or it may reflect a sensitivity to study characteristics including the type(s) of plant communities considered, the taxonomic scope, the length of the gradient sampled, the spatial grain and extent of analyses (14,15), and the particular measure of net primary productivity (16). Although others would argue (6), we maintain that the question remains whether the HBM serves as a useful and general model for grassland ecosystem theory and management. 5 We quantified the form and strength of the richness-productivity relationship using novel data from a globally-coordinated (17), distributed, scale-standardized and consistently designed survey, in which plant richness and biomass were m...

Despite long-time awareness of the importance of the location of buds in plant biology, research on belowground bud banks has been scant. Terms such as lignotuber, xylopodium and sobole, all referring to belowground bud-bearing structures, are used inconsistently in the literature. Because soil efficiently insulates meristems from the heat of fire, concealing buds below ground provides fitness benefits in fire-prone ecosystems. Thus, in these ecosystems, there is a remarkable diversity of bud-bearing structures. There are at least six locations where belowground buds are stored: roots, root crown, rhizomes, woody burls, fleshy swellings and belowground caudexes. These support many morphologically distinct organs. Given their history and function, these organs may be divided into three groups: those that originated in the early history of plants and that currently are widespread (bud-bearing roots and root crowns); those that also originated early and have spread mainly among ferns and monocots (nonwoody rhizomes and a wide range of fleshy underground swellings); and those that originated later in history and are strictly tied to fire-prone ecosystems (woody rhizomes, lignotubers and xylopodia). Recognizing the diversity of belowground bud banks is the starting point for understanding the many evolutionary pathways available for responding to severe recurrent disturbances.

MotivationThe BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community‐led open‐source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene.Main types of variables includedThe database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record.Spatial location and grainBioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km2 (158 cm2) to 100 km2 (1,000,000,000,000 cm2).Time period and grainBioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year.Major taxa and level of measurementBioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.Software format.csv and .SQL.

Summary Trait‐based approaches have improved our understanding of plant evolution, community assembly and ecosystem functioning. A major challenge for the upcoming decades is to understand the functions and evolution of early life‐history traits, across levels of organization and ecological strategies. Although a variety of seed traits are critical for dispersal, persistence, germination timing and seedling establishment, only seed mass has been considered systematically. Here we suggest broadening the range of morphological, physiological and biochemical seed traits to add new understanding on plant niches, population dynamics and community assembly. The diversity of seed traits and functions provides an important challenge that will require international collaboration in three areas of research. First, we present a conceptual framework for a seed ecological spectrum that builds upon current understanding of plant niches. We then lay the foundation for a seed‐trait functional network, the establishment of which will underpin and facilitate trait‐based inferences. Finally, we anticipate novel insights and challenges associated with incorporating diverse seed traits into predictive evolutionary ecology, community ecology and applied ecology. If the community invests in standardized seed‐trait collection and the implementation of rigorous databases, major strides can be made at this exciting frontier of functional ecology.

Despite growing recognition of the conservation values of grassy biomes, our understanding of how to maintain and restore biodiverse tropical grasslands (including savannas and open‐canopy grassy woodlands) remains limited. To incorporate grasslands into large‐scale restoration efforts, we synthesised existing ecological knowledge of tropical grassland resilience and approaches to plant community restoration. Tropical grassland plant communities are resilient to, and often dependent on, the endogenous disturbances with which they evolved – frequent fires and native megafaunal herbivory. In stark contrast, tropical grasslands are extremely vulnerable to human‐caused exogenous disturbances, particularly those that alter soils and destroy belowground biomass (e.g. tillage agriculture, surface mining); tropical grassland restoration after severe soil disturbances is expensive and rarely achieves management targets. Where grasslands have been degraded by altered disturbance regimes (e.g. fire exclusion), exotic plant invasions, or afforestation, restoration efforts can recreate vegetation structure (i.e. historical tree density and herbaceous ground cover), but species‐diverse plant communities, including endemic species, are slow to recover. Complicating plant‐community restoration efforts, many tropical grassland species, particularly those that invest in underground storage organs, are difficult to propagate and re‐establish. To guide restoration decisions, we draw on the old‐growth grassland concept, the novel ecosystem concept, and theory regarding tree cover along resource gradients in savannas to propose a conceptual framework that classifies tropical grasslands into three broad ecosystem states. These states are: (1) old‐growth grasslands (i.e. ancient, biodiverse grassy ecosystems), where management should focus on the maintenance of disturbance regimes; (2) hybrid grasslands, where restoration should emphasise a return towards the old‐growth state; and (3) novel ecosystems, where the magnitude of environmental change (i.e. a shift to an alternative ecosystem state) or the socioecological context preclude a return to historical conditions.