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.

The terrestrial biosphere is a key component of the global carbon cycle and its carbon balance is strongly influenced by climate. Continuing environmental changes are thought to increase global terrestrial carbon uptake. But evidence is mounting that climate extremes such as droughts or storms can lead to a decrease in regional ecosystem carbon stocks and therefore have the potential to negate an expected increase in terrestrial carbon uptake. Here we explore the mechanisms and impacts of climate extremes on the terrestrial carbon cycle, and propose a pathway to improve our understanding of present and future impacts of climate extremes on the terrestrial carbon budget.

Based on measurements of δO and δC in organic matter of C-plants, we have developed a conceptual model that gives insight into the relationship between stomatal conductance (g ) and photosynthetic capacity (A) resulting from differing environmental constraints and plant-internal factors. This is a semi-quantitative approach to describing the long-term effects of environmental factors on CO and HO gas exchange, whereby we estimate the intercellular CO concentration (c ) from δC and the air humidity from δO. Assuming that air humidity is an important factor influencing g , the model allows us to distinguish whether differences in c are caused by a response of g or of A. As an application of the model we evaluated the isotope data from three species in plots differing in intensity of land use (hay meadows and abandoned areas) at three sites along a south north transect in the Eastern Alps. We found three different δO-δC response patterns in native and planted grassland species (cultivated in the greenhouse). After preliminary confirmation by gas-exchange measurements we conclude that the proposed model is a promising tool for deriving carbon water relations in different functional groups from δO and δC isotope data.

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.

Extreme droughts, heat waves, frosts, precipitation, wind storms and other climate extremes may impact the structure, composition and functioning of terrestrial ecosystems, and thus carbon cycling and its feedbacks to the climate system. Yet, the interconnected avenues through which climate extremes drive ecological and physiological processes and alter the carbon balance are poorly understood. Here, we review the literature on carbon cycle relevant responses of ecosystems to extreme climatic events. Given that impacts of climate extremes are considered disturbances, we assume the respective general disturbance-induced mechanisms and processes to also operate in an extreme context. The paucity of well-defined studies currently renders a quantitative meta-analysis impossible, but permits us to develop a deductive framework for identifying the main mechanisms (and coupling thereof) through which climate extremes may act on the carbon cycle. We find that ecosystem responses can exceed the duration of the climate impacts via lagged effects on the carbon cycle. The expected regional impacts of future climate extremes will depend on changes in the probability and severity of their occurrence, on the compound effects and timing of different climate extremes, and on the vulnerability of each land-cover type modulated by management. Although processes and sensitivities differ among biomes, based on expert opinion, we expect forests to exhibit the largest net effect of extremes due to their large carbon pools and fluxes, potentially large indirect and lagged impacts, and long recovery time to regain previous stocks. At the global scale, we presume that droughts have the strongest and most widespread effects on terrestrial carbon cycling. Comparing impacts of climate extremes identified via remote sensing vs. ground-based observational case studies reveals that many regions in the (sub-)tropics are understudied. Hence, regional investigations are needed to allow a global upscaling of the impacts of climate extremes on global carbon-climate feedbacks.

Plant functional trait change across a warming tundra biomeThe tundra is warming more rapidly than any other biome on Earth, and the potential ramifications are far-reaching because of global feedback effects between vegetation and climate. A better understanding of how environmental factors shape plant structure and function is crucial for predicting the consequences of environmental change for ecosystem functioning. Here we explore the biome-wide relationships between temperature, moisture and seven key plant functional traits both across space and over three decades of warming at 117 tundra locations. Spatial temperature-trait relationships were generally strong but soil moisture had a marked influence on the strength and direction of these relationships, highlighting the potentially important influence of changes in water availability on future trait shifts in tundra plant communities. Community height increased with warming across all sites over the past three decades, but other traits lagged far behind predicted rates of change. Our findings highlight the challenge of using space-for-time substitution to predict the functional consequences of future warming and suggest that functions that are tied closely to plant height will experience the most rapid change. They also reveal the strength with which environmental factors shape biotic communities at the coldest extremes of the planet and will help to improve projections of functional changes in tundra ecosystems with climate warming. Environment-trait relationships across the tundra biomeWe found strong spatial associations between temperature and community height, SLA and LDMC (Fig. 2a, Extended Data Fig. 2 and Supplementary Table 3) across the 117 survey sites. Both height and SLA increased with summer temperature, but the temperaturetrait relationship for SLA was much stronger at wetter than at drier sites. LDMC was negatively related to temperature, and

A substantial body of evidence has demonstrated that biodiversity stabilizes ecosystem functioning over time in grassland ecosystems. However, the relative importance of different facets of biodiversity underlying the diversity-stability relationship remains unclear. Here we use data from 39 grassland biodiversity experiments and structural equation modelling to investigate the roles of species richness, phylogenetic diversity and both the diversity and community-weighted mean of functional traits representing the 'fast-slow' leaf economics spectrum in driving the diversity-stability relationship. We found that high species richness and phylogenetic diversity stabilize biomass production via enhanced asynchrony in the performance of co-occurring species. Contrary to expectations, low phylogenetic diversity enhances ecosystem stability directly, albeit weakly. While the diversity of fast-slow functional traits has a weak effect on ecosystem stability, communities dominated by slow species enhance ecosystem stability by increasing mean biomass production relative to the standard deviation of biomass over time. Our in-depth, integrative assessment of factors influencing the diversity-stability relationship demonstrates a more multicausal relationship than has been previously acknowledged.

Question: Are plant traits more closely correlated with mean annual temperature, orwithmean annual precipitation? Location: Global. Methods: We quantified the strength of the relationships between temperature and precipitation and 21 plant traits from 447,961 species-site combinations worldwide. We used meta-analysis to provide an overall answer to our question. Results: Mean annual temperature was significantly more strongly correlated with plant traits than was mean annual precipitation. Conclusions: Our study provides support for some of the assumptions of classical vegetation theory, and points to many interesting directions for future research. The relatively low R2 values for precipitation might reflect the weak link betweenmean annual precipitation and the availability of water to plants