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.

Background and Aims It is frequently assumed that phenotypic plasticity can be very advantageous for plants, because it may increase environmental tolerance (fitness homeostasis). This should, however, only hold for plastic responses that are adaptive, i.e. increase fitness. Numerous studies have shown shade-induced increases in specific leaf area (SLA), and there is wide consensus that this plastic response optimizes light capture and thus has to be adaptive. However, it has rarely been tested whether this is really the case.Methods In order to identify whether SLA plasticity does contribute to the maintenance of high biomass of plant species under shaded conditions, a meta-analytical approach was employed. The data set included 280 species and 467 individual studies from 32 publications and two unpublished experiments.Key Results Plants increased their SLA by 55Á4 % on average when shaded, while they decreased their biomass by 59Á9 %. Species with a high SLA under high-light control conditions showed a significantly greater ability to maintain biomass production under shade overall. However, in contrast to the expectation of a positive relationship between SLA plasticity and maintenance of plant biomass, the results indicated that species with greater SLA plasticity were less able to maintain biomass under shade.Conclusions Although a high SLA per se contributes to biomass homeostasis, there was no evidence that plasticity in SLA contributes to this. Therefore, it is argued that some of the plastic changes that are frequently thought to be adaptive might simply reflect passive responses to the environment, or result as by-products of adaptive plastic responses in other traits.

Aim A major challenge in ecology is to understand how multiple causal factors, which may interact, drive success of non native plants in new ranges. In this study we addressed the role of introduction history, climatic suitability, native range size, species traits and their interactions in the establishment of Chinese woody species in Europe.Location China (native range), Europe (new range).Methods We tested whether establishment of 449 Chinese woody species in Europe was associated with residence time (time since earliest planting), planting frequency, climatic suitability, native range size and species traits. We also considered possible nonlinear effects and interactions among these variables. For the 38 species that have established in Europe, we further tested whether these variables and interactions explained their establishment in multiple European countries.Results Establishment of the 449 species in Europe was positively associated with residence time, planting frequency and climatic suitability. Except residence time, these factors were also positively associated with establishment of the 38 species in multiple countries. None of the traits tested had statistically significant main effects on establishment in Europe, but, for the established species, longer flowering period and having compound leaves were positively associated with establishment in multiple countries. The positive association between establishment in Europe and residence time was stronger for evergreen than for deciduous species. In addition, evergreens, unlike deciduous species, showed a positive association between establishment in Europe and fruiting duration. Moreover, establishment in multiple countries was positively associated with planting frequency for species with compound leaves but not for species with simple leaves, and the association between the establishment and fruiting duration changed from negative to moderately positive as climatic suitability increased.

Chilling (0–18°C) and freezing (<0°C) are two distinct types of cold stresses. Epigenetic regulation can play an important role in plant adaptation to abiotic stresses. However, it is not yet clear whether and how epigenetic modification (i.e., DNA methylation) mediates the adaptation to cold stresses in nature (e.g., in alpine regions). Especially, whether the adaptation to chilling and freezing is involved in differential epigenetic regulations in plants is largely unknown. Chorispora bungeana is an alpine subnival plant that is distributed in the freeze-thaw tundra in Asia, where chilling and freezing frequently fluctuate daily (24 h). To disentangle how C. bungeana copes with these intricate cold stresses through epigenetic modifications, plants of C. bungeana were treated at 4°C (chilling) and -4°C (freezing) over five periods of time (0–24 h). Methylation-sensitive amplified fragment-length polymorphism markers were used to investigate the variation in DNA methylation of C. bungeana in response to chilling and freezing. It was found that the alterations in DNA methylation of C. bungeana largely occurred over the period of chilling and freezing. Moreover, chilling and freezing appeared to gradually induce distinct DNA methylation variations, as the treatment went on (e.g., after 12 h). Forty-three cold-induced polymorphic fragments were randomly selected and further analyzed, and three of the cloned fragments were homologous to genes encoding alcohol dehydrogenase, UDP-glucosyltransferase and polygalacturonase-inhibiting protein. These candidate genes verified the existence of different expressive patterns between chilling and freezing. Our results showed that C. bungeana responded to cold stresses rapidly through the alterations of DNA methylation, and that chilling and freezing induced different DNA methylation changes. Therefore, we conclude that epigenetic modifications can potentially serve as a rapid and flexible mechanism for C. bungeana to adapt to the intricate cold stresses in the alpine areas.

Models of natural processes necessarily sacrifice some realism for the sake of tractability. Detailed, parameter‐rich models often provide accurate estimates of system behaviour but can be data‐hungry and difficult to operationalize. Moreover, complexity increases the danger of ‘over‐fitting’, which leads to poor performance when models are applied to novel conditions. This challenge is typically described in terms of a trade‐off between bias and variance (i.e. low accuracy vs. low precision). In studies of ecological communities, this trade‐off often leads to an argument about the level of detail needed to describe interactions among species. Here, we used data from a grassland biodiversity experiment containing nine locally abundant plant species (the Jena ‘dominance experiment’) to parameterize models representing six increasingly complex hypotheses about interactions. For each model, we calculated goodness‐of‐fit across different subsets of the data based on sown species richness levels, and tested how performance changed depending on whether or not the same data were used to parameterize and test the model (i.e. within vs. out‐of‐sample), and whether the range of diversity treatments being predicted fell inside or outside of the range used for parameterization. As expected, goodness‐of‐fit improved as a function of model complexity for all within‐sample tests. In contrast, the best out‐of‐sample performance generally resulted from models of intermediate complexity (i.e. with only two interaction coefficients per species—an intraspecific effect and a single pooled interspecific effect), especially for predictions that fell outside the range of diversity treatments used for parameterization. In accordance with other studies, our results also demonstrate that commonly used selection methods based on AIC of models fitted to the full dataset correspond more closely to within‐sample than out‐of‐sample performance. Synthesis. Our results demonstrate that models which include only general intra and interspecific interaction coefficients can be sufficient for estimating species‐level abundances across a wide range of contexts and may provide better out‐of‐sample performance than do more complex models. These findings serve as a reminder that simpler models may often provide a better trade‐off between bias and variance in ecological systems, particularly when applying models beyond the conditions used to parameterize them.