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.

SummaryLeaf dark respiration (R dark ) is an important yet poorly quantified component of the global carbon cycle. Given this, we analyzed a new global database of R dark and associated leaf traits. Data for 899 species were compiled from 100 sites (from the Arctic to the tropics). Several woody and nonwoody plant functional types (PFTs) were represented. Mixed-effects models were used to disentangle sources of variation in R dark .Area-based R dark at the prevailing average daily growth temperature (T) of each site increased only twofold from the Arctic to the tropics, despite a 20°C increase in growing T (8-28°C). By contrast, R dark at a standard T (25°C, R dark 25 ) was threefold higher in the Arctic than in the tropics, and twofold higher at arid than at mesic sites. Species and PFTs at cold sites exhibited higher R dark 25 at a given photosynthetic capacity (V cmax 25 ) or leaf nitrogen concentration ([N]) than species at warmer sites. R dark 25 values at any given V cmax 25 or [N] were higher in herbs than in woody plants.The results highlight variation in R dark among species and across global gradients in T and aridity. In addition to their ecological significance, the results provide a framework for improving representation of R dark in terrestrial biosphere models (TBMs) and associated land-surface components of Earth system models (ESMs).

Summary The temperature response of photosynthesis is one of the key factors determining predicted responses to warming in global vegetation models (GVMs). The response may vary geographically, owing to genetic adaptation to climate, and temporally, as a result of acclimation to changes in ambient temperature. Our goal was to develop a robust quantitative global model representing acclimation and adaptation of photosynthetic temperature responses. We quantified and modelled key mechanisms responsible for photosynthetic temperature acclimation and adaptation using a global dataset of photosynthetic CO2 response curves, including data from 141 C3 species from tropical rainforest to Arctic tundra. We separated temperature acclimation and adaptation processes by considering seasonal and common‐garden datasets, respectively. The observed global variation in the temperature optimum of photosynthesis was primarily explained by biochemical limitations to photosynthesis, rather than stomatal conductance or respiration. We found acclimation to growth temperature to be a stronger driver of this variation than adaptation to temperature at climate of origin. We developed a summary model to represent photosynthetic temperature responses and showed that it predicted the observed global variation in optimal temperatures with high accuracy. This novel algorithm should enable improved prediction of the function of global ecosystems in a warming climate.

of origin and growth form, but respiration was not completely homeostatic across temperatures in the majority of cases. Leaves that developed at a new temperature had a greater capacity for acclimation than those transferred to a new temperature. We conclude that leaf respiration of most terrestrial plants can acclimate to gradual warming, potentially reducing the magnitude of the positive feedback between climate and the carbon cycle in a warming world. More empirical data are, however, needed to improve our understanding of interspecific variation in thermal acclimation capacity, and to better predict patterns in respiratory carbon fluxes both within and across biomes in the face of ongoing global warming. Keywords Climate change · Global patterns · Metaanalysis · Plant ecophysiology · Warming IntroductionClimate warming is predicted to increase the release of carbon dioxide (CO 2 ) from the terrestrial biosphere into the atmosphere, thus triggering a positive climate-terrestrial carbon feedback that accelerates warming (Cox et al. 2000;Luo 2007). However, plant respiration (non-photorespiratory mitochondrial CO 2 release) may be downregulated in response to warming of temperature regimes over days to months, and such acclimation may reduce the potential decline in net primary productivity (NPP) (King et al. 2006;Smith and Dukes 2013;Slot et al. 2014a). High and mid-latitude ecosystems experience more rapid, and greater degrees of warming than the tropics (Stocker et al. 2013), and temperature effects on plant and ecosystem functions have been studied more extensively in temperate and boreal ecosystems than in the tropics. Although tropical regions Abstract Respiration is instrumental for survival and growth of plants, but increasing costs of maintenance processes with warming have the potential to change the balance between photosynthetic carbon uptake and respiratory carbon release from leaves. Climate warming may cause substantial increases of leaf respiratory carbon fluxes, which would further impact the carbon balance of terrestrial vegetation. However, downregulation of respiratory physiology via thermal acclimation may mitigate this impact. We have conducted a meta-analysis with data collected from 43 independent studies to assess quantitatively the thermal acclimation capacity of leaf dark respiration to warming of terrestrial plant species from across the globe. In total, 282 temperature contrasts were included in the meta-analysis, representing 103 species of forbs, graminoids, shrubs, trees and lianas native to arctic, boreal, temperate and tropical ecosystems. Acclimation to warming was found to decrease respiration at a set temperature in the majority of the observations, regardless of the biome Communicated by Rowan Sage. Electronic supplementary materialThe online version of this article