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.

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.

Heatwaves are likely to increase in frequency and intensity with climate change, which may impair tree function and forest C uptake. However, we have little information regarding the impact of extreme heatwaves on the physiological performance of large trees in the field. Here, we grew Eucalyptus parramattensis trees for 1 year with experimental warming (+3°C) in a field setting, until they were greater than 6 m tall. We withheld irrigation for 1 month to dry the surface soils and then implemented an extreme heatwave treatment of 4 consecutive days with air temperatures exceeding 43°C, while monitoring whole-canopy exchange of CO and H O, leaf temperatures, leaf thermal tolerance, and leaf and branch hydraulic status. The heatwave reduced midday canopy photosynthesis to near zero but transpiration persisted, maintaining canopy cooling. A standard photosynthetic model was unable to capture the observed decoupling between photosynthesis and transpiration at high temperatures, suggesting that climate models may underestimate a moderating feedback of vegetation on heatwave intensity. The heatwave also triggered a rapid increase in leaf thermal tolerance, such that leaf temperatures observed during the heatwave were maintained within the thermal limits of leaf function. All responses were equivalent for trees with a prior history of ambient and warmed (+3°C) temperatures, indicating that climate warming conferred no added tolerance of heatwaves expected in the future. This coordinated physiological response utilizing latent cooling and adjustment of thermal thresholds has implications for tree tolerance of future climate extremes as well as model predictions of future heatwave intensity at landscape and global scales.

CABI:20153174020Understanding how plants are constructed - i.e., how key size dimensions and the amount of mass invested in different tissues varies among individuals - is essential for modeling plant growth, carbon stocks, and energy fluxes in the terrestrial biosphere. Allocation patterns can differ through ontogeny, but also among coexisting species and among species adapted to different environments. While a variety of models dealing with biomass allocation exist, we lack a synthetic understanding of the underlying processes. This is partly due to the lack of suitable data sets for validating and parameterizing models. To that end, we present the Biomass And Allometry Database (BAAD) for woody plants. The BAAD contains 259634 measurements collected in 176 different studies, from 21084 individuals across 678 species. Most of these data come from existing publications. However, raw data were rarely made public at the time of publication. Thus, the BAAD contains data from different studies, transformed into standard units and variable names. The transformations were achieved using a common workflow for all raw data files. Other features that distinguish the BAAD are: (i) measurements were for individual plants rather than stand averages; (ii) individuals spanning a range of sizes were measured; (iii) plants from 0.01-100 m in height were included; and (iv) biomass was estimated directly, i.e., not indirectly via allometric equations (except in very large trees where biomass was estimated from detailed sub-sampling). We included both wild and artificially grown plants. The data set contains the following size metrics: total leaf area; area of stem cross-section including sapwood, heartwood, and bark; height of plant and crown base, crown area, and surface area; and the dry mass of leaf, stem, branches, sapwood, heartwood, bark, coarse roots, and fine root tissues. We also report other properties of individuals (age, leaf size, leaf mass per area, wood density, nitrogen content of leaves and wood), as well as information about the growing environment (location, light, experimental treatment, vegetation type) where available. It is our hope that making these data available will improve our ability to understand plant growth, ecosystem dynamics, and carbon cycling in the world's vegetation

Understanding physiological acclimation of photosynthesis and respiration is important in elucidating the metabolic performance of trees in a changing climate. Does physiological acclimation to climate warming mirror acclimation to seasonal temperature changes? We grew Eucalyptus tereticornis trees in the field for 14 months inside 9-m tall whole-tree chambers tracking ambient air temperature (Tair ) or ambient Tair  + 3°C (i.e. 'warmed'). We measured light- and CO2 -saturated net photosynthesis (Amax ) and night-time dark respiration (R) each month at 25°C to quantify acclimation. Tree growth was measured, and leaf nitrogen (N) and total nonstructural carbohydrate (TNC) concentrations were determined to investigate mechanisms of acclimation. Warming reduced Amax and R measured at 25°C compared to ambient-grown trees. Both traits also declined as mean daily Tair increased, and did so in a similar way across temperature treatments. Amax and R (at 25°C) both increased as TNC concentrations increased seasonally; these relationships appeared to arise from source-sink imbalances, suggesting potential substrate regulation of thermal acclimation. We found that photosynthesis and respiration each acclimated equivalently to experimental warming and seasonal temperature change of a similar magnitude, reflecting a common, nearly homeostatic constraint on leaf carbon exchange that will be important in governing tree responses to climate warming.