Phenotypic traits and their associated trade-offs have been shown to have globally consistent effects on individual plant physiological functions 1-3 , but how these effects scale up to influence competition, a key driver of community assembly in terrestrial vegetation, has remained unclear 4 . Here we use growth data from more than 3 million trees in over 140,000 plots across the world to show how three key functional traits-wood density, specific leaf area and maximum height-consistently influence competitive interactions. Fast maximum growth of a species was correlated negatively with its wood density in all biomes, and positively with its specific leaf area in most biomes. Low wood density was also correlated with a low ability to tolerate competition and a low competitive effect on neighbours, while high specific leaf area was correlated with a low competitive effect. Thus, traits generate trade-offs between performance with competition versus performance without competition, a fundamental ingredient in the classical hypothesis that the coexistence of plant species is enabled via differentiation in their successional strategies 5 . Competition within species was stronger than between species, but an increase in trait dissimilarity between species had little influence in weakening competition. No benefit of dissimilarity was detected for specific leaf area or wood density, and only a weak benefit for maximum height. Our traitbased approach to modelling competition makes generalization possible across the forest ecosystems of the world and their highly diverse species composition.Phenotypic traits are considered fundamental drivers of community assembly and thus species diversity 1,6 . The effects of traits on individual plant physiologies and functions are increasingly understood, and have been shown to be underpinned by well-known and globally consistent trade-offs 1-3 . For instance, traits such as wood density and specific leaf area capture trade-offs between the construction cost and longevity or strength of wood and leaf tissues 2,3 . By contrast, we still have a limited understanding of how such trait-based trade-offs translate into competitive interactions between species, particularly for long-lived organisms such as trees. Competition is a key filter through which ecological and evolutionary success is determined 4 . A long-standing hypothesis is that the intensity of competition decreases as two species diverge in trait values 7 (trait dissimilarity). The few studies [8][9][10][11][12][13] that have explored links between traits and competition have shown that linkages were more complex than this, as particular trait values may also confer competitive advantage independently from trait dissimilarity 9,13,14 . This distinction is fundamental for species coexistence and the local mixture of traits. If neighbourhood competition is driven mainly by trait dissimilarity, this will favour a wide spread of trait values at a local scale. By contrast, if neighbourhood interactions are mainly driven by the c...

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).

Remote sensing is revolutionizing the way we study forests, and recent technological advances mean we are now able -for the first time -to identify and measure the crown dimensions of individual trees from airborne imagery. Yet to make full use of these data for quantifying forest carbon stocks and dynamics, a new generation of allometric tools which have tree height and crown size at their centre are needed. Here, we compile a global database of 108753 trees for which stem diameter, height and crown diameter have all been measured, including 2395 trees harvested to measure aboveground biomass. Using this database, we develop general allometric models for estimating both the diameter and aboveground biomass of trees from attributes which can be remotely sensed -specifically height and crown diameter. We show that tree height and crown diameter jointly quantify the aboveground biomass of individual trees and find that a single equation predicts stem diameter from these two variables across the world's forests. These new Correspondence: Tommaso Jucker, tel. +44 1223 333911, fax: +44 1223 333953,

Summary1. Anthropogenic global change compromises forest resilience, with profound impacts to ecosystem functions and services. This synthesis paper reflects on the current understanding of forest resilience and potential tipping points under environmental change and explores challenges to assessing responses using experiments, observations and models. 2. Forests are changing over a wide range of spatio-temporal scales, but it is often unclear whether these changes reduce resilience or represent a tipping point. Tipping points may arise from interactions across scales, as processes such as climate change, land-use change, invasive species or deforestation gradually erode resilience and increase vulnerability to extreme events. Studies covering interactions across different spatio-temporal scales are needed to further our understanding. 3. Combinations of experiments, observations and process-based models could improve our ability to project forest resilience and tipping points under global change. We discuss uncertainties in changing CO 2 concentration and quantifying tree mortality as examples. 4. Synthesis. As forests change at various scales, it is increasingly important to understand whether and how such changes lead to reduced resilience and potential tipping points. Understanding the mechanisms underlying forest resilience and tipping points would help in assessing risks to ecosystems and presents opportunities for ecosystem restoration and sustainable forest management.

Established forests currently function as a major carbon sink, sequestering as woody biomass about 26% of global fossil fuel emissions. Whether forests continue to act as a global sink will depend on many factors, including the response of aboveground wood production (AWP; MgC ha(-1 ) yr(-1) ) to climate change. Here, we explore how AWP in New Zealand's natural forests is likely to change. We start by statistically modelling the present-day growth of 97 199 individual trees within 1070 permanently marked inventory plots as a function of tree size, competitive neighbourhood and climate. We then use these growth models to identify the factors that most influence present-day AWP and to predict responses to medium-term climate change under different assumptions. We find that if the composition and structure of New Zealand's forests were to remain unchanged over the next 30 years, then AWP would increase by 6-23%, primarily as a result of physiological responses to warmer temperatures (with no appreciable effect of changing rainfall). However, if warmth-requiring trees were able to migrate into currently cooler areas and if denser canopies were able to form, then a different AWP response is likely: forests growing in the cool mountain environments would show a 30% increase in AWP, while those in the lowland would hardly respond (on average, -3% when mean annual temperature exceeds 8.0 °C). We conclude that response of wood production to anthropogenic climate change is not only dependent on the physiological responses of individual trees, but is highly contingent on whether forests adjust in composition and structure.

a b s t r a c tForest inventory plots are widely used to estimate biomass carbon storage and its change over time. While there has been much debate and exploration of the analytical methods for calculating biomass, the methods used to determine rates of wood production have not been evaluated to the same degree. This affects assessment of ecosystem fluxes and may have wider implications if inventory data are used to parameterise biospheric models, or scaled to large areas in assessments of carbon sequestration. Here we use a dataset of 35 long-term Amazonian forest inventory plots to test different methods of calculating wood production rates. These address potential biases associated with three issues that routinely impact the interpretation of tree measurement data: (1) changes in the point of measurement (POM) of stem diameter as trees grow over time; (2) unequal length of time between censuses; and (3) the treatment of trees that pass the minimum diameter threshold (''recruits''). We derive corrections that control for changing POM height, that account for the unobserved growth of trees that die within census intervals, and that explore different assumptions regarding the growth of recruits during the previous census interval. For our dataset we find that annual aboveground coarse wood production (AGWP; in Mg ha À1 year À1 of dry matter) is underestimated on average by 9.2% if corrections are not made to control for changes in POM height. Failure to control for the length of sampling intervals results in a mean underestimation of 2.7% in annual AGWP in our plots for a mean interval length of 3.6 years. Different methods for treating recruits result in mean differences of up to 8.1% in AGWP. In general, the greater the length of time a plot is sampled for and the greater the time elapsed between censuses, the greater the tendency to underestimate wood production. We recommend that POM changes, census interval length, and the http://dx

AimThe geographic distributions of different forest types are expected to shift in the future under altered climatic conditions. At present, the nature, magnitude and timing of these shifts are uncertain because we lack a quantitative understanding of how forest distributions emerge from climate-and competition-related variation in underlying demographic processes. Forest dynamics result primarily from the manner in which the physical environment and competition for limiting resources affect tree growth, mortality and recruitment. We sought to uncover the relative importance of these processes in controlling the geographic limits of different forest types. Location Eastern USA.Methods We parameterized a climate-dependent forest dynamics model with extensive observations of tree growth, mortality and recruitment from forest inventory data. We then implemented the resulting demographic models in simulations of joint population dynamics for seven plant functional types (PFTs) across the region. By removing various climate effects in a series of simulation experiments, we assessed the importance of climate-dependent demography and competition in limiting forest distributions.Results Distributions that emerged from simulated population dynamics approximated the current distributions for all seven PFTs well and captured several known patterns of succession. Temperature-related increases in mortality determined the southern boundaries of three out of four boreal and northern temperate PFTs, whereas temperature-related decreases in recruitment controlled the northern limit of all three southern temperate PFTs. Changes in growth rates and competitor performance had only minor effects on the distribution limits of most PFTs. Main conclusionsOur results imply that dynamic global vegetation models, which are widely used to predict future vegetation distributions under climate change, should seek to more appropriately capture the observed climate sensitivity of mortality and recruitment. Understanding the mechanisms controlling forest distributions will enable better predictions of their future responses to climate change.