Knowledge of carbon exchange between the atmosphere, land and the oceans is important, given that the terrestrial and marine environments are currently absorbing about half of the carbon dioxide that is emitted by fossil-fuel combustion. This carbon uptake is therefore limiting the extent of atmospheric and climatic change, but its long-term nature remains uncertain. Here we provide an overview of the current state of knowledge of global and regional patterns of carbon exchange by terrestrial ecosystems. Atmospheric carbon dioxide and oxygen data confirm that the terrestrial biosphere was largely neutral with respect to net carbon exchange during the 1980s, but became a net carbon sink in the 1990s. This recent sink can be largely attributed to northern extratropical areas, and is roughly split between North America and Eurasia. Tropical land areas, however, were approximately in balance with respect to carbon exchange, implying a carbon sink that offset emissions due to tropical deforestation. The evolution of the terrestrial carbon sink is largely the result of changes in land use over time, such as regrowth on abandoned agricultural land and fire prevention, in addition to responses to environmental changes, such as longer growing seasons, and fertilization by carbon dioxide and nitrogen. Nevertheless, there remain considerable uncertainties as to the magnitude of the sink in different regions and the contribution of different processes.

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...

<p>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 ecosystems properties and derived benefits and detriments to people. Plant trait data thus represent the essential basis for a vast area of research spanning evolutionary biology, community and functional ecology, biodiversity conservation, ecosystem and landscape management and restoration, biogeography to earth system modeling. 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. Increasingly the TRY database also supports new frontiers of trait-based research, including identi:cation of data gaps and subsequent mobilization or measurement of new data. To support this development, in this article we take stock of trait data compiled in TRY and analyze emerging patterns of data coverage, representativeness, and gaps. Best species coverage is achieved for categorical traits (stable within species) relevant to determine plant functional types commonly used in global vegetation models. For the trait ‘plant growth form’ complete species coverage is within reach. However, most traits relevant for ecology and vegetation modeling are characterized by intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment: completeness at global scale is impossible and representativeness challenging. Due to the sheer amount of data in the TRY database, machine learning for trait prediction is promising - but does not add new data. We therefore conclude that reducing data gaps and biases by further and more systematic mobilization of trait data and new in-situ trait measurements must continue to be a high priority. This can only be achieved by a community effort in collaboration with other initiatives.</p>

Humans modify ecosystems and biodiversity worldwide, with negative consequences for ecosystem functioning. Promoting plant diversity is increasingly suggested as a mitigation strategy. However, our mechanistic understanding of how plant diversity affects the diversity of heterotrophic consumer communities remains limited. Here, we disentangle the relative importance of key components of plant diversity as drivers of herbivore, predator, and parasitoid species richness in experimental forests and grasslands. We find that plant species richness effects on consumer species richness are consistently positive and mediated by elevated structural and functional diversity of the plant communities. The importance of these diversity components differs across trophic levels and ecosystems, cautioning against ignoring the fundamental ecological complexity of biodiversity effects. Importantly, plant diversity effects on higher trophic-level species richness are in many cases mediated by modifications of consumer abundances. In light of recently reported drastic declines in insect abundances, our study identifies important pathways connecting plant diversity and consumer diversity across ecosystems.