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.

SummaryIntercropping is a farming practice involving two or more crop species, or genotypes, growing together and coexisting for a time. On the fringes of modern intensive agriculture, intercropping is important in many subsistence or low-input/resource-limited agricultural systems. By allowing genuine yield gains without increased inputs, or greater stability of yield with decreased inputs, intercropping could be one route to delivering 'sustainable intensification'. We discuss how recent knowledge from agronomy, plant physiology and ecology can be combined with the aim of improving intercropping systems. Recent advances in agronomy and plant physiology include better understanding of the mechanisms of interactions between crop genotypes and speciesfor example, enhanced resource availability through niche complementarity. Ecological advances include better understanding of the context-dependency of interactions, the mechanisms behind disease and pest avoidance, the links between above-and below-ground systems, and the role of microtopographic variation in coexistence. This improved understanding can guide approaches for improving intercropping systems, including breeding crops for intercropping. Although such advances can help to improve intercropping systems, we suggest that other topics also need addressing. These include better assessment of the wider benefits of intercropping in terms of multiple ecosystem services, collaboration with agricultural engineering, and more effective interdisciplinary research.

This work shows the applicability of a set of protocols that can be widely applied to assess the impacts of global change drivers on species, communities and ecosystems.

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Land use and climate changes induce shifts in plant functional diversity and community structure, thereby modifying ecosystem processes. This is particularly true for litter decomposition, an essential process in the biogeochemical cycles of carbon and nutrients. In this study, we asked whether changes in functional traits of living leaves in response to changes in land use and climate were related to rates of litter potential decomposition, hereafter denoted litter decomposability, across a range of 10 contrasting sites. To disentangle the different control factors on litter decomposition, we conducted a microcosm experiment to determine the decomposability under standard conditions of litters collected in herbaceous communities from Europe and Israel. We tested how environmental factors (disturbance and climate) affected functional traits of living leaves and how these traits then modified litter quality and subsequent litter decomposability. Litter decomposability appeared proximately linked to initial litter quality, with particularly clear negative correlations with lignin-dependent indices (litter lignin concentr tion, lignin:nitrogen ratio, and fiber component). Litter quality was directly related to community-weighted mean traits. Lignin-dependent indices of litter quality were positively correlated with community-weighted mean leaf dry matter content (LDMC), and negatively correlated with community-weighted mean leaf nitrogen concentration (LNC). Consequently, litter decomposability was correlated negatively with community-weighted mean LDMC, and positively with community-weighted mean LNC. Environmental factors (disturbance and climate) influenced community-weighted mean traits. Plant communities experiencing less frequent or less intense disturbance exhibited higher community-weighted mean LDMC, and therefore higher litter lignin content and slower litter decomposability. LDMC therefore appears as a powerful marker of both changes in land use and of the pace of nutrient cycling across 10 contrasting sites.