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.

In a range of plant species from three Californian vegetation types, we examined the widely used "normalized difference vegetation index" (NDVI) and "simple ratio" (SR) as indicators of canopy structure, light absorption, and photosynthetic activity. These indices, which are derived from canopy reflectance in the red and near‐infrared wavebands, highlighted phenological differences between evergreen and deciduous canopies. They were poor indicators of total canopy biomass due to the varying abundance of non‐green standing biomass in these vegetation types. However, in sparse canopies (leaf area index [LAI]°0‐2), NDVI was a sensitive indicator of canopy structure and chemical content (green biomass, green leaf area index, chlorophyll content, and foliar nitrogen content). At higher canopy green LAI values (>2; typical of dense shrubs and trees), NDVI was relatively insensitive to changes in canopy structure. Compared to SR, NDVI was better correlated with indicators of canopy structure and chemical content, but was equivalent to the logarithm of SR. In agreement with theoretical expectations, both NDVI and SR exhibited near‐linear correlations with fractional PAR intercepted by green leaves over a wide range of canopy densities. Maximum daily photosynthetic rates were positively correlated with NDVI and SR in annual grassland and semideciduous shrubs where canopy development and photosynthetic activity were in synchrony. The indices were also correlated with peak springtime canopy photosynthetic rates in evergreens. However, over most of the year, these indices were poor predictors of photosynthetic performance in evergreen species due to seasonal reductions in photosynthetic radiation‐use efficiency that occurred without substantial declines in canopy greenness. Our results support the use of these vegetation indices as remote indicators of PAR absorption, and thus potential photosynthetic activity, even in heterogeneous landscapes. To provide accurate estimates of vegetation‐atmosphere gas fluxes, remote NDVI and SR measurements need to be coupled with careful estimates of canopy photosynthetic radiation‐use efficiency.

Climatic changes, including altered precipitation regimes, will affect key ecosystem processes, such as plant productivity and biodiversity for many terrestrial ecosystems. Past and ongoing precipitation experiments have been conducted to quantify these potential changes. An analysis of these experiments indicates that they have provided important information on how water regulates ecosystem processes. However, they do not adequately represent global biomes nor forecasted precipitation scenarios and their potential contribution to advance our understanding of ecosystem responses to precipitation changes is therefore limited, as is their potential value for the development and testing of ecosystem models. This highlights the need for new precipitation experiments in biomes and ambient climatic conditions hitherto poorly studied applying relevant complex scenarios including changes in precipitation frequency and amplitude, seasonality, extremity and interactions with other global change drivers. A systematic and holistic approach to investigate how soil and plant community characteristics change with altered precipitation regimes and the consequent effects on ecosystem processes and functioning within these experiments will greatly increase their value to the climate change and ecosystem research communities. Experiments should specifically test how changes in precipitation leading to exceedance of biological thresholds affect ecosystem resilience and acclimation.

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