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.

Background and objective: Oxygen is used in many clinical scenarios, however the variable performance of nasal cannulae makes determining the precise fraction of inspired oxygen (FiO2) difficult.We developed a novel method for measurement of the tracheal FiO2 using a catheter placed via bronchoscopy. We investigate the effects of oxygen delivery, respiratory rate, mouth position and estimated minute ventilation (VE) on the FiO2 delivered by nasal cannulae. Methods: The catheter was placed in 20 subjects. Tracheal gas concentrations were analysed during six 5-min treatments controlling for oxygen delivery rate, respiratory rate and mouth position. Ventilation was monitored with respiratory inductive plethysmography (RIP). The FiO2 delivered by nasal cannulae was compared between treatments, and we investigated the relationships among the FiO2, alveolar partial pressure of oxygen (PAO2) and VE. Conclusions: Continuous measurement of the FiO2 using a transtracheal catheter provides detailed insight into inspiratory changes of the FiO2 delivered by nasal cannulae. Our study confirms that respiratory rate, VE and mouth position significantly influence the inspired oxygen concentration. These parameters should be accounted for when prescribing oxygen.

1.Non-native species can dominate plant communities by competitively displacing native species, or because environmental change creates conditions favourable to non-native species but unfavourable to native species. We need to disentangle these alternative mechanisms so that management can target competitively dominant species and reduce their impacts. 2.Joint-species distribution models (JSDMs) can potentially quantify competitive impacts by examining how species respond to environmental variation and to changes in community composition. We describe a JSDM to model variation in plant cover, which detected declines in species abundance in the presence of a dominant competitor.3.We applied our model to an experiment in an invaded grassy-woodland community in Australia where we manipulated biomass removal (through slashing and grazing by kangaroos) along a fertility gradient. Non-native species dominated plant cover at high fertility sites in the absence of biomass removal. Using a JSDM, we determined that three of the 72 non-native plant species (Bromus diandrus, Acetosella vulgaris and especially Avena fatua) were having a strong competitive impact on the community, driving changes in composition and reducing the cover of both native and non-native species, particularly in the absence of grazing. The dominant annual grasses (Bromus diandrus and Avena fatua) were two of the tallest species in the community and were good competitors for light under conditions of high fertility and low grazing. Consequently, their impacts were greatest on smaller statured species.4.Synthesis. We demonstrate a method to measure competitive impact using a JSDM, identify species driving compositional change through competitive displacement, and identify where on the landscape competitive impacts are greatest. This information is central to managing plant invasions: by targeting dominant non-native species with large competitive impacts, management can reduce impacts where they are greatest. We provide details of the modelling procedure and reproducible code to encourage further application.