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: The Vegetation Map of South Africa, Lesotho and Swaziland (National Vegetation Map [NVM]) is a fundamental data set that is updated periodically. The National Biodiversity Assessment (NBA) 2018 process provided an opportunity for a more comprehensive revision of the NVM and better alignment between the terrestrial, marine and estuarine ecosystem maps.Objectives: The aim of this study was to update the NVM 2018 and quantify spatial and classification changes since NVM 2012, and describe the rationale and data sources utilised. We also quantified spatial errors corrected in this version, highlighted progress since NVM 2006, and identified errors and gaps to make recommendations for future revisions.Method: Edits made to the NVM in ArcMap 10.4 were categorised into the following five groups for analysis: (1) New types, (2) Boundary edits, (3) Realm re-assignment, (4) Removed and replaced vegetation types and (5) Deleted map area. Changes were quantified by category and biome. We used various software platforms to correct and quantify spatial errors since 2006.Results: Vegetation types were added (n = 47), removed (n = 35) and had boundary edits (n = 107) in NVM 2018, which affected over 5% of the total map area, compared to 2.6% (2012) and 0.5% (2009) for previous versions. Several sources of error were identified and fixed, and prompted the development of standard mapping protocols.Conclusion: National Vegetation Map 2018 is the most substantial revision of this data set that now fully aligns with maps of all other realms that form part of the NBA. However, parts of the map remain unrefined and provide opportunities for future work.

1. Positive biotic interactions between plant species may strongly affect species and community-level patterns, but the processes through which benefactor species alter the performance of interacting species (via, e.g. beneficial mechanisms like resource provisioning) are still inadequately understood. One poorly explored potential explanation is that plant-plant facilitation could occur through the impact of benefactor species on the functional trait expression of beneficiary species. Indeed, plant species that affect local conditions can modify functional trait expression of interacting species, thereby improving their performance and resulting in a facilitative interaction. However, the response of intraspecific trait variation to biotically driven microhabitat modification, and its role in determining the outcome of plant-plant interactions, has rarely been explored. 2. Here, we test whether growing with benefactor species affects the expression of functional traits of eight species, encompassing different plant growth forms, in two contrasting study systems. This is achieved using a paired sampling approach to compare values of seven functional traits of conspecific individuals growing within and adjacent to cushion plants (i.e. benefactor species which are known to strongly alter microhabitat conditions and to have positive effects on some of the focal species). In addition, we test whether the effect of biotic interactions on functional trait expression changes along elevational gradients, as the outcome of biotic interactions is expected to vary with elevation. 3. Contrary to predictions, in both systems, intraspecific trait variation was not well explained by the biotic interaction with the cushion plant species or the variation in abiotic conditions associated with elevational gradients. Where biotic interactions did affect functional trait expression and bivariate trait relationships, traits responded variably between species, suggesting that context specificity may be a constraint to predicting how intraspecific trait variation responds to plant-plant interactions, adding to the growing body of literature that challenges the generality and predictability of the drivers of intraspecific trait variation. 4. This research, therefore, suggests that benefactor species' facilitative process is likely not through an impact on intraspecific trait expression, and that instead other processes may be more important for translating beneficial microhabitat 256 | Functional Ecology van der MerWe et al.

Research Highlights structures. In addition, our results highlight biologically-important differences in engineering impacts between burrow entrances, where soil is removed, and mounds, where soil is deposited. Such microscale differences are important to consider when examining bioturbation or, more generally, ecosystem engineering.

The updating and rethinking of vegetation classifications is important for ecosystem monitoring in a rapidly changing world, where the distribution of vegetation is changing. The general assumption that discrete and persistent plant communities exist that can be monitored efficiently, is rarely tested before undertaking a classification. Marion Island (MI) is comprised of species‐poor vegetation undergoing rapid environmental change. It presents a unique opportunity to test the ability to discretely classify species‐poor vegetation with recently developed objective classification techniques and relate it to previous classifications. We classified vascular species data of 476 plots sampled across MI, using Ward hierarchical clustering, divisive analysis clustering, non‐hierarchical kmeans and partitioning around medoids. Internal cluster validation was performed using silhouette widths, Dunn index, connectivity of clusters and gap statistic. Indicator species analyses were also conducted on the best performing clustering methods. We evaluated the outputs against previously classified units. Ward clustering performed the best, with the highest average silhouette width and Dunn index, as well as the lowest connectivity. The number of clusters differed amongst the clustering methods, but most validation measures, including for Ward clustering, indicated that two and three clusters are the best fit for the data. However, all classification methods produced weakly separated, highly connected clusters with low compactness and low fidelity and specificity to clusters. There was no particularly robust and effective classification outcome that could group plots into previously suggested vegetation units based on species composition alone. The relatively recent age ( c. 450,000 years B.P.), glaciation history (last glacial maximum 34,500 years B.P.) and isolation of the sub‐Antarctic islands may have hindered the development of strong vascular plant species assemblages with discrete boundaries. Discrete classification at the community‐level using species composition may not be suitable in such species‐poor environments. Species‐level, rather than community‐level, monitoring may thus be more appropriate in species‐poor environments, aligning with continuum theory rather than community theory.

The IAVS is here to connect people and to provide an intellectual home for those who focus on any aspect of vegetation. Although I have always been aware of the unique importance of the Association, reading the survey responses confirmed my concept of its role. And I am happy that many other people have such a positive attitude to and good experiences with the IAVS. I hope for a positive future for the Association and my hope is based on a strong participation of young people in the IAVS activities. This is important as the general interest of young people in natural sciences is rapidly declining; this is obvious probably also in other places than Central Europe where I live. I also hope that the atmosphere of our meetings will remain relaxed and friendly and it will not be spoiled by political developments in individual countries or by increasing scientific competitiveness in general. And I am looking forward to meeting many of you in Bozeman soon.

Cushion plants are a key Arctic, Antarctic, and alpine growth form, with many cushion-forming species strongly affecting community structure in abiotically stressful environments. Despite their ecological importance, there is little information about what drives the distribution of species exhibiting this growth form. This study investigates the determinants of the distribution of a cushion plant species, Euphorbia clavarioides at (1) a fine scale, using field-collected predictors from an alpine landscape; and (2) a broad scale, using distribution records and climate data across the species' distributional range. At the fine scale, the species was locally rare (occurring in about 4 percent of samples) and may be limited to specific microsites by interspecific competition with taller-growing species. Broad-scale species distribution modeling showed that both temperature and rainfall are important in predicting the distribution of E. clavarioides with a higher probability of occurrence in areas with higher annual precipitation and mean annual temperatures < 15°C. Given the species' sensitivity to competition and abiotic conditions (high temperatures and low precipitation), E. clavarioides may be vulnerable to environmental changes. Therefore, assuming that other cushion plant species exhibit similar patterns, species of this growth form may be particularly useful indicators of change in alpine, Arctic, and Antarctic areas.

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