AFFILIATIONS 1 Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry; 2 German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig; 3 Institute for Biology, University of Leipzig; 4 Department of Community Ecology, Helmholtz Centre for Environmental Research UFZ; 5 Institute for Biology, University of Halle INTRODUCTION Functional diversity of plants (FD) can be assumed to influence ecosystem functioning. We lack a consistent set of observations to investigate this influence at continental scales. Linking plant functional traits with species distribution and remote sensing data, we derive a map of FD indices across Europe. We correlate these indices to ecosystem properties in a moving window approach and show the advantage of using this approach for the study of ecosystem-level processes Exploring plant functional diversity effects on ecosystem resilience at the continental scale F. Schrodt 1,2, M. Mahecha 1, F. Gans 1, S. Ratcliffe 3, M. Liebergesell 3, E. Welk 5, M. Jung 1, M. Forkel 1, J. Kattge 1, I. Kühn 4 REFERENCES 6 Jalas & Suominen (1988) Atlas florae Europaeae: distribution of Vasular palnts in Europe University Press Cambridge 7 European Forest Genetic Resources Programme; International Plant Genetic Resources Instit., Rome (Italy) 8 Baeten, Verheyen, Wirth et al. (2013) Perspectives in Plant Ecology, Evolution and Systematics 15: Brus, Hengeveld, Walvoort et al. (2012) European Journal of Forest Resources 131: Kattge, Díaz, Lavorel, Prentice et al. (2011) Global Change Biology 17: Reichstein, Bahn, Mahecha, et al. (2014) Proceedings of the National Academy of Sciences 111: DATA Distributions for 182 tree species were assembled from six databases: the Atlas Flora Europaea 6, Erik Welk 5, EUFORGEN 7, Mario Liebergesell 3, FunDiv 8 and Brus et al. (2011) 9. Plant functional traits were extracted from the TRY database 10. Climate data was extracted from the Worldclim dataset and soils from the Harmonized World Soil Database METHODS Ensemble of 10 Species distribution models (SDM) with the 1 st 8 principal component axes of soil, climate & topography and pseudo-absences using biomod2 (R). Calculation of 9 Functional diversity indices linking 18 plant functional traits with the species distributions corrected for forest cover using MODIS satellite data. Moving window correlation (0.5°x0.5°) between the FD indices and ecosystem properties (EP). DISCUSSION & OUTLOOK High variability between different species distribution datasets (Fig.1). SDMs are effective extrapolations. E.g. Abies alba: known to occur on the British Isles despite of not being reported there in any of our distribution datasets (Fig 2). Strong patterns of correlation between different functional diversity indices and EP (Fig.4), contrary to previously reported analyses.  Ground-truthing with large European plant inventroy  1st validated map of plant traits (FD) across Europe.  Link validated map to climate extreme data  influence of FD to promote resilience to climatic extreme events. RESULTS Fig.4: Moving window correlation between two functional diversity measures and the ecosystem property water use efficiency as calculated in 11. The diversity measures are effective dependence (A) and number of species (B). Red indicates significant negative, green significant positive correlations (at p < 0.05). Fig.1: Overlap between species distribution datasets in the case of Abies alba. Red shows pixel where only 1 dataset, yellow where 2, light green where 3 and dark green where 4 datasets report occurrences of Abies alba. Fig.2: Probability of Abies alba occurring in a pixel with green being very high, brown medium and grey very low. Results are from an ensemble of 10 species distribution models (see Methods). A B