Abstract

Biodiversity ensures ecosystem functioning and provisioning of ecosystem services, but it remains unclear how biodiversity–ecosystem multifunctionality relationships depend on the identity and number of functions considered. Here, we demonstrate that ecosystem multifunctionality, based on 82 indicator variables of ecosystem functions in a grassland biodiversity experiment, increases strongly with increasing biodiversity. Analysing subsets of functions showed that the effects of biodiversity on multifunctionality were stronger when more functions were included and that the strength of the biodiversity effects depended on the identity of the functions included. Limits to multifunctionality arose from negative correlations among functions and functions that were not correlated with biodiversity. Our findings underline that the management of ecosystems for the protection of biodiversity cannot be replaced by managing for particular ecosystem functions or services and emphasize the need for specific management to protect biodiversity. More plant species from the experimental pool of 60 species contributed to functioning when more functions were considered. An individual contribution to multifunctionality could be demonstrated for only a fraction of the species.

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Acknowledgements

We thank E. Marquard, I. Kertscher, Y. Kreutziger, S. Rosenkranz and A. Sabais for providing additional data and T. Lewinsohn for comments on the paper. We thank the gardeners, technicians, student helpers and managers of the Jena Experiment for their work. The Deutsche Forschungsgemeinschaft (FOR 456 and FOR 1451) and Swiss National Science Foundation financed the Jena Experiment.

Author information

Affiliations

  1. Terrestrial Ecology Research Group, Department of Ecology and Ecosystem Management, School of Life Sciences Weihenstephan, Technical University of Munich, Hans-Carl-von-Carlowitz-Platz 2, 85354, Freising, Germany

    • Sebastian T. Meyer
    •  & Wolfgang W. Weisser
  2. WasserCluster Lunz, Dr. Carl Kupelwieser Promenade 5, 3293, Lunz am See, Austria

    • Robert Ptacnik
  3. Institute for Chemistry and Biology of Marine Environments, Carl-von-Ossietzky University Oldenburg, Schleusenstrasse 1, 26382, Wilhelmshaven, Germany

    • Helmut Hillebrand
  4. Humboldt-Universitaet zu Berlin, Institute of Plant Nutrition, Albrecht-Thaer-Weg 4, 14195, Berlin, Germany

    • Holger Bessler
    •  & Christof Engels
  5. Institute of Agricultural Sciences, ETH Zurich, Universitätsstrasse 2, 8092, Zurich, Switzerland

    • Nina Buchmann
  6. Institute of Ecology, University of Jena, Dornburger Strasse 159, D–07743, Jena, Germany

    • Anne Ebeling
    • , Stefan Halle
    •  & Winfried Voigt
  7. German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, 04103, Leipzig, Germany

    • Nico Eisenhauer
    • , Christiane Roscher
    •  & Alexandra Weigelt
  8. Institute of Biology, Leipzig University, Johannisallee 21, 04103, Leipzig, Germany

    • Nico Eisenhauer
    •  & Alexandra Weigelt
  9. Institute of Plant Sciences, University of Bern, Altenbergrain 21, Bern, CH-3013, Switzerland

    • Markus Fischer
  10. Chair of Nature Conservation and Landscape Ecology, University of Freiburg, Tennenbacher Strasse 4, 79106, Freiburg, Germany

    • Alexandra-Maria Klein
  11. Geoecology, University of Tübingen, Rümelinstraße 19–23, 72070, Tübingen, Germany

    • Yvonne Oelmann
  12. UFZ, Helmholtz Centre for Environmental Research, Physiological Diversity, Permoserstrasse 15, 04318, Leipzig, Germany

    • Christiane Roscher
  13. Institute of Biochemistry and Biology, Biodiversity Research/Systematic Botany, University of Potsdam, Maulbeerallee 1, 14469, Potsdam, Germany

    • Tanja Rottstock
  14. Institute of Landscape Ecology, University of Muenster, Heisenbergstrasse 2, 48149, Muenster, Germany

    • Christoph Scherber
  15. J. F. Blumenbach Institute of Zoology and Anthropology, University of Göttingen, Untere Karspüle 2, 37073, Göttingen, Germany

    • Stefan Scheu
  16. Department of Evolutionary Biology and Environmental Studies and Zurich–Basel Plant Science Center, University of Zurich, Winterthurerstrasse 190, CH-8057, Zurich, Switzerland

    • Bernhard Schmid
  17. Max Planck Institute for Biogeochemistry, Hans-Knoell-Strasse 10, 07745, Jena, Germany

    • Ernst-Detlef Schulze
    •  & Vicky M. Temperton
  18. Institute of Ecology, Leuphana University Lüneburg, Scharnhorststrasse 1, 21335, Lüneburg, Germany

    • Vicky M. Temperton
  19. Agroecology, University of Göttingen, Grisebachstrasse 6, 37077, Göttingen, Germany

    • Teja Tscharntke
  20. Institute of Geography and Geoecology, Karlsruhe Institute of Technology, Reinhard-Baumeister-Platz 1, 76131, Karlsruhe, Germany

    • Wolfgang Wilcke

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Contributions

S.T.M., R.P., H.H. and W.W.W. conceived the study and developed the analytical procedure. S.T.M. and R.P. performed the analyses with contributions from W.V. All authors contributed measured data. S.T.M and W.W.W. wrote the paper. All authors contributed to writing and editing the paper.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Sebastian T. Meyer.

Electronic supplementary material

  1. Supplementary Information

    Supplementary material, Supplementary Tables, Supplementary Figures, Supplementary References

  2. Life Sciences Reporting Summary

  3. Supplementary Data 1

    List of explanatory variables describing the plots of the Jena experiment. Given are plotcodes, spatial blocks, the sown species richness, the number of functional groups sown in the plot and information on the presence of individual functional groups in the plots

  4. Supplementary Data 2

    The measured values for the 82 ecosystem variables indicating functions in the 81 plots of the Jena experiment from the last year available as used in the main analyses

  5. Supplementary Data 3

    The measured values for the 54 ecosystem variables indicating functions in the 81 plots of the Jena experiment all measured in 2004 as used in a sensitivity analysis for the effect of including data on ecosystem functions measured in different years

  6. Supplementary Data 4

    Information for each ecosystem variable whether higher or lower values are considered indication of higher functioning

  7. Supplementary Code 1

    R code to calculate an index of multifunctionality using the introduced multivariate approach

  8. Supplementary Code 2

    R code to updating the turnover approach to multifunctionality to included more stringent criteria for considering an effect of an individual species informative. This allows to compensate for a high number of tests when many functions and many species are included in an analysis using the turnover approach. The code also includes analyses of simulated data to explore, based on permutation procedures, how large the potential bias in the results of the turnover approach are when using very large data sets

  9. Supplementary Figure 1

    High-resolution version of the Supplementary Figure 2.3 showing loadings of all 82 ecosystem variables on principle components of the ordination calculated in the main analysis

  10. Supplementary Figure 2

    High-resolution version of the Supplementary Figure 2.4 showing pairwise correlations between all 82 ecosystem variables included in the main analysis to indicate ecosystem functions and the calculated index of multifunctionality