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The results of biodiversity–ecosystem functioning experiments are realistic

Nature Ecology & Evolution volume 4, pages 1485–1494 (2020)Cite this article

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Abstract

A large body of research shows that biodiversity loss can reduce ecosystem functioning. However, much of the evidence for this relationship is drawn from biodiversity–ecosystem functioning experiments in which biodiversity loss is simulated by randomly assembling communities of varying species diversity, and ecosystem functions are measured. This random assembly has led some ecologists to question the relevance of biodiversity experiments to real-world ecosystems, where community assembly or disassembly may be non-random and influenced by external drivers, such as climate, soil conditions or land use. Here, we compare data from real-world grassland plant communities with data from two of the largest and longest-running grassland biodiversity experiments (the Jena Experiment in Germany and BioDIV in the United States) in terms of their taxonomic, functional and phylogenetic diversity and functional-trait composition. We found that plant communities of biodiversity experiments cover almost all of the multivariate variation of the real-world communities, while also containing community types that are not currently observed in the real world. Moreover, they have greater variance in their compositional features than their real-world counterparts. We then re-analysed a subset of experimental data that included only ecologically realistic communities (that is, those comparable to real-world communities). For 10 out of 12 biodiversity–ecosystem functioning relationships, biodiversity effects did not differ significantly between the full dataset of biodiversity experiments and the ecologically realistic subset of experimental communities. Although we do not provide direct evidence for strong or consistent biodiversity–ecosystem functioning relationships in real-world communities, our results demonstrate that the results of biodiversity experiments are largely insensitive to the exclusion of unrealistic communities and that the conclusions drawn from biodiversity experiments are generally robust.

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Fig. 1: Experimental versus real-world communities.
Fig. 2: BEF relationships.

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Data availability

The data supporting the findings of our study are available at https://doi.org/10.25829/idiv.1869-11-3082.

Code availability

The R code to reproduce the findings and figures of our study is available at https://doi.org/10.25829/idiv.1869-11-3082.

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Acknowledgements

We thank the establishers, maintainers, coordinators, technical and research staff, and data owners of all involved projects, as well as the TRY initiative. We thank S. Soliveres and E. Allan for discussion; S. Thiel, G. Luo, D. Bahauddin and F. Schneider for help with data extraction and handling; and R. Junker and B. Blonder for assistance with the calculation of multidimensional hypervolumes. This study was funded through Jena Experiment SP 7 (Swiss National Science Foundation grant no. 310030E-166017/1). Further support came from the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, funded by the German Research Foundation (grant no. FZT 118). The Jena Experiment was funded by the Deutsche Forschungsgemeinschaft (grant nos FOR 456 and FOR 1451) with additional support from Friedrich Schiller University Jena, the Max Planck Institute for Biogeochemistry in Jena and the Swiss National Science Foundation. All Cedar Creek studies are funded by the US National Science Foundation’s Long-Term Ecological Research (LTER) programme (grant no. DEB-1234162). F.I. acknowledges funding from the LTER Network Communications Office (grant no. DEB-1545288). We thank the iDiv Data Repository for hosting our R code and aggregated datasets and for performing the related quality checks.

Author information

Authors and Affiliations

  1. Institute of Plant Sciences, University of Bern, Bern, Switzerland

    Malte Jochum, Markus Fischer, Steffen Boch, Rafael Molina-Venegas, Caterina Penone, Daniel Prati, Abiel Rindisbacher & Deborah Schäfer

  2. German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany

    Malte Jochum, Christiane Roscher, Nico Eisenhauer, Jens Kattge, Anja Vogel & Alexandra Weigelt

  3. Institute of Biology, Leipzig University, Leipzig, Germany

    Malte Jochum, Nico Eisenhauer & Anja Vogel

  4. Department of Ecology, Evolution and Behavior, University of Minnesota, Saint Paul, MN, USA

    Forest Isbell, Jeannine Cavender-Bares & David Tilman

  5. Department of Physiological Diversity, UFZ, Helmholtz Centre for Environmental Research, Leipzig, Germany

    Christiane Roscher

  6. Systematic Botany and Functional Biodiversity, Institute of Biology, Leipzig University, Leipzig, Germany

    Fons van der Plas & Alexandra Weigelt

  7. WSL Swiss Federal Research Institute, Birmensdorf, Switzerland

    Steffen Boch

  8. Max Planck Institute for Biogeochemistry, Jena, Germany

    Gerhard Boenisch, Gerd Gleixner, Jens Kattge & Markus Lange

  9. Institute of Agricultural Sciences, ETH Zürich, Zürich, Switzerland

    Nina Buchmann & Valentin H. Klaus

  10. Department of Geography, King’s College London, London, UK

    Jane A. Catford

  11. Institute of Ecology and Evolution, University of Jena, Jena, Germany

    Anne Ebeling & Anja Vogel

  12. Institute of Landscape Ecology, University of Münster, Münster, Germany

    Norbert Hölzel

  13. Institute of Landscape Ecology and Resources Management, Giessen University, Giessen, Germany

    Till Kleinebecker

  14. Senckenberg Biodiversity and Climate Research Centre (SBiK-F), Frankfurt, Germany

    Gaëtane Le Provost & Peter Manning

  15. Terrestrial Ecology Research Group, School of Life Sciences Weihenstephan, Technical University of Munich, Freising, Germany

    Sebastian T. Meyer & Wolfgang W. Weisser

  16. GloCEE–Global Change Ecology & Evolution group, Department of Life Sciences, University of Alcalá, Madrid, Spain

    Rafael Molina-Venegas

  17. Plant Ecology and Nature Conservation Group, Wageningen University and Research, Wageningen, The Netherlands

    Liesje Mommer

  18. Geoecology, Geoscience Department, University of Tübingen, Tübingen, Germany

    Yvonne Oelmann

  19. Department of Forest Resources, University of Minnesota, Saint Paul, MN, USA

    Peter B. Reich

  20. Hawkesbury Institute for the Environment, Western Sydney University, Penrith South DC, New South Wales, Australia

    Peter B. Reich

  21. JF Blumenbach Institute of Zoology and Anthropology, University of Göttingen, Göttingen, Germany

    Stefan Scheu

  22. Centre for Biodiversity and Sustainable Land Use, University of Göttingen, Göttingen, Germany

    Stefan Scheu

  23. Department of Geography, University of Zürich, Zürich, Switzerland

    Bernhard Schmid

  24. Institute of Ecology, College of Urban and Environmental Sciences, Peking University, Beijing, China

    Bernhard Schmid

  25. Bren School of Environmental Science and Management, University of California, Santa Barbara, CA, USA

    David Tilman

  26. Agroecology, Department of Crop Sciences, University of Göttingen, Göttingen, Germany

    Teja Tscharntke

  27. Department of Evolutionary Biology and Environmental Studies, University of Zürich, Zürich, Switzerland

    Cameron Wagg

  28. Institute of Geography and Geoecology, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany

    Wolfgang Wilcke

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  1. Malte Jochum
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  2. Markus Fischer
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Contributions

M.J., P.M., M.F. and F.v.d.P. conceived and designed the study. M.J., M.F., F.I., C.R., S.B., G.B., N.B., J.A.C., J.C.-B., A.E., N.E., G.G., N.H., J.K., V.H.K., T.K., M.L., G.L.P., S.T.M., L.M., Y.O., D.P., P.B.R., D.S., S.S., B.S., D.T., T.T., A.V., C.W., A.W., W.W.W., W.W. and P.M. contributed data. M.J. developed the analytical framework and analysed the data. R.M.-V. constructed the phylogenetic hypothesis trees. M.J. and P.M. wrote the manuscript. M.J., M.F., F.I., C.R., F.v.d.P., S.B., G.B., N.B., J.A.C., J.C.-B., A.E., N.E., G.G., N.H., J.K., V.H.K., T.K., M.L., G.L.P., S.T.M., R.M.-V., L.M., Y.O., C.P., D.P., P.B.R., A.R., D.S., S.S., B.S., D.T., T.T., A.V., C.W., A.W., W.W.W., W.W. and P.M. contributed to the discussion of the results and writing of the manuscript.

Corresponding author

Correspondence to Malte Jochum.

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The authors declare no competing interests.

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Extended data

Extended Data Fig. 1 List of German and US datasets for vegetation and ecosystem function data.

Lists country, project name, project code used in this paper, main reference, number of plots we used, years we have vegetation data for, functions we used including years. Most of the raw data is openly available in various online repositories: Jena Experiment (http://jenaexperiment.uni-jena.de/index.php/data/), Biodiversity Exploratories (https://www.bexis.uni-jena.de/Login/Account.aspx), Cedar Creek (https://www.cedarcreek.umn.edu/research/data). Data from the Saale grasslands (Jena real world) were provided by Christiane Roscher and are currently not openly available. Aggregated datasets used for this study are now available online101.

Extended Data Fig. 2 Temporal movement of Jena invasion communities into the real-world realm.

Based on the PCA in Fig. 1a. Different shades of purple show Jena invasion communities across the years from 2003-2009. Orange and gray ellipses show 95% confidence intervals for Jena Experiment and combined real-world plots (but their communities are not plotted here), respectively. Note that while the points in different panels are from single years, the ellipses are fixed to the across-year comparison in Fig. 1a. The last panel shows the PCA factor loadings for the 12 vif-selected community properties (arrows scaled to improve visibility - “const=25” in R vegan “biplot” function87). Within six years of succession, the plant communities of Jena invasion plots fully “moved” into the core of the community property space defined by the combined real-world plots (German real world and Jena real world, respectively).

Extended Data Fig. 3 Violin plots of all 21 community properties of German data.

Experimental (E, Jena Experiment, strong orange, 82 plots), unrealistic experimental (unreal., intermediate orange, 59 plots), selected realistic experimental (real., weak orange, 23 plots) and combined real-world plots (German real world, Jena real world, gray, 164 plots), all averaged across years per plot. Combination of boxplot and rotated kernel density plot (R package “vioplot”51). Realistic plots were calculated based on the 12 vif-selected community properties and the convex hull volume method. Units: leaf area (mm²), leaf dry mass (mg), leaf dry matter content (LDMC, g/g), leaf nitrogen concentration (leaf N, mg/g), leaf phosphorus concentration (leaf P, mg/g), plant height (m), specific leaf area (SLA, mm²/mg) and seed mass (dry mass in mg). Other community properties are dimensionless.

Extended Data Fig. 4 Violin plots of all 21 community properties of US data.

Experimental (E, BioDIV, strong orange, 159 plots), unrealistic experimental (unreal., intermediate orange, 37 plots), selected realistic experimental (real., weak orange, 122 plots) and combined real-world plots (Fertilization 1 & 2, gray, 369 plots), all averaged across years per plot. Combination of boxplot and rotated kernel density plot (R package “vioplot”51). Realistic plots were calculated based on the 12 vif-selected community properties and the convex hull volume method. Units: leaf area (mm²), leaf dry mass (mg), leaf dry matter content (LDMC, g/g), leaf nitrogen concentration (leaf N, mg/g), leaf phosphorus concentration (leaf P, mg/g), plant height (m), specific leaf area (SLA, mm²/mg) and seed mass (dry mass in mg). Other community properties are dimensionless.

Extended Data Fig. 5 Model parameters for BEF relationships presented in Fig. 2.

Values are presented for unconstrained (u) and constrained (c) models of Jena (J) and BioDIV BEF relationships. Constraining was done using the 12 vif-selected community properties and the convex hull method. Sample size (n), slope estimates (slop), lower (low) and upper (upp) 95% confidence intervals, p-values (p) and adjusted R2 values (R2). All values are rounded to two decimal places.

Extended Data Fig. 6 Variance explained by 12 PCA axes (12 vif-selected community properties).

Percentage of total variance explained by each of the 12 PCA axes (PC’s, see Fig. 1) for each region (GER = Germany and US = USA). Rounded to two decimal places.

Extended Data Fig. 7 PCA scores for 12 vif-selected community properties of PCA’s in Fig. 1.

Scores have been produced using the scores() command of the “vegan” package87 in R and have been rounded to two decimal places.

Supplementary information

Supplementary Information

Supplementary Figs. 1–10, Tables 1–17, Supplementary Information on Sensitivity Analyses 1 and 2, and methods.

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Jochum, M., Fischer, M., Isbell, F. et al. The results of biodiversity–ecosystem functioning experiments are realistic. Nat Ecol Evol 4, 1485–1494 (2020). https://doi.org/10.1038/s41559-020-1280-9

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