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Biodiversity at multiple trophic levels is needed for ecosystem multifunctionality

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Many experiments have shown that loss of biodiversity reduces the capacity of ecosystems to provide the multiple services on which humans depend1,2. However, experiments necessarily simplify the complexity of natural ecosystems and will normally control for other important drivers of ecosystem functioning, such as the environment or land use. In addition, existing studies typically focus on the diversity of single trophic groups, neglecting the fact that biodiversity loss occurs across many taxa3,4 and that the functional effects of any trophic group may depend on the abundance and diversity of others5,6. Here we report analysis of the relationships between the species richness and abundance of nine trophic groups, including 4,600 above- and below-ground taxa, and 14 ecosystem services and functions and with their simultaneous provision (or multifunctionality) in 150 grasslands. We show that high species richness in multiple trophic groups (multitrophic richness) had stronger positive effects on ecosystem services than richness in any individual trophic group; this includes plant species richness, the most widely used measure of biodiversity. On average, three trophic groups influenced each ecosystem service, with each trophic group influencing at least one service. Multitrophic richness was particularly beneficial for ‘regulating’ and ‘cultural’ services, and for multifunctionality, whereas a change in the total abundance of species or biomass in multiple trophic groups (the multitrophic abundance) positively affected supporting services. Multitrophic richness and abundance drove ecosystem functioning as strongly as abiotic conditions and land-use intensity, extending previous experimental results7,8 to real-world ecosystems. Primary producers, herbivorous insects and microbial decomposers seem to be particularly important drivers of ecosystem functioning, as shown by the strong and frequent positive associations of their richness or abundance with multiple ecosystem services. Our results show that multitrophic richness and abundance support ecosystem functioning, and demonstrate that a focus on single groups has led to researchers to greatly underestimate the functional importance of biodiversity.

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Figure 1: Effects of multitrophic richness and abundance on grassland functioning.
Figure 2: Functional importance of multiple trophic groups.
Figure 3: Biotic versus abiotic drivers of ecosystem functioning.

Change history

  • 22 August 2016

    Figure 1 has been corrected to fix incorrect hatching in panels e, f, g and h.


  1. Cardinale, B. J. et al. Biodiversity loss and its impact on humanity. Nature 486, 59–67 (2012)

    Article  CAS  ADS  PubMed  Google Scholar 

  2. Naeem, S., Duffy, J. E. & Zavaleta, E. The functions of biological diversity in an age of extinction. Science 336, 1401–1406 (2012)

    Article  CAS  ADS  PubMed  Google Scholar 

  3. Allan, E. et al. Interannual variation in land-use intensity enhances grassland multidiversity. Proc. Natl Acad. Sci. USA 111, 308–313 (2014)

    Article  CAS  ADS  PubMed  Google Scholar 

  4. Newbold, T. et al. Global effects of land use on local terrestrial biodiversity. Nature 520, 45–50 (2015)

    Article  CAS  ADS  PubMed  Google Scholar 

  5. Naeem, S., Hahn, D. R. & Schuurman, G. Producer-decomposer co-dependency influences biodiversity effects. Nature 403, 762–764 (2000)

    Article  CAS  ADS  PubMed  Google Scholar 

  6. Balvanera, P. et al. Linking biodiversity and ecosystem services: current uncertainties and the necessary next steps. Bioscience 64, 49–57 (2014)

    Article  Google Scholar 

  7. Hooper, D. U. et al. A global synthesis reveals biodiversity loss as a major driver of ecosystem change. Nature 486, 105–108 (2012)

    Article  CAS  ADS  PubMed  Google Scholar 

  8. Tilman, D., Reich, P. B. & Isbell, F. Biodiversity impacts ecosystem productivity as much as resources, disturbance, or herbivory. Proc. Natl Acad. Sci. USA 109, 10394–10397 (2012)

    Article  CAS  ADS  PubMed  PubMed Central  Google Scholar 

  9. Petchey, O. L., McPhearson, P. T., Casey, T. M. & Morin, P. J. Environmental warming alters food-web structure and ecosystem function. Nature 402, 69–72 (1999)

    Article  CAS  ADS  Google Scholar 

  10. Duffy, J. E. et al. The functional role of biodiversity in ecosystems: incorporating trophic complexity. Ecol. Lett. 10, 522–538 (2007)

    Article  PubMed  Google Scholar 

  11. Jing, X. et al. The links between ecosystem multifunctionality and above- and belowground biodiversity are mediated by climate. Nat. Commun. 6, 8159 (2015)

    Article  ADS  PubMed  Google Scholar 

  12. Douglass, J. G., Duffy, J. E. & Bruno, J. F. Herbivore and predator diversity interactively affect ecosystem properties in an experimental marine community. Ecol. Lett. 11, 598–608 (2008)

    Article  PubMed  Google Scholar 

  13. Deraison, H., Badenhausser, I., Loeuille, N., Scherber, C. & Gross, N. Functional trait diversity across trophic levels determines herbivore impact on plant community biomass. Ecol. Lett. 18, 1346–1355 (2015)

    Article  PubMed  Google Scholar 

  14. Handa, I. T. et al. Consequences of biodiversity loss for litter decomposition across biomes. Nature 509, 218–221 (2014)

    Article  CAS  ADS  PubMed  Google Scholar 

  15. Delgado-Baquerizo, M. et al. Microbial diversity drives multifunctionality in terrestrial ecosystems. Nat. Commun. 7, 10541 (2016)

    Article  CAS  ADS  PubMed  PubMed Central  Google Scholar 

  16. Garibaldi, L. A. et al. Wild pollinators enhance fruit set of crops regardless of honey bee abundance. Science 339, 1608–1611 (2013)

    Article  CAS  ADS  PubMed  Google Scholar 

  17. McGrady-Steed, J., Harry, P. M. & Morin, P. J. Biodiversity regulates ecosystem predictability. Nature 390, 162–165 (1997)

    Article  CAS  ADS  Google Scholar 

  18. Grime, J. P. Benefits of plant diversity to ecosystems: immediate, filter and founder effects. J. Ecol. 86, 902–910 (1998)

    Google Scholar 

  19. Hillebrand, H., Bennett, D. M. & Cadotte, M. W. Consequences of dominance: a review of evenness effects on local and regional ecosystem processes. Ecology 89, 1510–1520 (2008)

    Article  PubMed  Google Scholar 

  20. Soliveres, S. et al. Locally rare species influence grassland ecosystem multifunctionality. Phil. Trans. R. Soc. B 371, 20150269 (2016)

    Article  PubMed  PubMed Central  Google Scholar 

  21. Grace, J. B. et al. Integrative modelling reveals mechanisms linking productivity and plant species richness. Nature 529, 390–393 (2016)

    Article  CAS  ADS  PubMed  Google Scholar 

  22. Byrnes, J. E. K. et al. Investigating the relationship between biodiversity and ecosystem multifunctionality: challenges and solutions. Methods Ecol. Evol. 5, 111–124 (2014)

    Article  Google Scholar 

  23. Millennium Ecosystem Assessment. Ecosystems and Human Well-Being 1–86 World Resources Institute (2005)

  24. Maestre, F. T. et al. Plant species richness and ecosystem multifunctionality in global drylands. Science 335, 214–218 (2012)

    Article  CAS  ADS  PubMed  PubMed Central  Google Scholar 

  25. Hector, A. & Bagchi, R. Biodiversity and ecosystem multifunctionality. Nature 448, 188–190 (2007)

    Article  CAS  ADS  PubMed  Google Scholar 

  26. Bruno, J. F., Boyer, K. E., Duffy, J. E. & Lee, S. C. Relative and interactive effects of plant and grazer richness in a benthic marine community. Ecology 89, 2518–2528 (2008)

    Article  PubMed  Google Scholar 

  27. Balvanera, P. et al. Quantifying the evidence for biodiversity effects on ecosystem functioning and services. Ecol. Lett. 9, 1146–1156 (2006)

    Article  PubMed  Google Scholar 

  28. Lefcheck, J. S. et al. Biodiversity enhances ecosystem multifunctionality across trophic levels and habitats. Nat. Commun. 6, 6936 (2015)

    Article  CAS  ADS  PubMed  Google Scholar 

  29. Naeem, S., Thompson, L. J., Lawler, S. P., Lawton, J. H. & Woodfin, R. M. Declining biodiversity can alter the performance of ecosystems. Nature 368, 734–737 (1994)

    Article  ADS  Google Scholar 

  30. Manning, P. et al. Grassland management intensification weakens the associations among the diversities of multiple plant and animal taxa. Ecology 96, 1492–1501 (2015)

    Article  Google Scholar 

  31. Fischer, M. et al. Implementing large-scale and long-term functional biodiversity research: The Biodiversity Exploratories. Basic Appl. Ecol. 6, 473–485 (2010)

    Article  Google Scholar 

  32. Blüthgen, N. et al. A quantitative index of land-use intensity in grasslands: integrating mowing, grazing and fertilization. Basic Appl. Ecol. 13, 207–220 (2012)

    Article  Google Scholar 

  33. Zavaleta, E. S., Pasari, J. R., Hulvey, K. B. & Tilman, G. D. Sustaining multiple ecosystem functions in grassland communities requires higher biodiversity. Proc. Natl Acad. Sci. USA 107, 1443–1446 (2010)

    Article  CAS  ADS  PubMed  PubMed Central  Google Scholar 

  34. Allan, E. et al. Land use intensification alters ecosystem multifunctionality via loss of biodiversity and changes to functional composition. Ecol. Lett. 18, 834–843 (2015)

    Article  PubMed  PubMed Central  Google Scholar 

  35. Hautier, Y. et al. Eutrophication weakens stabilizing effects of diversity in natural grasslands. Nature 508, 521–525 (2014)

    Article  CAS  ADS  PubMed  Google Scholar 

  36. Gamfeldt, L., Hillebrand, H. & Jonsson, P. R. Multiple functions increase the importance of biodiversity for overall ecosystem functioning. Ecology 89, 1223–1231 (2008)

    Article  PubMed  Google Scholar 

  37. Gamfeldt, L. et al. Higher levels of multiple ecosystem services are found in forests with more tree species. Nat. Commun. 4, 1340 (2013)

    Article  ADS  CAS  PubMed  Google Scholar 

  38. Cardinale, B. J. et al. Effects of biodiversity on the functioning of trophic groups and ecosystems. Nature 443, 989–992 (2006)

    Article  CAS  ADS  PubMed  Google Scholar 

  39. Moran, M. D. Arguments for rejecting the sequential Bonferroni in ecological studies. Oikos 100, 403–405 (2003)

    Article  Google Scholar 

  40. Tylianakis, J. M. et al. Resource heterogeneity moderates the biodiversity-function relationship in real world ecosystems. PLoS Biol. 6, e122 (2008)

    Article  CAS  PubMed Central  Google Scholar 

  41. R Development Core Team. R: A Language And Environment For Statistical Computing (R Foundation For Statistical Computing, 2014)

  42. Borcard, D., Legendre, P. & Drapeau, P. Partialling out the spatial component of ecological variation. Ecology 73, 1045–1055 (1992)

    Article  Google Scholar 

  43. Peres-Neto, P. R., Legendre, P., Dray, S. & Borcard, D. Variation partitioning of species data matrices: estimation and comparison of fractions. Ecology 87, 2614–2625 (2006)

    Article  PubMed  Google Scholar 

  44. Micallef, L. & Rodgers, P. eulerAPE: drawing area-proportional 3-Venn diagrams using ellipses. PLoS One 9, e101717 (2014)

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  45. Worm, B. & Duffy, J. E. Biodiversity, productivity and stability in real food webs. Trends Ecol. Evol. 18, 628–632 (2003)

    Article  Google Scholar 

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We thank B. Schmid, F. T. Maestre and S. Kéfi for comments that helped improve this manuscript. W. Ulrich and N. J. Gotelli provided statistical advice. We thank the people who maintain the Biodiversity Exploratories program: A. Hemp, K. Wells, S. Gockel, K. Wiesner and M. Gorke (local management team); S. Pfeiffer and C. Fischer (central office), B. König-Ries and M. Owonibi (central database management); and E. Linsenmair, D. Hessenmöller, J. Nieschulze, E.-D. Schulze and the late E. Kalko for their role in setting up the project. This work was funded by the Deutsche Forschungsgemeinschaft Priority Program 1374 ‘Infrastructure-Biodiversity Exploratories’. Fieldwork permits were given by the responsible state environmental offices of Baden-Württemberg, Thüringen and Brandenburg (according to §72 BbgNatSchG). Figure icons were created by R. D. Manzanedo.

Author information

Authors and Affiliations



S.S. and E.A. conceived the idea of this study. M.F. initiated the Biodiversity Exploratories project aimed at measuring multiple diversities and functions in the field sites. All authors but S.S., E.A. and F.V.D.P. contributed data. S.S. and F.V.D.P. performed the analyses. S.S. and S.C.R. performed the literature search. S.S. wrote the first draft of the manuscript and all the authors (especially E.A., P.M., F.D.V.P., M.M.G. and D.P.) contributed substantially to the revisions.

Corresponding author

Correspondence to Santiago Soliveres.

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The authors declare no competing financial interests.

Additional information

Reviewer Information

Nature thanks Y. Hautier, F. Isbell and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Extended data figures and tables

Extended Data Figure 1 Functional effects of multitrophic richness and abundance on 14 grassland ecosystem services.

a, Standardized coefficients (mean ± s.e.m.) of the abundances (triangles) and richness (circles) of those trophic groups that significantly affect a given function are shown. b, The net effect (that is, the sum of significant standardized effects). c, Difference in adjusted R2 between the final multitrophic models and those models using the abundance and richness of the best performing individual trophic group (unitrophic) or plant species richness (plant richness). Ecosystem services are organized by the main four types of services they associate with (provisioning, supporting, regulating and cultural). The number of trophic groups included in the most parsimonious model is given next to their adjusted R2. Multifunctionality results at 25%, 50%, 75% and 90% thresholds are also shown (see Methods).

Extended Data Figure 2 Functional effects of environmental factors and multitrophic richness and abundance on 14 grassland ecosystem functions.

a, Standardized slope estimates (mean ± s.e.m.) for each significant predictor are shown, with the exception of study region and soil type, which were retained in all models. b, Net effect (sum of significant standardized effects) for multitrophic richness and abundance. c, The total amount of variance explained by either environmental + plant species richness, environmental + the abundance and richness of the best individual trophic predictor, or by environmental + multitrophic diversity and abundance are shown for each function (adjusted R2, to control for the high number of predictors included). The number of trophic groups included in the best models (2.15 ± 1.2 across functions, and 1.94 ± 1.2 across functions and multifunctionality indices) is given next to the adjusted R2 value. The increase in the adjusted R2 values in models with plant-species-richness averaged 0.07 ± 0.12 (across functions) and 0.06 ± 0.11 (across functions and multifunctionality indices). Ecosystem services are organized by the main four types of services they associate with (top–bottom: provisioning, supporting, regulating and cultural). TWI, topographic wetness index, based on the aspect and position in the slope, and the inclination of the slope. Multicollinearity between the predictors introduced is unlikely (Extended Data Table 3).

Extended Data Figure 3 Number of trophic groups necessary to predict multifunctionality measures calculated with all possible combinations of 1–9 services, and their net effects.

The number of predictors selected in the best models (left) and their overall effects (sum of standardized coefficients; right) across all possible combinations of 1–9 services (N = 501) are shown. Error bars show the 95% confidence intervals, estimated for all possible combinations of n (1 to 9) functions in both cases. Only the 9 services with fewer than 20 data gaps were considered in these analyses (see details in Methods). Multifunctionality for these combinations was calculated at the 25% (upper panel), 50%, 75% and 90% (bottom panel) thresholds. Services removed were flower cover, arbuscular mycorrhizal colonization, soil aggregate stability, phosphorous retention index and pest control.

Extended Data Figure 4 Functional effect of the different trophic groups on contrasting multifunctionality scenarios.

Overall functional effects (significant standardized coefficients; mean ± s.e.m.) from the most parsimonious model) of the richness (open bars) and abundance (hatched bars) of each group are shown according to ref. 34.

Extended Data Figure 5 Functional importance of species richness and abundance compared to environmental drivers.

Venn diagrams showing the variance partition for the four components of our statistical models (environment: climate, soil and land-use intensity; species richness of the nine trophic groups, abundance of primary producers, above- and below-ground predators, below-ground herbivores and soil microbial decomposers). The variance not explained by the model (the residual) is also shown. The variance explained by richness, abundance and their overlap is summed up as Biota. Each panel represents an individual function or multifunctionality metric.

Extended Data Figure 6 Functional effect of the different trophic groups.

Overall functional effects (mean ± s.e.m. of the standardized slopes obtained from the model; with the exception of a, where error could not be estimated) of the richness (open bars) and abundance (hatched bars) of each group. a, The values were calculated after weighting each standardized coefficient (those in Extended Data Fig. 1) by the adjusted R2 of the model to account for differences in model performance. b, c, The values were calculated as the standardized coefficients in a general model fitted to all services at once, including ‘service identity’ as an extra predictor and ‘plot’ as random factor to control for pseudo-replication (reduced models (b); the ones presented in the main text), or full models (c) and, d, calculated as multi-model average parameters from a model fitted to all services at once. Correlations (Spearman’s rank correlation coefficients) between the different approaches are given.

Extended Data Table 1 Re-analysis of manipulative multitrophic studies
Extended Data Table 2 Details of the sampling procedure for each trophic group and function
Extended Data Table 3 Correlations between diversity predictors from the models in the main text
Extended Data Table 4 Model selection

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Soliveres, S., van der Plas, F., Manning, P. et al. Biodiversity at multiple trophic levels is needed for ecosystem multifunctionality. Nature 536, 456–459 (2016).

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