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Eutrophication weakens stabilizing effects of diversity in natural grasslands

Nature volume 508, pages 521–525 (2014)Cite this article

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Abstract

Studies of experimental grassland communities1,2,3,4,5,6,7 have demonstrated that plant diversity can stabilize productivity through species asynchrony, in which decreases in the biomass of some species are compensated for by increases in others1,2. However, it remains unknown whether these findings are relevant to natural ecosystems, especially those for which species diversity is threatened by anthropogenic global change8,9,10,11. Here we analyse diversity–stability relationships from 41 grasslands on five continents and examine how these relationships are affected by chronic fertilization, one of the strongest drivers of species loss globally8. Unmanipulated communities with more species had greater species asynchrony, resulting in more stable biomass production, generalizing a result from biodiversity experiments to real-world grasslands. However, fertilization weakened the positive effect of diversity on stability. Contrary to expectations, this was not due to species loss after eutrophication but rather to an increase in the temporal variation of productivity in combination with a decrease in species asynchrony in diverse communities. Our results demonstrate separate and synergistic effects of diversity and eutrophication on stability, emphasizing the need to understand how drivers of global change interactively affect the reliable provisioning of ecosystem services in real-world systems.

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Figure 1: Relationships of temporal stability of ANPP (upper row) and species asynchrony (lower row) with species diversity.
Figure 2: Relationships between temporal stability of ANPP (natural log transformed) and species asynchrony in 41 grassland sites of the Nutrient Network.
Figure 3: Relationships of temporal mean and standard deviation of ANPP (natural log transformed) to species diversity in 41 grassland sites of the Nutrient Network.

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Acknowledgements

The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 298935 to Y.H. (with A.H. and E.W.S.). This work was generated using data from the Nutrient Network (http://www.nutnet.org) experiment, funded at the site-scale by individual researchers. Coordination and data management have been supported by funding to E.T.B. and E.W.S. from the National Science Foundation Research Coordination Network (NSF-DEB-1042132), the Long Term Ecological Research (LTER) programme (NSF-DEB-1234162 to Cedar Creek as well as other LTER sites), and the Institute on the Environment at the University of Minnesota (DG-0001-13). We also thank the Minnesota Supercomputer Institute for hosting project data, and the Institute on the Environment for hosting Network meetings. We thank R. S. L. Veiga, F. Isbell, R. K. Didham, H. McGinness and M. O’Brien for suggestions that improved the manuscript.

Author information

Authors and Affiliations

  1. Department of Ecology, Evolution, and Behavior, University of Minnesota, St Paul, 55108, Minnesota, USA

    Yann Hautier, Eric W. Seabloom, Elizabeth T. Borer & Eric M. Lind

  2. Institute of Evolutionary Biology and Environmental Studies, University of Zurich, 8057 Zurich, Switzerland,

    Yann Hautier

  3. Department of Wildland Resources and the Ecology Center, Utah State University, Logan, 84322, Utah, USA

    Peter B. Adler

  4. Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, 50011, Iowa, USA

    W. Stanley Harpole

  5. Institute for Chemistry and Biology of the Marine Environment, Carl-von-Ossietzky University Oldenburg, D-26111 Oldenburg, Germany,

    Helmut Hillebrand

  6. Department of Integrative Biology, University of Guelph, Guelph, Ontario N1G 2W1, Canada,

    Andrew S. MacDougall

  7. Lancaster Environment Centre, Lancaster University, Lancaster LA1 4YQ, UK,

    Carly J. Stevens

  8. School of Environmental and Forest Sciences, University of Washington, Seattle, 98195, Washington, USA

    Jonathan D. Bakker

  9. Australian Research Council Centre of Excellence for Environmental Decisions, School of Biological Sciences, The University of Queensland, Queensland 4072, Australia,

    Yvonne M. Buckley

  10. Department of Zoology, School of Natural Sciences, Trinity College Dublin, Dublin 2, Ireland,

    Yvonne M. Buckley

  11. State Key Laboratory of Grassland and Agro-Ecosystems, Research Station of Alpine Meadow and Wetland Ecosystems, School of Life Sciences, Lanzhou University, Lanzhou 730000, China,

    Chengjin Chu

  12. Department of Biology, MSC03-2020, University of New Mexico, Albuquerque, 87131, New Mexico, USA

    Scott L. Collins

  13. Instituto de Investigaciones Marinas y Costeras (IIMyC) (CONICET-UNMdP), Mar del Plata 7600, Argentina,

    Pedro Daleo

  14. Department of Zoology, University of Wisconsin, Madison, 53706, Wisconsin, USA

    Ellen I. Damschen

  15. Department of Ecology and Evolutionary Biology, University of Colorado, Boulder, 80309, Colorado, USA

    Kendi F. Davies & Brett A. Melbourne

  16. United States Department of Agriculture Agricultural Research Service, Grassland Soil and Water Research Lab, Temple, 76502, Texas, USA

    Philip A. Fay

  17. Queensland University of Technology, School of Biological Sciences, Brisbane 4000, Australia,

    Jennifer Firn

  18. Department of Entomology, University of Maryland, College Park, Maryland 20742, USA,

    Daniel S. Gruner

  19. United States Department of Agriculture Agricultural Research Service, Agroecosystem Management Research Unit, Lincoln, 68583, Nebraska, USA

    Virginia L. Jin

  20. Department of Forest, Rangeland and Watershed Stewardship, Colorado State University, Fort Collins, 80523, Colorado, USA

    Julia A. Klein

  21. School of Biological Sciences, University of Nebraska, Lincoln, 68588, Nebraska, USA

    Johannes M. H. Knops

  22. Berkeley Initiative for Global Change Biology, University of California, Berkeley, 94720, California, USA

    Kimberly J. La Pierre

  23. Yunnan Academy of Biodiversity, Southwest Forestry University, Kunming, 650224, China

    Wei Li

  24. Department of Plant and Soil Sciences, University of Kentucky, Lexington, 40546, Kentucky, USA

    Rebecca L. McCulley

  25. Australian Research Centre for Urban Ecology, Melbourne, c/o School of Botany, University of Melbourne, Victoria 3010, Australia,

    Joslin L. Moore

  26. School of Biological Sciences, Monash University, Victoria 3800, Australia,

    Joslin L. Moore

  27. Department of Zoology, Oregon State University, Corvallis, 97331, Oregon, USA

    Lydia R. O’Halloran

  28. CSIRO Ecosystem Sciences, Wembley, WA 6913, Australia,

    Suzanne M. Prober

  29. Swiss Federal Institute for Forest, Snow and Landscape Research, 8903 Birmensdorf, Switzerland,

    Anita C. Risch & Martin Schuetz

  30. School of Biology, University of Leeds, Leeds LS2 9JT, UK,

    Mahesh Sankaran

  31. National Centre for Biological Sciences, GKVK Campus, Bangalore 560065, India,

    Mahesh Sankaran

  32. Department of Plant Sciences, University of Oxford, Oxford OX1 3RB, UK,

    Andy Hector

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Contributions

E.W.S., E.T.B., W.S.H. and E.M.L. are Nutrient Network coordinators. Y.H. and A.H. developed and framed research questions. Y.H., E.W.S., E.T.B., P.B.A., W.S.H., H.H., A.S.MD., C.J.S., J.D.B., Y.M.B., C.C., S.L.C., E.I.D., K.F.D., P.A.F., J.F., D.S.G., V.L.J., J.A.K., J.M.H.K., K.J.L., W.L., R.L.McC., B.A.M., J.L.M., S.M.P., A.C.R., M.S., M.S. and A.H. collected the data used in this analysis. Y.H. and A.H. analysed the data. E.W.S., E.T.B., H.H., E.M.L., P.D., K.J.L., J.L.M., L.R.O. and M.S. contributed to data analyses. Y.H. and A.H. wrote the paper with input from all authors.

Corresponding author

Correspondence to Yann Hautier.

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Competing interests

The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 1 Locations of the 41 Nutrient Network sites included in this study.

Numbers correspond to the ‘site code’ column in Extended Data Table 1.

Extended Data Figure 2 Effect of fertilization-induced changes in diversity on changes in stability of ANPP and changes in species asynchrony.

a, Changes in stability of ANPP (slope and 95% confidence intervals: 0.009 (−0.048 to 0.030)); b, changes in species asynchrony (0.012 (−0.004 to 0.027)). Neither was related to changes in species richness caused by fertilization. Flat lines represent the overall non-significant mean effects. Nutrient-induced changes were calculated as the average difference per block between fertilized and unmanipulated Nutrient Network plots. Colours correspond to the ‘colour code’ column in Extended Data Table 1. Points are values for individual plots (n = 117).

Extended Data Table 1 Additional information on the 41 Nutrient Network study sites
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Extended Data Table 2 Multiple regression evaluating the influence of plant diversity and key biotic and abiotic factors, productivity and climate, on stability of ANPP in our 41 grasslands
Full size table

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Hautier, Y., Seabloom, E., Borer, E. et al. Eutrophication weakens stabilizing effects of diversity in natural grasslands. Nature 508, 521–525 (2014). https://doi.org/10.1038/nature13014

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