Addition of multiple limiting resources reduces grassland diversity

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Niche dimensionality provides a general theoretical explanation for biodiversity—more niches, defined by more limiting factors, allow for more ways that species can coexist1. Because plant species compete for the same set of limiting resources, theory predicts that addition of a limiting resource eliminates potential trade-offs, reducing the number of species that can coexist2. Multiple nutrient limitation of plant production is common and therefore fertilization may reduce diversity by reducing the number or dimensionality of belowground limiting factors. At the same time, nutrient addition, by increasing biomass, should ultimately shift competition from belowground nutrients towards a one-dimensional competitive trade-off for light3. Here we show that plant species diversity decreased when a greater number of limiting nutrients were added across 45 grassland sites from a multi-continent experimental network4. The number of added nutrients predicted diversity loss, even after controlling for effects of plant biomass, and even where biomass production was not nutrient-limited. We found that elevated resource supply reduced niche dimensionality and diversity and increased both productivity5 and compositional turnover. Our results point to the importance of understanding dimensionality in ecological systems that are undergoing diversity loss in response to multiple global change factors.

At a glance


  1. Biodiversity and number of resources.
    Figure 1: Biodiversity and number of resources.

    a, Loss of species diversity with greater number of added resources (effective number of equally abundant species: ESNPIE); this effect increased with years of treatment 1–8 (Extended Data Table 1); year 0 shows pre-treatment diversity. Bold lines show overall mean responses of 45 sites; y axis is log-transformed. b, Greater number of added resources increased the mean rates of diversity loss per year (filled points; F1,134 = 24.8, P < 0.0001), and the proportional loss of species relative to the controls, shown as the effect size (open points; F1,134 = 46.2, P < 0.0001). c, Rate of diversity loss per added resource (nres) was associated with greater total site species number (log), R2 = 0.25, P = 0.0004, n = 45). Error bars show mean ± 95% confidence intervals.

  2. Biomass and light.
    Figure 2: Biomass and light.

    a, The rate of live biomass change per year increased with an increasing number of added resources (F1,1031 = 55.0, P < 0.0001). b, The proportion of photosynthetically active radiation (PAR) reaching the ground surface decreased with a greater number of added resources, expressed as annual rate of change (F1,782 = 62.4, P < 0.0001). c, The mean rate of litter (dead biomass) change per year increased with the number of added resources (F1,783 = 4.37, P = 0.037). Error bars show mean ± 95% confidence intervals.

  3. Multiple resource limitation.
    Figure 3: Multiple resource limitation.

    a, Increased number of added resources resulted in positive and increasing biomass at sites showing multiple resource limitation (filled points); sites not limited by multiple resources tended to show negative biomass responses with resource addition (open points). b, Increased number of added resources drove similar diversity loss at sites where biomass production was limited by multiple resources (filled points) and at sites where it was not (open points). c, Negative relationship between the effect of addition of three resources on biomass and diversity (one-tailed test for negative relationship, R2 = 0.11, P = 0.012, n = 45). Error bars show mean ± s.e.

  4. Community composition.
    Figure 4: Community composition.

    a, Community composition diverged from control plots with greater number of added resources (Bray–Curtis dissimilarity index). Resource addition caused greater dissimilarity of community composition relative to mean pre-treatment dissimilarity, indicated by grey stars. b, Addition of single nutrient additions of N, P or K resulted in communities that diverged as much from each other as they did on average from the control plots. Pre-treatment values indicated by grey stars. c, Negative relationship between the effect of addition of three resources on community dissimilarity relative to controls and diversity (one-tailed test for negative relationship, R2 = 0.10, P = 0.019, n = 45). Error bars indicate mean ± 95% confidence intervals.


  1. The effects of nutrient addition on diversity loss and richness loss increase with time
    Extended Data Table 1: The effects of nutrient addition on diversity loss and richness loss increase with time
  2. The number of added resources predicts diversity loss after controlling for other variables
    Extended Data Table 2: The number of added resources predicts diversity loss after controlling for other variables
  3. The number of added resources is an important predictor even after controlling for other variables, for sites that had light and litter data
    Extended Data Table 3: The number of added resources is an important predictor even after controlling for other variables, for sites that had light and litter data
  4. Diversity loss due to addition of nutrients associated with soil properities
    Extended Data Table 4: Diversity loss due to addition of nutrients associated with soil properities


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Author information


  1. Department of Physiological Diversity, Helmholtz Center for Environmental Research – UFZ, Permoserstrasse 15, Leipzig 04318, Germany

    • W. Stanley Harpole
  2. German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, Leipzig 04103, Germany

    • W. Stanley Harpole &
    • Jonathan Chase
  3. Institute of Biology, Martin Luther University Halle-Wittenberg, Am Kirchtor 1, Halle (Saale) 06108, Germany

    • W. Stanley Harpole &
    • Jonathan Chase
  4. Department of Ecology, Evolution, and Behavior, University of Minnesota, St Paul, Minnesota 55108, USA

    • Lauren L. Sullivan,
    • Eric M. Lind,
    • Elizabeth T. Borer &
    • Eric W. Seabloom
  5. School of Earth, Environment and Biological Sciences, Queensland University of Technology, Brisbane, Queensland 4001, Australia

    • Jennifer Firn
  6. Department of Wildland Resources and the Ecology Center, Utah State University, Logan, Utah 84322, USA

    • Peter B. Adler
  7. USDA-ARS Grassland Soil and Water Research Lab, Temple, Texas 76502, USA

    • Philip A. Fay
  8. Ecology and Biodiversity Group, Department of Biology, Utrecht University, Padualaan 8, Utrecht, CH 3584, The Netherlands

    • Yann Hautier
  9. Institute for Chemistry and Biology of the Marine Environment, University of Oldenburg, Schleusenstrasse 1, Wilhelmshaven, D-26381, Germany

    • Helmut Hillebrand
  10. Department of Integrative Biology, University of Guelph, Guelph, Ontario N1G 2W1, Canada

    • Andrew S. MacDougall
  11. Agricultural and Biosystems Engineering, Iowa State University, Ames, Iowa 50011, USA

    • Ryan Williams
  12. School of Environmental and Forest Sciences, University of Washington, Seattle, Washington 98195, USA

    • Jonathan D. Bakker
  13. Department of Biological Sciences, University of Toronto – Scarborough, 1265 Military trail, Toronto, Ontario M1C 1A4, Canada

    • Marc W. Cadotte
  14. IFEVA/CONICET – Departamento de Recursos Naturales y Ambiente, Facultad de Agronomía, Universidad de Buenos Aires. Av. San Martín 4453 (C1417DSE) Buenos Aires, Argentina

    • Enrique J. Chaneton
  15. SYSU-Alberta Joint Lab for Biodiversity Conservation, State Key Laboratory of Biocontrol and School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, China

    • Chengjin Chu
  16. Ecology, Behavior & Evolution Section, University of California, La Jolla, San Diego, California 92093, USA

    • Elsa E. Cleland
  17. Department of Ecology, Evolution and Marine Biology, University of California, Santa Barbara, California 93106-9620 USA

    • Carla D’Antonio
  18. Department of Ecology and Evolutionary Biology, University of Colorado, Boulder, Colorado 80309, USA

    • Kendi F. Davies
  19. Department of Entomology, University of Maryland, College Park, Maryland 20742, USA

    • Daniel S. Gruner
  20. School of Life Sciences, University of KwaZulu-Natal, Pietermaritzburg 3209, South Africa

    • Nicole Hagenah &
    • Kevin Kirkman
  21. School of Biological Sciences, University of Nebraska, Lincoln, Nebraska 68588, USA

    • Johannes M. H. Knops
  22. Department of Integrative Biology, University of California, Berkeley, California 94720, USA

    • Kimberly J. La Pierre
  23. Department of Plant and Soil Sciences, University of Kentucky, Lexington, Kentucky 40546, USA

    • Rebecca L. McCulley
  24. School of Biological Sciences, Monash University, Victoria 3800, Australia

    • Joslin L. Moore
  25. Department of Ecology, Environment and Evolution, La Trobe University, Bundoora, Victoria 3086, Australia

    • John W. Morgan
  26. CSIRO Land and Water, Private Bag 5, Wembley, Western Australia 6913, Australia

    • Suzanne M. Prober
  27. Swiss Federal Institute for Forest, Snow and Landscape Research, Community Ecology, Birmensdorf 8903, Switzerland

    • Anita C. Risch &
    • Martin Schuetz
  28. Lancaster Environment Centre, Lancaster University, Lancaster LA1 4YQ, UK

    • Carly J. Stevens
  29. Department of Ecology & Evolutionary Biology, Yale University, 165 Prospect Street, New Haven, Connecticut 06511, USA

    • Peter D. Wragg


W.S.H. analysed the data and wrote the paper with contributions and input from all authors. L.L.S., E.M.L. and J.F. contributed to data analysis. W.S.H., E.W.S. and E.T.B. developed and framed the research questions. W.S.H., E.W.S., E.T.B. and E.M.L. are Nutrient Network coordinators. All authors collected data used in this analysis. Author contribution matrix provided as Supplementary Table 2.

Competing financial interests

The authors declare no competing financial interests.

Corresponding author

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Reviewer Information Nature thanks J. Levine, B. Schmid and the other anonymous reviewer(s) for their contribution to the peer review of this work.

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    This file contains Supplementary Tables 1-2.

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