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Clarifying the effect of biodiversity on productivity in natural ecosystems with longitudinal data and methods for causal inference

Author

Listed:
  • Laura E. Dee

    (University of Colorado)

  • Paul J. Ferraro

    (Johns Hopkins University
    Johns Hopkins University)

  • Christopher N. Severen

    (Federal Reserve Bank of Philadelphia)

  • Kaitlin A. Kimmel

    (University of Colorado)

  • Elizabeth T. Borer

    (University of Minnesota)

  • Jarrett E. K. Byrnes

    (University of Massachusetts Boston)

  • Adam Thomas Clark

    (University of Graz)

  • Yann Hautier

    (Utrecht University)

  • Andrew Hector

    (University of Oxford)

  • Xavier Raynaud

    (Sorbonne Université, Université Paris Cité, UPEC, IRD, CNRS, INRA, Institute of Ecology and Environmental Sciences, iEES Paris)

  • Peter B. Reich

    (University of Michigan
    University of Minnesota
    Western Sydney University)

  • Alexandra J. Wright

    (California State University Los Angeles)

  • Carlos A. Arnillas

    (University of Toronto at Scarborough)

  • Kendi F. Davies

    (University of Colorado)

  • Andrew MacDougall

    (University of Guelph, Guelph)

  • Akira S. Mori

    (The University of Tokyo)

  • Melinda D. Smith

    (Colorado State University
    Colorado State University)

  • Peter B. Adler

    (Utah State University)

  • Jonathan D. Bakker

    (University of Washington)

  • Kate A. Brauman

    (The University of Alabama)

  • Jane Cowles

    (University of Minnesota)

  • Kimberly Komatsu

    (Smithsonian Environmental Research Center)

  • Johannes M. H. Knops

    (Xián Jiaotong-Liverpool University)

  • Rebecca L. McCulley

    (University of Kentucky)

  • Joslin L. Moore

    (Monash University)

  • John W. Morgan

    (La Trobe University)

  • Timothy Ohlert

    (Colorado State University)

  • Sally A. Power

    (Western Sydney University)

  • Lauren L. Sullivan

    (Michigan State University
    Michigan State University)

  • Carly Stevens

    (Lancaster University)

  • Michel Loreau

    (Theoretical and Experimental Ecology Station, CNRS)

Abstract

Causal effects of biodiversity on ecosystem functions can be estimated using experimental or observational designs — designs that pose a tradeoff between drawing credible causal inferences from correlations and drawing generalizable inferences. Here, we develop a design that reduces this tradeoff and revisits the question of how plant species diversity affects productivity. Our design leverages longitudinal data from 43 grasslands in 11 countries and approaches borrowed from fields outside of ecology to draw causal inferences from observational data. Contrary to many prior studies, we estimate that increases in plot-level species richness caused productivity to decline: a 10% increase in richness decreased productivity by 2.4%, 95% CI [−4.1, −0.74]. This contradiction stems from two sources. First, prior observational studies incompletely control for confounding factors. Second, most experiments plant fewer rare and non-native species than exist in nature. Although increases in native, dominant species increased productivity, increases in rare and non-native species decreased productivity, making the average effect negative in our study. By reducing the tradeoff between experimental and observational designs, our study demonstrates how observational studies can complement prior ecological experiments and inform future ones.

Suggested Citation

  • Laura E. Dee & Paul J. Ferraro & Christopher N. Severen & Kaitlin A. Kimmel & Elizabeth T. Borer & Jarrett E. K. Byrnes & Adam Thomas Clark & Yann Hautier & Andrew Hector & Xavier Raynaud & Peter B. R, 2023. "Clarifying the effect of biodiversity on productivity in natural ecosystems with longitudinal data and methods for causal inference," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-37194-5
    DOI: 10.1038/s41467-023-37194-5
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