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A Mixed Model for Assessing the Effect of Numerous Plant Species Interactions on Grassland Biodiversity and Ecosystem Function Relationships

Author

Listed:
  • Jack McDonnell

    (Dundalk Institute of Technology
    Teagasc, Animal and Grassland Research and Innovation Centre, Moorepark
    Maynooth University)

  • Thomas McKenna

    (University of Kansas)

  • Kathryn A. Yurkonis

    (University of North Dakota)

  • Deirdre Hennessy

    (Teagasc, Animal and Grassland Research and Innovation Centre, Moorepark)

  • Rafael Andrade Moral

    (Maynooth University)

  • Caroline Brophy

    (Trinity College Dublin)

Abstract

In grassland ecosystems, it is well known that increasing plant species diversity can improve ecosystem functions (i.e., ecosystem responses), for example, by increasing productivity and reducing weed invasion. Diversity-Interactions models use species proportions and their interactions as predictors in a regression framework to assess biodiversity and ecosystem function relationships. However, it can be difficult to model numerous interactions if there are many species, and interactions may be temporally variable or dependent on spatial planting patterns. We developed a new Diversity-Interactions mixed model for jointly assessing many species interactions and within-plot species planting pattern over multiple years. We model pairwise interactions using a small number of fixed parameters that incorporate spatial effects and supplement this by including all pairwise interaction variables as random effects, each constrained to have the same variance within each year. The random effects are indexed by pairs of species within plots rather than a plot-level factor as is typical in mixed models, and capture remaining variation due to pairwise species interactions parsimoniously. We apply our novel methodology to three years of weed invasion data from a 16-species grassland experiment that manipulated plant species diversity and spatial planting pattern and test its statistical properties in a simulation study.Supplementary materials accompanying this paper appear online.

Suggested Citation

  • Jack McDonnell & Thomas McKenna & Kathryn A. Yurkonis & Deirdre Hennessy & Rafael Andrade Moral & Caroline Brophy, 2023. "A Mixed Model for Assessing the Effect of Numerous Plant Species Interactions on Grassland Biodiversity and Ecosystem Function Relationships," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 28(1), pages 1-19, March.
  • Handle: RePEc:spr:jagbes:v:28:y:2023:i:1:d:10.1007_s13253-022-00505-2
    DOI: 10.1007/s13253-022-00505-2
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    References listed on IDEAS

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    1. Bates, Douglas & Mächler, Martin & Bolker, Ben & Walker, Steve, 2015. "Fitting Linear Mixed-Effects Models Using lme4," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(i01).
    2. Nash, John C. & Varadhan, Ravi, 2011. "Unifying Optimization Algorithms to Aid Software System Users: optimx for R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 43(i09).
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