Randomization tests for quantifying species importance to ecosystem function

Authors

  • Nicholas J. Gotelli,

    Corresponding author
    1. Department of Biology, University of Vermont, Burlington, VT 05405, USA
      Correspondence author. E-mail: ngotelli@uvm.edu
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  • Werner Ulrich,

    1. Department of Animal Ecology, Nicolaus Copernicus University in Toruń, Gagarina 9, 87-100 Toruń, Poland
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  • Fernando T. Maestre

    1. Departamento de Biología y Geología, Área de Biodiversidad y Conservación, Escuela Superior de Ciencias Experimentales y Tecnología, Universidad Rey Juan Carlos, 28933 Móstoles, Spain
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Correspondence author. E-mail: ngotelli@uvm.edu

Summary

1. Quantifying the contribution of different species to ecosystem function is an important challenge. We introduce simple randomization tests (and software) for quantifying the average effect of species on ecosystem variables measured in multiple plots with and without the presence of a particular species. These randomization tests formalize the analysis of uncontrolled ‘natural experiments’ and quantify species effects in standardized deviation units.

2. We tested the method with data on ecosystem function in biological soil crust assemblages of lichens in semi-arid gypsum outcrops in central Spain. In sixty-three 50 cm × 50 cm sample plots, we measured the presence and percentage cover of 17 species of lichens and the levels of five important ecosystem variables (organic carbon, total nitrogen, urease activity, phosphatase activity and β-glucosidase activity). The randomization tests revealed 13 positive and six negative associations between species presence and ecosystem function.

3. We used data from an independent microcosm experiment on ecosystem function and species composition to validate these results. Microcosms that had higher levels of organic carbon and total nitrogen also had higher average species effect scores (measured from the survey data) for the species that were present in each experimental treatment.

4. As in all natural experiments, strong species interactions, effects of unmeasured abiotic variables on species occurrence and reciprocal effects of ecosystem variables on species occurrence can potentially confound estimates of species importance. Nevertheless, the method we propose provides a simple index and statistical test of species importance that can form the basis for additional hypothesis tests and experimental studies of species occurrence and ecosystem function.

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