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The Use of the Evenness of Eigenvalues of Similarity Matrices to Test for Predictivity of Ecosystem Classifications

Author

Listed:
  • Enrico Feoli

    (Department of Life Sciences, University of Trieste, 34127 Trieste, Italy)

  • Paola Ganis

    (Department of Life Sciences, University of Trieste, 34127 Trieste, Italy)

Abstract

The use of the evenness ( E ( λ )) of the eigenvalues of similarity matrices corresponding to different hierarchical levels of ecosystem classifications, is suggested to test correlation (or predictivity) between biological communities and environmental factors as one alternative of analysis of variance (parametric or non-parametric). The advantage over traditional methods is the fact that similarity matrices can be obtained from any kind of data (mixed and missing data) by indices such as those of Goodall and Gower. The significance of E ( λ ) is calculated by permutation techniques. One example of application of E ( λ ) is given by a data set describing plant community types (beech forests of the Italian peninsula).

Suggested Citation

  • Enrico Feoli & Paola Ganis, 2019. "The Use of the Evenness of Eigenvalues of Similarity Matrices to Test for Predictivity of Ecosystem Classifications," Mathematics, MDPI, vol. 7(3), pages 1-6, March.
    • Handle: RePEc:gam:jmathe:v:7:y:2019:i:3:p:245-:d:212483
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    Cited by:

    1. Natalya Ivanova & Ekaterina Zolotova, 2023. "Landolt Indicator Values in Modern Research: A Review," Sustainability, MDPI, vol. 15(12), pages 1-22, June.

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