Researches on Population Ecology

, Volume 41, Issue 2, pp 203–215 | Cite as

A comparison of species diversity estimators

  • D. Mouillot
  • Alain Leprêtre
Original Article


Although having been much criticized, diversity indices are still widely used in animal and plant ecology to evaluate, survey, and conserve ecosystems. It is possible to quantify biodiversity by using estimators for which statistical characteristics and performance are, as yet, poorly defined. In the present study, four of the most frequently used diversity indices were compared: the Shannon index, the Simpson index, the Camargo eveness index, and the Pielou regularity index. Comparisons were performed by simulating the Zipf–Mandelbrot parametric model and estimating three statistics of these indices, i.e., the relative bias, the coefficient of variation, and the relative root-mean-squared error. Analysis of variance was used to determine which of the factors contributed most to the observed variation in the four diversity estimators: abundance distribution model or sample size. The results have revealed that the Camargo eveness index tends to demonstrate a high bias and a large relative root-mean-squared error whereas the Simpson index is least biased and the Shannon index shows a smaller relative root-mean-squared error, regardless of the abundance distribution model used and even when sample size is small. Shannon and Pielou estimators are sensitive to changes in species abundance pattern and present a nonnegligible bias for small sample sizes (<1000 individuals).

Key words: Diversity indices Estimator performances Simulation 


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Copyright information

© The Society of Population Ecology and Springer-Verlag Tokyo 1999

Authors and Affiliations

  • D. Mouillot
    • 1
  • Alain Leprêtre
    • 2
  1. 1.Laboratoire d'Ecologie Méditerranéenne, Université de Corse, BP 52, 20250 Corte, France Tel. +33-04 95 45 00 29; Fax +33-04 95 61 05 51 e-mail: Office de l'Environnement de la Corse, FranceFR
  2. 2.Laboratoire d'Ecologie Numérique (UPRES A 8013 CNRS ELICO), Université Lille I, FranceFR

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