Shannon diversity index: a call to replace the original Shannon’s formula with unbiased estimator in the population genetics studies

Abstract

Background The Shannon diversity index has been widely used in population genetics studies. Recently, it was proposed as a unifying measure of diversity at different levels—from genes and populations to whole species and ecosystems. The index, however, was proven to be negatively biased at small sample sizes. Modifications to the original Shannon’s formula have been proposed to obtain an unbiased estimator. Methods In this study, the performance of four different estimators of Shannon index—the original Shannon’s formula and those of Zahl, Chao and Shen and Chao et al.—was tested on simulated microsatellite data. Both the simulation and analysis of the results were performed in the R language environment. A new R function was created for the calculation of all four indices from the genind data format. Results Sample size dependence was detected in all the estimators analysed; however, the deviation from parametric values was substantially smaller in the derived measures than in the original Shannon’s formula. Error rate was negatively associated with population heterozygosity. Comparisons among loci showed that fast-mutating loci were less affected by the error, except for the original Shannon’s estimator which, in the smallest sample, was more strongly affected by loci with a higher number of alleles. The Zahl and Chao et al. estimators performed notably better than the original Shannon’s formula. Conclusion The results of this study show that the original Shannon index should no longer be used as a measure of genetic diversity and should be replaced by Zahl’s unbiased estimator.

A Meta-Analytical Investigation of the Gap between Measured and Predicted Inter-Population Genetic Diversity in Species of High Conservation Concern—The Case of the Critically Endangered European Mink Mustela lutreola L., 1761

“…Additionally, the Shannon-Wiener index, originally adopted as a measure of the biodiversity, is widely used in population genetic studies. It should be pointed out that its use to measure genetic diversity is sometimes questioned as being negatively biased at small sample sizes [15]. However, due to the comparative nature of the analyses in this work, the possible influence of the sample size on the result basically confirms our interpretation, additionally pointing to the advisability of more detailed studies of the SE population (as indicated by the results of the jackknife analysis).…”

“…Another strategy is multiple sampling; however, in most cases, only a single sample from a population is taken, without accounting for sampling uncertainty [11]. Finally, sampling schemes can be validated ex post, by utilizing methods such as jackknifing [12], the Good-Turing frequency estimation [13], regression models [14], or rarefaction analysis [1], to account for unsampled (unmeasured) alleles or haplotypes [15]. Such approaches mainly aim to inform future sampling design [4].…”

Transferability of ISSR, SCoT and SSR Markers for Chrysanthemum × Morifolium Ramat and Genetic Relationships Among Commercial Russian Cultivars

“…According to our results, the standard deviations of the mean h were too high, indicating that h should be assessed separately by each marker rather than by the average of all the markers. In addition, these results confirmed that the genetic diversity parameters are more dependent on the size and content of the analysed dataset rather than the marker type [ 43 , 44 ]. This could be a reason why this parameter has not been correlated with the polymorphism of the marker.…”

Comparison of four species diversity indices in mangrove community

“…It's true to argue that dominant species influence the Simpson index and the chances of species similarity in a community so high dominance or chances of two individuals in the same species indicate low species diversity Simpson (1949). The same arguments by Daly et al (2018) indicated that the Shannon index is insensitive to rare species and highly biased on a small sample size (Konopiński 2020). It is reliable in measuring species abundance with individual distribution dominated by common species (Magurran 2004).…”

“…Different indices indeed allow quantifying different facets, mainly species number, evenness, or more complex variations considering taxonomic, phylogenetic, and/or functional differences between species (Meynard et al 2011;Pavoine 2012;Granger et al 2015). Menhinick,Shannon, indices are good bird and copepod taxa measures in various communities or locations (Heip and Engels 1974;Hubalek 2000;Goudarzian and Evanirfad 2017;Konopiński 2020;Tinio and Sebual 2021). Even According to Garcia et al (2015), the Simpson Index (1-D) is the most useful to define which regions have a greater diversity of ecosystems compared to them.…”