Diversity analysis: Richness versus evenness
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Published on: October 25, 2011
1Department of Mechanical Engineering and Department of Industrial and Systems Engineering University of Minnesota Minneapolis Minnesota USA.
Abstract:
Richness and evenness, two important components of diversity, have been the subject of numerous studies exploring their potential dependence or lack thereof. The results have been contradictory and inconclusive, but tending to indicate only a low (positive or negative) correlation. While such reported studies have been based on particular data sets and species abundance distributions, the present article provides the results of a study using randomly generated abundance distributions and hence more generalizable findings and valid statistical results. The results reveal no statistically significant correlation between richness and evenness based on such random sample of abundance distributions and on four well-known measures of diversity, including Simpson's indices and the entropy index. Of the two diversity components, evenness is found to have the strongest influence on diversity, but for numbers-equivalent or effective-number formulations, richness tends to be the most influential diversity component. For analyzing the tradeoff between richness and evenness for any given diversity measure and abundance distribution, the richness-evenness curve is introduced as a new tool for diversity analysis.
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