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On four measures of taxonomic richness

Published online by Cambridge University Press:  16 March 2020

John Alroy*
Affiliation:
Department of Biological Sciences, Macquarie University, New South Wales, Australia. E-mail: [email protected]

Abstract

The choice of measures used to estimate the richness of species, genera, or higher taxa is a crucial matter in paleobiology and ecology. This paper evaluates four methods called shareholder quorum subsampling, true richness estimated using a Poisson sampling model (TRiPS), squares, and the corrected first-order jackknife (cJ1). Quorum subsampling interpolates to produce a relative richness estimate, while the other three extrapolate to the size of the overall species pool. Here I use routine ecological data to show that squares and cJ1 pass several basic validation tests, but TRiPS does not. First, TRiPS estimates are insensitive to the shape of abundance distributions, being entirely predicted by total counts of species and of individuals regardless of the details. Furthermore, TRiPS tends not to extrapolate at all when sampling is moderate or intense. Second, all three extrapolators yield lower values when they work with small uniform subsamples of large raw inventories. The third test is a split-analyze-and-sum analysis: each inventory is divided between the most common and least common halves of the abundance distribution, the methods are applied to the half-inventories, and the estimates are summed. Squares and cJ1 perform well here, but TRiPS does not extrapolate as long as the full inventories are reasonably well-sampled. It is otherwise not particularly accurate. The extrapolators are largely insensitive to the influence of abundance distribution evenness, as quantified using Pielou's J and a new index called the ratio of means. Quorum subsampling generally performs well, but it stumbles on the split-analyze-and-sum test and is confounded somewhat by evenness.

Type
Articles
Copyright
Copyright © 2020 The Paleontological Society. All rights reserved

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Footnotes

Data available from the Dryad Digital Repository: https://doi.org/10.5061/dryad.86922

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