Hostname: page-component-78c5997874-4rdpn Total loading time: 0 Render date: 2024-11-17T02:46:18.178Z Has data issue: false hasContentIssue false

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: john.alroy@mq.edu.au

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

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

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

References

Alroy, J. 2008. Dynamics of origination and extinction in the marine fossil record. Proceedings of the National Academy of Sciences USA 105:1153611542.10.1073/pnas.0802597105CrossRefGoogle ScholarPubMed
Alroy, J. 2009. A deconstruction of Sepkoski's Phanerozoic marine evolutionary faunas based on new diversity estimates. Geological Society of America Abstracts with Programs 41:507.Google Scholar
Alroy, J. 2010a. Geographic, environmental and intrinsic biotic controls on Phanerozoic marine diversification. Palaeontology 53:12111235.10.1111/j.1475-4983.2010.01011.xCrossRefGoogle Scholar
Alroy, J. 2010b. The shifting balance of diversity among major marine animal groups. Science 329:11911194.10.1126/science.1189910CrossRefGoogle Scholar
Alroy, J. 2014. Accurate and precise estimates of origination and extinction rates. Paleobiology 40:374397.10.1666/13036CrossRefGoogle Scholar
Alroy, J. 2015. The shape of terrestrial abundance distributions. Science Advances 1:e1500082.CrossRefGoogle ScholarPubMed
Alroy, J. 2017. Effects of habitat disturbance on tropical forest biodiversity. Proceedings of the National Academy of Sciences USA 114:60566061.10.1073/pnas.1611855114CrossRefGoogle ScholarPubMed
Alroy, J. 2018. Limits to species richness in terrestrial communities. Ecology Letters 21:17811789.CrossRefGoogle ScholarPubMed
Bapst, D. W. 2013. A stochastic rate-calibrated method for time-scaling phylogenies of fossil taxa. Methods in Ecology and Evolution 4:724733.10.1111/2041-210X.12081CrossRefGoogle Scholar
Bradford, M. G., Murphy, H. T., Ford, A. J., Hogan, D., and Metcalfe, D. J.. 2014. Long-term stem inventory data from tropical rain forest plots in Australia. Ecology 95:2362.CrossRefGoogle Scholar
Bunge, J., Willis, A., and Walsh, F.. 2014. Estimating the number of species in microbial diversity studies. Annual Review of Statistics and Its Application 1:427445.10.1146/annurev-statistics-022513-115654CrossRefGoogle Scholar
Burnham, K. P., and Overton, W. S.. 1978. Estimation of the size of a closed population when capture probabilities vary among animals. Biometrika 65:625633.CrossRefGoogle Scholar
Buzas, M. A., Koch, C. F., Culver, S. J., and Sohl, N. F.. 1982. On the distribution of species occurrence. Paleobiology 8:143150.10.1017/S0094837300004486CrossRefGoogle Scholar
Chao, A. 1984. Non-parametric estimation of the number of classes in a population. Scandinavian Journal of Statistics 11:265270.Google Scholar
Chao, A., and Jost, L.. 2012. Coverage-based rarefaction and extrapolation: standardizing samples for completeness rather than size. Ecology 93:25332547.CrossRefGoogle ScholarPubMed
Chao, A., and Shen, T. J.. 2010. Program SPADE: Species prediction and diversity estimation. Program and user's guide. CARE, Hsin-Chu, Taiwan.Google Scholar
Close, R. A., Evers, S. W., Alroy, J., and Butler, R. J.. 2018. How should we estimate diversity in the fossil record? Testing richness estimators using sampling-standardised discovery curves. Methods in Ecology and Evolution 9:13861400.CrossRefGoogle Scholar
Colwell, R. K., and Coddington, J. A.. 1994. Estimating terrestrial biodiversity through extrapolation. Philosophical Transactions of the Royal Society of London B 345:101119.Google ScholarPubMed
Ezard, T. G., Quental, T B., and Benton, M. J.. 2016. The challenges to inferring the regulators of biodiversity in deep time. Philosophical Transactions of the Royal Society of London B 371:20150216.10.1098/rstb.2015.0216CrossRefGoogle ScholarPubMed
Fisher, D. C. 1988. Stratocladistics: integrating stratigraphic and morphologic data in phylogenetic inference. Geological Society of America Abstracts with Programs 20:A186.Google Scholar
Foote, M., and Raup, D. M.. 1996. Fossil preservation and the stratigraphic ranges of taxa. Paleobiology 22:121140.10.1017/S0094837300016134CrossRefGoogle ScholarPubMed
Good, I. J. 1953. The population frequencies of species and the estimation of population parameters. Biometrika 40:237264.CrossRefGoogle Scholar
Heck, K. L. Jr., van Belle, G., and Simberloff, D.. 1975. Explicit calculation of the rarefaction diversity measurement and the determination of sufficient sample size. Ecology 56:14591461.CrossRefGoogle Scholar
Hill, M. O. 1973. Diversity and evenness: a unifying notation and its consequences. Ecology 54:427432.CrossRefGoogle Scholar
Hunt, G., and Slater, G.. 2016. Integrating paleontological and phylogenetic approaches to macroevolution. Annual Review of Ecology, Evolution, and Systematics 47:189213.CrossRefGoogle Scholar
Hurlbert, S. H. 1971. The nonconcept of species diversity: a critique and alternative parameters. Ecology 52:577586.CrossRefGoogle Scholar
Kvålseth, T. 2015. Evenness indices once again: critical analysis of properties. SpringerPlus 4:232.CrossRefGoogle ScholarPubMed
May, R. M. 1975. Patterns of species abundance and diversity. Pp. 81120in Cody, M. L. and Diamond, J. M., eds. Ecology and evolution of communities. Belknap Press, Cambridge, Mass.Google Scholar
Mitchell, J. S. 2015. Preservation is predictable: quantifying the effect of taphonomic biases on ecological disparity in birds. Paleobiology 41:353367.CrossRefGoogle Scholar
Pielou, E. C. 1966. The measurement of diversity in different types of biological collections. Journal of Theoretical Biology 13:131144.10.1016/0022-5193(66)90013-0CrossRefGoogle Scholar
Raup, D. M. 1972. Taxonomic diversity during the Phanerozoic. Science 177:10651071.CrossRefGoogle ScholarPubMed
Sanders, H. L. 1968. Marine benthic diversity: a comparative study. American Naturalist 102:243282.CrossRefGoogle Scholar
Simpson, E. H. 1949. The measurement of diversity. Nature 163:688.CrossRefGoogle Scholar
Smith, B., and Wilson, J. B.. 1996. A consumer's guide to evenness indices. Oikos 76:7082.CrossRefGoogle Scholar
Stadler, T. 2010. Sampling-through-time in birth-death trees. Journal of Theoretical Biology 267:396404.10.1016/j.jtbi.2010.09.010CrossRefGoogle ScholarPubMed
Stadler, T., Gavryushkina, A., Warnock, R. C. M., Drummond, A. J., and Heath, T. A.. 2018. The fossilized birth-death model for the analysis of stratigraphic range data under different speciation modes. Journal of Theoretical Biology 447:4155.CrossRefGoogle ScholarPubMed
Starrfelt, J., and Liow, L. H.. 2016. How many dinosaur species were there? Fossil bias and true richness estimated using a Poisson sampling model. Philosophical Transactions of the Royal Society of London B 371:20150219.CrossRefGoogle ScholarPubMed
Wagner, P. J. 1998. A likelihood approach for evaluating estimates of phylogenetic relationships among fossil taxa. Paleobiology 24:430449.10.1017/S0094837300020091CrossRefGoogle Scholar
Wagner, P. J., and Marcot, J. D.. 2013. Modelling distributions of fossil sampling rates over time, space and taxa: assessment and implications for macroevolutionary studies. Methods in Ecology and Evolution 4:703713.CrossRefGoogle Scholar