Volume 11, Issue 6 pp. 940-948

A comparative assessment of univariate longevity measures using zoological animal records

Jacob A. Moorad

Jacob A. Moorad

Department of Biology, Duke University, Durham, NC, USA

Duke Population Research Institute, Duke University, Durham, NC, USA

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Daniel E. L. Promislow

Daniel E. L. Promislow

Department of Genetics, University of Georgia, Athens, GA, USA

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Nate Flesness

Nate Flesness

International Species Information System, Eagan, MN, USA

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Richard A. Miller

Richard A. Miller

Department of Pathology, University of Michigan, School of Medicine, Ann Arbor, MI, USA

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First published: 17 July 2012
Citations: 38
Jacob Moorad, Department of Biology, Duke University, Box 90339, Durham, NC 27708, USA. Tel.: (919) 660 7291; fax: (919) 660 7293; e-mail: [email protected]

Summary

Comparative biogerontology evaluates cellular, molecular, physiological, and genomic properties that distinguish short-lived from long-lived species. These studies typically use maximum reported lifespan (MRLS) as the index with which to compare traits, but there is a general awareness that MRLS is not ideal owing to statistical shortcomings that include bias resulting from small sample sizes. Nevertheless, MRLS has enough species-specific information to show strong associations with many other species-specific traits, such as body mass, stress resistance, and codon usage. The major goal of this study was to see if we could identify surrogate measures with better statistical properties than MRLS but that still capture inter-species differences in extreme lifespan. Using zoological records of 181 bird and mammal species, we evaluated 16 univariate metrics of aging and longevity, including nonparametric quantile-based measures and parameters derived from demographic models of aging, for three desirable statistical properties. We wished to identify those measures that: (i) correlated well with MRLS when the biasing effects of sample size were removed; (ii) correlated weakly with population size; and (iii) were highly robust to the effects of sampling error. Nonparametric univariate descriptors of the distribution of lifespans clearly outperformed the measures derived from demographic analyses. Mean adult lifespan and quantile-based measures, and in particular the 90th quantile of longevity, performed particularly well, demonstrating far less sensitivity to small sample size effects than MRLS while preserving much of the information contained in the maximum lifespan measure. These measures should take the place of MRLS in comparative studies of lifespan.

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