Abstract
Evolution drives, and is driven by, demography. A genotype moulds its phenotype’s age patterns of mortality and fertility in an environment; these two patterns in turn determine the genotype’s fitness in that environment. Hence, to understand the evolution of ageing, age patterns of mortality and reproduction need to be compared for species across the tree of life. However, few studies have done so and only for a limited range of taxa. Here we contrast standardized patterns over age for 11 mammals, 12 other vertebrates, 10 invertebrates, 12 vascular plants and a green alga. Although it has been predicted that evolution should inevitably lead to increasing mortality and declining fertility with age after maturity, there is great variation among these species, including increasing, constant, decreasing, humped and bowed trajectories for both long- and short-lived species. This diversity challenges theoreticians to develop broader perspectives on the evolution of ageing and empiricists to study the demography of more species.
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Acknowledgements
We thank S. Alberts for data on baboon demography, J. Curtsinger for data on Drosophila demography and O. Burger, D. Levitis, B. Pietrzak, F. Quade, F. Ringelhan and L. Vinicius for contributing published data about various species. J.W.V. and A.S. acknowledge support from NIH grant PO1 AG-031719. H.C. acknowledges a Research Award from the Alexander von Humboldt Foundation and Advanced Grant 322989 from the European Research Council. R.S.-G. acknowledges support from ARC DP110100727. A.B. acknowledges funding from the Max Planck Society to establish the Max Planck Research Group ‘Modeling the Evolution of Aging’.
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This research project was initiated by J.W.V. A.S. wrote the first draft; O.R.J., with help from A.S., R.S.-G., H.C., A.B. and J.W.V., wrote subsequent drafts; J.W.V. and O.R.J. completed the final draft. The Figure was produced by O.R.J. with suggestions from J.W.V., A.S., A.B. and H.C. A.B. suggested the method of standardization and the distinction between shape and pace. C.G.C. developed methods to smooth mortality and fertility trajectories. H.C. and R.S.-G. contributed to the analysis of stage-classified species. A.S., R.S.-G., O.R.J. and H.C. each provided data, derived from the literature, for several species. R.S. contributed unpublished data for hydra; J.E., J.D. and M.B.G. for Borderea; R.S.-G. and B.B.C. for Cryptantha; and E.M. and P.F.Q.-A. for Hypericum. O.R.J., A.S., R.S.-G. and H.C. screened the species for data quality.
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Extended data figures and tables
Extended Data Figure 1 Standardized mortality trajectories.
a, Trajectories for laboratory rats. b, Trajectories for laboratory mice. Each line represents a different strain, sex or population (see Supplementary Methods for sources). We standardized the age axis to consider the trajectories from age at maturity to the age at which 5% survivorship from maturity occurs. The trajectories were smoothed using P-splines. We then calculated the force of mortality (μx) and standardized it by dividing by the average value, weighted by survivorship from maturity (lx). Note that the sample sizes in most cases were small (approximately 50 to 60 individuals) and thus random fluctuations may lead to erratic curves in some cases.
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41586_2014_BFnature12789_MOESM44_ESM.mp3
In many species mortality increases with age. But that’s not true across the whole tree of life. Digest the demography with authors Owen Jones and Rob Saluero-Gomez.
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Supplementary Information
This file contains Supplementary Methods split into 4 sections: details of each dataset used in analysis; rationale of data set selection given as response to reviewer; description of calculation of age trajectories of mortality/fertility from stage-classified population projection matrices and finally, the computer code. It also contains a Supplementary Note, the analysis of intraspecific variation in standardised mortality trajectories of laboratory rodents and Supplementary References. (PDF 742 kb)
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Jones, O., Scheuerlein, A., Salguero-Gómez, R. et al. Diversity of ageing across the tree of life. Nature 505, 169–173 (2014). https://doi.org/10.1038/nature12789
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DOI: https://doi.org/10.1038/nature12789
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