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A new metric of inclusive fitness predicts the human mortality profile

Newman, Saul J.; Easteal, Simon

Description

Biological species have evolved characteristic patterns of age-specific mortality across their life spans. If these mortality profiles are shaped by natural selection they should reflect underlying variation in the fitness effect of mortality with age. Direct fitness models, however, do not accurately predict the mortality profiles of many species. For several species, including humans, mortality rates vary considerably before and after reproductive ages, during life-stages when no variation in...[Show more]

dc.contributor.authorNewman, Saul J.
dc.contributor.authorEasteal, Simon
dc.date.accessioned2015-05-27T05:02:41Z
dc.date.available2015-05-27T05:02:41Z
dc.identifier.issn1932-6203
dc.identifier.urihttp://hdl.handle.net/1885/13613
dc.description.abstractBiological species have evolved characteristic patterns of age-specific mortality across their life spans. If these mortality profiles are shaped by natural selection they should reflect underlying variation in the fitness effect of mortality with age. Direct fitness models, however, do not accurately predict the mortality profiles of many species. For several species, including humans, mortality rates vary considerably before and after reproductive ages, during life-stages when no variation in direct fitness is possible. Variation in mortality rates at these ages may reflect indirect effects of natural selection acting through kin. To test this possibility we developed a new two-variable measure of inclusive fitness, which we term the extended genomic output or EGO. Using EGO, we estimate the inclusive fitness effect of mortality at different ages in a small hunter-gatherer population with a typical human mortality profile. EGO in this population predicts 90% of the variation in age-specific mortality. This result represents the first empirical measurement of inclusive fitness of a trait in any species. It shows that the pattern of human survival can largely be explained by variation in the inclusive fitness cost of mortality at different ages. More generally, our approach can be used to estimate the inclusive fitness of any trait or genotype from population data on birth dates and relatedness.
dc.format8 pages
dc.publisherPublic Library of Science
dc.rights© 2015 Newman, Easteal. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
dc.sourcePLOS ONE
dc.titleA new metric of inclusive fitness predicts the human mortality profile
dc.typeJournal article
local.identifier.citationvolume10
dcterms.dateAccepted2014-12-17
dc.date.issued2015-01-21
local.identifier.absfor060400 - GENETICS
local.identifier.absfor110300 - CLINICAL SCIENCES
local.identifier.ariespublicationa383154xPUB917
local.publisher.urlhttps://www.plos.org/
local.type.statusPublished Version
local.contributor.affiliationNewman, S. J., John Curtin School of Medical Research, The Australian National University
local.contributor.affiliationJEasteal, S., John Curtin School of Medical Research, The Australian National University
local.identifier.essn1932-6203
local.bibliographicCitation.issue1
local.bibliographicCitation.startpagee0117019
local.bibliographicCitation.lastpage8
local.identifier.doi10.1371/journal.pone.0117019
dc.date.updated2015-12-10T09:37:30Z
local.identifier.scopusID2-s2.0-84921802160
CollectionsANU Research Publications

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