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dc.contributor.authorAraya-Ajoy, Yimen
dc.contributor.authorBolstad, Geir Hysing
dc.contributor.authorBrommer, Jon
dc.contributor.authorCareau, Vincent
dc.contributor.authorDingemanse, Niels J.
dc.contributor.authorWright, Jonathan
dc.date.accessioned2018-11-19T10:09:58Z
dc.date.available2018-11-19T10:09:58Z
dc.date.created2018-07-06T12:14:10Z
dc.date.issued2018
dc.identifier.citationBehavioral Ecology and Sociobiology. 2018, 72:75 (5), 1-14.nb_NO
dc.identifier.issn0340-5443
dc.identifier.urihttp://hdl.handle.net/11250/2573394
dc.description.abstractComparative analyses have demonstrated the existence of a ^pace-of-life^ (POL) continuum of life-history strategies, from fastreproducing short-lived species to slow-reproducing long-lived species. This idea has been extended to the concept of a ^pace-oflife syndrome^ (POLS), an axis of phenotypic covariation among individuals within species, concerning morphological, physiological, behavioral and life-history traits. Several life-history metrics can be used to place species in the fast-slow continuum; here, we asked whether individual variation in POL can also be studied using similar life-history measures. We therefore translated measures commonly used in demographic studies into individual-level estimates.We studied fecundity rate, generation time, lifespan, age at first reproduction, fecundity at first reproduction, and principal component scores integrating these different metrics. Using simulations, we show how demographic stochasticity and individual variation in resources affect the ability to predict an individual’s POL using these individual-level parameters.We found that their accuracy depends on how environmental stochasticity varies with the species’ position on the fast-slow continuumand with the amount of (co)variation in life-history traits caused by individual differences in resources. These results highlight the importance of studying the sources of life-history covariation to determine whether POL explains the covariation between morphological, physiological, and behavioral traits within species. Our simulations also show that quantifying not only among-individual but also among-population patterns of lifehistory covariation helps in interpreting demographic estimates in the study of POLSs within species.nb_NO
dc.language.isoengnb_NO
dc.titleDemographic measures of an individual's "pace of life": fecundity rate, lifespan, generation time, or a composite variable?nb_NO
dc.title.alternativeDemographic measures of an individual's "pace of life": fecundity rate, lifespan, generation time, or a composite variable?nb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionacceptedVersionnb_NO
dc.rights.holder© Springer-Verlag GmbH Germany, part of Springer Nature 2018nb_NO
dc.subject.nsiVDP::Zoologiske og botaniske fag: 480nb_NO
dc.subject.nsiVDP::Zoology and botany: 480nb_NO
dc.source.pagenumber1-14nb_NO
dc.source.volume72:75nb_NO
dc.source.journalBehavioral Ecology and Sociobiologynb_NO
dc.source.issue5nb_NO
dc.identifier.doi10.1007/s00265-018-2477-7
dc.identifier.cristin1596100
dc.relation.projectAndre: European Research Council (ERC-2010-AdG 268,562)nb_NO
dc.relation.projectNorges forskningsråd: 223257nb_NO
cristin.unitcode7511,3,0,0
cristin.unitnameAvdeling for akvatisk økologi
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1


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