Literature DB >> 22664576

Trading stages: life expectancies in structured populations.

Ulrich K Steiner1, Shripad Tuljapurkar, Tim Coulson, Carol Horvitz.   

Abstract

Interest in stage-and age structured models has recently increased because they can describe quantitative traits such as size that are left out of age-only demography. Available methods for the analysis of effects of vital rates on lifespan in stage-structured models have not been widely applied because they are hard to use and interpret, and tools for age and stage structured populations are missing. We present easily interpretable expressions for the sensitivities and elasticities of life expectancy to vital rates in age-stage models, and illustrate their application with two biological examples. Much of our approach relies on trading of time and mortality risk in one stage for time and risk in others. Our approach contributes to the new framework of the study of age- and stage-structured biodemography.
Copyright © 2012 Elsevier Inc. All rights reserved.

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Year:  2012        PMID: 22664576      PMCID: PMC3437015          DOI: 10.1016/j.exger.2012.05.015

Source DB:  PubMed          Journal:  Exp Gerontol        ISSN: 0531-5565            Impact factor:   4.032


  21 in total

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2.  Asymmetric segregation of protein aggregates is associated with cellular aging and rejuvenation.

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4.  Patterns of variance in stage-structured populations: evolutionary predictions and ecological implications.

Authors:  C A Pfister
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Review 5.  Biodemographic trajectories of longevity.

Authors:  J W Vaupel; J R Carey; K Christensen; T E Johnson; A I Yashin; N V Holm; I A Iachine; V Kannisto; A A Khazaeli; P Liedo; V D Longo; Y Zeng; K G Manton; J W Curtsinger
Journal:  Science       Date:  1998-05-08       Impact factor: 47.728

6.  Individual histories and selection in heterogeneous populations.

Authors:  Stanislas Leibler; Edo Kussell
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7.  Coupled dynamics of body mass and population growth in response to environmental change.

Authors:  Arpat Ozgul; Dylan Z Childs; Madan K Oli; Kenneth B Armitage; Daniel T Blumstein; Lucretia E Olson; Shripad Tuljapurkar; Tim Coulson
Journal:  Nature       Date:  2010-07-22       Impact factor: 49.962

8.  Exceptional survivors have lower age trajectories of blood glucose: lessons from longitudinal data.

Authors:  Anatoli I Yashin; Konstantin G Arbeev; Igor Akushevich; Svetlana V Ukraintseva; Alexander Kulminski; Liubov S Arbeeva; Irina Culminskaya
Journal:  Biogerontology       Date:  2009-07-31       Impact factor: 4.277

9.  The dynamics of a quantitative trait in an age-structured population living in a variable environment.

Authors:  Tim Coulson; Shripad Tuljapurkar
Journal:  Am Nat       Date:  2008-11       Impact factor: 3.926

10.  Beyond R0: demographic models for variability of lifetime reproductive output.

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  2 in total

1.  Quantifying the effect of genetic, environmental and individual demographic stochastic variability for population dynamics in Plantago lanceolata.

Authors:  Ulrich K Steiner; Shripad Tuljapurkar; Deborah A Roach
Journal:  Sci Rep       Date:  2021-11-30       Impact factor: 4.379

2.  Poverty dynamics, poverty thresholds and mortality: An age-stage Markovian model.

Authors:  Shayna Fae Bernstein; David Rehkopf; Shripad Tuljapurkar; Carol C Horvitz
Journal:  PLoS One       Date:  2018-05-16       Impact factor: 3.240

  2 in total

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