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Optimal lineage principle for age-structured populations. | LitMetric

Optimal lineage principle for age-structured populations.

Evolution

Research Center for Complex Systems Biology, University of Tokyo, 3-8-1 Komaba Meguro-ku Tokyo 153-8902, Japan.

Published: January 2012

AI Article Synopsis

  • This research introduces a new way to analyze age distributions in populations through branching and aging processes, providing fresh insights into classical aging theories.* -
  • The authors establish a variational principle that connects how population growth rates respond to changes in mortality and reproduction with the age distribution along lineages.* -
  • They also explore the Bellman-Harris process, demonstrate its relationship to classical aging, and validate their theories with experimental tests using bacteria in microfluidics.*

Article Abstract

We present a formulation of branching and aging processes that allows age distributions along lineages to be studied within populations, and provides a new interpretation of classical results in the theory of aging. We establish a variational principle for the stable age distribution along lineages. Using this optimal lineage principle, we show that the response of a population's growth rate to age-specific changes in mortality and fecundity--a key quantity that was first calculated by Hamilton--is given directly by the age distribution along lineages. We apply our method also to the Bellman-Harris process, in which both mother and progeny are rejuvenated at each reproduction event, and show that this process can be mapped to the classic aging process such that age statistics in the population and along lineages are identical. Our approach provides both a theoretical framework for understanding the statistics of aging in a population, and a new method of analytical calculations for populations with age structure. We discuss generalizations for populations with multiple phenotypes, and more complex aging processes. We also provide a first experimental test of our theory applied to bacterial populations growing in a microfluidics device.

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Source
http://dx.doi.org/10.1111/j.1558-5646.2011.01418.xDOI Listing

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