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The long-run moulding of senescence

Authors: Bahry, David;

The long-run moulding of senescence

Abstract

Senescence (ageing) evolves because natural selection cases less about late life than early life. Hamilton formalized this in terms of the sensitivities of the intrinsic rate of increase, a measure of fitness appropriate for density-independent age-structured populations, to small additive changes in mortality or fecundity rates; the framework can also be adjusted to alternative genetic and ecological assumptions. However, any age-specific force of selection is itself a function of the age-structured life history, meaning that as the life history evolves, the forces of selection evolve too; this raises the challenge of how to model evolution beyond the short term. This paper addresses long-run life history evolution by considering two simple evolutionary models, and for each, deriving equilibrium conditions that a life history must fulfill in order to no longer be evolving. The results shed further light on topics in the evolution of senescence, including high juvenile mortality and models predicting “catastrophic senescence.” A key conclusion is that the models have different, mutually exclusive equilibrium conditions, highlighting how the evolution of senescence depends not only on the forces of selection but also on the available genetic variation. Based on (Bahry, 2022, MSc thesis). v1: draft preprint; no supplementary material included. v2: added axis labels to Fig. 2; removed a stray minus sign from eqn. 2b

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green