Evol Ecol Res 15: 527-543 (2013) Full PDF if your library subscribes.
Viscous populations evolve altruistic programmed ageing in ability conflict in a changing environment
School of Life Sciences, Nanjing University, Jiangsu, China
Correspondence: J.-N. Yang, School of Life Sciences, Nanjing University, Jiangsu 210093, China.
Questions: Is ageing evolutionarily adaptive? Can programmed ageing widely evolve as altruism in viscous populations (i.e. widely distributed populations with limited offspring dispersal) in a changing environment?
Features of model: The model is individual-based. The probabilities of survival and reproduction are determined by abilities, and abilities increase with both inherited abilities and age-related abilities, so the old can survive and reproduce even if they are genetically less adapted to the environment (termed ‘ability conflict’). Inherited traits are determined by multiple independent loci; thus active ageing can enhance the local accumulation of adaptive inherited abilities in viscous populations.
Ranges of key variables: Dispersal varied from 0 (no dispersal) to 1 (global). The probability of environment-change during each calculation cycle varied from 0 to 1.
Conclusions: Altruistic ageing evolves in structured viscous biological populations with ability conflict in a changing environment to allow the survival of genetically fitter young progenies. To evolve altruistic ageing requires no more environmental change than does sex, suggesting that the generality of altruistic ageing should be no less than sex in viscous populations. If selfish mutants appear only at low rates, higher-level selection would be stabilized even if the environment changes slowly. More extrinsic death can decrease ageing rate (intrinsic death rate) to ensure the same expected lifespan in altruistic ageing, providing testable predictions against traditional ageing theories. My individual-based model also shows how traditional mathematical population genetics largely underestimated the prevalence of group selection.
Keywords: evolvability, genetic creativity, kin selection, longevity, population viscosity, senescence.
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