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Beyond fitness: The information imparted in population states by selection throughout lifecycles

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  • Smith, Eric

Abstract

We approach the questions, what part of evolutionary change results from selection, and what is the adaptive information flow into a population undergoing selection, as a problem of quantifying the divergence of typical trajectories realized under selection from the expected dynamics of their counterparts under a null stochastic-process model representing the absence of selection. This approach starts with a formulation of adaptation in terms of information and from that identifies selection from the genetic parameters that generate information flow; it is the reverse of a historical approach that defines selection in terms of fitness, and then identifies adaptive characters as those amplified in relative frequency by fitness. Adaptive information is a relative entropy on distributions of histories computed directly from the generators of stochastic evolutionary population processes, which in large population limits can be approximated by its leading exponential dependence as a large-deviation function. We study a particular class of generators that represent the genetic dependence of explicit transitions around reproductive cycles in terms of stoichiometry, familiar from chemical reaction networks. Following Smith (2023), which showed that partitioning evolutionary events among genetically distinct realizations of lifecycles yields a more consistent causal analysis through the Price equation than the construction from units of selection and fitness, here we show that it likewise yields more complete evolutionary information measures.

Suggested Citation

  • Smith, Eric, 2024. "Beyond fitness: The information imparted in population states by selection throughout lifecycles," Theoretical Population Biology, Elsevier, vol. 157(C), pages 86-117.
  • Handle: RePEc:eee:thpobi:v:157:y:2024:i:c:p:86-117
    DOI: 10.1016/j.tpb.2024.04.003
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    References listed on IDEAS

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    1. Ewens, Warren J. & Lessard, Sabin, 2015. "On the interpretation and relevance of the Fundamental Theorem of Natural Selection," Theoretical Population Biology, Elsevier, vol. 104(C), pages 59-67.
    2. Robert S. Maier & Daniel L. Stein, 1996. "Oscillatory Behavior of the Rate of Escape through an Unstable Limit Cycle," Working Papers 96-09-076, Santa Fe Institute.
    3. Katarína Bod’ová & Enikő Szép & Nicholas H Barton, 2021. "Dynamic maximum entropy provides accurate approximation of structured population dynamics," PLOS Computational Biology, Public Library of Science, vol. 17(12), pages 1-22, December.
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