Evolution of fixed demographic heterogeneity from a game of stable coexistence

Giaimo, Stefano; Li, Xiangyi; Traulsen, Arne; Baudisch, Annette

doi:10.4054/demres.2018.38.8

Cited by 1 publication

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References 55 publications

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“…Studies that assume equivalence between dynamic heterogeneity and individual stochasticity typically view dynamic heterogeneity as an evolutionarily neutral process (Authier et al, 2017; Steiner & Tuljapurkar, 2012). These studies assume that random differences throughout an individual's life that do not change its potential vital rates are non‐heritable (Bonnet & Postma, 2016; Giaimo et al, 2018). Hence, the variation that is generated cannot be passed on to the next generation and it is neutral with respect to evolution.…”

Section: Defining Heterogeneitymentioning

confidence: 99%

Demystifying individual heterogeneity

2021

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Among‐individual variation in vital rates, such as mortality and birth rates, exists in nearly all populations. Recent studies suggest that this individual heterogeneity produces substantial life‐history and fitness differences among individuals, which in turn scale up to influence population dynamics. However, our ability to understand the consequences of individual heterogeneity is limited by inconsistencies across conceptual frameworks in the field. Studies of individual heterogeneity remain filled with contradicting and ambiguous terminology that introduces risks of misunderstandings, conflicting models and unreliable conclusions. Here, we synthesise the existing literature into a single and comparatively straightforward framework with explicit terminology and definitions. This work introduces a distinction between potential vital rates and realised vital rates to develop a coherent framework that maps directly onto mathematical models of individual heterogeneity. We suggest the terms “fixed condition” and “dynamic condition” be used to distinguish potential vital rates that are permanent from those that can change throughout an individual's life. To illustrate, we connect the framework to quantitative genetics models and to common classes of statistical models used to infer individual heterogeneity. We also develop a population projection matrix model that provides an example of how our definitions are translated into precise quantitative terms.

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