How to make an inclusive-fitness model.

Thomas W Scott, Geoff Wild
Author Information
  1. Thomas W Scott: Department of Biology, University of Oxford, 11a Mansfield Road, Oxford OX1 3SZ, UK. ORCID
  2. Geoff Wild: Department of Mathematics, Western University, 1151 Richmond Street, London, Ontario, Canada N6A 5B7. ORCID

Abstract

Social behaviours are typically modelled using neighbour-modulated fitness, which focuses on individuals having their fitness altered by neighbours. However, these models are either interpreted using inclusive fitness, which focuses on individuals altering the fitness of neighbours, or not interpreted at all. This disconnect leads to interpretational mistakes and obscures the adaptive significance of behaviour. We bridge this gap by presenting a systematic methodology for constructing inclusive-fitness models. We find a behaviour's 'inclusive-fitness effect' by summing primary and secondary deviations in reproductive value. Primary deviations are the immediate result of a social interaction; for example, the cost and benefit of an altruistic act. Secondary deviations are compensatory effects that arise because the total reproductive value of the population is fixed; for example, the increased competition that follows an altruistic act. Compared to neighbour-modulated fitness methodologies, our approach is often simpler and reveals the model's inclusive-fitness narrative clearly. We implement our methodology first in a homogeneous population, with supplementary examples of help under synergy, help in a viscous population and Creel's paradox. We then implement our methodology in a class-structured population, where the advantages of our approach are most evident, with supplementary examples of altruism between age classes, and sex-ratio evolution.

Keywords

Associated Data

figshare | 10.6084/m9.figshare.c.6837186

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MeSH Term

Humans
Biological Evolution
Social Behavior
Altruism
Reproduction
Sex Ratio
Selection, Genetic
Genetic Fitness

Word Cloud

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