Why there are so many definitions of fitness in models

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Authors

Daniel Jefferson Smith , Guilhem Doulcier, Pierrick Bourrat, Peter Takacs, Joanna Masel

Abstract

“Fitness” quantifies the ability to survive and reproduce, but is operationalized in many different ways. Generally, short-term fitness (e.g., expected number of surviving offspring) is assigned to genotypes or phenotypes, and used to non-trivially derive longer-term operationalizations of fitness (e.g. fixation probability or sojourn time), providing insight as to which organismal strategies tend to evolve due to natural selection. Assigned fitness operationalizations vary, but all summarize currently expected organismal vital rates (i.e. births, deaths, organismal growth). Derived operationalizations also depend on assumptions regarding demographic stochasticity, environmental stochasticity, feedbacks whereby births, deaths, and organismal growth cause environmental change, and the impact of migration and niche construction on which environment is experienced. After reviewing existing derived fitness operationalizations, we propose a new one that meets the particular challenges posed by balancing selection. Population genetic models generally sidestep ultra-high-dimensional phenotype space and genotype spaces by instead deriving the long-term evolutionary fate/fitness of a lower-dimensional set of genetically encoded “strategies”. Strategies (e.g. costly developmental commitment to producing armaments) are causally upstream from realized phenotypes (e.g. armament size). While selection is best understood in terms of differences in organismal vital rates, its derived outcomes are most easily understood as properties of genetic lineages.

DOI

https://doi.org/10.32942/X2V61T

Subjects

Biology, Computational Biology, Ecology and Evolutionary Biology, Evolution, Genetics, Genetics and Genomics, Life Sciences, Population Biology

Keywords

Invasion fitness, Malthusian parameter, individuality, theoretical population genetics, bet-hedging, life history strategy, density-dependent selection, Malthusian parameter, individuality, theoretical population genetics, Bet-hedging, life history strategy, density-dependent selection

Dates

Published: 2024-04-11 14:10

Last Updated: 2024-10-16 22:07

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License

CC-BY Attribution-NonCommercial-ShareAlike 4.0 International

Additional Metadata

Language:
English

Conflict of interest statement:
None

Data and Code Availability Statement:
Code is publically available at: https://github.com/DanielSmithEcology/Fitness_Definitions_Code