The estimation of reproductive values from pedigrees

Mirjam J. Borger, Jan Komdeur, David S. Richardson, Franz J. Weissing

Research output: Contribution to journalArticlepeer-review

Abstract

Quantifying fitness is important to understand adaptive evolution. Reproductive values are useful for making fitness comparisons involving different categories of individuals, like males and females. By definition, the reproductive value of a category is the expected per capita contribution of the members of that category to the gene pool of future generations. Life history theory reveals how reproductive values can be determined via the estimation of life-history parameters, but this requires an adequate life-history model and intricate algebraic calculations. Recently, an alternative pedigree-based method has become popular, which estimates the expected genetic contribution of individuals to future generations by tracking their descendants down the pedigree. This method is versatile and intuitively appealing, but it is unknown if the method produces estimates of reproductive values that are accurate and precise. To investigate this, we implement various life-history scenarios (for which the "true"reproductive values can be calculated) in individual-based simulations, use the simulation data to estimate reproductive values with the pedigree method, and compare the results with the true target values. We show that the pedigree-based estimation of reproductive values is either biased (in the short term) or imprecise (in the long term). This holds even for simple life histories and under idealized conditions. We conclude that the pedigree method is not a good substitute for the traditional method to quantify reproductive values.

Original languageEnglish
Pages (from-to)850-861
Number of pages12
JournalBehavioral Ecology
Volume34
Issue number5
Early online date23 Jun 2023
DOIs
Publication statusPublished - 1 Sep 2023

Keywords

  • fitness in a life history context
  • individual reproductive value
  • individual-based simulations
  • life-history model

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