Putting life history theory to the test - the estimation of reproductive values from field data

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 intricate algebraic calculations. Recently, a more intuitive, pedigree-based method has become popular, which estimates the genetic contributions of individuals to future generations by tracking their descendants down the pedigree. Here we compare both methods. 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 both methods, and compare the results with the true target values. We show that the pedigree-based estimation of reproductive values is either systematically biased (and hence inaccurate), or very imprecise. This holds even for simple life histories and under idealized conditions. In contrast, the traditional algebraic method estimates reproductive values with high accuracy and precision. Lay SummaryTo study evolution in empirical systems it is important to accurately and precisely measure fitness. Here, using simulations, we compare two methods for estimating fitness and test their accuracy and precision. One estimates life-history parameters and calculates a fitness proxy using complex algebra. The other method estimates genetic contribution to future generations by tracking descendants down the pedigree. We conclude that the pedigree method is unreliable, while the algebraic method is accurate and precise.