The relative contributions of ancestry, chance, and past and ongoing election to variation in one adaptive (larval feeding rate) and one seemingly nonadaptive (pupation height) trait were determined in populations ofDrosophila melanogaster adapting to either low or high larval densities in the laboratory. Larval feeding rates increased rapidly in response to high density, and the effects of ancestry, past selection and chance were ameliorated by ongoing selection within 15–20 generations. Similarly, in populations previously kept at high larval density, and then switched to low larval density, the decline of larval feeding rate to ancestral levels was rapid (15-20 generations) and complete, providing support for a previously stated hypothesis regarding the costs of faster feeding inDrosophila larvae. Variation among individuals was the major contributor to variation in pupation height, a trait that would superficially appear to be nonadaptive in the environmental context of the populations used in this study because it did not diverge between sets of populations kept at low versus high larval density for many generations. However, the degree of divergence among populations (FST) for pupation height was significantly less than expected for a selectively neutral trait, and we integrate results from previous studies to suggest that the variation for pupation height among populations is constrained by stabilizing selection, with a flat, plateau-like fitness function that, consequently, allows for substantial phenotypic variation within populations. Our results support the view that the genetic imprints of history (ancestry and past selection) in outbreeding sexual populations are typically likely to be transient in the face of ongoing selection and recombination. The results also illustrate the heuristic point that different forms of selection-for example directional versus stabilizing selection—acting on a trait in different populations may often not be due to differently shaped fitness functions, but rather due to differences in how the fitness function maps onto the actual distribution of phenotypes in a given population. We discuss these results in the light of previous work on reverse evolution, and the role of ancestry, chance, and past and ongoing selection in adaptive evolution.

In the late 19th century, the evolutionary approach to the problem of ageing was initiated by August Weismann, who argued that natural selection was more important for ageing than any physiological mechanism. In the mid-twentieth century, J. B. S. Haldane, P. B. Medawar and G. C. Williams informally argued that the force of natural selection falls with adult age. In 1966, W. D. Hamilton published formal equations that showed mathematically that two ‘forces of natural selection’ do indeed decline with age, though his analysis was not genetically explicit. Brian Charlesworth then developed the required mathematical population genetics for the evolution of ageing in the 1970’s. In the 1980’s, experiments using Drosophila showed that the rate of ageing evolves as predicted by Hamilton’s ‘forces of natural selection’. The discovery of the cessation of ageing late in life in the 1990’s was followed by its explanation in terms of evolutionary theory based on Hamilton’s forces. Recently, it has been shown that the cessation of ageing can also be manipulated experimentally using Hamilton’s ‘forces of natural selection’. Despite the success of evolutionary research on ageing, mainstream gerontological research has largely ignored both this work and the opportunity that it provides for effective intervention in ageing.

Census population size, sex-ratio and female reproductive success were monitored in 10 laboratory populations of Drosophila melanogaster selected for different ages of reproduction. With this demographic information, we estimated eigenvalue, variance and probability of allele loss effective population sizes. We conclude that estimates of effective size based on genefrequency change at a few loci are biased downwards. We analysed the relative roles of selection and genetic drift in maintaining genetic variation in laboratory populations of Drosophila. We suggest that rare, favourable genetic variants in our laboratory populations have a high chance of being lost if their fitness effect is weak, e.g. 1% or less. However, if the fitness effect of this variation is 10% or greater, these rare variants are likely to increase to high frequency. The demographic information developed in this study suggests that some of our laboratory populations harbour more genetic variation than expected. One explanation for this finding is that part of the genetic variation in these outbred laboratory Drosophila populations may be maintained by some form of balancing selection. We suggest that, unlike bacteria, medium-term adaptation of laboratory populations of fruit flies is not primarily driven by new mutations, but rather by changes in the frequency of preexisting alleles.