Explaining the evolutionary dynamics of the public population, EP1. (

*A*) Adaptive surfaces and evolutionary trajectory. Data have been normalized to mean = 0 and SD = 1. The contours show fitness (probability of reproduction) and are based on cubic-spline regressions using data from all generations. The dark green lines show the progress of the bivariate means of the populations binned over 10 generation intervals for clarity, and the green and white circles are the start and end generations, respectively. This shows that the last generation and many previous generations do not approach the adaptive peak; thus, the failure of the population to progress cannot be attributable to stabilizing selection. EP1 has a single adaptive peak; a model with

interaction explains significantly more of the variation than one without (

, log-likelihood test). Similar analyses of EP2 and EP3 can be found in

*SI Appendix*, Fig. S7. (

*B* and

*C*) Frequency distributions of

and

*R* in the public population, EP1, over generations, unnormalized data. These show that at no point does the population become fixed for high

or

*R* variants; thus, the failure of the population to progress cannot be attributable to complete exhaustion of variation in these traits. Similar analyses of EP2 and EP3 can be found in

*SI Appendix*, Fig. S8. (

*D*) Change in Price parameters as a function of the current value,

, in EP1. As evolution proceeds, the change in mean from one generation to the next,

, declines. This can be attributable to a decline in the covariance term, the transmission term, or both. In the first 400 generations, for both

and

*R*, only the transmission term shows a significant decline, suggesting that the initial decline in the rate of evolution is attributable to an increased mutational or recombinational load. This is comparable to what is seen in the replicate populations, EP2 and EP3, over the same time period. Considering all 2,513 generations, however, the covariance term also declines, suggesting that either the intensity of selection or variability also contributes to population stasis in the long term. The latter proves to be the case (

*SI Appendix*, B.6). Error bars are twice the SE of the estimate.

## PubMed Commons