λ = 0.2, , | λ = 0.006, , | |||
---|---|---|---|---|

r(s, c) | 0.0 | 0.5 | 0.0 | 0.5 |

A. | ||||

0.51 ± 0.022 | 0.54 ± 0.024 | 0.21 ± 0.012 | 0.25 ± 0.018 | |

b_{y.x} | 0.17 ± 0.003 (0.18) | 0.19 ± 0.006 (0.19) | 0.03 ± 0.002 (0.07) | 0.03 ± 0.002 (0.07) |

0.28 ± 0.002 | 0.31 ± 0.003 | 0.08 ± 0.001 | 0.09 ± 0.002 | |

1/b_{x.y} | 0.32 ± 0.002 (0.33) | 0.34 ± 0.003 (0.34) | 0.13 ± 0.008 (0.15) | 0.12 ± 0.005 (0.16) |

B. | ||||

0.28 ± 0.031 | 0.29 ± 0.021 | 0.12 ± 0.006 | 0.16 ± 0.015 | |

b_{y.x} | 0.11 ± 0.004 (0.12) | 0.11 ± 0.003 (0.12) | 0.00 ± 0.000 (0.03) | 0.00 ± 0.000 (0.03) |

0.19 ± 0.003 | 0.19 ± 0.003 | 0.02 ± 0.001 | 0.02 ± 0.000 | |

1/b_{x.y} | 0.34 ± 0.004 (0.88) | 0.35 ± 0.002 (0.81) | 0.11 ± 0.099 (0.15) | 0.22 ± 0.174 (0.16) |

The coefficient of selection for fitness is

*cs*, where*c*is uniformly distributed between 1 and 3, and the intended correlation between*s*and*c*is*r*(*s*,*c*). Results are from diffusion approximation for a population of size*N*= 10^{5}. (A) Model where*h*follows a beta distribution (*r*≅ −0.4; and 0.02 for and 0.2, respectively). (B) Model where*h*follows a uniform distribution between 0 and exp(−*ks*) (;*r*≅ −0.32 and −0.58 for and 0.2, respectively). β = 1.01. Parameters and definitions are as in Table 2.