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. 2014 Aug 4;198(2):685–697. doi: 10.1534/genetics.114.168567

Table 2. Proportions (%) of trajectories that lead to one of the equilibria in the deterministic case.

Equilibrium Descriptiona Constant environment, weak selection Constant environment, strong selection Changing environmentb Optimum changec General fitnessd
E1 Polymorphic/symmetric 1.97 21.21 2.63 0 0
E2 + E3 Polymorphic/unsymmetric 4.6 4.46 2.73 1.91 2.19
E4 A polymorphic, loss at B 34.89 25.81 39.09 22.07 17.32
E5 A polymorphic, fixation at B 0.92 0.68 2.9 3.63 4.28
E6 Fixation at A, loss at B 31.44 31.16 41.58 7.76 14.53
E7 Loss at A, fixation at B 10.75 10.8 9.15 25.54 12.13
E8 Loss at A, loss at B 0 0 0 0 14.99
E9 Fixation at A, fixation at B 0 0 0 16.22 23.99
Sweep at A (fixation in E6)e 48.03 47.79 0.48 44.85 54.44
Sweep at B (fixation in E5)e 1.09 0 0 44.08 49.07
Sweep at B (fixation in E7)e 9.67 11.85 0.22 40.6 51.69
Sweep at A and B (fix. in E9)e 0 0 0 31.81 32.56
Transient 13.56 4.53 0 9.79 0
Unclassified 1.87 1.35 1.92 13.08 10.57
Sweeps total 16.15 16.17 0.22 20.61 24.09
a

The equilibria E1–E9 are defined following Bürger (2000, p. 205).

b

Environmental changes were defined by random change of the original effects and selection coefficient.

c

In the shifted optimum model (see Models) the phenotypic optimum takes an arbitrary position 0 < θ < 1.

d

In the general fitness model the effects have arbitrary values sampled from (0, 2) such that A is major locus.

e

Selective sweeps are defined here as trajectories that lead to fixation from very low initial frequencies (<0.01). Numbers denote the proportions of fixations with initial frequencies <0.01.