Predicted and observed short-term changes in strain composition
Our model finds strong variation in the fixation probability among the
20 strains, and different treatments have different most likely winners
(range: 0.7-16.8 %; SI Appendix, Fig. S7). For the range front
treatment, multiple regression analysis (Table S1) shows that both
dispersal and r0 are positively associated with strain
winning probability, and this with equal strength (standardised beta (β)
regression coefficients: +0.55 and +0.64, respectively; Fig. 3). Thus,
selection is predicted to favour strains that both disperse more and
grow faster. In contrast, in the core and control treatments, strain
winning probability is mainly associated with high growth rate (β
> +0.96), accompanied by weak selection against clones with
higher dispersal (β ≤ -0.27) or equilibrium density (β ≤ -0.33).
Molecular analysis of the 15 lines based on COI genotype indicates
complete genetic divergence between selection treatments. For all 9
range core and control lines, only the b05 COI genotype was detected.
The two strains in the founder population that carry this genotype
(Table S1) have very high growth rates and very low dispersal, the trait
combination favoured in the model. Indeed, the candidate strain
AMF_11_1A has the highest growth rate overall and is the most likely
winner in core and control treatments according to our model (Fig. 3).
In contrast, all 6 range front lines appear to be fixed for the b07 COI
genotype. This genotype is shared by 13 founder strains (Table S1),
which may thus have gone to fixation in groups or individually. Among
these candidate strains is the most likely winner (goe_14) predicted by
the model: it has the highest growth rate and the third-highest
dispersal, in line with the prediction of the two traits being under
joint positive selection in this treatment. As shown in Fig. 2, trait
values of the most likely front and core winner strains (goe_14 vs
AMF_11_1A; strain posterior distributions on the right) show a good
match with both the predicted model outcomes (left distributions; Fig.
2) and the experimental data.