Table 2.

AIC analysis of the results of the field transmission experiment

Model	AICc	ΔAICc	AICc WT
No treatment effect, linear model	183.9	13.10	0.001
No treatment effect, nonlinear model	177.9	7.17	0.026
JA linear, control linear	186.0	15.22	0.001
JA linear, control nonlinear	170.8	0.00	0.940
JA nonlinear, control nonlinear—( same, C different)	178.8	7.51	0.022
JA nonlinear, control nonlinear—( different, C same)	179.9	9.13	0.001

The best model is in boldface. The model for which transmission was linear on induced branches and nonlinear on control branches provided an overwhelmingly stronger explanation for the data, such that the AIC difference for the next-best model was more than 7 (some more complex models are not included because they converged on the best model; SI Appendix). Moreover, the second-best model that allowed for a treatment effect assumed that the infection rate function was nonlinear on both induced and noninduced branches, again with lower infection risk on JA-treated branches. The probability that induction lowered variability in infection risk was thus greater than 0.96 .