Common environment variances were consistently overestimated and residual variances underestimated, whereas genetic variances were biased in both directions depending on the trait and pre-selection intensity.
One consequence of this is that, since there will nearly always be some variation in immigration rates, classical models that treat migration as a single parameter (with zero variance) will consistently overestimate the influence of immigration relative to local selection, and thus underestimate the potential for local adaptation and speciation.
Yet, between-lake genetic variance was consistently higher than subdrainage variance, even when Lake Clark was excluded (additional file 2).
Clearly, at higher abundances (approximately 6 pMol or higher), variance is consistently low and replicates have almost equal variance indicated by overlapping data points.
Factor solutions collectively explaining 79% of the variance, with consistently strong factor loadings >0.5, were used to classify the 17 face shape variables into five dimensions (D1 to D5; table 4).
Table 5 shows that, between traits, direct heritabilities and phenotypic variances when estimated by A1 and S-MGS models were very similar but the residual variances were consistently larger for S-MGS models compared to both A1 and A2 models.
Alternative models gave broadly similar results, although constant-variance models consistently found no evidence that influenza B made any contribution to mortality (Web Tables 3 9).
When the target phenotype was changed periodically, we observed that the increase and decrease of the variances were consistently repeated, when the noise level was near the transition value (σ c), where rapid adaptation to new environment and robustness in phenotype were compatible.
Indeed, one should not do so, because d′ is confounded with response bias whenever the underlying evidence distributions have unequal variance, as is consistently observed in recognition memory judgments (e.g., Ratcliff, Gronlund, & Sheu, 1992).
