Simulating contests to determine the relative importance of correlated traits on the winning chances

In intraspecific agonistic interactions, it is expected that traits that are more important in determining the winning chances should exhibit greater differences between winners and losers than traits that are less important. However, several of the traits used to determine the winning chances are correlated. When these traits vary in their importance to win, it becomes hard (if not impossible) to disentangle an effect due to trait correlation from the true effect of each trait on winning. To test the impact of trait correlation on the relative importance of each trait on winning chances, we developed an individual-based simulation model that investigated how different values of trait correlation and the relative importance of each trait impact the expression of trait differences between winners and losers. We hypothesized that less important traits may show smaller winner-loser differences than more important traits for small trait correlation values. Surprisingly, we found that the most important trait for winning had a detectable larger difference between winners and losers than the less important trait for strong correlations (up to 0.9). Also, for correlation values around 0.5, it was harder to detect difference between winners and losers, even for the trait that was more important in determining victory. We provide a suggested guide on how the patterns obtained in our model may be used to identify the relative importance of correlated traits on winning chances in empirical studies.