(Un)predictability has only recently been recognized as an important dimension of animal behavior. Currently, we neither know if (un)predictability encompasses one or multiple traits nor how (un)predictability is dependent on individual conditions. Knowledge about condition dependence, in particular, could inform us about whether predictability or unpredictability is costly in a specific context. Here, we study the condition dependence of (un)predictability in the escape behavior of the steppe grasshopper Chorthippus dorsatus. Predator–prey interactions represent a behavioral context in which we expect unpredictability to be particularly beneficial. By exposing grasshoppers to an immune challenge, we explore if individuals in poor condition become more or less predictable. We quantified three aspects of escape behavior (flight initiation distance, jump distance, and jump angle) in a standardized setup and analyzed the data using a multivariate double-hierarchical generalized linear model. The immune challenge did not affect (un)predictability in flight initiation distance and jump angle, but decreased unpredictability in jump distances, suggesting that unpredictability can be costly. Variance decomposition shows that 3–7% of the total phenotypic variance was explained by individual differences in (un)predictability. Covariation between traits was found both among averages and among unpredictabilities for one of the three trait pairs. The latter might suggest an (un)predictability syndrome, but the lack of (un)predictability correlation in the third trait suggests modularity. Our results indicated condition dependence of (un)predictability in grasshopper escape behavior in one of the traits, and illustrate the value of mean and residual variance decomposition for analyzing animal behavior.

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