Condition dependence of (un)predictability in escape behavior of a grasshopper species

Abstract

(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.

Keywords: Orthoptera; condition dependence of animal behavior; double-hierarchical generalized linear model; escape behavior; residual intra-individual variance; unpredictability.

Figure 1.

Observed measurements of escape behavior traits for immune-challenged and untreated steppe grasshopper Chorthippus dorsatus. Plots represent average (on the left plots), standard deviation (on the center plots), and coefficient of variation (on the right plots) values per individual, based on up to 10 observations per individual.

Figure 2.

Posterior distributions of fixed effect slopes for escape behavior traits of the steppe grasshopper C. dorsatus. Slopes were standardized for the standard deviation of each covariate. Points show the median and thick and thin bars represent 50% and 95% HPD intervals, respectively. The darker shade of gray highlights cases in which 95% HPD intervals do not include zero.

Figure 3.

Variance decomposition of escape behavior in the steppe grasshopper C. dorsatus. The residual variance of average behavior (gray slice on the left pies) is further decomposed into the amount of variance explained by phenotyping date, individual identity, and residual variance in unpredictability (right pies). Variance components were estimated while accounting for fixed effects.

Figure 4.

Correlations among traits in the steppe grasshopper C. dorsatus. Plots show the posterior distributions of correlations among traits in the mean and dispersion parts of a multivariate DHGLM at the level of individuals (lower triangle) and phenotyping dates (upper triangle). The darker shades highlight cases in which 95% HPD intervals do not include zero.