Pagès JF et al. (2021), The scent of fear makes sea urchins go ballistic.

ECB-ART-48922

Mov Ecol 2021 Oct 09;91:50. doi: 10.1186/s40462-021-00287-1.

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The scent of fear makes sea urchins go ballistic.

Pagès JF , Bartumeus F , Romero J , Alcoverro T .

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BACKGROUND: Classic ecological formulations of predator-prey interactions often assume that predators and prey interact randomly in an information-limited environment. In the field, however, most prey can accurately assess predation risk by sensing predator chemical cues, which typically trigger some form of escape response to reduce the probability of capture. Here, we explore under laboratory-controlled conditions the long-term (minutes to hours) escaping response of the sea urchin Paracentrotus lividus, a key species in Mediterranean subtidal macrophyte communities. METHODS: Behavioural experiments involved exposing a random sample of P. lividus to either one of two treatments: (i) control water (filtered seawater) or (ii) predator-conditioned water (with cues from the main P. lividus benthic predator-the gastropod Hexaplex trunculus). We analysed individual sea urchin trajectories, computed their heading angles, speed, path straightness, diffusive properties, and directional entropy (as a measure of path unpredictability). To account for the full picture of escaping strategies, we followed not only the first instants post-predator exposure, but also the entire escape trajectory. We then used linear models to compare the observed results from control and predators treatments. RESULTS: The trajectories from sea urchins subjected to predator cues were, on average, straighter and faster than those coming from controls, which translated into differences in the diffusive properties and unpredictability of their movement patterns. Sea urchins in control trials showed complex diffusive properties in an information-limited environment, with highly variable trajectories, ranging from Brownian motion to superdiffusion, and even marginal ballistic motion. In predator cue treatments, variability reduced, and trajectories became more homogeneous and predictable at the edge of ballistic motion. CONCLUSIONS: Despite their old evolutionary origin, lack of cephalization, and homogenous external appearance, the trajectories that sea urchins displayed in information-limited environments were complex and ranged widely between individuals. Such variable behavioural repertoire appeared to be intrinsic to the species and emerged when the animals were left unconstrained. Our results highlight that fear from predators can be an important driver of sea urchin movement patterns. All in all, the observation of anomalous diffusion, highly variable trajectories and the behavioural shift induced by predator cues, further highlight that the functional forms currently used in classical predator-prey models are far from realistic.

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	Fig. 1. Sea urchin final and initial distribution of heading angles in the control (n = 29) and predator (n = 21) treatments. The distribution of angles was considered uniform according to Rayleigh tests both for initial control (z = 0.16, P-value = 0.46), initial predator (z = 0.23, P-value = 0.32), final control (z = 0.21, P-value = 0.29) and final predator trials (z = 0.19, P-value = 0.48)
	Fig. 2. Violin plots of the different sea urchin movement variables analysed: a Sea urchin trajectories were on average straighter (less tortuous) and b faster (higher mean speeds) in the predator treatment (n = 21) compared to controls (n = 29). c Scaling exponents of the qth order structure functions indicated that, on average, sea urchins shifted from a wide range of spreading patterns, including Brownian motion, in control conditions to superdiffusive and marginal ballistic motion in the presence of predator chemical cues. The dashed and dotted lines in panel c represent the theoretical slope of purely Brownian and ballistic motion respectively. Different lower-case letters indicate statistically significant differences (see also Table 1). Shaded areas (‘violin-plots’) illustrate the kernel probability density of the data for each experimental treatment. Black points correspond to each individual observation (each sea urchin)
	Fig. 3. Analysis of empirical sea urchin trajectories. a, c Control (blue paths) and predator treatment (orange paths) sea urchin trajectories on an x, y coordinate system (n = 29 and n = 21, respectively). b, d Results from analysing control (blue lines) and predator treatment (orange lines) sea urchin trajectories using the qth order structure functions framework. Dotted and dashed lines in (b, d) correspond to the theoretical outputs of a ballistic (scaling exponents ζ(q) = q) and a Brownian trajectory (scaling exponents ζ(q) = q/2), respectively. Line transparency has been scaled by slope coefficient—solid colours indicate higher slope coefficients and increasing transparency indicates lower slope coefficients. The units of X and Y axes in (a) and (c) are pixels
	Fig. 4. Directional entropy of sea urchin trajectories. a The directional entropy of sea urchins in the control treatment (blue, n = 29) was higher than for sea urchins subjected to predator cues (orange, n = 21). b The directional entropy of sea urchins’ trajectories decreased with steeper slopes of the scaling exponents of the qth order moments (ζ(q)), indicating that the predictability of individual trajectories increases as we move from Brownian motion towards ballistic movements. Points correspond to each individual observation and shaded areas in (b) correspond to 95% confidence intervals

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Bartumeus, Optimizing the encounter rate in biological interactions: Lévy versus Brownian strategies. 2002, Pubmed