4.5 Article

Tonic immobility is a measure of boldness toward predators: an application of Bayesian structural equation modeling

Journal

BEHAVIORAL ECOLOGY
Volume 23, Issue 3, Pages 619-626

Publisher

OXFORD UNIV PRESS INC
DOI: 10.1093/beheco/ars006

Keywords

activity; animal personality; antipredation behavior; Bayesian structural equation modeling; boldness; fear; repeatability; tonic immobility

Funding

  1. Junta de Andalucia (Spain) [P07RNM02918, P08RNM4014]
  2. Fundacion Repsol
  3. Spanish Ministry of Science
  4. JAE-DOC from the Spanish Ministry of Science

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Animals attacked by predators often enter a state of tonic immobility (TI) in which individuals appear to simulate death. Despite the fact that TI is often used as a proxy of fear in domesticated animals, quantitative data on individual variation is very scarce for wild vertebrates. As a consequence, we lack ecological interpretations for the variability in TI that may exist in wild populations. Here, we tested whether there are consistent differences among individuals in 2 components of TI within wild populations of 2 avian species, the Yellow-crowned bishop (Euplectes afer) and the Tree sparrow (Passer montanus). We next tested whether this variation reflects variation in boldness toward predators (measured as the response to 2 predator models) or is simply related to variation in general activity/restlessness (measured as baseline activity) in the bishop. We analyzed our data by means of Bayesian structural equation modeling (SEM), which has several general advantages and, moreover, allowed us to analyze censored (truncated) data. We found good support for relatively high repeatability within individuals of both components of TI. Measures of TI appeared to be uncorrelated with baseline activity. In contrast, our results suggest that individual variation in TI in a wild vertebrate can be interpreted in a context of boldness toward predators, making TI a meaningful and practical behavioral trait for studies involving personality and antipredation behavior in wild populations. In addition, we show that the Bayesian structural equation modeling approach to analyze censored data had greater statistical power than other approaches. Hence, this rarely implemented technique deserves to be more widely used.

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