MEPS 373:37-52 (2008)  -  DOI: https://doi.org/10.3354/meps07749

ABSTRACT: Spatio-temporal hydrodynamic signal fields were quantified for ambush-feeding Oithona plumifera females sensing motile Strobilidium ciliates. First, videotaped Oithona–ciliate encounters were image-analyzed to retrieve ciliate trajectories, O. plumifera attack kinematics and reaction distances to the ciliates. Second, using computational fluid dynamics (CFD), flow disturbances created by swimming ciliates were examined for 5 common ciliary forcing schemes. Third, using the CFD results and measured ciliate trajectories as inputs, a hydrodynamic model was developed to calculate ciliate-generated hydrodynamic signal patterns for observed encounters. Wide variance was found in measured reaction distances. Good correlations existed between measured predator attack kinematics and measured pre-attack prey locations. Moreover, data analysis showed that O. plumifera preferred small attack angles, presumably to enhance capture success. From hydrodynamic modeling, several distinct spatio-temporal hydrodynamic signal patterns were identified, and estimated hydrodynamic signal strengths immediately prior to attack were all above a minimum required signal level but differed substantially in magnitude. These results support the notion that by monitoring and recognizing the spatio-temporal pattern of ciliate-created flow disturbances, O. plumifera can perceive and project the ciliate’s instantaneous location and velocity, and hence precisely time its attack when the ciliate reaches a location where it can most easily be captured. Instead of reacting to a constant signal strength, O. plumifera females adapt their capture behaviors to perceived signal patterns. CFD simulations also revealed species-specific flow patterns and spatial decays in hydrodynamic disturbances created by swimming protists. The predator may use this species-specific information to distinguish among prey species.

KEY WORDS: Oithona plumifera · Ciliate · Predator–prey interaction · Hydrodynamic signal perception · Spatio-temporal pattern · Hydrodynamic modeling · Capture difficulty