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Journal of Plankton Research Vol.22 no.10 pp.1871, 2000
© Oxford University Press 2000

Modelling the attack success of planktonic predators: patterns and mechanisms of prey size selectivity

Philippe Caparroy, Uffe Høgsbro Thygesen and André W. Visser1

Department of Marine Ecology and Aquaculture, Danish Institute for Fisheries Research, Kavalergaarden, 6, DK 2920 Charlottenlund, Denmark

1 To whom correspondence should be addressed

A mathematical model of the attack success of planktonic predators (fish larvae and carnivorous copepods) is proposed. Based on a geometric representation of attack events, the model considers how the escape reaction characteristics (speed and direction) of copepod prey affect their probability of being captured. By combining the attack success model with previously published hydrodynamic models of predator and prey perception, we examine how predator foraging behaviour and prey perceptive ability affect the size spectra of encountered and captured copepod prey. We examine food size spectra of (i) a rheotactic cruising predator, (ii) a suspension-feeding hovering copepod and (iii) a larval fish. For rheotactic predators such as carnivorous copepods, a central assumption of the model is that attack is triggered by prey escape reaction, which in turn depends on the deformation rate of the fluid created by the predator. The model demonstrates that within a species of copepod prey, the ability of larger stages to react at a greater distance from the predator results in increased strike distance and, hence, lower capture probability. For hovering copepods, the vorticity field associated with the feeding current also acts in modifying the prey escape direction. The model demonstrates that the reorientation of the prey escape path towards the centre of the feeding current's flow field results in increased attack success of the predator. Finally, the model examines how variability in the kinetics of approach affects the strike distance of larval fish. In cases where observational data are available, model predictions closely fit observations.


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